0:00:05 Hi and welcome to the A16Z podcast. I’m Hannah and in this episode we talk all about the remarkable
0:00:12 story of one American family, the Galvans, Mimi, Don, their 10 sons, and two girls,
0:00:18 out of whom six sons were afflicted with schizophrenia, following them from the 1950s to today.
0:00:22 Robert Kolker, author of the book and previous author of “Lost Girls,” writes,
0:00:29 “They lived through the eras of institutionalization and shock therapy, the debates between psychotherapy
0:00:34 versus medication, the needle in a haystack, search for genetic markers for the disease,
0:00:38 and the profound disagreements about the cause and origin of the illness itself.”
0:00:44 And because of that, this story is really more than just a portrait of one family. It’s a portrait
0:00:49 of how we have struggled to understand this mental illness, the biology of it, the drivers,
0:00:54 the behaviors and pathology, the genomics of it, and of course the search for treatments that might
0:01:00 help. Also joining Robert Kolker and myself for this conversation is Stefan McDonough, Executive
0:01:05 Director of Genetics at Pfizer World R&D, who is one of the genetic researchers who worked closely
0:01:11 with the Galvans. We start by talking about our attempts to understand and treat schizophrenia
0:01:17 from Freud to lobotomies to the entrance of Thorzine onto the scene, where that understanding
0:01:22 of the disease finally began to shift, especially with new technologies and the advent of the human
0:01:28 genome project, and where we are today in our understanding of the disease, how to treat it,
0:01:33 and where our next big break might come from. What really struck me about this book was that
0:01:41 it was this huge story, not just about one family and this particular disease of schizophrenia,
0:01:46 but also kind of a portrait of our entire effort to understand mental illness period,
0:01:53 and not just how we understand it, but how we experience it and how we try to treat it.
0:01:59 Let’s go back a little bit and talk about schizophrenia itself. I’d love to hear where
0:02:05 you think our modern understanding of the disease really began. You describe a key moment in 1903
0:02:11 where we shift from thinking of it as a religious ailment into something else, or where would
0:02:16 you begin that story? That’s around the time of the dawn of psychiatry as we understand it today.
0:02:21 Obviously, there are glimmers beforehand of people believing that mental illness is physical and
0:02:27 not spiritual or religious, but by the turn of the century, there was an entire field emerging,
0:02:31 and there was a nature-nurture debate over what schizophrenia was that really,
0:02:37 in many ways, continues today in a different form. Back then, the debate was between Freud,
0:02:43 who believed that therapy could cure schizophrenia, that schizophrenia was something that happened in
0:02:48 the nurture side of things, something that happened in your childhood caused it, perhaps bad parenting.
0:02:54 On the other side were a lot of other psychiatrists, including the ones who named schizophrenia,
0:02:59 who believed it had some sort of physical property, but could never put their finger
0:03:05 on what it was. Into this debate come the Galvans, who by the 1950s and ’60s are starting to become
0:03:10 mentally ill at a time where most psychotherapy believes it’s the parent’s fault, and medical
0:03:16 psychiatry is sure that drugs can hit whatever is happening genetically, but they really have no
0:03:21 clue how those drugs work or what genes are really at play, and this continues for decades.
0:03:27 The story of the family starts in the 1950s, but you describe some developments before you
0:03:34 get to this with Dr. Frome Reichman and Gregory Bateson and a couple of other characters that,
0:03:39 to me, felt like kind of key points as our understanding of the disease was developing.
0:03:45 In 1948, Frita Frome Reichman, who was a psychoanalyst then living in America, came up with a term
0:03:51 called the Schizophrenogenic Mother, which she believed was a certain type of mother or father,
0:03:58 in some cases, who was so bad at parenting, was so torturous in the way that they dealt with their
0:04:04 children that the child then would somehow create their own imaginary reality in order to escape from
0:04:11 that parent and become schizophrenic. That was the split. The split was from internal to external.
0:04:15 Exactly. Sometimes people think schizophrenia means split personality,
0:04:20 but it really never did, and it’s really a split between your perceptions of reality and of what’s
0:04:26 happening inside you. Frita Frome Reichman was doing this at a time where lots of psychoanalysts
0:04:32 were blaming mom and dad for lots of things. Of course, by 1960, you have the movie Psycho,
0:04:36 the greatest homicidal maniac in all of cinema. His problem is his mother, and everybody says,
0:04:42 “Oh, yes, that must be what happened.” It seems strange now, but when you think about it back then,
0:04:48 people like Frita Frome Reichman and Gregory Bates, they were doing battle against eugenics
0:04:52 at the time of modern feeling that you could breed out schizophrenia and that you should
0:04:59 sterilize or even euthanize mentally ill people. They were also doing battle with people who were
0:05:04 committing lobotomies and insulin shock therapy and electroshock therapy. They were doing battle
0:05:09 with a medical field that was treating schizophrenic people as subhuman. They felt like they were on
0:05:15 the side of the angels. It was really interesting to me that the kind of duality from Reichman,
0:05:21 her position, on the one hand, having more compassion than anyone had ever really had before
0:05:25 for the people suffering from this disease, but on the other hand, having so little compassion.
0:05:29 For the mothers, it was just a very interesting split there.
0:05:35 Yes, indeed. I think she and a lot of other therapists of her generation were threatened
0:05:40 by changes in society. Women are working after the war. The family unit is being threatened
0:05:46 in some way. The sexual revolution is about to happen. Any major changes in society then began
0:05:51 to be attached to the idea of mental illness until the researchers who went after the Galvin
0:05:57 family who came up in the late ’60s and early ’70s at a time when a lot of established psychiatry
0:06:02 was telling them still that parents were the problem and that working mothers in particular
0:06:07 were the problem. One of the things that really struck me, Bob, was you start in a really interesting
0:06:17 place. You begin with a story of training a falcon and Mimi, you call her a refined daughter of
0:06:23 Texas aristocracy by way of New York, clutching a live bird in one hand and a needle and thread
0:06:30 in the other, preparing to sew the bird’s eyelids shut. Can you tell me why did you start this huge
0:06:36 story about mental illness with this one incredibly vivid and surprising moment?
0:06:43 This took place maybe a week or two after Mimi and her children moved to Colorado Springs in
0:06:48 the early ’50s to join their husband who had just moved there for the Air Force. The whole thing was
0:06:53 unfamiliar to her. It was out of her comfort zone and then to be thrust into this situation where
0:07:00 she was suddenly getting into falconry and having to sew eyelids shut, this was as foreign as it
0:07:05 came to her. The point of the story really is that she accomplishes it. She winds up training and
0:07:12 disciplining the falcon and it winds up becoming almost an allegory for how she approaches the rest
0:07:16 of her life, including the raising of children. She thinks if she tries hard enough, does all the
0:07:21 right things and does them all in the right way with discipline and pressure, she will get the
0:07:26 results she desires. And we all know that with children that isn’t exactly true, but in the
0:07:34 Galvin family’s case, it’s tragically true. 12 children, six of whom had acute mental illness.
0:07:41 And before we get into this particular family and how they dealt with this, I just want to talk
0:07:46 also a little bit about up until that moment, the different treatments that had matched up to our
0:07:51 understanding of the disease that we had tried. You mentioned insulin shock in the 1930s, lobotomizing
0:07:56 attempts and things like that. Can you kind of map out those early therapeutic attempts?
0:08:01 Well, lobotomy is about severing nerves in your frontal lobes. It’s an extreme measure and I
0:08:07 think most people would consider it barbaric now, but it was intended to impair you just enough
0:08:11 so that you would stop hurting yourself mentally. That seemed to be the justification for it at the
0:08:16 time. But the other procedures that you mentioned, things like electroshock therapy and insulin
0:08:22 shock therapy all sort of operate on the same principle, which is to somehow induce enough
0:08:29 stimulation, enough of a seizure, even almost a medical coma, so that you shock the patient into
0:08:35 focusing and not being so distracted or drawn away by whatever is going on with their brain chemistry.
0:08:41 And sometimes it would seem to work at least temporarily, and other times they would decide
0:08:46 that the person needed to be shocked every day. So then in the 1950s, a major development on the
0:08:51 drug side, you talk about the entrance of thorazine onto the scene, which dominates the next
0:08:55 second half of the century and still has a huge legacy in how we handle this
0:09:03 mental illness. Can you talk about what brought thorazine in and what that moment was like?
0:09:08 Like a lot of pharmaceutical advances, it happened sort of sideways or by accident.
0:09:12 There was a French surgeon who was trying to come up with a battlefield anesthetic,
0:09:20 and he did some combining of traditional anesthetic and narcotics and found that the people he was
0:09:26 testing it on, it almost induced a happy coma on them the way that he described it. This drug
0:09:32 eventually was thorazine and even now, really, thorazine is the great advancement pharmacologically
0:09:38 for schizophrenia and still is. And then there’s an atypical version or variety of a psychotropic
0:09:44 drug called chlozapine. And my understanding is that those two drugs really are the coke and pepsi
0:09:50 of this field and that any drug out there is sort of a derivation of one or the two.
0:09:56 There are people who were in such extreme condition and harming themselves so much
0:10:00 that certainly drugs like this could be helpful to them to keep them alive.
0:10:05 But I think the other sad fact is that they aren’t cures and that it’s been decades now
0:10:10 and there really has been no revolutionary drug for schizophrenia since the 1950s and 60s.
0:10:14 The best clue to actually understanding how to attack a disease is have something that cures
0:10:19 the disease, especially something like schizophrenia where the etiology, we may be starting to
0:10:24 understand some of the underpinnings with it, but people don’t come to us at birth and say,
0:10:29 “I’m going to have schizophrenia. Please modify me in some way.” We wait until the symptoms develop
0:10:35 and so exactly as Bob said, it was the cornerstone advance in the field to find a therapy that you
0:10:41 can take as a pill that did in some ways make some patients better. Then you can just simply
0:10:46 reverse engineer that therapy and try to find out on a molecular level what is it doing.
0:10:50 And then that leads to understanding of disease, to dopamine receptors, to serotonin receptors,
0:10:56 and so on. So let’s go back now to that moment in the 1950s which is basically where the Galvan
0:11:03 story starts as well. By the 1960s, the oldest of the 12 Galvan children were starting to go
0:11:08 off to college and as we know schizophrenia’s onset is quite often in late adolescence. And so
0:11:13 the oldest son, Donald, the star of the family, the football star, the guy who dated the general’s
0:11:20 daughter and who was a master falconer and repeller on the cliffs of central Colorado,
0:11:25 he had really had secretly felt quite alienated from mainstream life and really was struggling
0:11:30 in many ways privately and that struggle went public by the middle of college. He ran into a
0:11:36 bonfire and didn’t know why, he tortured a cat and killed it and didn’t know why. He ended up in
0:11:42 student health services for many different reasons until finally psychiatrists got involved. And this
0:11:49 was a panic moment for Don and Mimi Galvan, the parents, because they knew that first of all they
0:11:55 would be judged because at the time if your child had a psychiatric problem it obviously must have
0:12:01 been the parent’s fault. And so they went shopping for a good opinion because back then really what
0:12:06 illness you had psychiatrically really depended on what doctor you visited. Some would say give him
0:12:12 Thorazine, others would say give him a lobotomy. So they went and they found a doctor who recommended
0:12:17 he could go back to college and that he would just grow out of it. And then he got worse and worse
0:12:24 and until finally he had a moment of violence with his young wife, that was it for him. He went off to
0:12:28 the state mental institution for a few weeks and then spent the rest of his life
0:12:34 really at home with Don and Mimi, with his parents, almost as a revolving door between the state
0:12:40 institutions and home. It struck me that every story kind of showed the different lenses that
0:12:47 we’ve used to try and understand this disease. Each had some of these common traits and some
0:12:54 wild discrepancies and differences. A lot of the stories began with we sort of always knew,
0:12:59 but some of them became completely out of left field. And then some of them even seemed like
0:13:05 they come from a cultural moment like Michael who goes to live on the farm in the 1960s.
0:13:09 That’s right. Michael’s sort of a hippie and he is rebelling and then that gets confused with
0:13:16 mental illness for a time. He insists that he is not mentally ill. Peter was very, very
0:13:21 oppositional as a kid said no all the time and then he had psychotic breaks. So you could say
0:13:26 they saw that coming. Joseph had a detachment from reality, it seemed now and then. And so
0:13:31 everybody was sort of waiting for him to finally have a psychotic break and he did in the early
0:13:36 80s. But then there were surprises. Matt, who was a talented ceramic artist suddenly one day out of
0:13:43 nowhere, smashes something that he made and strips naked in a friend’s house and suddenly
0:13:50 he becomes medicalized as well. So it’s interesting how some seem explainable and others do not.
0:13:55 At the same time as we’re hearing this story of how our understanding of the disease changed and how
0:14:02 this one family that manifested so many of those efforts to understand and manage it,
0:14:08 it’s also a story of technology, the developing technology that we have to understand biology
0:14:13 and to understand our brain. Another key moment was when suddenly we start being able to see the
0:14:21 brain through scans in the 70s. Can we go to how this story evolved when that kind of technology
0:14:29 came on the scene? Yes, by the 70s researchers were able to have some glimpses into the brain
0:14:35 thanks to technology, thanks to MRIs and PET scans and CT scans and the like. And with the
0:14:41 sequencing of DNA, it became possible to think about being able to actually study the genetics of
0:14:46 any sort of population of people with any sort of illness or disease. Technology drives biology
0:14:50 across multiple areas. I see that story again and again in whatever field I’m in. You look at the
0:14:55 beginning, the first MRIs, those could only be structure. This might tell you is the structure
0:14:59 of the brain different, but it doesn’t tell you how it functions. It feels like it’s a story about
0:15:04 a family, but it’s also really a story about kind of modern genomics and going from understanding
0:15:11 something as a inherited disease in some way to dialing into a way different level of understanding
0:15:17 about genetic information. So what was the genomic story of what we understood of schizophrenia
0:15:23 pre-Galvin’s? Why was the family such a turning point in the context of the human genome project?
0:15:28 And then what did we learn from them? I write about Robert Friedman, who’s at the University
0:15:34 of Colorado Hospital, and Lynn Delisi, who is at the National Institute of Mental Health.
0:15:38 Lynn’s story really intersects with Stefan’s, my fellow guest on this show.
0:15:44 And before she met Stefan, she was a pioneer in studying families like the Galvans. And the
0:15:49 Galvans were the biggest family she ever found in those early years. And she was convinced that
0:15:54 families were the best way to take a look at this illness because you weren’t searching for a needle
0:15:59 in a haystack. You had a much smaller haystack to look through. They were a closed petri dish of
0:16:04 shared genetic data with a lot of incidents of schizophrenia. Multiplex families like the Galvans,
0:16:09 with lots of schizophrenia in them, have something to teach us. And she amassed the largest collection
0:16:14 of family DNA for this purpose. But there came a time in the ’90s when the human genome project
0:16:19 was underway, when everyone thought that once the genome was sequenced, they’d be able to do
0:16:25 entire population-wide studies. And that anyone with schizophrenia or with any other complex
0:16:31 genetic disorder would sort of stick out like a sore thumb, you would find the smoking-gun gene,
0:16:38 or genes. And then you’d have a target to medicate with a drug. And bingo, we’d all be cured by the
0:16:45 time dinner came. But the problem is that with complex conditions like schizophrenia, it only
0:16:51 complicated things so much more. They found one genetic irregularity for schizophrenia, and then
0:16:57 another, and then another, and then another. Until now, there are far over 100 genetic issues.
0:17:04 Unfortunately, each one of these irregularities contributes just a fraction of a percentage of
0:17:09 the probability that you might get the illness. And so it winds up being meaningless. It strikes
0:17:15 me as just as fluid and complicated and long a list as the list of symptoms that over the last
0:17:21 century have been associated with the disease, the manifestations of it. Exactly. And it’s not
0:17:27 helpful clinically. It might be helpful for future research, but at the moment, it just makes the
0:17:33 mystery more mysterious, which is what makes it so interesting that when Stefan recognized that
0:17:38 families might have something to offer and wondered, hmm, who out there has been studying
0:17:43 families? And lo and behold, there was a woman who had been doing it all this time, and the two of
0:17:47 them teamed up. Stefan, can you talk about what it was like to enter on the scene in that moment and
0:17:54 what the genomic aha was for you there? Yeah, the technology had not been there to really analyze
0:17:59 the families that Lynn collected. She collected them so much before the technology was available to
0:18:04 really look in fine depth at the genome and find, is there something different? Back when I was in
0:18:10 grad school studying genetics, it was mustard weed and fruit flies and sort of model organisms.
0:18:15 When the genomic revolution came along, so much computational power came to be developed. The
0:18:21 technology just kept developing to be able to sequence entire genomes rapidly and inexpensively,
0:18:26 comparatively inexpensively. People sort of thought with a disorder that is so strongly
0:18:33 heritable as schizophrenia, there must be something there. And again, what was turned up in surveys
0:18:38 of tens of thousands of schizophrenia, looking at all the genetic variants they carried versus tens
0:18:44 of thousands of people matched controls as best they could, say for ethnicity and other factors.
0:18:49 No question there are differences. Those have led to some hypotheses, like sort of a general
0:18:55 overall role of the immune system. But in terms of discovering what is the driver
0:19:01 for a disease like schizophrenia, it just simply didn’t work that way. And we still don’t understand
0:19:07 why. Where are we starting to make progress there and understanding kind of the biology
0:19:13 and the drivers and potentially how to treat them? You talked about looking at when a drug
0:19:18 like Thorazine works and trying to work backwards from that to understand more of the biology.
0:19:23 Are we still there or does our understanding of the underlying genomics shifted a bit?
0:19:30 Shifted a bit. I think we’ve gone from a picture of, again, as Bob said, evil spirits or dreams
0:19:36 or some environmental influence or a mother to sort of a holistic picture of the brain whereby
0:19:42 following Thorazine, we would say, okay, well, dopamine is dysregulated or glutamate is dysregulated
0:19:46 and these are chemicals neurotransmitters for how nerve cells communicate with one another.
0:19:53 Now we’re verging towards a sort of cellular synaptic view. Another of the technology that
0:19:59 developed probably in the 80s and especially 1990s was the ability to really look in very,
0:20:05 very fine detail in sort of millisecond scale resolution at how nerves communicate with one
0:20:10 another. You can stick an electrode on one nerve and stick an electrode on the other and really
0:20:15 record how they’re communicating. So this is, I think, how our overall picture of biology is
0:20:22 evolving into as to what it means how we cure the disease. Classic analogy, in order to fix a
0:20:27 broken TV set, you have to know what makes it work in the first place. And we’re still not there,
0:20:32 but we’re getting closer. What is the technology that’s coming onto the scene now that is changing
0:20:38 our potential understanding moving forward? I think one of the areas that’s exciting now
0:20:43 is you can actually take a skin cell from somebody and treat it with appropriate biological factors
0:20:49 and it will differentiate into something that to first approximation might be a human neuron.
0:20:54 I haven’t seen therapies come out of it yet. In fact, it may be another blind alley as with
0:21:00 all areas of research. But there is the hope that if you take a skin cell or a group of skin cells
0:21:06 from somebody with schizophrenia, perhaps that mutation is genetic. Perhaps that mutation then
0:21:12 is still carried in the skin cells and their nerves might look different. So this is a possible angle.
0:21:16 It’s a bit of a risky one for many reasons. You never know if you’re actually dealing with a neuron.
0:21:20 What do you mean by it’s hard to even know if you have a neuron?
0:21:26 Well, you’ve taken a fibroblast, a skin cell, you’ve treated it with appropriate factors and
0:21:31 certainly it elongates, it starts sending out processes and if you can stick an electrode
0:21:36 in it, you can see that it’s electrically active. Does that mean that it really is close enough to
0:21:41 a human neuron in a human brain that has developed through its entire life, through the entire life
0:21:45 of the individual and has been exposed to all the different environmental influences?
0:21:46 Right.
0:21:51 The question isn’t, is one thing like the other? They are like on some level, unlike on others.
0:21:56 Is it enough alike that you could actually try to turn a therapeutic on it and try to do your
0:22:01 modification now you’ve got sort of a disease in a dish? And that’s an open question.
0:22:06 Bob, where would you see the Galvanes their story if it was unfolding today? Can you talk a little
0:22:12 bit about how it kind of mapped to where the understanding is, where their story ended?
0:22:16 Well, the two separate teams who studied the Galvanes, each have come forward with some really
0:22:23 interesting advances, both of which offer a lot of hope. Lynn, Delisi, and Stefan sequenced the
0:22:29 genome of the Galvan family and found one irregularity in a gene called shank 2. This is not a
0:22:34 silver bullet or a smoking gun. It’s not like the shank 2 gene is the ketoschizophrenia. However,
0:22:41 assuming that it is the player that really did its trick on the Galvan family, it is a gene that’s
0:22:45 highly related to brain function and could, with further study, point the way to understanding
0:22:51 how schizophrenia works, how that TV set works, as Stefan had said before. And so that’s exciting.
0:22:57 And more broadly, in terms of drug discovery, families like the Galvanes can be almost sort
0:23:03 of test kitchens. You can look at how their genetic code might interact with certain potential
0:23:08 therapies and see perhaps how it might go with the broader population. Then with that second
0:23:14 set of researchers led by Robert Friedman over in the University of Colorado, he, with help from
0:23:19 the Galvanes and other families, identified another genetic area called churn a seven. And churn a
0:23:25 seven is related to the vulnerability theory of schizophrenia, which is that perhaps one is
0:23:31 oversensitive or has a sensitivity issue to stimuli. It looks at schizophrenia as a developmental
0:23:37 disease, one that really begins in utero even though it manifests itself much later. And over the
0:23:43 years, he struggled to find a way to perhaps make the churn a seven area more healthy or more resilient
0:23:51 and less vulnerable. And he has a hypothesis that there actually is a safe nutritional supplement,
0:23:58 choline can strengthen brain health generally of the unborn child, but also perhaps cross your
0:24:05 finger 16 times, perhaps many years from now prove to make the children more resilient,
0:24:11 less vulnerable to psychosis. And they’re doing longitudinal studies right now using choline,
0:24:15 and if it shows any promise at all, he has the Galvanes and other families like them to thank.
0:24:20 Stephanie, it would be very interesting to hear from your side of the kind of story of the pharma
0:24:26 industry attempt to manage this as well. Where would you see those attempts after Thorzine?
0:24:30 Then where did we go next? And what was the sort of industry response? Where are we today
0:24:34 in the possibility? Yeah, there was a quite productive age where drugs like Cypraxa were
0:24:39 developed, where we’re looking for simply animal behaviors that were related to schizophrenia.
0:24:44 And here is where having sort of a toolkit is quite valuable in a sense, because if you know,
0:24:49 for example, if there’s some odd behavior that an animal is showing that Thorzine mitigates,
0:24:53 then without even knowing the receptors involved, perhaps you can test drugs and animals
0:24:58 for other drugs that mitigate those behaviors and perhaps don’t have side effects.
0:25:03 So the problem, of course, is that rats don’t get schizophrenia. They don’t even have sort of the
0:25:07 massive cortical structures in the folding that we think is where the
0:25:10 higher processes that are affected in schizophrenia reside.
0:25:14 So to your point about cells in a dish, I mean, it’s really a problem of models, right?
0:25:19 It’s a problem of models. How do you, before doing a clinical trial in humans,
0:25:25 how do you get confidence that your drug is going to work? And I think in the 1990s, there were
0:25:29 a number of very good efforts based on sort of synaptic studies. People have known, again,
0:25:34 going back to some of the early pharmacology that dopamine was involved, that glutamate was involved.
0:25:39 Now we started to identify with the human genome project and just molecular cloning in general.
0:25:45 We started to uncover what the molecules are that regulate glutamate and regulate dopamine.
0:25:50 And a number of clinical trials were done on these as well.
0:25:54 What still does stymie the field today is, if you take the overall disease,
0:25:59 what is your model? What do you test it on that gives you confidence that you can test
0:26:01 this safely in humans and that it will have some effect?
0:26:07 How do people even do that? I mean, are there any other tools before you begin clinical trials in
0:26:11 humans when there’s a disease that really doesn’t present anywhere else outside of humans?
0:26:16 Schizophrenia is a tough one. It’s very tough. Now nothing is easy, but for example,
0:26:21 tumors do grow in animals. And you can implant a patient-derived x-plant,
0:26:25 a patient-derived tumor into an animal, and perhaps test therapies there.
0:26:31 Or you do have cancer cell lines, tumors will actually, cell lines will actually grow in a dish.
0:26:35 And so something that kills those could reasonably be called to be acting on the tumor.
0:26:38 And we simply don’t have that equivalent for schizophrenia.
0:26:43 So what was the next moment where there was sort of a something that seemed
0:26:47 on the pharmacology side like a real viable treatment that we were,
0:26:50 you know, that people were getting excited about? And where are we now?
0:26:54 People were excited about metapotropic glutamate receptors. That’s a particular type,
0:26:58 a subtype of glutamate, which is the main excitatory neurotransmitter in the nervous
0:27:03 system in humans. People were excited about sort of finer manipulations of dopamine receptors.
0:27:07 And again, by reverse engineering some of the atypical antipsychotics,
0:27:11 you could find out that serotonin receptors also had involvement.
0:27:15 Now each of these is going to be a broad family of many, many genes.
0:27:22 So can you do more finer manipulations of these? Not every advance in drug therapy has to be a
0:27:29 totally new mechanism. Schizophrenics and other CNS disorders are famous for going off their medications.
0:27:34 So if you can perhaps make a medication that just simply lasts longer
0:27:39 and can be given maybe every month or even at less duration under a doctor’s supervision,
0:27:43 that’s a significant medical advance. And this is an engineering challenge.
0:27:49 I started life as an engineer and drug discovery is really biological engineering.
0:27:53 I’m not saying it’s easy, but we do know how to make drugs last longer in the body.
0:27:56 There’s a very interesting story in there with Nicotine.
0:28:02 The receptor that Robert Friedman in Colorado had identified with help from the Galvin family
0:28:07 and other families like them was a nicotinic receptor. And strictly speaking,
0:28:13 that’s a receptor that when medicated might actually help with focus and concentration.
0:28:18 I mean, there’s a stereotype of schizophrenic patients actually getting some relief from chain
0:28:23 smoking because it focuses their mind. And there’s a hypothesis related to nicotine,
0:28:28 and there was for a time that if you could somehow drug this receptor a little bit to help it along,
0:28:34 that perhaps this would prevent delusions or even prevent psychotic breaks.
0:28:39 And Robert Friedman did try for a while to work on a drug for that, and he reports anecdotal
0:28:45 excellent results from many patients. But it was a drug that you had to take several times a day,
0:28:50 and that was something that the pharmaceutical companies couldn’t bring through trials to make
0:28:56 into a once a day drug. So it went away. So he decided to go after the nicotinic receptor
0:29:04 in utero through choline. Especially in the 1990s, there was a lot of companies and a lot of academic
0:29:10 researchers investigating nicotine and nicotinic receptors. And again, there did seem to be a
0:29:15 clear link to schizophrenia. Perhaps schizophrenics are self-medicating by smoking. If so, perhaps
0:29:21 you can make sort of a subtype of nicotine that gives you some benefit or perhaps even some more
0:29:26 benefit. And again, as Bob said, that perhaps lasts long enough in the body to be practical to
0:29:32 be taken as a drug. So in this case, there was a biological challenge there, no question. But it
0:29:39 became also an engineering challenge, as all drug discovery does. Nicotine is quite a non-selective
0:29:43 molecule. Well, everything it hits is called a nicotinic receptor. But your body has something
0:29:49 like 14, 15 genes for individual subunits that together come together to form a receptor for
0:29:54 nicotine. And they all mix and match in very unpredictable ways and ways that still are not
0:30:01 well known. So the challenge was quite formidable. People did go ahead for technical reasons.
0:30:06 It turned out to be easy to make sort of a subform of nicotine that would only hit Alpha 7
0:30:12 receptors. Not easy, but not impossible either. People had good reason to think that this might
0:30:18 work. No question, it was a huge downer for patients, for the field, for everybody when
0:30:23 this entire class of drugs just sort of didn’t seem to come to nothing. But we learned.
0:30:30 And the negative result often is just as informative as the positive result we do learn.
0:30:37 Can I ask how incentivized is the sort of pharmaceutical industry right now to find
0:30:43 other alternatives to things like the class of drugs that, you know, Thorazine and some others
0:30:48 that you’ve mentioned? I mean, because those do work to some extent, yes?
0:30:53 To some extent. So I’m not a clinician. About 50% of the patients respond well to
0:30:59 atypical antipsychotics. But this doesn’t touch sort of the cognitive and the emotional problems.
0:31:04 And one of the things, one of the many things I’m grateful to Lynn for was really taking me
0:31:10 to visit her patients so that I could really see there’s no question something is wrong,
0:31:16 just sort of a very emotionless, flat affect. The cognition is fine. Clearly,
0:31:21 these people are very articulate. They’re very bright in many cases. But something’s
0:31:27 badly wrong. So to your question, what is the incentive for pharmaceutical companies?
0:31:32 It’s a huge incentive. I think lots of people would love to do it because schizophrenia is
0:31:39 1% of the population. This is across populations, across cultures. So it’s a huge opportunity
0:31:43 to make therapies that help patients. For what is not a rare disease.
0:31:49 For what is not a rare disease. And if you go beyond that, again, as Bob’s book so amply
0:31:56 demonstrates to the toll on people’s lives, it’s far beyond that 1%. We just don’t know how to do it.
0:32:02 Not for the broad schizophrenia there. And this is where I came from my angle
0:32:07 to sort of look at perhaps there might be subtypes of schizophrenia defined by genetics,
0:32:11 where you really would have one particular form of schizophrenia.
0:32:18 So Stefan, if you, as a researcher, if you could wave a magic wand right now,
0:32:24 you know, you mentioned better models. What are the things that if you could wish something here
0:32:29 tomorrow in the form of a new technology or a new capability, what would that be that would
0:32:34 really push us forward into a new chapter? I’ll go way afield. But if we could monitor
0:32:40 the brains of a schizophrenic with sufficient resolution with high resolution, right now we
0:32:46 get about a millimeter voxel with the best bold fMRI experiments. While they’re actually having
0:32:51 a psychotic break, the resolution is still, of course, could be made finer and finer. We still
0:32:56 can’t get down to the level of a single cell. But now with the blood oxygen level dependent,
0:33:02 magnetic resonance imaging, we can get a measure of function in somebody’s brain in real time.
0:33:05 Difficult to do, takes a lot of equipment, takes a particular stimulus,
0:33:08 but one could perhaps hope that this will lead to more insight.
0:33:13 Oh my gosh, how fascinating that we’ve never seen. We actually have no idea what’s really happening.
0:33:18 I mean, consider the logistics. You can’t consent somebody and get them to sit in a machine and
0:33:24 then wait for them to have a psychotic break. Yeah. What would you be looking for?
0:33:31 We need mechanism. If the field as a whole could say, here is a particular area where the excitability
0:33:37 is abnormal, an area of brain tissue that is abnormally excitable, or a particular receptor
0:33:43 that is abnormally excitable, that gives us a good place to start. That gives us mechanism.
0:33:48 And then perhaps we could study what do existing drugs do to that. What is missing with existing
0:33:55 drugs? That’s fascinating. It almost sounds like you need like a wearable MRI, a very high resolution.
0:34:04 Silicon Valley, go to it. What about things like CRISPR? If you do start defining some very specific
0:34:09 narrow, very entirely genetic cause, is that a possibility as well?
0:34:17 So we’ll give a possibility. Say if we knew that a baby galvan or their modern-day counterpart babies
0:34:23 had a variant in a gene that we thought because of families like the galvanes that we had good
0:34:28 reason to believe would make them develop schizophrenia. Can we get in there and change
0:34:36 that one nucleotide to the wild type? It’s conceivable, but again the challenge here is
0:34:43 the engineering challenge. We can do it in a dish, but trying to get just that one gene edited,
0:34:50 trying to get it in just that one nucleotide changed in every cell in the brain and no changes in
0:34:56 any other nucleotides in the brain and delivering something that will actually cross the blood
0:35:02 brain barrier and then doing it on an infant. How would you even test this? Very, very difficult.
0:35:08 Bob, you describe when Lynn Delisi first met the galvan family and you write this incredibly
0:35:12 profound line that really stuck out for me. As she walked through the door of the house at
0:35:17 Hidden Valley Road, she couldn’t help but recognize a perfect sample. This could be the most mentally
0:35:23 ill family in America and you really dove into every element of what that meant for them into
0:35:31 this family’s innermost suffering and struggles. It was just so intimate on some level and also
0:35:36 such a big story on another level of not just schizophrenia, but the way we struggle with
0:35:43 all mental illness, including trauma and depression. What was the kind of big takeaway for you for
0:35:50 having lived inside this family’s mental illness for several generations, really?
0:35:56 Well, I really think the day, hopefully not too long from now, that all this research yields real
0:36:02 rewards will be the day that this family’s sacrifice will finally find its true meaning.
0:36:08 But also, this is a story about experiencing unbelievable and mysterious tragedies one after
0:36:13 the other and coming out the other side. There are members of this family who have found a way
0:36:16 through this and found meaning in life when everything seemed to be going against them.
0:36:22 It’s really about the value of family, in my opinion, this story and the hope for the future.
0:36:26 Stefan, on the research side, what’s coming that we should be aware of that might be
0:36:29 bringing hope to the next generation of Galvans?
0:36:34 It’s tough. I could answer this for Parkinson’s. I could answer for Alzheimer’s. I could answer for
0:36:39 any number of diseases. Schizophrenia is really, really tough. We need some help. We need something
0:36:44 to break in the academic world and that break will come from studying people. There are ever better
0:36:50 ways of studying what is really going on with human biology in people who are kind enough and
0:36:55 selfless enough to volunteer themselves and their families for research. Not just their genome,
0:36:59 we can measure the protein circulating in their blood. There are ways to do this massively in
0:37:04 parallel. Stem cells, organoids, I think it’s too early to see if these are going to be helpful,
0:37:09 but no question, these are a way to explore. People can do longitudinal studies for how people
0:37:14 are changing over time. Imaging lets us look into the brain better than ever before and these
0:37:20 technologies just keep accelerating and improving. We need somebody to set the goalposts. There’s
0:37:26 a lot of advanced technology. Technology will drive biology. We are focused on human subjects.
0:37:32 Something’s got to break. That’s amazing. Thank you so much for both of you joining us on the
0:37:44 A16Z podcast and here’s hoping we get to that break soon.

0:00:05 The content here is for informational purposes only, should not be taken as legal business
0:00:10 tax or investment advice, or be used to evaluate any investment or security and is not directed
0:00:15 at any investors or potential investors in any A16Z fund. For more details, please see
0:00:21 a16z.com/disclosures. Hi, and welcome to the A16Z podcast. I’m
0:00:27 Doss, and this episode is all about what the numbers, both financials and KPIs, do and
0:00:32 don’t tell you about your business. Our guests for this episode are A16Z General Partner and
0:00:37 Managing Partner Jeff Jordan, who previously ran several businesses and took a company
0:00:42 public right after the 2008 financial crisis. David George, who runs our late-stage venture
0:00:47 operation, and Caroline Moon, who leads our financial operations practice and helps companies
0:00:54 with their own best practices. She’s also a former CFO. In our conversation, we cover
0:00:58 the most common mistakes people make when it comes to understanding numbers. When investors
0:01:03 think when they look at a company’s profit and loss statement and why, how investors
0:01:07 use metrics to determine if a business is healthy, and how some founders may use them
0:01:13 to navigate times of crisis. We begin, though, with the basics of the three core financial
0:01:18 statements, the income or PNL statement, the balance sheet, and the cash flow statement.
0:01:24 The first voice you’ll hear after Caroline’s and mine is Jeff’s, followed by David’s.
0:01:28 Especially in the early days of a startup, they’re just going to do cash accounting,
0:01:30 and that’s just literally how much cash you had in the beginning of the period and how
0:01:35 much you had cash at the end of the month. That’s not the same thing as what a PNL really
0:01:41 should show, because your PNL paints the picture of how your business did in a particular period
0:01:46 of time and measurement, whether that’s quarterly or yearly, or the cash statement then reconciles
0:01:49 that with what did you actually collect. Everything that happens on that cash flow
0:01:52 statement then ends up on your balance sheet.
0:01:57 The reason why it’s important to be able to present it in that fashion, it’s called generally
0:02:03 accepted accounting principles, so GAP accounting, is because that’s how everyone understands
0:02:08 that the comparisons are apples to apples when you look across companies.
0:02:12 When you are trying to figure out how a business is doing, what are the financials that you
0:02:13 look at?
0:02:20 Typically, the early investing, you don’t emphasize financial metrics that much, because
0:02:24 usually, there isn’t a mature go-to-market organization. I tend to focus much more on
0:02:31 KPI-type metrics, users, daily to monthly users, engagement, and things on those lines,
0:02:34 and then the financials tend to emerge over time.
0:02:40 Yeah, I would say I care most about two very high-level topics at the later stage. The
0:02:47 first is, can you demonstrate that you can have very persistent growth? Secondly, how
0:02:53 profitable will you be when you reach scale? I spend less time for later-stage high-growth
0:02:58 companies staring at their balance sheet than I do KPIs, income statements, and cash flow.
0:03:02 The main thing I look for in the balance sheet is the comparison for how much traction they
0:03:06 have on the income statement and the cash flow documents relative to the amount that’s
0:03:10 been invested in the company. For me, the most important balance sheet metric early
0:03:15 is how much capital is the company deployed to get to where they’re going.
0:03:19 How do you guys know when a business is truly profitable?
0:03:24 I do think you go to the unit economics and really understand them, but this is often
0:03:29 a lot of art as well as a good amount of science. Some of the most frustrating interactions
0:03:34 I’ve had with companies are where they’re presenting that their unit economics work,
0:03:38 but the business isn’t working. And so I had one where, okay, we’re capital efficient,
0:03:43 the unit economics are working, we acquire users, they’re profitable in three months,
0:03:48 and the company was hemorrhaging cash. It turns out the unit economics actually weren’t working.
0:03:53 The cash flow statement was the arbiter of truth and the analysis that the company had
0:03:57 done on unit economics was wrong. Yeah, I agree. I think lifetime value is one
0:04:01 of those traps that people fall into. They’re assuming, oh, our customers are going to stay
0:04:05 with us for five years, three years, so we’ve got plenty of time to do the payback,
0:04:09 but that’s a key driver to whether or not your unit economics work.
0:04:14 There’s nothing that’s less consistent in the market than how lifetime value to
0:04:20 cost of acquisition of the customer. LTV to CAC is defined. What I always counsel companies and I
0:04:26 like to see is very transparent calculations of what goes into the LTV side and the CAC side.
0:04:33 So the LTV to CAC metric that I like to look at is for the LTV, so the lifetime value side,
0:04:38 I always use gross profit, not revenue. And then I like to use a shorter duration than
0:04:43 founders typically like to use. So I like to use three years. Often founders present five years,
0:04:47 and the point I make on that is that five years is too uncertain and long of a period of time,
0:04:52 whereas three years is much more visible, and then use actual retention statistics that you’ve
0:04:57 experienced in the past to project those three years. The thing that I really try to emphasize
0:05:03 to founders when they talk about these kinds of metrics is, look, this is not about necessarily
0:05:07 showing investors. This is how you have to run your business. What am I spending on sales and
0:05:12 marketing? What am I spending on my R&D? And how much am I spending on G&A? And is that
0:05:17 the right level of investment that I should be making in my company? So you need to be as honest
0:05:21 with yourself as possible as to what all these things cost you and what you’re really generating
0:05:25 in terms of revenue, because if you can’t be honest with yourself, you can’t run your business.
0:05:30 What are some of the other really common mistakes or things that founders do in presenting numbers
0:05:34 that you’d want to help them correct or you’d like to see them do differently?
0:05:39 You know, one tell for me where business is probably struggling is when they come up with
0:05:46 North Star metrics, you know, KPIs, and then when they come back to report on them a quarter later,
0:05:50 they’ve changed. And then they come back a quarter later and they’ve changed again. And what I found
0:05:55 a little bit of pattern recognition is when the KPIs change all the time, it’s largely because
0:06:01 they’re not working. And the company’s trying to navigate through it. For me, you pick your metric,
0:06:07 you report on it. And ideally, your understanding of the business improves over time as your metric
0:06:12 and your models are either validated or unvalidated. That leads this interesting question, I think,
0:06:18 of the psychology and how you look at your numbers. So how do you manage your own psychology
0:06:21 so that the numbers are a tool, not this obsession where it’s like,
0:06:26 my obsession is I want to reach my KPIs. So I’m going to keep adjusting my KPIs. So I do.
0:06:30 You know, the reason they’ve so defined the three financial statements is it’s kind of truth-seeking
0:06:36 and trying to fool your investors or lack of better word or your board. You know,
0:06:42 I don’t want to let them know how bad things are. By not telling the truth to your key constituents,
0:06:47 you often run the risk of not telling the truth to yourself. And so I’ve had a couple founders
0:06:53 where sometimes they fall prey to it themselves, where they believe their own machination,
0:06:57 and then the board and investors can’t help them based on the truth.
0:07:03 What do the best founders do, especially in challenging moments, like when the finances
0:07:07 and the numbers maybe aren’t going your way, or you know that you do have to tell a difficult truth?
0:07:13 They typically acknowledge it. They take it as, okay, the truth isn’t what I wanted it to be.
0:07:17 So now, what can I do to change the business to improve the truth?
0:07:21 The only thing I would add to that that I’ve observed from some of the best founders of
0:07:28 later stage companies is they’re very careful not to drown themselves in KPIs. So you can actually
0:07:34 inundate yourself with KPIs, but the very best ones pick out a very few handful of metrics that
0:07:39 they think are the most important drivers of their business. And if they see those divert from where
0:07:44 they would like them to be, they dig in from there. So for example, Ali from Databricks always
0:07:50 focuses on the productivity of a sales rep because he believes that indicates health
0:07:55 of the business in many different ways. So how well is the sales organization actually functioning?
0:07:58 What are the market dynamics? What’s competition? How is the product performing?
0:08:03 And you do get a real force for the trees. I have companies that will present you 50 pages
0:08:09 of metrics based on the last quarter and you just drown versus what in here is really important?
0:08:13 What are the key ones? Are the one or two that matter the same for every company or does it
0:08:18 depend on the nature of the company and the stage that they’re at? I think to some degree,
0:08:22 some of them are the same. For instance, retention should matter to any business model.
0:08:26 You spent money to acquire your customer base. How long are you hanging on to them?
0:08:31 Yeah, I find they are consistent by type of business. So marketplace metrics typically
0:08:36 have a lot in common with each other, but they’re very, very different than e-commerce metrics.
0:08:40 The key e-commerce metrics typically center around the efficiency of customer acquisition
0:08:46 and LTB to CAC. A lot of marketplaces I work with don’t spend a penny on customer acquisition.
0:08:52 And so it’s got organic distribution or something like that. So comparing across models can be
0:08:58 challenging. Comparing within models can be very helpful. So for B2B companies, for example,
0:09:03 the efficiency with which you spend a sales dollar, whether it’s on a rep or marketing
0:09:07 or bottoms-up sales, inside sales, outside sales, is always one of the most important things that
0:09:12 you look to. Things change. Markets are unpredictable, which is something I think we’re seeing now
0:09:18 more than ever. How do you use finances to make better, faster decisions, especially in uncertain
0:09:24 times? You know, I started my career in finance. I ended up as CFO at the Disney Store. So it’s
0:09:28 near and dear to my heart. The typical finance function is conceived of as kind of keeping score,
0:09:34 the accounting control function, just reporting back. For me, that was necessary but not sufficient.
0:09:39 The finance function has access to all of the key data. And so I look at them not only to keep
0:09:45 score, but to score points to make the business better by leveraging their access to the information
0:09:49 and to the trends and to the unit economics to improve the business.
0:09:57 A good finance leader needs to work with the CEO to make sure that the company has
0:10:04 enough money to not just survive but thrive. So that is becoming super intimately familiar
0:10:08 with the business, not the financial statements, not the accounting that goes into developing
0:10:11 these things, because those just represent what’s happening at the business level.
0:10:17 They really need to understand how everything works and then where are the levers that you can
0:10:22 change, that you can pull on, that you can push on to accomplish the things that you want to do
0:10:27 as a business in the timeframe that you need it all backs up with the cash that you have on hand.
0:10:32 When I was managing businesses, I always had a mental model of how the business should work.
0:10:37 And that mental model typically, ideally, was consistent with the financial model.
0:10:43 eBay, back when I managed it, was a perfect economy. And eBay as a platform attracted every
0:10:48 leading finance professional who was into micro because it was one of the most pure examples
0:10:54 of a perfect economy. If there was an increase in supply, prices fell. If you change the fee
0:11:00 structure, behavior changed. And so it’s when businesses diverge from my mental model that
0:11:05 you really needed to pay attention. It’s like, why is the conversion rate going down? My god,
0:11:10 I’ve never seen it go down like that. That’s a big warning indicator for me. So I would
0:11:15 typically be pretty comfortable running the business until anomalies emerge. And then I just
0:11:19 would need to understand the driver of the anomaly. And I can’t emphasize enough how important it is
0:11:24 for companies to understand their bottoms up for how revenue is generated. I see a lot of people do
0:11:30 tops down forecasting. So the last quarter, we had whatever, a million dollars in revenue, 10
0:11:35 million dollars revenue. And then you go, okay, and historically, we’ve grown 50% or 100%. And so
0:11:41 we’re going to model something similar to that for the next year. And so that’s our number.
0:11:45 And that’s got no intelligence built into it whatsoever. What you have to do is double click
0:11:50 on that and go, okay, so we made whatever $10 million last year, how was it made? What was the
0:11:55 makeup of that customer base? Who’s likely to still be here? Who’s going to spend more? Who’s
0:12:00 not going to spend more? Who’s going to completely leave the platform? In marketplaces, you often
0:12:05 get two shots at bottoms up because you typically can build a model based on the supply,
0:12:09 or you can build a model based on the demand. Get an example at eBay. We would look at the
0:12:15 behavior of sellers and we had this many sellers growing this fast, doing this kind of behavior,
0:12:20 and then you just kind of roll them together and come up with a revenue estimate. Then we’d sanity
0:12:26 check it with, we have this many buyers buying this frequently, spending this much and coming onto the
0:12:31 platform at this rate. And then you’d run up that number. And ideally, the two would inform each
0:12:37 other. So one of the best CEOs who I worked with, who I partnered with was George Kurtz from Crowdstrike.
0:12:42 He had an exceptional business. One of the things when we were working together that we came to
0:12:48 realize was his gross margins were a little lower than most other software companies that we were
0:12:54 working with. He actually made the decision in one quarter based on that to try and experiment
0:13:00 where he made gross margin actually be part of the calculus for sales compensation for the reps
0:13:06 in that quarter. And his gross margins over the last three years have actually gone from 35% to 70%.
0:13:12 So a very operational tactical decision that can have a massive impact on the value of the business.
0:13:17 So I wanted to go back to a point, I think, Jeff, that you brought up of having this mental model
0:13:22 of your business and hoping that that matches the financials and how then you have those red flag
0:13:27 moments. And I think a lot of companies right now are having a red flag moment because of a
0:13:32 lot of circumstances very beyond their control. I’d love to hear, what are you telling founders
0:13:37 right now when it comes to how to think about their financials? This is one of the most significant
0:13:41 disruptions I’ve experienced. I’ve had a long enough career that I’ve experienced a bunch of them,
0:13:47 the bubble bursting in 99, 2000, the financial crisis of 2008, 2009, which by the way, we took
0:13:54 OpenTable public in May 2009. So the future isn’t dictated. But a couple of things come to mind.
0:13:59 One is cash is king. The income statement, throw it away. Just look at the cash flow statement.
0:14:03 How much cash do you have? How’s the burn? How are you adding or using cash over time? So
0:14:08 cash becomes completely king. Throw out your forecast because the forecast is now meaningless.
0:14:13 It was based on a bunch of assumptions that no longer hold. So throw the financial print out
0:14:17 and start looking really hard at things like year over year, which typically doesn’t lie.
0:14:23 And then just do tons of sensitivities. And you got to do it decisively. I always like this thought
0:14:31 exercise of how bad could this possibly get? Just let’s take the absolute worst. How bad could it
0:14:37 get? Because I think people tend to do the opposite. They iterate down of like, okay, I’m going to,
0:14:42 we’re down 5%. I’m going to plan down 10%. But if it’s going down 5% per day,
0:14:47 plenty down 10% just met your plans out late in two days. And so I found it helpful both from a
0:14:52 business, prudent cash management perspective, also from a mental perspective. Don’t let this
0:14:57 just continue to erode. And I get more and more depressed every day. Get really depressed one
0:15:02 day, look at reality and then try to change it. Yeah, I agree. So I was a CFO at a company
0:15:07 called Adbride in 2008. And I think that at first we didn’t want to believe that it could get that
0:15:12 bad. But we were an advertising network. And so unless you were Google and even they were impacted
0:15:16 by this, your customers weren’t going to advertise anymore. The marketing departments were decimated.
0:15:21 So there were situations where we were like, some of this is just going to become zero.
0:15:26 Contracts that were signed are now just getting outright canceled. So we made the decision to
0:15:31 cut really deep and as quickly as possible. Because we knew that even if we got it wrong,
0:15:37 at least we could then rebuild the company and do it only once. And then your employees then
0:15:41 are told, hey, we’ve made this big decision. Here’s what we based it on. Here’s our cash
0:15:45 position. Here’s what we’ve sort of expecting in terms of worst case scenario. You bring them
0:15:50 into that circle of trust of what’s happening at the company. But there’s asymmetric potential
0:15:57 issues. If you underestimate how bad it’s going to get and don’t deal with the situation quickly,
0:16:01 the outcome is very well be you lose your company. Yeah, death by a thousand cuts.
0:16:05 Yeah. And if you overreact and it doesn’t end up being as bad as it would have been,
0:16:11 you might have suboptimized your company for some period of time, but it’s alive.
0:16:16 So for me, the mistake is to underestimate the potential versus overestimating.
0:16:20 Yeah, I want to go back to something Jeff said, which was this notion of throwing your forecast
0:16:26 out the window. Very much agree with that on the top line on your revenue. But you have this whole
0:16:30 base of costs that are under your control, those are your operating expenses. And so
0:16:36 we’ve spent a lot of time focused with our companies running sensitivities of, hey, this is
0:16:41 your operating expense budget. And what’s an operating expenses are your salespeople, your
0:16:47 marketing people, your CFO function, your HR function, your engineer’s product. Those are all
0:16:54 people and costs that you have as a base. What happens to that cost base in order to preserve
0:17:00 cash under various scenarios of revenue decline? And so I think that’s the way that you have to
0:17:05 be managing your business on a very, very granular level. And especially since companies,
0:17:10 especially startups, they staff in advance of growth. And so you have to really be honest with
0:17:16 yourself. I want to just also chime in and just say, look, these are all very, very hard decisions.
0:17:22 And I think Caroline and Jeff, especially because you’ve been in the seat of operators
0:17:27 during really, really trying times, you’re probably pretty diagnostic about it. But suffice
0:17:32 to say it’s hard decisions, you know, people’s jobs, decisions not to be taken lightly.
0:17:37 And that’s why there are cases where it is a death by a thousand cuts because people are reluctant
0:17:43 to do those layoffs, make those cuts. And believe me, you don’t sleep when you have to make these
0:17:48 decisions. It’s so tough. So I don’t take that lightly at all. But when you’re running a company,
0:17:53 number one is making sure the company can make it through to the other side. And so you have to
0:17:58 make these really tough decisions. And believe me, I understand how difficult that can be.
0:18:00 But you can’t kick the can down the road on some of these things.
0:18:06 Everyone in the organization knows that the proverbial shit is at the fan. And so if the
0:18:13 leader is unwilling to acknowledge that with the team, that for me creates a crisis of confidence.
0:18:20 I always found it way better just to call it what it is, share it, try to enlist the team. And
0:18:24 do you agree with this version of reality and try to get agreement? And then it’s like, okay,
0:18:29 what do we do? But denial and trying to hide it from your team is a failing strategy completely.
0:18:34 And I understand the human psychology around that because I think people don’t like to give
0:18:39 bad news. And so I think the natural impulse is to hide those things. But these are the moments
0:18:44 where you have to actually be the most transparent. Talk about why you’re doing what you’re doing,
0:18:48 how much cash you’ve got left, how much you want to preserve. And what I find is when you do that,
0:18:52 when you bring everybody into the fold, they all become part of the solution. So they understand
0:18:58 that cash is king, and they’ll figure out ways to be even scrappier than they might have been
0:19:03 otherwise. Jeff, you’ve lived through some crises already. Go back to a time when you were facing
0:19:07 a crisis where things were rapidly changing. You were having to make some of these difficult
0:19:13 decisions. What was a day in a life like then? And what were you doing, especially with regards to
0:19:20 the financials? I got a good one for you. So OpenTable in mid-2008, the board decided it’s
0:19:25 time. Let’s go public. The market wasn’t good. But for a variety of internal reasons for the
0:19:29 company, we decided, okay, we have to, quote unquote, get the puck on the ice. And so we got
0:19:36 ready for the IPO. And we did our bake-off in, I think it was August 2008 and did it like on a
0:19:42 Thursday. And Friday, we informed the six banks whether they got on the offer or not.
0:19:46 We told Lehman on Friday they didn’t get the offer. They went out of business on Saturday.
0:19:51 We told Merrill Lynch, they did get the assignment to take OpenTable public,
0:19:57 and they traded to Bank of America on Sunday. So over that weekend, the number of people dining
0:20:03 in fine dining restaurants in America went down by 15% in one weekend. So we had the org meeting
0:20:07 Monday morning. I walk in, sit down, all the bankers there, all the lawyers there, and this is not
0:20:15 going well. Our business is in free fall. The bank just changed. The consumers terrified. And so
0:20:20 it was pretty clear we could not proceed with the IPO at that point because we couldn’t predict it.
0:20:25 But then we just said, okay, what can we predict? And so we put it on hold for three or four months.
0:20:30 And it turned out that the consumer kept dining in restaurants at 85% of what they had the prior
0:20:34 year. And all of a sudden, we got confident that the business was predictable at that point. And we
0:20:38 restarted the process and went out. And it ended up being a successful offering.
0:20:42 How were you looking at the financials during that time? How did those come into play as you went
0:20:47 through that? We were watching the year-over-year change in reservations of people dining and
0:20:52 reservations made daily, just like, okay, where’s this business going? Because if it kept falling,
0:20:57 one of the scenarios we were concerned by is more and more people would stop eating as they got more
0:21:03 and more nervous about the economy. And we’d go from revenue of X to revenue of like 0.3X. And the
0:21:08 business would have been hugely stressed at revenue of 0.3X. So we were watching that the
0:21:15 one key North Star metric of diners per night, year-over-year, maniacally. And that ended up
0:21:19 giving us the confidence to restart the offering. How does a startup or a founder right now approach
0:21:24 contingency planning around their finances, especially if you’re a high growth startup that’s
0:21:29 been going through cash quickly and been pretty aggressive with your risk taking until now?
0:21:36 For me, you don’t scenario plan constantly. But when a shock hits the system like this shock has
0:21:44 hit this system, hit the world, is you want to plan quickly, even if it’s bluntly. If I was running a
0:21:50 business in this environment, I would get the expected outcome. Maybe it won’t go there quickly,
0:21:55 outcomes are slightly better, but also just what is the worst case? Where could this go? And then
0:22:02 you build your response if each of those comes true. And for me, you put much more time into the
0:22:08 plan, what if, than you do in the building the sensitivity scenarios. One of the less productive
0:22:14 activities is making that sensitivity beautiful and accurate. And it takes two months to come out
0:22:19 with and the company’s out of business. Yeah, just take the bluntest assessment. David and his team
0:22:24 has done this for a few of our internal companies. Yeah, what we did is we basically took every
0:22:30 company’s financials and started with revenue and said, okay, let’s start with your budget.
0:22:36 And then let’s run sensitivity analyses for your revenue. Let’s assume you hit your budget,
0:22:42 that you’re flat, that you don’t grow, that you declined by 25% or that you declined by 50%.
0:22:48 And then we compared that with a company’s operating expense budget. And across all those
0:22:54 different scenarios, if you run your current budget of operating expenses, if you assume you
0:22:59 don’t grow your operating expenses, and then if you assume you decline your operating expenses by
0:23:05 25% or 50%, what is your cash runway in each of those scenarios? And we plug that in for each of
0:23:11 our companies and gave it to them. And I think it’s just a helpful way for them to put some parameters
0:23:17 around, hey, if things get really bad, this is what our runway is. And often it helps them just to
0:23:23 start thinking about, okay, how do I contingency plan in the event of flat revenue? I had never
0:23:27 even thought about that before. If that happens, I only have this much runway. Maybe I should take
0:23:32 action. And another thing that I would say to you, a lot of times companies are building things as the
0:23:37 plane is in the air, and they solve their problems linearly by throwing bodies at it. This is an
0:23:42 opportunity to be able to potentially refactor your code base, to shore up infrastructure,
0:23:48 to build internal tools to make your teams more efficient, so that when you do come out on the
0:23:53 other side, that you are primed and ready to just hit the ground running and run in a million miles
0:23:57 an hour, because you have now built the foundation that you need to be able to really scale your
0:24:02 business, a company called AdBright. We were an ad network. This was before Amazon Web Services was
0:24:07 really a big thing. And so you had to have your own data centers, which means you had to buy
0:24:13 equipment. So we were a very capital intensive business. And what we realized was that we weren’t
0:24:17 going to be able to afford anymore to be constantly replacing our servers, because we just did not
0:24:24 have the money to do it. And our CTO had been playing around with this thing called AWS and
0:24:29 brought it to us and said, one, we can’t afford to upgrade our servers, even though we need to.
0:24:34 And two, this is going to probably in some ways improve our gross margins, because now
0:24:39 we can flex up and down when we need the capacity. So can we give it a try?
0:24:46 This was cloud-based. Anything was still pretty new. This was 2008, I think, AWS launch in 2006.
0:24:50 So we became a data customer of theirs. At the end of the day, when we came out of the crisis,
0:24:56 we were pretty much a cloud-based ad serving company. We deprecated all of our data centers
0:25:01 when we just moved everything to AWS. So what bottom line advice right now are you giving to
0:25:07 founders? One anecdote about the 2008 credit crisis, when housing prices dropped like 30
0:25:11 to 40%, if you were to interview people on the street who owned homes, you asked them, hey,
0:25:15 what do you think the US residential market has done in terms of real estate values?
0:25:20 They would across the board say, oh, it’s down 30 to 40%. And then they would be asked,
0:25:25 all right, what do you think happened to the value of your own home? And they say, oh, nothing,
0:25:28 nothing at all. It’s still fine. It’s not down at all. And it’s like, well, that’s not how averages
0:25:33 actually work. And so no one believes that it’s going to happen to them. But believe me, it is
0:25:39 happening to them. And that is the thing that I want founders to understand. You are not going to
0:25:43 be impacted asymmetrically compared to everybody else. You’re not going to be that outlier more
0:25:49 likely than not. So we’ve had a lot of advice in here on confront reality decisively, plan for
0:25:56 the worst case, scenario plan the worst case. And psychologically, that is pretty darn challenging
0:26:01 on the founder. I mean, I’ve lived it, I understand there. So that brings the point that it’s just
0:26:06 incredibly important for the founder to manage their own psychology. And I think probably the
0:26:10 best resource I’ve read on that is Ben’s book, The Hard Things About Hard Things. You flip from
0:26:17 peacetime to wartime, people are looking for you to lead, and you’ve just got to take the horn.
0:26:23 But I always was most uncomfortable with my personal psyche when things were going great.
0:26:30 I mean, when OpenTable was trading for like 21 times forward revenues, which is an absurd valuation,
0:26:36 I was jumping out of my skin. But once you confront the fact that, okay, we’re in one of those
0:26:42 moments and I need to lead out of it, I actually found it after an absolutely miserable X hours.
0:26:48 I found it motivating. We can get over this, let’s show them what we can do. For me, the CEO and
0:26:54 founder needs to confront reality quickly and then they need to lead. And you can lead your company
0:26:58 through these things and get to the other side, then things will get better again. But the biggest
0:27:03 thing is manage your psychology actively. I just want to thank you, David. Thank you, Jeff. Thank
0:27:07 you, Caroline, for joining us on the podcast today. Thank you. Thank you.

0:00:04 The content here is for informational purposes only should not be taken as legal business
0:00:10 tax or investment advice or be used to evaluate any investment or security and is not directed
0:00:14 at any investors or potential investors in any A16Z fund.
0:00:17 For more details, please see a16z.com/disclosures.
0:00:20 Hi, and welcome to the A16Z podcast.
0:00:22 I’m Lauren Murrow.
0:00:26 Since social distancing measures were first put in place, time spent gaming has gone up
0:00:28 75% during peak hours.
0:00:34 In this hallway-style conversation, A16Z partner John Lai joins me to talk about how the stay-at-home
0:00:39 movement is fueling gaming, what we’re playing, and why live streaming is having its moment.
0:00:44 Playtime in general is up massively across every category of gaming.
0:00:49 PC games erupt, steam, the world’s largest marketplace for digital PC games.
0:00:54 Steam has been around for 20 years and it’s never seen this level of user activity.
0:00:59 Average concurrent users online typically hover around 15 million.
0:01:04 It hit an all-time record high this past Saturday, around 22 million concurrent users online.
0:01:07 So that’s a spike of almost 50%.
0:01:09 Console games are up massively as well.
0:01:10 What is driving this spike?
0:01:15 Obviously, we’re all at home more, but what other factors are coming into play?
0:01:20 So I think what’s special about games versus other types of media is that gaming is a
0:01:24 massive activity that a set of friends can engage in at the same time.
0:01:30 There are moments of levity, competition, there are emotional highs and lows over the
0:01:32 course of a typical gaming session.
0:01:36 These are bonding moments for people and they create really deep social relationships.
0:01:40 It seems like smart game studios are also putting measures into place to encourage more
0:01:41 at-home play.
0:01:46 I know Pokemon Go changed its mechanics a bit to make it easier for people to play
0:01:47 from home.
0:01:50 It changed its events to make it easier for people to play alone.
0:01:51 Absolutely.
0:01:54 Blizzard of World of Warcraft, which is one of the largest and longest-running MMOs of
0:01:59 all time, launched a whole series of benefits during quarantine so that if you’re playing
0:02:05 right now, you actually get double experience as a way of incentivizing people to continue
0:02:06 playing the game.
0:02:09 What kinds of games are popular amid this crisis?
0:02:10 Are there particular titles?
0:02:15 One game that I’ll highlight as an example is a fairly recent one, Call of Duty Warzone,
0:02:19 which is a new battle royale game from Activision that just launched March 10th.
0:02:24 It ended up being one of the most successful and fastest growing PC console game launches
0:02:25 in history.
0:02:30 Over the course of three days, it reached 15 million players, and I think it reached
0:02:32 30 million players after two weeks.
0:02:37 I saw Infinity Ward had 6 million players in its first 24 hours.
0:02:41 I think a lot of games that are launching this month are seeing major spikes.
0:02:48 So Xbox Live, which is the multiplayer service for Xbox consoles, has had several outages
0:02:52 twice over the last week as more users logged on than the infrastructure can handle.
0:02:56 And Microsoft has some of the world’s best cloud infrastructure, so if they’re having
0:02:58 trouble with it, it’s got to be a lot of people logging on.
0:03:03 I’ve read of developers experimenting with ways to include a higher player count and
0:03:08 larger squads with all these new users, but that’s also potentially risky.
0:03:12 As you mentioned, Nintendo, Xbox Live, and Discord have all experienced outages within
0:03:13 the last month.
0:03:17 How are game developers responding to this massive influx of players?
0:03:19 Yeah, it’s a double-wed sword.
0:03:24 On one hand, you have unprecedented numbers of users coming to your servers, and you want
0:03:26 to be able to support them.
0:03:31 Increasing the number of users currently in a session is one way to try to minimize the
0:03:37 sheer number of servers or shards that you need to spin up for a game, but at the same
0:03:39 time that comes with its own technical challenges.
0:03:42 And so I think everyone’s just struggling to keep the lights on.
0:03:47 Discord announced that they had increased server capacity by 20% to keep up with demand,
0:03:52 and promptly, right after making that announcement, they had server outages themselves as well.
0:03:55 This isn’t something that’s just specific to games.
0:04:00 Netflix, for example, just cap bit rates over in Europe, so in an effort to sort of keep
0:04:06 bandwidth down, they’re no longer streaming in 4K or HDTV, and it’s clearly an attempt
0:04:10 to contain costs and continue maintaining the quality of the service in the face of
0:04:11 a lot of demand.
0:04:15 Is there anything surprising that you’ve noticed in the types of games you’re seeing played
0:04:18 more amid the coronavirus quarantine?
0:04:25 Online multiplayer games are the ones that are seen the most obvious and largest growth,
0:04:29 which makes sense because they’re fundamentally social games that you play with other people.
0:04:35 I actually think that VR, virtual reality, might be seen as surge in popularity.
0:04:36 How so?
0:04:41 Well, the whole notion of VR is predicated on enabling people to escape the real world
0:04:44 to a virtual reality, right?
0:04:48 And even prior to COVID, there were early indicators that in-home consumer VR may be
0:04:53 turning the corner, so the Oculus Quest was estimated to have sold well over a million
0:04:56 units before it went in backorder.
0:05:01 The Valve Index, which is perhaps the most powerful headset to date, sold out in minutes
0:05:03 upon initial release.
0:05:07 So VR headsets seem to have finally reached a price point and a hardware quality that
0:05:08 has mass market appeal.
0:05:13 And at the same time, you have exclusive AAA games coming to VR for the first time, titles
0:05:21 like Half-Life Alyx, and Half-Life is arguably Valve’s biggest and most exciting IP, a sci-fi
0:05:24 franchise that put them on a map, initially.
0:05:29 It’s famous for ending the franchise essentially on a cliffhanger, and the resolution for the
0:05:35 story is this Half-Life Alyx game, and it’s a VR exclusive, so you can only find out what
0:05:39 happens if you buy a VR headset and you play in VR.
0:05:44 Educational games are actually seeing tremendous growth as well these days.
0:05:47 Teachers in schools are also holding online classes through Discord.
0:05:49 I think that’s an interesting use case.
0:05:55 So rather than platforms like Zoom, some are turning to apps that were traditionally gaming
0:05:57 platforms like Discord or Twitch.
0:06:02 Yeah, I think they’re picking the platform that their audience is already on.
0:06:07 So if you’re an instructor and you’re trying to get kids to come online in order to listen
0:06:13 to AP buyer or whatever subject matter you’re teaching, it’s going to be easier to convince
0:06:17 them to come online if you pick Discord, because chances are they already use Discord to play
0:06:18 their favorite games.
0:06:23 So Discord actually just made a number of moves specifically to help educators come on
0:06:24 the platform.
0:06:29 It’s the user limit on screen change from 10 to 50 users, so you can accommodate larger
0:06:30 class sizes.
0:06:35 And in this case, the actual friction is on teaching the instructors, the teachers themselves
0:06:36 how to use Discord.
0:06:42 One thing in these gaming platforms is that as we’ve seen with video conferencing, the
0:06:45 natural rhythm of the conversation is off.
0:06:49 It’s difficult to respond without interrupting, sometimes it’s difficult to interject.
0:06:57 So when it comes to learning how to have a live interactive conversation online, ironically
0:07:03 I think gamers have received way more training in that area than almost any other demographic.
0:07:09 Because the very nature of playing a game and chatting with someone over Discord or
0:07:14 interacting with a livestream, it’s basically a constant act of juggling foreground versus
0:07:15 background activity.
0:07:19 And so being able to contact switch from okay, I’m listening to the lecture, to now I have
0:07:22 a question and we’re going to talk about this question.
0:07:26 This is something that gamers and then livestreamers in particular have a lot of experience with.
0:07:31 And I think it’s interesting to think about how this might become an increasingly more
0:07:38 critical skill in society as more teams and general folks start working and learning remotely
0:07:40 versus in person traditionally.
0:07:46 So you’re saying gamers may actually be prepared for this future whereas perhaps most of us
0:07:49 who are not gamers may have a steeper learning curve?
0:07:50 That’s right.
0:07:53 John, I want to talk about who is playing.
0:07:57 I think a lot of people have the conception that because schools are canceled in many
0:08:03 places, a lot of it is teens and kids playing more video games.
0:08:09 The average age of a gamer on League of Legends, for example, actually skews fairly old.
0:08:14 I think it’s something in the 20s or the 30s, over time it’s crept up.
0:08:19 And so you have a mix of adults, you have a lot of kids that are definitely playing since
0:08:20 they’re out of school.
0:08:24 And I think one of the neat things is that you have families that are coming together
0:08:28 and playing games potentially for the first time as a sort of quarantine.
0:08:35 Dungeons and Dragons, which is a tabletop fantasy RPG, has actually seen massive growth
0:08:37 as well over the course of quarantine.
0:08:42 In these turbulent times you end up having a lot of folks that are playing D&D together
0:08:44 over Zoom and House Party.
0:08:49 Those broadcast in the live streaming site Twitch is up 34% just in the last week, if
0:08:50 you’re not familiar.
0:08:55 It’s a tabletop game where a group of people role play a story and that story is often
0:08:58 created just by another player of the game.
0:08:59 It’s a giant improv party, essentially.
0:09:04 Yeah, I think it’s important to remember that there’s this whole new audience that is rediscovering
0:09:06 gaming as adults.
0:09:07 Absolutely.
0:09:11 A lot of people are coming back to games as a result of being housebound and they’re
0:09:16 discovering that even though they may not have a console or a gaming PC, they actually
0:09:18 already have an awesome gaming device on them.
0:09:23 PUBG Mobile, which is the mobile version of a player unknown battlegrounds reported increased
0:09:28 revenue of over 50% just in the last week compared to the prior week.
0:09:33 One of the largest mobile games in the world, Tencent’s Honor of Kings grew from an average
0:09:39 baseline of 60 million daily active users to over 100 million plus in February at the
0:09:44 height of quarantine in China, and that’s 60% plus growth, which is pretty amazing given
0:09:46 how large that game was to begin with.
0:09:50 Essentially, you have a lot of new gamers rediscovering that they have a gaming device
0:09:52 and perform at their smartphone.
0:09:55 And some of these newcomers may be traditional sports fans.
0:09:59 As in real life games and sporting events have been canceled, some of these leagues and
0:10:02 teams have been moving online to a digital format.
0:10:07 So about a week ago, the NBA turned one of their canceled games, I think it was Phoenix
0:10:09 versus the Dallas Mavericks.
0:10:14 They took that game and they actually turned it into an NBA 2K game, which is the video
0:10:20 game equivalent of the real NBA, and it was livestreamed on Twitch for everyone to watch.
0:10:26 It’s very trippy for me when I see an NBA star play their virtual persona in a video
0:10:27 game.
0:10:32 Well, and as NBA players have been put in isolation, I think many of them have been
0:10:33 turning to gaming.
0:10:37 There was a Call of Duty tournament for Miami Heat players that was also broadcast on Twitch.
0:10:44 And NASCAR just replaced the canceled races with the first ever eNASCAR series where you
0:10:47 were essentially piloting virtual race cars.
0:10:51 And they brought back a lot of recent legends like Dale Earnhardt Jr. to drive those race
0:10:52 cars.
0:10:57 So professional race car drivers are competing against each other in racing simulation software.
0:10:58 That’s right.
0:11:03 So could eSports be a gateway to turn non-gamers into gamers?
0:11:09 It’s a bit of a hybrid between traditional video games and that live, crowd-driven competitive
0:11:10 event.
0:11:11 It remains to be seen.
0:11:17 I think, yes, from the perspective that you’re having an audience that may have never actually
0:11:24 watched NBA 2K or FIFA, for example, any of these sports video games that are now exposed
0:11:27 to that and might actually think it’s pretty cool.
0:11:32 And it’ll be interesting how many of these NBA players, one, how many of them can build
0:11:38 large eSports followings and then, two, if their eSports followings actually end up being
0:11:42 larger than their real-life following, I think that would be a real success story.
0:11:44 It’s a brave new world.
0:11:46 Let’s turn to live streaming.
0:11:47 Absolutely.
0:11:52 So the analytics site, Sully Nome, actually just released a couple of data insights.
0:11:56 The high-level headline is that Twitch is essentially having the biggest month of its
0:11:57 history.
0:12:02 Livecast hours also grew by 35% over the last week compared to the average of the prior
0:12:03 three weeks.
0:12:10 And Sunday ended up being an all-time record breaker, where 47.7 million hours watched.
0:12:13 Why this rise in live streaming?
0:12:17 Part of that could be due to the fact that you have people that are checking out live
0:12:19 streaming for the first time.
0:12:26 Another interesting nugget was that downloads of the Twitch app increased by about 30% just
0:12:32 in the US alone between the weeks of March 8th and March 15th, so you have a lot of
0:12:34 people that are checking it out for the first time.
0:12:40 I think a second thing is that live streaming is unique as a media format and that it combines
0:12:45 the reach of a public broadcast with the intimacy of a small group community.
0:12:51 And what I mean by that is essentially, as a live streamer, you can reach hundreds of
0:12:53 millions of people with a single live stream.
0:12:59 So it is a public broadcast media just like TV or the radio.
0:13:03 But because of the fact that it’s interactive, your viewers can type at you and you can have
0:13:07 a conversation with them and you can adapt what you’re doing in real time to what your
0:13:09 viewers demand.
0:13:11 It feels like a smaller group conversation.
0:13:14 And you can monetize in real time, right?
0:13:15 That’s right.
0:13:18 People tip in real time if you’re doing something that’s very popular, that if you’ve answered
0:13:24 a request, people can subscribe to your channel and the subscriptions cost money anywhere from
0:13:26 a couple of dollars that way more.
0:13:31 So it’s interesting as both an engagement and a monetization model for influencers these
0:13:32 days.
0:13:39 So it’s kind of a hybrid of YouTube and TikTok in that you can amass this online following,
0:13:42 you can be streaming live, but you can also be monetizing instantly.
0:13:43 That’s right.
0:13:48 On YouTube and TikTok, for example, you produce content and then you upload it in any
0:13:51 way that you have to wait and see what happens and you’re not actually getting that much
0:13:53 in terms of real time feedback.
0:13:59 TikTok is slightly more real time than YouTube, simply because the videos are shorter and
0:14:03 people can like and comment very quickly after you upload something.
0:14:07 But live streaming platforms are unique in the sense that you are literally performing
0:14:12 in real time for a live audience and you’re getting the feedback just as if you’re a stage
0:14:17 performer in real life in real time, given either clapping or throwing tomatoes at you,
0:14:19 or digital tomatoes.
0:14:20 That’s right.
0:14:24 And I think that’s one of the things that makes live streaming work so well right now
0:14:26 in COVID times.
0:14:31 It’s because people are actually able to get a sense of community online through live
0:14:35 streaming that may otherwise be hard to find in the real world because we can’t get together
0:14:37 in large groups anymore, right?
0:14:41 Like you can’t go to church, you can’t go to school, you’re not at work.
0:14:45 So a lot of the communities that people are ordinarily members of I think have sort of
0:14:50 fallen by the wayside and Twitch has been able to provide that sense of community for
0:14:51 a lot of its viewers.
0:14:58 As opposed to passively binging Netflix, people want this more interactive way of being social
0:15:00 with their friends and family.
0:15:04 I mean, speaking of relationships, it’s a bit of a personal story, but video games actually
0:15:08 saved my marriage and totally not getting here.
0:15:10 How so?
0:15:15 So when my wife Jen and I first started dating, we were actually long distance for the first
0:15:16 year of our relationship.
0:15:21 I was in San Francisco, she was in New York, so we actually met at a New York City to get
0:15:27 together and then I had to fly out literally two days from afterwards and it was really
0:15:28 tough.
0:15:31 We didn’t know each other that well, but we started playing an online game called League
0:15:35 of Legends together and that completely saved the relationship.
0:15:39 When we didn’t feel like talking about serious things, we could just play the game and there
0:15:45 were enough sort of highs and lows and moments of tension and drama that we also got to know
0:15:47 each other better as we played together.
0:15:48 I love that story.
0:15:51 Yeah, so who says you can’t find love in video games, right?
0:15:53 So you’ve been married 10 years now.
0:15:56 Are you still playing League of Legends together?
0:15:57 We still are.
0:16:02 It’s one of the mainstays of our relationship actually, so a light-hearted way to spend time
0:16:06 and I imagine that’s what a lot of people these days are doing in quarantine as well.
0:16:11 You know, if you’re in a small apartment or a house with members of a larger extended
0:16:16 family, there’s only some sort of conversation you can have before fights start breaking
0:16:22 out, so maybe you break out the Xbox, play some mobile games, play some party games and
0:16:26 it helps generally improve the quality of life in the house.
0:16:29 I think there’s definitely a social dynamic at play.
0:16:35 A lot of people aren’t necessarily comfortable FaceTiming or video chatting and seeing their
0:16:38 own face reflected as they talk to family members.
0:16:41 So I think gaming provides this distraction.
0:16:45 You’re doing something else while you’re connecting with your family or friends.
0:16:50 Yeah, I think one of the best ways I’ve heard it described by a live streamer is actually
0:16:57 that games can switch back and forth between foreground and background activity, so you’re
0:17:01 not really thinking too hard about the game, but you’re actively conversing and you might
0:17:06 actually be talking about something that’s like very serious, but then you can just switch
0:17:09 the game back into the foreground and you both concentrate on the activity.
0:17:15 And so it provides activity to fill in the gaps that are very natural in conversations
0:17:19 and it doesn’t feel like just long periods of silence if you don’t have anything to say
0:17:20 to each other.
0:17:23 Yeah, I think that’s something we’re all familiar with.
0:17:28 The point is social distancing, quarantine, it’s lonely and I think a lot of people are
0:17:31 rediscovering gaming as a way to connect with others.
0:17:36 So after we weather this crisis, what will this mean for the games industry?
0:17:37 What is the bigger picture?
0:17:43 The bigger picture here is that gaming is unique as a media type and that it’s real
0:17:45 time and it’s fundamentally social.
0:17:50 When you’re playing a game, you’re partaking in an immersive activity with someone else.
0:17:54 And so I think that’s one of the reasons why gaming has seen such explosive growth since
0:17:56 the start of coronavirus.
0:18:01 And so I think games and live streaming are offering a lot of the social connections that
0:18:05 people are missing as they’re staying at home these days and I think that will only
0:18:06 continue over time.
0:18:12 So once this crisis is over, do you expect these new gamers to stick around?
0:18:13 I hope so.
0:18:17 It’s easier than ever to get into games today with just so many different platforms that
0:18:18 you can play on.
0:18:22 If you have a console or a gaming PC, that’s great but you don’t need one.
0:18:27 You can also play phenomenal, triple-way quality games in your mobile phones these days.
0:18:32 And so the barrier is the entry for people coming back in the game to discovering games
0:18:34 for the first time is lower than ever.
0:18:35 Great.
0:18:37 Well, John, thank you so much for joining us on the A16Z podcast.
0:18:38 It’s been a pleasure.
0:18:39 Thanks for taking the time.