0:00:05 So that’s my advice is every day, every day, you should be in ChatGPT.
0:00:07 I don’t care what your job is, right?
0:00:10 You could be a sommelier at a restaurant and you should be using ChatGPT every day
0:00:12 to make yourself better at whatever it is you do.
0:00:20 Can I ask you about the story really quick?
0:00:23 And you have like a list of stuff here that’s like all amazing.
0:00:24 It’s actually a lot of it’s very actionable.
0:00:27 But the reason I want to ask you about the story is for the listener.
0:00:29 Dharmesh founded HubSpot, $30 billion company.
0:00:30 You’re the CTO.
0:00:34 So you and you’re an OG for Web 1.0, Web 2.0.
0:00:39 And your first round or one of your first rounds was funded by Sequoia.
0:00:42 Your partner, Brian, is an investor at Sequoia.
0:00:44 So you are in the insider.
0:00:45 You’re an insider, I believe.
0:00:47 You may not acknowledge it.
0:00:47 I don’t know if you do or do not.
0:00:48 You are an insider.
0:00:51 The cool part is that you’re accessible to us.
0:00:55 When did you first see what Sam was working on?
0:00:58 And how long have you felt that this is going to change everything?
0:01:02 So I actually have known Sam before he started OpenAI.
0:01:06 And I got access to the GPT API.
0:01:11 It was a toolkit for developers to be able to kind of build AI applications, right?
0:01:12 Effectively.
0:01:17 And so I built this little chat application that used the API.
0:01:19 And so I could have a conversation with him.
0:01:20 So I actually built that thing that night.
0:01:22 It was a Sunday.
0:01:25 I had the full transcript two years before ChatGPT came out.
0:01:26 So that’s four years ago?
0:01:28 It was 2020.
0:01:29 So five years ago.
0:01:30 Wow.
0:01:30 Okay.
0:01:31 This summer.
0:01:36 And so even then, it’s like, and as soon as I, like, you sort of have that moment.
0:01:38 It’s the same that all of us have with ChatGPT.
0:01:40 I just had it two years earlier.
0:01:43 And then I’m showing everyone, like, Brian, you are not going to believe.
0:01:46 Like, I have this thing, you know, through this company called OpenAI.
0:01:49 And watch me, like, type stuff into it and see, like, see what happens.
0:01:52 And we would ask it, like, strategic questions about HubSpot.
0:01:54 It’s like, how should it, like, who are the top competitors?
0:01:59 And they were, even then, two years before Chat, it was shockingly good, right?
0:02:03 But the thing you sort of have to understand about the constraints of how a large language
0:02:08 model actually works is that you type and you have a limited, just imagine this, if we’re
0:02:13 going to just use the physical analog sheet of paper can only fit a certain number of words
0:02:14 on it.
0:02:20 And that certain number of words includes both what you write on it, that says, I want
0:02:23 you to do this, and the response has to fit on that sheet of paper.
0:02:28 And that sheet of paper is what, in technical terms, would be called the context window.
0:02:30 And you’ll hear this tossed around.
0:02:33 It’s like, oh, this, you know, ChatGPT has a context window of whatever, or this model has
0:02:34 a context window of whatever.
0:02:35 That’s what they’re talking about.
0:02:37 All right, so why is that?
0:02:39 Why does anybody care about the context window?
0:02:45 It’s like, well, sometimes you want to provide a large piece of text, let’s say, summarizes
0:02:45 for me.
0:02:48 Well, in order for you to do that, it has to fit in the context window.
0:02:52 So if you want to take two books worth of information and say, I want you to summarize this in 50
0:02:57 words, those two books worth of information have to fit inside the context window in order
0:02:58 for the LN to process it.
0:03:03 Most, the frontier models are roughly 100,000 to 200,000.
0:03:06 They measure it in tokens, which is like 0.75 of a word.
0:03:07 That’s like a book.
0:03:08 So yeah, is that a book?
0:03:09 I think it’s an average.
0:03:13 I think the average book is like 240,000 words, I think, but I’m not sure.
0:03:13 That’s not a lot.
0:03:19 So when I, the way that I use ChatGPT is I’ll like, let’s say a fun way is I’ll, I’ll put
0:03:22 a historical book that I loved reading and I’ll be like, summarize this so I remember
0:03:23 the details.
0:03:28 So you’re telling me that if it’s a thousand page book, it’s not even going to accurately
0:03:29 summarize that book?
0:03:30 It won’t fit.
0:03:35 You’re like, if you pay something large enough into ChatGPT or whatever AI application you’re
0:03:38 using, it will come back and say, sorry, that doesn’t fit.
0:03:41 Effectively, what they’re saying is that does not fit in the context window.
0:03:42 So you’re gonna have to do something different.
0:03:44 All right.
0:03:50 A few episodes ago, I talked about something and I got thousands of messages asking me to
0:03:51 go deeper and to explain.
0:03:52 And that’s what I’m about to do.
0:03:57 So I told you guys how I use ChatGPT as a life coach or a thought partner.
0:04:01 And what I did was I uploaded all types of amazing information.
0:04:07 So I uploaded my personal finances, my net worth, my goals, different books that I like,
0:04:09 issues going on in my personal life and businesses.
0:04:12 I uploaded so much information.
0:04:17 And so the output is that I have this GPT that I can ask questions that I’m having issues
0:04:18 with in my life.
0:04:20 Like, how should I respond to this email?
0:04:21 What’s the right decision?
0:04:25 Knowing that you know my goals for the future, things like that.
0:04:29 And so I worked with HubSpot to put together a step-by-step process, showing the audience,
0:04:35 showing you the software that I use to make this, the information that I had ChatGPT ask me,
0:04:36 all this stuff.
0:04:37 So it’s super easy for you to use.
0:04:40 Like I said, I use this like 10 or 20 times a day.
0:04:41 It’s literally changed my life.
0:04:43 And so if you want that, it’s free.
0:04:44 There’s a link below.
0:04:47 Just click it, enter your email, and we will send you everything you need to know to set
0:04:49 this up in just about 20 minutes.
0:04:52 And I’ll show you how I use it again, 10 to 20 times a day.
0:04:53 All right.
0:04:54 So check it out.
0:04:55 The link is below in the description.
0:04:57 Back to the episode.
0:05:03 I usually use projects and I have like, let’s say a health project and I’ll upload tons and
0:05:05 tons of books or tons of blood, blood work.
0:05:09 And I hope I’m hoping that it’s going to pull from all those books in my project.
0:05:10 Is that true?
0:05:11 That that is true.
0:05:13 So here, and this is a perfect segue, right?
0:05:15 Because this is the next big unlock.
0:05:19 So number one thing to like understand in our heads is there’s this thing called a context
0:05:19 window.
0:05:20 Here’s why it matters.
0:05:24 So let’s, we’re going to take a, we’re going to pop that on the stack and we’re going to
0:05:26 push on the stack and we’re going to come back to it.
0:05:27 So the thing we have to remember is two things.
0:05:31 Number one, it doesn’t know what it’s never been trained on.
0:05:33 That’s one of the limitations, right?
0:05:38 So if you ask it something that only you, Sam, have in your, in your files and your email,
0:05:42 whatever, that the training model was, I mean, the LLM was never trained on, it’s not going
0:05:43 to know those things.
0:05:44 It doesn’t matter how smart it is.
0:05:46 It’s just information it’s never seen.
0:05:47 So it’s not going to know that.
0:05:48 That’s kind of problem number one.
0:05:50 Problem number two.
0:05:56 So let’s say your website for Hampton was actually on, um, uh, in the training set,
0:05:56 right?
0:06:00 Because it’s on the public internet or whatever, but the training happened at a particular point
0:06:01 in time.
0:06:04 Like they ran the training, ran the training, ran the training and said, okay, we’re done
0:06:05 with the training now.
0:06:07 The machine is done.
0:06:10 Let’s let the customers in right now.
0:06:14 If the website changes, it’s not going to know about those new updates that you’ve made
0:06:17 to your website because the training was done at a particular date.
0:06:19 If completed, it’s kind of training course, right?
0:06:22 So those are the two things we sort of have to remember is that it doesn’t know what it
0:06:23 doesn’t know.
0:06:27 And number two, that the things that did know were frozen at that particular point in time,
0:06:27 right?
0:06:28 So it has a seen new information.
0:06:32 And those are relatively large limitations, right?
0:06:35 So especially if you’re going to use it for business use or personal, it’s like, well,
0:06:39 I’ve got a bunch of stuff that I want it to be able to answer questions about or whatever
0:06:42 inside my company or inside, uh, my own personal life.
0:06:44 How do I get it to do that?
0:06:46 Um, and so here’s the hack.
0:06:48 And this is, this was a brilliant, uh, brilliant discovery.
0:06:54 So what they figured out is to say, okay, let’s say you have a hundred thousand documents
0:06:56 that were never on the internet.
0:06:57 That’s in your company.
0:07:00 It’s all your employee hiring practices, your model.
0:07:01 Here’s how we do compensation.
0:07:02 All of it, right?
0:07:03 It’s like, oh, you have a hundred thousand documents.
0:07:06 And obviously you can’t ask questions about those hundred thousand documents straight
0:07:07 to chat GPT.
0:07:09 It doesn’t know anything about those, never seen those documents.
0:07:14 So this is, and we talked about this two episodes ago, um, this thing called vector embeddings
0:07:17 and RAG retrieval augmented generation.
0:07:20 Um, and I’ll, I recommend you folks go listen to that.
0:07:23 I think it’s a, it’s a, it’s a fun episode, but I’ll kind of summarize it, which is what
0:07:24 you can do.
0:07:27 And what we do is to say, we’re going to take those hundred thousand documents and we’re
0:07:31 going to put them in this special database called a vector store, a vector database.
0:07:36 And what we can do now is when someone asks the question, we can go to the vector store,
0:07:41 not the LLM, go to the vector store and say, give me the five documents out of the hundred
0:07:45 thousand that are most likely to answer this question based on the meaning of the question,
0:07:48 not keywords based on the actual meaning of the question.
0:07:51 So it’s called a semantic search is what the vector store is doing.
0:07:53 So it comes back with five documents.
0:07:58 Let’s just say now, as it turns out, five documents do fit inside the context window.
0:08:01 So effectively we said, okay, well, yeah, it would have been nice.
0:08:04 Had you trained on the hundred thousand documents, but that was not practical because I didn’t
0:08:05 want to expose all of that.
0:08:07 I’m going to give you the five documents that you actually need.
0:08:10 I can just say, give it to you in the context window.
0:08:16 And now, as you can imagine, it does an exceptionally good job at answering the question when it knows
0:08:17 the five documents that should be looking.
0:08:18 You just gave it to them.
0:08:18 Right?
0:08:21 So it’s having this, uh, so we’ll kind of, uh, jump metaphors here.
0:08:25 It’s like hiring a really, really good intern that has a PhD in everything, right?
0:08:27 They went to school, they read all the things, read all the internet.
0:08:31 The intern knows everything about everything that ever was publicly accessible.
0:08:34 They’re trained, show up for the first day of work.
0:08:35 That’s all they know.
0:08:38 They’re not learning anything new and they know nothing about your business.
0:08:41 Now it’s like, okay, well, I know, you know, everything about everything.
0:08:43 I have this question about my business.
0:08:48 Here are five documents that you can read right now and answer my question.
0:08:50 It’s like, oh, I can do that.
0:08:54 I like that analogy, the intern with the PhD and everything.
0:08:55 That’s so much how it is, right?
0:09:02 It’s as helpful and available as an intern, but it’s as knowledgeable as somebody with a
0:09:03 PhD in everything.
0:09:07 Um, and then like you said, you know, my, the, another analogy for that is like, it’s
0:09:11 a store, you have shelf space, which is kind of limited, but they do have a back and you
0:09:15 can always get, send the employee to the back and see if they can find it in the back for
0:09:15 you.
0:09:15 Right.
0:09:17 That’s kind of like what you’re saying, put it in the database.
0:09:20 They can go fetch the specific thing that you’re asking for.
0:09:22 Uh, because you know, you gave it access to the back.
0:09:24 You gave it a badge that lets it go in there.
0:09:29 Have you uploaded all of hub, like, have you figured, first of all, I want to know what
0:09:30 your chat GPT looks like.
0:09:33 I want to know how you use it on a, like, I just want you to just screen share, just like
0:09:37 show me exactly what you do, but also have you uploaded your entire life?
0:09:42 Like, have you uploaded all of HubSpot to chat GPT where you could just ask it any question?
0:09:43 Yeah, multiple times.
0:09:43 Right.
0:09:46 Um, so, and what format, tell me how you did that.
0:09:52 Uh, so I did, so open AI has, um, called this, uh, it’s called an embeddings algorithm that
0:09:56 takes any piece of text, a document, an email, whatever it happens to be, and creates this
0:10:00 kind of point in the high dimensional space, um, called, you know, called a vector embedding.
0:10:03 And, you know, a point in high dimensional space.
0:10:07 So in three dimensional space, physical space that we know of, we think of points being in
0:10:08 three dimensions, X, Y, and Z axis.
0:10:10 Like, oh, here’s where this point is in space.
0:10:13 Uh, high dimensional space, you can have a hundred dimensions.
0:10:14 You can have a thousand dimensions.
0:10:16 You can describe each document as this kind of point in space.
0:10:22 So what I’ve done, so it used to be, um, in the early kind of GPT world,
0:10:25 the number of dimensions you had access to was roughly like a hundred to 200 dimensions.
0:10:27 And so you would lose a lot of the meaning of a document, right?
0:10:28 They would sort of get it right.
0:10:30 It was sort of captured the meaning.
0:10:33 Uh, and then, uh, then we went to like a thousand dimensions.
0:10:39 It’s like, oh, well now it can much more accurately sort of represent, um, and, and capture, um,
0:10:43 a document of kind of arbitrary length and, and be able to find it, uh, give it a prompt
0:10:45 or given some sort of search query.
0:10:50 Uh, and then recently within the last year, we’ve gone, the, the latest algorithm, uh,
0:10:55 from open AI, uh, embeddings algorithm is like 3072, I think, uh, dimensions.
0:10:57 But, but where, where do you do this?
0:11:01 Do you just literally upload it as a project or you, you had to do an API connection?
0:11:02 What did you, how do you actually do this?
0:11:03 I had an API connection, right?
0:11:05 In fact, I’m running the lease.
0:11:06 Let me see where it is now.
0:11:10 And anyone could do this or you have special access because you’re friends?
0:11:11 No, anyone can do this.
0:11:14 The, the, uh, the API for the embeddings model, they have two versions.
0:11:16 They have the 3000 dimension version.
0:11:18 They have a 1000 dimension version.
0:11:22 And is the results of this, like, are you driving a NASCAR and I’m driving like a scooter?
0:11:23 Like, is that the difference?
0:11:28 Like if I just like, for example, uh, what I will do is I’ll just like download my company’s
0:11:29 financials and I’ll upload it.
0:11:32 And then I’ll like explain what my company does.
0:11:34 But the way that you do it is a lot different.
0:11:38 Now, are we talking a massive gap in results that you get versus what I get?
0:11:41 Um, yes.
0:11:44 The short answer is yes.
0:11:48 Uh, and, and the reason is like, so I do, I do that as well in terms of how I’ll describe
0:11:49 the company or whatever.
0:11:50 I try to provide it context.
0:11:52 And that’s why it’s called the context windows.
0:11:55 You try to provide the LLM, uh, context for what you’re asking it to do.
0:12:01 Um, you know, the difference is that, you know, because I can go through like, and by the
0:12:02 way, the richest, and I’m working on a,
0:12:08 kind of nice and weekends project right now, um, that takes, uh, email, uh, which, you
0:12:10 know, so you would be amazed.
0:12:14 Like if you had to write no other words right now, if you did nothing, but say, I’m going
0:12:19 to take all of my emails I’ve ever written, uh, that are still stored and give it, uh, to
0:12:23 a vector store, use an embedding’s algorithm and then use chat GPT to let me kind of answer
0:12:24 questions.
0:12:28 So if I want to say, Oh, I want you to give me a timeline for when we start first started
0:12:31 using hub to name products or whatever, and how’d that come about?
0:12:35 Or what were the winning arguments against doing that versus whatever?
0:12:41 Like it’s shocking how good the responses are when you give it access to that kind of rich
0:12:42 data, right?
0:12:46 Somebody needs to create just like a $10 a month, a single website.
0:12:48 That’s like, Hey, make your chat GPT smarter.
0:12:52 And it’s a website where it’s like, connect your Gmail, connect your Slack, connect your
0:12:52 everything.
0:12:57 I would pay them happily 20 bucks a month to just set this up for me so that my chat
0:13:03 to, to give my chat GPT, like the extra pill that says, you now have access to my data.
0:13:07 Is this because, because you’re talking about like, I have the API to the vector embeddings
0:13:10 and like, well, I have the flux capacitor too, but I don’t know what to do with it.
0:13:10 Right?
0:13:15 Like I need a button on a website with a Stripe payment button that I could just connect the
0:13:15 stuff.
0:13:16 Is it not?
0:13:18 Is there, is there a caveman version of this?
0:13:22 Oh, there’s, I mean, there are, uh, tools out there do, and there are startups working on
0:13:22 it, right?
0:13:23 Uh, there’s two pieces of good news.
0:13:25 One is there are startups working on it.
0:13:29 The challenge here is, uh, not that they’re doing a bad job.
0:13:34 The challenge actually comes down to, uh, if it were a startup and a startup came to you,
0:13:37 it’s like, Oh, we just started last, last week, but we’ve got this thing.
0:13:38 It really works.
0:13:44 Uh, in fact, Darmection, maybe, uh, investor, how willing would you be to hand over literally
0:13:47 your entire life and everything that’s in your email over to this startup?
0:13:51 Like, so part of the challenge we have is that the access control that let’s say you’re
0:13:56 using Gmail, which, uh, a lot of us use when you provide the keys to your Gmail account
0:14:00 to a third party, uh, there is no degree of real granularity.
0:14:02 You can say, Oh, I wanted to read the metadata.
0:14:04 That’s like level one, level two access.
0:14:05 I wanted to read my full email.
0:14:08 And level three is I want it to be able to write and delete emails on my behalf.
0:14:13 But if you wanted to like read like the actual body of the email, you can’t say, I only wanted
0:14:16 to read messages that are from HubSpot.com.
0:14:19 Or I own, I want to ignore all messages from my wife and my family or whatever in the thing.
0:14:21 There’s no way to control that.
0:14:21 Right.
0:14:22 So you sort of have to have a trust.
0:14:27 Is there any product that you would trust right now or that you can recommend that guys
0:14:31 like Sean and I should use as chat GPT add-ons or accelerators?
0:14:38 No, not that I don’t trust them, but it’s like, I wouldn’t trust really anyone right
0:14:39 now with that.
0:14:42 And it’s one of the reasons I sort of run it locally, even though I know these things are
0:14:42 out there.
0:14:47 Um, I predict what’s going to happen is we’re going to have, uh, any of the major players
0:14:49 and you can see this happening already, right?
0:14:53 We see this with, um, you know, you have the ability to create custom GPTs and open AI and
0:14:55 do projects and quad.
0:14:58 You have Google gems, which are essentially like a small baby version of this, right?
0:15:02 That says, Oh, you can upload 10 documents, a hundred documents that it’ll let you ask
0:15:05 questions, uh, against the, what it’s really doing behind the scenes is creating a vector
0:15:05 store.
0:15:07 That’s effectively what it’s, what’s happening.
0:15:14 Um, my expectation is all the major companies, um, will actually have a variation of this,
0:15:18 uh, starting with Google should be the first one because they already have the data.
0:15:25 There is absolutely zero reason why dual Gemini does not let you have a Q and a with your own
0:15:26 email account.
0:15:28 That’s just like insanely stupid, right?
0:15:30 Like I’ll just go ahead and say it.
0:15:32 It’s just, it’s just, there’s something not right with the world.
0:15:36 Uh, when they already have the data and it’s like, and they have the algorithm, they have
0:15:38 Gemini 2.5 pro, which is an exceptionally good model.
0:15:39 Right?
0:15:43 So there you have all the pieces, uh, but have not yet delivered, but I hope it’s a little
0:15:43 distant.
0:15:48 Then tell me and Sean, we’re early adopters, but neither of us are technical.
0:15:51 What can we do to, I want to get it on this baby.
0:15:52 All right.
0:15:53 So give me, give me two weeks.
0:15:53 Here’s, here’s what I’ll be.
0:15:56 Uh, so that’s the one thing I do trust that I trust myself.
0:15:58 Um, I’m, I’m an honest guy.
0:16:03 Uh, I’ll give you like this internal app that I’m building, let you put your Gmail to it.
0:16:06 It’ll go and it’ll run for a day or two days or something like that.
0:16:07 And then you will be amazed.
0:16:08 You will be able to ask questions.
0:16:14 Um, and by the way, like, and the thing I’m like working on now is once you have this,
0:16:15 this capability, right?
0:16:18 Like step one is just being able to do Q and a, right?
0:16:22 It’s like, Oh, just, I’m going to step to like, imagine kind of fast forwarding.
0:16:23 Like it has access to all of your kind of history.
0:16:25 So imagine you’re able to say, you know what?
0:16:30 I’m not doing this by the way, but if I were, it’s like, I want to write a book about HubSpot
0:16:32 and all the lessons learned and all like everything.
0:16:33 It’s all in my email.
0:16:36 Do the best possible job you can writing a book.
0:16:39 If you have questions along the way, ask me, but other than that, write the book.
0:16:40 I think you would be able to write the book.
0:16:41 Wow.
0:16:43 What else are you doing with AI?
0:16:45 So, uh, give me your day to day.
0:16:50 I like, for example, the CEO of Microsoft had this great thing where he goes, I think with
0:16:52 AI, then I work with my coworkers.
0:16:53 And that really shifted the way I worked.
0:16:57 Cause I used to brainstorm or have a meeting to talk about stuff with my coworkers, which
0:17:00 was honestly always like a little disappointing.
0:17:03 I felt like I’m the one bringing the energy and the ideas and the questions, and I’m hoping
0:17:08 that they’re going to, but dude, just sparring with AI first and then taking the kind
0:17:12 of like distilled thoughts to my team of like, here’s how we’re going to execute has been
0:17:13 way better.
0:17:16 Like that little one sentence he said shifted the way I was doing it.
0:17:19 How are you kind of using this stuff?
0:17:19 Yeah.
0:17:20 So a couple of things.
0:17:23 Um, so I’ll let, let’s start at the high level and we’ll drill in a little bit.
0:17:28 So, uh, what we’re used to with, uh, chat GPT, this is sort of your kind of early evolution
0:17:32 of most people’s use is because it’s called generative AI, use it to generate things, right?
0:17:37 Uh, generate a blog post, generate an image, generate a video, generate audio, all those
0:17:37 things.
0:17:39 That’s kind of the generation kind of aspect.
0:17:41 Uh, and that’s part of what it’s good at.
0:17:45 Then you sort of get into the, Oh, but it can also kind of summarize and synthesize things
0:17:46 for me.
0:17:49 It’s like, Oh, take this large body of text, take this blog post, take this academic paper
0:17:51 and summarize it in this way.
0:17:53 Or like, so a seven year old would understand it kind of thing.
0:17:53 Right.
0:17:57 So that’s the kind of step number, um, step number two, step number three.
0:17:59 And we’re going to get into how this is now possible.
0:18:03 Um, is you can do, um, effectively you can take action.
0:18:06 Um, have the LM actually do things for you.
0:18:10 Uh, and I’ve always kind of put it broadly in the kind of automation bucket, like I can
0:18:12 automate things that I was doing manually before.
0:18:15 Uh, and then the fourth thing is around orchestration.
0:18:20 It’s like, can I just have it manage a set of AI agents?
0:18:22 And we’ll talk about agents in a little bit and just do it all for me.
0:18:24 I just want to give it a super high order goal.
0:18:27 It has access to an army of agents that are good at varying different things.
0:18:29 I don’t want to know about any of that.
0:18:31 I just wanted to go do this thing for me.
0:18:31 Right.
0:18:33 And then that’s sort of where we are on the slope of the curve.
0:18:36 Uh, the first three things are possible today.
0:18:38 And work well today.
0:18:38 Right.
0:18:40 So you can generate, as we know, it can generate blog posts.
0:18:41 It could write really well.
0:18:45 Uh, it can generate great images now, including images with text.
0:18:48 It can do great video now with, uh, you know, higher fidelity, higher character cohesion, all
0:18:49 these things.
0:18:53 Uh, Sean, so the thing, the vision you had three years ago when I was on was around creating
0:18:55 the next Disney, the next kind of media company.
0:18:58 You have the tools now, my friend, uh, to finally start to approach that.
0:18:58 Right.
0:19:02 But then you should sort of move into, and this is what we were just talking about, this kind
0:19:03 of synthesis and analysis thing.
0:19:06 This is, okay, this is where deep research kinds of features come in.
0:19:09 It’s like, okay, well, I want you to take the entire of the internet or entirety of what,
0:19:11 uh, Sean has written about copywriting.
0:19:16 And I want you to write a book just for me that summarizes all of that in ways that I enjoy.
0:19:19 Because I like, I like analogies and I like jokes and I like this and I like that.
0:19:22 Write a custom version of Sean Puri’s book on copywriting, right?
0:19:25 That kind of synthesis, um, I think would be, uh, super interesting.
0:19:27 And then automation is now possible.
0:19:28 So agent.ai is one of those things.
0:19:32 There’s other tools out there that says, Hey, I want to take this workflow or this thing that
0:19:34 I do, and I want you to just do it for me.
0:19:38 Give us a specific, what’s a specific, specific automation that you’ve used.
0:19:40 That’s like, you know, useful, helpful, saves you time.
0:19:42 I’ll tell you a couple.
0:19:44 One is around domain names, which is, okay.
0:19:50 So I have an idea for a domain name, um, and I’m going to type words in and these things
0:19:50 exist.
0:19:52 And I’ll tell you the manual flow that I used to go to.
0:19:56 It’s like, okay, first of all, I can brainstorm myself and come up with possible words and
0:19:58 various other words, whatever, here’s the things that I’ll say.
0:19:58 Okay.
0:19:59 Which domains are available?
0:20:03 Absolutely zero of them, uh, that are good that will pop into my mind are like freely
0:20:05 available to kind of just register that no one’s registered before.
0:20:05 Okay.
0:20:06 Fine.
0:20:08 Then I’ll say, okay, well, which ones are available for sale?
0:20:09 Okay.
0:20:10 What’s the price tag?
0:20:12 Is that a fair approximation of the value?
0:20:15 Is it like below market, above market?
0:20:17 We don’t know because there’s no Zillow for domain names yet.
0:20:18 Uh, so create that.
0:20:23 So I have something that automates all of that and says, oh, so you have this particular idea
0:20:27 for this concept, for this business, business, whatever it is, uh, here are names.
0:20:28 You’re the actual price points.
0:20:31 Here’s the ones that I think are below market value, above market value.
0:20:32 Tell me which ones you want to register.
0:20:34 That’s in chat GPT.
0:20:37 No, it’s an agent.ai is where it lives right now.
0:20:42 But now there’s a connector between agent.ai and chat GPT through this thing called MCP, which
0:20:44 you’ll hear about, uh, a bunch if, if you haven’t already.
0:20:49 Um, one thing I want to kind of get out there, just so we keep connecting the dots, um, because
0:20:52 I want, I want everyone to have this framework in their head.
0:20:54 Uh, so we talked about large language models.
0:20:55 It can generate things.
0:20:56 We talked about the context window.
0:21:00 We talked about faking out the context window by saying, oh, we can do this vector database
0:21:03 and bring in the right five documents, stuff them into the context window.
0:21:06 Uh, here’s the other big breakthrough that’s happened.
0:21:10 Uh, I’ll say recently within the last year, year and a half is what’s called tool calling.
0:21:14 And what tool calling is, is a really brilliant idea.
0:21:18 And the tool calling says, okay, well, the LLM was trained on a certain number of things,
0:21:22 but if we had this intern that came in, it would be like saying, okay, well, whatever you
0:21:24 know, you know, but we’re not going to give you access to the internet.
0:21:27 Like that would be stupid, right?
0:21:28 We would give the intern access to the internet.
0:21:31 It’s like, if I ask you something that you weren’t trained on, go look it up, right?
0:21:34 That, that would be like, like thing number one on the first day of work.
0:21:39 And as it turns out, the LLM world, the intern couldn’t, didn’t have access to the internet.
0:21:43 All it had was whatever notes that happened to take during its PhD training and all things,
0:21:43 right?
0:21:47 And so what tool calling allows, and this is a weird, um, weird approach to it, but this is
0:21:48 because of the way LLMs work.
0:21:54 So remember the LLM, it’s architected such that you give it the context window in, it spits
0:21:55 things out.
0:21:55 That’s it.
0:21:58 It doesn’t have, and you can’t reprogram the architecture.
0:22:00 But now all of a sudden we’re going to give you access to tool calling.
0:22:02 So here’s the hack that they came up with.
0:22:08 They said, okay, in the instructions that we give it in the context window, we’re going
0:22:11 to say you have access to these four tools.
0:22:13 And it doesn’t actually have access to the four tools.
0:22:17 It’s that I want you to pretend like you have access to these four tools.
0:22:19 The first tool is this thing called the internet.
0:22:23 And the way the internet works is you type in the query and it will give you some things
0:22:23 back.
0:22:28 You have this other thing called a calculator and you can give it a mathematical expression
0:22:29 and it gives you an answer back.
0:22:32 And you have this other tool that lets you do this and you can have a number of tools.
0:22:34 And so here’s what happens.
0:22:41 In the context window happening behind the scenes, chat GPT, which is the interface right
0:22:44 now that is interacting with the LL, you’re not talking with the LM directly, right?
0:22:49 It gets a prompt and it says, okay, by the way, LLM, I want you to pretend like you have
0:22:50 access to these four tools.
0:22:56 And anytime you need them, when you pass the note back to me, the results, the output, just
0:22:57 tell me when you want to use one of those tools.
0:22:59 All right.
0:23:00 So we give it a query.
0:23:04 It’s like, okay, well, I want to look up like the historical stock valuation for HubSpot and
0:23:07 when it changed as a result of, is there any correlation to the weather?
0:23:09 Is it seasonal or whatever it is, right?
0:23:13 In terms of market cap of HubSpot versus seasonal changes.
0:23:14 All right.
0:23:17 Well, that’s not something you would have access to, but here’s what actually happens.
0:23:17 This is so cool, right?
0:23:22 So the LM gets it and the LM’s in the context window that we gave it.
0:23:23 We gave it instructions.
0:23:25 It’s a pretend like you have these four tools.
0:23:28 One of which is stock price lookup, let’s say, historical stock price lookup.
0:23:34 It’ll pass the output back to the application, not us, and say, and in the output, it says,
0:23:39 oh, please invoke that tool you told me I had access to and look up this result.
0:23:40 I want you to search the internet for X.
0:23:41 What was the weather?
0:23:42 I want you to do this for the stock price.
0:23:45 And then we do that.
0:23:51 We, the ChatGPT application, fill the context window with whatever it is the LM asked for
0:23:52 and then pass it back in.
0:23:57 So the LM effectively has access to those tools, even though it never accessed the internet,
0:24:01 it never accessed the stock market, but it pretended like it had access to it.
0:24:02 And we never see this.
0:24:03 This is happening behind the scenes.
0:24:07 Now, here is the big, massive unlock, right?
0:24:10 Which is, well, everything can be a tool, right?
0:24:13 Now you don’t have to build this kind of vector store or whatever, because you would never
0:24:16 build a vector store of all possible stock prices from the dawn of time.
0:24:18 Now, I guess you could, but then it’s outdated immediately.
0:24:23 Now it’s like, what if we just gave it 20 really powerful tools, including browser access,
0:24:23 to the internet?
0:24:30 Well, that’s like a 10,000, 100,000 times increase in that intern’s capability, right?
0:24:35 And so that’s where our brain should be headed now, which is exactly where the world is headed,
0:24:40 that says, what tools can we give the LM access to that will amplify its ability and cause
0:24:43 zero change to the actual architecture?
0:24:45 Literally, it doesn’t have to know anything about anything.
0:24:47 It’s like, I just want you to pretend that you have access to these tools.
0:24:49 It doesn’t need to know how to talk to those tools.
0:24:50 It doesn’t need to know about APIs.
0:24:52 It doesn’t need any of that stuff.
0:24:57 Cutting your sales cycle in half sounds pretty impossible, but that’s exactly what Sandler
0:24:59 training did with HubSpot.
0:25:06 They use Breeze, HubSpot’s AI tools to tailor every customer interaction without losing their
0:25:06 personal touch.
0:25:08 And the results were incredible.
0:25:11 Click-through rates jumped 25%.
0:25:13 Qualified leads quadrupled.
0:25:16 And people spent three times longer on their landing pages.
0:25:21 Go to HubSpot.com to see how Breeze can help your business grow.
0:25:28 Do you think that, I mean, this is all mind-blowing, and you have an interesting perspective because,
0:25:33 you know, I think three episodes ago that you’re on, you created this thing called Wordle.
0:25:34 Was it Wordle?
0:25:34 Wordplay.
0:25:35 Wordplay.
0:25:37 That does like 80 grand a month.
0:25:39 It was just like a puzzle that you do with your son.
0:25:39 It was amazing.
0:25:46 But now you have new projects, you have agent AI, you have a few other things, but you still
0:25:47 run a $30 billion company.
0:25:55 Do you think that the majority of value creation, like, am I going to, is my stock portfolio going
0:25:58 to go up because I own a basket of tech stocks?
0:26:05 Or is the best way to capitalize as an outsider, obviously, you start a company, or is it investing
0:26:09 in new startups that are using AI or AI-first startups?
0:26:12 Yeah, it’s a good question.
0:26:15 I’m neither an economist nor a stock analyst, but I will say this.
0:26:21 The thing I’m most excited about with AI, and I actually said exactly this in a talk I gave
0:26:26 well before GPT on the inbound stage, and I said, you know, as AI is starting to kind of
0:26:29 come up, it’s not a you versus AI.
0:26:31 That’s not the mental model you should have in here.
0:26:34 It’s like, oh, well, AI is going to take my job because it’s me trying to do things that
0:26:36 the AI is then eventually going to be able to do.
0:26:40 The right mental frame of reference you should have, it’s you to the power of AI.
0:26:43 AI is an amplifier of your capability.
0:26:47 It will unlock things and let you do things that you were never able to do before, as a
0:26:50 result of which it’s going to increase your value, not decrease it, right?
0:26:55 But in order for that to be true, you actually have to use it.
0:26:56 You have to learn it.
0:26:57 You have to experiment with it.
0:27:02 And the only real way to get a feel for what it can and can’t do is you have to do it.
0:27:03 So I’ll give you the very, very simple.
0:27:04 Everyone should do this.
0:27:05 I do this personally.
0:27:12 is that anytime you’re going to sit down at a computer and do something, research, whatever
0:27:17 it is you’re going to do, you should give chat GPT or your AI tool of choice a shot at
0:27:17 it.
0:27:23 Try to describe and pretend like you have access to this intern that has a PhD in everything.
0:27:26 It’s like, okay, well, maybe it doesn’t know anything about me or whatever.
0:27:26 Fine.
0:27:28 So then tell it a few things about you.
0:27:31 But imagine you have access to this all-knowing intern that has a PhD in everything.
0:27:34 Give it a crack at solving the problem that you’re about to sit down and spend some time
0:27:39 on and what you will invariably find, number one, is you’ll be surprised by the number of
0:27:42 times it actually comes up with a helpful response that you would never have expected
0:27:44 it would be even remotely able to do.
0:27:46 Like, how can it do that?
0:27:48 It’s because it has a PhD in everything, right?
0:27:52 And it’s now actually, we’ll talk about reasoning and whether models are actually doing that or
0:27:52 not if we have time.
0:28:00 But so that’s my advice is every day, every day, you should be in chat GPT.
0:28:04 If you’re a knowledge worker at all, it doesn’t actually, you don’t even have to be a
0:28:04 knowledge worker.
0:28:06 And I don’t care what your job is, right?
0:28:10 You could be a sommelier at a restaurant and you should be using chat GPT every day to make
0:28:12 yourself better at whatever it is you do.
0:28:17 And that might be the introduction of that orthogonal skill to bring it back to the, which I never
0:28:17 explained the word orthogonal.
0:28:19 I’ll do it in 30 seconds.
0:28:23 So orthogonal means a line that’s 90 degree intersection to another line.
0:28:27 And the most common use is when we have an X and Y axis, right?
0:28:31 It’s like, oh, the X axis and the Y axis are orthogonal to each other because they have
0:28:32 90 degrees separating them.
0:28:36 The common usage, when you say, oh, that’s an orthogonal concept, it means it’s unrelated.
0:28:37 It’s completely different.
0:28:40 That’s like the Y and X axis are completely independent of each other.
0:28:43 You can say, oh, you can be here on the X axis, but here on the Y axis and they’re not
0:28:44 related to each other.
0:28:48 So that’s what I mean when I say orthogonal concepts or skills or ideas.
0:28:49 Yeah.
0:28:52 Is there anything you disagree with that’s kind of the consensus?
0:28:55 Because a lot of things you’re talking about, like, hey, AI is going to change everything.
0:28:56 It’s super smart.
0:28:57 Agents are coming.
0:28:59 They can do some stuff now, more stuff later.
0:29:03 These are all probably right, but they’re also consensus.
0:29:06 I’m just curious, like, is there anything you disagree with that you hear out there that
0:29:09 drives you nuts where you’re just like, people keep saying this.
0:29:11 I think that’s either wrong.
0:29:12 It’s overrated.
0:29:13 It’s the wrong timeline.
0:29:14 It’s the wrong frame.
0:29:15 It’s whatever.
0:29:18 Is there anything that you disagree with that you’ve heard out there?
0:29:22 I’ve heard variations, two variations I disagree with.
0:29:27 One that I’ve, I think, spent so much time hopefully kind of talking folks out of, which
0:29:29 is it’s just autocorrect.
0:29:30 It’s not really thinking.
0:29:34 And that’s a matter of, like, what do you think thinking is, right?
0:29:39 It’s like, okay, well, if it produces the right output to which we think would require
0:29:45 thought, so I think that is flawed reasoning to say, oh, well, and this often comes from
0:29:49 the smartest people, the most experts in their field, because, oh, it’s really like a stochastic
0:29:49 parrot.
0:29:53 You’ll hear this phrase, which is, it’s like a Paul Billy-driven pattern matching based.
0:29:57 It just so happens that it’s been trained on the internet, but it’s not really like human
0:29:58 intelligence.
0:30:02 And I agree with that phrasing, which is it’s not like human intelligence, but that does not
0:30:06 mean that all it’s doing is sort of mimicking stochastically all the things I’ve read before,
0:30:11 because in order to do what it does, it is a form of creativity different from what we
0:30:12 normally experience.
0:30:15 That’s kind of thing number one that I disagree with.
0:30:20 Thing number two is people are thinking, I both disagree with the, oh, the scaling laws are
0:30:23 going to continue forever indefinitely, that the more and more compute we throw at, the
0:30:26 more knobs we put on the machine, the smarter and smarter it’s going to get.
0:30:29 I think there’s going to be a limit to that at some point.
0:30:30 It’s like nothing goes on forever.
0:30:33 It’s going to asymptotically move towards, we’re going to have to come up with new algorithms.
0:30:36 So that’s GPT can’t be the do all end of all things, right?
0:30:39 There will be a new way, you know, discovered.
0:30:40 So I think that’s going to happen.
0:30:46 But I think the smarter, and I did not say this, other people have said it, the best way
0:30:53 to kind of think about AI right now is as you use it, it’s the kind of truly find, find a
0:30:55 frontier of what it’s incapable of.
0:30:59 It’s like, okay, it can sort of do this thing, but not very well.
0:31:04 If, if that’s the way you describe its response, you are exactly where you need to be, which
0:31:08 is if you can sort of do it right now, sort of, if you have to squint a little bit, it’s
0:31:12 like, ah, well, it’s kind of something, but wait six months or a year, right?
0:31:15 Like it’s, uh, that’s the beauty of an exponential curve.
0:31:19 It gets so better, so much better, so fast, uh, that if it can sort of do it now, it will
0:31:20 be able to do it.
0:31:21 And then it’ll be able to do it really well.
0:31:24 That’s the inevitable sequence of events.
0:31:24 That’s going to happen.
0:31:25 Stan, have you heard this about startups?
0:31:30 There’s like a kind of the smart money in startups believes that the right startup to build is
0:31:33 basically the thing that AI kind of can’t do right now.
0:31:39 That’s the company to start today because you just have to stay alive long enough.
0:31:44 Give it the 12 to 18 month runway that it needs for the thing to go from, eh, didn’t really
0:31:46 work very well to like, oh my God, this is amazing.
0:31:50 But you’ve built your brand, your company, your mission, you’ve, your customer, but you’ve
0:31:54 been building that all along the way and you’re basically just betting you’re going to be able
0:31:56 to surf the improvement of the model.
0:31:57 Dude, by the way, that’s, that’s how I feel about my company.
0:32:02 My company is not related to this, but at all, but in terms of like our operations, we’re like
0:32:07 things are very manual and I’m like, oh my God, once I’m able to finally implement AI
0:32:10 when it can work for this purpose, my profit margins are going to go through the roof.
0:32:14 I mean, that’s how I, that’s how I feel about it, but it, which isn’t entirely related
0:32:19 that Sean, but a little bit, one, one, one thing I’ll plant out there since, uh, this
0:32:20 is my first million.
0:32:23 We, we like talking about ideas at a macro level.
0:32:28 Here’s the entirely new pool of ideas that I think are now available, um, on a trend that
0:32:32 I think is inevitable, which is ad agents get better and better, right?
0:32:37 Um, right now, most of us, when we use, uh, use AI, use chat TPD, uh, we use them as tools,
0:32:38 which is great.
0:32:38 Perfect.
0:32:39 Uh, fine.
0:32:43 Uh, over time, you need to shift your thinking and think of them as teammates.
0:32:46 Think of them as that intern that just got hired, right?
0:32:51 Uh, and, and as a result of that, so let’s, let’s assume for a second, let’s stipulate that
0:32:52 I I’m right.
0:32:55 All we don’t know is how long is it going to take for me to be right is that we’re going
0:32:59 to have effectively digital teammates that are part of all of our teams.
0:33:05 Every company is going to someday have a hybrid team consisting of carbon-based life forms and
0:33:07 these kinds of digital AI, um, AI agents.
0:33:07 Okay.
0:33:12 So if you accept that, the way that’s going to happen is not going to be like, all of
0:33:15 a sudden we one day wake up and every organization now starts kind of mixing them.
0:33:18 What’s going to happen is it’s going to slowly introduce this way.
0:33:21 It’s like, oh, I have this one task, whatever that an agent is better at is real.
0:33:23 It’s reliable enough for the thing.
0:33:24 And the risk is low enough.
0:33:24 I’m going to have it do that.
0:33:25 Right.
0:33:28 Well, we already see elements of that, but here’s, what’s going to happen as a result of
0:33:31 that kind of gradual kind of infusion and adoption of that technology.
0:33:37 Uh, the way to win and the opportunities that get created is like, how do I help the world
0:33:40 accomplish this end state that I know is going to come?
0:33:42 So here, I’ll give you some examples.
0:33:48 Uh, if we were to hire, if you, uh, Sam were to hire a new employee, uh, tomorrow, here’s
0:33:48 what you would do.
0:33:52 You would say, oh, well, I’m going to onboard that employee, spend a couple of days.
0:33:55 I’m going to tell them about the business, uh, whoever’s managing that employee, let’s
0:33:59 say with a direct report of yours, maybe you’ll have a weekly one-on-one or every other week
0:34:04 or whatever that one-on-one will consist of, uh, looking at the work they did, whatever’s
0:34:05 like, oh, over here, you did this or whatever.
0:34:06 And it could be copy editing.
0:34:08 It could be anything, whatever the role happens to be.
0:34:09 You’re going to give them feedback, right?
0:34:11 That’s what you do for a human worker.
0:34:18 All of those things have a direct, literally a direct analog in the agent world, right?
0:34:21 And what we’re doing right now is we’re hiring these agents and expecting them to do
0:34:27 magic, just like if we hired an exceptionally smart, uh, has a PhD in everything employee
0:34:30 and expected them to do magic with no training, no onboarding, no feedback, no one-on-one, no
0:34:31 nothing.
0:34:33 Well, your results are not going to vary.
0:34:37 They’re going to be crap, uh, because you did not make the investment in getting that agent.
0:34:40 Now the, the, the big unlock here.
0:34:43 So whether you’re an HR person or whatever, it’s like figure out, well, what does employee
0:34:45 training look like for digital workers?
0:34:48 What do performance reviews look like for digital workers?
0:34:50 How do we do, how do we do recruiting for digital workers?
0:34:53 How do we like, what, what are all the mechanisms that need to exist?
0:34:55 What is a manager of the future?
0:34:58 What are the new roles that will be created as a result of having these hybrid teams?
0:35:01 It’s like, okay, well now maybe we’re going to need someone.
0:35:06 That’s like the agentic manager, human that knows all the agents that are on their team
0:35:10 or whatever, and has kind of built the skillset, uh, how to do recruiting for their team, uh,
0:35:12 how to do performance reviews, how to do all of that.
0:35:16 But for agents or hybrid teams, um, you know, versus just purely human ones, uh, that, that’s
0:35:19 just a whole other, and we’re going to need the software.
0:35:20 We’re going to need the onboarding.
0:35:20 We’re going to need training.
0:35:21 We’re going to need books for it.
0:35:23 And we’re going to need all of it to kind of adopt.
0:35:26 And it’s going to take, uh, it’s going to take years, right?
0:35:32 It’s not, uh, two years ago, I asked you, is it going to be as bad?
0:35:35 Or I think you said, I asked, is it going to be horrible or is this going to be amazing?
0:35:38 And you said, uh, I saw this with the internet.
0:35:41 Nothing is as extreme as the most extreme predictions.
0:35:44 I listened to you and I trusted you.
0:35:49 Then I actually think knowing what I know now, I’m actually more fearful, uh, than I was
0:35:52 a couple of years ago where I’m like, oh, this is actually going to put a lot of people
0:35:53 out of work.
0:35:56 And, um, it’s maybe not good or bad, but things are going to change.
0:35:58 drastically more than I thought.
0:36:04 And my, so I don’t remember how I phrased the question, but is this going to change the
0:36:09 future more than you thought two years ago or less than you thought two years ago?
0:36:11 Um, has your opinion on that changed?
0:36:14 I still think they’re going to be unrecognizable.
0:36:19 My, my kind of macro level sense, and this is maybe just my inherent, uh, optimism about
0:36:24 things is that it’s going to be kind of a net positive for humanity.
0:36:27 And this is the other thing that, um, you know, lots of people would disagree with me
0:36:27 on this.
0:36:31 Like, oh, well, is this an existential crisis to the species?
0:36:37 Um, and I’ve not said this before, but I’m going to see how it sounds as the words leave
0:36:38 my mouth.
0:36:38 I’m probably going to regret it.
0:36:43 But in a way we are actually, and Sammy, um, Sean, you said this earlier, we’re sort
0:36:45 of producing a new species, right?
0:36:50 So that’s like saying, okay, well, homeo sapiens as they exist, absent AI is likely not going
0:36:50 to exist.
0:36:55 So the way we know the species as it exists today with where we have a single brain and,
0:36:57 and, and, in natural form, you know, four appendages or whatever, maybe that’s going
0:36:58 to be different.
0:37:03 Uh, but I think of that as an extension of humanity, not the obliteration of humanity, right?
0:37:08 That’s the, that’s, you know, human 2.0 or n.0, uh, of the way we kind of think of the
0:37:08 species right now.
0:37:12 So I’m, uh, I think things are still moving very, very fast.
0:37:16 And this is the, this is why I think humans have, uh, issues with exponential curves.
0:37:20 We’re just not used to them when something is kind of doubling or, uh, you know, um, every
0:37:25 end months, it’s hard to wrap our brains around how fast this stuff, uh, you know, can move
0:37:31 things that we thought were like the things we have today, Sam, um, if we had just described
0:37:36 them to someone a year and a half ago, there’s like, ah, well, chat CPT is cool or whatever,
0:37:37 but it’s never going to be able to do that.
0:37:41 And now we’re like, those are like par for the course, right?
0:37:45 Like we can do like, um, things that were literally like, oh, there’s no way, no way.
0:37:48 It’s like, yeah, it’s good at like texts and stuff like that, but that’s because it’s been
0:37:48 trained on text.
0:37:50 Now I can do images.
0:37:53 Well, I can do images, but like video is like 30 frames a second.
0:37:58 That’s like third and generating 30 images per frame of like per second of videos, like all
0:37:58 of that.
0:38:02 It’s like, yeah, but you know, diffusion models, the way they work is because you’re
0:38:03 not going to get, you get a different image every time.
0:38:04 So how are you going to create a video?
0:38:07 Because it requires the same character, the same setting in subsequent frames.
0:38:09 That’s not how the thing is arched.
0:38:10 That’s not how image models were.
0:38:12 And we solved all of those things, right?
0:38:15 Now we have character cohesion, setting cohesion, video generational.
0:38:15 Anyway.
0:38:23 So my answer is it’s exactly, not exactly, but it’s close to like, yep, this is what exponential
0:38:25 advancement looks like.
0:38:28 I’m still of the belief that we’re going to have more net positive.
0:38:31 That is not to say that in the interim, there’s not going to be pain.
0:38:34 And there’s two things I’ll put out there as cautionary, cautionary words.
0:38:40 One is in the interim, anyone that tells you that there’s not going to be job dislocation,
0:38:43 there’s not going to be roles that get completely obliterated, is lying to you.
0:38:44 That is going to happen.
0:38:46 It’s already happening, right?
0:38:49 It’s that there is no world in which that does not occur.
0:38:50 That’s kind of thing number one.
0:38:56 Thing number two, and we didn’t talk about this, but we should have, is that because of
0:39:00 the architecture of how LMs currently work, maybe they’ll figure out a way to do that,
0:39:01 they produce hallucinations.
0:39:05 And that’s just a fancy way of saying it makes things up, right?
0:39:10 And that’s sort of okay, but not okay, because it doesn’t know it’s making it up.
0:39:15 Because of the way the architecture works, it’s like the intern that thinks it’s been
0:39:16 exposed to all there is to know in the world.
0:39:17 It’s like, I know all the things.
0:39:18 You’re asking me a question.
0:39:19 I know I know all the things.
0:39:21 So I’m going to tell you the thing that I know.
0:39:23 It was like, well, yeah, but you didn’t know this.
0:39:27 And what you said is actually, factually, like provably, demonstrably wrong.
0:39:33 And it has absolutely zero lack of confidence in its output, which is fine for some things
0:39:36 if you’re writing a short fiction story or something like that.
0:39:40 It’s not great at all for other things like healthcare related where you need kind of
0:39:41 predictable, accurate responses.
0:39:44 So I think we need to be aware of the limitations around it.
0:39:46 when we’re doing research and things like that.
0:39:52 And the problem is when we have relatively, I’ll say naive, I don’t mean this in a disparaging
0:39:58 way, folks that are naive to a subject area asking ChatGPT for things where it can’t judge
0:39:59 the response, right?
0:40:04 We’re sort of taking it on faith that it’s ChatGPT and our Mesh said it’s got a PhD in everything.
0:40:05 So of course it’s going to be right.
0:40:07 Well, no, it’s often not right.
0:40:12 And it’s kind of up to us to figure out what our kind of risk tolerance is.
0:40:14 It’s like, what is it okay for it to be wrong?
0:40:18 How would I test it for my domain, for my particular use cases?
0:40:23 So you guys know this, but I have a company called Hampton.
0:40:24 Joinhampton.com.
0:40:26 It’s a vetted community for founders and CEOs.
0:40:27 Well, we have this member named Levan.
0:40:32 And Levan saw a bunch of members talking about the same problem within Hampton, which is that
0:40:35 they spent hours manually moving data into a PDF.
0:40:37 It’s tedious, it’s annoying, and it’s a waste of time.
0:40:40 And so Levan, like any great entrepreneur, he built a solution.
0:40:42 And that solution is called Molku.
0:40:47 Molku uses AI to automatically transfer data from any document into a PDF.
0:40:52 And so if you need to turn a supplier invoice into a customer quote or move info from an application
0:40:57 into a contract, you just put a file into Molku and it autofills the output PDF in seconds.
0:41:00 And a little backstory for all the tech nerds out there.
0:41:03 Levan built the entire web app without using a line of code.
0:41:05 He used something called Bubble.io.
0:41:09 They’ve added AI tools that can generate an entire app from one prompt.
0:41:09 It’s pretty amazing.
0:41:13 And it means you can build tools like Molku very fast without knowing how to code.
0:41:18 And so if you’re tired of copying and pasting between documents or paying people to do that
0:41:20 for you, check out Molku.ai.
0:41:23 M-O-L-K-U dot A-I.
0:41:24 All right, back to the pod.
0:41:31 What do you think about this situation where Zuck is throwing the bag at every researcher?
0:41:36 A hundred million dollar signing bonuses, even more than that in comp.
0:41:39 And he’s poaching basically his own dream team.
0:41:41 He’s like, okay, you’re not going to, I can’t acquire the company.
0:41:43 Well, why don’t I go get all the players?
0:41:45 If you can keep the team, I’ll keep the players.
0:41:49 And he’s going after them with these crazy nine figure offers.
0:41:54 A hundred million signing bonus and 300 million over four years, I think is what I saw.
0:41:54 Is that true?
0:41:56 I think that was like the higher, yeah.
0:41:56 So the higher end.
0:42:00 And some people have said there’s even like billion dollar offers to certain people that are
0:42:00 out there.
0:42:02 This is like job offers.
0:42:04 So Dharmesh is like, were you shocked by this?
0:42:07 Because I mean, my reaction to this was that’s bullshit.
0:42:08 First time I heard it.
0:42:10 Then I was like, wait, the source is Sam Altman.
0:42:10 Why would he say that?
0:42:13 And then I was like, okay, that’s insane.
0:42:16 And then an hour later, I was like, wait, that’s actually genius.
0:42:20 Because for a total of 3 billion or something, he can acquire the equivalent of one of these
0:42:23 labs that’s valued at 30, 40, 50, or $200 billion.
0:42:25 What a power play.
0:42:29 I know, obviously, you’re an investor in OpenAI, so maybe you don’t like this.
0:42:31 Maybe you have a different bias here.
0:42:36 But I’m just, from one kind of like leader of a tech company to another, like what’s your
0:42:37 view of this move?
0:42:39 I think it’s one of the crazier moves.
0:42:45 If I had to use one word, I would say diabolical, not stupid, not silly, but diabolical.
0:42:46 And here’s why, right?
0:42:48 This is the, like in the grand scheme of things.
0:42:52 So this is not just a, oh, can we use this technology and build a better product that will
0:42:56 then drive X billion dollars of revenue through whatever business model we happen to have.
0:43:01 There’s a meta thing at play here that says whoever gets to this first will be able to
0:43:05 produce companies with billions of dollars of revenue or whatever, right?
0:43:09 Because that’s, it’s like kind of finding the secret to the universe, the mystery of life
0:43:09 kind of thing.
0:43:14 It’s like, okay, well, whoever wins that and gets there first will then be able to use
0:43:19 the technology internally for a little while and be able to just kind of run the table for
0:43:20 as long as they want.
0:43:22 So there’s, it’s got incalculable value, right?
0:43:27 The upside is just so high that no amount of, like if you can increase your probability even
0:43:31 by a marginal amount, if you had the cash, why wouldn’t you do it, right?
0:43:34 So do you think, A, do you think it’ll work?
0:43:36 Do you think this tactic will work for him?
0:43:38 Do you think he will be able to build a super team?
0:43:41 Is he just going to get a bunch of engineers who now have yachts and don’t work?
0:43:45 Like what’s going to happen when you give somebody a hundred million dollars offers, you put together
0:43:49 this, smash together this team of, I think he’s got a hit list of 50 targets.
0:43:53 And I think like, you know, something like 19 or 20 of them have come on board already.
0:43:56 What’s your prediction of how this plays out?
0:43:58 It feels a little bit like a Hail Mary pass, right?
0:43:59 That’s okay.
0:44:00 They’re going to take this.
0:44:01 It’s like, okay, well, there’s not a whole lot of things we can do.
0:44:03 You know, the chips are down.
0:44:04 I’m going to mix metaphors now too.
0:44:07 But that works sometimes.
0:44:09 It works sometimes.
0:44:10 That’s exactly why people do it.
0:44:12 It’s like, okay, what other option do we have, right?
0:44:13 Like everything else hasn’t worked yet.
0:44:15 So let’s try this thing.
0:44:20 But I think the challenge, I still think it’s a dialogically smart move.
0:44:23 I’m not going to use the word ethics or anything like that.
0:44:24 But here’s the challenge though, right?
0:44:28 If we were having this conversation, we’ll call it two years ago, give or take.
0:44:33 Open AI was so far ahead in terms of the underlying algorithm.
0:44:36 And this is even before ChatGPT hit the kind of revenue curve that it’s hit.
0:44:40 Just raw, the GPT algorithm was just so good and they were so far ahead.
0:44:45 It was actually inconceivable for folks, including me, that others would catch up.
0:44:47 It’s like, okay, well, they’ll make progress.
0:44:48 They’ll get closer.
0:44:50 But then Open AI is obviously going to still keep working on it.
0:44:52 And they’re going to be far ahead for a long, long time.
0:44:54 That’s proven not to be true, right?
0:44:56 We’ve seen open source models come out.
0:44:57 We’ve seen other commercial models come out.
0:44:58 There’s Anthropic.
0:45:02 And they have, by most measures, comparable large language models, right?
0:45:03 Within like one standard deviation.
0:45:04 They’re pretty good.
0:45:06 And sometimes they’re better at some things, worse at others.
0:45:09 But it’s not this single horse race anymore.
0:45:12 So the thing that I’m a little bit dubious of is that even if you did this,
0:45:15 you pull all these people together, like it didn’t
0:45:18 really work for Open AI in the true sense of the word, right?
0:45:21 Like they weren’t able to create this kind of magical thing that it’s like,
0:45:23 okay, maybe they end up doing it somewhere else.
0:45:27 But I think there’s more smart people out there.
0:45:30 The technology has kind of deep-seek proved that you could actually,
0:45:34 and they didn’t actually have an actual innovation in terms of reasoning models
0:45:37 and things like that versus kind of the early generation large language model.
0:45:39 So jury’s still out.
0:45:44 How much better is a $300 million over,
0:45:48 so $100 million a year engineer over like a $20 million engineer?
0:45:51 Is it like, I followed some of these guys on Twitter,
0:45:53 and it was, they’re fantastic follows.
0:45:57 And do you think that their IQ is just so much better?
0:45:58 Or is it because they’ve had experience?
0:46:02 Is it really because they just saw how Open AI works,
0:46:03 and they want that experience?
0:46:05 Are they like, is this like espionage?
0:46:10 What is, how good could a $100 million or $300 million a year engineer be?
0:46:12 Well, that’s the thing, though.
0:46:13 This is software, right?
0:46:17 So this is a, you know, a world of like 95% margins.
0:46:19 So let’s say, yeah, I think part of the value is,
0:46:20 yes, they’re super smart,
0:46:24 but even human IQ asymptotically moves towards a certain ceiling, right?
0:46:26 You take smartest people in the world,
0:46:27 however you want to measure IQ.
0:46:30 And so that doesn’t explain away the value, right?
0:46:31 That’s not that.
0:46:33 It’s not that they’ve seen the inside of Open AI,
0:46:35 and they have some trade secrets in their head
0:46:36 that they can then kind of carry over.
0:46:37 It’s like, oh, here’s how we did it over there,
0:46:39 and here’s how we ran evals,
0:46:41 and here’s how we did, you know, the engineering process.
0:46:42 They’ll have some of that,
0:46:46 because we always carry some amount of kind of experience in our heads.
0:46:48 I think the larger thing,
0:46:51 I think kind of primary kind of vector of value
0:46:54 is they sort of have demonstrated the ability
0:46:56 to kind of see around corners and see into the future, right?
0:46:57 They believed in this thing
0:47:00 that almost no one believed in at the time.
0:47:02 They sort of saw where it was headed,
0:47:03 and they were working at it,
0:47:04 tripping away at it, whatever.
0:47:06 And that’s much rarer than you would think.
0:47:09 For really smart people to do this stupidly foolish,
0:47:11 seemingly stupid foolish thing,
0:47:13 it’s like, you’re going to do what now, right?
0:47:16 And we’re still asking ourselves a variation of that question
0:47:17 that we would have asked three years ago,
0:47:19 except now we have ChatGPT,
0:47:20 and we have the things in it,
0:47:21 and we’re still like,
0:47:23 well, you say that we’re going to have, like,
0:47:24 these kind of digital teammates,
0:47:25 and they’re going to be able to do all these things,
0:47:27 and it can’t even do this simple thing right, right?
0:47:29 Like, we sort of keep elevating our expectations
0:47:31 in what we believe is or is not possible.
0:47:33 They sort of know what’s possible,
0:47:35 and they almost think of what many of us
0:47:36 would consider impossible
0:47:37 as actually being inevitable.
0:47:39 Have you guys, as HubSpot,
0:47:40 have you made any of these offers?
0:47:41 I don’t think so,
0:47:43 but that’s not the game we’re in, right?
0:47:45 So we’re not in that league.
0:47:46 We’re not trying to build a frontier model.
0:47:48 We’re not trying to invent AGI.
0:47:49 We’re at the application layer of the stack.
0:47:51 So we want to benefit from it, right?
0:47:55 We didn’t, in any layer of my entrepreneurial career,
0:47:58 I have not been the guy in the center of the universe
0:47:59 or the company in the center of the universe.
0:48:00 But you’re not like,
0:48:01 oh, man, I met this person.
0:48:03 Like, we need to offer, like,
0:48:05 an NBA contract in order to secure this guy.
0:48:07 No, and there’s a reason for this, right?
0:48:09 It’s like, for the kinds of problems we’re solving,
0:48:11 what’s the, there’s a sports term
0:48:12 about the best alternative to the player
0:48:13 or something like that,
0:48:14 the replacement cost?
0:48:15 More, wins above replacement
0:48:17 is the metric they use in sports.
0:48:19 So, yeah, it’s just not,
0:48:20 it’s not worth it,
0:48:21 given our business model,
0:48:21 given what we do.
0:48:24 I have one last thing on the kind of AI front.
0:48:25 This is one of the things,
0:48:27 answering your question, Sean,
0:48:29 in terms of things I disagree with folks on,
0:48:33 is that there’s a group of people,
0:48:35 very smart, that will say,
0:48:37 oh, well, AI is going to lead
0:48:39 to a reduction in creativity,
0:48:40 broadly speaking, right?
0:48:41 Because you’re just going to have AI do the thing.
0:48:42 Why do you need to learn to do the thing?
0:48:44 And I have a 14-year-old, right?
0:48:45 So it’s like, okay, well,
0:48:47 if he just uses AI to write his essays
0:48:48 and do his homework or whatever,
0:48:50 it’s going to kind of reduce his creativity.
0:48:52 And I understand that particular
0:48:54 kind of line of reasoning that says,
0:48:55 yeah, if you just have it do the thing,
0:48:56 you’re not going to.
0:48:58 But I think the part
0:49:00 those folks are missing
0:49:02 is that, you know,
0:49:04 creativity is kind of,
0:49:05 in the literal sense of the word,
0:49:06 is like, okay,
0:49:07 I have this kind of thing,
0:49:08 idea in my head,
0:49:10 and I’m going to express it
0:49:10 in some creative form,
0:49:11 be it music,
0:49:11 be it art,
0:49:13 be it whatever it happens to be.
0:49:15 And the problem right now
0:49:16 is that
0:49:19 whatever creative ideas
0:49:19 we have in our head
0:49:21 are limited
0:49:23 in terms of how we can manifest them
0:49:24 based on our emerging skill set.
0:49:25 So Sean can have
0:49:27 a song in his head right now
0:49:27 that, like,
0:49:29 he may be composing things in his head,
0:49:31 but until he learns the mechanics
0:49:32 of how to actually play
0:49:33 an instrument,
0:49:34 whatever the instrument happens to be,
0:49:35 there’s no real way
0:49:36 to manifest that, right?
0:49:38 We can’t tap into his brain
0:49:38 and do that.
0:49:40 So in my mind,
0:49:42 AI actually increases creativity
0:49:43 because it will increase
0:49:44 the percentage of ideas
0:49:46 that people have in their heads
0:49:47 that they will then be able
0:49:47 to manifest
0:49:48 regardless of what their skills
0:49:49 are or not.
0:49:51 And I love that.
0:49:51 So my son,
0:49:53 he’s a big Japanese culture fan,
0:49:54 big manga fan,
0:49:57 Japanese comic books and anime.
0:50:00 And so he’s an aspiring,
0:50:02 you know, author someday.
0:50:03 And what he can do now, right,
0:50:04 and he’s been able to do this
0:50:05 for years,
0:50:05 which is,
0:50:07 so he’s always had,
0:50:07 again,
0:50:08 he likes fantasy fiction as well.
0:50:09 So he’s had these ideas
0:50:10 for writing things,
0:50:12 but he lacked the writing skills.
0:50:13 He doesn’t know about character development,
0:50:14 doesn’t know about any of these things.
0:50:16 So what he uses ChatGPT for
0:50:17 is he’s got this,
0:50:17 like,
0:50:18 2,000 word prompt
0:50:20 that describes his fictional world.
0:50:21 Here are the characters.
0:50:22 Here’s a power structure.
0:50:23 Here are the powers people have.
0:50:24 Here’s what you can and can’t do.
0:50:27 And then the way he tests the world
0:50:28 is he turns it into a role-playing game.
0:50:29 It’s like,
0:50:29 okay,
0:50:31 I’m going to jump into the world.
0:50:32 Now you, ChatGPT,
0:50:33 I’m going to do this.
0:50:33 Tell me what happens.
0:50:34 Oh, this happened.
0:50:35 Okay, now I’m going to do this.
0:50:36 Okay, well,
0:50:37 now you’ve got this power.
0:50:38 And so it will sort of
0:50:39 kind of pressure test
0:50:40 kind of his world.
0:50:41 And so that’s an expression
0:50:42 of his creativity
0:50:43 because the world
0:50:44 was sitting in his head,
0:50:45 but now he can actually
0:50:46 share that with friends.
0:50:48 Maybe turn that into a book someday
0:50:48 because it’s going to take
0:50:49 the ideas that he has
0:50:51 and hopefully in the meantime,
0:50:53 he will kind of develop
0:50:54 some of those foundational skills,
0:50:54 but he doesn’t have to wait
0:50:56 until like 12 years
0:50:56 of writing education
0:50:58 before he can take this idea
0:50:58 as a child.
0:51:00 He has lots of creativity,
0:51:02 but as a practitioner,
0:51:03 most of those things
0:51:03 that he would love
0:51:04 to be able to manifest
0:51:05 in the world,
0:51:07 he has nothing close
0:51:08 to the skills required,
0:51:09 whether it’s drawing
0:51:10 or writing or anything.
0:51:11 So I think that’s what
0:51:13 AI can help us kind of elevate.
0:51:14 And once again,
0:51:16 we have to use it responsibly,
0:51:17 but it should be able
0:51:18 to elevate our skills.
0:51:19 I want to show you guys
0:51:22 an example of this real quick.
0:51:24 So I had this idea
0:51:25 not long ago,
0:51:25 a couple of weeks ago
0:51:29 of creating a game
0:51:30 using only AI.
0:51:32 So I don’t know
0:51:33 if you guys ever played
0:51:34 the Monkey Island games
0:51:36 from like when I was a kid.
0:51:37 I played Monkey Island.
0:51:38 It was an incredible game.
0:51:39 It’s got basically
0:51:40 this guy wants to be a pirate.
0:51:41 It’s like this very funny,
0:51:43 but like 8-bit art style game.
0:51:45 And so I created a version of that
0:51:47 called Escape from Silicon Valley.
0:51:48 I didn’t create the whole game,
0:51:49 but I create like the art,
0:51:50 but like check this out.
0:51:52 So I go into AI
0:51:53 and I basically start
0:51:54 creating the game art.
0:51:55 And so it’s like the story
0:51:57 is basically like deep in San Francisco.
0:51:58 The year is 2048.
0:52:00 The block is starting
0:52:01 his third term in office.
0:52:04 You know, Nancy Pelosi passes away,
0:52:06 the richest woman on earth.
0:52:07 And then, you know,
0:52:08 Elon is promising
0:52:09 that self-driving cars
0:52:10 are coming really, really soon
0:52:11 for real this time.
0:52:12 And here you are,
0:52:13 you’re this character
0:52:16 and you’re in the opening AI office.
0:52:17 And basically the idea is like-
0:52:18 Oh, Charlie, look at that.
0:52:19 What’s that?
0:52:20 Look at the Charlie bar.
0:52:22 Yeah, yeah, exactly.
0:52:23 I was putting in some references
0:52:24 to like, you know,
0:52:24 stuff that I thought was,
0:52:25 it would be cool.
0:52:27 That is so cool.
0:52:27 What did you use
0:52:28 to make those images?
0:52:29 So that right there
0:52:31 was just ChatGPT
0:52:33 and the Journey mix.
0:52:34 I tried using, you know,
0:52:35 Scenario and a couple other
0:52:36 like game-specific tools.
0:52:37 Like check this out.
0:52:38 So like I created
0:52:39 all these like technical characters.
0:52:40 So it’s like I create
0:52:41 Zuck and Palmer Luckey
0:52:42 and like Chamath
0:52:43 and Elizabeth Holmes in jail.
0:52:44 Oh, that is awesome.
0:52:45 And I had it basically
0:52:46 write the scenes
0:52:47 for the levels with me,
0:52:48 like write the dialogue with me,
0:52:50 create the character art.
0:52:51 Dude, that’s like sick.
0:52:52 Why didn’t you do that?
0:52:55 Well, because I did the fun part
0:52:56 in the first two weeks
0:52:57 where I was like,
0:52:58 oh, the concept,
0:52:59 the levels,
0:53:01 the character art,
0:53:01 the music,
0:53:02 seeing what AI could do.
0:53:04 But then to actually make the game,
0:53:06 the AI can’t do that.
0:53:07 And so I was like,
0:53:08 oh, now I need to like,
0:53:10 I mean, people who build games
0:53:11 spend years building it.
0:53:11 It’s like, oh,
0:53:12 this is like minimum
0:53:13 six to 12 months
0:53:14 doing this like very,
0:53:15 very arbitrary project.
0:53:17 But I still love the idea
0:53:18 and I’m going to like
0:53:20 package up the whole idea.
0:53:22 Darmesh, last question.
0:53:23 Just really quick,
0:53:24 like you,
0:53:26 where do you hang out
0:53:27 on the internet
0:53:29 that we and the listener
0:53:30 can hang out
0:53:31 to stay on top
0:53:32 of some of this stuff?
0:53:33 Like are there,
0:53:34 like who’s a reputable
0:53:35 handful of people
0:53:36 on Twitter to follow
0:53:37 or reputable websites
0:53:38 or places to hang out at?
0:53:40 That’s interesting.
0:53:41 So I spend most of my time
0:53:44 on YouTube,
0:53:45 as it turns out.
0:53:49 And I sort of give into the,
0:53:50 give into the vibe,
0:53:51 so to speak,
0:53:52 and let the algorithm
0:53:52 sort of figure out
0:53:54 what things I might enjoy.
0:53:56 It gets it right sometimes,
0:53:57 it gets it wrong sometimes.
0:53:58 So it’s a mix of things.
0:54:01 But the person that I think,
0:54:03 if you want to kind of get deeper
0:54:04 into like understanding AI,
0:54:05 there’s a guy named,
0:54:06 Andre Karpathy,
0:54:07 I don’t know if you’ve
0:54:08 come across him.
0:54:09 Just search for Karpathy.
0:54:10 Dude,
0:54:10 you don’t want to know
0:54:11 how I know,
0:54:12 like I get so many ads
0:54:14 that says like Andre Karpathy
0:54:16 said this is the best product
0:54:17 or Andre Karpathy
0:54:18 showed me how to do this,
0:54:19 now I’m going to show you.
0:54:20 Like I don’t even know
0:54:21 who Andre is
0:54:22 other than ads
0:54:23 run his name
0:54:24 to promote him.
0:54:25 Yeah, I mean he’s
0:54:27 one of the true OGs
0:54:27 in AI,
0:54:28 but he has that
0:54:30 his orthogonal skill
0:54:30 or one of them,
0:54:31 I think he’s got like nine,
0:54:33 he’s probably like a nine tool
0:54:33 player of some sort,
0:54:35 but he’s able to really
0:54:37 simplify complicated things
0:54:39 without making you feel stupid,
0:54:39 right?
0:54:41 So he’s not talking down to you.
0:54:41 He’s like,
0:54:42 okay,
0:54:43 like here’s how we’re going
0:54:43 to do this.
0:54:44 We’re going to kind of build it
0:54:45 brick by brick
0:54:46 and you’re going to understand
0:54:48 at the end of this hour and a half
0:54:49 how X works,
0:54:49 right?
0:54:51 and he’s amazing.
0:54:52 So that would be one.
0:54:53 So him,
0:54:54 any other YouTubers
0:54:55 or Twitter people or blogs?
0:54:56 On the business side,
0:54:56 actually,
0:54:58 like Aaron Levy from Box
0:54:59 is actually very,
0:55:00 very thoughtful on the,
0:55:01 if you’re in software
0:55:02 or in business
0:55:04 and the AI implications there,
0:55:04 I think he’s really good.
0:55:06 Hiten Shah,
0:55:07 who you both know
0:55:08 now at Dropbox
0:55:09 through the acquisition,
0:55:11 has been on fire lately
0:55:12 on LinkedIn.
0:55:14 So he’s one I would go back,
0:55:15 especially for the last
0:55:16 like three,
0:55:16 four months
0:55:18 and read all the stuff
0:55:18 he’s written.
0:55:19 I think he’s on point
0:55:19 on the app.
0:55:21 Those are awesome.
0:55:21 Darmash,
0:55:22 thanks for coming on.
0:55:23 Thanks for teaching us.
0:55:24 You’re one of my favorite teachers
0:55:26 and entertainers.
0:55:27 So thank you for coming on, man.
0:55:29 My pleasure.
0:55:30 It was good to see you guys.
0:55:30 It was fun.
0:55:31 Likewise.
0:55:31 Thank you.
0:55:32 That’s it.
0:55:32 That’s the pod.
0:55:36 I feel like I can rule the world.
0:55:38 I know I could be what I want to.
0:55:40 I put my all in it
0:55:41 like no day’s off.
0:55:42 On the road,
0:55:42 let’s travel,
0:55:44 never looking back.
0:55:44 All right,
0:55:44 my friends,
0:55:46 I have a new podcast
0:55:47 for you guys to check out.
0:55:47 It’s called
0:55:49 Content is Profit
0:55:50 and it’s hosted by
0:55:52 Luis and Fonzie Cameo.
0:55:53 After years of building
0:55:55 content teams and frameworks
0:55:56 for companies like Red Bull
0:55:57 and Orange Theory Fitness,
0:55:58 Luis and Fonzie
0:55:59 are on a mission
0:56:00 to bridge the gap
0:56:01 between content
0:56:02 and revenue.
0:56:03 In each episode,
0:56:03 you’re going to hear
0:56:04 from top entrepreneurs
0:56:05 and creators
0:56:06 and you’re going to hear them
0:56:07 share their secrets
0:56:07 and strategies
0:56:09 to turn their content
0:56:09 into profit.
0:56:11 So you can check out
0:56:12 Content is Profit
0:56:13 wherever you get
0:56:14 your podcasts.

0:00:07 The energy grid and electrical grid of the future, it’s not just going to be the dichotomy of generation, transmission, and storage.
0:00:12 This sort of next generation of what the grid looks like is going to be in a much more decentralized way.
0:00:14 Why are delivery costs such a big problem?
0:00:20 The grid is aging now and brittle. The workforce has aged out.
0:00:24 Should we just leapfrog the grid? I need this power now, today.
0:00:27 The United States needs to get better at megaprojects.
0:00:29 Things that are a billion dollars, things that are at scale.
0:00:35 There is no safety, there is no national defense, there is no national security without a reliable electrical grid.
0:00:40 U.S. energy usage per capita peaked in 1973.
0:00:42 Since then, it’s been flat.
0:00:46 Meanwhile, China’s per capita energy use has grown ninefold.
0:00:54 Today, with AI, EVs, manufacturing, and data centers demanding more power than ever, America’s electrical grid is buckling.
0:00:57 We haven’t just underbuilt it, we’ve forgotten how to build it.
0:01:06 In this episode, I’m joined by A16Z general partners David Yulevich and Aaron Price-Wright and investing partner Ryan McIntosh from the American Dynamism team.
0:01:11 We talk about how the U.S. energy system broke, why fixing it is about more than megawatts,
0:01:15 and what it’s going to take from new tech and talent to faster permitting and smarter software.
0:01:25 As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax, or investment advice,
0:01:32 or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.
0:01:37 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
0:01:45 For more details, including a link to our investments, please see A16Z.com forward slash disclosures.
0:01:53 U.S. energy peaked in 1973 in terms of per capita usage.
0:01:56 China’s has increased ninefold over that same time period.
0:02:00 We have some reasons to be optimistic now that things have started to change or will change further.
0:02:02 Why don’t you give some context there?
0:02:04 What’s happened and why should we be excited about what’s coming forward?
0:02:09 The history of the grid in the United States was build big power plant industry formed around it.
0:02:12 The grid grew incredibly fast through the 20th century.
0:02:15 Then around the 80s and 90s, things started slowing down.
0:02:19 And then through the early 2000s, the grid effectively froze in the United States.
0:02:25 A big piece of that was a lot of the energy generation, a lot of the manufacturing, a lot of sort of heavy industry moved to Asia.
0:02:29 And so for the last 20 years, effectively, the grid has ossified.
0:02:32 We forgot how to build new power plants.
0:02:38 We forgot how to build new power projects, new loads, sort of large data centers, large factories, large megaprojects.
0:02:41 And you say we forgot, were we not allowed to, or we actually just lost the know-how?
0:02:42 We were allowed to, but we lost the skill set.
0:02:45 And I think you can see it in more extreme examples with nuclear power plants.
0:02:47 All of that sort of transition happened decades before.
0:02:54 But basically, the grid itself, the grid operators, forgot how to plan, how to move quickly, how to do it cheaply.
0:02:57 And so now we’re at this point in time where we are reshoring.
0:03:00 And we are bringing back manufacturing, we are bringing back data centers.
0:03:06 And there’s this highly concentrated demand, and it’s now, now, now at sort of any price, but they cannot move fast enough.
0:03:07 And so that’s what we’re seeing today.
0:03:10 We talk about data centers and the grid being inflexible to this.
0:03:12 It’s playing catch up.
0:03:16 We need to do a lot of the growth that happened in China and bring this here and do it incredibly fast.
0:03:20 How did this forgetting happen, and how can this relearning happen or this retraining happen?
0:03:22 It’s a good question.
0:03:24 I think a lot of it’s like a workforce issue.
0:03:25 I think a lot of it’s a policy issue.
0:03:39 I think the United States, historically, was a bunch of regulated utilities, sort of the top-down, big thermal power plant, big transmission lines connecting to substations, then distribution lines going to individual factories, homes, things like that.
0:03:45 And I think some of the newer technologies don’t necessarily benefit from scale in the same ways that these large thermal plants typically did.
0:03:50 And so this sort of next generation of what the grid looks like is going to be in a much more decentralized way.
0:03:53 So there’s also an element of relearning of what is the grid actually?
0:03:57 Is the grid these large sort of power systems and large infrastructure projects?
0:04:04 Or does it look like a lot more decentralized way where we can eliminate a lot of the wires in between, things like delivery costs, which have increased exponentially?
0:04:07 And can we do it in a more dynamic and flexible way?
0:04:10 So things like solar and batteries, they don’t need to be massive.
0:04:11 You can put them anywhere.
0:04:12 You can put them next to load.
0:04:16 And so this is also sort of an element that grid operators are thinking through.
0:04:22 How do we do that while also managing frequency, voltage, things like that, without causing sort of a grid to go down?
0:04:23 So there’s a lot of challenges.
0:04:28 Well, if you think about what our grid is, I mean, it’s a piece of technology that was designed about 100 years ago.
0:04:33 And very little technology on the grid has changed in those 100 years.
0:04:36 And you look at why are delivery costs such a big problem.
0:04:38 Grid is at capacity.
0:04:42 Getting a new project onto the grid today, you know, you sign up for interconnection, it could take a decade.
0:04:46 There’s a backlog of 20 plus years to get a new transformer.
0:04:51 The transformer technology we’re using today is kind of bananas if you actually look at what makes a transformer.
0:04:58 First of all, there’s one company that makes these, and there’s one plant in the U.S. that produces the right type of steel that you need in order to make these transformers.
0:05:03 And it’s 100-year-old tech, and it’s like the wait list for transformers is insane.
0:05:12 So I think we’re getting to the point in demand starting to rise again and the calcification of grid technology where it’s like should we just leapfrog the grid?
0:05:15 Like do we really need to wait in line and wait for this to catch up?
0:05:17 I think there’s like two versions of how you do that.
0:05:23 One is how do you get power gen and power storage essentially as close to demand as possible?
0:05:34 And that’s a problem for new tech to really help solve because we’re talking about instead of these like mega projects that we’re used to building, well, not used to building anymore, like massive nuclear plants, massive new natural gas plants, etc.
0:05:40 We’re talking about much smaller and more distributed sources of power bypassing interconnection altogether in many cases.
0:05:48 We’re seeing that as a pretty big trend with data centers as data centers are just building power directly on site and co-locating power with the data center because they’re like, I can’t wait.
0:05:52 Microsoft’s like, I can’t afford to wait 10 years to get an interconnection with the grid.
0:05:54 I need this power now today.
0:05:59 So how do you get power more tightly coupled with the load that it’s actually going to serve?
0:06:10 And that’s a really interesting problem for tech also from a software perspective because if you get generation, storage, and usage all co-located very closely together, like that’s a very good problem for AI to solve, like reinforcement learning.
0:06:14 Stick that in there and suddenly you get massively efficient systems that you couldn’t get at grid scale.
0:06:20 I think an interesting point to add on to that is that there’s very little visibility into the grid itself.
0:06:29 So like they understand sort of power plants are operating or not, but especially at sort of the distribution level, the things, the power lines you might see outside your home, there’s very little understanding of what’s actually going on there.
0:06:35 And so there’s like a reluctance, especially when you have things like net metering where I’m sending from my home a battery back to the grid.
0:06:37 Things get incredibly complicated.
0:06:44 And so the grid operators don’t have a very good understanding of when can they allow new projects to go online, how much power, when to actually cut people off.
0:06:53 And so there’s a lot of these policies, interconnections, sort of the general term, but like states like Texas have much more lenient policy of you can build wherever you want.
0:06:55 If we need to cut it off from the grid, we’re going to do so.
0:06:57 And so it’s sort of this connect and manage approach.
0:07:09 Whereas other states, like they will do these incredibly long feasibility studies in like a variety of sort of scenarios with like the entire grid is at peak capacity, but they want to make sure this specific project can stay online 24-7.
0:07:13 So that ends up creating these massive delays of being able to study every single possibility.
0:07:16 So there’s a lot of policy approaches here as well.
0:07:27 And there’s a bunch of these technologies called grid enhancing technologies, which are effectively like, you know, an average power line might be used at 50% capacity, but it needs to be designed for the peak capacity for the summer when everyone has their AC on.
0:07:31 And so there’s a lot of sensors or other technology that could be placed there.
0:07:35 So you have a much more dynamic view of what our infrastructure actually was looking like.
0:07:39 And so when we have these new technologies, then we can much more efficiently use the infrastructure we have.
0:07:42 What are your reactions to this conversation thus far?
0:07:45 Where are some areas you’re particularly excited about or reasons to be optimistic?
0:07:57 Well, I think the reason we’re having this conversation is we’re touching on a bunch of these topical themes, which is that we’re in a moment in time where, exactly like Ryan said, the grid is aging now and brittle.
0:07:59 The workforce has aged out.
0:08:01 We’ll talk about that more, I think, in a minute.
0:08:14 But we had to go out and hire and train entire specialized crews, specialized people that work with cement and concrete, specialized people that work with steel to go build the large Vogel reactors in Georgia.
0:08:17 We put them on Vogel reactors three and four.
0:08:18 We turned them on.
0:08:19 Huge win.
0:08:22 And then those people that went back to building highways or like bridges or something else.
0:08:31 And like instead of just going and put them on Vogel like five, six, seven, eight, nine, ten and building just like this massive crescendo of nuclear power, we just put these people back into the general workforce.
0:08:33 And so we’re not learning our lesson there in the workforce.
0:08:51 And at the same time, we have this insatiable thirst for energy, whether it’s EVs, whether it’s data center compute for AI, or just generally a shift toward more and more consumption of electricity, or even just like the reshoring and manufacturing, all these things that are just very, very electron heavy.
0:09:01 At the same time that we’re seeing this, you know, what Aaron brings up to me is a piece that we hardly ever talk about, which is resiliency and not having people be as dependent on the,
0:09:03 the interconnectedness of the grid.
0:09:15 People that you deploy solar, you know, we talk about like distributed compute for those of us that are in the tech world and like how important it is to like have distributed compute and have networks be able to suffer and survive through segmentation things.
0:09:17 But like the grid is very interdependent.
0:09:22 Even in the US, there’s really only a few major regions that can segment themselves off.
0:09:34 But when you deploy solar or you deploy batteries, or you deploy an SMR reactor or your own power generation on site for your own data center, you don’t have to worry about how brittle the grid is because you’re fairly resilient from it.
0:09:44 And I think that’s a component is that the energy grid and electrical grid of the future, it’s not just going to be the dichotomy of generation, transmission and storage.
0:09:52 But as Aaron brought up, you might do all three of those things in the same place and not have to worry about how robust the grid is or how capable the grid operators are.
0:09:56 And I think that’s a dimension that was never important to people before, but it’s important today.
0:10:06 And you can certainly imagine if you’re the military, you certainly care about having reliable access to power at all your forward operating bases and even at home at your home military bases.
0:10:09 Like you just cannot lose your ability to have electricity.
0:10:11 And so I think all these things are just coming together at once.
0:10:14 And it’s really exciting moment in time.
0:10:33 And I think it’s buoyed by the fact that we’re also at this sort of technology inflection point where AI can help some of these things, not just be a consumption driver, but even be an enabler and facilitating more efficient use of electricity, better monitoring of the grid, better ways to even go through the regulatory and permitting process, which is onerous for many cases.
0:10:42 Building on that, I think Texas, literally today, we’re recording this during a massive heat wave that’s affecting most of the eastern and southern United States.
0:10:59 And if you compare the grids of Texas with New York, Texas famously, historically, had massive grid failures several years ago when a big heat wave came through, the grid couldn’t keep up with all the air conditioners that were going on, and people saw massive power outages.
0:11:00 Everyone was really mad.
0:11:02 People were like, oh, ERCOT doesn’t work.
0:11:03 DREG doesn’t work.
0:11:05 And what has Texas done in the couple of years since that happened?
0:11:09 They have absolutely flooded the grid with solar capacity.
0:11:13 Texas has doubled their solar capacity in the last approximately three years.
0:11:17 And with that, they’ve just deployed thousands of batteries.
0:11:26 One of our portfolio companies, Base Power, is one of the players here, but there’s many battery power companies deploying all across Texas to provide storage for that solar power.
0:11:38 And if you look at the performance of the Texas grid versus the performance of the New York and surrounding area grid during this heat wave, I must have seen 10 news articles this morning about how well Texas grid has done.
0:11:45 The elasticity and ability to react to very quick changes in demand without having to change kind of baseload power.
0:11:50 Like, you can’t build a new natural gas plant or a new nuclear reactor overnight.
0:11:53 But solar is just so insanely cheap.
0:11:58 Like, it’s basically having a giant, massive, huge nuclear reactor in the sky that will go forever.
0:12:00 And Texas isn’t a green state.
0:12:01 This isn’t a political issue.
0:12:11 But it’s like, why aren’t we deploying the world’s cheapest form of power literally everywhere we possibly can and then just putting batteries everywhere?
0:12:12 Like, there just should be batteries everywhere.
0:12:19 It’s bananas to me that batteries as a topic has, like, recently gotten caught in the sort of political crosshairs.
0:12:23 We really, as a society, need to be good at power storage and batteries.
0:12:25 Like, this shouldn’t be a controversial topic.
0:12:27 We invented the lithium-ion battery.
0:12:42 And yet today, if you want to buy a battery, whether it’s for a drone or for the grid or for your car or for whatever it is, like, you’re either buying a battery made in a lights-out factory in China or you’re buying a battery produced in Vietnam by a Chinese company.
0:12:45 And, like, there’s no meaningful effort in the U.S. to change that.
0:12:54 And I think that this is a really critical problem, not just to manage power load on the grid, but for power for all of the things that we need to power the next generation of innovation in the United States.
0:13:03 I think we’d be hard-pressed on the American dynamism team to think of a company that we’ve met with an interesting technology in the last two years that doesn’t have a battery in it somewhere.
0:13:08 So, as a country, we need to be investing in battery technology and battery manufacturing.
0:13:21 By the way, if China decides that whatever your company is doing that’s using batteries doesn’t align with what they like or they want to punish you, being cut off from being able to buy batteries from China is incredibly punitive to a company.
0:13:23 And we’ve certainly seen that happen with some of our startups.
0:13:31 And then you find out quickly that the ability to procure and source batteries from places that are not in China is very difficult.
0:13:39 If you extrapolate that out to what would happen to our whole country if we just were unable to buy batteries from China, it could be catastrophic in a very short period of time.
0:13:49 Just to add on to a quick point on the grid side of batteries, if the rest of the country, which is presumably watching what’s going on in ERCOT, which is the grid operator in Texas,
0:14:02 if Texas can prove that you can deploy these sort of decentralized distributed energy resources and to sort of flatten these peaks, provide more resiliency and ultimately lower price of electricity, then every state should go and do this.
0:14:07 There’s a very complex web of deregulated and regulated entities when it comes to the grid.
0:14:13 Of course, there are a lot of different policy and workforce and political reasons why not everywhere is this decentralized world.
0:14:18 And it’ll probably be more complex than just these deregulated energy-only markets that Texas works with.
0:14:23 But I think this is going to be very obvious if it isn’t obvious already.
0:14:29 And I think the United States needs to move incredibly fast to make this happen and hook up batteries, solar panels, make it easier and cheaper to do it.
0:14:33 Even co-location for large loads is still a very politically fraught issue.
0:14:35 Utilities are pushing against this.
0:14:38 It’s still really hard to hook up solar and batteries to your home.
0:14:43 I think it’s actually cheaper to put residential solar on your home in Germany than in the United States.
0:14:46 And that’s largely a permitting, largely an installation issue.
0:14:47 That’s crazy.
0:14:48 That should not be the case.
0:14:51 Erin, I believe the quote in your college yearbook was,
0:14:52 drill, baby, drill.
0:14:57 How do you think about your sort of love for oil and gas with other sources of energy?
0:14:59 Oh, my parents will be shaking their heads if they hear this.
0:15:04 I think, broadly speaking, our approach to energy in the U.S. just needs to be yes and.
0:15:11 You look at the sort of atrophy of our power build-out over the last 30, 50, whatever, you know,
0:15:14 you name your time frame years compared to, let’s say, China.
0:15:19 And if we want to accomplish the goals that we’ve set out as a society to accomplish over the next decade,
0:15:20 like, we need more power.
0:15:22 And it’s a matter of yes.
0:15:25 And I think solar and batteries, extremely important.
0:15:29 And D, you should talk more about the exciting things that are happening around nuclear.
0:15:32 But, like, there is a place for oil and gas.
0:15:35 Like, I cut my teeth at Palantir working in oil and gas.
0:15:37 My husband worked in oil and gas.
0:15:40 Like, the first check I wrote at A16Z isn’t an oil and gas company.
0:15:43 So, this isn’t me coming with a particular agenda around carbon.
0:15:47 This is me coming and realizing that, like, we basically need every tool in our toolkit.
0:15:54 And we should be using technology to deploy whatever makes most sense, wherever it makes most sense at scale.
0:15:58 If we’re talking, like, energy mix of where we’re at today and where do we think we’re headed,
0:16:05 if I were to make, like, a personal bet, solar batteries are just the ability to be incredibly cheap and deploy incredibly fast.
0:16:07 Spin up and spin down.
0:16:07 Yeah.
0:16:09 And I think that already is a way, but I think that will continue.
0:16:12 But I think to be very clear is that you need all different types of energy.
0:16:15 You’re going to need true sort of baseload, dispatchable power.
0:16:16 It’s going to be gas.
0:16:17 It’s going to be nuclear.
0:16:18 It’s going to be geothermal.
0:16:20 It’s going to be a lot of hydro as well.
0:16:25 And I think as you attach more of these sort of renewable resources or these non-reliable resources,
0:16:28 while they’re incredibly cheap and works most of the time,
0:16:34 this long-tail risk, once you get to, like, 50% to 75% of the grid, is going to become very, very expensive.
0:16:36 You need a lot more battery backup, things like that.
0:16:39 And so I think it’s going to be very complex and it’s going to be different for many different regions.
0:16:43 But certainly it’s not all of any given resource.
0:16:50 Yeah, when you look at, like, the changing nature of load over the next decade, some of that is going to come from data centers.
0:16:51 Some fraction.
0:16:57 I would say it’s probably overstated how much data centers contribute to the growing load in the United States over the next decade.
0:17:00 Data centers generally are baseload.
0:17:05 If you’re training a model, you’re largely using a dedicated amount of power for the long term.
0:17:08 Maybe there are some fluctuations if you’re doing more inference.
0:17:11 But I would generally say, like, data centers represent baseload.
0:17:13 But then you also have things like electric vehicles.
0:17:15 You have things like heat pumps and air conditioners.
0:17:20 You have industrial autonomy, which may or may not be running 24-7.
0:17:24 So you’re going to have some increase in the base level of power we as a society need.
0:17:29 But continuing to increase the size of the peaks and troughs of how we use energy on a day-to-day basis.
0:17:37 And we should be thinking about designing our grid and designing our energy mix and power sources around what those loads look like.
0:17:41 And not over-solving for either baseload or variable power.
0:17:50 I think just to put this in more tangible terms, the peak summer load in places like California might be half of what it is in winter or something like that.
0:17:51 And it depends on what climate you’re in.
0:17:58 And so the concept of baseload is, like, do you build all the plants you’d need for the 100 gigawatts of power you’re going to need when it’s wintertime?
0:18:01 Or in the summer, you know, half the year, you’re only going to need 50.
0:18:02 So, like, what would be baseload?
0:18:08 What you need to do in sort of modern civilization is, every time you turn on the switch, like, the power is working.
0:18:14 And so how you actually match supply with that very, very fluctuating load, both daily and seasonally, is very complex.
0:18:21 And so, like, today, you might have to build a natural gas, what’s called, like, a peaker plant, that might only operate, like, a week a year.
0:18:28 And so that’s an incredibly expensive asset that is going to only be delivering very expensive power, but is only needed when all the other resources are tapped.
0:18:31 And it’s, like, that last couple megawatts of power.
0:18:44 The alternative now you could do is what’s called, like, demand response or with batteries on the grid is say, okay, well, instead of doing this $10,000 sort of a megawatt hour plant, I can just make it so everyone’s thermostat in this area turns down a couple degrees.
0:18:49 And so then an aggregate means that I don’t need to build that large asset or pay that expensive premium.
0:18:51 Okay, pushing back on that.
0:18:59 Like, I think that the American consumer will fully organ reject that level of dictation over how they use their power.
0:19:10 I think a more likely outcome is that you can do it on the compute side and just say, look, these three racks of the data center are just going to go offline during the peak summer heat when you’re running your AC.
0:19:13 This is not a critical job.
0:19:13 Right.
0:19:14 It’s a non-critical job.
0:19:15 It’s not a mission job.
0:19:17 It’s a back office job.
0:19:19 And you’re just going to run it at night instead of during the day.
0:19:22 And you’re going to pay less electricity for that benefit.
0:19:26 I don’t know if I agree with Aaron that AI is not going to suck up all the compute.
0:19:30 I think that Constellation just turned up a new nuclear reactor or is reactivating a reactor.
0:19:40 I think Meta immediately sucked up all of the power that they’re going to generate or nine-tenths of it or something from the new Constellation reactor that Meta signed the contract extension for.
0:19:50 And so I think we actually probably are underestimating the amount of compute that we’re going to soak up with electricity over the next 10, 20, 30, 40, 50 years.
0:19:52 The amount of data we’re going to start storing.
0:19:53 Just look at video.
0:19:57 The amount of video we create per minute has just ballooned way beyond anyone’s expectations.
0:19:59 I’m sure the same will be true for AI compute.
0:20:05 And I think once you start getting into like robotics and autonomy, if you think about compute expansively, I totally agree.
0:20:05 Yeah.
0:20:12 And so like those things are going to be much more responsive than do I want to go have my room be 74 degrees instead of 71 degrees.
0:20:17 Well, let me tell you, anyone that’s done business in Tokyo in the summer knows as a nation, by the way, Japan has done this.
0:20:19 It is absolutely terrible.
0:20:20 It’s horrible.
0:20:21 We’re not going to do that in America, please.
0:20:23 We’re not going to do that.
0:20:24 We’re not going to do that in America.
0:20:30 You’re in like the 40th floor of a Japanese building wearing a suit, by the way, because you have to wear a suit.
0:20:31 It’s swelteringly hot.
0:20:34 Everyone is walking around like they’re not miserable, but they are miserable.
0:20:36 And you watch them out a window, but the window won’t open.
0:20:38 It is one of the worst.
0:20:39 Why doesn’t France work in the summer?
0:20:40 This is why.
0:20:41 It’s terrible.
0:20:41 Exactly.
0:20:43 So we hate this idea.
0:20:44 I’m spoiled living in California.
0:20:49 I will say like one of the biggest proponents of this or current users is like crypto mining.
0:20:50 It’s like these are flexible.
0:20:51 Yeah, but that’s right.
0:20:53 But those people are demand responsive, right?
0:20:56 So those people will just turn off their compute when it’s not cost effective.
0:20:56 Yeah.
0:21:01 But it’s important for the grid is that you can build these assets and you have the demand for power here.
0:21:02 Like they’re going to soak up that demand.
0:21:06 But if it gets far too expensive, they will also shed that demand.
0:21:10 In the U.S., my guess is that this already is reflected in the fact that you have peak load pricing.
0:21:14 Like for me, my power is 10x more expensive between the hours of 4 and 9 p.m.
0:21:15 So we don’t run the washing machine.
0:21:16 Yeah, right.
0:21:20 And so leave it to organizations or individuals to figure out how to manage that.
0:21:22 But just like charge people for more power.
0:21:26 It’s a little bit of a non sequitur, but I like that we keep talking about oil and gas.
0:21:27 We’re talking about natural gas.
0:21:28 We’re talking about batteries.
0:21:29 We’re talking about solar.
0:21:30 We’re talking about nuclear.
0:21:34 Ryan even mentioned hydro, which of course is totally viable in some places.
0:21:39 The thing that nobody ever brings up anymore, except for I think a very fringe group, is wind power.
0:21:42 And I’m very happy to hear that nobody here is jumping for wind.
0:21:45 I think wind is incredibly cheap when it’s working.
0:21:48 You kind of know solar is going to work and like sort of this reliable schedule.
0:21:49 The sun’s going to be out.
0:21:50 It’s going to be working.
0:21:53 Spare some cloudy days, but there’s still always something coming through.
0:21:55 But the wind might not blow for a week.
0:21:56 I think it’s worse than that.
0:22:01 I think I read that globally, one third of all wind turbines are out of service at any given time.
0:22:07 The other thing is, I think wind is the only power generation mechanism where when you get too much of the input,
0:22:10 the blades of a wind turbine feather and turn off.
0:22:13 Whereas there’s still something that’s too much sun for solar.
0:22:16 Too much water and hydro, like that’s not a problem.
0:22:18 But like too much wind and the wind generator turns off.
0:22:21 Well, who wants a system where you get more of the input you want and then it stops working?
0:22:25 It’s also just extremely hard and dangerous and specific to service.
0:22:29 Like you see those videos of people climbing the ladder up to the top of the wind turbine.
0:22:35 Grid operators look at wind and it’s like great when it’s working, but they can’t plan for it.
0:22:37 They have to build other capacity to supersede that
0:22:38 if it’s not going to be there when they need it.
0:22:39 So fine, I cede wind.
0:22:41 We can move past wind.
0:22:42 Yeah, I agree.
0:22:42 So no wind.
0:22:46 But I do think the demand response, this went to the point that Ryan brought up,
0:22:47 that monitoring the grid is really important.
0:22:50 Being able to send signaling on the grid is really important.
0:22:52 And you have to remember, we’re all used to the internet,
0:22:55 which has bidirectional communication and messaging.
0:22:57 It has data layer and control layers.
0:23:00 And there’s like a full control plane and things like that for the internet.
0:23:02 The electrical grid doesn’t really have that.
0:23:04 And so to be able to send messaging and things is very, very difficult.
0:23:07 And now a lot of people just do it out of band using the internet.
0:23:13 To actually send messaging and do monitoring of the grid itself without an overlay network is very hard.
0:23:16 And that’s one of the challenges that people are now, I think, starting to address.
0:23:21 Yeah, it’s wild how much of a mystery what’s happening on the grid is at any given time.
0:23:23 Like we really have very little visibility.
0:23:31 And it’s very hard for, I think, centralized utilities to deploy meaningful software to understand that.
0:23:36 So when we think about as VCs, like what types of things do we look at and what do we get excited about?
0:23:40 I think companies that kind of are going at this monitoring from the opposite direction.
0:23:43 Like how do you get software almost insidiously on the grid?
0:23:49 Like how do you start learning more about demand and generation as close to the source as possible?
0:23:52 And then try to feed that information back from each other.
0:24:00 Like the idea that you’re going to go sell a software tool to a PG&E or similar and have a reasonably speedy top-down implementation
0:24:04 where you actually get good signal and metrics and can actually do interesting things with that data.
0:24:08 To me, I find like a little bit unbelievable.
0:24:11 Something very interesting that I learned is a lot of the load forecasting,
0:24:15 which is basically like the tasking of when plants need to go online.
0:24:19 So there’s usually a 24-hour ahead sort of market, day-ahead market that’ll basically say,
0:24:21 you need to run your plan at this time.
0:24:23 And then they sort of supply and demand match to a price.
0:24:24 And there’s like a merit order.
0:24:25 It’s complex, but that’s how it’s done.
0:24:29 But most of this load forecast is done by just looking at the weather.
0:24:31 They look at basically one of the best indexes.
0:24:35 They look at where the homes are, how many people are there, and then what the temperature is going to be.
0:24:38 That often is sort of the largest factor that goes into this modeling.
0:24:42 But if we have all these sort of connected resources, we have solar, we have EV chargers,
0:24:45 all of this stuff is spitting off data, telemetry, and things like that,
0:24:50 we’re going to get a much better look of how like load is actually being forecasted real-time,
0:24:54 which is going to help a lot of understanding like where do we actually need to build?
0:24:55 Like what is the actual price of power?
0:24:57 And then you can start making these markets, I think, a lot more efficient.
0:25:02 Well, when you look at energy desks for the big hedge funds or energy trading companies,
0:25:06 their weather guy is usually the highest paid person on the desk outside the portfolio manager.
0:25:10 Those climate and weather PhDs that are working on a trading desk,
0:25:16 they are just absolutely raking it in because they’re like God right now because there’s very little other data.
0:25:19 That’s why you see when the stuff that goes on in Texas, like heat waves and things like that,
0:25:23 if they even get it wrong by a couple of degrees where it’s like they think it’s going to be hot,
0:25:26 but it gets actually really hot, that’s when you get these crises,
0:25:28 like crises that end up causing a lot of strain on the grid
0:25:32 and then you have to turn off all these very expensive plants and then you get the headlines.
0:25:34 That are usually also the ones that are the worst for the environment as well.
0:25:35 Yep.
0:25:39 Let us know if you have any reactions to this or otherwise give us the state of nuclear.
0:25:40 Where are we right now?
0:25:41 What are the major bottlenecks?
0:25:42 What are we excited about?
0:25:48 I think that the biggest thing that’s shifted in the last two or three or three or four years in nuclear
0:25:51 is that everybody now acknowledges that nuclear energy is clean energy.
0:25:55 I think that’s been one major shift in public sentiment and perception.
0:26:01 Nonetheless, there’s still major headwinds politically with nuclear that need to be overcome.
0:26:04 Taiwan, for instance, turned off their last nuclear reactor.
0:26:05 Insane.
0:26:06 It’s unbelievable.
0:26:11 This is an island country that is seven days away from a total energy blackout
0:26:13 if they get an oil and gas blockade from China
0:26:17 so that they can’t bring in ships to deliver oil and fuel.
0:26:20 So at any given time, they’re like seven days away from a total blackout
0:26:22 and they turned off their last nuclear reactors at all.
0:26:22 Why’d they do it?
0:26:27 Because they caved to political, like very loud vocal minority groups.
0:26:28 Like environmentalist activist reason?
0:26:29 Yeah.
0:26:33 This party ran on a commitment to turn off the reactor before they realized how stupid it was.
0:26:34 It’s just like colossally stupid.
0:26:39 By the way, turning off a reactor, like a real full-scale reactor, it’s not like an SMR where
0:26:42 you can just flip it on like a few days later or a month later.
0:26:45 With these large reactors, it could take years to turn them back on.
0:26:46 That was just terrible.
0:26:51 But broadly, I think the tailwinds for nuclear are just getting stronger, where people recognize
0:26:52 realize that it is clean energy.
0:26:55 I think there’s still messaging work to be done.
0:26:59 We should stop calling the spent fuel nuclear waste because it’s really not waste.
0:27:01 Almost all of it can be recycled and reused.
0:27:04 People do need to recognize that those tailwinds are shifting.
0:27:05 So that’s happening.
0:27:08 I think that people understand that it’s baseload power, right?
0:27:10 So it’s not dependent on it only working during daytime.
0:27:15 It’s not like hydro where you have to be around an appropriately configured water source.
0:27:21 And then I think that one of the largest inhibitors to creating new power plants in this country,
0:27:23 it’s not that we can’t do it.
0:27:24 We can.
0:27:29 There’s a huge regulatory and permitting, I would say, morass that has to be swam through
0:27:36 that is incredibly expensive, requires an army of consultants, many tens of millions of dollars,
0:27:41 many, many thousands of pages of applications and documentation and process review.
0:27:45 And again, this has to do with building the power plant, getting the fuel, transporting the
0:27:46 fuel, storing the fuel.
0:27:52 Each step along the way is extremely laden with regulation and policy.
0:27:54 And some of that’s for good reason.
0:27:59 But finding ways to better navigate that to make it more efficient is really a step in areas
0:28:02 that a lot of companies and people are focused on now.
0:28:06 And actually, I think the government now is also focused on how do we streamline the approval
0:28:08 process for a new reactor?
0:28:10 How do we start approving new reactor designs?
0:28:16 And then I think the last thing I guess I would say is that right now, if you’re going to put
0:28:19 a lot of energy and work into building a nuclear power plant, you want to build a really big one.
0:28:23 We largely only see really big power plants in this country, like the AP1000s that we turned
0:28:24 on in Georgia.
0:28:28 And those again came in, I think they were 10 years late and multiple billions over budget.
0:28:31 We only do that because if you’re going to put in the effort and time, you want to get the
0:28:33 most bang for your buck and generate the most power.
0:28:38 We are now starting to see movement from the government in the DOD, in the Department of
0:28:43 Energy, and from the national labs to really try to create a more fast track process for
0:28:50 these small modular reactors or even micro reactors that use a much safer form of fuel, use much
0:28:57 less nuclear fuel, use a different kind of nuclear fuel that’s not nearly as risk prone as the kind
0:29:01 of nuclear material you’d use them like a weapon, but it’s not nearly as enriched to the same degree.
0:29:03 It’s not even the same material.
0:29:06 And so that process is now getting a lot of steam.
0:29:08 We have an investment in a company called Radiant Nuclear.
0:29:12 They are building a factory that creates what effectively is an SMR.
0:29:14 They would probably call it a micro reactor.
0:29:16 It’s a one megawatt reactor.
0:29:19 It can be put on the back of an 18-wheeler and shipped around.
0:29:23 You can move it to where you need power if there’s been a natural disaster, like a hurricane,
0:29:25 and you need to bring in power overnight.
0:29:30 You could bring in a few trucks with four or eight of these reactors and power up a whole
0:29:31 city after a disaster.
0:29:34 And so that kind of flexibility and power is really compelling.
0:29:36 I think there’s a lot of tailwinds, a lot of good things happening.
0:29:42 One thing to understand is that the DOD spends an incredible amount of money dealing with the
0:29:46 cost and, frankly, the risk to human lives, not just the cost, but the real risk to human lives,
0:29:50 transporting fuel around the world to forward operating bases.
0:29:55 Anytime we do a military exercise, anytime we’re engaged in a conflict, the movement of
0:30:00 fuel factors in as a primary concern and consideration of what we deal with.
0:30:04 And so we’ve read reports that they spend well over $200 a gallon at times, sometimes up to
0:30:09 $400 a gallon for diesel, effectively, to get diesel into the right place at the right time.
0:30:14 And so you can just imagine that having a nuclear reactor you can put on the back of a C-130
0:30:19 and fly around the world to wherever you need power, drop it in the middle of the desert,
0:30:21 turn it on, you have power for five years.
0:30:22 It’s just an incredibly compelling value prop.
0:30:25 There is no question that nuclear needs to be part of the equation.
0:30:30 Not only is that baseload power, but on the SMR micro reactor side, it gives us this incredible
0:30:32 flexibility in grid resilience.
0:30:36 There should not be a single military base in this country that’s not nuclear backed from
0:30:42 a power standpoint, because if the grid goes down, whether it’s from a cyber attack or just
0:30:48 instability or demand issues or cascading failures, you want to be able to fail over to nuclear power
0:30:50 and not worry about the runway lights turning off.
0:30:50 Yeah.
0:30:55 And especially as we start to look at the kind of electrification of our weapon systems,
0:31:02 our military vehicles, our drones, et cetera, like those all need to get charged up somewhere.
0:31:05 And how better to charge them than a nuclear reactor?
0:31:09 Another thing I’ll add to your nuclear comment is I think the advantage of nuclear, and I think
0:31:13 that Radiant has done very well of really leaning in on, is the power density factor.
0:31:18 If you want a reactor that is reliable and power dense, you want it to operate at very high
0:31:19 temperatures.
0:31:22 You want as highly enriched fuel as you possibly can, where it makes sense commercially.
0:31:26 So you want Halo fuel and you want to serve customers that will pay the premium for that.
0:31:29 That’ll be able to buy this reactor that they know is going to work.
0:31:32 And if you’re doing that, you want to have these economies of scale on the manufacturing
0:31:33 side.
0:31:36 You want it to be done out the door and don’t need to like assemble it on site.
0:31:38 You don’t want to have to like have constant maintenance.
0:31:42 And I think the other sort of reactors that we see, maybe on the civilian side, if you build
0:31:46 a reactor in a factory or you build modular components in a factory, but you still need
0:31:51 to do construction work on site, you’re still a construction company, even if the technology
0:31:51 is there.
0:31:54 And I would argue a lot of the existing AP1000 technology is quite good.
0:31:56 And other countries can do it quite cheaply.
0:31:58 China is using a very similar design.
0:32:00 The UAE just built one for incredibly cheap.
0:32:04 And they have very similar nuclear regulation, like in terms of frameworks.
0:32:07 And obviously their regulatory bodies might move faster and things like that, but they’re
0:32:09 not like completely ignorant of some of the concerns.
0:32:12 Well, and maybe this is a much more broad question, but the United States needs to get better
0:32:13 at mega projects.
0:32:16 Things that are a billion dollars, things that are at scale.
0:32:20 And I would argue the NRC is a big component of why it’s expensive, but I think it’s also
0:32:24 the same reason that it takes a billion dollars to build a bike lane in San Francisco is why
0:32:25 we are not able to build stupid power.
0:32:28 Or why we don’t have a high-speed rail in California.
0:32:28 Yep.
0:32:31 We might not have a high-speed rail in California because nobody wants it.
0:32:33 And nobody wants it where they’re building it.
0:32:33 I want it.
0:32:34 I fly to LA all the time.
0:32:35 Sorry.
0:32:36 Nobody wants it where they’re building it.
0:32:37 Sure.
0:32:37 Yeah.
0:32:39 Bakersfield is not a prime destination.
0:32:42 I want to train from San Francisco to LA.
0:32:44 It takes an hour and a half.
0:32:49 We debate a lot internally, like, where does it make sense for VCs and VC capital to plug
0:32:49 in?
0:32:55 And arguably, like, we’re not going to move the needle on, you know, these multi-billion dollar
0:32:56 mega projects in the U.S.
0:33:01 Like, we’re probably not the best people to figure out how to capitalize and build a multi-billion
0:33:04 dollar project in California to generate the power for the grid.
0:33:10 But I do think that there is a role for technology at kind of, like, every single layer and every
0:33:12 single phase of how mega projects get built.
0:33:17 It’s like, how do you use AI to navigate kind of site selection?
0:33:22 How do you use tools to, like, move through the various permitting processes faster?
0:33:27 Like, how do you use AI to help you do extremely complex and interdependent project management
0:33:28 better and more effectively?
0:33:33 So that’s something that you have a project with 4,000 people working on it and everyone
0:33:36 engaging with different suppliers and timelines that are dependent on each other.
0:33:39 Like, how do you get all those things to align better so that you don’t get these 10-year
0:33:44 delays so that projects actually happen on time and on budget and, as a result, attract
0:33:46 private capital backers?
0:33:48 Like, I think that there’s a role of technology here.
0:33:49 You know what that looks like.
0:33:50 TBD.
0:33:53 We’ve seen a lot of companies that maybe five years ago were primarily trying to sell
0:33:57 to utilities and grid operators, which is incredibly painful, incredibly difficult.
0:33:58 Perhaps rightfully so.
0:34:00 Like, they have poles in the ground that are 50 years old.
0:34:03 Why would they trust a two-year-old company to sell them software?
0:34:04 Are they going to be around in 20 years?
0:34:07 And this is a fair question to ask, especially for something as critical as the grid.
0:34:11 But now they’re developing this software and there’s such demand of understanding how grid
0:34:15 operators might think and potentially get there faster or, you know, have different conclusions.
0:34:20 And so now you can go to data centers or people who want to build solar farms or people who
0:34:21 want to build massive, like, battery farms.
0:34:23 And you can sell a very similar software.
0:34:26 Individual people who want to make sure that their power isn’t going to go out and they’re
0:34:29 going to be caught without energy during an important moment in their lives.
0:34:29 Yeah.
0:34:30 And so everyone cares now.
0:34:35 There’s a lot more money who cares about what is the grid actually going to think and where
0:34:35 can I build?
0:34:37 Where is there excess capacity?
0:34:41 Maybe I’m connected to the grid, but I also need some battery and solar backup or like a
0:34:45 radiant microreactor or something like that to be used in certain situations.
0:34:49 It’s a lot more complex, this sort of microgrid setup, but it’s the way we’re headed.
0:34:50 And software is going to be a big piece of that.
0:34:55 I want to hear more about our requests for startups or things that we want to exist that
0:34:55 we haven’t yet discussed.
0:34:59 I mean, put differently, I’m curious where we think there’s most bang for the buck in terms
0:35:03 of the issues that we’ve been talking about in terms of if there was like a regulatory intervention
0:35:05 or some sort of technological unlock.
0:35:06 What comes to mind?
0:35:11 One area where there’s probably a venture scale software company to be built is really around
0:35:13 grid management monitoring.
0:35:19 I think we see this in the IT landscape, we see it in the OT landscape, but we don’t really
0:35:22 see it in the grid where there’s just full, very, very large.
0:35:24 There is no Splunk for the electrical grid.
0:35:27 There’s no power to networks for the electrical grid yet.
0:35:31 There’s a whole bunch of things that mirror the IT and OT landscape, whether it’s around cyber
0:35:34 and monitoring and logging and analytics.
0:35:37 There’s no looker for the electrical grid yet.
0:35:38 There’s just none of these companies exist.
0:35:42 I’m not sure if it’s three separate companies, I’m not sure if it’s one company, but there
0:35:48 is a big company to be built and really managing and monitoring the grid and helping to orchestrate
0:35:53 and even deal with some of the things Ryan spoke around, around demand response, coordinating
0:35:56 that, creating those marketplaces, tracking all those incentives.
0:36:00 So I think when we see a company that we think can really be the breakout company there, we
0:36:00 would lean into it.
0:36:06 I also think around sort of project planning and development, how do you make it faster
0:36:09 and easier to build projects within the current regulatory framework?
0:36:10 How do you do site selection?
0:36:12 How do you navigate permitting?
0:36:14 How do you navigate project management?
0:36:16 How do you navigate your sort of construction supply chain?
0:36:20 We’re starting to see companies pick off pieces of that, but I think broadly speaking, there’s
0:36:24 room for tech and software in that kind of project development space as well.
0:36:29 I think, you know, in a more general sense, like anything that can bring generation capacity
0:36:32 or storage capacity closer to load, I think is going to be very compelling.
0:36:37 And a lot of the times it’s less maybe the technology, novel technology, but it’s a system integration
0:36:38 or it’s an innovative business model.
0:36:42 I think something like radicalizing that I experienced is, and I implore everybody to go home and check
0:36:46 their power bill, they’ll now like often separate like the delivery costs from the actual
0:36:47 generation costs.
0:36:51 So what we’ve seen and we’ve mentioned it, but like the cost to generate electricity, the cost
0:36:55 of like power has dropped immensely, gas, solar, things like that.
0:36:58 But the cost to actually deliver that electricity has increased a ton.
0:37:00 And so in net, it’s sort of not changed.
0:37:01 And I think that’s terrible.
0:37:03 And I think we all agree that’s bad.
0:37:06 And so I think there’s a lot of opportunity of bringing sort of that generation capacity.
0:37:09 In some ways, this is sort of like this more liberalizing force.
0:37:10 It’s like we all should have our own backup.
0:37:11 We all should have our own technology.
0:37:14 I think there’s a lot of really interesting ways to do that and scale it.
0:37:19 And overall, as a grid gets more heterogeneous, all of the seams and intersections between
0:37:24 things, like there’s just so much more opportunity for technology than when you had a single utility
0:37:27 managing a single source of power centrally distributed out broadly.
0:37:30 I’ll throw another one out there as I’m just thinking about this.
0:37:36 One thing that I’ve been noodling around is this idea that all the regulation and permitting
0:37:40 and policy frameworks that we have in this country, you could think of those as part of
0:37:44 the like infrastructure that we all have to like live and work with and interact with.
0:37:49 So companies that really facilitate, and I would say applying AI to navigating the permitting
0:37:50 process.
0:37:51 So nuclear is a good example.
0:37:58 Again, a nuclear reactor application or a fuel transport license or a fuel manufacturing license.
0:38:03 These things have thousands and thousands of pages of regulation and documentation that go
0:38:04 with them.
0:38:08 You make one small change in your application, it has these reverberation effects.
0:38:09 You have to update all your documents elsewhere.
0:38:13 If you’re the regulator trying to go through all these applications, it’s just incredibly
0:38:18 onerous, borderline impossible to imagine that a regulator can even possibly get it right.
0:38:20 You could argue that it’s actually not possible.
0:38:21 They just do a best effort.
0:38:27 But AI could actually help these things, could help the applicants go through the process of
0:38:30 filling out their applications and saying, hey, this is where you should drill down.
0:38:31 This is where you should clarify.
0:38:36 They can look at all previous published applications and say, this is how you need to tailor it.
0:38:41 You can probably make it 85% the same, and then based on your design or your location or
0:38:42 whatever, make some modifications.
0:38:45 And then the regulator can do the same and say, look, here’s an application that came in,
0:38:49 highlight all the areas I need to drill down, or show me the things that are different from
0:38:52 every other nuclear fuel transport application we’ve ever seen.
0:38:54 Are they using the rail infrastructure?
0:38:57 Are they using the national highway infrastructure to move the fuel?
0:39:02 AI can just automate all these things that take armies of consultants months or years to do,
0:39:05 can be brought down into being minutes or hours.
0:39:08 I’m not sure how big of a company, but I think potentially there’s a very large company
0:39:09 to be built there.
0:39:13 If our check sizes were in the billions, not just the millions, which were in Jason Horowitz,
0:39:15 you never know, how would our strategy change?
0:39:17 I think you need even more than just billions.
0:39:18 It’s tens of billions, hundreds of billions.
0:39:20 It’s such a tough question.
0:39:23 I think there’s tons of policy around this as well.
0:39:27 I hesitate to say we should look to how China has built up their grid,
0:39:30 but I think the elephant in the room is in the early 2000s, they were experiencing blackouts.
0:39:32 This was a very common thing.
0:39:33 This was horrific.
0:39:37 But now, think of 4X their grid in the last couple of decades.
0:39:41 And so the way they’ve done this is by basically deploying generation capacity,
0:39:46 building hydro, building massive storage facilities, of course, BYD, CATL, tons of battery production.
0:39:51 They built HVDCs, these large high-voltage transmission lines.
0:39:52 I would do all of that.
0:39:53 I mean, I would look to all of it.
0:39:56 And whether or not it’s a good investment or not, I’d look at a number of factors,
0:40:00 but it is much more of the infrastructure projects, the glue that connects this stuff together.
0:40:05 I think our lens today is looking at these technologies that enable a lot of this more flexible grid.
0:40:08 But I think there’s also going to be these large infrastructure, the webbing in between it.
0:40:12 I think software is a big piece of it that we’re spending a lot of time on looking at.
0:40:14 But I think, how is ERCOT going to be connected to the rest of the grid?
0:40:16 Or how are we going to move this power around?
0:40:19 If it’s really sunny in the Southwest, solar is going to be really cheap.
0:40:22 Is there an efficient way to move that to New York or something like that?
0:40:23 China’s done this effectively.
0:40:26 And I think if you had hundreds of billions of dollars spent or trillions of dollars,
0:40:28 what does the grid look like?
0:40:29 Like, it’s going to be a lot more interconnected.
0:40:33 Maybe another answer to your question or a different answer to your question is,
0:40:37 I think the energy industry is probably medium to long-term,
0:40:42 like one of the most prime spots to deploy physical autonomy.
0:40:50 So when you think about applications of robotics, whether it’s humanoids or more kind of task-specific
0:40:53 robotics, we’re talking about dangerous jobs often.
0:40:57 We’re talking about manufacturing jobs to build up, whether it’s small-scale reactors or batteries
0:40:58 or whatever.
0:41:04 So I don’t know what the shape of the company is here and how reliant it would be on some of
0:41:06 the robot learning work that’s happening.
0:41:10 But I do think that as we scale our energy capacity, there’s going to be a pretty massive
0:41:13 application of industrial robotics to the energy sector.
0:41:19 I made this joke, I think, once to Ryan, or maybe I made it at the American Dynamism Summit,
0:41:24 that we survived the greatest nuclear disaster in U.S. history just recently when we finished
0:41:28 the Vogel 3 and 4 reactors and let all those employees go back to other jobs.
0:41:32 So I think if we were writing a billion-dollar check into power, what we would do is we would
0:41:36 just give jobs to those people and not let them go back to whatever it was they were doing
0:41:38 before they were building nuclear reactors.
0:41:43 And we would just really work to streamline the process to make sure that we go build Vogel
0:41:48 5, 6, 7, 8, 9, 10, and all these different states around the country and just put these
0:41:52 people to work for the next decade-plus building reactors.
0:41:56 And that, to me, was the greatest miss and probably the greatest opportunity.
0:42:01 I don’t think it’s particularly our opportunity, but I do think it’s an opportunity for somebody
0:42:02 to do.
0:42:07 Labor broadly, like, this is a little tangential, but when Microsoft was building their new data
0:42:12 center in Georgia last year, at one point, they had on staff at Microsoft or on contract
0:42:15 more than a third of the electricians in the state of Georgia.
0:42:17 And they basically maxed out.
0:42:20 They hired every single electrician that they possibly could.
0:42:23 So I don’t think it applies to just electricians.
0:42:29 It’s, do you, to your point, like the cement mixers, it’s the mechanical engineers, it’s the nuclear
0:42:30 engineers.
0:42:36 Like, how do we actually train the next generation energy workforce that we’re going to need to
0:42:39 modernize the grid is a big, big challenge.
0:42:43 These are very high-paying jobs where you don’t have to check your email on your phone at 9 p.m.
0:42:45 at night after you go home from work.
0:42:46 They’re high-paying.
0:42:48 It’s good exercise jobs.
0:42:50 And they’re relatively low stress.
0:42:51 These are good jobs for people.
0:42:55 I think one more comment on this, and it’s more of an industrial policy question, is we’re
0:42:59 talking about specific things, but like oftentimes that just moves the bottleneck.
0:43:01 Like we could solve a lot of sort of the grid connection hookup.
0:43:05 We could build a lot of like transmission lines, but then we need more transformers.
0:43:07 And to build more transformers, you need more electric steel.
0:43:10 You can do the same sort of equation for much of the supply chain.
0:43:14 Battery is another good example is then, okay, cool, we’re building cells, but then we also
0:43:17 need active materials and we need to mine and things like that.
0:43:21 And so, you know, it’s sort of a whole effort of examining sort of our infrastructure and
0:43:23 our supply chains, and you need to do all of it.
0:43:25 And I think that’s a complicated question.
0:43:26 That’s an expensive question.
0:43:27 Any last reflections?
0:43:32 I think the last thing I would say is that people underestimate how critical and important
0:43:38 a resilient, reliable, dispatchable electrical grid is to our national security.
0:43:42 You cannot have national defense and national security without reliable electricity.
0:43:44 It’s just not possible.
0:43:48 So all of these things we’re talking about are about the upside, about capitalizing on
0:43:53 AI compute, the switch to electric vehicles and our insatiable thirst for electricity.
0:43:56 But at a fundamental level, there is no safety.
0:43:57 There is no national defense.
0:44:00 There is no national security without a reliable electrical grid.
0:44:06 To reiterate on that, people want reliable, cheap, and clean power in that order.
0:44:09 And I think that’s, I think largely how we should think about our energy policy.
0:44:12 And I think that’s sort of the direction we’re going.
0:44:14 And I think we need to make sure we stay aligned with that.
0:44:16 That’s an exciting note to wrap on.
0:44:17 David, Ryan, Aaron, thanks so much for coming to the podcast.
0:44:18 Thank you.
0:44:19 Thank you.
0:44:23 Thanks for listening to the A16Z podcast.
0:44:28 If you enjoyed the episode, let us know by leaving a review at ratethispodcast.com slash
0:44:29 A16Z.
0:44:32 We’ve got more great conversations coming your way.
0:44:33 See you next time.
0:44:44 We’ll see you next time.
0:44:44 We’ll see you next time.

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0:01:12 This week on A Touch More,
0:01:16 we’re talking all about the WNBA All-Star roster
0:01:20 with ESPN analyst and former All-Star herself,
0:01:20 Chenea Gumake.
0:01:23 She also tells us what she wants to see
0:01:24 from the CBA negotiations.
0:01:28 Plus, I’m sharing some of the record-breaking updates
0:01:30 from the Euros in Switzerland.
0:01:33 Check out the latest episode of A Touch More
0:01:35 wherever you get your podcasts and on YouTube.
0:01:41 Welcome to Raging Moderates.
0:01:42 I’m Scott Galloway,
0:01:44 and President Trump is clearly in the Epstein files.
0:01:47 Oh, good morning to you too, Scott.
0:01:48 Come on.
0:01:49 Come on.
0:01:50 That’s why we’re here, Jessica.
0:01:51 In today’s episode,
0:01:54 I was in Ibiza last week.
0:01:57 Word has it, I did Molly and had an amazing time,
0:01:59 and I think I’m enjoying this more.
0:02:00 Yeah.
0:02:02 It’s just taking you to another level.
0:02:03 Oh, my God.
0:02:04 This is my hot girl summer.
0:02:07 Today, we’re going to talk about,
0:02:08 today, we’re going to talk about MAGA revolting
0:02:10 over the Epstein files,
0:02:12 an all-time high of Americans now seeing immigration
0:02:14 as a positive for the country.
0:02:17 Well, welcome to pulling your head out of your ass
0:02:20 and a proposal to evaluate lawmakers’
0:02:22 cognitive fitness for office.
0:02:24 That’s ageist, Jess.
0:02:26 That’s ageist.
0:02:28 Anyways, let’s get right into it.
0:02:31 The president is once again at odds with his own base.
0:02:33 This time, it’s over Jeffrey Epstein.
0:02:37 But we should really be focusing on Rosie O’Donnell.
0:02:39 I think that’s not a distraction.
0:02:41 Our favorite Irish lass, Rosie.
0:02:42 Yeah.
0:02:44 No, that is not an attempt to distract and say,
0:02:46 look over here from the fact that he is clearly
0:02:47 in the Epstein files.
0:02:50 After the DOJ released a memo concluding Epstein died
0:02:52 by suicide and had no secret client list,
0:02:55 Trump urged supporters to move on
0:02:58 and defended Attorney General Pam Bondi,
0:02:59 calling her fantastic.
0:03:02 He also claimed critics were just selfish people
0:03:03 trying to hurt him.
0:03:05 But MAGA world isn’t buying it, Jess.
0:03:07 At Turning Point USA Student Summit,
0:03:09 the crowd booed Bondi’s memo,
0:03:11 accusing Trump of breaking his own promise
0:03:13 to release the full files.
0:03:15 And influencers, including Steve Bannon and Laura Loomer,
0:03:17 are openly criticizing the administration.
0:03:19 Loomer is now calling for a special counsel.
0:03:21 Who the fuck cares what Loomer wants?
0:03:21 But anyways.
0:03:22 Trump cares.
0:03:24 There you go.
0:03:27 The leader of the free world happens to care.
0:03:27 He cares.
0:03:29 Inside the administration,
0:03:30 the fallout is even worse.
0:03:34 FBI deputy director and podcaster Dan Bongino
0:03:35 almost resigned.
0:03:35 Almost?
0:03:36 Oh, no, Dan.
0:03:40 We hate to lose someone as competent as you
0:03:41 from our public ranks.
0:03:44 He almost resigned after a tense blow up with Bondi.
0:03:45 He skipped work Friday.
0:03:48 It’s like one of these little tech Google bitches
0:03:50 doing a lunch walkout,
0:03:51 pretending that anyone cares.
0:03:54 Oh, he took the day off.
0:03:55 That’ll show him, Dan.
0:03:58 And he hasn’t spoken to DOJ leadership since.
0:04:00 He hadn’t spoke to him in a whole four days.
0:04:02 Bongino’s future is uncertain.
0:04:04 But for now, he’s still on the job.
0:04:06 Bondi’s still in Trump’s good graces
0:04:10 and even took her to the football game on Sunday,
0:04:11 which, by the way, was outstanding.
0:04:12 Yeah, it was kind of funny
0:04:14 how he wouldn’t get out of the picture, though.
0:04:15 Yeah, and he was booed.
0:04:16 That was my favorite part.
0:04:18 But this episode exposed serious fractures
0:04:21 within the MAGA world and Trump’s grip on it.
0:04:24 Jess, give us your thoughts on this.
0:04:26 I got this wrong.
0:04:27 I didn’t think it was going to be that big a deal.
0:04:28 And it’s just blown up.
0:04:29 Give us your take.
0:04:30 Yeah.
0:04:33 We are conditioned to think nothing matters
0:04:37 because nothing has mattered up until this point, right?
0:04:39 So you think, oh, this is a news story
0:04:41 for maybe a couple of days.
0:04:43 And you worry if you’re recording something
0:04:46 that it’s going to be old by the next day, right?
0:04:47 But this one has had legs.
0:04:52 And a lot of that is because you have the luminaries,
0:04:54 and I’m being generous with that term,
0:04:58 but, you know, the faces of the party upset
0:05:00 and the rank and file upset.
0:05:03 And usually those things don’t coincide, right?
0:05:05 You get a few pissed off people here,
0:05:06 but down here, everyone’s fine.
0:05:08 Or down here, people are upset,
0:05:10 but up here, folks aren’t.
0:05:13 And we have to be real about this.
0:05:15 There are folks who were very outspoken
0:05:17 about the Epstein files and being upset,
0:05:19 like Charlie Kirk, Benny Johnson.
0:05:21 They’ve already fallen back in line.
0:05:23 Trump called Charlie Kirk, apparently.
0:05:26 Then he starts posting, you know,
0:05:27 this isn’t really worth our time.
0:05:30 And Benny Johnson, who had a four-point plan
0:05:33 to how the administration could make things better,
0:05:35 which also included, you know,
0:05:37 something having to do with Bill Clinton,
0:05:41 now is saying that MAGA is taking this seriously,
0:05:44 and apparently Bondi is going to start
0:05:46 dribbling out more information,
0:05:48 or that’s what we heard from Lara Trump.
0:05:51 But I’m kind of in two minds about it.
0:05:52 So the one mind,
0:05:54 which I think is more like your Ibiza-Molly mind,
0:05:57 is I’m excited by this,
0:06:00 because it also shows that for some in this movement,
0:06:02 there is a bridge too far,
0:06:04 or a line that you can’t cross.
0:06:06 And there are a lot of people,
0:06:08 especially the rank and file,
0:06:12 who are upset because this guy was running a pedophile rank,
0:06:13 right?
0:06:15 There were kids that were being abused
0:06:17 who deserved justice,
0:06:20 and that that’s something that should matter,
0:06:22 no matter what.
0:06:25 The other side of that is that it obviously exposes
0:06:29 that Trump, someone who has managed miraculously
0:06:30 to market himself as someone
0:06:33 who isn’t just in it for himself
0:06:35 and isn’t part of the swamp
0:06:37 and the cabal of powerful people
0:06:40 that will protect themselves no matter what,
0:06:42 is exposed now as someone
0:06:44 who’s just your run-of-the-mill,
0:06:47 you know, sharky salesman, right?
0:06:48 That’s how it always was.
0:06:50 And for those of us who aren’t particular fans of his,
0:06:52 that’s how we saw him from the jump,
0:06:54 not even just with the Epstein stuff.
0:06:55 In general,
0:06:57 especially if you’d been around New York,
0:06:59 you knew exactly who Donald Trump was.
0:06:59 You know,
0:07:01 the guy who’s stiffing his contractors,
0:07:05 who’s saying disgusting things about women,
0:07:06 who’s, you know,
0:07:08 cheating on everyone he ever married.
0:07:11 And that never penetrated.
0:07:12 So I kind of just gave up hope,
0:07:13 I guess,
0:07:15 that people would see
0:07:16 that aspect of his character.
0:07:18 And that has been affirmed now
0:07:20 that people are seeing this.
0:07:21 The other side of me,
0:07:23 which is a bit of a Debbie Downer,
0:07:25 and I hate to bring the mood of the pod down
0:07:27 because it has been snappy to begin,
0:07:30 is that I’m also concerned
0:07:32 that we’re going to spend all this time
0:07:33 on the Epstein files,
0:07:34 and it won’t matter,
0:07:37 and we’ll forget to talk about real stuff
0:07:38 that actually affect people’s pocketbooks
0:07:39 and how they’re going to vote.
0:07:41 And, you know,
0:07:43 we’ll show up with campaign posters for 2026
0:07:44 that don’t say,
0:07:45 he took away your Medicaid,
0:07:46 and it’ll say, like,
0:07:48 Pedo Island or something.
0:07:50 It won’t be that extreme,
0:07:51 but, you know,
0:07:53 being relentlessly focused on the things
0:07:54 that win elections
0:07:58 are how you capture people’s attention,
0:07:59 and this is,
0:08:01 it’s an enjoyable sideshow,
0:08:03 I guess is how I would describe it.
0:08:06 So what are your feelings besides elation?
0:08:10 Well, so I teach a session on crisis management,
0:08:13 and there’s sort of just three basics to remember,
0:08:14 and they’re easy to remember,
0:08:15 but they’re hard to do.
0:08:17 And the first is to acknowledge the issue.
0:08:20 The second is to take responsibility,
0:08:21 and the third is to overcorrect.
0:08:26 And I would imagine that the vast majority of people
0:08:27 who went to this island
0:08:31 or accepted private jet travel with Epstein
0:08:33 did not engage in pedophilia.
0:08:35 I mean, there’s a lot of strafe here.
0:08:37 A lot of people have been caught up in this who,
0:08:39 I mean, should wealthy, powerful people
0:08:41 do enough diligence on someone to recognize,
0:08:44 okay, if he’s been convicted of a sex crime
0:08:46 or has questionable activities,
0:08:48 I’m not going to, you know, fraternize with him.
0:08:51 But if the president, in my view,
0:08:52 it’s always the cover-up.
0:08:54 It’s not the scandal, it’s the cover-up.
0:08:56 And if the president had said,
0:08:58 you know, when I was younger, I liked to party.
0:08:59 I met this guy.
0:08:59 He was fun.
0:09:01 He was known for being, having a good time.
0:09:03 He was giving money away.
0:09:03 He seemed legitimate.
0:09:06 And I spent time with him, went to the island,
0:09:09 did not engage in any of these illegal activities.
0:09:12 It was a huge error in judgment, and I apologize.
0:09:14 I think this whole thing would blow over.
0:09:16 And if he said, even if he didn’t mean it,
0:09:20 and I’ve instructed my AG to release the files
0:09:22 or look into it, and then just like he said,
0:09:24 he was going to release his taxes and never did,
0:09:26 I think he’d be fine.
0:09:29 But he could not be acting more guilty.
0:09:31 Oh, wait, wait, wait.
0:09:34 Let’s cancel Rosie’s citizenship.
0:09:35 Look over here.
0:09:37 Nothing to see over here.
0:09:38 He could not.
0:09:41 It’s when my dog gets into the trash
0:09:42 and I walk into the kitchen,
0:09:45 I know my dog has gotten into the trash.
0:09:49 I mean, she could not be more transparent in her guilt.
0:09:52 And it’s as if a communications consultant has said,
0:09:56 okay, do you want to come across as guilty as possible?
0:09:58 Do you want it to seem like, in fact,
0:09:59 you weren’t just down there,
0:10:02 but there’s some really ugly information
0:10:03 about you in these files?
0:10:04 Okay, then act like this.
0:10:06 And this is exactly what he’s acting like.
0:10:10 I feel as if he has such strong political instincts
0:10:11 in terms of his base.
0:10:13 And here he’s just,
0:10:16 he literally looks like guilty.
0:10:19 And now I believe there’s something more here.
0:10:22 I used to think, okay, you know,
0:10:24 all of these guys accepted a party.
0:10:25 They like to have a good time.
0:10:27 They like to be around hot people.
0:10:29 And I would imagine just in terms of probability,
0:10:32 the majority of them did not engage in a crime.
0:10:34 I’m sure some did.
0:10:38 But this feels like this guy is scared to death
0:10:40 of this thing coming out.
0:10:43 And he comes across as really guilty.
0:10:44 Having said that,
0:10:45 and then this is my prediction around this,
0:10:46 and I’m curious to get yours.
0:10:50 Every time I’m hopeful that Senator Susan Collins
0:10:53 actually gives a goddamn about her constituents,
0:10:56 or Senator Murkowski is going to find a backbone
0:10:59 and realize that this is really counter
0:11:00 to the values she espouses, too.
0:11:02 And then they all fall in line.
0:11:06 And I think the same thing’s going to happen here.
0:11:06 And, you know, all of a sudden,
0:11:07 Charlie Kirk’s saying,
0:11:11 you know, after trying to stir this conspiracy outrage
0:11:14 and everything about, you know,
0:11:17 the election being stolen and a pedophile ring
0:11:20 in a basement that is non-existent of a pizza shop
0:11:23 where Secretary Clinton was drinking the blood
0:11:24 of sacrificed children,
0:11:27 it is very rewarding to see the snake
0:11:28 eating its own tail here.
0:11:31 But I think eventually he calls them
0:11:33 and they all snap and fuck in line.
0:11:36 And this just, we just move on.
0:11:37 Your thoughts?
0:11:38 Yeah.
0:11:40 I mean, I largely agree with you.
0:11:43 It doesn’t mean that you can’t enjoy something fleeting.
0:11:44 Revel in it.
0:11:46 Like we all love Chinese food, right?
0:11:48 And then we forget that we ate an hour later.
0:11:49 It’s Christmas for Jews.
0:11:50 Chinese food for everyone.
0:11:51 Yep.
0:11:53 So enjoy it.
0:11:57 Like the turning point clips will live forever of,
0:12:01 you know, Steve Bannon and Megyn Kelly and Tucker Carlson,
0:12:05 though I’m very confused about the Mossad connect,
0:12:08 you know, that he was a intelligence asset,
0:12:10 also worked for the Israeli government.
0:12:14 But, you know, I’m happy to indulge in some more conspiracy.
0:12:17 But yeah, I generally think that they’re going to fall in line.
0:12:20 And part of that is that there’s no alternative.
0:12:23 And I’m not even talking about, oh, you’re going to wake up and you’re going to vote for
0:12:24 Democrats.
0:12:33 Donald Trump has so completely owned the right wing of the country that you’ve got nowhere
0:12:33 to go.
0:12:40 There have been many moderate Republican soldier that has tried to stand up there and say,
0:12:41 hey, look over here.
0:12:45 There are other people who believe in, quote, conservative values.
0:12:46 And you could give it a shot.
0:12:50 Nikki Haley, Chris Christie in 2016, everybody and their mother tried.
0:12:51 Right.
0:12:52 Ted Cruz even won Iowa.
0:13:02 And he has captivated the attention and the loyalty of this group of Americans in a way that I
0:13:06 certainly haven’t seen politically, at least in my time.
0:13:09 And so they don’t really have an alternative of somewhere else to go.
0:13:15 And MAGA, more so than the Democrats, which we talk about this part all the time, they don’t
0:13:17 run purity tests the same way we do.
0:13:20 They allow for ideological inconsistency.
0:13:25 And yes, I think that there are going to be people that don’t move past this, but it
0:13:32 is going to be a drop in the bucket compared to the general MAGA movement because they’ve
0:13:34 got no other optionality.
0:13:41 And we’ll see what he essentially makes Pam Bondi do to try to paper over this because they’re
0:13:44 saying now that there’s going to be more releases coming.
0:13:49 And I, I’m not sure there has to be a sacrificial lamb.
0:13:51 If there will be, I think it’s Pam Bondi.
0:13:57 And if I were to put on my conspiracy theory hat, which is very chic, I would say that my
0:14:06 old colleague, Jeanine Pirro, would be a wonderful replacement for Pam Bondi if she ended up exiting
0:14:08 stage left in all of this.
0:14:10 I’m not sure if you’re being serious or not.
0:14:11 You’re being serious?
0:14:12 No, I am being serious.
0:14:15 You think that Jeanine Pirro would be a good attorney general?
0:14:23 I, I, she wouldn’t be our choice necessarily, but I think that Pam Bondi has seemed miraculously
0:14:29 unserious in this role for someone who had a very important job, obviously in Florida, was
0:14:31 instrumental to Trump in being able to win the state.
0:14:35 And she’s been a bit blah, right?
0:14:36 In this role.
0:14:38 She doesn’t even perform that well in the cabinet meetings.
0:14:43 And, you know, Jeanine Pirro is now the U.S. attorney for D.C.
0:14:45 So she is in the administration already.
0:14:49 And it, it wouldn’t surprise me is what I’m saying.
0:14:51 So yes, I am being serious about that.
0:14:56 You know, you, none of these people would be our picks, but the Wall Street Journal even
0:15:03 wrote a piece about how much the D.C. office is loving having Pirro there and how they have
0:15:05 been surprised by her seriousness.
0:15:08 And she’s reverted back to what she was like as a D.A. in Westchester.
0:15:11 So anyway, I’m just throwing that out there.
0:15:13 Well, at 74, she’d be one of the younger people in government.
0:15:14 There you go.
0:15:15 Yeah.
0:15:16 That’s exactly what people wanted.
0:15:18 Jeanine, you look fantastic.
0:15:22 But do you think someone is going to have to go that there’ll be a Mike Waltz?
0:15:24 Is there’ll be a blood offering?
0:15:26 It’s a really interesting one.
0:15:30 I just don’t, I have a striking inability to predict what’s going on here.
0:15:32 I don’t know.
0:15:33 I guess it depends how long it goes.
0:15:37 What do you think of this effort by a couple Democrats to force a vote?
0:15:38 The Ro Khanna vote?
0:15:39 Yeah.
0:15:40 What do you think of that?
0:15:41 Do you think that’s a good move politically?
0:15:41 Yeah.
0:15:42 I mean, it happened last night.
0:15:44 It got voted down.
0:15:45 That’s right.
0:15:45 Shocker.
0:15:47 Well, they’re in charge.
0:15:50 I mean, this is why you got to win fucking elections, right?
0:15:51 Because then you have the votes to do things like this.
0:15:53 Right on, sister.
0:15:53 Yeah.
0:15:55 It’s a well-timed F-bomb.
0:15:55 That’s right.
0:15:56 That’s what we’re supposed to do.
0:15:57 Like one per day, right?
0:15:58 I think it’s the role for Democrats.
0:15:59 That was mine.
0:16:03 But yes, I think it’s right to be drawing attention to this.
0:16:08 And I also think the attitude the Democrats have had about this consistently, which is,
0:16:09 put it all out there.
0:16:15 There are going to be some folks on our side that are in these five—I don’t even know.
0:16:16 They’re playing semantics with it.
0:16:17 Is it a file?
0:16:17 Is it a list?
0:16:24 And Alan Dershowitz, who defended Epstein and also has been accused of being part of this
0:16:28 cabal, has said in interviews recently, there’s a list.
0:16:29 I know there’s a list.
0:16:33 Galene Maxwell is trying to get her story out there.
0:16:37 You know, she was the front page of Drudge, which you know that things are going really
0:16:39 badly for the president when that’s happening.
0:16:45 And you do have a person who is alive and, for now, and hopefully stays alive, sitting in
0:16:48 a jail cell who probably knows a thing or two about this.
0:16:55 So I think Ro Khanna and folks should be out there really holding their feet to the fire,
0:16:56 not losing the plot.
0:17:01 You know, they’re cutting food assistance and Medicaid and giving tax breaks to the wealthy
0:17:03 and all these things that people actually vote on.
0:17:11 But this is a cultural moment, I guess, not only because the Epstein files and did Jeffrey
0:17:15 Epstein kill himself and all of that has taken on pop culture relevance, but it is saying
0:17:22 something generally about class warfare and it is saying something about where the president
0:17:27 fits in that conversation that we don’t usually have a chance to partake in.
0:17:32 It’s usually just partisans kind of peeing into the wind about it, right?
0:17:34 And it doesn’t matter at all.
0:17:36 And now they’re receiving a little bit of it.
0:17:36 Yeah.
0:17:44 So just going back to Janine Pirro as attorney general, I hadn’t realized that she was actually
0:17:46 nominated for a daytime Emmy award.
0:17:48 So I do think she’s qualified.
0:17:48 Yeah.
0:17:53 And also her criticizing the prosecutors, the January 6th defendants saying they hadn’t done
0:17:53 their job.
0:17:54 She’s clearly.
0:17:59 I just got to ask you, Matt Gates, Pam Bondi.
0:18:05 You’re saying you think he’s going to wake up and say, I’d love we really love Merrick
0:18:05 Garland back.
0:18:09 That just feels like even the president could do a little bit better than that.
0:18:10 But anyways.
0:18:12 Anywho.
0:18:12 Yeah.
0:18:13 Please move on.
0:18:18 So just some quick data here around this that shocked me and you’re a pollster.
0:18:18 You’ll find this interesting.
0:18:24 According to new polling from Morning Consult, Trump’s approval rating has fallen about six
0:18:28 percent since his comments about the Epstein case.
0:18:30 That’s that’s a pretty big move, isn’t it, Jess?
0:18:35 Yeah, it’s things have been at certain moments in complete freefall for him.
0:18:40 And we’re going to talk about immigration where that is very pronounced on the economy as well.
0:18:45 But, yeah, people are not into how this is being handled.
0:18:50 And you’re completely correct that there was a way to manage this properly where you just
0:18:54 said, you know, I want to protect the victims, for instance.
0:18:57 And some people would say that’s a load of BS.
0:19:02 But in general, the people who are prone to forgive him would forgive him.
0:19:06 And certainly none of these influencers, I think, would have been mad about it.
0:19:10 So it’s completely relevant that you could go down six points that quickly.
0:19:17 And you know that his team is paying attention to it as well and saying, like, well, what can
0:19:23 we do to leak out enough that nobody is incriminating or we don’t have to hand over the proverbial
0:19:27 list or files or whatever we’re calling it and still be able to manage this base?
0:19:32 Because, you know, he has things that he’s doing that he certainly feels really good
0:19:37 about, right, that he has a couple weeks of good news for his side, you know, getting the
0:19:38 reconciliation bill across.
0:19:42 There’s going to be the rescission bill, the Iranian strikes.
0:19:46 Like, he’d love to be talking about all of those things.
0:19:49 And now this is all that he’s getting.
0:19:53 I mean, trying to change the subject now he’s going after Adam Schiff for a bad mortgage in
0:19:53 Maryland.
0:19:55 I mean, it’s completely laughable.
0:19:59 So just a quick test of your political knowledge here.
0:20:02 There’s only one cabinet member that has a net positive rating.
0:20:04 Any guesses who that is?
0:20:05 Rubio?
0:20:08 No, it’s RFK Jr.
0:20:08 What?
0:20:10 RFK Jr. is the most—he isn’t that wild?
0:20:13 He has a plus 5% net approval rating.
0:20:15 It’s because he’s good looking.
0:20:19 I’m pretty sure that the pollsters asked Rubella and Measles who their favorite cabinet
0:20:20 member is.
0:20:23 OK, with that, let’s take a quick break.
0:20:23 Stay with us.
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0:23:59 Welcome back in a quiet but seismic shift.
0:24:04 The U.S. recently deported eight men to South Sudan, most of whom aren’t even from there.
0:24:10 Under a controversial third-country deportation policy, the legal experts say could amount to enforced disappearance.
0:24:11 Their words.
0:24:20 Their families haven’t heard a word since July 4th, and now ICE has issued new guidance to fast-track similar deportations with minimal notice and virtually no chance for migrants to object.
0:24:24 And that’s just one piece of a much bigger picture.
0:24:26 Across the country, immigration crackdowns are intensifying.
0:24:35 The new remote detention camp in Florida, Alligator Alcatraz, is drawing outrage for inhumane conditions and the fact that hundreds held there have no criminal charges.
0:24:41 Meanwhile, the administration is appealing a court order to blocked race-based immigration rates in California.
0:24:46 But a new Gallup poll shows Americans are more supportive of immigration than they’ve been in decades.
0:24:50 Even a majority of Republicans now favor a path to citizenship.
0:24:52 That’s a switch.
0:25:00 But if you’re wondering how far Trump might go to flex his immigration powers, look no further than his latest threat to strip Rosie O’Donnell of her citizenship.
0:25:01 Yeah, that makes sense.
0:25:03 He called her a threat to humanity.
0:25:04 Huh.
0:25:09 And said she should stay in Ireland, where she moved after his re-election.
0:25:13 Legal experts quickly pointed out that’s not how citizenship works.
0:25:19 Still, it’s a telling moment, one that shows how far the rhetoric and policy is escalating.
0:25:20 It’s a weapon of mass distraction.
0:25:27 Jess, how does the Supreme Court’s green light on third country deportations open the door for more extreme removals?
0:25:36 And what legal or diplomatic fallout do you think we might see if other nations refuse to cooperate or detainees simply vanish, like in the South Sudan case?
0:25:38 I’m going to say it again.
0:25:42 You got to win elections because then you get to appoint people to the court.
0:25:48 And we are so massively screwed because of this conservative majority.
0:25:55 And my expectation is that Trump will probably get another appointment before he finishes in 2028.
0:25:58 And that really scares me.
0:26:02 You know, there are moments where you say, like, Amy Coney Barrett, I love you, or whatever.
0:26:03 Not this one.
0:26:09 And the most disturbing part of it to me, or the thing that I guess stuck out the most,
0:26:14 is that as part of getting rid of this nationwide injunction that came from the lower court,
0:26:21 is that it does away with having to give meaningful notice before deporting to a third country.
0:26:28 So what they’ve been doing is essentially running out the clock or having no clock,
0:26:34 so that family and attorneys cannot get to a lot of these people who have been either wrongfully detained
0:26:39 or really should just be deported back to their country of origin.
0:26:46 And you hear this constantly, whether we’re talking about CECOT or detention facilities all over the U.S.,
0:26:48 makeshift or permanent.
0:26:50 You know, we’ll talk about Alligator Alcatraz.
0:26:55 But nobody is getting their due process.
0:27:00 Nobody is getting time to talk to an attorney, let alone to their wife or their husband.
0:27:04 And that the Supreme Court could be comfortable with that.
0:27:07 Even when I think about it, it was just a few months ago, right,
0:27:13 where they seemed like some sort of arbiters of humanity about the deportations to CECOT,
0:27:18 where they said they have to make a meaningful effort to produce Kilmar Abrego-Garcia.
0:27:22 Now we have South Sudan with no call to your lawyer is fine.
0:27:23 Yeah.
0:27:27 It strikes me that in a weird way, a lot of these things are interconnected.
0:27:30 And I’ve been thinking about, I hate anonymity.
0:27:35 And I’m interviewing today Greg Lukianoff, who’s a big First Amendment guy.
0:27:36 And I imagine he’ll give me a—
0:27:36 He runs fire, right?
0:27:39 Yeah, he’ll give me a cogent argument for why anonymity is so important.
0:27:45 But my sense is our fidelity or conflating free speech with anonymity has led to an environment
0:27:52 where people will weaponize millions of trolls to create intimidation and shape the discourse
0:27:57 around what’s advantageous for some folks who don’t have America’s best interests at heart.
0:28:02 I don’t think people would ever behave this way if they had to have their identity released online.
0:28:07 And in general, I think that almost anything involving a government investigation,
0:28:13 there might be a quiet period for security reasons, but I think there’s no reason not to release everything.
0:28:19 I just—I can’t understand why any file isn’t ultimately released that the FBI aggregates
0:28:21 unless they see it as a security concern.
0:28:29 And then, more generally, what do stormtroopers ice the KKK and weirdos not letting Jews access
0:28:31 certain parts of UCLA have in common?
0:28:33 And the answer is masks.
0:28:40 And when I think about what’s been a hugely accretive or beneficial move for our men and women in blue
0:28:43 and our trust in police forces around the nation, it’s been body cams.
0:28:48 And the fact that they have their badge number and their name right on their—visible on their chest,
0:28:53 and they’re not allowed to wear masks because they have to take accountability for their actions.
0:28:57 And it’s been, I think, one of the greatest innovations in law enforcement
0:29:02 that if you’re going to apply force or you’re here to protect and to serve,
0:29:05 that you need to show all of your actions in 4D color.
0:29:11 And what do you know, ICE enforcement agents are wearing masks, which tells you, in my opinion,
0:29:15 everything about how they’re acquitting themselves or what they’re doing.
0:29:18 They wouldn’t dare want anyone to actually know who they actually are.
0:29:23 So this, to me, comes back to a basic trend in our society that’s a wrong trend,
0:29:28 and that is an acceptance and even reverence for anonymity as opposed to forcing people
0:29:30 to take accountability for their actions.
0:29:34 And people come back and say, well, what about the civil rights lawyer in the Gulf that needs
0:29:35 to protect our identity?
0:29:39 We could absolutely have anonymous accounts online and ensure that people are using them
0:29:42 for reasons where they would need anonymity.
0:29:48 But when you go onto your feed—and, Jess, I imagine you get a lot of this because I found
0:29:53 a disturbing trend online where women are subject to more hate-filled emails and rhetoric and threats
0:29:59 of violence by virtue of the fact that they’re women—I don’t think it’s healthy, this protection.
0:30:06 I think every social media platform should force identity and age gate and accepting a federal agency
0:30:12 that now has greater funding than the Federal Bureau of Investigation, not doing covert or national
0:30:18 security work, but treating people—you just wouldn’t see them putting their knees on the heads
0:30:22 of people or separating women from their 13-year-old screaming daughters if they actually had to show
0:30:23 their fucking faces.
0:30:28 So whether it’s the Epstein files and a belief that, oh, some things should stay out of public
0:30:35 view or masks covering the real identity and thereby reducing the accountability of this
0:30:40 enforcement agency, which we are paying for, I think all of it comes back to the same place,
0:30:43 and that is we have gone way too far with a reverence and an acceptance for anonymity and
0:30:45 not connecting identity to people’s actions.
0:30:46 Your thoughts?
0:30:49 I think it’s an incredibly important point.
0:30:55 And if you wanted to get into the nuance of what has to be for national security, what actually
0:31:00 needs to be put out in the world, I think that you can have those conversations on a case-by-case basis.
0:31:07 But in general, you know that society would run a hell of a lot different if people had to show
0:31:12 themselves, if they had to own what they’re saying in-person and online behaviors.
0:31:20 And you’re completely correct that it is a complete cesspool of what goes online, especially when it comes
0:31:21 to misogyny and harassment.
0:31:22 I’m going through this right now.
0:31:30 There’s a large conservative account that posted a picture of me with my ex-boyfriend and a picture of me with my husband.
0:31:36 And the post says that I cheated on my first husband.
0:31:37 I don’t have a first husband.
0:31:38 I only have one husband.
0:31:41 And, you know, it gets worse.
0:31:44 We’re talking whore, the C word, all of it.
0:31:53 And this is because I responded to the news that Ken Paxton, AG in Texas, his wife has filed for divorce after 38 years together.
0:31:57 It has been rumored for a long time that he cheats on her.
0:32:00 And she’s just had enough at this point.
0:32:09 Anyway, so I wrote The Party of Family Values strikes again because we’re constantly lectured by conservatives about how Democrats are folks that are part of a pedophile ring.
0:32:18 And it has unleashed a torrent online that I haven’t seen worse than actually when the president of the United States of America comes after you.
0:32:22 A lot from women, a lot from good Christians, right?
0:32:25 You know, I’m the best Christian there ever was.
0:32:38 And you’re an enormous whore and can’t get it taken down because of what goes on on social media now and the changes that have happened under Elon Musk.
0:32:42 And so I’m kind of just sitting here having to take it.
0:32:48 The algorithms love this type of outrage, this type of incendiary, ridiculous content.
0:32:55 And first off, I’m sorry you’re going through this, but to anyone that doesn’t have their head up their ass, realize this is all total bullshit.
0:33:08 But what this continues is a long tradition of misogyny that has gone just apeshit online where people don’t have to take accountability for their hateful, weird rhetoric, which sometimes can be very – it’s not only damaging emotionally and mentally.
0:33:11 It can put people in physical danger because people start believing this shit.
0:33:14 And then a crazy person picks up on it.
0:33:29 But it continues a long tradition that has gotten much worse online, which a bunch of dudes refuse to address because it’s difficult to imagine what it’s like to be a victim of this when you’ve never been a victim of this.
0:33:41 And the misogyny here is just so stark because, according to online trolls and especially the right, infidelity is a feature, not a bug for men.
0:33:43 And it’s a crime against humanity for women.
0:33:49 So why not just accuse women of something, whereas it would be a compliment?
0:33:52 I mean, that’s a real man on the Republican side.
0:33:53 He should even be president.
0:34:02 Well, the people who are making these comments about you, one, I don’t know if it’s a media organization, but effectively this goes back to big tech.
0:34:12 The platform platforming this clearly false content, most likely, and it sounds like it’s Twitter, the algorithms see it like how much activity it’s getting.
0:34:17 And so they elevate it and they give it more organic reach than it deserves on its own.
0:34:18 There’s no veracity here.
0:34:24 People wouldn’t be spreading this type of information as far and wide organically.
0:34:32 But because it invokes a lot of reactions and back and forth, and I’m sure people are weighing in and defending you, the algorithms love it.
0:34:40 So they spread it further than it would go on its own, thereby disparaging your reputation and also creating emotional harm.
0:34:49 When you algorithmically elevate content, you are now an editor and there’s no reason you shouldn’t be subject to the same liability and slander laws as traditional media.
0:35:08 Fox News, including your endorsement for attorney general, she was named in a case for spreading misinformation about Smartmatic, purposely and knowingly spreading misinformation around a company, knowing that it was false information that caused material and economic harm.
0:35:14 This is happening to you right now, but because it’s happening to you, Twitter knows this is bullshit.
0:35:18 And it’s very easy to see that this is causing real harm and disruption in your life.
0:35:30 But because they’re, quote unquote, a nascent technology company, which is what it was called in 1997 when this ridiculous 230 law was passed, they are not subject to the same liability as Fox News when they spread misinformation.
0:35:44 So this all comes back to big tech figuring out a way to weaponize Republicans and Democrats to avoid any real responsibility or liability for things that traditional media has been responsible and liable for.
0:35:52 It not only tears at the fabric of our society, it not only tears at the fabric of our society and coarsens our dialogue, but creates a post-truth society where nobody knows what to believe anymore.
0:35:59 Because the reality is, if somebody sees a story over and over, it becomes, in their mind, naturally, less of a lie.
0:36:03 It’s like, oh, I’m seeing this everywhere and there must be some truth to it.
0:36:13 No, it just means the algorithms have decided, regardless of how disparaging or slanderous it is, if it creates more engagement, we’re going to spread it far and wide.
0:36:26 So I kind of lay this at the feet, not only of the people who created this false narrative, but the fact that, one, the social media platform doesn’t force identity when people weigh in and say vile things about you.
0:36:27 We should know who they are.
0:36:29 They should have to stand behind it.
0:36:37 And also, this organization or the people posting this content, or the platform specifically, should be subject to the same laws as traditional media.
0:36:43 Anyways, I’m sorry you’re going through that, and I hope you recognize that in the moment, everything seems worse than it actually is.
0:36:48 This isn’t that meaningful, and everyone will forget about it and move on.
0:36:49 Yeah, I hope so.
0:36:55 Yeah, and I’m, you know, it’s been a few days, and you learn to move on quickly, which is probably another statement on how society works.
0:37:09 But I just wanted to add to your analysis to say that a critical component of why things are so bad is that we are so intellectually lazy now that no one wants to even Google something.
0:37:22 You know, this happens constantly, and I understand that it is baked into the job for me to bring information that is different from the mainstream conservative point of view that my colleagues are espousing.
0:37:38 But because you don’t want to spend any time taking a look at what Quinnipiac is saying or taking a look at what Marist is saying or even the Fox News poll, you just immediately dismiss anything that makes your antenna go a little haywire.
0:37:47 You know, to loop it back to the immigration issue, Trump has blown his best issue in historic terms.
0:37:57 I mean, he’s negative 27 on immigration now with Gallup, negative 16 with Quinnipiac, negative 9, Marist, Fox News, minus 7.
0:37:59 Totally lost support of the Hispanic votes.
0:38:04 Remember, that was one of their favorite things to talk about, how the hombres actually wanted this.
0:38:10 Well, it turns out the hombres are not actually interested in the way immigration law is being enforced at this particular moment.
0:38:15 And it probably has to do with the fact that 70 percent of people who are being detained haven’t been convicted of anything.
0:38:18 So they say, oh, well, people are pending charges.
0:38:22 You can say whatever you want about someone like this is the United States of America.
0:38:27 You have to be convicted of something, not just that they’re floating the idea that you did a very bad thing.
0:38:34 But you talk to the strongest section of his base about this, of Trump’s base.
0:38:38 Those poll, they’re all fake news polls, right, if they even exist.
0:38:45 And they haven’t spent any time actually going around and looking at a source that doesn’t confirm their immediate bias.
0:38:56 And so the masking thing with ICE agents, I don’t know if you’ve seen these stories, but there are people impersonating ICE agents, just like putting on masks and robbing, throwing people in trucks.
0:39:06 I mean, and some folks don’t even know if it isn’t actually an ICE agent that is doing something like this because the reality on the ground is that there are folks that are doing this.
0:39:09 And Brian and I were talking about this over the weekend.
0:39:18 We hadn’t been seeing that many stories from New York City about these immigration raids, like hearing a lot about what’s going on in Chicago and in Boston.
0:39:30 And I heard from a friend that apparently in big immigrant neighborhoods out in Queens in particular, that there are ICE agents everywhere there now.
0:39:37 So the city is not being spared because Eric Adams is a friend of the Trump administration in any way.
0:39:43 And I assume that the stories are going to start rolling in of these terrible things happening, you know, all over the subways.
0:39:52 And it’s just I’m not saying that immigration law doesn’t need to be enforced, but I don’t want our country looking like this.
0:39:54 Yeah, but it’s it’s so gross.
0:40:05 It’s performance and pageantry and fear and not really addressing the issue because going to the very core of the issue, while most people acknowledge immigration has been the secret sauce for American prosperity or one of them.
0:40:11 What they don’t want to have an honest conversation about is that the most profitable part of immigration has been illegal immigration.
0:40:14 And we can just wake up with tens of millions of illegal immigrants.
0:40:23 It’s a flexible workforce that comes in, pays Social Security taxes, commits crimes at a lower rate and then melts back to their own country when the work dries up.
0:40:27 It’s been this unbelievable, profitable, flexible workforce.
0:40:32 And where I see the far right go is they say, look, and it’s a solid argument.
0:40:33 Theoretically, they broke the law.
0:40:34 They broke the law.
0:40:35 They knew they were breaking the law.
0:40:37 They should be subject to enforcement.
0:40:45 But they never want to talk about, well, based on that law, shouldn’t we be prosecuting all the employers who knew they were employing undocumented workers?
0:40:47 And by the way, that is a crime.
0:40:49 But we don’t talk about that.
0:40:56 We don’t talk about the cut and dry, the employers, whether it’s fast food restaurants or families employing undocumented workers.
0:41:03 We seem to forgive those less brown, older, less vulnerable people, right?
0:41:06 So we’re just not focused on the right thing.
0:41:15 If you want to talk about an alien invasion, if you want to talk about millions of people storming the shores and offer their services for free, you want to talk about disruption.
0:41:26 What if seven or eight or 10 million immigrants stormed the shores, just overwhelmed the United States and were willing to work for free 24 by seven?
0:41:27 And what would that do to certain industries?
0:41:29 Well, it’s here, folks.
0:41:30 It’s called AI.
0:41:45 And instead of focusing on AI and taking some of that $12 billion and upskilling people and training to be critical thinkers and understand AI and how to leverage it and job training to get people out of things like trucking, which clearly AI is going to just decimate.
0:42:11 We want to scare the shit out of people and increase inflation by getting rid of three percent of America’s working population, which is ISIS goal, which will be somewhere between five and 15 percent of the agricultural and construction communities between tariffs on drywall gypsum, Canadian lumber and then emptying out construction sites of which 15 percent of the workforce is undocumented workers.
0:42:15 And by the way, when you lose 15 percent of your workforce, the industry kind of collapses for a while.
0:42:22 You’re going to see massive inflation and you’re going to see huge economic strain.
0:42:43 But instead, you know, instead of focusing on our economy, instead of focusing on how we would use that money to upskill people and protect jobs, I just think the president, I think they love this macho mass big guys ripping families apart that they’re I think so many Americans are so angry and upset that they actually enjoy some of this footage.
0:42:45 It’s like, oh, we’ll show those, you know, those criminals.
0:42:53 But, you know, the nice the nice white family that owns the car wash has been hiring undocumented workers and wink, wink.
0:42:56 Everybody’s put up with this for a long time.
0:42:58 Leave those good Americans alone.
0:42:59 I wonder what’s going to happen.
0:43:04 I think at some point there’s going to be a confrontation that’s going to turn violent in the United States.
0:43:07 I think I think people are so correctly horrified.
0:43:12 There was a really interesting video taken in a hospital where doctors just surrounded ice and said, what are you doing?
0:43:13 Get out of here.
0:43:18 And what is going on here is so craven and so aggressive and so upsetting.
0:43:23 I mean, at least the brown shirts in Nazi Germany showed their faces.
0:43:27 You know, these guys showing up with masks and the militarization.
0:43:31 I mean, it’s happened incrementally, so we’re not a shock.
0:43:45 But if someone had played just a few years ago what was going to happen here at car washes in Calabasas or to, you know, Uber drivers or or people showing up for their citizen hearings or church.
0:43:49 I think we would have just said, well, of course, that would never happen in America.
0:43:51 Well, well, it is.
0:43:57 Anyways, with that, we’ll take another quick break and we’ll be back in just a moment.
0:44:03 OK, welcome back.
0:44:06 Before we go, Washington Representative Marie Glessencamp-Perez.
0:44:13 She’s doing a few lawmakers have dared to do publicly question whether some of her older colleagues are still mentally fit to serve.
0:44:21 The 36-year-old Democrat is pushing a proposal that would allow the House Ethics Office to assess whether a member’s cognitive decline is impairing their ability to do the job.
0:44:24 An idea that was quickly swatted down by her colleagues in committee.
0:44:26 Are they really fucking old people?
0:44:27 Seriously, it’s become.
0:44:28 Actually, no.
0:44:28 Really?
0:44:31 They’re not really fucking old people that swatted it down.
0:44:34 It’s people who want to hang out for the next 50 years in Congress.
0:44:40 Or who are scared of the really fucking old people who wield a tremendous amount of power as well.
0:44:47 Fair Point, her call for cognitive oversight lands in a moment when concerns about mental acuity in government aren’t just theoretical, they’re fueling investigations.
0:44:57 Republicans are now probing whether Biden was mentally fit enough to authorize end-of-term and clemency decisions, claiming staff may have used an auto pen without his direct input.
0:45:02 Biden says he made every decision himself and slammed Trump and his allies as liars.
0:45:06 But still, the broader question remains, when is it too old to govern?
0:45:09 Curious on your thoughts on this.
0:45:11 How realistic is Perez’s proposal?
0:45:16 And could it actually break an unspoken code of silence around age and capacity in Congress?
0:45:19 Or will it just be another flashpoint that fades without reform?
0:45:19 What do you think, Jess?
0:45:23 It’s definitely not going to pass.
0:45:24 Right.
0:45:33 But I do think that it’s important for people to show who they are and their morality and their beliefs.
0:45:34 And that’s what she’s doing.
0:45:36 She’s just making a public declaration.
0:45:47 And this is coming from her constituents, who were all deeply concerned about President Biden and his mental fitness, as millions of Americans were, yourself included.
0:45:56 And she’s putting her stake in the ground, where she just says, this is something that we need to be talking about more and to be thinking about.
0:46:04 And maybe it’s not the end of the world if there’s some mechanism to step in when there is a problem.
0:46:12 And the argument against it is, well, we, you know, we have elections and they have to stand again and get voted back in.
0:46:17 But in a lot of these districts, they’re rubber stamps for whoever is in the majority.
0:46:19 You’re talking about D plus 30 districts.
0:46:23 And if someone isn’t getting primaried, then that carries on.
0:46:30 There’s a lawmaker, I think she’s 86 years old, who’s been flirting with maybe I’m going to run, maybe I’m not going to run.
0:46:35 Her staff has to kind of clean up after she makes a comment about it.
0:46:36 And now she’s decided that she’s going to run again.
0:46:40 Maxine Waters, she’s 86 years old.
0:46:41 I get it.
0:46:45 These are only two-year terms, so it should be out by 89 or whatever.
0:46:49 But, like, some things just don’t feel appropriate.
0:46:54 And I also think that there is an unfair sliding scale for folks.
0:47:02 Like, I interviewed Greg Kassar for our podcast, and he wants a new generation of leaders.
0:47:03 He’s part of that.
0:47:05 He’s on the progressive left of the party.
0:47:07 He’s been on tour with Bernie and AOC.
0:47:12 So I say, you know, well, Bernie’s 82 years old, and he’s going to run again for his Senate seat.
0:47:16 Well, there’s a carve-out for Bernie because Bernie has a ton of energy.
0:47:17 And, yes, I get it.
0:47:23 Bernie Sanders, you have a lot more faith in his ability to survive a term than you did necessarily about Joe Biden.
0:47:28 But you either have a standard or you don’t have a standard.
0:47:38 And that’s where this representative, Glucin-Kamp-Perez, is kind of putting her stake in the ground and just saying, we need to have standards that everyone abides by.
0:47:51 And then you can plan for what life after Congress looks like for you if it’s just retirement or maybe you want to go into the private sector or you want to go back to teaching if you’re a teacher or maybe, you know, want to travel the world, whatever it is.
0:48:02 But a lot of people have been talking a big game about passing the torch and a new generation of leaders or what it takes to do this job, which is an incredibly special, elite job.
0:48:04 There are only 435 people with this job on the Senate side.
0:48:09 Only 100 people in a country of 330 million who get this job.
0:48:11 Take it more seriously.
0:48:13 I love this.
0:48:24 And I think it’s just insane that we’ve decided that a 34-year-old doesn’t have the cognitive ability or life experience to run for president, but someone, 81, can do it.
0:48:30 16 years, term limits, or 18 years and 75, you’re out.
0:48:31 It’s just insane to me.
0:48:38 We have, we age gate all sorts of tests, whether it’s pilots, whether it’s CEOs of public companies.
0:48:44 And we’ve decided that, arguably, to your point, the most important decision, we’re not going to have age limits on.
0:48:46 And it really hurt Democrats.
0:48:49 I think five representatives died.
0:48:50 I think it’s three.
0:48:50 Was it three?
0:48:52 I thought it was five of them passed away.
0:48:53 Like, since the term.
0:48:54 Yeah, three.
0:48:55 It’s a lot of people.
0:48:57 I mean, I joked, I’m going to go see the F1 movie.
0:49:03 And I’m like, I think it’s hilarious that Brad Pitt is an F1 driver who clearly, I can, spoiler alert, I’m pretty sure he probably wins the race.
0:49:07 But in 10 years, his kids are probably going to take his driver’s license away.
0:49:13 It not only creates a situation where you have people who are cognitively impaired and make poor decisions, including to run again.
0:49:15 Bernie should not be allowed to run again.
0:49:17 That’s insane because biology is undefeated.
0:49:24 And by the time he’s 86 or 87, he’s probably going to slow down and not be able to represent his constituency very well.
0:49:27 And there will always be examples of the 100-year-old who runs a marathon.
0:49:39 But in general, we’ve decided that 17-year-olds don’t have the cognitive capacity to decide to join the army for good reason or that they, you know, kids should not be able to access pornography, at least theoretically.
0:49:42 We age-gate all sorts of stuff on the bottom end.
0:49:47 And the cognitive decline is just as severe on the back end.
0:49:49 Of course we should age-gate this.
0:49:51 And the dialogue, I believe, has actually progressed.
0:49:58 When I first said that Biden was too old to run on Bill Maher two and a half years ago, it was called an ageist and how dare you.
0:50:16 And, okay, in addition to the cognitive decline, which puts serious strain on the public, having to put up with individuals who no longer have good judgment or even just the capacity to do their jobs, it creates an environment where we’re not thinking long-term.
0:50:19 Two-thirds of Congress will be dead within 25 years.
0:50:24 Are they really that concerned at the end of the day about deficits and climate change?
0:50:35 And they get all indignant and clutch their pearls that they got as a wedding gift in the 30s and say, okay, you’re being ageist.
0:50:38 We care about climate change and our grandchildren?
0:50:39 No, you don’t.
0:50:44 Listen to young people talk about the deficit and the climate change.
0:50:46 They’re going to be around to have to pay this shit back.
0:50:58 They’re going to be around when everyone has to move out of or there’s forced mass migration and an unbelievable tax on everybody when we have to pay for disaster relief on super fires that are happening every other week.
0:51:02 So we absolutely need a representative democracy.
0:51:09 And the average age of our elected representatives across the world, this is a global phenomenon, has risen from 55 to 62.
0:51:16 And the U.S. has the oldest, I believe, of any G7, except we haven’t taken a note from other countries.
0:51:19 Most countries, there’s age gates.
0:51:22 You know, firefighters in the U.S. have to retire at 57.
0:51:29 You have to retire from the armed forces at 64 because you might make bad decisions to kill other people when you’re 84.
0:51:36 But we’ve decided, no, you can make decisions about who gets food stamps or what nations we do or do not declare war against.
0:51:41 Finland requires medical testing for driver’s license applicants after the age of 45.
0:51:47 England has an age limit of 75 for sitting on a jury.
0:51:57 They realize at 76, you may not have the cognitive ability or the physical stamina to pay attention to ensure that an individual is acquitted fairly through the court process.
0:52:01 Eighty-six members of the House and 33 members of the Senate are now over the age of 70.
0:52:04 In the House, the average age is 57.
0:52:07 In the Senate, it’s 65.
0:52:10 And this is the third oldest Congress in 1789.
0:52:11 Enough already.
0:52:12 Enough already.
0:52:13 We need age limits.
0:52:18 If we have them on the bottom end, there is no reason we shouldn’t have them on the top end.
0:52:23 It’s also a worse problem on the Democratic side than it is on the Republican side.
0:52:23 Fair.
0:52:27 Trump aside, who’s obviously an incredibly old president.
0:52:34 But the rank and file, and this is they doing as well with the Supreme Court nominations, too.
0:52:39 You know, I could see a world in which we were in power and we’re like, I’m really into this 65-year-old.
0:52:40 I think it would be great on the bench.
0:52:42 I’m like, take the teenager.
0:52:44 Put the teenager on the court.
0:52:45 Put in Representative Tallarico.
0:52:47 That’s a great plug.
0:52:47 Yeah.
0:52:49 We’ll have him on the podcast on Friday.
0:52:49 There you go.
0:52:51 This is how you’ve got to be thinking about it.
0:52:57 I do want to say something positive about the current state of Democratic politics.
0:52:58 Go on.
0:53:03 Because we don’t do this nearly enough, and these are fundamentally our people.
0:53:14 There’s new polling out from Tony Fabrizio, Trump’s pollster, showing that Republicans are trailing on the generic ballot in 28 House battleground seats.
0:53:19 There are huge amounts of pickup opportunities, especially with the big, beautiful bill.
0:53:21 Don’t blow it by only talking about Epstein.
0:53:33 And one thing that I saw that I thought you would really like is there’s this up-and-coming ad-making firm that’s Cool Campaigns, Van Ness Creative.
0:53:41 And they have basically issued a warning saying that if you’re not going to get online, then you just need to retire.
0:53:52 That no one should be making you ads or supporting campaigns of people who cannot communicate the way that the world is getting information and ingesting it.
0:54:00 And, you know, there’s an effort that you can make if, you know, you’re older and all you can do is hold a camera up to your face while you’re sitting in a car or whatever.
0:54:13 That’s still making some sort of effort, but there are actually pretty high numbers of folks in elected office who don’t even want to partake in the main vehicle for political communication at this point.
0:54:19 And that those people need to retire along with the 85-year-olds.
0:54:19 I agree.
0:54:25 Across both chambers, there are 20 members who are 80 years or older who likely think CHAT-GPT is a venereal disease.
0:54:31 I mean, the Congress is beginning to look like the waiting room at a cardiologist in Boca Raton.
0:54:33 It just, for God’s sakes, enough already.
0:54:34 All right.
0:54:37 Jess, that’s all for this episode.
0:54:39 Thank you for listening to Raging Moderates.
0:54:42 Our producers are David Toledo and Eric Jenikas.
0:54:44 Our technical director is Drew Burrows.
0:54:47 Going forward, you’ll find Raging Moderates every Wednesday and Friday.
0:54:53 Subscribe to Raging Moderates on its own feed to hear exclusive interviews with sharp political minds.
0:54:58 This week, Jess and I are talking with, and we’re excited about this, with Texas State Representative James Tallarico.
0:55:03 Make sure to follow us wherever you get your podcasts so you don’t miss an episode.
0:55:05 Jess, have a great rest of the week.
0:55:05 You too.

0:00:03 It’s valid that you want to protect them, but is helicoptering protecting them?
0:00:06 No, because they’re not developing the skills they need to do it themselves.
0:00:11 So what you need to do is be able to step back and let them fall.
0:00:18 You have to trust in the wisdom that growth happens through quote-unquote failure, that
0:00:22 when you try and protect your kids from failure, you’re ultimately protecting them from growth.
0:00:27 I’m Guy Kawasaki.
0:00:31 This is the Remarkable People Podcast, and today is a special edition.
0:00:34 We’re coming to you from Honolulu, Hawaii.
0:00:38 So what you see behind me is not a virtual background.
0:00:39 That’s a real background.
0:00:41 That is Waikiki.
0:00:43 I’m near Diamond Head.
0:00:46 I’m looking towards Waikiki the other way.
0:00:48 Usually Diamond Head is that way.
0:00:50 Queen Surf is that way.
0:00:54 So I’m not here to be the Hawaii Visitors Bureau.
0:01:00 I’m here to help you be remarkable, and we have found a very remarkable person.
0:01:02 She is in California right now.
0:01:09 If I were in California right now, we’d be only about 20 miles apart, but now we’re 2,500 miles apart.
0:01:12 So our guest is Caroline Fleck.
0:01:17 And I got to tell you, her book is the most interesting.
0:01:22 And I have to tell you, Caroline, I felt convicted in your book many, many times.
0:01:27 And yeah, I feel like I’m a bad parent, bad spouse, bad everything.
0:01:28 So anyway.
0:01:28 No, no.
0:01:38 So Caroline is a clinical psychologist, and her practice is really focused on emotional resilience and communication.
0:01:43 And she kind of bridges psychology and real-world challenges.
0:01:47 And she’s very famous for this concept called validation.
0:01:49 So that’s what we’re going to talk about.
0:01:50 Okay, Caroline?
0:01:52 Yeah, I got to tell you.
0:01:59 So, you know, first of all, I often go off the rails when I start a podcast, and that’s going to be true today.
0:02:03 So I have to tell you, there’s one sentence in your book.
0:02:07 When I read it, I stopped.
0:02:09 I was reading the PDF.
0:02:11 I selected it.
0:02:12 I quoted it.
0:02:13 I put it in my notes.
0:02:18 And you will not guess what quote I took, but I love this sentence.
0:02:23 I’ve never read a sentence like this in a business book, and I have to read 52 books a year.
0:02:24 Oh, my God.
0:02:31 The quote is, an anecdote isn’t a substitute for scientific evidence.
0:02:32 Oh, my God.
0:02:33 Oh, my gosh.
0:02:37 Basically, you just indicted every nonfiction writer.
0:02:39 My God, especially business book.
0:02:43 Malcolm Gladwell is turning over in his grave right now.
0:02:45 Oh, I love that.
0:02:46 I appreciate it.
0:02:50 And then we’re just going to fanboy out a little bit for a while.
0:02:50 Let’s do it.
0:03:00 So then I come to the end of your book, and I have to say that I think your epilogue is the best epilogue I have ever written a book.
0:03:02 Oh, my gosh.
0:03:05 I hope I don’t get in trouble with Madison for saying this.
0:03:10 And it starts with the sentence, I have no boobs.
0:03:11 And I read that.
0:03:15 I said, you know, that is not a typical epilogue start.
0:03:18 And then you go in to discuss cancer and all.
0:03:20 I’m like, wow, what a powerful epilogue.
0:03:21 Anyway.
0:03:23 Oh, my gosh.
0:03:24 You are so kind.
0:03:25 Thank you.
0:03:28 And thank you for reading the epilogue, actually.
0:03:32 Because a lot of people, they don’t even finish the book, much less read epilogues these days.
0:03:33 So I appreciate it.
0:03:39 I loved in the middle of the book where you said something like, well, if you’ve gone this far, I really thank you.
0:03:44 And you don’t have to read the rest of the book because you probably read more than most people ever read in a book.
0:03:47 I looked at that and said, that’s probably true.
0:03:53 I’m going to put that line in my next book because one of the key skills you talk about is copying.
0:03:56 And I know how to copy people.
0:03:57 I work for Steve Jobs.
0:03:59 If anything, I learned what to steal.
0:04:02 And that is a concept worth stealing.
0:04:04 Oh, I love that.
0:04:05 I love that.
0:04:06 What to steal.
0:04:09 I hadn’t thought about copying in those terms, but you’re exactly right.
0:04:10 It is.
0:04:18 Well, I think there’s a very famous Picasso quote, something along the lines that real artists steal or something like that.
0:04:18 Yes, yes, yes.
0:04:19 I know what you’re saying.
0:04:19 I know.
0:04:21 And it rang true to me as well.
0:04:25 Thank God for Xerox Park is all I can say.
0:04:29 So listen, let’s just start off really basically.
0:04:33 Could you just explain what is validation?
0:04:36 And I don’t mean for your parking ticket at the restaurant or the hotel.
0:04:40 What is validation to a clinical psychologist like you?
0:04:52 Validation is simply a way of communicating that you’re there, you get it, and you care, and that you accept the other person non-judgmentally.
0:04:57 It’s the feeling of feeling seen or feeling heard.
0:05:04 When we have that experience, what we are experiencing, according to clinical psychologists like myself, is validation.
0:05:06 We feel validated.
0:05:09 We feel like somebody sees us.
0:05:11 They understand us.
0:05:16 They see the rationality not just in our thoughts, but also in our emotions.
0:05:23 And it’s probably that latter part, seeing the rationality in our emotions, that really does something for us.
0:05:28 Now, are you telling me that everybody’s feelings are valid?
0:05:32 Are there not cases that you shouldn’t validate them?
0:05:35 Leave that to the psychologists.
0:05:47 And I mean that so seriously because, and this is serious, the effects of invalidation on children, on adults, on everybody, it’s devastating.
0:05:59 So coming from an environment in which a child, for instance, was exposed to pervasive invalidation, meaning when they said they felt sad, the parents said, walk it off, right?
0:06:02 If they were frustrated, it’s your being a baby.
0:06:06 Basically, whatever emotion they expressed was dismissed or criticized.
0:06:15 That type of invalidation leads to some of the most serious types of psychopathology or psychological disorders that we know of.
0:06:17 So it’s not small stuff.
0:06:22 And so if you don’t understand where someone’s coming from, you can disagree with their thoughts.
0:06:24 You can argue with their reasoning.
0:06:29 Just don’t be in the business of telling people that they don’t feel what they’re telling you they feel.
0:06:31 A psychologist can unpack that.
0:06:32 You just focus on something else.
0:06:37 You haven’t been talking to my children, have you?
0:06:41 Well, yeah.
0:06:41 Okay.
0:06:47 So just give me like a definition of what are the qualities of what’s valid.
0:06:50 You raise a good point, which is, is everything valid?
0:06:57 As psychologists, when I’m working with patients, I need to form a relationship and I need to do that quickly.
0:07:02 And the quickest, swiftest way to form a relationship is through validation.
0:07:03 Okay.
0:07:04 It’s by validating them in some way.
0:07:07 And I’ve got three things I could validate.
0:07:11 I could validate their thoughts, their emotions, or their behavior.
0:07:12 Okay.
0:07:14 Thoughts are valid if they’re logical.
0:07:16 Behavior is valid if it’s effective.
0:07:19 Emotions are valid if they fit the situation.
0:07:20 All right.
0:07:23 But you only need to focus on one of those.
0:07:24 Does that make sense?
0:07:25 It does.
0:07:28 But let’s hypothetically say…
0:07:28 Do it.
0:07:28 Do it.
0:07:29 Yeah.
0:07:34 Let’s hypothetically say a politician shows up in your office and says,
0:07:39 I believe it’s Jewish space lasers that’s controlling the weather.
0:07:41 Are you going to validate that?
0:07:42 No, I’m not.
0:07:43 Those thoughts are not valid.
0:07:51 However, if they say to me, and I am terrified about the implications of that, I want to get
0:07:57 out and raise as much money and get as much support as I can to protect us from this manipulation,
0:08:02 that emotion, I understand that emotion based on what they’re thinking.
0:08:09 The thoughts are not valid, but the emotion makes sense in light of what they’re thinking.
0:08:14 That is my whole job, both as a clinical psychologist, working with folks who have
0:08:19 thought disorders and all sorts of things, and frankly, as a parent to a young kid, a lot
0:08:21 of what they’re saying, I’m like, that’s not rational.
0:08:22 That does not quite make sense.
0:08:25 And yet her emotion is real, right?
0:08:28 I don’t need to validate the thought to speak to the emotion.
0:08:30 And this is the critical thing.
0:08:38 You stand no chance of changing someone’s opinion, of getting through to them, of challenging
0:08:42 their assumptions if they don’t feel accepted by you.
0:08:52 So, are you telling me that validation is not at all the same thing as agreement?
0:08:54 It is not.
0:08:57 I’m so glad you flagged this because this is where folks get stuck.
0:08:58 We’re afraid.
0:09:00 Well, I don’t want to say that I agree, right?
0:09:01 I don’t agree.
0:09:02 I’ll give you an example.
0:09:07 I’m a vegetarian for animal, ethical, and environmental reasons.
0:09:13 That said, I see a lot of valid reasons why somebody would choose to eat meat, okay?
0:09:14 I don’t agree with them.
0:09:16 I make a different decision.
0:09:22 But if I just wanted to validate what’s logical there, there’s tons that I could focus on.
0:09:26 Now, if I wanted to try and change their opinion or change their position, I could come at that a
0:09:33 different way, but I don’t have to agree with someone to see the facts that they’re building
0:09:37 off of and to see the logic in what they’re saying, presuming it’s there.
0:09:42 In the case of the politician that you described, the logic wasn’t there, and so I couldn’t validate
0:09:42 that.
0:09:44 But this is the game.
0:09:46 It’s trying to find the kernel of truth.
0:09:52 What’s valid in this person’s perspective and zoning in on that first, rather than what
0:09:57 do I disagree with and let me hammer that over and over again until I get through to them.
0:10:04 So I’m going to ask you to tell the story, which was my favorite story of the whole book,
0:10:06 because I felt convicted.
0:10:10 I’ve done things like this, of Havana and the tick.
0:10:11 Can you please tell that?
0:10:13 That is a great story.
0:10:16 Every parent will be able to relate to Havana and the tick.
0:10:19 Havana is my daughter.
0:10:22 She’s 11 now, but I think she was maybe seven.
0:10:24 And we were going on a hike, all right?
0:10:27 And I was very excited going down to one of my favorite places to hike.
0:10:29 And it’s a drive.
0:10:31 It’s like 30, 40 minutes.
0:10:35 And we get there and Havana is in a mood, right?
0:10:39 Like, you know that feeling when you open, like one of your kids is off and it’s just like
0:10:43 the entire afternoon hangs in the balance, like which way is this going to go?
0:10:46 And she was feeling a little carsick and she was crabby.
0:10:50 And so we start hiking and she’s kind of dragging, but she’s doing it.
0:10:51 We’re not even five minutes in.
0:10:54 And she screams like she has been shot.
0:10:55 Okay.
0:11:00 And she says, oh my gosh, this tree, mom, it stabbed me.
0:11:02 And I kind of, I’m like, where?
0:11:03 She lifts up her shirt.
0:11:04 I don’t see anything.
0:11:05 I’m like, let’s keep going.
0:11:07 You know, come on, come on.
0:11:09 And that’s it.
0:11:11 Like the trip is over from that point for her, right?
0:11:14 Every five minutes she needs to stop to rest her back.
0:11:16 And she wants us to carry her.
0:11:19 And I find myself being like, we got to keep going.
0:11:20 Come on, come on.
0:11:21 I don’t want to reinforce this.
0:11:24 I don’t want to just give into this.
0:11:25 I’m a behaviorist.
0:11:26 I understand how this works.
0:11:28 And then, oh golly.
0:11:29 Oh boy.
0:11:33 We get home and she’s still complaining about her back.
0:11:35 So she goes to get in the shower.
0:11:36 I’m helping her get in the shower.
0:11:38 She says, it hurts too much to lift my arm.
0:11:40 And I’m like, oh my golly.
0:11:47 I lift off her shirt and I see she has this huge tick lodged in her back.
0:11:51 I actually had a picture of it that I was going to include in the book, but it was too grainy
0:11:54 because it looks so gnarly.
0:11:55 Okay.
0:12:02 And all of a sudden I realized that the emotion, the frustration, the pain that she
0:12:04 was describing was valid.
0:12:11 And I had spent the last however many hours invalidating her with, we can’t be overdramatic.
0:12:15 If you’re upset, you can use your words, but like all the traditional parenting stuff.
0:12:19 And I just had this moment of like, well, I stepped in that one.
0:12:27 Well, in a sense, I’m glad to hear that even a clinical psychologist, an expert like you
0:12:28 blows it.
0:12:30 Oh, that’s, that’s the whole name of the game, right?
0:12:35 I mean, it, but it really is about, as you describe in your book, that growth mindset that
0:12:37 I can do better.
0:12:43 I think it’s critical to look at skills like validation as skills.
0:12:45 You develop them over time.
0:12:50 You grow into them through practice, through exposure and through understanding.
0:12:53 And so, yes, please go screw it up.
0:12:55 That’s the whole point.
0:12:56 That’s the only way you learn.
0:13:04 Now you draw a very clear dichotomy between validation and problem solving.
0:13:05 Yeah.
0:13:09 So let’s explore the relationship between those two things.
0:13:11 We’ve talked about validation.
0:13:17 Is validation now a precursor to problem solving, or is it a substitute for problem solving?
0:13:20 Or is it a foundation for problem solving?
0:13:22 Oh my gosh.
0:13:26 The relationship between the two is almost like a, a Zen cone.
0:13:30 If you try and validate someone, a Zen cone, like a riddle.
0:13:33 I know what a, I know what a shave ice cone is.
0:13:35 I don’t know what is a Zen cone.
0:13:36 It’s like a riddle.
0:13:43 And it seems like two things don’t go together, but to figure out the riddle, you have to understand
0:13:46 how they can coexist, but it doesn’t make sense because they seem kind of diametrically
0:13:47 opposed.
0:13:55 And at the core of this is the idea that acceptance, accepting someone is actually critical to helping
0:13:56 them change.
0:13:58 And so how is that?
0:14:01 I mean, if you accept someone, you can’t also want them to change.
0:14:02 That doesn’t work.
0:14:04 And yet it, it does.
0:14:12 So problem solving, problem solving is an attempt to change how someone feels, how they’re reacting,
0:14:14 whatever outcome they had.
0:14:16 It comes from a good place.
0:14:17 Our kid comes home.
0:14:18 They didn’t do well on their quiz.
0:14:20 They’re so upset.
0:14:22 We jump in with, it’s okay, right?
0:14:23 It’s not that big a deal.
0:14:28 Which is a subtle attempt to change how they feel.
0:14:32 I’m challenging their thoughts in that moment.
0:14:33 I’m trying to reframe it.
0:14:38 I could then come at it and say, next time, let’s just review your words on the drive into
0:14:38 school.
0:14:44 There I am trying to problem solve or change their behavior so that we get a different outcome
0:14:45 next time.
0:14:48 That is all change focused.
0:14:52 It’s very different from saying, ah, you must be devastated.
0:14:58 When I was your age, I failed a math quiz and I remember crying in the bathroom at school.
0:14:59 I was so upset.
0:15:01 And my mom had to come pick me up.
0:15:03 And right, really just leaning into that.
0:15:06 That is a very different response.
0:15:13 And usually, and I can say this with some authority, as someone who speaks to people day in and day
0:15:14 out about their problems.
0:15:20 When folks come to us with an issue, they are seeking validation and not problem solving.
0:15:22 At least initially.
0:15:28 They need to trust that we understand if they’re going to listen to us down the line anyway.
0:15:29 Right?
0:15:33 Like, I don’t take the advice of people if I don’t think they understand the situation or can
0:15:34 relate to where I’m at.
0:15:36 So where do you draw the line?
0:15:37 Okay.
0:15:39 So I understand the validation part.
0:15:40 You had a bad quiz.
0:15:41 I understand.
0:15:42 I had the same thing.
0:15:45 You know, you’re attending, you’re copying.
0:15:46 Yes.
0:15:47 I got the whole acronym.
0:15:50 I got all eight stages right.
0:15:51 Okay.
0:15:54 So you attend, you copy, you do all that.
0:16:01 But then after you do all that, then do you suggest ways to study for the next quiz or you
0:16:03 just lay off that completely?
0:16:04 It depends.
0:16:06 It’s the most frustrating answer in the world.
0:16:08 It depends for several reasons.
0:16:16 The first of which is that if you do this well, you will be surprised by the other person’s
0:16:20 ability, oftentimes, to come up with solutions themselves.
0:16:21 All right.
0:16:25 So you’re all ready with your arsenal of things that you think they should do.
0:16:31 But just in feeling accepted or understood, as they start to talk it out, they often, not
0:16:33 always, but there are times when they get there themselves.
0:16:39 If not, then I have to decide, is this the right moment?
0:16:42 So we’re really eager to get that problem solving in there.
0:16:49 But sometimes, in the example with the spelling test, it’s fine to just let that sit.
0:16:53 I can circle back the next day and talk about study strategies.
0:16:55 I don’t need to do it right then.
0:16:59 So it’s just, I know I need to get there.
0:17:04 It’s about being intentional and focusing on being effective rather than just getting it
0:17:05 out there.
0:17:08 There’s no point in getting out your great ideas if they’re not going to be received.
0:17:10 It’s just, it doesn’t matter.
0:17:14 Did you just put every tutor out of business?
0:17:18 No, because tutors are hired for problem solving, right?
0:17:20 That’s what they’re asked to do.
0:17:21 It’s very clear.
0:17:26 But when someone comes to you for support, they’re not necessarily asking for you to solve
0:17:29 whatever it is they’re dealing with.
0:17:33 They might just want to hear, yeah, it’s really hard raising teenagers, right?
0:17:36 Not, you need to validate your kids more if you want them to, right?
0:17:44 If you were a high school tutor and you started off with validation, you would become a better
0:17:46 tutor in general, wouldn’t you?
0:17:47 I think so, yeah, I do.
0:17:54 I think, this is a weird language perhaps to use in the context of tutoring, but validation
0:17:56 is really at the core of relationships.
0:18:02 It is what it means to feel loved in a sense, right?
0:18:03 Because it communicates acceptance.
0:18:08 And if we don’t feel accepted, it’s hard to feel loved.
0:18:14 And I think that’s a really, really critical point that we confuse or lose in the shuffle.
0:18:18 That acceptance is critical in that sense.
0:18:23 As soon as this recording ends, I’m going to start validating Madison.
0:18:25 I’m going to practice on Madison.
0:18:26 So I get good at validating.
0:18:29 Then I’m going to go to my kids and my family.
0:18:31 Oh, just do it all.
0:18:32 Do it all at once.
0:18:33 Don’t hold back.
0:18:34 Don’t hold back at all.
0:18:54 So have you noticed a difference in validation skills by gender?
0:18:54 Wow.
0:18:56 What a great question.
0:19:02 So in my book, I talk, there’s, you know, about eight different validation skills that
0:19:03 we as therapists are trained in.
0:19:04 We learn these skills.
0:19:09 We have to master them so that we can go out and validate our clients and
0:19:14 establish a therapeutic alliance and trust and everything else.
0:19:18 Of these eight skills, one of them is called taking action.
0:19:22 And it’s weird because it sounds a little bit like problem solving in that it has you
0:19:25 intervene, go in there and do something, right?
0:19:29 If somebody got a flat tire and they call you and they say, I’m on the side of the road.
0:19:33 And you say, oh my gosh, you must be so upset and worried, right?
0:19:34 They can validate all day long.
0:19:39 But if they don’t take action and come and get you, you’re not going to feel like they really
0:19:40 appreciate the situation.
0:19:46 And my hypothesis, I don’t know if I ever formulated it in this way, but I always assumed
0:19:51 that men would be more receptive to taking action.
0:19:56 In other words, that they would be seeking taking action more from their partners, perhaps,
0:20:00 as opposed to like emotional or verbal types of validation.
0:20:03 And that has not proven to be true.
0:20:09 On the contrary, I’ve just, and this is just, again, anecdotal from my clinical work.
0:20:10 I’ve observed.
0:20:16 Wait, you said anecdotes is not a substitute for scientific.
0:20:18 It’s true.
0:20:21 And if we had data on it, I would refer to that data.
0:20:24 In the absence of it, I will just give my anecdotes.
0:20:27 And that did surprise me.
0:20:33 And so in my work with couples, it’s often about helping them figure out what it is they’re
0:20:39 actually seeking, what actually helps them feel seen and heard, because it’s not often what
0:20:40 the other person would expect.
0:20:46 And have you also noticed differences for validation by culture?
0:20:50 Are there different cultures that validate more or validate less?
0:20:54 There’s huge differences in the extent to which we validate emotions.
0:20:59 And even within American culture, there’s been somewhat of a revolution, right?
0:21:04 We didn’t talk about emotions forever, much less validate them, or make an effort to really
0:21:06 go out of our way to validate them.
0:21:09 So I think there are differences.
0:21:16 The most meaningful thing, however, is within your culture, is if you are receiving
0:21:23 more or less validation than is typical of, say, a child in that culture, if that makes sense.
0:21:30 In the same way that we see punishment, different types of punishment may be perceived as more
0:21:37 damaging, more abusive to a child who is being raised outside of a culture or raised in a country
0:21:41 where the cultural practices do not apply in the same way.
0:21:45 And so they feel more targeted, if that makes sense.
0:21:46 Yes, it does.
0:21:49 Okay, so the last variable is age.
0:21:54 As you get older, do you get more able to validate people?
0:21:56 Oh, do you get better at it?
0:21:57 That’s interesting.
0:22:00 I thought you were going to ask, do different ages require different types of validation?
0:22:02 Well, that’s a good question too, yeah.
0:22:04 Just to validate your question.
0:22:11 That one, I think you know the answer to, because you have four kids.
0:22:13 Depends how you define adolescence.
0:22:15 Out of adolescence or in adolescence?
0:22:18 Depends how you define adolescence.
0:22:19 Adolescence, that’s right.
0:22:27 Well, I’m sure you notice that when your kids are younger, they just want all sorts of, I see how hard you tried.
0:22:30 All of that type of like warm, fuzzy, right?
0:22:32 You really worked hard on that.
0:22:39 If you try that with a 15-year-old, right, they are going to just squirm inside.
0:22:41 They are not feeling validated.
0:22:43 They are feeling annoyed.
0:22:51 And so as they get older, they need much less in the form of that like, I see you type of stuff.
0:22:53 Because they don’t really want to be seen.
0:22:55 They want to be respected, right?
0:23:05 And so validating their thoughts or their rationale goes a lot further than going in with the like, I see your effort there.
0:23:06 I see what you did.
0:23:11 And then they kind of move back out of that into adulthood a little bit and become more balanced.
0:23:15 Do we get better at validation as we get older?
0:23:17 It really depends.
0:23:19 It depends on what is modeled for you.
0:23:30 And I say this because we know, as I said, with folks who are exposed to chronic invalidation and then have different disorders where they end up in treatment,
0:23:39 one of my jobs as a psychologist is to teach them how to validate themselves and others because it was not modeled for them.
0:23:44 And validation is very much like a language.
0:23:51 It is a language we should be teaching kids at a young age because they pick it up so fast.
0:23:59 It is fascinating to me trying to teach a 10-year-old versus a 20-year-old how to validate themselves or another person.
0:24:02 The 10-year-old picks it up.
0:24:05 The 20-year-old, it takes two, three times as long.
0:24:09 They don’t develop that language capacity in the same way.
0:24:12 Your practice is in Silicon Valley.
0:24:17 And we can edit this answer out.
0:24:27 But do you look at these, what has been labeled the nerd Reich, do you look at these nerd Rikers, these tech bro billionaires?
0:24:30 They are the richest people in the world.
0:24:31 They have everything.
0:24:32 They have wealth.
0:24:33 They have power.
0:24:34 They have visibility.
0:24:35 They have everything.
0:24:44 And yet they seem to be primarily concerned with long-term capital gains rates and, you know, making crypto successful.
0:24:50 Why aren’t they taking the high road and helping society instead of just trying to make more money?
0:24:57 Do you think it’s because they weren’t validated when they’re young or, you know, am I just trying to criticize these shitbags?
0:25:02 Yeah, yeah, yeah, and there are so many shitbags, let’s just be clear, in Silicon Valley.
0:25:06 I think, again, we search for validation in different ways.
0:25:13 And I think that money is a sense that we are valued and that we are valuable.
0:25:20 And once you’ve had that hit, right, that little dopamine hit of, ooh, I’m valuable.
0:25:21 People see my worth.
0:25:23 You continue to seek it out in those ways.
0:25:30 But as you will see, it’s an insatiable thirst because you’re not actually giving yourself water.
0:25:32 It’s like coffee, right?
0:25:33 It dehydrates you more.
0:25:42 And so they’re actually seeking validation, acceptance through the wrong sources.
0:25:48 And therefore, they consume more and try and get more and more because it just keeps dehydrating them.
0:25:55 So is there a fine line between too much and too little seeking external validation?
0:25:59 I mean, I would think it’s healthy to seek external validation.
0:26:02 It’s kind of reinforcing its feedback.
0:26:08 On the other hand, I would say that maybe our current president is just obsessed with external validation.
0:26:12 So where’s the fine line between too much and too little?
0:26:15 How can you tell if you’re trying to get it too much?
0:26:16 Good question.
0:26:19 We talked about the difference between validation and agreeing, right?
0:26:21 I said it’s not the same as agreeing.
0:26:24 It’s also not the same as praise.
0:26:27 Praise is a positive judgment.
0:26:29 It’s positive, but it’s a judgment nonetheless.
0:26:31 It says, good job.
0:26:32 You’re great.
0:26:35 It’s a heart emoji on Instagram, right?
0:26:38 And it reinforces facades.
0:26:45 It reinforces us for exceeding expectations and tweaking ourselves and filtering ourselves, right?
0:26:49 To be seen as better than, to get that positive.
0:26:51 Validation is about acceptance.
0:26:56 It says, I accept you independent of how you look or perform.
0:27:03 So when people say we shouldn’t rely too much on external validation, they’re really talking about praise.
0:27:05 Praise can be good, right?
0:27:08 You need that feedback as you were describing in some ways.
0:27:12 But if you build your life around it, it’s hollow, right?
0:27:17 Because you will have to distort yourself to continue to get it, right?
0:27:21 You have to just keep putting yourself out there and pushing and pushing and pushing.
0:27:24 There is no sense that you’re accepted just as you are.
0:27:34 So radically, I would say, no, there is no amount of external acceptance that is too much.
0:27:37 That has not been my observation.
0:27:45 The more accepted we feel, the greater the sense of belonging, the more we flourish.
0:27:52 That has been consistently my observation, and it is what the evidence supports.
0:27:54 Again, I can’t say that for praise.
0:27:58 If you go around chasing praise your whole life, it’s going to get Trumpy and very quickly.
0:27:59 Okay.
0:28:00 Yeah.
0:28:08 Now, what happens if validation doesn’t necessarily address the underlying causes of issues?
0:28:14 Are you saying that validation puts you on the path to address the underlying causes?
0:28:15 That is right.
0:28:16 That is right.
0:28:22 So in my line of work, I work with folks who have severe behavioral issues, folks who
0:28:25 are suicidal, folks who are hurting other people.
0:28:30 I need to change that quickly, right?
0:28:33 It’s not like, oh, I just hope I go in there and I accept them and everything.
0:28:36 Like, I need to make sure that that behavior changes.
0:28:39 And so acceptance is a piece.
0:28:40 It is a piece of that puzzle.
0:28:42 It puts me on the right track.
0:28:49 It opens the door for collaboration and feedback so that when I do give advice or skills training
0:28:53 or whatever it may be, the other person listens to me.
0:28:57 That is, at least in a therapeutic sense, that’s kind of the name of the game.
0:29:05 But is there no role for friction and conflict and struggle and, you know, shame and healthy
0:29:05 development?
0:29:11 To put it in parental term, what if you’re a helicopter parent or a lawnmower parent?
0:29:12 I’m a lawnmower parent.
0:29:13 Are we defeating ourselves?
0:29:14 How so?
0:29:21 Well, I mean, if we are helicopter parents or lawnmower parents and we always are in problem
0:29:22 solving mode.
0:29:25 how does a person become their own problem solver?
0:29:27 How do you become your own problem solver?
0:29:28 No.
0:29:33 How does my kids or, you know, people who work for me solve their own problems?
0:29:34 Yeah.
0:29:36 You need to back off of the problem solving.
0:29:40 That’s 100%.
0:29:40 It’s problematic.
0:29:42 Absolutely.
0:29:43 I would subscribe to that.
0:29:47 Now, the question is, the question, do you need feedback on that in order to get there?
0:29:53 I think your whole book was feedback, to tell you the truth.
0:30:00 I bet a lot of people listening to this podcast can relate to this concept of helicopter or lawnmower
0:30:01 parenting, right?
0:30:05 So, like, where’s the line?
0:30:05 Yeah.
0:30:09 I think, again, the emphasis is on effectiveness.
0:30:14 You had someone on your podcast recently that was talking about neurologically what happens
0:30:18 in a young person’s brain when they hear nagging.
0:30:24 And the short of it was that the parts of their brain that would actually be needed to take in that
0:30:28 feedback and do something with it shut down.
0:30:31 And just hearing that nagging, they shut down.
0:30:37 And that’s the point with the helicoptering is that at some point, your background noise, right?
0:30:39 You’re always in their face telling them what to do.
0:30:45 And they listen to you less over time, and they don’t develop the capacity to do it themselves.
0:30:46 So those are the costs.
0:30:48 We have to call them what they are.
0:30:52 Now, there are valid reasons you’re helicoptering.
0:30:54 And it’s important to see that as well.
0:31:00 You’re trying to keep your kids safe in a world that has become incredibly dangerous psychologically.
0:31:06 I think as parents, the world feels dangerous for our kids with social media and the internet
0:31:07 and all of these things.
0:31:10 The question is, what’s going to be most effective?
0:31:14 And the answer is that helicoptering is not it.
0:31:15 Okay.
0:31:17 Helicoptering is not it, but what is it?
0:31:20 How would you define helicoptering?
0:31:21 Let’s break it down.
0:31:28 I would define helicoptering as always hovering over your kid and making sure that it’s like
0:31:32 the golden dome of parenting that no missiles get through.
0:31:34 Okay.
0:31:38 Does it include lecturing, in your opinion?
0:31:39 Lecturing the kids?
0:31:40 Or is that separate?
0:31:49 I would say it unavoidable because every time you fire an anti-missile missile, it’s a lecture.
0:31:49 Okay.
0:31:51 Again, I will reiterate.
0:31:53 It’s valid that you want to protect them.
0:31:55 But is helicoptering protecting them?
0:31:58 No, because they’re not developing the skills they need to do it themselves.
0:32:03 So what you need to do is be able to step back and let them fall.
0:32:09 You have to trust in the wisdom that growth happens through, quote unquote, failure.
0:32:14 That when you try and protect your kids from failure, you’re ultimately protecting them
0:32:14 from growth.
0:32:22 Once you accept that, that is the mantra you have to return to again and again to come out
0:32:23 of that helicoptering mode.
0:32:26 Now, does that mean no oversight whatsoever?
0:32:27 No, of course not.
0:32:31 But it means challenging yourself because when we get into a mode like helicoptering, it’s become
0:32:32 default.
0:32:34 We’re not thinking, is this effective?
0:32:35 It’s just what we do.
0:32:36 They ask, can I go out?
0:32:37 No, no, no.
0:32:40 Not unless so-and-so goes with you and like all these other things.
0:32:41 Just stop.
0:32:43 Is this a moment where I could loosen up?
0:32:45 What’s the worst that could happen here?
0:32:54 Okay, now that we solved all the parenting issues, let’s move on to self-validation.
0:32:56 How does one self-validate?
0:32:58 Yeah, such a great question.
0:33:00 We don’t learn this, do we?
0:33:04 This is something that really, really strikes me.
0:33:09 Working with folks as an executive coach, you’ve got these, like you said, tech billionaires,
0:33:10 right?
0:33:12 To folks struggling with severe psychopathology.
0:33:17 And what I see across the spectrum, honestly, I have yet to have someone come into my office
0:33:24 who was really good at validating their own emotions, be it tech billionaire or person struggling
0:33:26 with bipolar disorder, right?
0:33:35 What we do instead is we tend to criticize ourselves and lash ourselves into doing better.
0:33:42 And this is incredibly problematic because we don’t trust our emotions.
0:33:55 We see shame or sadness as indications of failure, again, failure, rather than opportunities for compassion.
0:33:58 The belief that we should treat others the way we would want to be treated.
0:34:02 And I think actually the reverse is true.
0:34:07 We should treat ourselves the way we would treat somebody else who was struggling.
0:34:10 Wow, that’s interesting.
0:34:10 Right, though?
0:34:15 Because if someone was to come to you feeling deeply ashamed, you wouldn’t, like, twist the
0:34:20 knife and say a bunch of other things that they did that proved how worthless they were, right?
0:34:22 But that’s often what we do to ourselves.
0:34:28 We go through our history and collect all the supporting evidence as to why we suck and we’re
0:34:29 never going to X, Y, or Z.
0:34:31 But you would never do that to a friend.
0:34:33 That would seem cruel.
0:34:39 So one of the reasons, back to children, one of the reasons I am so adamant about validating
0:34:45 children is because I want them to develop the capacity to validate themselves.
0:34:51 That doesn’t mean that everything they think or do is correct, but it means that they should
0:34:53 be able to see the validity in what they’re feeling.
0:34:57 So I’ll often say it’s not okay to yell or scream or whatever.
0:34:58 It’s okay to be upset.
0:35:00 It’s okay to be angry.
0:35:01 It’s okay to be frustrated.
0:35:03 All right.
0:35:05 The behavioral expression is different from the emotion.
0:35:10 So being able to validate your own emotions, being able to see, why does it make sense
0:35:11 that I feel this way?
0:35:14 Up next on Remarkable People.
0:35:16 There’s some of this in what you do as well.
0:35:23 You’re trying to help the guest message, get that message across as effectively as possible.
0:35:26 And it’s reflected in how you listen and the questions you ask.
0:35:28 And that’s what we’re going for here.
0:35:31 It’s not about like, haha, I’m so much smarter than them.
0:35:34 These idiots, let me come in and do this better than they’re doing it.
0:35:39 No, it’s more just, you would ask questions differently if you were trying to flesh out
0:35:41 your understanding or their point.
0:35:51 Do you want to be more remarkable?
0:35:57 One way to do it is to spend three days with the boldest builders in business.
0:36:02 I’m Jeff Berman, host of Masters of Scale, inviting you to join us at this year’s Masters
0:36:05 of Scale Summit, October 7th to 9th in San Francisco.
0:36:12 You’ll hear from visionaries like Chobani’s Hamdi Ulukaya, celebrity chef David Chang, Patagonia’s
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0:36:24 That’s mastersofscale.com slash remarkable.
0:36:27 And Guy Kawasaki will be there too.
0:36:32 Become a little more remarkable with each episode of Remarkable People.
0:36:37 It’s found on Apple Podcasts or wherever you listen to your favorite shows.
0:36:42 Welcome back to Remarkable People with Guy Kawasaki.
0:36:47 Let us get to the validation ladder.
0:36:53 I would like you to explain the validation ladder so that people have a sort of a framework to
0:36:55 understand your work.
0:36:56 So please explain the ladder.
0:36:57 Yeah.
0:37:00 So this is a collection of skills.
0:37:04 We’ve got eight different skills that you can use to validate someone.
0:37:07 These are basically just little communication tactics.
0:37:11 If you use this skill, it will convey some degree of validation.
0:37:15 And to understand this, it helps to break down validation.
0:37:21 I said it really quick at the beginning, but the key components are mindfulness, understanding,
0:37:22 and empathy.
0:37:23 All right.
0:37:28 You’re trying to convey those qualities in such a way that the person feels accepted.
0:37:30 And you’re like, how do you do that?
0:37:31 How do you do it in such a way that they feel?
0:37:33 This is how with these skills.
0:37:39 So the first set are just what we call mindfulness skills.
0:37:42 They’re just helping you project that mindful awareness.
0:37:43 All right.
0:37:56 If I am sitting across from, let’s say, Donald Trump, and he is, let’s just say, and he is, I’m just trying to picture myself debating this guy.
0:37:56 It would just be so.
0:37:58 I would honestly love it.
0:38:02 I feel like it would be the ultimate test of my validation skills here.
0:38:07 But he’s going to be saying, inevitably, a lot of stuff that I do not understand.
0:38:10 Not just don’t agree with, but logically do not understand.
0:38:14 And when that is the case, all I can do is be mindful.
0:38:15 Okay.
0:38:18 All I can do is attend or copy.
0:38:23 These are the two skills we have to be mindful and to show that we’re mindful.
0:38:26 And that’s a pretty low level of validation, you might think, right?
0:38:27 It’s just awareness.
0:38:29 But a couple of things there.
0:38:33 One, awareness is incredibly powerful.
0:38:38 Attention is one of the most reinforcing experiences that we can provide.
0:38:49 If we want to torture somebody in this country, the method we use is to deprive them of attention by putting them in solitary confinement, right?
0:38:56 When we remove attention, people struggle, and they struggle deeply, all right?
0:39:00 But now, like, negative attention doesn’t necessarily feel good, right?
0:39:04 The task is just to be just non-judgmentally aware.
0:39:08 And that’s what these two skills help us do, attending and copying.
0:39:15 I got the basics of attending about it’s contact, it’s proximity, it’s gesturing, and it’s nodding.
0:39:19 So I love all those things.
0:39:23 But what do you do in a virtual world where it’s Zoom?
0:39:26 This is such a great question.
0:39:36 Again, as a psychologist, someone who’s working with emotion and people every day, the pandemic was such an immediate and visceral.
0:39:39 It created this visceral sense of disconnection.
0:39:43 And I think we all experienced it over time.
0:39:46 As a psychologist, I got to tell you, it hit me right away.
0:39:50 Because these tools that I rely on to connect were taken away.
0:39:57 And if you’re Zooming or whatever the case may be, you have to just be more intentional about those cues.
0:40:04 For instance, I will make a point of leaning in and make it clear that I’m leaning in.
0:40:13 I will adjust my monitor so that my eyes are as close to the camera as possible, so that it’s as close to eye contact as possible.
0:40:17 You can see it in this interview, in the recording.
0:40:18 I do a lot of gesturing.
0:40:22 And I’m making a point of doing it up here, right?
0:40:25 I’m showing that I am engaged through those nonverbals.
0:40:27 But you have to be more intentional about them.
0:40:28 That’s the key.
0:40:31 The worst is to do the camera off.
0:40:33 You’re just listening or something and people can’t see.
0:40:34 That is like the absolute worst.
0:40:37 And yet, that is where many of us reside.
0:40:41 So with the nonverbals over virtual, you just have to be more intentional about it.
0:40:42 That’s all you can do.
0:40:51 You made a point, and I cannot remember which one of the eight skills it was affiliated with.
0:41:02 But I love this point, which is that you should find a way to help the other person make their point.
0:41:02 Oh, yeah.
0:41:06 So first of all, refresh my senile mind.
0:41:13 What is this concept of helping people be a better communicator by suggesting things?
0:41:15 What is that associated with?
0:41:17 So there’s two things at play there.
0:41:18 One of them is attending, okay?
0:41:20 So that’s that we were talking about.
0:41:21 You can use these nonverbals.
0:41:25 And then the other way to attend is in how you listen.
0:41:33 And it’s a little game that you play with yourself where you’re thinking as you’re listening, what’s this person’s point?
0:41:35 And like, why does it matter to them?
0:41:37 You’re streaming information, trying to figure that out.
0:41:43 And then, and this is critical, how could I do a better job of making this person’s point?
0:41:46 Again, not do I agree with it?
0:41:48 Not how could I defeat it or argue it?
0:41:49 What’s my rebuttal?
0:41:49 No.
0:41:53 It’s how could I articulate this better than they’re doing right now?
0:41:59 But isn’t that going to create hostility?
0:42:03 Who the hell is this person to tell me, you know, how to do this better?
0:42:04 Sure, sure.
0:42:05 At this point, you don’t tell them.
0:42:08 This just informs how you are listening.
0:42:16 And if you watch great late night show hosts, you will see that they are all playing some version of this game.
0:42:19 They are trying to get the best interview they can.
0:42:23 As a podcast host, I imagine you, there’s some of this in what you do as well.
0:42:30 You’re trying to help the guest message, get that message across as effectively as possible.
0:42:33 And it’s reflected in how you listen and the questions you ask.
0:42:35 And that’s what we’re going for here.
0:42:38 It’s not about like, haha, I’m so much smarter than them, these idiots.
0:42:41 Let me come in and do this better than they’re doing it.
0:42:47 No, it’s more just you would ask questions differently if you were trying to flesh out your understanding or their point.
0:42:54 I have to admit that I slightly misinterpreted this thought.
0:42:57 And then I said, okay, so this is a great thought.
0:43:03 What can I constructively offer Caroline about her book?
0:43:06 So I came up with some ideas.
0:43:09 But now that you tell me that, maybe I should just keep them to myself.
0:43:11 Oh, no, no, I want to hear them.
0:43:14 Okay.
0:43:19 Okay, so take this in a spirit of one author to another.
0:43:20 Oh, please.
0:43:23 Some slight changes that I would do.
0:43:24 Yeah.
0:43:25 Okay.
0:43:27 Positively.
0:43:29 I want to validate your great book.
0:43:29 I love you.
0:43:32 You wouldn’t be on this podcast if I didn’t like what you did.
0:43:37 So I have one idea.
0:43:40 In the back of your book, you have this appendix.
0:43:43 And this appendix lists like, you know, these are the eight skills.
0:43:44 This is a summation.
0:43:46 This is an example, right?
0:43:47 There’s a one-page appendix.
0:43:53 I think you should move that up into the first time you discuss the latter.
0:43:59 Because when I read about your latter, I have to admit, I had some mental fog.
0:44:04 I had to go back several times because it was like, she just said there’s eight things.
0:44:07 But then she’s talking about three things, mindfulness.
0:44:08 Yeah, yeah, yeah, yeah, yeah, yeah.
0:44:11 So I said, so is it the three or is it the eight?
0:44:12 The eight, right.
0:44:18 And it took me quite a while to figure out the three contain the eight.
0:44:23 The eight is divided into three sections of mindfulness, understanding, and empathy.
0:44:27 And those eight things add up to those three things.
0:44:28 So that took me a while to figure it out.
0:44:33 But your appendix, when I saw that appendix, I said, aha, now I get it.
0:44:39 This is such frustrating feedback because between you and me, this was such a fight.
0:44:41 Like, I agree.
0:44:44 I wanted that earlier in the book.
0:44:48 And the concern was that it would be too much content too soon.
0:44:51 I have to invalidate your editor or publisher.
0:44:53 They’re wrong about that.
0:44:55 Right, because you need to see it all.
0:45:00 Yeah, I mean, you need to understand the big picture that, you know, these three subsections
0:45:03 are made out of eight skills, add up to the latter.
0:45:05 I have one more comment.
0:45:11 I got to tell you, when I read this, I thought, this is the most interesting story.
0:45:13 This cannot possibly be true.
0:45:17 So I went to chat, GPT, and I asked this question.
0:45:19 And of course, it is true.
0:45:24 You say in your book that there’s a golden rule.
0:45:32 And the golden rule is that in a court case, a lawyer cannot suggest to the jury, put yourself
0:45:33 in this person’s place.
0:45:35 Isn’t that how you would react?
0:45:38 You cannot appeal to empathy.
0:45:40 It is illegal to do that.
0:45:41 And I read that.
0:45:43 I said, that cannot be true.
0:45:44 And it is true.
0:45:44 It’s true.
0:45:47 It is really, really true.
0:45:48 I had no idea.
0:45:49 So can you explain that?
0:45:51 Because that was shocking to me.
0:45:51 Yeah.
0:45:55 So this is getting at some of those understanding skills.
0:45:59 Like, how do you understand and connect with someone else’s experience?
0:46:02 And one of the things we’re always told is to put yourself in the other person’s shoes.
0:46:06 But really, that is quite effective.
0:46:11 It is a skill to be able to say, how would this feel to me?
0:46:14 Like, in that same way that we were talking about, do they need acceptance or problem solving?
0:46:15 Put yourself in the kid’s shoes.
0:46:18 What do they want to hear after getting a bad grade?
0:46:19 Do they want to hear how to study better?
0:46:23 Or do they want to hear, that sucks, right?
0:46:25 How awful, X, Y, or Z.
0:46:32 So when you do that, it immediately changes your perception of the experience.
0:46:38 And interestingly, it’s so effective in doing so that, yeah, you’re not allowed to do that
0:46:42 as a lawyer in appealing to the court.
0:46:48 You can’t ask jurors to think from that angle because it could make them empathize.
0:46:52 And that could influence their decision, right?
0:46:56 Isn’t the whole point to be tried by a jury of your peers?
0:46:58 I know, right, right?
0:47:05 But there seems to be this concern about objectivity being tainted by emotion.
0:47:08 I don’t know if I agree with that per se.
0:47:14 I think that’s part of the reasoning is the emotional logic that goes into it.
0:47:20 I see them as very equally important in making smart judgments and wisdom.
0:47:26 If you were a prosecuting attorney and you said, put yourself in the place, there’s three cops
0:47:27 holding you down.
0:47:29 One has his knee on your neck and you’re choking.
0:47:31 Put yourself in that place.
0:47:31 Yeah.
0:47:38 Or how about if you are an immigrant and you’ve been here 40 years, you’ve raised kids, three
0:47:39 of them are Marines.
0:47:42 And now you get arrested in Home Depot for what?
0:47:43 For what?
0:47:45 I mean, you pay your taxes.
0:47:46 You do everything, right?
0:47:46 Yeah.
0:47:51 Again, another really visceral, I don’t know why I keep coming back to kids on this podcast.
0:47:57 I’m not usually this kid focused, but I think of often tell parents, like, especially a big
0:48:05 guy, you’re 200 pounds yelling at somebody who is three feet tall.
0:48:08 Think about how that would feel.
0:48:13 Do that kind of perception shift and let that inform your reaction.
0:48:18 Because you may not feel like you’re being scary, but that’s terrifying.
0:48:24 We are at the one hour mark.
0:48:26 Oh, I can’t believe it.
0:48:32 Maybe I should change this podcast to the Remarkable Parenting Podcast.
0:48:32 I know.
0:48:35 I don’t know why I went so far in that direction.
0:48:37 No, I took you in that direction.
0:48:39 I wanted to go in that direction.
0:48:41 What else is more important than parenting?
0:48:41 I know.
0:48:42 Yes.
0:48:44 I’ve come to believe that more and more.
0:48:47 I have so much more faith in our children than in us.
0:48:49 I hate to say it.
0:48:52 Maybe I should interview Havana.
0:48:55 Havana, listen, your mom says she validates you all the time.
0:48:56 Is that true?
0:48:59 Does she problem solve for you, Havana?
0:49:01 Or does she let you figure everything out?
0:49:02 You know what Havana says?
0:49:05 She says, I know you’re validating me.
0:49:08 And it feels good, but I know what you’re doing.
0:49:12 She’ll say, it feels good, but I know what you’re doing.
0:49:21 She’s going to read this book someday and say, my God, Ma, couldn’t you have used the pseudonym or something?
0:49:22 Yes, exactly.
0:49:26 Okay, so I have one last question, and it’s about Havana.
0:49:28 Why Havana?
0:49:30 There must be a story.
0:49:36 You know, you didn’t call her Houston or Dallas or Mar-a-Lago or Los Angeles or Portland.
0:49:37 Why Havana?
0:49:39 Are you a socialist?
0:49:43 My mother fled communist Cuba, and she grew up in Havana.
0:49:52 And her middle name is after her grandmother on my husband’s side, and then her first name is after, not after my mom, but speaks to her experience, yeah.
0:49:55 You don’t meet many kids in Havana.
0:49:57 I know, and we’ve found one.
0:50:00 We have found one, and it’s like through Instagram or something.
0:50:04 And I feel just like such a kinship to this young child that I’ve never met.
0:50:08 All righty.
0:50:09 All righty, Caroline Fleck.
0:50:13 As you can tell, I really learned a lot from your book.
0:50:17 Now, we only did attending, really, and copying.
0:50:17 Yes.
0:50:19 And there are six more skills.
0:50:26 I really recommend this book, and I hate to tell you, Caroline, but I recommend that you start with the appendix.
0:50:30 If you start with the appendix, you will really understand.
0:50:31 Yeah.
0:50:32 I agree.
0:50:33 I support that.
0:50:36 So, read this book backwards.
0:50:39 Basically, what we’ve said is the appendix is good and the epilogue is great.
0:50:42 So, just start at the end and go backwards.
0:50:51 I’m all about the recency is more important than primacy or whatever the opposite is.
0:50:51 That is right.
0:50:52 That is right.
0:50:55 All right, Caroline Fleck.
0:51:05 Thank you so much for being on this podcast, and I think people listening to this and reading your book will have a very good tool to be remarkable.
0:51:08 So, thank you for coming on my podcast.
0:51:10 Thank you so much for having me.
0:51:11 This was an absolute blast.
0:51:15 I bet you say that and validate all the podcasters.
0:51:16 No, no.
0:51:18 Just you.
0:51:20 Yeah, I believe you.
0:51:25 Because, you know, I need validation so much.
0:51:27 We all do.
0:51:29 All righty.
0:51:38 So, now I want to validate the rest of the Remarkable People podcast staff, which is Madison Nisner, this ace producer and co-author.
0:51:43 Tessa Nisner, who are a researcher and co-producer, JFC.
0:51:46 And finally, sound designer, Shannon Hernandez.
0:51:49 That’s the Remarkable People team.
0:51:54 So, until next time, be remarkable and go out and validate somebody.
0:51:59 Actually, start by validating yourself and then go out and validate people.
0:52:04 This is Remarkable People.