0:00:05 The content here is for informational purposes only, should not be taken as legal business
0:00:10 tax or investment advice or be used to evaluate any investment or security and is not directed
0:00:15 at any investors or potential investors in any A16Z fund. For more details, please see
0:00:21 a16z.com/disclosures. Hi everyone, welcome to the A6Z podcast. I’m
0:00:26 Sonal. Today we have another one of our podcast on the road episodes with guests from New
0:00:33 York City on the topic of crypto, but more broadly on crypto networks as emerging economies.
0:00:38 This conversation goes into the super interesting nuances of structuring these networks to avoid
0:00:43 some of the failings we’ve seen in the monetary and fiscal policies of traditional economies,
0:00:49 including debating how to empower users when it comes to risk, but also how to better distribute
0:00:54 access in terms of who captures value from networks. We then also discovered different
0:00:59 mindsets for the governance of these networks, which are really crypto economic systems,
0:01:04 especially as they evolve and grow more mainstream over time. Joining us to have this conversation,
0:01:09 we have two guests, our friends at Placeholder VC. Chris Berniske, who formerly led ARC Invest
0:01:13 Crypto Efforts, has written a lot about financial modeling influence frameworks for analyzing
0:01:18 crypto and co-wrote a book on crypto assets, and Joel Monegro, who before starting Placeholder
0:01:23 with Chris was an analyst at USV, where he helped develop their early blockchain theses
0:01:28 prior to that, he managed the Dominican Republic’s government office in charge of developing
0:01:32 the country’s national and digital economy technology agenda. I share all that as key
0:01:36 context for the conversation that follows. And last but not least, we have two of our
0:01:41 partners from A6 and Z Crypto, Jesse Walden and Dennis Nazarov, formerly co-founders
0:01:45 of MediaChain, which was acquired by Spotify, Jesse and Dennis interview our guests and
0:01:50 also add their perspectives in the discussion and debate. On that note, the content here
0:01:57 is for informational purposes only and should not be taken as legal business tax or investment
0:02:03 advice or be used to evaluate any investment or security. It is not directed at any investors
0:02:10 or potential investors in any fund. For more details, please also see a6nzcrypto.com/disclosures.
0:02:15 Before the discussion goes into what it takes to design such crypto economic systems at
0:02:20 scale from value capture to risk to governance, they first quickly begin with the fundamental
0:02:26 concept of layers in a stack of protocols and decentralized applications. The first
0:02:31 voice you’ll hear is Joel followed by Chris’s and then Jesse and Dennis joins in later.
0:02:35 You can think about it from an engineering point of view and how different kinds of
0:02:40 software are layered on top of each other. You can think about it also from a more social
0:02:46 point of view. Layer one is more machine work and layer two is more human work. And as you
0:02:51 transition from layer one to layer two, then you end up with lighter weight models because
0:02:55 you don’t have the capital cost of the machines to actually do the work, to store the files,
0:03:00 to mine the transactions. What we see at layer two are more abstract units of work that require
0:03:06 human judgment. And there the cost is harder to model because it’s harder to quantify what
0:03:10 is the value that goes into performing some unit of work. And that unit of work can be
0:03:16 anything from curating content to making a governance decision. All of those things are
0:03:21 very difficult to put in a spreadsheet model, but we have the aid of the invisible hand
0:03:26 in a way and that’s helping us figure out what human work is worth. I think the infatuation
0:03:31 with layer one comes from it being much easier to understand the cost and value relationship
0:03:35 between providing a service and consuming a service. It gets harder as you move up the
0:03:40 layers. Once you get into the realm of human work is when you start to really imagine that
0:03:44 there are different ways in which crypto can really change the way we do things.
0:03:48 I think as we go up higher in these layers we’re going to see different incentivization
0:03:54 and therefore value capture mechanisms. Layer one, the priority is security because that’s
0:03:59 basically our clearing and settlement layer. And so we’ve really seen Bitcoin prioritize
0:04:05 security or Ethereum. And because if we build all these layers on top of an insecure layer
0:04:11 one then we’re screwed, right? And then as we move up the stack it’s less about that
0:04:18 machine security say and more about how do you incentivize the economic actors to perform
0:04:23 the service that you’ve promised to provide. And the only way that that ends up being a
0:04:28 service that the end user uses is either if it’s cheaper than existing services that
0:04:32 you can get from the centralized model but on par in terms of user experience or it’s
0:04:38 a fundamentally new experience or service and this is the only place I can get it there’s
0:04:43 the access tokens where basically there’s demand of what I find interesting about an
0:04:47 access token is historically we’ve thought of tokens as needing to connect the supply
0:04:52 side and demand side. An access token really just focuses on the supply side and it can
0:04:56 have a fixed supply and there can be scarcity because basically if the supply side needs
0:05:01 that token to perform the service and performing the service is a profitable activity for them
0:05:06 then there will be a clamoring to get a hold of that token and that drives its own scarcity
0:05:11 and that’s slightly easier to model you can actually use discounted cash flow model to
0:05:17 approximate the value of that token and the demand side can pay in fiat if they want and
0:05:21 I think we’ll increasingly see this where the demand side is going to just pay in whatever
0:05:26 asset they want they don’t need to interface with crypto assets from a day to day perspective
0:05:31 but you can still have value in a work token that organizes the supply side and induces
0:05:34 a competition around being able to provide that service.
0:05:39 So in the model you described Chris we call it the taxi medallion model what’s interesting
0:05:44 about it is there’s one token that is the right to do the work and the other token which
0:05:49 is the payment token and so as you said it’s you can do sort of a cash flow analysis on
0:05:54 what the work token is going to earn and this differs from the base layer where you know
0:06:00 today most of the layer one blockchains use one token for both rewarding the supply side
0:06:05 and for the demand side to consume the service and I’m curious what do you guys think the
0:06:13 implications of moving to work token model are is there any sort of implications for
0:06:17 users and suppliers not being aligned around the same token.
0:06:23 Well the thing that’s really scary about this trend to create dual token systems where one
0:06:27 token gives you access to the supply side or a right to participate in the supply side
0:06:31 and another one into being the payment token whether it’s another token that it’s created
0:06:36 by the crypto network or something like ETH or any other one is that you were doing the
0:06:42 same thing that we did with the world economy which is that we separated currency and capital
0:06:47 the moment that we moved into a fiat currency model in modern capitalism.
0:06:53 We have two major kind of asset types we have capital and we have that and currencies are
0:06:57 really a form of debt at the end of the day and backtracking a little bit the reason we
0:07:01 separated currency from capital is because the transaction velocity of capital is very
0:07:08 low the transaction velocity of a dollar is very high and so as the economy grows exchanging
0:07:12 gold or land or just a barter system is not going to work and so we needed currencies
0:07:19 to accelerate economic growth so far so good the problem is that capital and currencies
0:07:24 respond very differently to economic growth capital appreciates together with economic
0:07:28 growth and currencies actually depreciate as an economy grows.
0:07:34 Inflation is commonly thought of as the printing of new money but really a more traditional
0:07:40 definition of inflation is increases in prices over time as a result of economic growth and
0:07:45 capital as an asset type appreciates as the economy grows because it is more scarce than
0:07:50 currency currency we print more of it to keep up with inflation to keep prices stable and
0:07:53 that’s how they end up devaluing over time because we’re creating more and more and more
0:07:58 what happens over time then is that actually capital becomes more and more concentrated
0:08:02 because its transaction velocity is so low and the problem with that is that we end up
0:08:07 with a lot of people living their lives in in currency and very few people living their
0:08:08 lives in capital.
0:08:13 What part of the promise of crypto networks at least to me is that we are able to combine
0:08:18 currency and capital into a single asset so that then we don’t get the same kind of income
0:08:24 inequality or wealth inequality being created as any individual crypto network grows and
0:08:29 the risk of separating the access token or the work token from the currency token is
0:08:34 that the people who accumulated the access tokens early on that group becomes increasingly
0:08:39 concentrated over time as the economy grows or as the crypto network grows the value of
0:08:44 combining the two. If you have a single token that is both a supply site token and a payment
0:08:50 token in order for the supply site to provide its service it has to take payment in that
0:08:53 token so the token has to be in the user’s hands in order for them to actually consume
0:08:58 the service and so that creates a pressure to sell the work token or sell the capital
0:09:02 token as the network grows because otherwise you’re not going to get any customers. Everyone
0:09:06 in a crypto network can participate from the value created as opposed to just one segment.
0:09:12 I definitely agree there’s a risk to backtracking a little bit with the ethos of crypto separating
0:09:17 the work or the capital and currency. I think one thing even if we end up in a work token
0:09:23 world or taxi medallion world where we’ve separated capital and currency again at least
0:09:29 within those networks the one reassuring thing is that you can’t be a passive accumulator
0:09:35 of capital. You have to be more active like you stake the work token and then you have
0:09:40 to continue to provide work for the network to continue to collect cash flows.
0:09:43 So I would argue that that’s not entirely true and that’s because in these proof of
0:09:49 stake systems you often have the ability to delegate stake and so what happens there is
0:09:53 a marketplace emerges where there are people sitting on capital and they just point that
0:09:58 capital at a worker so it’s very much like taxi medallions work in New York City. They’re
0:10:02 mostly bought up by hedge funds and the like and then they hire drivers to go and drive
0:10:06 the cars and earn passive income on those medallions. And so I think that does speak
0:10:11 to Jule’s point that the separation of these two things does result in a concentration
0:10:17 of capital but I would argue that the flip side is that the users of the service don’t
0:10:22 have to take any risk. So when I get into a taxicab I don’t have to think about whether
0:10:28 Uber or Lyft are going to have a real big impact on the value of my medallion and the
0:10:33 future utility I’ll get out of it. So humans tend to think in one unit of account because
0:10:37 it’s just easier to reason about and you don’t want to be taking risk necessarily when you’re
0:10:42 buying a coffee or a pizza and that ends up going on to be worth millions of dollars.
0:10:49 And so there is this sort of simplicity in the tax now in versus currency model that
0:10:54 I think it’s hard to get away from just because of human nature.
0:10:59 I argue that risk is good because you can’t create value without creating risk. And again
0:11:04 it’s that same kind of thinking that led to the world where we are today. It’s much simpler
0:11:09 to have everyone use dollars because no one has to think about how the markets are moving
0:11:12 and how your value is changing over time. Rather you trust the government. You trust
0:11:18 that they’re going to maintain a certain monetary policy such that you hope that your
0:11:22 hundred thousand dollars today is going to maintain a certain degree of purchasing power.
0:11:28 The problem with that is that by not allowing people to take risks in a way then we’ve cheated
0:11:33 them away from capturing some of the upside of the value. And I think it’s time to rethink
0:11:39 how we think about risk for people more broadly. If we prevent people or the science systems
0:11:44 that make it harder for people to take those risks and participate in the value then we’re
0:11:48 going to end up in the same world where we are today where the values concentrated amongst
0:11:52 those who took the greatest risks. Now obviously it can go really badly if you have a whole
0:11:55 bunch of risk spread a whole whole bunch of people and then everything comes crashing
0:12:00 down then you have a real problem. So it’s not that there isn’t value instability and
0:12:05 value in currencies that make it easier for consumers to go about their daily lives. But
0:12:09 I also don’t think we’re heading to a world where you buy your coffee with Bitcoin. I
0:12:14 also think that the overall argument of well we need to create these systems because otherwise
0:12:18 it’s too risky and then people are not going to use it. I think it’s a little not patronizing
0:12:23 but it underestimates people’s ability to make those decisions for themselves.
0:12:29 I remember asking you about three four years ago whether it’s actually a good idea to make
0:12:35 your users investors because there’s a cognitive overhead that is associated with that. You’re
0:12:42 asking your users to be sophisticated about the underlying infrastructure powering their
0:12:48 daily experience and I think increasingly in in crypto we’re seeing that at least when
0:12:53 you have some skin in the game participants in these networks are willing to go in a little
0:12:58 bit deeper and the types of communities that emerge are on these projects are just fundamentally
0:13:02 different like people have a different relationship with the network. Ethereum participants own
0:13:08 the token and therefore have an emotional connection to the values of the infrastructure
0:13:13 and its goals and what it achieves. Sometimes. Yeah, to a fault sometimes and I think the
0:13:20 question is how scalable is this? Can we scale this model to the entire world or is it limited
0:13:26 to a subset of users who are sophisticated enough and want to take on that risk and so
0:13:31 just to push back a little bit on the idea that we will be able to scale this model sort
0:13:35 of all the way up. I think the idea of having this work token currency model it doesn’t
0:13:41 preclude power users from participating in the network and then through delegation the
0:13:45 owner of that token does not need to necessarily provide the work. So a power user can invest
0:13:51 in the success of the network that they’re using but it’s a choice and so I think there’s
0:13:56 flexibility both ways. On one side the assumption is that we should give risk to everyone and
0:14:00 that’s that optimal in the other side is we should let people choose. You can argue both
0:14:05 sides of the table and so what that tells me is let the people make the choice but then
0:14:09 that becomes a question of what’s the default. So you know we’ve all gone through a sign-up
0:14:14 form where the checkboxes are checked by default or not that opt you into certain things and
0:14:19 we’ve learned that people tend to stick with the default and so I would rather see a world
0:14:23 where the default is we’re all participating in the value. Yeah, any citizen can go and
0:14:27 open a brokerage account and buy stocks and participate in the market but most people
0:14:32 don’t because that’s not the default. So I think one thing that we can do here is actually
0:14:37 create a model and train another generation of users to think as users who are staked
0:14:41 in the network in a way that we really couldn’t before and the generational aspect I think
0:14:46 is very important because the other thing that’s going on here is that the way these
0:14:51 assets accrue value is very different to the way that other previous kinds of assets accrue
0:14:57 value. Previously in a more traditional world when we had companies go public it was a lot
0:15:02 of the same philosophy of you, you’re a customer of Walmart, Walmart goes public, you can buy
0:15:06 stock in Walmart and then every time that you go to Walmart and you’re paying with your
0:15:12 dollars you know there is some value accruing back to you as a shareholder of the company.
0:15:15 But in order to properly analyze an equity you have to go to business school and learn
0:15:19 how to do this kind of cash flows and how to figure out you know how to analyze whether
0:15:23 management is doing things correctly and so on. What’s different here is that we’re dealing
0:15:28 with these decentralized networks where if they’re properly constructed the value doesn’t
0:15:32 really necessarily depend on the actions of a management team but rather on the overall
0:15:33 network.
0:15:39 Yes, we were talking about the consumer perspective and them being a shareholder and that’s one
0:15:43 side of the argument, the other is from the developer and people who are actually building
0:15:44 these protocols.
0:15:49 So I want to take a step back because we’ve been saying user network participant those
0:15:57 kinds of things and I think that it really depends on which network participant we’re
0:15:58 referring to.
0:16:03 So early on in a network where it’s mostly the supply side right because the supply side
0:16:08 has to come on board to actually provision the asset and presumably the supply side is
0:16:15 going to be a much more sophisticated person at least in their understanding of the network
0:16:16 than the demand side.
0:16:20 At least as we scale out over the long term I think that’s an assumption we can make.
0:16:24 And so that supply side can tolerate that earlier risk because presumably they’re more
0:16:27 sophisticated and so that all makes sense.
0:16:32 Where I think we start to encounter more problems especially if crypto goes mainstream we will
0:16:38 have you know hundreds of millions billions of end users on the demand side and I think
0:16:43 it’s a stretch to ask the demand side to be an expert in the network.
0:16:46 The supply side this is different from our current equity environment.
0:16:52 If you set aside stock based comp traditionally an employee at a company doesn’t necessarily
0:16:54 have exposure to the upside of that company.
0:16:59 Stock based comp has changed that a lot but that employee mostly gets paid in fiat currency
0:17:03 which goes back to Joel’s point of you know they don’t get to participate in the capital
0:17:08 appreciation as much as the management and the concentrated owners of capital.
0:17:11 So for me that’s a big improvement.
0:17:18 Early on demand-siders they’ll be early adopters but I think as this space grows we will abstract
0:17:22 a lot of that complexity away from them and the demand side will just pay in whatever
0:17:27 they want to pay it be they in Kenya be they in the US be they in Korea you pay for the
0:17:32 service with whatever currency you want that ends up getting converted and the supply side
0:17:37 will get paid in the native asset of the network through whatever it may be.
0:17:41 But the key is that the supply side gets access to that risk and that capital appreciation
0:17:42 for me for me.
0:17:47 So I think an interesting sort of avenue to go down here is to again come back to this
0:17:51 idea of the different layers in the stack and how it may be different at each of them.
0:17:56 So at the base layer it makes a lot of sense for there to be sort of one currency or you
0:18:01 know because because you do really want to align the incentives of the supply side and
0:18:07 the users because it’s this very general substrate upon which you know like all all kinds of
0:18:11 more complex applications can be built but this because it’s very general you want there
0:18:17 to be this sort of network effect that everyone is everyone converges on the values and the
0:18:22 goal of this general substrate as you get further up the stack and you build more complex
0:18:28 applications something like a stable coin for example requires sort of more specialization
0:18:32 in terms of the type of work that’s being done and this is to Joel’s point earlier that
0:18:39 it’s it’s more human work and more specialization generally means more expertise.
0:18:45 And so once you get into those types of applications I think it becomes a little bit harder for everyday
0:18:49 users to be sophisticated about the work that’s going on behind the scenes.
0:18:54 People probably don’t need to understand how Ethereum computers you know determine consensus
0:18:59 but I think the difference is that in order for a stable coin to work it’s a much more
0:19:03 you know complicated system and it has parameters that need to be tuned and they probably need
0:19:08 to be tuned by experts whereas computation is deterministic it’s sort of a binary outcome
0:19:11 right or wrong and it can be verified by computers.
0:19:16 And so I would argue that the base layer of the system being more general lends itself
0:19:20 to this sort of single token model a little bit better but as you move further up the
0:19:24 stack I think you do want this separation between sort of the management and the users
0:19:27 because it requires expertise.
0:19:29 And that brings us to governance.
0:19:30 Right.
0:19:34 And maybe an analogy is the base layer sort of like a country it’s like you’re a citizen
0:19:40 of America you get to vote and participate in you know elections and to decide kind of
0:19:41 policy.
0:19:46 Taxation policy is the substrate for all economic activity built on top of America and then
0:19:51 there’s more specific corporations inside of America and they have their own governance
0:19:56 practices they have their own equity and then participating in them is much more specialized
0:20:01 but you have this broad substrate that everyone else builds on top of with different governance
0:20:02 parameters.
0:20:07 So I like to think of or we like to think of crypto networks as emerging economies and
0:20:13 what’s interesting about that is that if you compare crypto network to a country you start
0:20:18 to see a number of similarities there’s a currency that’s exchanged between buyers and
0:20:23 sellers there’s if you think of the executive team or the executive branch is the core development
0:20:28 team and you think of the blockchain as the court or the legislative system where you
0:20:32 know all the rules go there and then you have the supply side which are the miners or the
0:20:36 producers and you have the demand side which are the users who are consuming the service
0:20:39 that starts to look a lot like a small economy.
0:20:44 And then what’s cool about that is that you can use this model to think through whether
0:20:47 a crypto network is properly constructed or not.
0:20:52 So for example things that we’ve learned over time that we like to see in physical economies
0:20:58 like low degrees of corruption and sound monetary policies and fiscal policies and a rich supply
0:21:03 side and an active demand side it ends up getting us into the topic of governance because
0:21:08 one of the things that can determine the success of a national economy or not is how that economy
0:21:09 is governed.
0:21:14 There’s a broader conversation about where is the value of governance in crypto networks
0:21:18 and governance is a difficult topic because it is so broad but I’ll bring it even further
0:21:24 back to the history of information technology in the 50s and 60s.
0:21:27 That era was based around the hardware how quickly you could iterate on hardware and
0:21:31 how quickly could you get computers in the market and IBM won that war because they were
0:21:36 able to design custom computers for custom use cases faster than than anybody else.
0:21:40 That business started breaking down in the 70s and 80s following the introduction of
0:21:45 the microprocessor which consolidated a whole bunch of those circuits into a single part
0:21:49 that was widely available and that created two things.
0:21:53 It first it unbundled the hardware industry and we went from effectively one computer
0:21:58 manufacturer to dozens of PC manufacturers and so on.
0:22:01 But then what happened is that value moved one layer up to the software layer and so
0:22:05 we have Microsoft and the PC software boom of the 70s and 80s.
0:22:09 We saw that get built on top of the microprocessor standard or platform.
0:22:15 Fast forward to the end of the 80s and into the 90s and we went from having dozens of
0:22:22 independent software ventures to having Microsoft consolidating that entire ecosystem and building
0:22:27 its business on the basis of proprietary software and proprietary distribution of that software.
0:22:30 What happened in the 90s is we got two things.
0:22:35 We got the internet and we got Linux which was free software and free distribution and
0:22:38 so that directly challenged Microsoft.
0:22:43 And so we got into the web era where the value moved again one layer up to data which is
0:22:44 where we live today.
0:22:50 We have the big tech companies of today Google, Apple, Facebook, Amazon and so on.
0:22:54 Their main asset their main capital asset is all the data that they’ve been able to
0:22:56 accrue over time as people have used their service.
0:23:01 So we’ve been in this stage for about 20 years now and right on schedule we get the
0:23:07 arrival of a new open technology which are blockchains that directly challenge the proprietary
0:23:11 data business model just as the internet and Linux challenged the proprietary software
0:23:12 and distribution business model.
0:23:16 It gets into a question of okay if we see this pattern of value moving one layer up,
0:23:20 one layer up, one layer up and we’ve gone from hardware to software and from software
0:23:22 to data and now data is free.
0:23:23 What’s above data?
0:23:29 The layer that exists at a higher level and to us that’s governance because it becomes
0:23:33 a question of how do we manage, how do we control, how do we manipulate the data and
0:23:38 how do we agree on a single source of truth which is the whole thinking behind designing
0:23:40 these consensus systems.
0:23:44 The crypto networks at the end of the day are systems that we designed to arrive at a shared
0:23:49 understanding of what is the right data to observe in a world where all the data is open.
0:23:51 And ultimately that is a governance system.
0:23:57 With that model do you think the base layer, the computational substrate, does that become
0:23:58 a commodity?
0:24:02 How do you think about the value of the base layer and how governance of the base layer
0:24:05 relates to the governance of the applications on top of it?
0:24:11 I think we need to be careful of thinking of it statically because just as Joel just
0:24:15 went through there’s this evolution of value capture that we saw with information technology
0:24:22 and I think we will see an evolution of value capture within crypto where value will start
0:24:24 to move up the protocol stack.
0:24:29 Right now we’re focused a lot on developer protocols because we believe it’s the developer
0:24:35 era of crypto and those are the most valuable people and developer attention is the most
0:24:38 valuable resource I would argue within crypto right now.
0:24:44 And we may have this period of value accrual and developer facing networks which then may
0:24:48 become commoditized and shift up to more consumer facing protocols.
0:24:50 But it’s more that there’s this evolution.
0:24:53 So how do you justify that more concretely?
0:24:58 For example, two transactions can use the same amount of gas, they could use the same
0:25:04 amount of the computational resource of Ethereum, but their economic value can be drastically
0:25:05 different.
0:25:09 I mean that brings a question of there’s sort of this tragedy of the commons problem that
0:25:14 one user of the protocol derives way more value from this underlying substrate than
0:25:15 another.
0:25:19 We can compare the foundational layer of a blockchain smart contract platform and decentralized
0:25:23 applications being built on top of it to general cloud computing infrastructure such
0:25:30 as Azure or Google Cloud or Amazon AWS and all the super valuable kind of union or applications
0:25:31 built on top of it.
0:25:37 They all utilize this commodity layer and kind of pay for computation at the level of
0:25:42 the resource, but the value they derive from the cloud platform is immensely higher, hence
0:25:46 their market caps combined are much higher than the cloud platforms underneath them.
0:25:50 So I don’t think every layer one protocol will capture a ton of value.
0:25:53 I think most of them will get commoditized and the ones that don’t will be the ones that
0:25:59 become these stores of value for these really important settlement protocols within the
0:26:00 space.
0:26:05 But I think that as we move up past that, we could see these middleware protocols actually
0:26:09 have more scale than the underlying smart contract protocols.
0:26:13 Start now with the developer in the future with the consumer, but still largely in the
0:26:14 protocol layer.
0:26:18 And I mean, we’re talking about a multi-decadal evolution here, but an evolution nonetheless.
0:26:23 I have a different way of thinking about value, which is through the lens of cost.
0:26:27 And this goes back to Econ 101, one of the first things they teach you is marginal benefit
0:26:30 equals marginal cost at equilibrium.
0:26:36 And bringing that into the discussion of where does value accrue, then you can then extend
0:26:40 that and okay, value will accrue to where there is the highest cost.
0:26:42 And it doesn’t really matter where in the layer that is.
0:26:46 It matters more what is the kind of service that’s being provided and what is the cost
0:26:47 of that service.
0:26:49 And then the other dimension is scale.
0:26:54 I think people sometimes confuse commodity with value less.
0:26:58 You can have something that is a complete commodity like milk and still get enormous amounts of
0:27:03 scale that permit value to accrue at that layer regardless.
0:27:08 As you move up the different layers or you start thinking about where does value accrue
0:27:14 in different places, just bringing back the whole governance umbrella, making a decision.
0:27:15 What’s the value of a decision?
0:27:19 Well, it might be in precisely where they’re implementing it in the governance over the
0:27:24 standard and over the protocol over time, where perhaps over time as the protocol becomes
0:27:30 more important and the standard becomes more widespread, then the value or the cost of
0:27:33 making a protocol decision increases over time because it affects a greater number of
0:27:35 people.
0:27:39 And so that’s one way in which you can kind of use the lens of cost to kind of chase down
0:27:44 where value might accrue in different services or across an ecosystem.
0:27:51 I think one helpful analogy with the governance space and value accrue from the perspective
0:27:57 of cost, if you look at, for example, United States, the United States has a fixed supply
0:28:05 of one president, but the cost of being that president has grown over time as the network
0:28:08 of the United States has also grown over time.
0:28:12 And this is actually where I think fixed supply works in a governance token setting.
0:28:16 If you have a fixed supply of that asset, but the cost and value of governing that network
0:28:21 is going up, then so too should the cost per token of that asset.
0:28:23 And so that’s a useful analogy for thinking through it.
0:28:28 And just thinking about America being a substrate for businesses built on top of it, the incentives
0:28:35 there is that corporations that exist within America are taxed to fund that substrate.
0:28:38 Better infrastructure, all kinds of services.
0:28:42 And to my earlier point, that there is no kind of economic relationship in the same
0:28:46 way that there is in America between Ethereum, for example, and the applications built on
0:28:52 top of it, you could imagine that there is some way in protocol to say it’s an upgrade
0:29:00 to ERC 20 standard, that 10% of the tokens every quarter, it’s a tax that goes to fund
0:29:01 the base chain.
0:29:08 And maybe this is a way to solve the problem of how do we fund innovation of the base chain.
0:29:09 I’m curious what you think of that.
0:29:16 I think traditionally taxation is one of the mechanisms through which a currency can boot
0:29:17 strap value.
0:29:22 And this goes back to, for example, the shardless theory that the government has to spend the
0:29:25 currency first and get it into circulation and then collect taxation.
0:29:28 And so that kick starts the economic flywheel.
0:29:32 People are experimenting with different forms of taxation in the space.
0:29:35 And really a transaction fee is a form of tax.
0:29:43 But we haven’t seen direct taxation to fund core developers beyond the inflationary model.
0:29:47 And that’s really kind of taxation through senior age or dilution.
0:29:52 For example, there’s Zcash or Decred or some of these networks that are working with this
0:29:57 idea of, okay, part of the monetary policy, we’re going to mint out over time and Decred
0:30:03 allocates 10% of each Coinbase reward to the developer pool, which will be allocated through
0:30:05 governance and the community’s decision to write it.
0:30:07 That’s effectively a 10% tax.
0:30:10 And same with Zcash, it’s a 20, 30% tax.
0:30:14 And because it’s of the income, right, if you think of every time a new block is produced,
0:30:15 that’s income that’s going to the miners.
0:30:18 But 10% of that is coming back to development.
0:30:22 It’s an implicit as opposed to an explicit tax that then funds the network.
0:30:27 You know, if you start thinking about governance first through the lens of this idea of taxation,
0:30:31 you can think of your kind of analogy of we have a fixed supply of one precedent and then
0:30:35 we can figure out how much it’s cost to run for precedent over time and figure out, you
0:30:38 know, what’s the cost of that governance model.
0:30:41 But there’s something that we can observe more concretely, which is just a tax rate
0:30:43 over time in world economies.
0:30:49 And we have seen tax rates as a proportion of GDP increase over time, as GDP increases
0:30:54 because the cost of governing the economy grows together with the growth of the economy.
0:30:59 And so how we can translate that into crypto networks is thinking through what is the cost
0:31:04 of governing a crypto network and the cost of maintaining an economic system over time.
0:31:08 And how does that change as that network grows or contracts over time?
0:31:13 So again, we keep coming back to this conversation around different layers in the stack and we
0:31:17 did a whole podcast on this about how the emergence of base layer crypto networks are
0:31:24 like cities in that there’s a bunch of people that have a vested interest in the infrastructure
0:31:27 upon which they’re building and they’re pulling it in different directions.
0:31:30 But there’s actually at the birth of a lot of cities, there’s not this like formal process
0:31:35 for coordinating that it just consensus emerges to this very rough process.
0:31:39 A lot of these ideas around rough consensus and running code are from Venkatesh Rao’s
0:31:43 post on Breaking Smart, which we’ve referenced a number of times on the podcast and we keep
0:31:44 coming back to.
0:31:50 We also talked about the emergence of internet standards and specifically the internet engineering
0:31:55 task force was this loose group of academics and engineers that were working on base layer
0:32:00 internet protocols and they had this very formal policy to not have voting, but instead
0:32:05 sort of weekly coordinated consensus mechanism whereby people argued their points with strong
0:32:06 opinions.
0:32:10 It was sort of a robust and sort of scientific approach and the best ideas were converged
0:32:11 upon.
0:32:17 So it’s this idea that a rough consensus emerges from one strong opinions weekly held to running
0:32:20 code in order to form those opinions.
0:32:24 And that’s very much the governance model of Bitcoin and Ethereum today.
0:32:27 Other projects are taking a different approach with formal on chain governance.
0:32:32 I think our view is that the more general the network, in terms of the service that it’s
0:32:37 providing, the more it lends itself to this process of rough consensus.
0:32:43 If you go all the way down the stack down to IP protocol, it’s this very general protocol.
0:32:48 It’s completely un-opinionated about the packets that it’s moving from A to B and the rough
0:32:53 consensus process or work there, it’s very lightweight and easy to integrate.
0:32:59 I would make the argument that general computation platform would lend itself to that same process
0:33:04 because you want it to do this very general thing and a thing that is very deterministic.
0:33:07 It doesn’t require human subjectivity to validate.
0:33:11 Then as you go further up the stack, there are applications built on top of the substrate
0:33:17 and as Dennis made earlier, it’s like the businesses built on top of America.
0:33:19 Each of them are providing different services.
0:33:23 They require different expertise in order to provide those services.
0:33:27 I would make the argument that at that layer in the stack, governance does become important.
0:33:32 The expertise requires specialization and these applications need to be more dynamic and responsive
0:33:38 to their users versus general computation, which over time should hopefully remain fairly
0:33:43 consistent such that these applications can build on top without the rules changing on
0:33:44 them.
0:33:51 There are many factors that go into governance decision processes that are informal.
0:33:55 One factor is the original roadmap of the project.
0:34:01 Does this change fit within the original vision outlined by both the founders and the community?
0:34:04 In Bitcoin, there is a promise of 21 million Bitcoins.
0:34:05 That is very important to it.
0:34:09 Also, there’s figureheads, Vitalik, for example, has very strong opinions.
0:34:13 While people trust him, he is one of many voices in the community.
0:34:15 I think it’s not dictatorial.
0:34:19 He proposes changes and there’s a debate and a conversation.
0:34:25 The base layer today in a platform like Ethereum is both the medium of exchange and the reward
0:34:28 for the supply side of the network.
0:34:31 Importantly, the governance process is this process of rough consensus where there is
0:34:35 no default setting for upgrading the network.
0:34:41 This is an important connection to draw because the users of the network have an active interest
0:34:44 in how the network evolves.
0:34:47 They are incentivized to participate in this process of rough consensus.
0:34:52 Whereas an application built on top of Ethereum, that layer in the stack, the expertise required
0:34:57 may necessitate that the management of this organization, whether it’s a central company
0:35:02 or a loosely affiliated group of people all over the world, that those stakeholders have
0:35:04 that expertise in order to make those decisions.
0:35:06 I think this is a really critical difference.
0:35:08 The base layer is very general.
0:35:13 Users wanted to do this one thing and do it well, compute things in a deterministic way,
0:35:17 but as you get further up the stack, it becomes a lot harder to reason about those mechanics.
0:35:22 I’ve started to use the term power tokens instead of governance tokens to refer to tokens
0:35:28 that represent the power to change the rules or change the makeup of a crypto network or
0:35:32 at least one vote to change the rules of the crypto network.
0:35:36 One way that I like to describe it is that crypt economics are the rules of the game
0:35:41 and governance is the power to change the rules of the game.
0:35:46 My belief is that as the game becomes more valuable, then the power to change the rules
0:35:48 becomes more valuable as well.
0:35:52 That’s the umbrella that I like to use to think through what’s the value of power, what’s
0:35:54 the value of changing the rules of the game.
0:36:00 If power tokens were the only means of making decisions, it’s sort of a very heavy-handed
0:36:06 specific tool that if manipulated incorrectly, it will lead to negative outcomes.
0:36:13 This more informal process through hard forks, you also, in addition, have checks and balances
0:36:17 where, as you mentioned earlier, there are different classes of participants, the miners,
0:36:22 the developers, the users, different bodies of the government that developers proposed
0:36:23 the code.
0:36:28 It has to be agreed upon by the miners to implement it, so it’s a more multifaceted multi-stakeholder
0:36:33 operation as opposed to who owns the tokens gets to, and the other problem is it creates
0:36:34 a default.
0:36:41 If the network automatically upgrades into some specific version of the code, the catastrophic
0:36:45 scenarios are much worse because everyone opts into a default, whereas in this more
0:36:49 weak consensus model, everyone has to agree in a broader way.
0:36:53 I have a twist on rough consensus and running code, which is crypt economic consensus and
0:36:59 running code, and my take on it is rough consensus works well when you’re small, and when the
0:37:03 number of stakeholders is fairly small, when the IETF was working through these protocol
0:37:09 iterations, you didn’t have to find consensus amongst a very large group of people in terms
0:37:11 of who is really affected by these decisions.
0:37:15 Today, it’s a completely different kind of dynamic where the underlying protocols have
0:37:20 remained fairly stagnant, and all of the innovation in terms of use cases has happened above,
0:37:24 where governance is a lot more fluid in the sense that each individual application can
0:37:28 construct its environment or its system in the way they prefer.
0:37:34 But bringing these ideas back to crypto, there’s another model that I like to think about which
0:37:37 is on-chain governance, off-chain diplomacy.
0:37:42 So by off-chain diplomacy, I mean every time that a core developer team meets with each
0:37:47 other to make a decision, or a user or an application of that protocol wants to lobby
0:37:48 for a change.
0:37:54 The human process by which we arrive at proposals and ultimately decisions, you still have meetings
0:38:00 between people debating and arriving at decisions and proposing different ideas.
0:38:01 All sorts of issues can emerge, right?
0:38:06 You can have concentration in the power token that enables a small group of people to really
0:38:10 control the network, but you can have the same kind of dynamic today with rough consensus.
0:38:14 If you don’t have a formal process that allows everyone that they can participate in that
0:38:18 process, you can end up with a clique that effectively governs the network through their
0:38:21 own rough consensus and cuts out everyone else.
0:38:26 Let’s make sure everyone in the network has a fundamental right to participate in that
0:38:27 governance process.
0:38:32 And let’s have mechanisms for people to get together and have sophisticated discussions
0:38:33 about how decisions were made.
0:38:37 But let’s make them convince the community and convince the network that that is the
0:38:38 right thing to do.
0:38:44 I think also, if you don’t have formal governance mechanisms and clarity around it, you devolve
0:38:47 into governance by defection.
0:38:48 And we saw that with Bitcoin.
0:38:51 We’re not necessarily arguing for complicated governance.
0:38:59 We’re arguing for rules and transparency such that the network participants all understand
0:39:02 not only what the rules are, but how the rules are changed.
0:39:07 Yeah, I guess where we might diverge a bit is that we are arguing that the more general
0:39:11 the service of a crypto network, the more it should be ossified.
0:39:17 So again, coming back to this IP is ossified, Bitcoin has ossified, maybe a general computation
0:39:23 substrate is better ossified because it lends itself to the trust that the developers building
0:39:27 on top need in order to feel comfortable building there.
0:39:31 However, those applications that developers build because they’re complex and dynamic
0:39:35 and interfacing with end users need to be able to change.
0:39:41 And in order for them to do so, a formal governance process is probably necessary.
0:39:45 The default is to take whatever the coin holders vote upon and upgrade the system.
0:39:50 And so I think one of the assumptions is that the token holders participating in the vote
0:39:56 and prior to that participating in the diplomacy are experts and have the best interests of
0:39:58 their users in mind.
0:40:01 Their interests are hopefully aligned with their end users.
0:40:03 And they pay for it if they mess up through dilution.
0:40:04 Right.
0:40:05 That’s right.
0:40:09 And so the incentives are tightly coupled so that the experts make decisions for the
0:40:12 benefit of their users and for the benefit of themselves.
0:40:15 And you end up with this very dynamic system where the end users don’t necessarily need
0:40:19 to think about the complexity of the underlying mechanic of the thing.
0:40:24 And importantly, there’s explicit enforceability over one canonical group of contracts that
0:40:26 control the system.
0:40:32 And so the output of the governance process doesn’t require, for example, end users or
0:40:36 other participants in the network to download new software and run it.
0:40:41 The analogy of a blockchain is we’re traveling down a highway.
0:40:47 And then we decide that we want to take a turn, one of two turns into two different futures.
0:40:52 And that will be upgrading– miners upgrade their software to a new fork version.
0:40:57 What forks are in protocols is different than forks are on base layers.
0:41:02 You can’t fork in the case of a stable coin because it has all this collateral.
0:41:06 You can’t fork the collateral because your DAP doesn’t control that.
0:41:09 You are using the existing platforms collateral.
0:41:10 So the upgrade process has to be different.
0:41:14 In the governance debate, there’s nuance in what it means to upgrade a DAP that’s running
0:41:16 on top of ProCo and the protocol itself.
0:41:19 You brought up the example of a computation network.
0:41:22 It’s a very well-defined kind of service.
0:41:24 A computer runs the code, and the code has an output.
0:41:28 If you focus on something more controversial, like how value is distributed, then all of
0:41:30 a sudden you find that the governance is really important.
0:41:37 And I’d also argue that power token voting excludes the needs of miners and the needs
0:41:38 of users.
0:41:39 That depends on how you design it.
0:41:43 If you think of power as a source of value, then you want to make sure that that power
0:41:46 is evenly distributed amongst the participants of the network.
0:41:49 Otherwise, you end up, again, where we are in the modern economy today with very few
0:41:53 people with a lot of power, and most people with not that much power.
0:41:58 So just one thing I wanted to add is that one of the problems with thinking about on-chain
0:42:03 governance as a way for users to actively participate in the evolution of a network
0:42:07 is that in practice, if we look at the real world and how governance systems work, there’s
0:42:09 actually very low participation.
0:42:16 This is because as an individual user, an individual voter, my one vote, my little say doesn’t
0:42:19 have all that much influence on its own.
0:42:22 And so there’s this apathy about participation.
0:42:28 And so a assumption is that when we talk about users affecting or risking together and participating
0:42:33 in governance, is that they have some sort of emotional stake in the outcome of governance
0:42:34 processes.
0:42:41 And that may be the case in very niche applications where users feel a strong affinity to the application
0:42:42 they’re using.
0:42:46 If I don’t have a strong connection to participating in voting, maybe I’d be more likely to sell
0:42:48 my vote to someone who does.
0:42:53 And the result of that is the same risk that Joel described earlier, where the capital
0:42:57 and the currency become disaggregated.
0:42:59 And this could undermine on-chain governance processes.
0:43:03 It’s important to note that on-chain governance is really hard for a number of reasons.
0:43:07 In the context of blockchains, it’s very difficult to know who the participants are.
0:43:12 You can be hundreds of people just by generating multiple keys.
0:43:17 And so when you have this system that is synonymous, it’s difficult to enforce behavior patterns
0:43:22 that lead to good governance, say, in shareholder governance where shareholders are bound by
0:43:23 fiduciary law.
0:43:28 There’s a great post by a researcher at Cornell who we recently had on the podcast named
0:43:32 Phil Diane, and he went deep down the rabbit hole into different attacks that you could
0:43:33 launch.
0:43:34 The rise of dark doubts?
0:43:39 Yeah, the post dives in deep and our podcast does as well on different sort of attacks
0:43:43 that you can launch to bride participants in on-chain governance schemes.
0:43:49 I think a lot of arguments against on-chain governance are kind of primitive in their
0:43:52 thinking around how is that governance applied.
0:43:57 One common element of a lot of the counterarguments is the assumption that governance power is
0:44:02 linear and one token equals one vote, whereas in crypto networks, we have the opportunity
0:44:05 to design much more intricate systems with much more intricate rules.
0:44:09 And so, yes, you can replicate yourself across a thousand different addresses, while you
0:44:15 can make it such that your governance power is amplified if you have all your tokens
0:44:20 in one wallet and so you can make it actually more powerful to basically voluntarily disclose
0:44:24 still within the pseudonymous system how much of the token you have because you get more
0:44:30 power by aggregating your assets together and you can kind of change how the shape of
0:44:35 that curve, depending on the context, you can also do things like look at the age of
0:44:36 an address.
0:44:40 One thing that we learned actually from a non-crypto company that was in the online
0:44:44 community abuse space is that the length an account has been open is the greatest determinant
0:44:45 of whether it’s a troll or not.
0:44:50 And so you can use things like the life span of an account or of a wallet or the tokens
0:44:51 that it received.
0:44:55 And you can even make distinctions around whether the tokens in that wallet were purchased
0:44:58 from an exchange or were received directly through mining.
0:45:02 And you can factor all of those things into how you design, let’s call it your governance
0:45:03 curve.
0:45:07 Maybe those are all examples of on-chain reputation that’s sort of native to the system.
0:45:08 Exactly.
0:45:10 So yeah, thank you guys very much for coming on.
0:45:14 It’s been awesome sort of recapping the space and how it’s evolved over the last few years
0:45:20 and super excited to see how our theses play out over the years going forward.
0:45:21 Well thanks for having us.

0:00:03 – The content here is for informational purposes only,
0:00:05 should not be taken as legal business tax
0:00:07 or investment advice or be used to evaluate
0:00:10 any investment or security and is not directed
0:00:14 at any investors or potential investors in any A16Z fund.
0:00:18 For more details, please see a16z.com/disclosures.
0:00:22 – Hi everyone, welcome to the A16Z podcast, I’m Sonal.
0:00:25 Today’s episode is all about blockchain-based voting systems
0:00:29 which has implications for crypto economic security
0:00:32 and for governance, especially when you think
0:00:34 about the differences, both good and bad,
0:00:36 between real world and online systems
0:00:38 for coordinating groups of people to vote on something,
0:00:40 whether it’s a decision in a boardroom
0:00:42 or an election or anything else.
0:00:44 This episode was recorded as part
0:00:46 of our New York City podcast road show
0:00:49 and so it features Phil Dayan, a PhD at Cornell Tech,
0:00:51 working with Ari Jules there.
0:00:53 His research focuses on broad questions
0:00:55 of security of distributed systems,
0:00:56 specifically blockchains.
0:00:58 He also wrote a post last year
0:01:00 with Tyler Kell, Ian Mears and Ari Jules
0:01:05 on quote, “On-chain vote buying and the rise of dark DAOs.”
0:01:06 Joining Phil in this hallway style jam
0:01:09 to discuss these topics is Ali Yaya,
0:01:10 who was previously a software engineer
0:01:13 and machine learning researcher at Google X and Google Brain.
0:01:16 He also gave a talk at A16Z Summit on crypto
0:01:18 and the evolution of trust, which you can find
0:01:22 on our website, and he’s a partner on A16Z Crypto.
0:01:24 Speaking of, please note that the content here
0:01:26 is for informational purposes only,
0:01:29 should not be taken as legal business tax
0:01:32 or investment advice, or be used to evaluate
0:01:34 any investment or security and is not directed
0:01:38 at any investors or potential investors in any fund.
0:01:39 For more details, please also see
0:01:42 A16ZCrypto.com/disclosures.
0:01:44 The conversation that follows covers ways
0:01:46 in which blockchain systems are different
0:01:48 from real-world voting systems,
0:01:50 ways the system can be gamed
0:01:52 and what that means for security,
0:01:54 as well as possible solutions
0:01:56 and more importantly, questions
0:01:58 all blockchain system designers should think about
0:02:01 instead of making naive assumptions.
0:02:04 But first, Phil and Ali began by very briefly summing up
0:02:06 the issues in real-world elections
0:02:08 and electronic voting systems.
0:02:11 The first voice you’ll hear is Phil’s, followed by Ali’s.
0:02:14 – So one challenge people have seen is straight up hacking.
0:02:17 Of course, if there is electronic voting in use,
0:02:19 just tampering with the integrity of the election itself
0:02:21 or the integrity of the registration.
0:02:23 Another challenge that people have been worried about
0:02:26 in the past is vote buying and selling.
0:02:27 So if I want you to vote a certain way,
0:02:30 maybe I directly bribe you to do so
0:02:32 or maybe even in the current system,
0:02:34 I can indirectly do it.
0:02:37 But it’s very difficult to bribe someone in person
0:02:39 and sort of understand how they’re going
0:02:40 to act in an election.
0:02:42 – Yeah, you have this great example of how
0:02:44 if the price of a vote is a beer
0:02:45 and you take me out for a beer and say,
0:02:48 “Ali, I want you to vote for ex-candidate.”
0:02:50 I could drink your beer and then go to the poll
0:02:53 and submit whichever ballot I want.
0:02:56 And you have no real mechanism to enforce my vote
0:02:58 in one way or another.
0:03:01 And you then point out how this is not so much the case
0:03:03 when you go to the world of electronic voting.
0:03:04 – Yes, the price of the vote as a beer
0:03:06 is actually kind of realistic.
0:03:09 Like vote buying in general is empirically pretty cheap
0:03:10 for two reasons.
0:03:11 Number one, it’s actually the poorest
0:03:13 and least advantaged people that are the most inclined
0:03:15 to sell their votes.
0:03:17 And number two is most people are disinterested
0:03:18 in most elections.
0:03:20 So this actually makes vote buying pretty cheap.
0:03:22 And in electronic voting, this is a big problem
0:03:25 because with many electronic voting protocols,
0:03:26 you can actually tell at the end of the protocol
0:03:27 how someone voted.
0:03:30 So it becomes much easier for me to bribe you
0:03:31 because I can just say essentially I’ll give you a beer
0:03:34 if I check afterwards and you voted with my candidate
0:03:36 rather than sort of trusting you to go in the polling booth
0:03:38 and make the right decision where socially
0:03:40 I can’t follow you into that booth
0:03:41 and look over your shoulder.
0:03:42 – Exactly.
0:03:44 You point out how in the world of human voting,
0:03:47 there are three things that tend to make vote buying
0:03:48 a little bit more difficult.
0:03:49 And it’s the inefficiencies of the human world
0:03:51 that actually work to your advantage here.
0:03:53 So the first is that in the human world,
0:03:55 it’s a crime to buy votes and that itself
0:03:57 kind of can serve as a deterrent,
0:03:59 which doesn’t really exist so much
0:04:01 in the jurisdiction-less crypto world.
0:04:03 The second one was that ballots
0:04:04 tend to be casted in secrecy.
0:04:06 So there’s no way of me to produce a proof
0:04:08 that I voted in one way or another,
0:04:11 which makes the buying of the vote difficult to enforce.
0:04:13 And the third one you mentioned is that if you tell me
0:04:15 that you’re going to pay me in the future
0:04:16 for voting one direction or another,
0:04:18 I have a hard time trusting you
0:04:20 that you will actually in the end pay me.
0:04:22 And so there’s sort of counterparty risk.
0:04:25 And so in the same way that sort of blockchains
0:04:30 mitigate trust and improve coordination for good purposes,
0:04:34 they can also be used to improve coordination
0:04:36 for sort of malicious purposes.
0:04:38 In this case, vote buying is like a double-edged sword.
0:04:41 Blockchains can be used to increase the efficiency
0:04:44 and effectiveness of bribery and vote buying.
0:04:45 Yes.
0:04:46 In the traditional world,
0:04:48 there’s been a long line of academic research.
0:04:51 So very early on people said we want to vote electronically.
0:04:52 It’ll make tallying cheaper.
0:04:54 It can maybe use cryptography
0:04:55 to increase the integrity of our elections.
0:04:57 So we don’t rely on these pieces of paper
0:05:00 sort of with this weird chain of human custody
0:05:01 and things like that.
0:05:03 But early schemes sort of suffered from this receipt property
0:05:06 where I could produce a proof that like here is the outcome
0:05:09 and here is what I actually voted to lead to this outcome.
0:05:11 So there was a wide range of work early on
0:05:12 on how to sort of solve this issue
0:05:15 and create voting schemes that are receipt free,
0:05:17 which means that after the fact,
0:05:19 I cannot produce a receipt or a proof
0:05:20 to tell you which way I voted.
0:05:22 And it’s sort of equally likely from your perspective
0:05:24 that I voted in any direction.
0:05:27 Later work sort of said that this is not strong enough.
0:05:29 Essentially the high level is
0:05:31 if you’re looking over my shoulder electronically,
0:05:33 like you have a virus on my computer
0:05:35 or you’re just physically looking over my shoulder,
0:05:36 at the time that I’m voting,
0:05:38 even receipt freedom is not enough
0:05:40 because you might be able to see in real time
0:05:42 the direction in which I’m voting
0:05:43 and enforce my vote that way.
0:05:45 So that led to an even stronger property
0:05:46 called coercion resistance,
0:05:48 which is that even if you compromise me
0:05:49 for some period of time,
0:05:52 you still are not able to get me to vote a certain way
0:05:54 in a way that you can trust.
0:05:55 – Yeah, that’s very interesting.
0:05:59 And so let’s connect this to sort of the blockchain world.
0:06:01 These questions of electronic voting have existed
0:06:03 for decades and predate the world
0:06:05 of blockchains and crypto networks.
0:06:07 But now there’s like a resurgence of research
0:06:10 in this direction because so many blockchain
0:06:11 and crypto network projects
0:06:14 want to use on-chain voting for all sorts of purposes.
0:06:16 – So I mean, in blockchain networks in general,
0:06:17 you often need to make decisions.
0:06:20 That’s like part of the attractive point of blockchains
0:06:22 that it makes coordinating group decisions
0:06:24 among actors who don’t trust each other
0:06:26 a little bit easier.
0:06:29 And to make these decisions sort of a natural response
0:06:30 is just vote, right?
0:06:31 That’s something you see in the real world.
0:06:34 It’s something you see in corporations with stockholders.
0:06:35 It’s something you see in boardrooms.
0:06:37 It’s something you see in political elections
0:06:39 and all sorts of other social systems.
0:06:41 So it’s just, I think, a natural human tendency
0:06:43 when asking sort of how to organize these things
0:06:47 that voting is the only real clear shelling point answer
0:06:48 that we can come up with.
0:06:49 So I think an important distinction
0:06:52 on why this stuff really matters in the blockchain world
0:06:54 is that the blockchain world and the real world
0:06:56 don’t operate in the same models.
0:06:57 If you’re going to a boardroom with someone,
0:06:59 you’re sitting next to the person, right?
0:07:02 We’re sort of operating in this model of social honesty
0:07:04 where people can see each other face to face.
0:07:05 You have shared interests in the company.
0:07:08 You sort of know their history at least somewhat.
0:07:10 Whereas in blockchains, you’re operating in an economic,
0:07:13 sort of an economically rational game theoretic model.
0:07:15 So you need much stronger guarantees from your systems.
0:07:17 Your systems need to be strong
0:07:20 even in the presence of economically motivated adversaries.
0:07:21 And they need to be secure,
0:07:24 assuming people are rational rather than honest.
0:07:25 So we don’t get to lean on this sort of honesty
0:07:28 that we have in the real world in blockchains.
0:07:29 And I think that’s where a lot of the mechanisms
0:07:32 that people try to sort of port over naively break down.
0:07:34 – Right, and this is especially important
0:07:36 because in most of the crypto networks
0:07:38 that are actually interesting,
0:07:42 the model is one where anyone can participate.
0:07:44 And people refer to this as the permissionless setting
0:07:46 and that anyone can connect to the network.
0:07:49 Anyone can sort of participate in the decisions
0:07:51 that are made through the governance processes
0:07:53 of the crypto network,
0:07:55 which makes the environment the very hostile one
0:07:57 because anyone anywhere can opt to participate
0:07:59 and they have an economic incentive to do so
0:08:01 because if they can game the system
0:08:03 or if they can sort of subvert it in some way,
0:08:05 then they could potentially profit.
0:08:06 – Exactly.
0:08:08 Satoshi released his white paper in ’09
0:08:10 and academics first started looking at Bitcoin
0:08:12 and its success and its rise
0:08:14 and asking like what is actually the interesting lesson
0:08:16 to be learned here from what we’ve been doing
0:08:17 for the last 20 years.
0:08:19 There was a whole space of consensus protocols
0:08:21 and Byzantine fault-tolerant protocols
0:08:22 that came to consensus on something
0:08:25 even in the presence of malicious users.
0:08:27 But what was really new about Bitcoin
0:08:30 is that it let anyone join and leave the network at any time.
0:08:32 And these people didn’t need to ask the people
0:08:35 who are already participating in the network
0:08:36 whether they can join or not.
0:08:38 So in most consensus protocols,
0:08:40 you have a sort of quorum that’s coming to decisions
0:08:41 and if you want to join,
0:08:43 you need to ask the quorum to join
0:08:45 because the quorum needs to agree on who’s in the quorum.
0:08:46 So they need to sort of come to consensus
0:08:48 on the fact that you’re allowed to join.
0:08:50 Whereas in something like Bitcoin,
0:08:51 if you want to start mining Bitcoin,
0:08:53 you just turn on your rig and as soon as you succeed,
0:08:55 people will accept that mathematically.
0:08:57 They don’t need any sort of membership proof
0:08:58 or anything like that.
0:08:59 What I think is relevant to voting
0:09:01 is that fundamental to the permissionless model
0:09:03 if you’re gonna use cryptography,
0:09:04 which all blockchains do,
0:09:06 is that if I can join and leave at any time,
0:09:08 I need to be able to like generate my own key
0:09:09 and join at any time.
0:09:10 – Right.
0:09:13 I mean, the uses of on-chain voting,
0:09:16 we’re voting within blockchain projects,
0:09:19 range all the way from setting the parameters,
0:09:21 like some parameter in the protocol
0:09:22 that may be something minor,
0:09:25 kind of like the price of gas, for example,
0:09:28 all the way over to sort of some intermediate level
0:09:30 where people use governance
0:09:32 and voting to decide how to allocate funds.
0:09:34 And then this goes all of the way over
0:09:37 to actually deciding how to change the protocol itself.
0:09:40 And so there are projects that are sort of self-amending
0:09:45 and that they use governance as a way of proposing updates
0:09:47 to the protocol and then deciding on which updates
0:09:50 should go through and which updates should not.
0:09:51 And so the stakes are high
0:09:55 and that if you have a governance system that can be gamed,
0:09:59 then all of these use cases may end up being vulnerable
0:10:00 to that kind of attack.
0:10:02 One way of thinking of governance that I quite like
0:10:04 that I think was proposed by Vitalik
0:10:07 is the coordination model of governance
0:10:10 and that really all governance decisions are in essence
0:10:13 a way of coordinating collective action.
0:10:16 He talks about how there are multiple layers
0:10:17 to governance, right?
0:10:19 The bottom layer is like what’s closest
0:10:20 to the real and physical world.
0:10:22 – Yeah, so maybe let’s go bottom up
0:10:24 on everywhere you have voting in blockchains.
0:10:25 At the very base level,
0:10:27 all consensus mechanisms are a vote,
0:10:29 so proof of work itself is a form of voting
0:10:30 on which block is valid
0:10:32 and which history is accepted by the network.
0:10:34 So you have voting at that layer.
0:10:35 Then that half layer up, like you said,
0:10:38 is this governance layer of how do blockchains
0:10:39 actually change their underlying code
0:10:42 and respond to attacks or new situations
0:10:45 or new technology or whatever it may be.
0:10:48 Traditionally, this has sort of gone with the fork model
0:10:50 where you just sort of spin up new code
0:10:52 and try to lobby everyone to just run this new system
0:10:53 instead of the old one.
0:10:55 This model has seen a lot of political strife,
0:10:59 a lot of inefficiency, a lot of sort of lobbying
0:11:01 and traditional politics like nastiness
0:11:03 in the blockchain space.
0:11:06 You can look at the Bitcoin block size debate,
0:11:07 whether to change the one to a two,
0:11:11 which spawned like a year long rift between the communities
0:11:13 that ended up in like several summits and agreements
0:11:16 and eventually a permanent split.
0:11:17 So some people look at that and say,
0:11:18 maybe we can make this more efficient
0:11:20 by just using voting and allowing the coin holders
0:11:22 to express their preference
0:11:23 and sort of just going with that.
0:11:25 And then another layer up from that,
0:11:27 you have the application layers like you were saying.
0:11:30 So these are your DAOs, these are your smart contracts
0:11:32 that wanna use voting to make decisions.
0:11:35 They could be, for example, on how to allocate funds.
0:11:37 They could be on how to change parameters
0:11:38 within their own smart contract.
0:11:41 So you really have voting throughout the blockchain stack.
0:11:42 A lot of projects are using it
0:11:46 and it has a very sort of wide impact as a general problem.
0:11:49 – So one observation that comes out of all of this
0:11:52 is that today’s governance systems
0:11:54 and sort of blockchains and crypto networks,
0:11:56 the way that they exist today will likely devolve
0:11:59 into plutocracy simply because the mechanisms
0:12:02 for vote buying are so effective as you described.
0:12:05 And some proponents of on-chain governance
0:12:07 will argue that plutocracy may not actually
0:12:08 be that bad of a thing.
0:12:10 They may be a bad thing for democracies,
0:12:12 but not so much for blockchains.
0:12:15 In the blockchain world for a crypto network,
0:12:17 it’s not so much a bad thing
0:12:20 because it’s in a sense incentive compatible,
0:12:21 at least at a surface level.
0:12:24 If they are voting using their coins
0:12:26 for any one upgrade to the protocol,
0:12:29 they will want to vote in the interest of other people
0:12:31 who also hold the coins in the interest of the network
0:12:34 because they own it and they have a stake in it.
0:12:37 And also their incentive to protect the network
0:12:38 is proportional to how many coins they own.
0:12:41 So like larger voters or stakeholders
0:12:43 who have more coins in the network
0:12:46 have an even greater incentive to protect the network.
0:12:48 What are your thoughts there?
0:12:49 – So I think every blockchain project
0:12:51 should take a step back and ask,
0:12:52 do we want plutocracy?
0:12:53 Do we want vote buying in our system?
0:12:55 And what are the consequences of that?
0:12:56 For many of them,
0:12:58 maybe it’s more acceptable than for others.
0:13:02 For example, if you have like a small closed sort of contract
0:13:03 that has a few shareholders,
0:13:05 something like an investment firm
0:13:06 and you have like one guy
0:13:08 who decides whether people get in or not,
0:13:10 maybe you’re not so concerned about vote buying
0:13:11 in that kind of a scheme.
0:13:15 Or if you have even like some sort of closed setting
0:13:17 where you can say things about the participants,
0:13:19 maybe you’re not so concerned about vote buying.
0:13:21 In a wider system where let’s say
0:13:23 the whole world is participating in it eventually,
0:13:25 I think the fundamental point is that
0:13:27 most people are disinterested in most votes
0:13:29 and the utility they get from the system
0:13:31 is not directly sort of correlated
0:13:34 with whether they vote A or B on this given issue.
0:13:36 Nonetheless, there are certain groups of people
0:13:37 who are extremely interested
0:13:39 in whether people vote A or B on a certain issue
0:13:41 and these are often pretty moneyed groups.
0:13:42 So in this way,
0:13:44 that kind of governance does sort of degenerate
0:13:45 into plutocracy.
0:13:48 And if that’s acceptable for your system, that’s fine.
0:13:49 I think for many systems, it’s not.
0:13:51 You need to care about these attacks
0:13:52 and you need to reason about
0:13:54 why your system is secure against this
0:13:56 and why your system actually doesn’t degenerate
0:13:57 to plutocracy.
0:13:58 People have tried to get around this
0:14:00 in two ways in blockchains.
0:14:02 The first one is they add some sort of identity.
0:14:03 So they have a third party service
0:14:05 that like you send your cell phone number
0:14:07 or something like that and it sends you a text
0:14:09 and sort of anti-sibles you that way
0:14:11 and then you’re able to participate in a vote.
0:14:15 So at least you can sort of attach some entity
0:14:17 to the person and then count votes per entity
0:14:18 rather than per coin.
0:14:21 This actually still degenerates into plutocracy
0:14:22 because of the way the Dark Dow works
0:14:25 because as long as these identities are keys
0:14:27 that people can sort of generate at any time,
0:14:30 they can be bought and sold and using the Dark Dow model
0:14:31 and you can essentially sell people
0:14:33 like the right to your identity
0:14:35 or you can sell people the right to a certain vote
0:14:38 using your identity or even more specific things than that.
0:14:40 So that kind of doesn’t work
0:14:42 unless you have a strong social protection
0:14:44 where like the person has to come in very often
0:14:46 and the network sort of authenticates
0:14:49 that they’re human or something like that.
0:14:50 That becomes very complicated
0:14:52 and steps much more into the messy world
0:14:53 of real world elections
0:14:56 and maybe doesn’t work for a global blockchain community.
0:14:58 Another way people have tried to get around it
0:15:00 which also kind of requires identity
0:15:03 is this new line of work by Vitalik Glenn Whale
0:15:05 and a few other people which is quadratic voting
0:15:07 where you actually allow vote buying.
0:15:09 So you allow people to buy votes
0:15:11 but only at an exponentially increasing price.
0:15:13 And this may kind of look like plutocracy
0:15:15 because you’re allowing people to buy votes
0:15:17 but if you actually do the math on the incentives,
0:15:20 it turns out that through this increasing function,
0:15:21 essentially people will express
0:15:22 their true preferences in the end.
0:15:26 And one rich person who really cares about A versus B
0:15:29 won’t be able to sort of overwhelm a disinterested majority
0:15:30 that weakly prefers A
0:15:32 and maybe each don’t have as many funds
0:15:33 as that one individual.
0:15:35 So this fixes some known pathologies
0:15:37 in real world voting systems
0:15:39 and also blockchain voting systems.
0:15:41 But it does require identity
0:15:43 and it’s extremely vulnerable to manipulation.
0:15:45 If this one rich person can pretend
0:15:47 that they’re two rich people or something like that,
0:15:48 the gig is sort of up.
0:15:51 And that’s what these new coordination mechanisms allow.
0:15:53 – Yes, I think this dependence on identity
0:15:55 that you are pointing out is very important
0:15:57 because as you pointed out,
0:15:59 anyone can pretend to be more than one person.
0:16:02 They can generate 10 different sets of key pairs
0:16:03 or hundreds of sets of key pairs
0:16:05 and pretend to be hundreds of people.
0:16:06 – Yeah, and the only thing you can do
0:16:07 is wait by coins basically.
0:16:08 – Exactly.
0:16:10 In that world, you end up with unfair representation
0:16:13 of you’re trying to assign a single vote to a key pair.
0:16:17 So proponents of on-chain coin holder governance
0:16:21 which means that one coin gives you one vote will argue.
0:16:23 It’s at the very least, civil resistant,
0:16:26 which means that if you have like 10 million coins
0:16:28 staked on one particular vote,
0:16:31 they’re basically used to vote for one particular outcome.
0:16:34 It’s very hard to argue that those 10 million coins
0:16:37 come from trolls that are trying to sway the election
0:16:39 because there’s real weight and real capital
0:16:41 that’s staked in one direction or another.
0:16:43 Whereas if you’re not using coin voting,
0:16:45 then that becomes more possible.
0:16:48 And so if you have a mechanism for identity
0:16:52 wherein you securely associate one human to one vote
0:16:53 or something like that,
0:16:57 then more sophisticated voting schemes become possible.
0:17:00 I think today, because we lack that kind of a mechanism,
0:17:03 people end up gravitating towards this simple
0:17:07 and somewhat, perhaps somewhat naive one coin, one vote model
0:17:09 which is vulnerable to this foot buying attack.
0:17:13 – Yeah, and this opens up a range of other issues.
0:17:15 So one problem that people have
0:17:16 when they analyze blockchain systems
0:17:18 and they sort of design these mechanisms
0:17:19 is that they look at their mechanism
0:17:21 and reason about its security properties,
0:17:23 but they do that in isolation.
0:17:25 And an important point is that none of these systems
0:17:27 really exist in a vacuum, right?
0:17:29 So take a look at any sort of blockchain
0:17:31 that uses coinholder voting to decide
0:17:33 the outcome of its consensus rules.
0:17:35 And there’s at least two such blockchains
0:17:37 that are sort of using this model.
0:17:39 If these two very large projects are approximately
0:17:41 the same size or one is a little bit bigger
0:17:43 than the other one or one is twice as big
0:17:45 as the other one or something like that,
0:17:47 it’s in the economic interests of everyone
0:17:49 who holds coins in the bigger project
0:17:51 to buy up coins on the smaller project
0:17:53 and influence votes in ways
0:17:55 that are sort of counter competitive.
0:17:57 And maybe even if they can’t buy up
0:17:58 enough of a blocked influence votes,
0:18:02 they can sow chaos and confusion and things like that.
0:18:05 So while one of these systems, you may say in isolation,
0:18:07 like, okay, the coinholders interests are represented
0:18:09 by this plutocracy, that doesn’t really work
0:18:11 when you have a whole world around it
0:18:13 that’s full of money that can frictionlessly
0:18:15 enter and exit the system at any time.
0:18:17 There’s no guarantee whatsoever
0:18:19 that the people who are economically in right this second
0:18:21 have an interest in that system,
0:18:22 especially when there are much bigger systems
0:18:24 that are competing with it.
0:18:25 So I think that’s a very important point
0:18:26 that people overlook.
0:18:28 And again, we mentioned that there’s this sort of stack
0:18:30 of voting, even at the consensus layer,
0:18:32 that has implications on the whole stack.
0:18:34 So if you have a fork that’s like 10%
0:18:36 of the size of a project,
0:18:38 and this fork could potentially impact
0:18:40 the price of the larger project,
0:18:42 it’s absolutely in the interest of that larger project
0:18:45 to launch attacks on that base layer proof of workflow
0:18:46 and do things like censorship,
0:18:48 use some small percentage of their hash power
0:18:51 to do 51% attacks or denial of service
0:18:52 or whatever they need to do to make sure
0:18:54 that that network goes down in price.
0:18:56 And that attack might even be profitable,
0:18:58 especially if there are mechanisms to short
0:18:59 that sort of smaller project.
0:19:00 – Yeah, that’s a very good point.
0:19:03 I think most proponents of a coinholder voting
0:19:07 would argue that it is just not in your interest
0:19:10 to sell your vote because you’d be damaging
0:19:11 the value of the asset that you hold.
0:19:14 And you hold a coin, and if you sell the votes
0:19:15 associated with that coin,
0:19:17 and that might reduce the value of the coin
0:19:20 in some way that sort of results in a net loss for you.
0:19:22 But that analysis happens entirely in a vacuum.
0:19:26 It happens sort of assuming that there aren’t any kind
0:19:28 of external mechanisms via which you could profit
0:19:31 from the loss of value of this particular coin.
0:19:32 Like for example, what you’re mentioning,
0:19:33 competition between blockchains.
0:19:36 If I’m a stakeholder, a much larger stakeholder
0:19:37 in a competing network,
0:19:39 then I might have a strong interest
0:19:41 in reducing the value of this particular coin,
0:19:42 and that that’s associated
0:19:44 with this one competing crypto network
0:19:46 because it may result in a larger profit
0:19:48 outside of the system.
0:19:51 And so I think, yeah, the incentive structures
0:19:53 that are built in aggregate tend to be far more complex
0:19:55 and they kind of interact in ways
0:19:58 that tend to be difficult to analyze
0:19:59 and could result in complexity
0:20:01 that could ultimately result in attacks.
0:20:03 And you post, you talk a little bit
0:20:05 about what you refer to as the dark DAO,
0:20:07 which sounds like a fairly dark picture
0:20:10 of what could end up being the case.
0:20:11 In your view, what is the worst case scenario here?
0:20:14 How could this unfold in a bad way?
0:20:15 – Yeah, so there’s a lot of different variants
0:20:17 of the dark DAO which have different assumptions
0:20:19 in the post, some of them require trusted hardware,
0:20:20 some of them don’t.
0:20:22 But the ultimate point of the dark DAO
0:20:23 is that it’s a private smart contract
0:20:26 for attacking a vote, for vote buying,
0:20:28 that essentially hides from the rest of the world
0:20:30 how much money is committed to this contract,
0:20:33 who is participating in the vote buying contract,
0:20:35 and sort of how far along the contract is.
0:20:37 But sort of is a way to frictionlessly
0:20:40 and permissionlessly form a vote buying cartel
0:20:41 for a particular vote.
0:20:42 And this could be sort of a funding pool,
0:20:44 anyone can come contribute money to it.
0:20:45 So if it’s outcome specific,
0:20:47 it could be funded by anyone who’s interested
0:20:48 in such an outcome,
0:20:50 whether it be other blockchain projects,
0:20:53 users on the system, outside groups, whatever it may be.
0:20:55 So once this dark DAO is funded,
0:20:57 what it does is sort of offer up vote buying
0:20:58 to people in the system.
0:21:01 And if people in the system come take this vote buying,
0:21:02 they retain access to their funds,
0:21:05 they keep using their wallet as they normally do,
0:21:07 but they’re sort of shackled by the dark DAO
0:21:08 that for this particular vote,
0:21:10 they can only vote in this certain way.
0:21:10 And this is trustless
0:21:12 because both sides have some guarantees.
0:21:16 So the vote buyers or vote buying network
0:21:18 or whatever it may be has guarantees
0:21:19 that potentially no one will find out
0:21:21 who’s being bought or sold
0:21:23 and how much money is pledged to it.
0:21:24 They’re guaranteed that if they pay for a vote,
0:21:27 this vote will actually be executed in the protocol,
0:21:29 even if the protocol does have
0:21:31 the classic properties of coercion resistance.
0:21:33 Another sort of sidebar of the dark DAO
0:21:36 is that trusted hardware, which is a new technology,
0:21:38 sort of breaks all classical coercion resistance voting
0:21:40 schemes in the blockchain world
0:21:42 and in the regular election world.
0:21:43 So once they launch this attack
0:21:45 and they start buying and selling people’s votes,
0:21:47 they have a number of options available to them.
0:21:48 One cool thing you can do
0:21:50 is you can tell everyone in the cartel
0:21:52 when a certain threshold is reached.
0:21:54 Let’s say when like 70% of the,
0:21:57 or 10% of the votes are locked into this DAO.
0:21:59 And you can do this in a way that’s deniable
0:22:01 such that everyone inside the cartel can check,
0:22:03 yes, 70% is reached,
0:22:05 but no one outside the cartel has any way of knowing
0:22:07 that this is actually reached.
0:22:09 So you can enforce an information asymmetry
0:22:12 that allows for profiting through things like shorting.
0:22:14 You can also enforce stronger information asymmetries,
0:22:16 so not even allow the people who are being bribed
0:22:19 to know at any time how much money is in it
0:22:23 or even potentially whether they voted at all
0:22:25 if the scheme is receipt free.
0:22:27 So it’s a very, very powerful class of attack.
0:22:29 You can spin it up however you want.
0:22:31 It allows people to pool their money and buy votes
0:22:34 in a way that they can keep any part of that secret
0:22:35 to any group of people that they want.
0:22:37 And the outside system has no way of knowing
0:22:39 sort of how far along the attack is.
0:22:41 In some ways, it also represents a credible threat.
0:22:42 If I were to launch a dark DAO,
0:22:44 I might not even need to necessarily have people
0:22:45 participate in it.
0:22:47 Just its existence might be enough
0:22:50 to shake people’s confidence in that underlying vote.
0:22:52 So when we publish that blog post,
0:22:54 we’ve had a lot of reactions from voting projects
0:22:55 and other people in the space.
0:22:57 And I think there is a good question
0:22:58 of why haven’t we seen this already?
0:23:01 But at the end of the day, these systems are tiny, right?
0:23:03 Blockchains today are a drop in the bucket
0:23:05 of like the world financial system
0:23:07 and the incentives just aren’t there yet.
0:23:08 But if we are to use these technologies
0:23:10 and if we are to scale things,
0:23:13 I think these are absolutely realistic scenarios
0:23:15 and potentially nightmare scenarios.
0:23:16 – Yeah, that sounds insane.
0:23:18 And that’s definitely an outcome that is to be prevented.
0:23:21 And I think, I mean, this matters because
0:23:24 if we just take a step back and think about why is governance
0:23:26 so topical and so important in the world of crypto
0:23:27 and blockchains today?
0:23:32 It is because so much of what drives the space forward
0:23:35 in what is sort of the underlying philosophical motivation
0:23:39 is that power over these networks is decentralized.
0:23:41 And so decentralization here refers to
0:23:42 a bunch of different things at the same time.
0:23:44 Like people talk about decentralization
0:23:46 as it refers to sort of consensus,
0:23:50 like who gets to decide like who modifies
0:23:51 the underlying ledger,
0:23:52 but also decentralization applies
0:23:54 to who gets to modify the code.
0:23:56 These networks are decentralized in that
0:23:58 they’re kind of like self-governing organizations
0:24:00 and they don’t have at least philosophically
0:24:03 any central points of control where any one individual
0:24:06 can decide how to sort of modify the code
0:24:08 or make it work in any particular way.
0:24:12 And so all of these initiatives to try to build in governance
0:24:15 into the protocols are an effort to try to
0:24:17 sort of decentralize even that aspect
0:24:20 and to try to make it so that the code itself can evolve
0:24:22 in a way that is still community driven
0:24:24 and not kind of centrally controlled
0:24:27 by the core developer team.
0:24:28 – Yeah, I think the promise of a lot of these systems
0:24:31 is sort of this crypto economic security, right?
0:24:33 You have this mechanism and because the mechanism works
0:24:34 and the incentives are set up right,
0:24:36 everyone comes together harmoniously
0:24:38 and produces something that is bulletproof
0:24:42 and very strong because of the incentives and the mechanism.
0:24:43 An example of this is Bitcoin.
0:24:45 Because of the money paid to miners,
0:24:48 people are burning a small country’s worth of electricity
0:24:50 to try to secure this transaction ledger
0:24:52 that has actually worked fantastically so far.
0:24:53 So when you design these systems,
0:24:56 there needs to be some sort of underlying mechanism
0:24:57 and some sort of reasoning about the security
0:24:59 of that mechanism.
0:25:01 But what these technologies like the dark dial
0:25:03 and private smart contracts allow you to do
0:25:06 is use external money to sort of alter the incentives
0:25:09 inside that game and alter the security properties
0:25:12 that people are actually getting from their project
0:25:15 in a permissionless and trustless way.
0:25:17 So this does sort of speak
0:25:20 to the fundamental coordination of blockchains, right?
0:25:23 Like how do we design these games to coordinate people
0:25:26 to make choices in a way that’s not controlled
0:25:28 by one particular individual, as you said,
0:25:30 or some social trust hierarchy,
0:25:32 but by the economics of the system itself?
0:25:33 And in that model,
0:25:35 if you can’t be secure against economic attacks,
0:25:38 then you’re sort of building something
0:25:40 that doesn’t make much sense in my opinion.
0:25:43 And so I guess that’s a lot of what my work is looking at.
0:25:45 – Right, what do you think are the implications
0:25:47 of vote buying on proof of stake?
0:25:50 – So proof of work is where people use hardware
0:25:51 to sort of solve hard problems.
0:25:53 And if they solve the problem,
0:25:55 then they can post a block to the network.
0:25:56 Rather than using this mechanism,
0:25:59 proof of stake allows people to vote using their coins.
0:26:01 So they lock up their coins for some long period of time
0:26:04 and they can use any number of protocols to do this.
0:26:07 The core idea here is that instead of proof of work
0:26:09 where the economic security you get
0:26:12 is because people are doing this useless computation problem
0:26:13 that is sort of burning money
0:26:16 and there’s some costs associated with doing this,
0:26:18 is that people are paying liquidity costs
0:26:20 to lock up these coins for a long, long period of time
0:26:22 and they’re also taking risks
0:26:23 that they may incur penalties
0:26:25 if they misbehave in the protocol.
0:26:27 And with these liquidity costs,
0:26:28 they’re taking like massive volatility risks
0:26:30 in cryptocurrencies, right?
0:26:32 So if they do something that crashes the system,
0:26:33 well, their coins are locked up
0:26:34 and they’re going to lose money.
0:26:36 If the network decides they misbehaved,
0:26:38 well, they can get rid of all their coins
0:26:39 and they’re gonna lose money.
0:26:40 So it’s this idea of bootstrapping
0:26:42 the economic security of the network from the coins
0:26:45 rather than from some external hardware source.
0:26:46 Obviously that comes with a lot of trade-offs
0:26:48 that are maybe beyond the scope of this discussion,
0:26:50 but at the end of the day, it’s also a voting protocol.
0:26:53 You have these people with coins, they decide how to vote.
0:26:55 So where does vote buying come in here?
0:26:57 Well, obviously this proof-of-stake protocol has an outcome.
0:27:00 It decides what history of the network is valid
0:27:02 and this outcome has all sorts of economic implications.
0:27:05 It decides who gets to send money to who.
0:27:07 It decides who is censored in the system.
0:27:10 It decides what order transactions happen in canonically
0:27:12 according to everyone in the system
0:27:14 and with that comes a lot of profit opportunity.
0:27:17 So I can potentially profit by censoring you
0:27:19 or I can profit by putting my transactions in front of yours
0:27:22 when you wanna execute an order on a decentralized exchange
0:27:25 or I can profit in sort of any number of different ways
0:27:26 by manipulating this vote.
0:27:28 So what you can do with the dark DAO
0:27:30 is to start a staking pool where I say like,
0:27:32 you know, let me do my algorithmic trading
0:27:34 and decide what order of transactions
0:27:35 makes me the most money.
0:27:36 You don’t necessarily care
0:27:38 if someone who’s doing a transaction on a dex
0:27:40 gets front-run and loses like $5, right?
0:27:43 So you say, okay, I’ll happily participate in this.
0:27:45 It’ll still keep the value of my coins high,
0:27:46 especially if I don’t have a lot of coins
0:27:48 and you’re paying me like twice as much
0:27:50 as any other staking pool.
0:27:52 So it sort of opens these coordination mechanisms
0:27:54 for attacks on the underlying transaction history
0:27:56 and the underlying consensus.
0:27:56 – Do you think that there’s a way
0:27:59 of making a proof-of-stake network secure?
0:28:01 – It depends on your definition of secure.
0:28:04 I think it really depends on the type of security you want,
0:28:05 I guess.
0:28:07 – Yeah, and this all gets to the broader question
0:28:10 of like economic security of a blockchain.
0:28:11 And in the case of proof-of-stake,
0:28:13 the resource that’s used to secure the blockchain
0:28:14 is internal to the network.
0:28:15 In the case of proof-of-work,
0:28:18 it’s sort of electricity and like hardware
0:28:21 that’s used external to the network to secure the ledger.
0:28:22 And there are many other kind of approaches.
0:28:26 Like people are experimenting with doing useful work.
0:28:28 Instead of burning electricity uselessly
0:28:30 as you do in proof-of-work,
0:28:32 people try to build a sort of proof-of-space
0:28:34 or proof-of-spacetime protocols
0:28:39 where like for example, you’re able to store files
0:28:41 and storage becomes the resource that people use
0:28:43 to then secure the network.
0:28:44 What do you think of that kind of approach?
0:28:46 – So fundamentally to vote buying,
0:28:48 it doesn’t actually matter what resource you’re using.
0:28:50 Vote buying works for proof-of-work too.
0:28:52 So I could use dark DAO like technology
0:28:53 to start the mining pool.
0:28:55 And the properties of the mining pool would be
0:28:56 you come, you mine here.
0:28:57 I’ll pay you more than we’re making
0:28:59 because I have some external incentive
0:29:02 to censor someone or reorder transactions or whatever.
0:29:04 And then you get the dark DAO privacy properties
0:29:06 of no one knows how much hash power is participating
0:29:09 in this pool or who’s getting paid or things like that.
0:29:11 So these certainly also apply to systems
0:29:15 that use things like files and other useful work properties.
0:29:17 I think there’s a whole class of other questions
0:29:19 on the economic security of those systems.
0:29:21 So you have to be really careful
0:29:23 about where the economic security comes from.
0:29:24 I think you have to be really careful
0:29:26 with what useful means.
0:29:28 Whether the fact that it’s useful also introduces
0:29:31 any external incentives to mess with it, right?
0:29:35 So you could imagine like if the useful thing
0:29:37 the network was doing was like powering a search engine
0:29:38 or something, right?
0:29:39 Those results are valuable
0:29:42 and they bring external actors in who want to manipulate that.
0:29:43 And there’s sort of this feedback loop
0:29:45 between the mechanism securing the protocol
0:29:48 and the utility of what the protocol is actually providing.
0:29:50 But there’s definitely some people in the community
0:29:53 that look at that and say this is all way too complicated.
0:29:54 This is never going to work.
0:29:55 You have to have it be useless
0:29:57 because there’s no external incentives
0:29:59 and messy things that way.
0:30:02 I personally think that’s an open question.
0:30:03 – Yeah, there’s this argument that people make
0:30:06 that if the resource that is used to secure the network
0:30:08 is very commoditized
0:30:09 and just generally exists in the world
0:30:12 in the world in sort of plentiful quantities
0:30:13 that for example, in the case of storage,
0:30:16 if storage is the resource that’s used to secure the network
0:30:17 then anyone with a bunch of storage
0:30:19 could presumably attack the network.
0:30:22 Whereas in the case of a network like say Bitcoin
0:30:25 where you have ASICs that are specific to the network
0:30:27 in order to attack the network
0:30:28 you have to get your hands on those ASICs
0:30:30 and those ASICs aren’t useful for anything
0:30:31 but mining Bitcoin.
0:30:35 So people would argue the security of that kind of
0:30:38 the economic security of that kind of model is better.
0:30:40 – Yeah, and Joe Bono has a fascinating line of work
0:30:41 on these problems.
0:30:42 So if you Google Goldfinger attacks
0:30:44 he has a paper and a presentation.
0:30:47 There’s also the question of like buying versus renting.
0:30:48 So if something is very commoditized
0:30:50 you may be able to rent it
0:30:52 which substantially subsidizes the tax.
0:30:54 You may be able to buy it, perform the attack
0:30:56 and then resell it into the commodity market
0:30:59 which again substantially subsidizes the attack.
0:31:02 So these are all open and very complex questions
0:31:04 but people will build the systems and we’ll see.
0:31:06 This is sort of a classic pattern you see
0:31:08 in traditional finance.
0:31:10 And then you’ll have sort of black swan
0:31:13 and tail risk like events that surprise people.
0:31:15 – So we’ve talked a lot about governance in general
0:31:19 but you obviously are working on a ton of interesting stuff
0:31:21 just generally with respect to economic security
0:31:23 for crypto networks and blockchain
0:31:24 just the computer security.
0:31:27 What are some of the other interesting ideas
0:31:29 or sort of lines of work that you’re exploring?
0:31:32 – So one that I’m extremely personally interested in
0:31:35 is fairness guarantees for users around these systems.
0:31:36 A lot of what attracted me to them in the first place
0:31:39 was this promise of sort of eliminating the middleman
0:31:41 and making things in control of the user.
0:31:43 Like be your own bank, you don’t need these institutions
0:31:45 to tell you how to set your money supply
0:31:47 or how to route your transactions
0:31:50 or what exchange to use, et cetera, et cetera.
0:31:52 I look a lot at those guarantees
0:31:54 and sort of the ways in which modern blockchain solutions
0:31:56 are failing to meet those guarantees.
0:31:59 So one example of that is in the decentralized exchange space.
0:32:01 That’s something that’s seen a lot of promise
0:32:03 from people who wanna build these exchanges
0:32:06 that aren’t vulnerable to hacks and other user fund theft.
0:32:08 Unfortunately, the way these mechanisms
0:32:10 that people are building interact with the blockchain
0:32:13 is very complex and opens the door for external actors
0:32:15 to make a lot of money from front running them
0:32:17 and make a lot of money from doing algorithmic trading
0:32:19 on the network and everything that you see
0:32:21 in the traditional financial world.
0:32:24 So some of my work is around how large is that economy
0:32:27 and what are the failures of those guarantees?
0:32:30 – What are some interesting results so far on that front?
0:32:33 – So it’s actually probably a bigger market than you think,
0:32:36 even though DEXs have not seen substantial volume.
0:32:38 So this is a big problem for users.
0:32:41 It also highlights a lot of weird quirks of these systems,
0:32:44 such as like allowing for typos that end up costing users
0:32:47 a lot of money when programmatic actors soup in
0:32:50 and sort of take advantage of these inefficient mechanisms.
0:32:53 And it also raises fundamental questions about, I guess,
0:32:55 whether we’ll be able to do something that’s different
0:32:57 from the current financial system
0:32:59 because there are still these information asymmetries
0:33:01 that come up and this is a worldwide network.
0:33:02 And at the end of the day,
0:33:04 someone is still ordering transactions.
0:33:07 So is this rent sort of implicit to all blockchains?
0:33:09 How large is it?
0:33:12 And does it threaten the security of the overall blockchain?
0:33:13 Which I think it may.
0:33:15 – So I think one very interesting line of work
0:33:18 that you did was around gas token
0:33:20 and tokenizing gas on the Ethereum network.
0:33:23 – So this sort of came out of this arbitrage project.
0:33:25 We wrote a blog post very early on,
0:33:27 last I think October, November,
0:33:29 essentially saying decentralized exchanges are flawed.
0:33:31 You can just run this 20 line Python script
0:33:33 and you can profit off of users in a way
0:33:34 that was maybe not foreseen
0:33:37 and is not sort of explicitly stated to them
0:33:39 because of how inefficient these mechanisms are.
0:33:40 And before we wrote this blog post,
0:33:42 we were actually doing this to test it, right?
0:33:44 And we said, we made X dollars, whatever.
0:33:45 After we wrote the blog post,
0:33:47 sort of this cottage industry spawned
0:33:50 of like a few dozen people who are competing
0:33:53 in sort of this market and trying to outbid each other
0:33:57 to get their transactions first in that mind order
0:33:59 and take advantage of these opportunities.
0:34:00 So we’ve been studying that market for quite a while
0:34:02 and competing against these guys.
0:34:04 And unfortunately at some point,
0:34:05 they started out competing us.
0:34:07 So we started competing on what’s called gas,
0:34:08 which is the price you’re willing to pay
0:34:10 per unit of transaction.
0:34:12 The way it works is you make a typo Ali,
0:34:14 it puts a million dollars on the table
0:34:16 for anyone who can get their order in ahead of that typo
0:34:18 and sort of take advantage of your typo.
0:34:20 And then I would like to do a $5 transaction
0:34:23 to take advantage of Ali’s mistake, right?
0:34:26 And then maybe someone else is willing
0:34:27 to do a $10 transaction
0:34:29 ’cause it’s a million dollar opportunity, right?
0:34:31 So we sort of get into this bidding war of like,
0:34:33 minor, please pick me first, minor, please pick me first.
0:34:35 That’s inherent to how these transactions
0:34:36 are ordered by miners.
0:34:38 And what we noticed is that when you have like 10 of these,
0:34:39 we were rarely profiting
0:34:40 because we didn’t have the best latency,
0:34:42 we didn’t have the best infrastructure
0:34:44 and they were getting their bids out faster.
0:34:46 They were getting them two miners faster
0:34:48 and they were willing to bid up higher than we were
0:34:50 to essentially take these opportunities.
0:34:51 So that’s where gas token came in.
0:34:54 It’s a way to sort of store this gas for the longer term
0:34:57 rather than just paying for it when you do your transaction.
0:34:59 So gas is the transaction fee.
0:35:00 And usually you say, okay,
0:35:03 I’m willing to pay a $100 fee for this transaction.
0:35:05 Instead, what you could do is sort of bank
0:35:06 a transaction’s worth of gas
0:35:08 and then just deploy that bank gas
0:35:09 and not pay as much fee
0:35:11 for the transaction you are doing.
0:35:12 And that works by taking advantage
0:35:16 of this fundamental issue in Ethereum’s resource model
0:35:18 which has to do with how you pay
0:35:22 to sort of incentivize people to clean up after themselves.
0:35:24 So in Ethereum, you actually give people a refund in gas
0:35:27 if they delete something they stored in the network previously
0:35:29 to incentivize them to not leave garbage around
0:35:30 that everyone has to store forever.
0:35:32 So what we do is when gas is cheap,
0:35:35 we fill the Ethereum state with junk
0:35:36 and then when it’s expensive, we delete this junk
0:35:39 which gives us a refund at that higher price
0:35:42 that we can use to subsidize these arbitrage transactions
0:35:44 which often costs thousands and thousands of dollars in fees.
0:35:47 Like people are bidding multiple thousands,
0:35:49 even tens of thousands in fees on these transactions.
0:35:51 – Right, and so to clarify for those not already familiar,
0:35:54 so gas is basically the resource that you use
0:35:56 to pay for computational resources
0:35:57 on the Ethereum blockchain.
0:36:00 So if you want it to buy computations, say instructions
0:36:03 that miners will execute for you, you pay for those in gas.
0:36:05 If you want it to buy a storage,
0:36:08 you similarly also pay for storage in gas.
0:36:10 And the current model of Ethereum is that you buy
0:36:14 some storage on the blockchain for a fixed price upfront
0:36:16 and then that storage sort of remains
0:36:18 on the blockchain forever.
0:36:20 And the Ethereum blockchain has this mechanism
0:36:22 that if you were to delete that storage,
0:36:23 if you were to free it,
0:36:26 then you will receive a refund for the amount that you paid.
0:36:30 Some refund for what you paid originally
0:36:31 for that amount of storage.
0:36:35 And so you’re basically saying that when gas is very cheap,
0:36:38 you can sort of fill storage on the blockchain
0:36:42 and then reclaim a refund later once gas is expensive.
0:36:45 And sort of the gas will be worth more at that point
0:36:47 than it was when you stored it.
0:36:48 And you could sort of leverage that
0:36:50 to kind of increase the amount of gas
0:36:51 that’s available to you.
0:36:53 – Yeah, and our fundamental observation was that
0:36:54 this is basically a derivative on gas.
0:36:57 It’s like a call option on some gas.
0:36:58 It led to the broader question
0:37:00 of how are these resources actually priced?
0:37:03 Like how do people choose how much is paid for storage?
0:37:06 How do people choose how much is paid for computation?
0:37:07 And in what ways are these suboptimal?
0:37:10 – So you mentioned the current model of pay one store forever.
0:37:12 That’s something we certainly address in our work,
0:37:14 proposing more of a rentful scheme
0:37:17 where you have to pay for ongoing costs at market rate.
0:37:19 There’s also the issue of who’s getting the payment.
0:37:21 So the fact that the miners get payment for storage
0:37:24 when the miners actually don’t need to store the whole state
0:37:26 and it’s the full nodes that bear the cost.
0:37:29 So this sort of asymmetry between who’s bearing the cost
0:37:31 like where the externality is
0:37:32 and like who’s actually profiting
0:37:34 is super important to study.
0:37:36 It leads to a sort of tragedy of the commons
0:37:38 in the worst case where the miners are happy to take payment
0:37:40 for as much storage as you want
0:37:42 because they don’t have to store it and they don’t care.
0:37:43 As long as they don’t break the whole network,
0:37:46 they’ll happily push out as many full nodes as they can.
0:37:47 So these are broader questions.
0:37:50 We have a broader initiative called Project Chicago,
0:37:53 which you can see at projectchicago.io.
0:37:55 That basically is studying these questions
0:37:56 of crypto commodities.
0:37:59 What are the underlying commodities behind blockchains?
0:38:02 For example, computation, relay network and storage.
0:38:03 How are these commodities priced?
0:38:05 How can you exploit these commodities?
0:38:07 How can you exploit like the relay network
0:38:09 to get information about people’s transactions earlier
0:38:13 or the computation layer to sort of, I don’t know,
0:38:16 do this kind of gas refund or something like that.
0:38:19 So there’s a lot of interesting work in that direction.
0:38:21 – Yeah, by the way, why is it called Project Chicago?
0:38:23 – So it’s called Project Chicago
0:38:25 ’cause our inspiration is sort of the Chicago mercantile
0:38:26 exchange.
0:38:28 That’s how businesses hedge against volatility
0:38:31 and sort of price commodities in real world markets.
0:38:35 So we think of this as sort of exploring something similar
0:38:36 on blockchains and asking like,
0:38:38 is that the right model or can we do better
0:38:40 now that we have all these decentralized tools
0:38:41 at our disposal?
0:38:42 – Best painting.
0:38:44 Well, thank you so much for coming on the podcast.
0:38:46 – Yeah, thanks for having me.

0:00:04 Hi, everyone. Welcome to the A6 and Z podcast. I’m Sonal.
0:00:08 Today’s episode continues our Enterprise Go-To-Market podcast series.
0:00:12 And the theme of this episode is for founders and product managers
0:00:15 to consider the tight relationship between product and go-to-market,
0:00:18 one informing the other in both directions.
0:00:22 What are the key milestones that go into both and in different phases of company building,
0:00:25 especially pre-to-post product-market fit?
0:00:31 The conversation features special guest Jyoti Bunsell, founder and founding CEO of AppDynamics.
0:00:34 He’s also a co-founder at Unusual Ventures and co-founder of Harness.
0:00:37 Joining me to interview Bunsell, we have General Partner Peter Levine,
0:00:41 who also put out a series of 16 short sales videos for founders,
0:00:45 which you can find at asixnz.com/16sales.
0:00:49 And then we have A6 and Z Enterprise Deal Team Partner Sathish Thaluri,
0:00:52 since he too came from AppDynamics, where he was last a senior director
0:00:55 of product and growth operations pre-sale to post-sale.
0:00:59 Speaking of, we go beyond the typical discussion of product-market fit
0:01:02 into the concept of product-market sales fit,
0:01:05 and what that means for product design, to services,
0:01:09 to pricing and packaging, to product management, and more.
0:01:14 But first, we quickly begin with the fundamental shift in mindset for technical founders.
0:01:17 The first voice you’ll hear is Jyoti’s, followed by Sathish’s,
0:01:20 talking about the initial insight behind AppDynamics,
0:01:26 which was acquired by Cisco last year for $3.7 billion the night before it was set to go public.
0:01:28 I was working as an engineer in a company,
0:01:32 and this was before the phrase you guys coined on software is eating the world.
0:01:33 This was 2008, right?
0:01:36 But it was clear that software is eating the world, right?
0:01:39 And to me, it’s like, okay, if everything is going to be software,
0:01:40 something goes wrong in software,
0:01:43 someone needs good tools to troubleshoot and fix it.
0:01:45 So that was really the insight.
0:01:51 AppDynamics was building monitoring and troubleshooting solutions for complex software apps.
0:01:56 So if you have an online banking and something goes wrong in your online banking,
0:01:59 you will use AppDynamics to figure out the root cause and fix it.
0:02:02 Or if Delta reservation systems are down and everyone is stuck on the airport,
0:02:06 someone needs to find tools to troubleshoot what’s the root cause of the problem and fix it.
0:02:09 That’s what AppDynamics built, those troubleshooting tools.
0:02:11 So now it’s like, when I jumped into it, I didn’t know anything.
0:02:14 I didn’t know how to raise capital.
0:02:16 I didn’t recruit anyone before AppDynamics.
0:02:18 So you had to go and figure out that out.
0:02:21 I didn’t know how to have lots of customer conversations
0:02:23 or even find customers to talk to.
0:02:26 At least during the pre-product market fit,
0:02:28 a lot of engineers, even including myself,
0:02:31 we get obsessed with the technology.
0:02:32 I’m not so much about the user.
0:02:36 At the end of the day, if the user adoption is not there, it’s no good.
0:02:38 I mean, there’s no market without the user.
0:02:38 Exactly.
0:02:40 You got the product side, but not the market.
0:02:42 I say a lot of engineers to be honest,
0:02:46 struggling about understanding that customer and user adoption
0:02:48 and the engagement metrics.
0:02:52 We thought that good UI/UX and really beat the open-source strategy
0:02:54 or the closed-source strategy doesn’t matter.
0:02:59 But user adoption is what should be driving the pre-product market fit.
0:03:02 Now, the challenges completely change after you have your initial product market fit.
0:03:06 They become all about sales and learning sales and scaling sales.
0:03:10 It’s almost like the companies go through the journey, right?
0:03:12 The pre-product market fit, the challenges are different.
0:03:15 Then after a product market fit,
0:03:18 the challenge becomes about selling and scaling sales organizations.
0:03:22 You’re saying on one hand that you have to sell after product market fit.
0:03:24 But on the other hand, I’ve heard that for a lot of enterprise businesses,
0:03:28 part of the act of selling is finding those users in the first place.
0:03:29 It’s a bit of a chicken-egg thing.
0:03:32 Well, a lot of us start our careers as engineers.
0:03:39 And a lot of our construction of a business is around the features
0:03:40 and around what the product does.
0:03:42 It’s all technically oriented, right?
0:03:45 Because what we often say is, “Okay, well, if we have these features,
0:03:47 then people will come and buy it.”
0:03:53 And I find that some of the go-to-market is an afterthought once you’ve built something.
0:03:55 And I would argue in today’s day and age,
0:04:00 if you’re going after small businesses versus large enterprises
0:04:03 or self-serve or whatever,
0:04:07 thinking about that up front along with the product requirements
0:04:11 and technical requirements may be a good thing to go and do.
0:04:18 Like, I think to sequentially order those probably results in an efficiency issue, right?
0:04:21 We go build something and, “Oh, who knows how to go sell this?”
0:04:27 And all of that might it be useful to say to technical entrepreneurs,
0:04:31 “In order to do this, you got to go figure out the go-to-market as well
0:04:35 as the product features and don’t eliminate that or push that off.”
0:04:36 I would totally agree.
0:04:42 The way I mentally think of this is two phases of product-market fit.
0:04:46 The phase one is really even figuring out where your target market is.
0:04:49 So for that one, you really want to start broad and then segment.
0:04:56 Like, if you don’t know where would your idea or your product fit the most?
0:05:00 Is it large enterprise? Is it SMB? Is it financial services?
0:05:04 Then I would just go and interview all of them and not narrow yet
0:05:06 and start building the product which is a little bit wider.
0:05:09 And how did you guys come to that?
0:05:10 Where did you start?
0:05:13 You had this wide aperture and then it narrowed to what was the first thing.
0:05:16 You know, to me it was that people are building this complex software apps
0:05:17 and they need to monitor them well.
0:05:20 And I had the technology idea that if you can instrument the code
0:05:23 and trace everything, then it would be a good product.
0:05:25 But I didn’t know who would buy it.
0:05:27 I started like, okay, let me go and broaden it.
0:05:30 Let me go and find people in larger enterprises to talk to.
0:05:32 Let me go and find people in startups to talk to.
0:05:35 Let me go and find people in mid-sized companies to talk to
0:05:38 and see where it sticks the most or where the most pain is.
0:05:41 And what I found was, okay, the most pain is where
0:05:43 they are these kind of medium to large companies
0:05:46 which are building these complex distributed Java applications.
0:05:48 So let me now focus more on that.
0:05:52 So I started broad and then we started narrowing down a bit of the focus.
0:05:56 And but after that, once you identify it, then it’s very important
0:06:00 that you marry the go-to-market model in your product thinking.
0:06:03 Because these days it’s all very tightly coupled together.
0:06:05 You don’t have like, you know, sales is different,
0:06:07 then marketing is different, then product is different,
0:06:09 then all of it’s all together in many ways, right?
0:06:12 So if you have an open source model or you have a freemium model
0:06:15 or if you have a, you know, is it SaaS, is it on-premise,
0:06:18 is it hybrid of it, is it going to be land and expand
0:06:21 and you have to engineer your product with that in mind.
0:06:24 Right. The features of the product almost have to inherit
0:06:28 part of the go-to-market within the product itself, right?
0:06:30 And a lot of product design, I think,
0:06:34 reflect the go-to-market attributes that need to be considered.
0:06:36 So in the epidemics, I used to say like,
0:06:39 it’s a little bit misleading to just call it product-market fit.
0:06:42 We should call it product-market sales fit.
0:06:43 Oh, I love that.
0:06:45 You know, it’s like, it’s like, have we found the right,
0:06:48 you know, there’s a right market and you have the right product
0:06:51 and we have the right sales or go-to-market strategy.
0:06:52 Right. That works for it.
0:06:54 So when you said two phases of product-market fit,
0:06:56 the first one was where, like the,
0:06:58 either the small, big enterprise, different domain or industry
0:07:01 and the second one was the sales motion.
0:07:03 So it’s, the thing of phase one is like, you know,
0:07:06 where is the most pain and where your product
0:07:09 or your unique approach or whatever it is
0:07:12 solves the pain in a way that people will pay for.
0:07:14 And you’re also validating like your technology,
0:07:14 does it really work?
0:07:16 Can you really build the product?
0:07:17 Does it really solve the pain?
0:07:19 And then you have to figure out like,
0:07:21 what is the sales strategy or go-to-market strategy
0:07:23 that will work and scale?
0:07:25 And does your product support that?
0:07:27 Because if your product doesn’t support it,
0:07:28 you know, many times people are like,
0:07:31 you know, we’re going to build a freemium strategy.
0:07:33 You know, but the problem is if your product is too complex,
0:07:34 freemium doesn’t work.
0:07:36 But just to drive this point home,
0:07:40 which I completely agree with, the product,
0:07:43 the features of the product need to inherit
0:07:46 part of the sales motion itself, right?
0:07:50 And that if you’re going after a certain motion
0:07:54 or certain customer, the product needs to be reflective of that.
0:07:55 And I think we often miss there.
0:07:59 Like we build a product and even if we define a go-to-market,
0:08:02 the product features or the interface,
0:08:07 the design may be completely misaligned
0:08:09 with the target audience or target go-to-market,
0:08:10 I should say.
0:08:14 And some of it you can also break into say revenue goals.
0:08:17 Like, you know, I would roughly think getting to your zero
0:08:19 to the first million ARR,
0:08:21 you’re in that phase one of product market fit.
0:08:23 – ARR is the annual recurring revenue.
0:08:24 – Annual recurring revenue, which is like, you know,
0:08:27 do you have a product someone will buy
0:08:28 and it’s solving some pain?
0:08:32 Then you’re like, you know, a million to the 10 million in revenue.
0:08:35 That’s where you’re retreating on the go-to-market strategy
0:08:37 and getting the product to be aligned with that.
0:08:39 And if you get that right, that like at 10 million,
0:08:40 you should be there like, you know,
0:08:44 you got the product market and sales fit as well.
0:08:47 And then you can, you know, press, you know,
0:08:51 the guests and go from 10 to 100 from there or like, you know,
0:08:55 but you got to get that iteration on the sales fit to it.
0:08:56 – So I have a question for you here.
0:08:58 So in your case, you had a product
0:09:00 where you knew the tool was solving an existing problem.
0:09:02 Does that calculus change if it’s a,
0:09:05 you’re creating a category and you’re going into a market
0:09:08 where quote, the problem does not already exist,
0:09:11 because then you don’t actually have the ability to necessarily
0:09:14 know where or how to figure out the sales motion yet.
0:09:16 Or is that not true?
0:09:18 Because I think a lot of founders might argue that,
0:09:20 well, why can’t I be like Steve Jobs and sort of invent,
0:09:23 like create the product that people all go to?
0:09:24 Like what would you say to that?
0:09:27 – Well, you’re always creating, you know,
0:09:28 either you’re solving a problem
0:09:31 significantly better than others have done in the past.
0:09:34 And the dimension of what does significantly mean
0:09:35 could be different.
0:09:37 It could be your 10x more scalable,
0:09:39 your 10x more easier, your 10x more cheaper,
0:09:39 whatever it is, right?
0:09:41 – Right, I’ll 10x better.
0:09:43 – It has to be 10x better in some dimension.
0:09:45 So in an existing problem,
0:09:47 or if it’s a new problem that’s emerging,
0:09:48 then it’s, you know, you’ll, you’ll,
0:09:51 you’ll still have the problem has to be there.
0:09:53 Either there’s problem with existing vendors,
0:09:56 or there’s problem because there is no solution there,
0:09:57 but it has to be there.
0:09:58 Otherwise you don’t have anything to sell.
0:10:02 – And I think in enterprise more than consumer,
0:10:04 there’s a budget, there’s a certain budget dollar
0:10:06 that you’re going to go after in enterprise,
0:10:09 maybe it comes out of the development budget,
0:10:12 it comes out of engineering, marketing, sales,
0:10:16 there’s something for which you can at least start to frame
0:10:19 this new thing, new market, whatever.
0:10:22 Like one of the questions to ask is,
0:10:24 who’s the potential buyer for this?
0:10:26 Even if it’s a totally new market, right?
0:10:29 But let’s call it enterprise products somewhere,
0:10:30 doesn’t exist before.
0:10:34 Still, who’s the buyer and what budget does it come out of?
0:10:37 And a lot of products actually where there isn’t a market yet
0:10:39 may span multiple buyers, in fact,
0:10:42 may come from multiple different departments
0:10:44 and span budgets and you need to think about that.
0:10:47 Like, okay, I’m creating this new market,
0:10:51 but perhaps the buying motion and what the customer
0:10:55 is used to actually doing from a buying behavior
0:10:57 is so complicated, it’s never going to happen.
0:11:00 – Yeah, even for the product managers or the founders,
0:11:03 it always helps to do a sales kind of play,
0:11:05 wherein how exactly you are going to sell
0:11:09 and who is the actual buyer and who is the actual user?
0:11:11 What are you going to say to the user?
0:11:13 What pain points you are going to solve?
0:11:17 And how exactly the user is going to use your product?
0:11:19 I think working with the salespeople
0:11:22 who are actually on the front lines to go and sell
0:11:25 for the engineers and the product managers,
0:11:26 it really helps.
0:11:28 And in fact, at your company,
0:11:31 you made a lot of engineers to go on those calls
0:11:35 to literally understand who exactly is buying that product,
0:11:36 how much is he going to pay.
0:11:39 And for that, what exactly you need to build.
0:11:41 So that connection for the engineers
0:11:44 to go on those sales calls really helped them
0:11:46 to understand that sales motion
0:11:48 and how to incorporate into that product.
0:11:50 That’s one of the best practices I allowed.
0:11:53 So that’s how engineers always got to understand
0:11:54 that sales motion.
0:11:56 – We had that strong belief is just that
0:12:00 we have to break the barriers between engineers and customers.
0:12:04 In the startups I worked at before AppDynamics as an engineer,
0:12:06 people will say engineers don’t know how to talk to customers.
0:12:09 So let’s keep them away from customers.
0:12:11 And so we are selling to engineers,
0:12:12 like our products are technical.
0:12:15 So that just doesn’t make any sense to me.
0:12:17 In the early days of finding the business case,
0:12:20 the finding where the budget will come from,
0:12:23 one of the questions that we always asked,
0:12:26 my favorite question to ask to any customer was,
0:12:28 how would you make the business case to your boss to buy this?
0:12:31 And that’s when you would start hearing like,
0:12:33 this is my business case like in every time we have outage,
0:12:39 we normally spending six engineers in a room for five hours
0:12:41 to try to figure this out with you guys.
0:12:44 I can reduce it down to one engineer for 15 minutes.
0:12:46 And that’s my business case.
0:12:48 And once you start hearing the business case,
0:12:50 then you can know that there is a business case.
0:12:53 You can monetize it and you can convert into dollars at some point.
0:12:55 – How do you navigate that though?
0:12:56 When you have multiple budgets
0:12:58 and multiple decision makers inside the enterprise,
0:13:01 different groups or departments have different problems
0:13:02 or itches that you’re scratching?
0:13:05 And how do you sort of up level it so that you’re selling
0:13:06 into getting the big bucks
0:13:08 and not just sort of the incremental budget?
0:13:11 – I mean, I would say it all depends again on this,
0:13:14 you know, product market sales strategy.
0:13:18 A lot of companies that start with bottoms up
0:13:20 only go after an individual user.
0:13:24 And then they get enough use on individual users
0:13:27 and propagation from the bottoms up.
0:13:28 I call that self-serve.
0:13:30 So there’s no complexity there.
0:13:34 There’s no, you know, multiple buying centers or whatever.
0:13:35 So it’s not a foregone conclusion
0:13:38 that you just, that that, you know, is the way to go.
0:13:41 Now, after enough people are using the product,
0:13:43 then you can come in with tops down and say,
0:13:45 “Hey, did you know like everyone in your organization
0:13:47 is already using the product?
0:13:48 You ought to have a corporate-wide license
0:13:50 so we can private support and all of that.”
0:13:53 So that would be an example of bottoms up
0:13:55 and then coming in on tops down.
0:13:57 Many other products that were designed
0:13:59 to be tops down as a starting point
0:14:02 because it may go across departments,
0:14:05 it may be more complicated.
0:14:07 There’s security needs, whatever,
0:14:09 where a bottoms up design just doesn’t work, right?
0:14:13 In which case then you probably need to start
0:14:16 with a more traditional, let’s say,
0:14:17 a direct sales organization.
0:14:20 It could be an inside sales organization
0:14:22 or direct calling in and actually getting the customer.
0:14:26 I mean, complex sales often requires multiple buyers,
0:14:29 multiple parts of the organization to come together
0:14:35 and that’s a skill set that a well-honed sales organization
0:14:36 will know how to do.
0:14:38 How did you guys, what was your sales motion at AppDynamics?
0:14:41 So ours was a combination of both.
0:14:44 We, you know, in AppDynamics, you call it the sandwich strategy.
0:14:44 The sandwich strategy.
0:14:47 You go from the bottom, you go from the top,
0:14:49 you’ll go to the developers and DevOps engineers directly.
0:14:52 It was done through a freemium kind of model
0:14:53 so that they will start for free
0:14:56 and they can use a light version of our product for free.
0:14:57 And then we will start going from the top,
0:15:00 where we will create air cover
0:15:02 and when we have multiple users in an organization,
0:15:03 then we’ll go and sell them more.
0:15:05 So really the sales motion was built on,
0:15:08 the end users can start for free.
0:15:10 Then we will have, sell them some licenses,
0:15:11 we call it land and expand.
0:15:13 The land deals, which are like, say,
0:15:16 $20,000, $30,000, $50,000 deal.
0:15:17 On phone, we can sell that.
0:15:19 And then we’ll expand into like half a million,
0:15:21 million, $2 million.
0:15:22 Now these days when $10 million deals,
0:15:25 that you need traditional enterprise sales people.
0:15:28 So inside sales versus field sales basically in that context?
0:15:31 Yes, but in most of these companies today,
0:15:32 you would probably need both.
0:15:32 Okay.
0:15:36 So it depends on, if the model is only top down,
0:15:37 you probably need only field sales
0:15:39 and you’re selling into large enterprises.
0:15:41 But if a model is this kind of a land and expand,
0:15:43 you want to do the land through inside sales
0:15:47 and you want to do the large, the expense with field sales.
0:15:49 Yeah, and offline, we are seeing scenarios
0:15:51 in which once you go to the top,
0:15:53 and if there are big enterprises,
0:15:56 services has becoming a very important component of it.
0:15:59 To be honest, it bottoms up a developer adoption,
0:16:02 great land, but once you expand and once you get
0:16:06 into multiple portfolios and into complex integrations,
0:16:10 services is essential component of the enterprise sales.
0:16:11 So something that take away on services,
0:16:13 because I’ve always heard and disillusioned me of this,
0:16:14 is that this is not correct,
0:16:17 that services are the things that reduce your margin.
0:16:19 So you don’t want to have too many services
0:16:20 or how do you balance that one?
0:16:24 It reduces your margin is from the perspective of you as a vendor.
0:16:26 But a thing from the perspective of a customer,
0:16:28 like if they spend a million dollars on your product
0:16:30 and they’re not getting the value of a million dollars
0:16:32 because they didn’t have enough,
0:16:34 the right people in place to implement your product,
0:16:37 that’s not good for them and eventually it’s not good for you
0:16:38 because you’re building a,
0:16:40 likely a recurring revenue business in some kind, right?
0:16:43 When we started, we were like, we’re not going to sell services,
0:16:44 not from a margin perspective,
0:16:46 because we wanted our product to be easy enough
0:16:47 that no one needs any services.
0:16:50 And that was true for a long period.
0:16:53 Actually, for the first four years, we had zero services.
0:16:55 And then we started getting into larger and larger enterprises
0:16:56 and larger and larger deals
0:16:58 where people were spending millions of dollars with us.
0:16:59 Yeah, you want to save that money.
0:17:03 Yes, and we figured out, if they don’t buy any services,
0:17:05 sometimes no fault of our product,
0:17:07 they just don’t get that option that we want.
0:17:10 So we were like, yes, too much services,
0:17:12 then the margins are low, right?
0:17:15 But we found the right balance was about 10 to 15%.
0:17:17 So if in our products, if people are buying,
0:17:20 let’s say they’re spending a million dollars with us on the software
0:17:24 and they spend like $100,000 or 10 to 15% on it,
0:17:27 on services, their adoption is much better and much faster.
0:17:29 So ideally, you actually make more money on the upsells
0:17:31 and cross-sells and more feature expansion
0:17:33 based off that 10 to 15%.
0:17:36 Eventually, if your users are getting an option
0:17:38 and happy with the product, the money will come.
0:17:40 The margins will come, right?
0:17:43 So you have to figure out if people are getting value or adoption or not.
0:17:45 Margin’s will come, I like that phrase.
0:17:50 If you think about in that example, let’s say services in that case
0:17:56 leads the buyer to purchase a million dollars of license,
0:18:00 the blended margin on that is extremely high,
0:18:05 much higher than it would be on a $20,000 no services deal, right?
0:18:08 So while services from a unit economic standpoint may be,
0:18:12 you know, a little more expensive from a margin standpoint,
0:18:16 if it drives very large deals with software margins,
0:18:18 you come out way ahead.
0:18:20 So you have to think about blended margin
0:18:23 and the idea that services are often a leader
0:18:29 into a company buying the million dollar, two million dollar license.
0:18:31 It’s just expected as part of that.
0:18:34 And the renewals, like, you know, the year two, year three,
0:18:37 year four renewal offer, like, so if you spend, if, you know,
0:18:39 for the first year because you sold services,
0:18:40 your margin may be lower.
0:18:43 But the, because of services, that option is higher.
0:18:45 So your chances of renewing in year two, year three,
0:18:46 year four, year five are much higher.
0:18:48 So the margins for those will go up.
0:18:51 At the end of the day, adoption is what it counts for a product, right?
0:18:52 And services help.
0:18:54 And also keeping aside the financial aspect,
0:18:59 even from a product aspect, it’s good in the sense that we hate shelfware.
0:19:02 What good is it if some enterprise bought one million?
0:19:03 And if they’re not using it.
0:19:05 Just sitting on the shelf, right?
0:19:07 It’s really bad from a product standpoint.
0:19:12 There are lots of these minor features which are custom.
0:19:14 They, they don’t fit in the product.
0:19:16 They actually fit well for the services.
0:19:20 So that’s why having a good combination of what’s going into the product
0:19:22 versus what should we be left in the services.
0:19:26 That’s a good play for the product manager or the CEO to make that call.
0:19:28 So that the product adoption goes well.
0:19:31 Adoption and the product services isn’t necessary.
0:19:33 It goes hand in hand.
0:19:34 That’s like, I’m really glad you’re about that up
0:19:37 because I want to segue to talking about the company building side of this.
0:19:39 So you’re describing the sales motion to customers
0:19:42 and the product market fit, pre-product market,
0:19:44 pre-product market sales fit and post.
0:19:47 Now, how, let’s spend the rest of the time
0:19:49 connecting it back to what happens inside the company.
0:19:50 So you’re describing the product.
0:19:52 How does this affect the product roadmap?
0:19:54 Like when you get all this feedback from customers
0:19:57 and you have the sales motion in place,
0:20:00 how does this then drive back inside your company
0:20:02 to further developing more features on the product,
0:20:04 making those balancing decisions
0:20:07 for what goes into the core, to what goes into the custom,
0:20:09 to what goes into the next iteration.
0:20:11 Kind of tell us about those trade-offs.
0:20:15 It depends on a different stage of the company.
0:20:18 When you’re in the very, very early stage of building the V1 product,
0:20:20 you really want to use the customer feedback
0:20:23 to figure out what you want to build that will sell.
0:20:26 That will get your first 10 customers, first 20 customers or so.
0:20:28 And you have to listen to customers.
0:20:30 That’s the product market fit exercise,
0:20:32 the customer validation exercise and all that, right?
0:20:34 Are they paying for this thing too?
0:20:35 Yes, and once you have customers,
0:20:42 like how you prioritize becomes what you’re hearing from customers,
0:20:43 what will it take them to be successful
0:20:46 and adopt the product more and buy the product more.
0:20:49 And you want to make sure that as the product teams,
0:20:51 ears are open, listening to customers,
0:20:53 listening to customer support, customer success.
0:20:54 They are watching the tickets.
0:20:57 They are watching what’s working, what’s not working.
0:21:01 Then sales is trying to expand and get more customers.
0:21:02 So you have to work with them as well
0:21:04 because they are competitive pressures.
0:21:08 You have to catch up to competitors on some features sometimes.
0:21:10 And so you have to make sure you’re winning enough in the market.
0:21:13 You can get enough revenue and you prioritize that also.
0:21:14 And but then there’s the third part,
0:21:16 which is you also want to keep expanding your product,
0:21:19 which are things that your current customers are not asking for,
0:21:24 but you need them for expanding your addressable market for customers, right?
0:21:28 And that’s where it’s from a product perspective.
0:21:29 It’s a balance of those three things.
0:21:34 Right? It’s what do we need to win more revenue today?
0:21:37 What do we need to keep our customers happy?
0:21:40 And what do we need to win more revenue two years from now?
0:21:43 So win and keep now to what do you need in the future to win?
0:21:46 Yes. And the rule of thumb that I followed there
0:21:47 was two-third of our engineering investment
0:21:50 should go with our existing TAM.
0:21:51 The core base.
0:21:53 And the one-third of our engineering investment
0:21:55 we should keep putting on expanding our TAM always.
0:21:57 So our total addressable market.
0:21:59 Right? So when we started with like our initial V1 product
0:22:02 was application monitoring for Java applications.
0:22:03 And that was our TAM.
0:22:06 Once we had that, we’ll start putting one-third of our engineering
0:22:09 on expanding it to the next adjacent market,
0:22:11 which is application monitoring for dotnet applications.
0:22:16 After a year, that became part, our product became Java and dotnet.
0:22:18 Now we look at what is the next adjacent market
0:22:20 where I can put another one-third of my engineering.
0:22:23 And then we kept doing it systematically for seven, eight years
0:22:26 and we just kept expanding our TAM.
0:22:27 So the two-third, one-third rule.
0:22:30 Yeah. But the interesting aspect even during that expansion
0:22:35 is that the target buyer, because he already,
0:22:38 we had an existing sales motion target buyer and user,
0:22:41 we didn’t change that drastically
0:22:44 because the sales motion is already oriented towards it.
0:22:47 So it’s like those agencies be dotnet
0:22:49 or the end user monitoring and so on and so forth.
0:22:52 Still, it’s targeting the same buyer and user
0:22:56 so that you can leverage your existing go-to-market sales motion.
0:23:00 That didn’t cause too much of distractions on the go-to-market side
0:23:03 that really helped expand your product portfolio.
0:23:06 But at the same time, leverage your existing sales motion
0:23:08 to go and attack and expand the market.
0:23:11 So understanding that if you change both product
0:23:13 and also your sales motion suddenly,
0:23:16 then it’s almost like again building from scratch
0:23:18 and that causes lots of disruptions in the company.
0:23:20 That’s exactly right.
0:23:23 I mean, if I go back to the sales videos that I did,
0:23:27 there was a concept in there called the sales learning curve,
0:23:30 which says that at different stages
0:23:32 of building out a sales organization,
0:23:34 there’s different people you need.
0:23:37 When a new product comes out inside a company,
0:23:41 you often need to start a new sales learning curve.
0:23:44 It’s not just the old one that you follow,
0:23:46 but you may have a new customer,
0:23:49 it may be a new market motion, whatever.
0:23:52 And the old organization may not be kept
0:23:54 because they’re at a mature level
0:23:56 of selling an existing product.
0:23:58 And now you start out with a different product.
0:24:01 You may have to have the evangelist sales person
0:24:05 start that new sales motion
0:24:08 and not have the bigger sales organization
0:24:10 take on that product in a new market.
0:24:12 They may not be able to do it.
0:24:14 And a lot of companies fail at that because they assume
0:24:18 just because they have scaled with one product line
0:24:20 that they can introduce another one,
0:24:22 let’s say for a completely different market in there,
0:24:24 and nothing happens, right?
0:24:28 And we learned that at AppDynamics in the hard way.
0:24:29 Yeah, I was a hard way.
0:24:31 A lot of companies do.
0:24:32 Yeah, because we built our first product
0:24:34 and it was selling and the sales process was mature.
0:24:36 We have a mature sales organization.
0:24:38 Now we started building our second product
0:24:40 and said, “If we have a mature sales organization,
0:24:42 let’s give them the second product to sell.”
0:24:45 They started selling the second product and they failed at it.
0:24:47 And I was like, “These people are so good in selling,
0:24:48 they’re just being so successful in it.”
0:24:51 But the challenge is when you have 100 customers
0:24:52 and you have 50 references
0:24:56 and you are in the magic quadrant for something
0:24:57 and everything is well refined
0:24:59 and how you sell is different than
0:25:01 when you’re a brand new product with zero customers.
0:25:04 So they just started struggling
0:25:05 and they say, “Your product sucks
0:25:06 and this new product is not good,
0:25:07 so we should throw this away.
0:25:08 We should not build any new product.”
0:25:10 And I was like, “If you’re not going to build new products,
0:25:11 our growth will slow down,
0:25:13 so we have to learn how to make, sell it.”
0:25:14 So we internally structured,
0:25:17 it’s like if we were good at selling a new product,
0:25:18 so what changed?
0:25:20 So maybe we should build a model
0:25:25 which used the same thing that worked for the very first product.
0:25:27 So we reorganize ourselves in a model
0:25:28 like all startups within startup.
0:25:29 So like we are a startup,
0:25:31 but we’ll form new startups inside it
0:25:34 and we’ll sell the same way, the way we sold our first product
0:25:35 in the beginning.
0:25:38 This is a well-known problem.
0:25:40 Often the second product never takes off
0:25:44 because it doesn’t get the visibility or attention
0:25:47 or expertise that’s required
0:25:49 when a new product is released.
0:25:51 And there’s a sales compensation aspect to it also.
0:25:51 Absolutely.
0:25:52 Because the sales people,
0:25:54 they can sell the mature product
0:25:57 and it’s just easy to sell at that point
0:25:59 and make their numbers by doing it.
0:26:00 Now you give them something,
0:26:02 a new product which is much harder to sell.
0:26:03 Because you’re not going to make your numbers.
0:26:05 So how did you adjust the compensation accordingly?
0:26:08 So you almost have to create a separate,
0:26:11 almost evangelical new sales team
0:26:12 just like you do in the beginning.
0:26:14 Just like you start out.
0:26:16 You don’t even know what the productivity is.
0:26:18 You don’t know a lot of things.
0:26:20 And you learn that across that new product line
0:26:23 just like you would do at the start of a company.
0:26:24 So this connects the dots
0:26:26 between the idea of a startup and a startup,
0:26:29 the evangelicals or evangelism that you mentioned
0:26:31 and the different sales learning curve for each.
0:26:32 They’re kind of all the same thing.
0:26:33 That makes a lot of sense.
0:26:34 I mean, quite frankly,
0:26:36 the analogy that came to mind for me
0:26:38 as an ex-developmental psychologist
0:26:40 is that when you’re doing some kind of a research study,
0:26:43 you can never know the effect of variable X
0:26:45 if you’re manipulating too many variables at the same time.
0:26:47 What you’re really describing is isolating one variable
0:26:49 in order to diagnose what problem
0:26:52 so you can then sell in this case that is a solution.
0:26:54 However, it’s expensive to go do that,
0:26:56 to have a startup within a startup.
0:26:58 Like here I have my sales organization,
0:27:01 now I have to go hire more sales people
0:27:03 that are different than the ones I already have
0:27:05 to go sell this new thing.
0:27:07 And at what point do you say,
0:27:09 okay, we have to, for every new product,
0:27:10 do you have a new sales force?
0:27:11 Well, what’s the answer?
0:27:12 I’m asking you guys.
0:27:15 Well, I’ll tell you what we did.
0:27:17 So what I broke into AppDynamics
0:27:20 was that we said the sales learning covers three phases.
0:27:23 One is my first 25 customers for the product.
0:27:25 25 to, that’s like phase one,
0:27:27 which is very, very, almost the founders are selling.
0:27:28 We call that the initiation phase.
0:27:30 Yes, there’s the 25 to 100 customers.
0:27:32 And then after 100 customers is a mature product
0:27:33 we can, our sales force can sell.
0:27:35 That’s the execution phase.
0:27:38 So for the first 25 customers for the new products,
0:27:40 we actually got the product management team
0:27:43 to really sell it the way your founders will sell
0:27:45 in the brand new startup,
0:27:47 instead of hiring a new sales force for that.
0:27:50 But after that, our sales force could take it.
0:27:51 The phase two, they could take it.
0:27:53 The phase three, they were good at it anyways.
0:27:54 So for our fourth product line,
0:27:56 which we call real-time business monitoring,
0:27:58 this is exactly what we observed.
0:28:01 The existing sales force was a lot more tuned
0:28:02 to selling the existing product
0:28:04 because it was well-trodden path.
0:28:05 For the fourth one,
0:28:08 we literally constituted what we call a SWAT team.
0:28:10 It constituted the product management.
0:28:12 Couple of engineers, the best sales engineers,
0:28:14 and one solution architect.
0:28:17 We literally went and sold some of the top deals
0:28:19 and created the sales enablement material,
0:28:21 the market positioning.
0:28:24 And in fact, once we created that,
0:28:27 then we used it to train the rest of the sales force,
0:28:28 even not everyone.
0:28:31 And once we hit that first 10 sales people,
0:28:32 they are cracking it.
0:28:34 They are making more money with better incentives.
0:28:36 Then the rest of the sales force is like,
0:28:38 “Oh, there is something big there
0:28:40 that I also need to sell.”
0:28:41 So we had to do it in stages,
0:28:45 but we literally did a SWAT motion for like eight months.
0:28:46 It’s kind of like a flywheel.
0:28:47 You have to get it going.
0:28:50 And once it has some momentum behind it,
0:28:52 everyone picks up on it.
0:28:57 I would also say that as the regular sales organization
0:29:00 starts to sell this new product,
0:29:02 as managers, you want to make a big deal about it, right?
0:29:05 You want to promote it and say,
0:29:07 “Hey, did you know in the East region,
0:29:09 we just sold new product X?”
0:29:15 And it was for $150,000 or $1 million or whatever.
0:29:17 And that gets everyone excited,
0:29:19 especially if it comes from the CEO.
0:29:23 Salespeople, I mean, everyone loves to be recognized
0:29:24 for their success.
0:29:26 And if it’s important to the company,
0:29:28 then doing something as simple as that
0:29:30 from a leadership standpoint
0:29:33 also has a very beneficial upside
0:29:36 for all the other people who want to get that recognition.
0:29:38 It’s an easy thing to do,
0:29:42 but you often may forget about it or whatever as a CEO.
0:29:43 Yeah, literally what Peter said.
0:29:45 Once we did this SWAT motion
0:29:48 and created those initial amazing sales,
0:29:50 the big dollar sales upwards of million and so on,
0:29:53 literally we did internal sales.
0:29:55 We had to sell to the rest of the salespeople.
0:29:57 We got our CRO, CEO.
0:29:59 They literally are the brand ambassadors
0:30:00 of this new product and say,
0:30:01 “The message is simple.
0:30:05 The best new product you can sell higher,
0:30:08 more in the short time and make more money.”
0:30:11 For our annual sales kickoff,
0:30:14 that’s a big message and we got our customers in there
0:30:16 and we got the best selling sales reps
0:30:19 and the rest of the sales team sees and…
0:30:20 They want to get on board.
0:30:22 Exactly. I want to get on to the train.
0:30:24 One of the things that I have seen
0:30:28 on the negative side of this
0:30:30 is companies release too many products.
0:30:33 And so then every week,
0:30:36 a new product manager is out there trying to…
0:30:37 Rally the team.
0:30:39 They are rallying the team around this head.
0:30:42 So it’s very important to make sure you’re focused
0:30:45 on a few things that are really going to work well
0:30:47 and don’t let it, from a leadership standpoint,
0:30:48 get out of control.
0:30:51 Like it’s great for people to try experiments and all that,
0:30:52 but don’t let it get mainstream
0:30:54 until you know it’s going to be mainstream.
0:30:57 Otherwise, there’s 50 products on the price list
0:30:59 and everyone’s fighting for visibility.
0:31:00 And it becomes very distracting.
0:31:01 Very distracting.
0:31:02 Because the sales force is expensive.
0:31:05 So if you take your sales force that’s doing
0:31:08 and you try to give them too many immature products to sell,
0:31:10 you’re reducing their productivity.
0:31:11 Your expense goes up.
0:31:11 It’s not good.
0:31:14 So you do want to get to that level of maturity
0:31:16 before you give it out to your broader sales force.
0:31:16 Right.
0:31:18 So tell me though, as a leader of the company then,
0:31:20 because you have these processes inside,
0:31:22 I’m hearing the broader context
0:31:24 of the trade-offs of both approaches.
0:31:25 How did you strike the balance
0:31:26 and figure out what to focus on
0:31:29 and then what to sort of keep off the list?
0:31:31 I mean, you have a lot of interesting rules of thumb so far.
0:31:33 Steve Jobs and the Walter Isis and Biography
0:31:36 have made the entire team list all the best things
0:31:37 that they were learning that they could do
0:31:39 and then they crossed everything else off the list,
0:31:40 except for the first, top three.
0:31:41 Like what was your process for that?
0:31:44 Our process, I would say, as a startup,
0:31:47 most of it in our case came from that 2/3/1/3 rule.
0:31:49 Like 1/3 of our engineering investment
0:31:52 we can put on expanding our addressable market.
0:31:56 Now 2/3 we put on serving our currently addressable market,
0:31:58 which is like improving the product,
0:31:59 adding features, capabilities, all of that.
0:32:03 And 1/3 we improve on new use cases,
0:32:06 new adjacent markets, new adjacent users
0:32:08 that we are currently not serving.
0:32:10 So whatever will fit into that will define that.
0:32:13 Another system that we use is working backwards
0:32:14 from a longer-term goal.
0:32:18 We put in this plan called our path to 100 million revenue.
0:32:20 And when we say, okay, we want to get to 100 million revenue
0:32:22 and how would our business look like
0:32:25 and how much we can do at a fast pace
0:32:27 with our existing products
0:32:30 and what we would need to add to the new products to get there.
0:32:32 And then we also have sort of a rough timeline with it.
0:32:34 But that’s once we got there,
0:32:35 we put a new plan together,
0:32:37 which is our path to a billion dollars of revenue.
0:32:38 So which was like, okay, from 100 million to,
0:32:41 if we want to get to a billion dollars of revenue,
0:32:42 what would our business look like?
0:32:44 And we realized when we did that math,
0:32:47 and this is again a rough math, you never know,
0:32:48 that if we want to get to a billion dollars of revenue
0:32:51 from 100 million in like seven years, let’s say,
0:32:53 or six years, our plan was,
0:32:55 we need to have at least 40% of our revenue
0:32:57 coming from these new adjacent products.
0:33:00 Otherwise, our growth would not get there.
0:33:02 And then we have to build this, like that’s,
0:33:04 so there was the part of like what you can do
0:33:06 from a bottom up investment perspective,
0:33:07 like engineering resources
0:33:10 and what you need top down to get to a billion dollar revenue.
0:33:13 – Right, it’s working backward to provide the focus.
0:33:14 – And you need to do both, you know,
0:33:17 and find the intersection of like what you can do bottom up,
0:33:18 you can’t build 10 new products.
0:33:20 So you, what you can build,
0:33:23 and then what you need to build to get to a,
0:33:25 some kind of revenue, long term goal you have.
0:33:27 – And at that point in time is probably when
0:33:31 you start to have a M&A function in the company
0:33:35 to start looking at outside, you know, you have, well,
0:33:36 you have organic growth,
0:33:39 which is using your team to go build
0:33:41 whatever needs to be built.
0:33:42 And then you have an organic growth,
0:33:47 which is basically buying or licensing technology and teams
0:33:49 that are not inside the company.
0:33:51 Because I would argue if AppDynamics
0:33:54 was growing to be a billion dollar company
0:33:56 and you had the capacity to support
0:33:58 from an engineering standpoint,
0:34:01 two or $300 million of product design,
0:34:03 how are you going to build 10 new products
0:34:07 if that was the envelope that, or even three products?
0:34:07 – Right, right.
0:34:12 – So at that point in time, it’s a build versus buy.
0:34:14 Do you raise more money and go build a team
0:34:15 to go build something,
0:34:18 or do you go buy something and integrate it in
0:34:20 and both have their challenges.
0:34:22 But that’s another function inside the company
0:34:24 that usually comes about that point in time.
0:34:26 – Like you acquired three small companies,
0:34:28 you know, as we did that for different things,
0:34:30 but sometimes it’s like just accelerating the time too.
0:34:31 – Exactly.
0:34:33 – It seems like it comes down to speed to market
0:34:34 and what the competitors are doing.
0:34:35 – Yes, like if you build from scratch,
0:34:37 like, you know, from zero lines of code,
0:34:39 it would have taken us two to three years
0:34:42 to get a reasonable product in the market.
0:34:43 You know, by the time we matured it
0:34:46 and found the product market sales fit of it and all that.
0:34:47 But if you acquired something,
0:34:50 we probably could have cut it down from two or three years
0:34:51 to half of it, right?
0:34:55 So, or maybe like, you know, maybe even 75% in some cases.
0:34:57 So that’s always a factor.
0:34:59 – Okay, so why don’t we then just talk a little bit
0:35:00 about pricing and packaging
0:35:02 because that’s such an interesting subset of this.
0:35:06 So we’ve so far talked about the product market sales fit,
0:35:08 the go-to market and the product as a part of that obviously
0:35:10 because those are the two things you need.
0:35:12 How does pricing and packaging come into this?
0:35:13 Because that’s a really top of mind question
0:35:15 for a lot of founders.
0:35:17 – Pricing and packaging is a complex thing.
0:35:20 Pricing is probably more complex than packaging in some ways.
0:35:24 I look at pricing as more a function
0:35:26 of what is the business value.
0:35:28 If someone buys your product, is it worth $50,000?
0:35:29 Is it worth $100,000?
0:35:31 Is it worth $300,000?
0:35:33 What would, how would people justify?
0:35:35 So that’s definitely one function.
0:35:38 Second is like, you know, the rule that I’ve used for pricing is
0:35:40 can your sales people describe it simply?
0:35:42 Like if a customer is going to ask you a simple question,
0:35:44 so how do you price your product?
0:35:46 And if you can’t describe it in half a sentence,
0:35:49 that’s, you have two complexes for pricing.
0:35:51 And yes, there could be like nuances to it
0:35:54 and there could be like details to it,
0:35:55 but you have to be able to describe it.
0:35:56 Like in AppDynamics,
0:35:59 we are monitoring all kind of different systems, right?
0:36:00 So the pricing was complicated,
0:36:03 but we said, okay, the simple pricing philosophy
0:36:04 that our sales people can tell is,
0:36:08 we price by how many production systems you have.
0:36:10 And that was kind of a rough unit of pricing.
0:36:12 And we can measure production systems in different ways,
0:36:14 but that’s how we price it, right?
0:36:16 So, and that’s, it’s at least simpler
0:36:18 that your pricing philosophy is simpler for people.
0:36:20 So that was my rule number one.
0:36:21 The rule number two there was
0:36:23 that whatever the pricing is measurable,
0:36:24 because if it’s not measurable,
0:36:25 and now the customer says, okay,
0:36:26 how many license I need to buy?
0:36:29 Our sales people cannot even tell them very clearly,
0:36:31 like, okay, this is how you measure how many you need to buy.
0:36:34 However, it will create a lot of friction.
0:36:36 Or like once they buy it,
0:36:37 we can’t measure and practice, like, you know,
0:36:39 how many they’re using it.
0:36:40 That’s a problem as well, right?
0:36:43 So if we can describe our pricing in half a sentence,
0:36:44 that’s one.
0:36:47 Second is it’s measurable that people can measure presale
0:36:49 and people can measure post-sale?
0:36:50 We have a good pricing system.
0:36:53 The question after that is, okay,
0:36:56 what is the price, like the dollar price of it,
0:36:59 for that model, per license, how much you pay?
0:37:02 That ideally, to me, it comes down to business value.
0:37:04 And enterprise software,
0:37:06 especially a selling to large enterprise,
0:37:09 I argue to most founders is that you should price
0:37:10 more than you think you should.
0:37:12 Oh, we always say raise prices.
0:37:13 That’s our mantra around here.
0:37:14 Exactly. So price higher.
0:37:15 You can always discount.
0:37:17 If there’s not value, you can always discount.
0:37:18 And customers are not going to pay more than what the thing
0:37:20 they should pay anyways.
0:37:22 So you can always discount and then go there
0:37:23 instead of pricing low.
0:37:27 I love the idea of this pricing framework.
0:37:30 A lot of companies try to come up with a new model of pricing.
0:37:35 So instead of price per user or price per application,
0:37:40 it’s price for the number of, you know, air vents your server has,
0:37:40 right?
0:37:44 Let’s just say you have to come up with pricing
0:37:47 that the customers used to actually paying for.
0:37:50 If you start to create something that’s totally new,
0:37:51 it creates friction in the system.
0:37:54 So it’s, you know, typically users or capacity
0:37:56 or numbers of something.
0:37:58 I love the measurable piece.
0:38:01 A lot of companies try to get overly cute
0:38:02 and it gets overly complicated.
0:38:05 And then salespeople can’t explain it.
0:38:06 And even if it’s simple,
0:38:11 if it’s not understandable by the buyer,
0:38:13 they’re going to be like, well, we don’t, you know,
0:38:14 like, what does that mean?
0:38:16 So I’m hearing you say founders out there,
0:38:17 be creative with your product,
0:38:19 but don’t get creative with pricing.
0:38:20 Like do what you need to do.
0:38:21 That makes sense to the buyers.
0:38:22 Yeah, exactly.
0:38:26 There’s difference between consumer purchase versus enterprise.
0:38:28 Enterprises, they need a little bit more certainty.
0:38:30 You’re getting it from a budget, right?
0:38:32 They’re already preplanned.
0:38:35 That’s one and they want certainty in the sense that,
0:38:39 oh, is it a one alert or thousand alerts?
0:38:40 And if it’s two variables,
0:38:42 then suddenly if it blows up budget,
0:38:43 he cannot manage it.
0:38:45 So that’s why they’ve won that certainty
0:38:47 and visibility into that pricing.
0:38:49 So by certainty, you mean they don’t want surprises.
0:38:49 Exactly.
0:38:53 They need to be able to be reasonably predictable on this
0:38:56 to not have surprises at the end to say, well, it’s free.
0:38:58 And then we’ll measure it in the future,
0:39:00 but they don’t know how to budget for it.
0:39:01 How do you as a founder know
0:39:02 that you’re not leaving value on the table
0:39:05 when you’re giving that certainty or like surety,
0:39:06 that this is what you’re going to get?
0:39:10 If you put in like the good other way process in your,
0:39:11 as part of your sales process,
0:39:15 that’s how you guarantee you’re not leaving money on the table.
0:39:17 We had a very structured sales process.
0:39:18 And in the sales process,
0:39:19 we would look at like, you know,
0:39:22 what is your current state of doing this?
0:39:24 How much is it costing you roughly, let’s say?
0:39:27 What would be a new state with AppDynamics
0:39:28 and what would that cost you
0:39:29 and how much money are you going to save?
0:39:32 And then price is a little bit of a function of,
0:39:33 you know, how much money are you going to save
0:39:34 and what’s your other way?
0:39:37 And that’s, you know, if we are charging more
0:39:38 than what’s going to save them,
0:39:40 they’re not going to pay for it anyways, right?
0:39:42 Most companies, I see the mistake of like,
0:39:44 you know, especially you’re selling into large enterprise
0:39:46 and you’re asking for, you know,
0:39:48 half a million dollars to someone.
0:39:50 You don’t back it up by a business case.
0:39:51 People are not going to pay you.
0:39:52 And then you leave a lot of money on the table.
0:39:54 If your business case is strong,
0:39:56 you would not leave money on the table.
0:39:59 Yeah. We had a process called Business Value Assessment, BVA.
0:40:01 It went along with the sales process
0:40:04 in which we always had that premium positioning.
0:40:09 And we enabled our sales to convey why we are premium.
0:40:13 And secondly, we had those steering committee meetings
0:40:15 in which the big check pair,
0:40:20 we literally read out the ROI value use cases back to them
0:40:22 so that they can justify internally
0:40:24 as to why they are paying that premium.
0:40:28 So giving that message so that they can repeat internally
0:40:31 and justify it, that’s what helps the part of the process
0:40:33 and the premium that we can extract from this.
0:40:36 So what I’m hearing you say is that sales enablement created,
0:40:39 it smoothed the road, kind of greased the wheels for you.
0:40:41 But then on top of it, you played back
0:40:42 and made sure to play back the ROI
0:40:46 so that then your internal champion could continue advocating
0:40:49 that just has value and keep moving that forward.
0:40:52 One question I have is the third element
0:40:55 you mentioned, Jyothi, in your framework, the value.
0:40:57 That’s the big kind of gray, goosey area
0:40:59 because that’s the least measurable one.
0:41:01 How do you know the value to the customer?
0:41:04 Did you just say the simple opportunity cost
0:41:05 if their systems went down?
0:41:07 Or did you think bigger than that?
0:41:08 How did you figure that out?
0:41:10 You know, the best way is to ask the customers.
0:41:15 And this is something I would do in the product market fit phase.
0:41:16 You don’t have, you know, a lot of people say,
0:41:18 “What is product market fit?”
0:41:19 Even the initial one.
0:41:20 It’s a very philosophical question.
0:41:21 What is product market fit?
0:41:24 In such a vague question, my simple definition is if you can,
0:41:27 if you understand the business value of your product,
0:41:28 that’s when you know.
0:41:30 And so, you know, the question that I used to ask
0:41:32 in the product market fit phase was,
0:41:35 how would you justify the business case to your boss?
0:41:38 So, like, I’m talking to, say, a director of DevOps,
0:41:40 I’ll say, “Okay, how would you make the business case
0:41:42 to your boss if you have to buy Abdynamics?”
0:41:44 And he’ll say, “We had one outage a month.
0:41:46 Every time we have an outage, you put six engineers there
0:41:47 and this is how much it costs us.
0:41:49 And because our users have bad experience,
0:41:51 we lose this revenue, this is how much it costs us.”
0:41:53 And once I start hearing it,
0:41:55 I know, like, this is what I would,
0:41:56 I would like to teach our sales force
0:41:57 how to make the business case
0:41:59 because this is how the customers are articulating.
0:42:01 And unless you understand the business case,
0:42:04 you don’t really have a product market fit.
0:42:06 You know, it’s because that’s what you have
0:42:07 to engineer your product around.
0:42:09 Right. So you’re saying the value is defined by the customers.
0:42:11 Do you guys have any thoughts on how to define the value?
0:42:14 That sort of loosey-goosey vague thing of,
0:42:16 you want to make sure you’re selling value?
0:42:18 You know, there’s a couple of things which I’ve used
0:42:20 in companies that I’ve run as,
0:42:22 if you look at competitive products,
0:42:24 what are they, what’s the chart, you know,
0:42:25 how much do those cost?
0:42:28 There’s an overall stack of technology.
0:42:30 And if you’re providing a certain solution,
0:42:32 what is that stack in general?
0:42:34 How do people, how have they budgeted for that?
0:42:39 And then I always like this concept of charge
0:42:40 more than you think in there.
0:42:42 And you can always discount back
0:42:47 to make sure that you’re not really leaving value on the table.
0:42:48 I didn’t say money.
0:42:49 I said value on the table,
0:42:51 which I think is very important.
0:42:55 You know, the thing that is also I learned along the way
0:42:58 is customers actually like to spend money for value.
0:43:00 It’s not a problem we all do, right?
0:43:03 Even as consumers, it’s not a problem.
0:43:05 And to come in with the low cost,
0:43:09 like if your value is lower cost or whatever,
0:43:14 that tends to be as soft as not standing up
0:43:16 for the value that you’re actually producing.
0:43:19 And if you have the proper go-to-market,
0:43:20 you have the proper product,
0:43:22 and you have the proper positioning,
0:43:28 then you can basically get the maximum dollars
0:43:29 that customers are willing to pay.
0:43:32 And everyone feels like it’s a very fair transaction
0:43:35 that the value being delivered to the customer
0:43:38 is very reflective of the price that they pay.
0:43:39 I think that the fair part is important.
0:43:40 Customer feel is fair,
0:43:43 and you have to help them feel it’s fair also
0:43:44 by making that case.
0:43:45 Yes, the competitive dynamic
0:43:47 will also describe some of the price.
0:43:49 If your competitor is selling for much cheaper,
0:43:51 there may be some pressure on you
0:43:53 to sell for that price as well, right?
0:43:56 But in amdonomics, we had a bit of that challenge.
0:43:59 One of our primary competitors was price much lower than us.
0:44:00 And they were designed more for SMB.
0:44:03 Their product wasn’t as strong as ours for enterprise.
0:44:05 And so internally, sometimes people will come in,
0:44:08 “Hey, our competitor is charging much lower.
0:44:10 Shouldn’t we decrease our price also?”
0:44:11 And I’ll tell them,
0:44:13 “Okay, do we really believe our product is superior?
0:44:16 If our product is really superior,
0:44:17 why would we not charge higher?”
0:44:18 So we’ve made a rule
0:44:20 that we can always charge higher than them.
0:44:20 We actually said-
0:44:23 So you existed the downward pricing pressure.
0:44:25 Yes, because if our product is superior,
0:44:28 we are, the customer is getting superior value.
0:44:29 Either we are lying about it
0:44:32 or we are misguided about it or whatever.
0:44:34 That we believe it is, but it’s not.
0:44:36 Or we are not articulating the superior value.
0:44:37 That’s our problem.
0:44:38 If our product has superior value
0:44:41 and we know how to articulate and make the case about it,
0:44:43 why won’t we charge superior than them?
0:44:45 And we always priced higher than our competitor
0:44:46 because of that.
0:44:48 And people are fine paying for it.
0:44:51 And I think that to further that point,
0:44:54 the articulation of value often comes
0:44:56 with having a sales organization.
0:44:57 That’s what they do.
0:45:00 And so when we often think about,
0:45:02 “Hey, let’s don’t have a sales organization
0:45:04 so we can build more product.”
0:45:05 Often what gets missed
0:45:08 in the whole product adoption cycle
0:45:12 is the idea of selling value into the customer
0:45:16 where value is not necessarily felt
0:45:18 through a self-service product or whatever.
0:45:20 You just can’t see the value
0:45:22 or appreciate the value
0:45:24 until an organization comes in
0:45:26 to actually promote those pieces
0:45:28 that may not be self-evident.
0:45:29 At the end of the day,
0:45:30 it’s all about marketing,
0:45:32 getting products to the market, right?
0:45:35 And for that, you have a classical four-piece.
0:45:37 So product, it doesn’t go in isolation.
0:45:41 Product, the pricing, promotion, and the place.
0:45:43 At the end of the day, it’s the customer.
0:45:45 With an intimate knowledge of the customer
0:45:48 and what exact pain process today
0:45:50 and how you want to change it in the future,
0:45:53 understanding that customer dynamic
0:45:56 literally helps you define these four aspects.
0:45:59 And that’s what a good founder earlier on
0:46:01 or a good product manager
0:46:03 literally defines these metrics
0:46:04 by understanding the customer.
0:46:05 So those four-piece.
0:46:07 Yeah, that’s what a good product manager
0:46:08 should be doing.
0:46:10 I was running the product line,
0:46:12 the new US business IQ product line,
0:46:14 both product and business operations.
0:46:15 Is that an unusual model?
0:46:18 Because you’re an engineer who’s doing product.
0:46:19 Like, what is the ideal way
0:46:22 to essentially architect the product management
0:46:25 or product org functions in this framework?
0:46:26 Are product managers salespeople?
0:46:27 Are they engineers?
0:46:29 Depends on who your audiences are.
0:46:32 To me, the product manager’s first job
0:46:34 is to understand the customer
0:46:35 and the classic definition
0:46:37 being the voice of the customer.
0:46:39 So at DevDynamics, the product was technical.
0:46:42 Our users were engineers in many ways.
0:46:46 So all our product managers had an engineering background.
0:46:47 But if I had a consumer product,
0:46:49 I’m building up a fashion app.
0:46:52 My product manager probably would be very good
0:46:53 in understanding my consumers
0:46:56 as someone who’s experienced in fashion.
0:46:57 For any business I’m doing,
0:46:59 I would hire a product manager
0:47:01 who can understand my end users very well.
0:47:03 So it kind of matches the profile of your target customer.
0:47:04 Exactly.
0:47:07 Did you guys have different product manager profiles, though,
0:47:09 then for the one-third of the organization
0:47:10 that was doing the more evangelical startup
0:47:13 within a startup next product line types
0:47:15 versus the ones that were doing the core?
0:47:17 Because I would imagine those are two different sensibilities
0:47:18 and they might or may or may not transfer.
0:47:22 Yes, I would say the profile is a bit different.
0:47:24 The product managers,
0:47:26 once you have a V1 product kind of going from there,
0:47:27 the profile could be a bit different.
0:47:30 But at that point, you need multiple product managers.
0:47:33 So you still want the product managers
0:47:36 who could go and help create something
0:47:41 disruptively unique, feature-set, etc.
0:47:42 But you also want product managers
0:47:44 who are very good in understanding
0:47:46 the how it’s working out in the market
0:47:49 and what’s the adoption curve
0:47:52 and what’s the pricing working.
0:47:56 So the product management skill set
0:47:58 also has different things to it, right?
0:48:00 What are the qualities to look for?
0:48:02 We typically look for three aspects.
0:48:03 During the initial phases,
0:48:06 the empathy to understand the customer,
0:48:08 to define your product.
0:48:12 And the second aspect is the business aspects of,
0:48:14 okay, how is it going to work with the sales?
0:48:16 So literally, the product managers,
0:48:18 they travel with the salespeople
0:48:21 and understand how do you position that value?
0:48:23 Okay, now how do I price it?
0:48:24 And so on and so forth.
0:48:26 And the third most important thing is execution.
0:48:27 Once you define it,
0:48:30 product doesn’t come out of thin air, right?
0:48:32 You need to work with the engineers,
0:48:34 literally attract your schedules
0:48:37 and really execute it and deliver it to the customers, right?
0:48:38 So these are the three aspects,
0:48:41 the empathy and those business aspects.
0:48:43 And finally, the execution.
0:48:45 So these are the three skill sets
0:48:48 that I typically look for in a very strong product manager.
0:48:51 They’re very creative parts of product management,
0:48:54 then trying to come up with creative solutions
0:48:55 as the second part.
0:48:58 And then scaling the operation behind it,
0:49:01 which is like a machine that can process the requirements
0:49:02 on customers, on sales,
0:49:05 figuring out the right pricing, packaging, all of that, right?
0:49:06 So you want different skills.
0:49:08 Seems like a bit of a unicorn, to be honest.
0:49:10 And many times it’s not just one person, right?
0:49:11 It’s your product management,
0:49:12 then becomes a group as a time.
0:49:14 And you want different people with different,
0:49:17 like that balances out the variety of skills.
0:49:19 You compliment each other’s skills,
0:49:20 and that’s the composition of an ideal team
0:49:23 while you have more than an individual contributor.
0:49:25 Okay, so any parting takeaways,
0:49:27 given your, I’m sure you have a million takeaways, Jyothi,
0:49:29 but any big message for our founders
0:49:31 and other founders out there trying to do this,
0:49:32 whether enterprise or not?
0:49:36 It was a good discussion on the product market sales kind of fit.
0:49:40 But my primary advice I will give to founders listening this is,
0:49:45 don’t overthink too far ahead in many cases as well.
0:49:46 Like, you know, the skills you need to master,
0:49:50 zero to one million dollars of revenue,
0:49:52 find the product market fit, one to ten million dollars,
0:49:55 find the product market sales fit,
0:49:59 iterate on it, let’s say ten to 75 million dollars,
0:50:03 scale the sales organization and go to your go-to-market.
0:50:06 Then 75 million plus is when this,
0:50:07 how do you build our product number two,
0:50:09 and product number three, and product number four starts.
0:50:10 That’s a great framework.
0:50:11 So, you know, anyone listening this,
0:50:13 I don’t want them to like, you know,
0:50:14 when they are in the zero to one million stage,
0:50:17 they’re trying to figure out how to do product number two.
0:50:19 That’s, there’s no point spending time on that.
0:50:21 So the skills that you have to learn in the,
0:50:24 you know, the organizationally, as an organization,
0:50:27 and also as a founder, they change as you go.
0:50:29 And my advice to people,
0:50:32 focus on the thing that you need to learn the most
0:50:35 to get to the next milestone and excel at it,
0:50:38 then worry about the next one when you get there.
0:50:40 That’s a great piece of parting advice,
0:50:42 and it brings us full circle to where we started
0:50:45 in terms of how founders evolve as their companies do.
0:50:46 And that’s a fabulous framework.
0:50:48 Thank you for joining the A6NZ Podcast, Jyoti.
0:50:51 Thank you all for this wonderful conversation.
0:50:51 Thank you Peter.

0:00:03 Hi, and welcome to the A16Z podcast.
0:00:05 This episode is a conversation between Mark Leslie,
0:00:08 former CEO and chairman and founding team member
0:00:10 of Veritas Software and a lecturer
0:00:12 at the Stanford Graduate School of Business
0:00:14 and A16Z general partner, Peter Levine.
0:00:16 In the conversation, which is based on an event
0:00:18 held at Andreessen Horowitz for Veterans,
0:00:21 Peter and Mark talk all about sales and entrepreneurship
0:00:23 from what makes a good salesperson
0:00:25 and how to best incentivize them
0:00:28 to how to build a culture that engenders loyalty and trust.
0:00:30 To learn more about this subject,
0:00:32 check out Peter Levine’s video sales primer
0:00:34 on how technical founders should think about sales
0:00:37 on A16Z’s YouTube channel.
0:00:38 We teach at Stanford together,
0:00:41 we’ve sit on boards together, we’ve worked together,
0:00:43 and so this is one of those occasions
0:00:45 which is super awesome for me to be here
0:00:47 and super awesome to have Mark here.
0:00:51 You often talk about the importance of authenticity
0:00:52 as an entrepreneur.
0:00:54 What do you mean by that?
0:00:57 To me, authenticity in that context
0:01:00 means that the person whose idea it is
0:01:03 and the thing they wanna craft and do
0:01:07 comes from real experience.
0:01:08 That they’re solving a problem
0:01:10 that they personally experience,
0:01:12 that they see their customers experience,
0:01:17 and it has a real kind of substance to it for those people.
0:01:19 There’s a lot of people who are really smart
0:01:20 and look at the world and say,
0:01:23 “I think there’s a problem over there that I can solve.”
0:01:24 I don’t think that’s authentic
0:01:28 and I think that the probability of success is much lower
0:01:29 when you’re trying to solve a problem
0:01:31 that you’ve never personally experienced.
0:01:34 So you have people come from a company
0:01:35 that’s in a similar technology,
0:01:37 they have a network of people,
0:01:41 they have seen the problems that they themselves experience
0:01:42 that are experienced in their company,
0:01:43 the companies or their customers,
0:01:48 and then they say, “Aha, I see something that no one else sees
0:01:49 and it can make a difference
0:01:51 and I can go build a company about that.”
0:01:52 So that’s what authenticity means.
0:01:55 Now, that’s for starting a company.
0:01:57 There’s another word of authenticity
0:02:01 having to do with leadership, separate concepts.
0:02:06 And authenticity in leadership is being a real person,
0:02:08 being comfortable in your own skin,
0:02:12 being willing to admit when you make a mistake publicly
0:02:15 and to take responsibility for that,
0:02:17 and having a human touch.
0:02:19 And it’s a crucial element of success in leadership
0:02:22 is being an authentic person, being a real person,
0:02:25 being someone who doesn’t try to be something they’re not.
0:02:26 They are who they are
0:02:29 and they are kind of internally accepting of that.
0:02:32 – I’m curious, you think this authenticity can be,
0:02:34 is it something that can be taught
0:02:38 or is it innate in people coming into an environment?
0:02:41 Yeah, you talk about it, but how do I know?
0:02:44 Am I authentic or not and can it be taught?
0:02:46 – Yeah, so one of the things I say
0:02:49 is that you can teach an entrepreneur
0:02:51 how to go start and build a company,
0:02:54 but you can’t teach someone to be an entrepreneur
0:02:55 who’s not an entrepreneur,
0:02:57 has to do with an inner drive
0:03:00 and their personal ambitions and desires
0:03:03 and their risk tolerance, their willingness to go
0:03:06 put themselves at risk to accomplish something.
0:03:10 So can you teach someone to be authentic?
0:03:11 I don’t think so.
0:03:14 How they deal with the rest of the world around them
0:03:16 and people and their social interactions
0:03:17 and all the things that go with that
0:03:19 and their business habits,
0:03:22 all those things together describe character.
0:03:25 And I think character, my personal opinion, is as immutable.
0:03:28 I don’t believe that you can change behavior of people.
0:03:31 I think people can change their own behavior
0:03:32 if they’re so motivated,
0:03:34 but that’s a long, hard journey
0:03:36 that people embark on by themselves,
0:03:38 but I don’t think you can beat it into people.
0:03:39 I think they are who they are.
0:03:41 And my view has always been
0:03:42 when you have a bunch of executives
0:03:43 that have different jobs, you say,
0:03:47 well, how can I get the best from each
0:03:50 and amplify their strengths?
0:03:53 And how can I reduce the impact of the problems,
0:03:56 meaning attenuate their weaknesses?
0:03:58 And so I always think of an organization
0:04:00 as having a lot of lines in it
0:04:02 and then the job of the leader of the organization,
0:04:04 it’s to blur the lines
0:04:07 to do that amplification and attenuation.
0:04:11 We often back technical founders or founding teams
0:04:14 that have very little sales expertise,
0:04:18 yet it becomes a critical part of a company.
0:04:20 So how do you think about approaching sales
0:04:22 from the perspective of a founder
0:04:24 who’s never done it before?
0:04:27 So the first thing you have to do
0:04:30 is sell someone on becoming your partner.
0:04:32 Then you have to sell friends and family
0:04:34 on providing you with the seed money.
0:04:36 Then you have to go sell individuals
0:04:40 to give up their career and invest their future in you.
0:04:42 Then you have to go out and raise money
0:04:47 by selling venture capitalists shares for money.
0:04:48 That’s the selling thing.
0:04:49 I’m gonna give you shares
0:04:50 and you’re gonna give me money, right?
0:04:52 So we were selling.
0:04:53 And then you develop your product
0:04:55 and then eventually you go out and meet customers
0:04:57 and you gotta go sell them.
0:04:58 But at this point in time,
0:05:01 there is nobody better equipped in a startup company
0:05:06 to talk about the beauty and the benefits of the product
0:05:09 and the vision of the future that we’re painting for.
0:05:11 There’s nobody better equipped to do that
0:05:14 than the founders who started the company for that reason.
0:05:17 Sales in the very early stages can’t be subcontracted.
0:05:19 Even if you hire a sales person,
0:05:20 they don’t know anything when they get there.
0:05:22 They have to go learn about the product
0:05:24 and the customers and the market and everything like that.
0:05:25 And where does that knowledge comes from?
0:05:28 It comes from the founders and the company.
0:05:31 So one of the things that technical founders,
0:05:33 they’re pretty good usually at the vision thing.
0:05:36 They’re not so good at asking for the order, right?
0:05:39 And in sales, you go spend time,
0:05:40 you tell them about all this stuff and you say,
0:05:43 “So look, I think you guys are interested
0:05:45 “in why don’t we kind of do a deal here, right?”
0:05:47 And make something happen.
0:05:49 They’re not comfortable kind of getting to that point.
0:05:50 So you have to get to that point.
0:05:55 Now, you are gonna sell for the rest of your life
0:05:59 in business, you’re gonna sell your ideas.
0:06:02 The higher up you get, the more opportunities you have
0:06:06 to represent your company and its mission and its ideas
0:06:07 and its product and everything else
0:06:10 in front of important people.
0:06:13 You will be selling all of your life.
0:06:15 When you are a leader of a company,
0:06:17 you define the mission and the vision
0:06:20 and then you evangelize that to the company.
0:06:22 The way you get people to subscribe to it
0:06:24 is you get them excited about it
0:06:26 and that’s another version of selling.
0:06:30 So it’s persuading and yielding from the persuasion
0:06:32 some outcome that has benefit to you
0:06:34 and you’re gonna do it all of your life.
0:06:37 And look, it takes a village to make a company, right?
0:06:39 You gotta have people to do all kinds of things
0:06:42 and it’s fine, but if you wanna go do that,
0:06:45 you better learn how to sell, present, persuade, et cetera.
0:06:47 – Perhaps a follow on question to this
0:06:49 is what makes a great salesperson
0:06:51 and is it a viable on-ramp, let’s say,
0:06:54 into a company joining a sales group
0:06:57 as opposed to marketing or engineering?
0:06:58 – This is a chicken and egg thing, right?
0:07:00 You show up and say, I wanna be a salesperson.
0:07:01 I say, well, what have you sold so far?
0:07:03 – Well, this would be my first time.
0:07:05 You should never be embarrassed about that.
0:07:06 – Everyone’s gotta start somewhere, right?
0:07:07 – Everyone’s gotta start somewhere.
0:07:10 – So I think the way, if you wanna break into sales
0:07:12 and the Valley, I think the place to where there’s
0:07:14 the most tolerance for that is what they call
0:07:16 inside sales, you dial for dollars,
0:07:20 you’re scripted, you have a manager that’s close by.
0:07:22 And what happens to people in inside sales,
0:07:26 the people who show promise and have energy and ambition,
0:07:29 they always get promoted to account executives
0:07:31 that have more responsibility.
0:07:35 So the typical, what they call OTE on target earnings
0:07:40 is today around $300,000, half in base, half in incentive.
0:07:42 And then if you sell more than your quota,
0:07:45 you can make a lot more than your 300K.
0:07:49 And it was always my privilege as a CEO
0:07:51 to bring someone up on the stage and say,
0:07:52 you made more than me this year,
0:07:54 here’s your check for a million dollars.
0:07:57 It’s a very highly paid profession.
0:08:00 So I’ve worked with people who come from an engineering
0:08:02 background and say, well, why does sales people
0:08:03 make so much money?
0:08:06 It doesn’t seem right ’cause engineers are smarter.
0:08:09 And then I say, so do you wanna be a salesperson?
0:08:11 And I say, no.
0:08:12 I say, that’s why they make more money.
0:08:15 (audience laughs)
0:08:17 There’s a large quantity of people out there in the world
0:08:19 that, you know, someone says no to them
0:08:21 and they’re just like crushed.
0:08:23 And if you’re in sales and someone says no,
0:08:25 you just dial the next guy.
0:08:27 – You know, often there’s this interesting perception
0:08:29 between sales and engineering,
0:08:32 that constantly sort of butts heads a little bit,
0:08:35 especially since companies typically are founded
0:08:37 by technical engineers.
0:08:39 And then you bolt, quote unquote,
0:08:41 bolt on a sales organization.
0:08:42 Everyone’s worried about culture
0:08:45 and kind of the changes and all of that.
0:08:46 Eventually everyone gets through it
0:08:49 and you have sort of a normalized kind of situation
0:08:50 where you have sales and engineering
0:08:53 and everyone, you know, mostly works together.
0:08:55 But that’s very typical in the Valley here.
0:08:57 – And one of the jobs of leadership
0:09:00 at that stage in a company is to build the bridges
0:09:01 between those two.
0:09:03 You know, there’s kind of a built in on both sides
0:09:04 and like, huh, who are those guys
0:09:06 and I don’t get them and everything.
0:09:07 And you build bridges.
0:09:11 You tell each one why the other one’s more important, you know.
0:09:13 So one of the big complaints you always get is,
0:09:16 you know, the sales guy say, the product’s late.
0:09:18 I’m a sales guy, I’m accountable.
0:09:19 How come nobody’s accountable?
0:09:22 So my experience with engineering projects
0:09:25 is that they can either be on time,
0:09:30 they can be fully featured or they can be high quality.
0:09:33 I’ve never seen it all come together on the same day.
0:09:36 So over years, I became very zen about the whole thing.
0:09:37 I was like, hey, look, it’ll be ready when it’s ready.
0:09:39 Let’s make sure it’s a great product
0:09:41 and got the features in it and we’ll just, you know,
0:09:43 manage the company around the fact that, you know,
0:09:47 I don’t know if you know about engineering chronology,
0:09:49 engineering time, you know about engineering time.
0:09:53 If an engineer says, we’ll definitely have it by next year,
0:09:55 that means December 32nd.
0:09:58 If they say I’ll have it this quarter,
0:10:00 that means March 32nd.
0:10:03 I mean, it’s the last possible moment of the time.
0:10:05 There’s always a way they kind of do the clock and always.
0:10:07 – For sure.
0:10:09 I was an engineer at Veritas when I started there.
0:10:12 And I had this lunch meeting with Mark.
0:10:13 He doesn’t even remember.
0:10:15 It’s one of those meetings that I remember.
0:10:17 By the way, there are often meetings in your life,
0:10:19 we talk about this a lot,
0:10:22 where you as the recipient of that meeting,
0:10:24 remember it as if it were yesterday
0:10:26 and the person who’s dispensing the advice
0:10:28 doesn’t ever remember that they even had the meeting, right?
0:10:29 That happens a lot.
0:10:33 So we go out to lunch and Mark was talking to me
0:10:34 about what do I want to do in my career?
0:10:37 I said, I wanted to run a company someday.
0:10:38 And he said, you don’t know what you don’t know
0:10:39 about running a company.
0:10:40 You need to know how to manage
0:10:42 and you need to know how to sell.
0:10:45 I was an engineer, didn’t know anything about sales, nothing.
0:10:46 Like I wrote code, that was it.
0:10:49 And I had no idea how money came in,
0:10:51 who was a customer, nothing.
0:10:54 So Mark said, well, why don’t you try sales?
0:10:57 So I’m like, all right, whatever, I’ll try sales.
0:10:59 I had no idea that I could be persistent
0:11:00 or any of this.
0:11:03 And so I would go out and go to all these crazy places
0:11:05 around the world to go get orders.
0:11:06 And I actually got a lot.
0:11:10 And the key was I was more afraid to come back
0:11:12 without an order than to go sit at a customer site.
0:11:15 And Mark would set it up where he would say like,
0:11:17 don’t come back until you have an order.
0:11:18 He didn’t even say, I’ll be really upset.
0:11:21 But I refused to come back because I knew people
0:11:24 would be more upset when I came back
0:11:26 than just sitting there at the customer site.
0:11:28 So I literally, when I would go to customer,
0:11:30 I swear that this is what happened.
0:11:33 Customer would often ask, well, when’s your flight back?
0:11:34 When are you going home?
0:11:36 I’m like, I’m not going back until I get the order.
0:11:37 And I was serious.
0:11:39 I would sit there for weeks.
0:11:42 Every day I’d show up and sit in the cafeteria.
0:11:43 I’d chase people into the bathroom
0:11:46 because I was more afraid to come back
0:11:49 with the wrath of Mark Leslie, like, where’s the order?
0:11:52 So I would just sit there until something happened.
0:11:53 It actually worked.
0:11:54 I mean, that was kind of my–
0:11:56 – So let me tell you, we have the NCR story,
0:11:58 which is like all these stories.
0:12:00 – So we’re at the end of the quarter,
0:12:02 and we’ve got to get this deal done at a–
0:12:03 – South Carolina.
0:12:05 – You know, young new salesman.
0:12:08 And we have this conference call on a Friday afternoon.
0:12:10 He says, yeah, it’s all set up.
0:12:11 We’re getting to the deal, that, out of that.
0:12:13 And I said, like, we don’t have an order here.
0:12:15 Like, I don’t know why you think there is,
0:12:16 but there’s no order here.
0:12:18 So I said, you need to be there Monday morning
0:12:20 when, you know, when business opens over there,
0:12:22 and you need to go and find out what’s going on
0:12:24 ’cause we don’t have an order.
0:12:25 And Wednesday is the end of the quarter.
0:12:27 – So we’re kind of like up against it over here.
0:12:30 – Right, I was gonna fly back to San Francisco on Friday.
0:12:33 – And I said, you can go anywhere you want.
0:12:35 But Monday morning, you gotta be over there,
0:12:37 and don’t come home without the order.
0:12:41 So he’s sitting in the lobby over there, right?
0:12:43 He’s a fixture.
0:12:45 And Monday goes by, no one will see him.
0:12:47 And Tuesday goes by, no one will see him.
0:12:49 And then the VP of sales walks out,
0:12:50 and he goes into the men’s room,
0:12:53 and Peter follows him into the men’s room.
0:12:55 I said, Russ, you’re a sales guy.
0:12:56 You gotta help me, I’m dying over here.
0:12:58 I gotta go see somebody, can you help me?
0:13:00 So he did, and then we got in,
0:13:03 and we closed the quarter successfully, it was great.
0:13:05 And it was a great learning experience for Peter, right?
0:13:06 – Yeah, yeah.
0:13:07 We did this big deal with Microsoft,
0:13:09 and it took months and months and months.
0:13:12 I mean, to where I basically lived in this guy’s office.
0:13:14 Every day, I’d show up and sit in his office
0:13:16 in a white chair.
0:13:17 And as I remember, one of those recline,
0:13:20 kind of 80s reclining chairs.
0:13:22 And I sat there for months, and every day I’d show up,
0:13:25 and I’d be there, get him coffee, whatever,
0:13:27 and he’d kind of shepherd me through, I swear.
0:13:30 And it became such a joke that after we did the deal,
0:13:33 and he left Microsoft, he actually sent me the chair.
0:13:37 Because he said, he said, no one has sat in this chair
0:13:39 more than you have in your entire life.
0:13:42 – Peter was a fearless warrior for the company.
0:13:46 We ran into a very, you know, difficult problem
0:13:48 the quarter after we went public.
0:13:50 And we were kind of stretching for,
0:13:51 where can we get some business?
0:13:54 And it turns out there was an accountant in UK
0:13:57 that was scheduled to do something in the following quarter.
0:13:58 And if we give him a nice discount,
0:14:00 we can bring him into this quarter.
0:14:02 And so we’re sitting in the staff meeting,
0:14:03 the executives, and we call Peter and say,
0:14:05 you know what’s going on, we’re like in trouble, right?
0:14:07 He says, yeah, we were in a lot of trouble,
0:14:09 and it was our first quarter of the public company.
0:14:11 It was a real dark day for the company.
0:14:13 And we said, yeah, so we understand there’s this deal
0:14:16 over there, do you think we could go close a deal?
0:14:17 Is it a 250K deal?
0:14:19 Can we get 175K if we do this quarter?
0:14:21 And he says, well, I think so.
0:14:23 I said, do you have your passport with you?
0:14:24 He said, yes.
0:14:27 Now he’s wearing flip-flops, short pants, dirty t-shirt.
0:14:29 And I said, listen, take your passport,
0:14:33 drive to the airport, we’ll have a ticket waiting for you.
0:14:35 And you go to UK and get a deal.
0:14:39 And so he says, okay, and gets in the car, drives in,
0:14:40 while he’s in the car, he takes out his cell phone,
0:14:42 he calls up the guy on the other side, he says,
0:14:45 I’m coming to do a deal, I have no place to sleep,
0:14:47 I have no clothes, and no toiletries,
0:14:49 can you help me out?
0:14:52 Actually, when I got to Customs at Heathrow,
0:14:54 they asked me where my bags were,
0:14:55 and I’m like, I don’t have any.
0:14:57 I almost got arrested because I’m on a mission.
0:15:00 That’s these stories that live on forever and ever,
0:15:03 at least for me, and I know in an environment,
0:15:07 they really do define a lot of how you go make things happen.
0:15:09 Not unlike the military.
0:15:12 People talk about in the military,
0:15:14 you kind of take care of each other.
0:15:16 In business, in all startups, there are dark days.
0:15:18 And the companies that come through that together,
0:15:22 and survive and thrive after that, have those memories,
0:15:24 and those are very powerful binding forces
0:15:26 among the people who are involved at that time.
0:15:30 Every company goes through some cathartic event,
0:15:33 where it’s the pit of despair.
0:15:36 Nothing can go well, and the companies that pull out of that
0:15:39 actually come out much stronger as a result.
0:15:43 It is not a straight line up into the right by any stretch.
0:15:46 And that gets to the topic of loyalty and commitment
0:15:48 to a team.
0:15:51 And I know loyalty and commitment to a team is paramount
0:15:54 when you’re in the service and in the military.
0:15:56 So how does that transcend into a company,
0:15:57 and what does that actually mean?
0:16:00 How do you build that in an organization?
0:16:05 – I think you engender loyalty by being loyal first.
0:16:09 I think you engender trust by trusting first.
0:16:12 Some people don’t like to trust,
0:16:14 because they might get betrayed.
0:16:16 And I always look to say, you know,
0:16:18 if you go first and you trust,
0:16:21 and somewhere along the way that trust is betrayed,
0:16:23 you have to weigh that cost
0:16:26 against the benefit of having expressed trust
0:16:28 to people before.
0:16:29 So one of the things we did at Veritas,
0:16:31 we were highly transparent.
0:16:33 We used to have a company meeting,
0:16:34 and we told them, you know, these are the good things,
0:16:36 these are the bad things.
0:16:38 I remember the company grew, we got public,
0:16:41 you know, we had limitations on what we could do,
0:16:43 and we’re sitting and kind of talking about this problem
0:16:46 of kind of expressing trust and sharing information,
0:16:49 and we had 5,000 employees at the time,
0:16:51 and I said, hey, why don’t we,
0:16:53 this staff meeting that we have,
0:16:57 why don’t once a month let every manager in the world
0:17:00 have a call and number and listen to what we talk about?
0:17:02 ‘Cause, you know, right now you close the door,
0:17:03 and everybody stands outside,
0:17:05 waiting for a little puff of white smoke
0:17:06 to come out of the chimney, right?
0:17:09 So we did that.
0:17:11 One of the questions you asked yourself in a company,
0:17:13 you run a company, should we tell people this?
0:17:15 Is this something we should talk about?
0:17:17 And we actually changed that question and said,
0:17:19 is there a good reason why we shouldn’t talk about that?
0:17:21 Is there any good reason why we shouldn’t tell people?
0:17:24 And that bought a lot of loyalty.
0:17:27 Now, the other part of buying loyalty is success.
0:17:30 People much more loyal to successful companies
0:17:32 than to unsuccessful companies,
0:17:35 but the importance of building trust,
0:17:38 I think of trust, I think of it as a bank of trust.
0:17:40 So in a bank of trust, you can make a deposit.
0:17:45 Meaning you can express trust and give people that sense.
0:17:47 In times of need, when things are bad
0:17:50 and you need people to stand by you,
0:17:52 you can make a withdrawal from that bank.
0:17:54 But they don’t make any loans.
0:17:58 So if you don’t make a deposit,
0:18:00 there’s nothing there when you go to the bank.
0:18:02 And that’s the way I think about it
0:18:04 in terms of running a company.
0:18:09 I think leadership is authenticity, loyalty, trust,
0:18:12 honoring people, fair play in all things,
0:18:16 meaning compensation and stock options and stuff like that.
0:18:17 Everybody understands the rules
0:18:18 and then you abide by the rules.
0:18:20 That doesn’t mean everybody gets the same amount of money,
0:18:25 but everybody gets treated in the same paradigm, right?
0:18:27 And all that responsibility falls
0:18:28 on the senior people in the company to do that.
0:18:32 Every day, culture in a company has nothing to do
0:18:34 with the values that are published.
0:18:37 Culture in a company has to do with what happens
0:18:40 in a company when things get bad
0:18:42 and people have to make decisions and how do they react.
0:18:44 And what they do in those days
0:18:47 determines what that company’s character is.
0:18:48 So when you think back to your career,
0:18:51 is there a moment that you remember
0:18:53 on a leadership challenge,
0:18:56 how you addressed it and what you learned from it?
0:18:57 There is a moment I think of,
0:18:59 and it’s actually part of that same story
0:19:00 that I told a little earlier.
0:19:04 I was away from the office on a Friday in February
0:19:06 of our first quarter as a public company.
0:19:10 And I was with my aunt and uncle who had come to town
0:19:11 from the East Coast and my wife,
0:19:13 and we were up in Point Reyes.
0:19:14 And it’s very beautiful.
0:19:16 And we didn’t have email then.
0:19:18 So I’m calling in all the time to get my voicemail
0:19:19 and I get a voicemail that says,
0:19:24 “Sequing computers canceled their $350,000 order,”
0:19:26 which was a development order
0:19:28 that we had been working on for a year
0:19:30 and we were taking it to revenue in the current quarter
0:19:32 and it canceled it.
0:19:34 Our goal for that quarter was about $2.5 million.
0:19:37 So it was a big hit, it was a 15% hit to the quarter.
0:19:38 And you can’t make the quarter,
0:19:39 you gotta exceed the quarter.
0:19:41 We’re a little company at the time, and public.
0:19:42 So the rest of the day,
0:19:45 I kept calling in for more news and there wasn’t any.
0:19:46 I kept calling in to find,
0:19:47 this is maybe something good happened.
0:19:48 There was no good news.
0:19:49 And the rest of the day,
0:19:51 I’m walking around with a rock in my stomach
0:19:53 and my wife and my aunt and my uncle
0:19:55 are all talking to each other
0:19:57 and I’m living in a silent movie.
0:20:00 I have no idea what’s going on.
0:20:03 So they had the weekend and that wasn’t in the office.
0:20:05 And it gave me time to think about it in a way.
0:20:08 And I said, this is a leadership opportunity.
0:20:12 And I came into the office and the first thing I said was,
0:20:14 we deserve to get canceled.
0:20:15 This isn’t the executive staff name.
0:20:16 We deserve to get canceled.
0:20:18 We did a terrible job.
0:20:20 And we need to figure out what we did wrong
0:20:21 and how to make it right.
0:20:23 But I don’t want to do that right now
0:20:25 ’cause I don’t want to go fix the blame.
0:20:26 I want to actually do a post mortem.
0:20:27 Let’s do that in a month.
0:20:29 So we kind of took that off the table.
0:20:31 And then I said, we got a $350,000 holds.
0:20:32 Anybody have an idea?
0:20:34 And the room did look just like this.
0:20:36 Everybody’s looking at me and nobody has an idea.
0:20:39 And I said, I have an idea.
0:20:44 I said, my idea is we go ask Sequin for $100,000.
0:20:48 And everybody’s kind of like, huh?
0:20:49 I said, so three things.
0:20:52 I said, first, we give them a clean release,
0:20:54 which has value to them.
0:20:58 Second, we understand that there’s guilt on both sides
0:20:58 when something fails.
0:21:02 So we don’t necessarily do anything with that,
0:21:04 but we make sure that we understand
0:21:06 that there’s failure on both sides.
0:21:09 And I said, the last thing we do is we beg for mercy.
0:21:12 We go up there and we say, hey, we’re a brand new company.
0:21:13 It’s our first quarter.
0:21:15 Give us $100,000.
0:21:17 You remember when you were a young company,
0:21:18 it will save our life.
0:21:21 And we go get on our knees and we beg.
0:21:22 And there ain’t nothing wrong with that
0:21:23 when you’re in business
0:21:25 that’s doing the right thing for your company.
0:21:26 And then we did the Peter thing
0:21:28 and then we did the other things.
0:21:32 And it was a moment in time at eight o’clock in the morning
0:21:34 it was black.
0:21:36 There was no hope, it was all despair.
0:21:41 And we came through that and that team remembers that day
0:21:43 and was a better team and a more loyal team
0:21:45 instead of a tragedy for the company.
0:21:47 So that was a leadership moment for me.
0:21:49 – My question was a little bit in response
0:21:52 to both of the last discussion you all were having on loyalty,
0:21:53 but specifically on incentives
0:21:56 and incentives around sales organizations.
0:21:59 Specifically, how do you structure incentives
0:22:01 such that your sales organization
0:22:05 is optimally competing outside rather than inside
0:22:08 and making sure it’s not cannibalizing profits
0:22:09 that could have been had?
0:22:10 How do you think about incentives in general
0:22:13 to maximize the overall company gain?
0:22:17 – Sales incentives are usually kind of structured economically.
0:22:19 You make your goal, you get this much.
0:22:20 And once you pass that,
0:22:22 you get an accelerator and stuff like that.
0:22:24 And the question is, are they behaving right?
0:22:25 Okay.
0:22:28 And the reason that sales people don’t behave right
0:22:31 relative to their compensation plan,
0:22:34 it’s not the salesman, it’s the compensation plan.
0:22:36 What a company needs to do is find out
0:22:39 what they want the sales people to do
0:22:41 and then pay them for that.
0:22:44 And to do that in a way that is simple.
0:22:45 So I’ll give you an example.
0:22:47 I was on the board of a SaaS company
0:22:49 and we have all kinds of sales plans.
0:22:50 And finally, one day I said,
0:22:53 “Look, the most important thing that we measure ourselves
0:22:55 “and the world measures on is ARR,
0:22:56 “the annual recurring revenue,”
0:22:58 or MRR monthly recurring revenue.
0:23:01 I said, “Why don’t we just pay for that?
0:23:03 “Why don’t we give each person a territory?”
0:23:06 And it said, “On the exit date last year,
0:23:10 “the ARR from this territory is $1.7 million.
0:23:13 “Your job is to get to $2.7 million.
0:23:16 “If you lose something along the way, it’s on you.
0:23:17 “Go figure it out.”
0:23:20 And you pay very simply
0:23:22 on the thing that’s most important to the company.
0:23:24 So the problem that most companies have
0:23:26 is that they don’t know what’s important to them.
0:23:27 And then the second problem that most companies have
0:23:30 is that everybody, particularly as a company gets larger,
0:23:32 everybody has a hobby horse that they wanted,
0:23:34 salespeople that they wanted to do this,
0:23:36 they wanted to sell this new product they wanted to do.
0:23:39 It’s incumbent upon the people who are in charge
0:23:41 to have clarity of thinking
0:23:43 and to express that in the compensation plan.
0:23:45 I think a compensation plan should be
0:23:46 on a three by five card.
0:23:48 This is what your base is, this is how much you’re getting.
0:23:51 These are the kind of notches as you go up the thing.
0:23:54 And here’s what we’re paying you for, go to work.
0:23:57 I had a very interesting little side story.
0:23:59 Sun Microsystems was a very big company
0:24:01 with a very big sales force.
0:24:03 And every year they had a new compensation plan.
0:24:04 And every year they worried about like,
0:24:08 “Ugh, what are the holes in it that we can’t see?
0:24:11 And what are the unintended consequences?”
0:24:14 So they got their five top salesmen in the world
0:24:16 and they brought them into the home office.
0:24:20 And they say the guy who breaks the compensation plan
0:24:23 most significantly gets a gold Rolex.
0:24:25 (laughs)
0:24:28 It worked, they found out all the holes in the plan, it’s good.
0:24:31 – So in the past, you’ve talked about the idea
0:24:34 that being the CEO or founder is not necessarily glamorous
0:24:37 and they used to like have to wake up at 2.30 in the morning
0:24:40 to go to do your like media call for the East Coast
0:24:41 and all that.
0:24:44 But when you’re fighting for sales talent specifically,
0:24:46 you kind of need to show up a little bit of the glamorous side.
0:24:50 How did you navigate those two of kind of showing that
0:24:52 this might not be the most glamorous thing,
0:24:53 but sales talent are kind of looking
0:24:55 to be a little glamorous at times?
0:24:58 – Sales people love to get sold too.
0:25:01 (laughs)
0:25:05 So I actually understand success in sales
0:25:07 having been through the whole thing myself.
0:25:08 It’s a very simple thing.
0:25:12 The most successful people go to work for a company
0:25:14 whose product people want to buy.
0:25:19 The second thing they do is they get a great territory.
0:25:24 The third thing they do is walk around
0:25:25 kind of talking about how bad things are
0:25:28 so that they get a great quota.
0:25:30 And then the rest of what they do
0:25:32 is the things they do every day,
0:25:35 which if you’ve done the first three, it’s a layup.
0:25:36 You just do it, right?
0:25:38 It’s just, you just roll it up and you do it.
0:25:41 So sales people want to feel like you got a hot product
0:25:42 in a hot market.
0:25:44 They want to feel like they’re gonna make a lot of money.
0:25:47 They want to feel like they can hit the million dollar mark.
0:25:50 One of the things as sales forces
0:25:51 kind of get a little bigger.
0:25:54 One of the things you think about is
0:25:57 what percentage of the people do we expect to make goals?
0:26:01 So the company knows what the productivity is
0:26:02 and they know what the mean and the median
0:26:03 and they know all this.
0:26:05 It’s my belief that you want to have a company
0:26:08 where 75% of the people get to 100%.
0:26:10 Then you have a reputation that this is a company
0:26:12 where people make money.
0:26:13 A lot of people say, well, let’s have,
0:26:15 let’s get ready to stretch goals.
0:26:17 You already stretch goals, everybody walks away,
0:26:19 only 30% of the people make it.
0:26:21 And then you got a downer, right?
0:26:24 You build a culture of success by managing
0:26:26 these things, you manage the environment.
0:26:29 Certainly when you start in the very beginning,
0:26:31 I have a belief that you look for,
0:26:34 there’s most sales people are what we call coin operated.
0:26:37 You hire them, you give them all the materials
0:26:39 and the territory and all this other stuff
0:26:40 and then they send you orders.
0:26:42 The more they send you, the more you pay them.
0:26:44 And I consider that to be the infantry
0:26:46 to translate it to you guys.
0:26:49 You do it with process and procedure
0:26:51 and rules and regulations and stuff like that.
0:26:53 But when you’re just starting out,
0:26:55 you want Delta Force.
0:26:59 You want resourceful people who have minimal resources
0:27:00 and can react in a way
0:27:02 and can pull other people in the company
0:27:04 and can do amazing things that you can’t,
0:27:06 that you don’t, you know,
0:27:09 a big sales force is a sales factory
0:27:12 like the infantry is a fighting factory, right?
0:27:14 But little sales force is really
0:27:16 a bunch of very, very special and unique people.
0:27:18 – Okay, with that, thanks Mark.
0:27:18 – Okay, great.
0:27:22 (audience applauding)

0:00:03 Hi, and welcome to the A16Z podcast.
0:00:05 I’m Hannah, and in this episode, Bob Tinker,
0:00:07 author of the new book, Survival to Thrivel,
0:00:09 and founding CEO of Mobile Iron,
0:00:12 and Peter Levine, A16Z general partner,
0:00:15 talk with me all about finding go-to-market fit
0:00:16 for the enterprise startup.
0:00:18 Even once you’ve found product market fit,
0:00:21 a lot of enterprise companies never quite hit the gas
0:00:24 on growth and can stall out at that critical juncture.
0:00:26 So what are the right tools to figure out
0:00:29 that missing link of the right go-to-market model?
0:00:31 How do you unlock real growth from that moment?
0:00:34 What are the different sales and go-to-market models,
0:00:35 and how do you choose between them,
0:00:37 and what are the important metrics
0:00:39 you need to be paying attention to?
0:00:41 So Bob, let’s first maybe start by talking about
0:00:44 what product market fit means for the enterprise startup.
0:00:46 How is it different for the enterprise startup
0:00:48 versus other categories?
0:00:51 I think there’s a bug in Silicon Valley,
0:00:53 which is that at our core,
0:00:55 I think we’re fundamentally a product shop,
0:00:57 and we are really, really, really good
0:00:59 at helping entrepreneurs build products.
0:01:02 But we are not that good at helping entrepreneurs
0:01:05 build go-to-markets on the back of their products.
0:01:08 There’s not necessarily sort of the institutional knowledge
0:01:10 that has passed from company to company to company
0:01:12 about how to build go-to-markets.
0:01:13 For consumer companies,
0:01:17 when you find product market fit, the company takes off.
0:01:19 Magic happens, growth unlocks.
0:01:21 For enterprise and B2B companies,
0:01:24 where the sales process is more systematic,
0:01:26 customer decisions are more complicated,
0:01:28 you can get the product market fit
0:01:30 when you’re first 15, 20 customers,
0:01:33 but growth never really unlocks.
0:01:37 One of the real core challenges for the B2B community is,
0:01:41 there’s a lot of startups that get to product market fit,
0:01:43 but never unlock growth and just sort of bump along.
0:01:45 How do you know you’ve got product market fit
0:01:47 if you’re not actually growing?
0:01:48 Doesn’t it, by almost by definition,
0:01:50 mean you don’t have it if you’re not growing?
0:01:52 Well, I think it’s an order of magnitude
0:01:54 about how fast are you growing.
0:01:56 In many ways for enterprise companies,
0:01:58 getting to product market fit means,
0:02:02 can you get to five, 10, 15, 20 customers that gave you money
0:02:04 and are they actually using your product
0:02:06 and are they willing to say good things?
0:02:07 That’s a huge accomplishment.
0:02:09 It’s incredibly hard and there’s a lot of startups
0:02:12 and ideas that never make it to that point.
0:02:16 For core enterprise companies,
0:02:19 how do you go from winning 10 customers a month
0:02:21 to 50 customers a month to 100 customers a month,
0:02:23 the 500 customers a month?
0:02:25 And that’s where sort of this missing link is
0:02:28 between how do you win some customers
0:02:30 and prove you have value to,
0:02:34 how do you really unlock rapid growth?
0:02:35 There’s a difference.
0:02:37 One of the things that we’re seeing
0:02:40 that’s sort of a new phenomena are enterprise companies
0:02:42 that do have a bottoms up model,
0:02:45 whereby they do start with the consumer,
0:02:50 which is typically a employee in a company
0:02:53 where the product in some ways sells itself.
0:02:56 And so that’s another way of thinking
0:02:59 about product market fit in terms of,
0:03:01 can I get a product out there
0:03:04 that’s used by a large constituency of users?
0:03:06 It’s not 10 or 20.
0:03:08 It’s probably hundreds, thousands,
0:03:11 maybe hundreds of thousands of users
0:03:12 that start the flywheel going.
0:03:13 And then the question is,
0:03:17 how do you capitalize on that with more of a top down?
0:03:20 I call itself serve versus sales serve in those environments.
0:03:22 And we’re seeing more of that now.
0:03:24 I think we’re actually talking about the same thing.
0:03:25 Okay.
0:03:26 When we looked at a bunch of companies
0:03:29 that had sort of won their first 15, 20 customers,
0:03:32 either through going direct to employees,
0:03:34 bottoms up or tops down,
0:03:36 the ones that did unlock growth,
0:03:39 they were able to define their go to market playbook,
0:03:41 which is what are the repeatable steps
0:03:44 for how they find and win customers
0:03:46 over and over and over and over and over
0:03:49 and over and over and over again.
0:03:52 And having your repeatable playbook applies,
0:03:54 whether it’s tops down or bottoms up.
0:03:55 That’s an excellent point.
0:03:56 I mean, I think what you’re both saying,
0:03:57 it’s really interesting is like,
0:03:59 once you get that started,
0:04:00 whether you get it started from bottoms up
0:04:01 or from top down,
0:04:04 there’s this moment where you can kind of stall out
0:04:07 and get stuck or you can get things in motion
0:04:08 and start growth going.
0:04:10 And that moment of getting stuck,
0:04:13 I just wanna back up for a second and like zero in on that.
0:04:15 What does that tend to look like?
0:04:18 Like, where do people tend to flounder there
0:04:20 and like not kind of kick into gear?
0:04:23 You know, you finally got product market fit,
0:04:24 but then you just stall out.
0:04:25 What does that actually look like?
0:04:26 It’s kind of funny actually.
0:04:28 You sort of see this in the conversations
0:04:30 between entrepreneurs and Silicon Valley,
0:04:33 which is, hey, we won our first customers
0:04:36 and they sort of get told to go figure out this sales stuff,
0:04:37 go figure out this go to market stuff.
0:04:40 And it was not a very organized conversation around,
0:04:41 well, what does that mean?
0:04:44 There’s a number of reasons why growth never really unlocks.
0:04:46 It can be founder selling.
0:04:49 It can be not finding urgency.
0:04:51 It can be spreading your resources too thin.
0:04:53 One of the places where I see these companies stall out
0:04:55 is they had founder selling
0:04:57 to be able to get to the first 10, 15, 20 customers.
0:04:59 And then when we start to add sales people,
0:05:01 they’re gonna market model.
0:05:02 They find, oh, wait a minute,
0:05:04 a regular sales or marketing person
0:05:07 can’t actually do what the founder was doing.
0:05:09 So, you know, people are gonna,
0:05:11 oh, maybe our sales team or marketing people
0:05:13 don’t really understand the product, they can’t sell it.
0:05:15 Like you end up in these sort of dysfunctions
0:05:18 because I think it didn’t really have
0:05:22 sort of the true market test of have you figured out
0:05:24 how to find and win customers
0:05:25 without relying on the founder.
0:05:28 That’s usually the first place I see things stall out
0:05:31 is sort of over reliance on founder selling.
0:05:34 The second one is trying to do too many things at once.
0:05:37 Trying to do two or three, go to market model at the same time.
0:05:38 We’re gonna do tops down, we’re gonna do bottoms up,
0:05:41 we’re gonna do framing, we’re gonna do market led.
0:05:43 And when you have relatively small number of resources,
0:05:45 they end up scattered so far
0:05:47 that you never actually really figure out
0:05:48 what the repeatable recipe is.
0:05:51 So you end up spending an enormous amount of energy
0:05:52 with a very little result.
0:05:55 So being able to pick your model and focus matters.
0:05:58 The third place where I think people stall out
0:06:03 is they think that they know their passion
0:06:05 for whatever their initial idea was
0:06:07 and may not necessarily be the thing
0:06:09 that actually unlocks growth.
0:06:10 There’s sort of a funny story we have
0:06:12 from the early days of Mobile Iron,
0:06:15 which was we were early in mobile security.
0:06:17 And when we first started,
0:06:21 we built this security and policy engine
0:06:23 for any mobile operating system.
0:06:25 So enterprises could adopt mobility
0:06:29 as a first class citizen, yay, we’re really proud of it.
0:06:31 The really forward thinking advanced customers would get it,
0:06:33 but a lot of them were just sort of looking at us
0:06:35 and be like, why do I need that?
0:06:37 And we weren’t able to translate that
0:06:40 into what’s the problem that got the customer
0:06:42 to say, okay, I need that right now.
0:06:43 And eventually what we did is we figured out
0:06:45 that that problem was,
0:06:46 dude, I need help with my iPhones.
0:06:47 And that’s the urgency.
0:06:49 And that was the urgency.
0:06:52 I think there’s one other related piece
0:06:53 with founders selling,
0:06:55 which is a very interesting point
0:06:57 ’cause we always encourage founders to go out
0:06:58 and sell, right?
0:07:00 It’s super important from a learning perspective.
0:07:01 To learn. Absolutely.
0:07:04 And then, you know, this whole notion
0:07:07 of the continuance of founders selling,
0:07:09 the founders of our companies
0:07:14 tend to be technical founders, right?
0:07:16 And they’re so intimate with the product
0:07:17 and the features and all that.
0:07:21 And often they view sales as a bit of a black box.
0:07:24 In my experience, the growth kind of stops
0:07:27 when they try to run sales too much
0:07:28 and kind of get involved in an area
0:07:31 where they have not a lot of experience, right?
0:07:34 And then kind of, you know,
0:07:37 hiring the sales VP or sales leader
0:07:39 becomes a bit of an issue.
0:07:43 And then the founders trying to micromanage
0:07:44 the sales leader because–
0:07:46 By saying, just do what I do.
0:07:48 I’m stressed out just thinking about it.
0:07:51 All of, you know, and then the sales leader
0:07:54 doesn’t quite work out and you have to fire people
0:07:56 and like it creates a, you know,
0:07:58 a lot of turmoil within the organization.
0:08:03 So it’s really like this whole founders selling
0:08:07 and then transitioning to a repeatable model,
0:08:09 i.e. no founders selling.
0:08:10 I mean, you can help out,
0:08:13 but not founder-led selling
0:08:15 is a really interesting transition point.
0:08:18 I mean, we see that quite a bit where, you know,
0:08:21 it’s like it’s kind of muddled up in there.
0:08:23 Are you gonna be able to hand the baton
0:08:24 to that machinery? Yeah, are you labeled
0:08:25 and do you have enough knowledge
0:08:28 to actually go and manage the things that are important
0:08:31 without getting overly involved, right?
0:08:32 It sounds very much like this moment
0:08:34 of reckoning, right?
0:08:35 Where you’re about to go into this
0:08:38 and you talk about it like this moment of reckoning
0:08:39 is sort of a missing link
0:08:41 that people don’t talk about, right?
0:08:43 You call it go to market fit.
0:08:45 So my first question about that
0:08:48 is how many people even recognize
0:08:50 that it is a moment of reckoning like that?
0:08:50 Or did they just kind of,
0:08:52 is it just, you just sort of slide into it
0:08:53 and then you’re either in or not?
0:08:56 You typically slide and fumble your way into it.
0:08:59 Where the light bulb usually goes off
0:09:00 that people feel like, uh-oh,
0:09:01 we may not have figured out
0:09:03 a repeatable go to market model
0:09:07 is you win your first 15, 20 customers,
0:09:08 maybe with founder-led selling
0:09:09 and you say, all right,
0:09:11 we’ve figured out product market fit,
0:09:12 it’s time to grow.
0:09:14 So the board comes in and says, okay,
0:09:15 you figured out product market fit,
0:09:17 it’s time to grow, go do sales.
0:09:20 Go hire VP of sales, go sell.
0:09:23 And so you go hire three or four people,
0:09:25 your burn rate goes up,
0:09:27 you put together some PowerPoint pitches,
0:09:28 and then you wake up six months later
0:09:31 and you went from 20 customers to like 24 or 25.
0:09:33 And your burn rate accelerates
0:09:34 and everybody’s looking at each other,
0:09:36 really stressed out.
0:09:38 And it’s a really scary moment for a company
0:09:39 to sort of say, all right,
0:09:41 we just hit the gas to go grow,
0:09:44 but we didn’t actually really have
0:09:46 our repeatable go to market model figured out.
0:09:50 So that’s usually when the reckoning comes.
0:09:53 – You know, also when that reckoning moment comes,
0:09:55 and I’ve seen this many times,
0:09:58 you’re also, the company is also debating,
0:10:01 is it a sales problem or is it a product problem?
0:10:03 You’re trying to understand,
0:10:05 like maybe the product that I’ve built really isn’t,
0:10:09 doesn’t solve, I love this urgency concept,
0:10:12 doesn’t really satisfy the urgency of the customer.
0:10:16 And so where, what are the levers that you pull
0:10:19 at that particular point in time to self-correct?
0:10:22 Is it a product problem or is it a go to market problem?
0:10:26 Right, and clearly over hiring sales people
0:10:29 and all that are symptoms of something, right?
0:10:31 Maybe you can’t reproduce the founder selling,
0:10:34 product’s great, but I can’t reproduce the selling.
0:10:37 Or the product isn’t hitting the market
0:10:38 or whatever, the only,
0:10:42 and it’s kind of a blended problem at that point in time.
0:10:44 – I mean, how do you start analyzing
0:10:45 and pulling apart the knot before,
0:10:47 presumably before you start building?
0:10:50 – Well, look, all these things are presumably
0:10:52 somewhat self-correctable,
0:10:56 provided that you have enough runway to go self-correct this.
0:11:00 I mean, there’s no substitute for awesome product market fit
0:11:01 and some companies nail it right away
0:11:04 and other companies start in one place
0:11:05 and migrate to another.
0:11:10 The problem is, is if you run out of runway, i.e. cash,
0:11:12 you don’t have time to figure it out.
0:11:17 So one of the elements is that before a company goes
0:11:21 and hires to Bob’s point,
0:11:24 the VP and once you hire a sales VP,
0:11:25 what do they want to go do?
0:11:26 Hire a bunch of reps.
0:11:28 So now you have all this expense
0:11:30 without knowing the urgency
0:11:32 or what’s actually going to work.
0:11:37 When I was CEO, I used this phrase with my team.
0:11:43 I said, we’re not going to expand the sales organization
0:11:45 till we see the whites of their eyes.
0:11:48 And I don’t know if you remember like Bunker Hill, right?
0:11:50 You only had a few bullets to shoot
0:11:53 and you weren’t instructed to not shoot the bullets
0:11:58 until you saw the whites of the eyes coming over the hill.
0:12:01 And it’s some subjectivity here to say,
0:12:05 look, when the customer starts demanding this,
0:12:08 then we’re going to go build a sales organization, right?
0:12:10 Or add the reproducibility.
0:12:15 And I waited for what some people could argue
0:12:17 is too long a time.
0:12:21 But I think we over rotate too soon
0:12:24 to go build up all this capacity
0:12:27 and all this, you know, customer support
0:12:31 and marketing and sales and all this stuff
0:12:34 when there’s no customer ready to actually go buy it.
0:12:35 I mean, what you’re basically saying
0:12:38 is wait until the urgency is painful.
0:12:41 Wait till the, or exactly, wait till you feel it, right?
0:12:44 There’s a really interesting dynamic here,
0:12:47 which I see, you know, and we even felt this,
0:12:49 which was that, hey, you figured out
0:12:51 your first 10 or 15 customers go hire sales.
0:12:53 And that’s sort of the mean that gets out there.
0:12:55 Wait a minute, is that what we really need to do?
0:12:59 And I think one of the mistakes is go hire VBS sales.
0:13:01 That’s what the first thing you need to do when you go sell.
0:13:05 My personal opinion on that is that’s not the right thing to do.
0:13:09 You need to find, like go hire more of like a Davy Crockett
0:13:13 type sales rep that can sell,
0:13:16 but also has a little bit of product and product marketing
0:13:18 in them because really what you’re still trying to do
0:13:21 right there is find your path through the go to market woods
0:13:24 and have it be done by a sales rep
0:13:26 or somebody that’s not the founder.
0:13:28 I think that’s really step one
0:13:31 because that’s the same way you iterate on a product
0:13:32 to find product market fit.
0:13:36 You need to iterate on your go to market and your pitch
0:13:38 and what’s the urgency and what’s the sales model
0:13:39 the same way.
0:13:43 And you need to iterate with those one or two
0:13:45 sort of Davy Crockett type people
0:13:47 that are able to help you find the path.
0:13:50 I mean, I’ve, the sales videos that I’ve done,
0:13:54 we point to this concept called the sales learning curve,
0:13:55 which Mark Leslie developed,
0:13:57 which talks about the renaissance sales rep
0:13:59 in that early phase.
0:14:03 They typically have a combination of technical skills
0:14:05 and sales skills and they can do a lot of things.
0:14:09 They’re kind of like a Swiss army knife of a sales person.
0:14:12 And they ask customers what about a problem right here?
0:14:12 What about a problem right there?
0:14:14 They look a little bit to the left,
0:14:15 they look a little bit to the right.
0:14:16 Figure things out.
0:14:19 You want to hire a couple of those people
0:14:22 or early on to help figure things out.
0:14:24 Okay. So say you have this reckoning and you say,
0:14:27 and you think, okay, shit, I got to figure this out.
0:14:29 What if you have already hired a VP of sales?
0:14:32 Like how do you kind of pause
0:14:34 and then go forward saying, okay,
0:14:36 now we’re going to systematically figure this out?
0:14:36 Maybe the question is,
0:14:38 how could we help avoid the reckoning?
0:14:41 Aren’t you saying it comes inevitably?
0:14:41 No, I don’t think it is.
0:14:44 I think the way to avoid that really painful,
0:14:48 like, oh crap, reckoning is as you shift off founder selling
0:14:50 and iterating on your product,
0:14:52 starting to be thinking your background about,
0:14:54 how do we iterate on go to market?
0:14:55 The same way you iterate on product.
0:14:58 And you’re looking a little bit to the left
0:15:00 or a little bit to the right for the urgency.
0:15:03 You’re trying to figure out like, do you go in bottoms up
0:15:04 or do you come in tops down?
0:15:06 Do you figure out your sales model?
0:15:09 This is something that I got horrendously wrong
0:15:10 as a first time CEO,
0:15:13 is that I thought like having a go to market playbook
0:15:17 essentially meant you have a really good PowerPoint pitch
0:15:18 and some good sales tactics.
0:15:20 And that was horrendously wrong
0:15:24 because your go to market playbook really is paying attention
0:15:27 to how you’re able to find customers,
0:15:29 move them through the buying journey,
0:15:30 what’s working, what’s not working
0:15:32 and how you ultimately get them to decide
0:15:34 and onboard and use your product.
0:15:36 And your early customer wins,
0:15:38 the universe is teaching you a lesson.
0:15:40 So pay really close attention to those first 10 or 15
0:15:43 or 20 wins to not just did you win it or not,
0:15:45 but like, how’d you get there?
0:15:47 What was the journey?
0:15:49 And how can you start to get insight from that
0:15:51 to figure out the repeatability,
0:15:54 really pay attention to what’s the repeatable playbook
0:15:56 and observe and iterate on that.
0:15:58 Then you can avoid that reckoning moment
0:16:01 because you start to see these pieces come together
0:16:03 and you start to see the whites of their eyes.
0:16:07 That’s when you know, okay, it’s time to hit the go button
0:16:09 and shift from sort of Davey Crockett
0:16:12 to like Braveheart or Joan of Arc.
0:16:14 And is that when you know
0:16:16 you’ve found the right go to market fit?
0:16:20 You know when you’re out of this sort of conundrum,
0:16:24 when you actually have reproducibility
0:16:26 from a sales capacity standpoint
0:16:29 or some reproducibility from a pipeline
0:16:31 to conversion standpoint, right?
0:16:33 When you’re out of it phase is
0:16:37 if I hire a salesperson and they cost X
0:16:41 and it takes Y time to generate Z revenue.
0:16:45 And if I can then put literally put on a spreadsheet
0:16:49 and say I’m hiring one rep, two reps, three reps, four reps
0:16:53 and they can reproduce what’s on the spreadsheet,
0:16:55 that’s the reproducible model.
0:16:57 Yeah, now you’re moving, the flywheel is going.
0:16:59 Right, the flywheel is going
0:17:02 and you can really at that point
0:17:03 can start to predict the future, right?
0:17:06 It sounds like you can start to trust a little bit,
0:17:09 like relax and to trust a little bit from that.
0:17:11 There really are those reproducible models
0:17:12 and even if it’s bottoms up
0:17:14 and it’s not hiring somebody,
0:17:18 it may be I have these leads that come in
0:17:22 for a marketing program turns into 100,000 users
0:17:26 and those 100,000 users, 5% of them pay
0:17:27 and that’s the model.
0:17:29 And I convert after three months of use
0:17:31 and so those metrics all have shapes to it, right?
0:17:35 The pipeline has a shape to it on sort of freemium,
0:17:38 sales reps have a shape to it on onboarding
0:17:41 and there are industry standards on all of this
0:17:44 but every company will have its own shape, right?
0:17:47 Yeah, this idea of how do you know you found it
0:17:48 and you’re out of it,
0:17:50 I think is a really profound question.
0:17:52 At the essence of this repeatability
0:17:55 is if you hire somebody new in sales,
0:17:56 do they know what to do?
0:18:00 Like if you have go-to-market fit, you’ve got urgency,
0:18:01 you’ve got your sales model, you’ve got your playbook,
0:18:03 you can hire somebody new in sales,
0:18:04 they kind of know what to do.
0:18:06 You can be like, do this and we win.
0:18:09 It’s like you bring in more people or add more resources,
0:18:10 you kind of know what to do.
0:18:13 And I think that’s really sort of the essence of this test
0:18:16 which is if you have that, I think you’re out of it.
0:18:19 And when you do that, you start to put more into the engine
0:18:22 and you feel that momentum of that repeatable go-to-market
0:18:25 and you go from winning five customers to 10 to 20
0:18:27 to 50, 100 to 500.
0:18:29 What other kinds of metrics are you looking at
0:18:31 to help you define that we’re now out of the woods?
0:18:32 You found this go-to-market fit
0:18:34 and you’re actually hitting real gas
0:18:36 instead of like flooding the engine.
0:18:38 There are measurements that are,
0:18:40 I believe are very important.
0:18:43 One of the key metrics for me is,
0:18:47 how do you know you’re in what we call execution mode,
0:18:51 this kind of rinse and repeat on the sales model?
0:18:55 What I like to look at is that a sales person
0:19:00 is generating greater than three times their loaded cost,
0:19:03 meaning base plus commission.
0:19:07 Let’s say a sales person cost $500,000 a year
0:19:09 or $200,000 a year,
0:19:14 they need to generate a three X multiple on that cost.
0:19:16 And it needs to be across the organization.
0:19:18 You can’t just have one person do it
0:19:20 and it can’t just be the average
0:19:24 because that’s a very misleading indicator.
0:19:26 I could have one sales rep who crushes it
0:19:28 and everyone else does zero.
0:19:30 And if I average that, I would say,
0:19:34 well, yeah, our 10 people are all over the three X metric,
0:19:36 but it happens to be one person.
0:19:41 So I would do it as 70% of the sales organization
0:19:46 need to be generating three X their base cost.
0:19:50 And that’s how you know you’re sort of out of this phase.
0:19:53 And then that’s also a way of knowing
0:19:55 when you should hire more people
0:19:58 because as that number gets greater and greater,
0:20:02 let’s say a sales person can generate five X their cost
0:20:05 or six X their cost, you’re hiring too slowly.
0:20:09 So there’s more deals that that person can hire
0:20:11 and you’re probably leaving things on the table.
0:20:14 So you want to normalize between four to five,
0:20:18 around four X their loaded costs and keep an eye on that.
0:20:21 If it’s too little, you probably have over hired, right?
0:20:24 Where a person only is generating one X
0:20:25 and that’s probably in the early days.
0:20:28 So that’s kind of, that’s a metric that is very important
0:20:31 in terms of, and it’s very simple, right?
0:20:33 Like it’s not this complex like-
0:20:35 Yeah, you can remember that formula.
0:20:38 Yeah, it’s just, and it tends to work reasonably well.
0:20:41 If you think about sort of the end to end sales
0:20:45 and marketing process, do you see as you invest more
0:20:47 in the front end of the pipeline,
0:20:49 you get more leads and more pipeline.
0:20:51 Like as you put X dollars in, you get Y out.
0:20:54 Like is it still linear or even getting better than linear?
0:20:57 Or are you starting to see decreasing marginal returns?
0:21:01 That’s sort of a way to know how hard to push the gas pedal.
0:21:04 When it comes to thinking about hiring reps
0:21:07 or sales engineers, it’s really all about ramp time.
0:21:10 Do your reps reach full productivity in nine months,
0:21:12 12 months, six months or three months?
0:21:15 The moment for me when I knew at Mobile Iron,
0:21:17 we had found good market fit
0:21:22 was when my VPS sales came in and said,
0:21:25 “Hey, I’m willing to take up my quota
0:21:27 “basically as high as you want
0:21:32 “because as long as you let me hire as many reps as I can,
0:21:36 “because I can get them productive in six months
0:21:39 “and I have so many opportunities I can’t get to them.”
0:21:41 He felt like he had a repeatable recipe
0:21:43 to bring new reps on and make them productive
0:21:45 and get them ramped in six months.
0:21:47 That was the point where for me,
0:21:49 like the bit flipped, we were sort of out of the woods.
0:21:54 One of the other elements to look at is pipeline itself.
0:21:57 One of the metrics to be used in the industry
0:21:59 is at the beginning of the quarter,
0:22:01 you wanna have between three and five times
0:22:04 the pipeline to close the quarter, okay?
0:22:08 If you don’t have four times the pipeline
0:22:09 at the beginning of the quarter,
0:22:11 you’re not gonna make your number.
0:22:14 And if you have over at the beginning of the quarter,
0:22:18 the beginning of the year might have been a six, seven, eight,
0:22:21 which means that you’re dropping opportunities on the floor
0:22:26 because the top of the pipeline is fat with opportunities
0:22:29 and you don’t have enough capacity to go and do it, right?
0:22:32 And so looking at that pipeline is also another way
0:22:36 to kind of help modulate how you’re gonna go hire salespeople
0:22:39 to either take up the slack,
0:22:41 meaning get after more opportunities
0:22:45 or don’t hire so many people if the pipeline isn’t there yet.
0:22:47 It sounds like temperature reads almost.
0:22:49 Keeping the metrics very simple
0:22:53 is way more important than having too many metrics
0:22:55 and then you’re trying to measure too many things.
0:22:57 We wanna measure everything, right?
0:22:58 And it gets too complicated
0:23:01 and then you don’t know exactly what to fix.
0:23:02 The fascinating thing that happens
0:23:04 is once you get this repeatable playbook in place
0:23:06 where you find and win customers
0:23:10 and you sort of, people know what needs to be done
0:23:11 at each part of it,
0:23:13 all of a sudden the company now sees
0:23:14 the things they’re working on,
0:23:16 the people in marketing, the people in engineering,
0:23:18 the people in support that are working on these different
0:23:20 things that support the go-to-market playbook,
0:23:24 they now see how what they’re working on
0:23:26 ties to the repeatable go-to-market playbook.
0:23:29 And it was, I didn’t sort of realize this going into this,
0:23:32 but that turned out to be a very powerful sort of
0:23:34 unifying force for the company
0:23:36 to know how what they were working on
0:23:39 tied to how we’re gonna grow the business, right?
0:23:40 And once you understand that,
0:23:43 then you’re out of this sort of mode of,
0:23:46 well, iterating, go-to-market and all that stuff.
0:23:47 And then you can grow from there.
0:23:52 Now, let me point out that if I enter into a new geography
0:23:57 or I build another product as part of the company,
0:24:00 you start over again, let’s say a US geography
0:24:03 and I wanna expand internationally,
0:24:05 maybe my go-to-market model is actually different.
0:24:06 It very well could be.
0:24:08 I might be direct in the US,
0:24:10 but I might go through the channel in Europe.
0:24:11 Exactly.
0:24:13 In which case I have to learn that over again
0:24:14 because I haven’t learned it.
0:24:18 Or I do in partner selling or whatever it might be.
0:24:22 So that’s another point of how do you know you’re out of it?
0:24:25 A company might get into it again
0:24:29 when you build a new product or go into a new geography.
0:24:32 So if we go back to that moment of trying to find
0:24:35 with a Davy Crockett, like feeling your way through the woods
0:24:38 to the right sales model, getting gathering information,
0:24:39 what are some of the questions you’re asking at that point
0:24:42 to find and identify what the right sales model is,
0:24:43 especially if you’re that founder
0:24:45 who doesn’t really know who for,
0:24:47 it is a kind of black box.
0:24:50 Yeah, this is a great question
0:24:52 because there’s all sorts of different types
0:24:54 of sales models you hear about.
0:24:57 And there are certain sales models that are kind of faddish
0:24:58 that get pushed on you.
0:24:59 Like this has been Vogue right now.
0:25:02 Oh, like a freemium sales model is really exciting.
0:25:04 So you should definitely do that.
0:25:07 Or you should follow Atlassian’s model
0:25:09 and have the no sales people product led model.
0:25:11 Like you hear about all these different things
0:25:14 as a founder and a CEO and you’re honestly like,
0:25:16 how do I figure out which ones to do?
0:25:21 So if you sort of think about sales models as a spectrum,
0:25:23 on the far left, you have heavy touch sales led,
0:25:24 which you hire sales reps
0:25:27 to call on customers to do big deals.
0:25:29 In the middle where marketing
0:25:30 does the front end of the sales process,
0:25:34 they find prospects, they drive them to an online eval,
0:25:36 and then you watch the metrics on the online eval
0:25:39 and then an inside sales person calls them
0:25:40 and takes the deal from there.
0:25:43 So it’s like 50/50 marketing sales.
0:25:45 And then on the far right,
0:25:49 you have a product led or zero touch sales model
0:25:50 where there’s no sales people
0:25:53 and literally the customer goes from find to eval
0:25:56 to online to purchase to upsell without a sales rep.
0:25:58 So like in Atlassian or Twilio.
0:25:59 We talked about this on a podcast recently
0:26:02 on the enterprise products about bottoms up growth.
0:26:05 Martin used a metaphor of a slider bar, right?
0:26:08 There’s a slider bar from total organic bottoms up growth
0:26:09 up to like heavy touch.
0:26:12 And where are you, how do you know where you are?
0:26:15 Yeah, and this is something I’ve certainly seen
0:26:17 to the venture capital industry push companies
0:26:19 to sort of the zero touch product led model
0:26:21 because it’s awesome if you can make it work
0:26:23 ’cause it’s super capital efficient.
0:26:24 The problem is that it doesn’t work
0:26:26 for all companies and products.
0:26:29 So the most important thing here is to pick the right model
0:26:32 for your product and your customers.
0:26:34 So then how do you do that?
0:26:36 If you pay attention to how your customer buys,
0:26:39 like what is that customer journey look like,
0:26:42 that will lead you to one sales model or another.
0:26:45 For example, you can distill it all down to one question,
0:26:49 which is how does the customer decide to buy your product?
0:26:50 How do you decide to buy?
0:26:51 Not how do they physically purchase it?
0:26:55 It’s how they decide in their mind to say I’m gonna buy.
0:26:58 If the buyer and decider are the same person
0:27:01 and you can reach them with digital marketing,
0:27:04 you can do a product led at Blasian Twilio sales model.
0:27:07 If the product and buyer are sort of two people
0:27:08 that are right next to each other,
0:27:11 like the buyer is the VP of marketing
0:27:13 and the decider is the CEO,
0:27:16 you can do a marketing led sales model
0:27:19 where it’s relatively small number of people involved.
0:27:22 If it’s a committee decision where you’d have the CIO,
0:27:23 the chief security officer,
0:27:26 the VP of infrastructure involved,
0:27:28 it’s really hard to do a marketing led
0:27:30 or product led when you have a committee decision.
0:27:32 As you’re winning those early customers,
0:27:34 pay attention, like watch the cognitive process
0:27:36 inside those customers
0:27:38 for how they’re actually deciding to buy.
0:27:40 I think that’s the biggest clue to wear
0:27:42 on that slider bar you end up.
0:27:44 They’re correlated with big size, small deals,
0:27:47 but I think the essence of it is actually this,
0:27:50 how does the customer make the mental decision to buy?
0:27:55 – I might add one more element in sort of the individual
0:27:59 being the buyer and the decider in one person
0:28:01 versus committee.
0:28:04 I mean, in some ways the product itself
0:28:05 has to be simple enough.
0:28:07 If it’s an individual person,
0:28:10 it has to be easy to understand.
0:28:13 If you have a super complex product
0:28:15 going after the individual,
0:28:17 their head might spin because it’s like,
0:28:19 how do I even think about,
0:28:20 it’s super complicated to use.
0:28:24 It’s complicated to try, complicated to install.
0:28:28 How complex is your product to allow the decider to do it
0:28:31 with whatever vehicle you’re actually explaining
0:28:32 those features, right?
0:28:37 The real exciting element to me is it was always assumed,
0:28:40 oh, enterprise direct sales
0:28:43 because the product is complicated, blah, blah, blah.
0:28:46 And consumer products would be this,
0:28:49 sort of viral uptake decision makers, the buyer.
0:28:53 I think that there is a lot of really interesting
0:28:58 innovation in ease of use for enterprise products
0:29:02 that are now being decided and bought by individuals.
0:29:04 Zoom is a great example.
0:29:05 GitHub is a good example.
0:29:06 Twilio is a good example.
0:29:08 Dropbox is a good example.
0:29:10 There are historical products,
0:29:13 which were super complicated in each of those areas
0:29:16 where you required an army of bought deciders
0:29:19 and an army of salespeople to get something like,
0:29:20 what does this thing do?
0:29:22 And all that stuff and how does it work?
0:29:24 And I think that companies now
0:29:27 who take user interface and design
0:29:31 and simplicity of product in the enterprise
0:29:32 are gonna be big winners.
0:29:37 You can’t just say we’re gonna go to do this,
0:29:39 Atlassian bottoms up model,
0:29:41 but does the product have the elegance
0:29:44 to be able to be sold without a sales organization?
0:29:47 Enterprise companies actually are looking
0:29:49 a little bit more like consumer companies
0:29:51 when it comes to product design,
0:29:53 fit and finish and all of that,
0:29:56 which before, it was like,
0:29:58 hey, like if I had a command line interface,
0:30:02 that’s enough with a thousand page user manual.
0:30:05 I think this is where this sort of go-to-market fit
0:30:07 and all these other linking go-to-market
0:30:08 and product come together.
0:30:11 It used to be that product was sort of over here
0:30:13 and did product stuff and sales is over here,
0:30:16 did sales stuff and was product management’s job
0:30:17 to figure out the middle.
0:30:19 What’s really neat about this is you will start
0:30:23 to see iterations between how does the go-to-market
0:30:24 put requirements on the product
0:30:26 and then how does the product influence the go-to-market?
0:30:28 There’s an iterative loop between those now
0:30:30 that I think is actually in many ways
0:30:32 sort of changing almost the cultures
0:30:34 of how enterprise products get built.
0:30:35 – I agree.
0:30:38 – Okay, so you mentioned this very specific moment
0:30:42 when you know your metrics, your product is dialed in,
0:30:44 you have a repeatable go-to-market strategy,
0:30:45 pick the right business model.
0:30:48 What are some of the like, whoops, don’t step in that.
0:30:50 Like, okay, I got it good.
0:30:51 Don’t do this moment.
0:30:54 The biggest pitfalls basically that you can come to.
0:30:57 – Yeah, so in the beginning of building a startup,
0:30:59 your mission is just don’t die.
0:31:00 (laughs)
0:31:02 It really is, just live to fight another day.
0:31:04 When you find go-to-market fit
0:31:07 and you start to feel that momentum, the world changes.
0:31:10 You shift from this, how do we not die mode to,
0:31:12 oh crap, how do we win?
0:31:14 And you’ve really entered a different mindset.
0:31:16 Once a company makes this shift from how do we not die
0:31:19 and how do we win, all hell breaks loose.
0:31:21 And at this point, your mission becomes,
0:31:23 how do we now accelerate the business
0:31:25 to become a category leader?
0:31:29 So you have to go from being sort of ruthlessly frugal,
0:31:31 pinching every penny and counting every nickel
0:31:35 to almost like calculated recklessness.
0:31:36 We’re gonna try some things
0:31:38 and spend some money on things and hire some people,
0:31:40 even though you’re not sure it’s totally gonna work.
0:31:43 And that’s a hard mindset shift for founders.
0:31:46 The second thing that changes is the company culture,
0:31:48 which is that usually up until this point,
0:31:50 you’ve been a very product-led culture
0:31:53 and that’s part of what has made the company successful.
0:31:57 But now as part of accelerating the category leader,
0:31:59 the company needs to have a balanced culture
0:32:02 between valuing both product and go-to-market
0:32:05 as equal citizens in the culture.
0:32:09 And those kind of culture shifts are actually hard for teams.
0:32:10 It’s a journey.
0:32:13 And this manifests in all sorts of ways like just hiring.
0:32:16 All of a sudden, recruiting becomes a core competency
0:32:20 for the company, finding talent becomes a core competency.
0:32:22 Managers are now evaluated
0:32:24 for how well they can hit hiring targets,
0:32:25 ’cause that’s the biggest thing
0:32:27 that’s gonna get in your way of execution.
0:32:29 And then how do you actually onboard all these people
0:32:32 and make them effective and part of the culture?
0:32:33 ‘Cause what actually happens at this point
0:32:36 is you can end up fracturing the culture of the company.
0:32:39 And in many ways, sort of committing hairy carry
0:32:40 by growing too fast
0:32:43 without actually onboarding people effectively.
0:32:47 – At that point, one of the key attributes of one of the key,
0:32:48 it’s not the only one attributes
0:32:51 being a great CEO and great leader
0:32:54 is hiring and retaining a world-class management team.
0:32:55 – That is exactly right.
0:32:58 – What I see is sub-optimizations made
0:33:03 are just not having enough pattern matching skills
0:33:07 to actually go recruit the right people for the right roles.
0:33:12 And I think that that then results in sub-optimal executives
0:33:16 kind of not all being great at what they do.
0:33:18 And then you run into problems that way
0:33:21 because scaling the organization
0:33:25 is about having reproducibility and being able to hire people,
0:33:28 being able to build processes into the organization.
0:33:30 And if the executive team can handle it,
0:33:34 they’re not capable of scaling, you run into a lot of problems.
0:33:36 – Yeah, I think that’s exactly right.
0:33:39 I mean, for me, I was the first time CEO in 2008.
0:33:41 And my job changed profoundly.
0:33:43 It was more like from Captain America
0:33:45 and sort of the platoon in the woods
0:33:47 to more like Captain America and the Avengers,
0:33:49 where you had to go hire your band of Avengers
0:33:51 where each one of your executives
0:33:53 has to have a special superpower
0:33:55 that’s better than you are at that job.
0:33:56 – Or that you did not have.
0:33:59 You have the self-knowledge to know you didn’t have.
0:34:02 – So in many ways, this hiring the leadership team
0:34:05 that Peter’s talking about is a tough transition
0:34:08 for the CEO because the CEO has to let go
0:34:11 of things that he or she was previously doing
0:34:13 that they may think are important and are scared of.
0:34:16 It’s also sort of create some insecurity
0:34:18 because all of a sudden you hire these people
0:34:20 who are grade A executives that join.
0:34:22 And the first thing they’re gonna do
0:34:24 is basically look at all the things you’ve been working on
0:34:26 and basically look at how screwed up they are
0:34:27 and their job is to fix them.
0:34:30 It creates this weird feeling of sort of insecurity
0:34:32 calling your baby ugly.
0:34:35 But I mean, if you hire a grade A VP of sales,
0:34:36 they’re gonna absolutely push you
0:34:38 and the rest of the organization
0:34:39 as they try and drive to scale.
0:34:41 And it’s gonna be uncomfortable.
0:34:44 And if it’s not, you may have not hired the right person.
0:34:47 – So it sounds to me like so much of what you’re describing
0:34:50 is about this ability to kind of look around you
0:34:55 and notice what’s, learn from it and then shift mindsets
0:34:59 or mechanisms or plans for the future based on that.
0:35:02 So it’s kind of about flexibility, right?
0:35:06 How do you stay in that mode as the company grows
0:35:09 and evolves and you are constantly being forced
0:35:12 to sort of examine and then shift?
0:35:14 – I think self-awareness is incredibly important
0:35:17 because you constantly need to be reflecting about
0:35:19 what are I and what are we doing well and not well
0:35:21 and what do we need to get better at?
0:35:23 We spend so much time learning
0:35:26 and in many ways the very things that make us successful
0:35:28 in getting from A to B, for instance,
0:35:31 getting through the survival phase of the company,
0:35:34 many of those same things actually now get in the way
0:35:36 or could kill you at the next stage.
0:35:41 So in addition to learning what you need to do next
0:35:43 and how to be a leader at the next stage of the company,
0:35:45 there needs to be a very conscious effort
0:35:49 to look in the mirror and perhaps unlearn
0:35:51 some of the things that got you there.
0:35:56 – I often describe running a company at different phases
0:35:58 and your ability to turn the ship
0:36:01 kind of like a rowboat versus a ship.
0:36:03 When you’re a small company
0:36:05 and you’re like in this little rowboat
0:36:07 and one big wave can sink you,
0:36:11 you can use the oars and turn the thing on a dime.
0:36:14 And then your boat gets bigger and bigger and bigger
0:36:16 and it’s way harder to turn
0:36:18 and think about a big company,
0:36:21 they’re like a freaking cruise ship, right?
0:36:22 And to turn that thing,
0:36:24 you have to start two miles ahead to turn it.
0:36:27 So what does that mean in terms of running a company?
0:36:32 To me, the horizon by which you look at as a CEO
0:36:35 gets farther and farther out in terms of planning,
0:36:36 right?
0:36:39 Like, if your company is reasonable size,
0:36:42 there’s almost nothing you can do this quarter
0:36:44 to change the outcome of this quarter.
0:36:45 You’re not gonna, like,
0:36:48 maybe you can help with a sales deal or whatever.
0:36:49 It’s probably like,
0:36:52 what can I do now to impact next year?
0:36:53 If you’re real small,
0:36:54 what I do today can impact tomorrow.
0:36:56 There’s always new projects and new things
0:37:00 that are the little boats that may surround the big boat,
0:37:03 you know, in which case you can do things much more nimbly.
0:37:05 If it’s the big thing,
0:37:08 it’s hard to go and change on a dime
0:37:13 when things are generally going in some direction, right?
0:37:17 CEOs and this whole self-awareness should be aware
0:37:21 of kind of the time horizon by which I’m operating at
0:37:26 and where my influence can most adequately be impacted
0:37:28 given that horizon.
0:37:31 – And when you need to pull out your telescope, basically.
0:37:32 – That’s wonderful.
0:37:35 Thanks so much for joining us on the A16Z podcast.
0:37:36 – My pleasure, our pleasure.
0:37:37 Thanks, Bob.
0:37:38 – Thanks.