Mastering modern entrepreneurship | Building lean, starting young, and studying customers | Steve Blank (Author of The Four Steps to the Epiphany)

Brett: so Why do you think there aren't more successful startups?

Steve: we still kind of get it wrong, uh, because of the, the makeup of entrepreneurs and the nature of capitalism and business. I mean, world class entrepreneurs want to create things and, and, even in my career, it was, you know, the tendency was to fire ready aim.

you know, the whole lean methodology I built was to kind of constrain myself that says, well, even though you believe, All you have is a series of untested hypotheses, and that's really, really hard to kind of integrate with the passion of the entrepreneur. 

and then there's probably a, a limited pool, but though I'm not sure we've tapped into it worldwide, a limited pool of people who truly can see over the horizon, who understand that integration of technology and art and the possible, and, and who know it's just the beginning of a conversation.

all the things we know about great entrepreneurs, they're relentless. They're irrational. They're passionate. they see things that other people don't. And that means that, you know, all of them think they're visionaries. And we know the data says 98 percent of them are hallucinating.

you know, so far, the the data says the, the world class ones, at least the ones that make it in Silicon Valley and the ones that get funded are completely anti social and probably come from usually dysfunctional families. I mean, it's not a requirement, but it seems to fit everybody from Ellison to, to certainly Musk to.

You know, the rest, where, in fact, the fact that they don't care about people, and work, you know, at irrational hours seems to be a competitive advantage. In fact, I, I remind my students that for those of you come from dysfunctional families, you actually do have first time advantage than any other place or time in your life, because survivors of dysfunctional families have figured out how to survive in not only chaos and uncertainty, but actually shut down everything except that necessary for survival and that ability to kind of do that, which, uh.

Makes you live longer in a dysfunctional household is also the criteria about what makes a great officers in a war zone, you know, if you hesitate and you can't figure out what's important, then others will figure that out for you. And in those cases, it's a life threat, you know, in my case, when I came to Silicon Valley in, uh, in the 70s, God, that was a long time ago.

I had just come from a war zone in Southeast Asia. And at least it wasn't me, but the pilots on the planes I was fixing, some of them didn't come back. and so when I got to Silicon Valley and moved in with a couple of housemates, thinking about joining my first startup, I still remember, I mean, a half a century ago, one of them saying, don't you understand how risky startups are?

You could lose your job. And I just looked at them. I mean, it was even hard to compute until I sputtered out something. Well, I just came from a place where risk meant you could lose your life. And what I truly did not understand is that for the next 20 years of my entrepreneurship career, that gave me an unfair advantage, I think, in that while risk was, is, you know, just wired into the nature of a new venture, I didn't care because I realized it was almost impossible to die in a startup.

I mean, you really had to work hard at it in the United States, particularly in California, you couldn't freeze to death, you know, you couldn't go hungry, you couldn't whatever, there was a bottom, there was a floor that wouldn't let you die. And if you didn't have family or other encumbrances at the time, then it was just an open field.

And it was to me, I did eight of those. And never thought once that like, this is a risky thing. I always thought the risk was on the investors. I couldn't believe people were writing me like checks to do X and Y. And, and something I, in fact, every one of them, I knew nothing about when I started, um. So it was just a wonderful opportunity.

Brett: if you look at a lot of the outlier founders, I would say it's something that we've talked about. They kind of overexpress sort of the traits of having some sort of challenge in childhood, oftentimes in some sort of dysfunction.

You started to talk a little bit about this, but I'm curious what's your theory as to how that connects with kind of maybe what's required to do something outlier.

Steve: Yeah, you know, when I came up with this theory, one of my mentors was a venture capitalist named Catherine Gould, who unfortunately passed too early. You know, when I came up with this idea, next time I had coffee with Catherine, I said, Catherine, look what I discovered, and I think there's a pattern here.

And she looked at me like the dog just talked. She said, Steve. Why do you think I invested in you? She said all my founders come from dysfunctional families. You guys, and back then it was guys, have something to prove. You have a chip on your shoulder, and you just will work irrationally hard to make it happen.

And when shit happens, nothing seems to faze you guys. And you drive your people at the same intensity that you work at and that Venn diagram of intensity, ability to operate in chaos and uncertainty. That is, I still remember multiple times. You know, the company's melting down. My co founder quits. The toilet stopped up and I'm the facilities manager.

My largest customer literally that day decided not to buy, you know, everybody's panicking on the exec staff. And I go, another day, another dollar. Okay, what are we doing next? And you kind of tease out, you know, what do you do, et cetera. And, and that's the job of a leader. and if you were trained for that, again, if you've come out of the military, you're kind of trained for that.

If you survived in a war zone, but most people come out of a dysfunctional family where every day you didn't know if, you know, your parent was going to be crazy and throwing shit at you, or like there was dinner on the table. I mean, I remember multiple days. I didn't know if I was going to eat or if, you know, I was going to be locked out of the house or whatever.

And it's just another day. Again, in hindsight, that was another preparation. So I had the, I had the war zone experience and the dysfunctional family experience personally. And it took me a couple of decades to realize. That's probably the cruelest, but most effective training ground to make, um, high functioning entrepreneurs and probably ill functioning human beings.

and by ill functioning, what I mean by that is that that's great for founders in the early stage where they operate most efficiently in chaos and uncertainty. But here's the, here's the problem is when the company finds product market fit, and you need to build repeatability and scalability in the company.

The same founders throw organizational hand grenades into their own organization and culture, trying to keep that chaos going on inside their company, because without that, they feel incredibly uncomfortable, in, in normal, repeatable processes, and that's why you see a lot of those great founders actually not being able to scale or in fact, get removed by investors because they are creating so much chaos and uncertainty.

Um, and, and in fact, what they really need is a good therapist. Unfortunately, it makes them, if they get good therapy, it makes them an ineffective founder for their next one because you beat that, that intensity out of them. 

Brett: for the founders that end up running their businesses at scale, do you think it's somewhat random luck in the sense of the organization can actually handle those peculiarities?

Or do you think they tend to go into different 

phases and maybe mature in some 

way?

Steve: no, I don't think they mature. I think they, uh, discover an organizational trick. One of my best friends, John Rubenstein, was, uh, uh, jobs as, uh, head of hardware for, you know, both at next and then at, uh, the reinvention of Apple. And John, I think was representative of Steve Jobs grow, grown up jobs was still insane, but, but the second coming of Steve Jobs.

Had an organizational level of world class executors, Tim Cook, John Rubenstein, Avi, et cetera, were all people who could take that craziness and filter it down to an organization that provided a level of stability. They were an impedance match. You know, between crazy whatever to competent management. And that's what Jobs lacked in his first incarnation at Apple.

There was no filter. There was no level of, operational excellence between his mouth and then the direct people he was trying to manage.

Brett: Do you think that's the pattern across all of these founders that tend to transition into excellent multi decade CEOs?

Steve: I think that's one pattern. I think some others is they do get healthier and they, you know, kind of understand that the, that the demons were driving them may not be effective. You know, at scale, again, some smart V. C. Some days or a couple of them will fund some sociology studies that might actually explain the pattern.

I think a bunch of people have some theories. Mine would be there's a there's a set of behaviors. One is that, operational level that goes underneath them. The other is uh they grow into maturity. And the other is just plain luck that, you know, they hire a great COO by accident or the board you know enforces some adult leadership between them, you know, we use that phrase adult leadership, but we're actually talking about, you know, a filter between, you know, that great visionary founder who you need in a business where technology is changing, you know, the mistake that people used to make was when we replaced the founder in the 20th century to take a company public, we forgot that that innovation cycle might be every, you know, 2 to 3 years and you could get liquidity for the investors, but then the company was dead because the innovation died because you just were on an execution track of the first product.

So we're smart enough now to want to keep those founders in the cycle. for multiple cycles of innovation, but as the company scales, you need to figure out whether your founder is scaling personally, or you're building an organization underneath them 

Brett: Going back to sort of what we were talking about a few minutes ago, do you have any ideas or interventions? If. If in the US, we wanted to 10 X, the number of successful companies that are started in a given year? What would need to happen? Maybe we could create more dysfunctional families, but I think we're probably at maximal capacity there.

Steve: you know, after I was an entrepreneur for 2 decades, I just realized I've been an educator now for even a longer amount of time, which is frightening on multiple levels. But but here's what I. I think I discovered, and I'm going to use an analogy for about 30 seconds to make the point. You know, in the middle ages, we discovered that to make great artists, you have them apprentice with other great artists and they would work in someone's studio and they would learn, you know, some techniques, et cetera.

And so, but people had to self select that they want to be artists. But in the 19th century, and certainly in the 20th century, we realized we can actually find artists earlier, and a lot more of them, if we did something that had never occurred to anybody before. And that is teach art appreciation all the way from kindergarten on up.

And what I mean by that is, we taught kids how to do painting. We taught them how to write stories. We taught them how to, you know, do little sculptures and put on plays, etc. And, or draw little cartoons. And most of us, including me, went, Well, I have no skill in this at all. But what's really interesting is, you know, some fraction of kids said, Really?

You can make a career out of writing? Wow! I want to do that. Or, wait a minute. You mean people will actually buy my paintings? And by the time they graduate high school, we have a cadre of kind of self identified artists. Because we decided to do this at the earliest possible age. We teach art appreciation.

Now, just let's take back your question and say, how come we don't have the equivalent K-12 in entrepreneurial appreciation? That is, it's not just how do I set up a lemonade stand it's how do I find product market fit as a you know 10 year old? You could, these concepts are not very hard and could be adapted and adopted to the equivalent of art appreciation classes.

And so I believe if you want to, create the biggest possible pool, I would figure out how to actually get this instead of it just happens like it does now. Is there some, you know, somebody who likes to code or create images or do something else early on? How do we actually make this a, uh, kind of a theme all the way through, uh, uh, K through 12 and, and into colleges?

Brett: it sort of makes me think about, Sports, right? If you didn't have sports when you were three and five and seven, how many few professional athletes would there be?

Steve: Right. I picked art because sports is not one of the colleges I, I would have

Brett: I know, by the way, I know nothing about sports. I play no 

Steve: sports 

right. But, 

Brett: but it just came to mind.

Steve: Yes, no, no. So, so I think, think about that. The country is an, the whole educational institution has decided that both sports and arts are something that's important to embed in our curriculum in the 20th century.

And we've not figured out that innovation and entrepreneurship, and it might just be that a we've not come up with a a curriculum to do so. It's not that hard. Probably a month's worth of work. I'd be happy to run that session. We could come up with some of those. And I've known some, some folks who have done their own and then, you know, a program to figure out because remember, you don't have infinite time in school days.

So now if I'm going to insert this, what am I going to remove? Let's take a country in Africa, I wanted to run a science experiment, it wouldn't take more than, I don't know, a couple million bucks to actually get some country to decide we want to run this experiment.

We're going to remove X from our curriculum and we're going to insert the entrepreneurship appreciation in a K 12 curriculum and stand back 5 years and see what we get. that would be my take on how to improve the pool. Now, that said, okay, the question is how many Michelangelos and Da Vinci's would actually have emerged in, if you had done this versus the ones that emerged themselves?

How many Steve Jobs and Elon Musk would come out of this that wouldn't have come out of this before? Not just, you know, the singles and doubles, but the, you know, home runs that like, you know, went 12 miles. I'm not sure, but I will guarantee you almost that we'll certainly, this process would certainly get more single doubles and triples.

I'm not sure if it would increase the outliers or not, but it would certainly create an entrepreneurial culture and nation in a way that we just don't have. So that would be my answer to your question.

Brett: there's also this interesting question. I think if you go back and look at why someone chose to start a company that ended up being consequential in some way. There's a lot of randomness. I'm not sure it was just, you know, it was preordained when they, you know, came out of their mother.

I think there are often these little interventions, these little nudges in different directions. This person that nudged somebody to get into computer science when they were going into college or

sort of all of these little events or somebody that raiseed someone's aspirations and pushed them in a different direction.

Steve: so I want to go back to connecting what you just said with, you know, this, uh. Entrepreneurial education track, I didn't realize that my kind of connection to this was my brother in law. My sister was 12 years older than me, and he was like, 15 years older than her. So just a, you know, age, whatever his brother in law, but, had had a job as a researcher in a place called IBM Yorktown.

And so when I was a teenager, I went up there and couldn't believe and I grew up in a very blue collar family where people were grocery clerks or carpenters or plumbers and couldn't believe there was a job that you sat in a table. And there was again, it was the 60s had a computer terminal, which was just unheard of.

And I didn't realize that that was an influence. And then when I found out how much money he made, it was like, well, that might be a potential career. And again, I didn't go right into that. But in hindsight, that was an influence. Just imagine if that was the influence you had for 10 years, you saw people having those jobs, et cetera, we weren't making it a vocational track, much like we don't make art or sports, your analogy a vocational track, but you're getting exposure to those as opportunities, I think you would increase the kind of the, the attack surface, if we could describe it that way of, of exposing people to, oh, that's a career you could have, or here's another version of the career, et cetera.

so, yes, I agree with you. I just think giving people more opportunities to see that these are possible options in your career. You know, the other piece that we don't talk about enough about for entrepreneurs, we talk about resilience and tenacity and agility, et cetera. We don't talk about curiosity, I did in my eight startups, there's only two that I did within the same industry, which were semiconductors.

And I would still tell you, I don't know much about them, but, um, but I was immensely curious in a lot of things I still am, you know, everything from particle physics to, you know, to life sciences, et cetera. While, you can't force someone to be curious. You can, again, teach them the benefits of being curious and, and again, increasing the opportunity for people to look at different markets and different segments.

you know, I've invested in things from life sciences to material science to computer science to whatever, and I could, you know, by now have a pretty interesting dialogue in each one of them because I'm, I'm honestly interested in learning new things. You could possibly teach people the benefits of learning new things, which also would increase that area.

I have found that things I've learned in, you know, in therapeutics actually have some crossover interest in material science of all things. Things I learned about physics, who would have known that, you know, knowing about free electron lasers and synchrotrons might be useful in the next generation of semiconductor manufacturing.

Brett: What do you make of instincts in this process to kind of get to product market fit or build something out of nothing? What's interesting about so much of your work, sort of that I've consumed over the years is a lot of it is organized around the idea of here is a set of activities or behaviors, that if you go through, have the chance to increase the chance you kind of build something that can compound over time or get to product market fit.

And on the other hand, I'm curious for whatever the source of sort of great instincts, what do you sort of make of them and how they fit into sort of this, um, equation of building outlier companies.

Steve: Yeah, you know, it's very funny because, um, I would have been the last person on earth. My friends who knew me as an entrepreneur to ever point to as the guy who would come up with any process at all, because I truly was the fire ready aim. But in hindsight, I was doing the intersection of what you just described, though I now describe it as great entrepreneurs who call it instinct.

There is no such thing, meaning what you're actually doing is, at least I believe, let me be clear, I believe you're consciously or unconsciously ingesting a whole ton of data and running in the background the equivalent of a neural net. That just hasn't been connected to your mouth and, and, and conscious yet, but that's going on as a background activity all the time.

I don't think you'd have much instinct or Steve Jobs would've have had much instinct locked up in a room, you know, with no input. So the more stuff you, kind of get in, some people actually have great neural nets that do world class pattern recognition. I think that is an innate skill. Now, when you have that, what I'll contend is while you think you have a vision, you now actually have a series of untested hypotheses, and that's the connection between lean.

I invented customer discovery for me, which was to inform my vision, not to create a goddamn focus group. We'll get out and talk to a lot of people because I wanted to get all their input. No, I wanted to inform that like vision I had that insight to figure out whether it was a hallucination or fact. And I wanted to create a methodology for doing that

as a series of steps rather than what I used to do is, which says, okay, we just raised a pile of money. Let's go build that. Perhaps after screwing that up enough was, well, let's actually test that and see whether anybody else like shared that vision. Or if they didn't, is it because I was prescient and can see over the horizon that it's a new market.

Or was I just wrong and missed something? 

Brett: Say more about this because I think it's probably a misunderstood part of a lot of your 

ideas 

Steve: Yeah so the key idea is, the whole notion of the Lean Startup, at least from one of its creators, is, no, it's to inform your vision. And if you don't have a vision, Don't start a company. You know, it's not like a set of spreadsheets. You want to get out of the building, build MVPs, et cetera, to validate your vision of what you think the world is.

And if you don't have a profound belief, then you're just going to be running to, then... Look, lean is not an excuse for attention deficit disorder. Though we seem to operate that way in a number of cases. If you don't have a profound belief that says, I think the world is going to go this way. I think people are going to want to need X. And either it's an existing market, so I could test it, they want something 10 percent faster, or they'll buy something if I, I just have a niche product for them, or I'm going to create something in a new market where it never existed before. And by the way, the way you test each one of those are quite different.

In an existing market, you could put something in front of someone or describe what it is, and we'd say it's half the price and they'll go, yeah, or go no, or whatever. In a new market, you could put the same thing in front of them and say half the price and they go of what. So you gotta, you gotta make sure which one you're testing, right?

but if you don't have anything to test it against, if you don't have a belief you could write down, we believe X or Y, we believe this is the problem we're solving, or we believe this is the need we're fulfilling. You have no idea what hypothesis you're testing, and therefore you're just throwing MVPs out the door without going, well, wait a minute, this was, and I use this, the phrase profound beliefs loosely held.

That's what you're testing. That is, the loosely held part is, well, that's why I'll do a pivot or I'll be agile. But I'm not going to do it against nothing.

Brett: Say more about doing this work in new markets and what that actually should look like.

Steve: Well, new markets is that, you know, that famous, I think, apocryphal Steve Jobs quote where, you know, if Henry Ford like asked people what they would have wanted, it would have been a horse with six legs. Well, yeah, you know, that was a new market. So in an existing market, as I said, you could go ask people, do you want this product?

It looks like this one, but it's better. It fits in your pocket. It's something else. By the way, the test of a new market is you ask people, would you like this half price? And if they go, what's this? It's a kind of a hint but in a in a a new market, you want to get out of the building to understand the day in the life of a customer.

You want to understand their problems, their need, how they do their work, et cetera. You truly want to understand their problems and you want to go to a whiteboard and be able to describe either the workflow or the problems or whatever. And then right underneath it, I want you to kind of describe how the world is going to change when your product is going to come out and what is it that that's that insight that will tell you that people will stop what they're doing in X.

And start doing your thing, Y. And that show me the evidence you have that either you're building MVPs, if you talk to people, and by the way, even telling me they don't get it yet is still okay. If you could explain to me why they don't get it yet, because all these other ancillary things need to happen.

5G needs to be embedded in everything or gee, we need 6G or whatever. But when that happens, we believe X and Y and here's why it's going to be transformative. Okay, well, tell me why you know that. Well, I've just spent, you know, four weeks living with these people, or I spoke to 75 people or sat in these 75 situations and basically the whole idea of lean, particularly in a new market, is you're trying to create evidence.

And what I actually call it when we do this in life science, because it matches the phrases they use there as well, is we're creating evidence based entrepreneurship. We're just not throwing stuff at the wall. Not only will we try to reduce infant mortality, we're trying to create as much evidence as we can.

In a set of uncertainty, we're trying to build a bounding box of, of how do we eliminate as much uncertainty as we can. And in a new market, there's a ton of uncertainty, right? But, but the rewards are enormous if we're right. so how do we, how do we do that? Well, you know, first of all. Here's the evidence I have.

Here are the risks I've identified. Here are the other things that need to happen. Oh, I remember when the web came out, there was a whole set and mobile came out, there was a whole set of underlying technologies that these new applications were betting on. And sometimes those shifts didn't happen fast enough or it didn't happen the way they had.

Well, if you would have articulated what they were, then you could have understood the risks. 

Brett: So how does that sort of inform your ideas around market timing and its role and how much of it is for a lot of folks actually accidental, 

Steve: So one of the things I, I, I drew in the first book I wrote, called the four steps of the epiphany, because this one took me a while, if I'm an investor or sitting on your board, and you tell me you're in an existing market with something better, your sales curve better look like this, right? Why?

Because you're taking share from the incumbent or the market's growing and whatever, or if you're an existing market, but you're going after a niche. Well, your sales curve is going to have a little hump, because you'll get all the early adopters in that niche, but if if you're right, it'll take a while, but then again, it'll grow, but it'll have a hump.

But if you're in a new market, that's the, that's the historic hockey stick. That's not the same sales curve as an existing market. And the, the first step is, when I teach students and you ask them for an Excel spreadsheet, every one of their spreadsheets have a five year plan that looks like this. And if you're in a new market, that's just impossible.

 do you have enough capital to go through those dark periods of like market adoption and that?

And by the way, Sales and marketing is still radically different if you're in an existing market, you're spending marketing dollars for demand creation, whether it's web or mobile or health care

it doesn't matter to create share. If you took those exact same dollars in a new market and did it, in fact, we ran this experiment in the first Internet bubble with Super Bowl ads in a new market and spent the exact same dollars with the exact same marketing. You just set that pile of money on fire in the middle of the street.

Because in a new market, it's a guerrilla set of activities for the first couple of years. There's some early adopters you have to incent, there are partners you have to incent, etc. It's a completely different, um, go to market strategy. and healthcare is different from fintech, which is different from enterprise software, which is different from for whatever.

The people who kind of knew this for decades are the people, delivering therapeutics, that is, drugs. where that time between when you start and the time where you might have some licensing revenue, let alone a phase three FDA approval, could be a decade or two. In software and consumer hardware, people have forgotten that difference between an existing and new market.

Brett: What do you make of The fact that there's so many examples of successful founders where their 2nd or 3rd thing works at extraordinary scale. And their previous attempts at starting companies didn't work.

Steve: I'm a personal example of that, although it wasn't the the 2nd and 3rd, it was, you know, I had done 8 startups and my 7th was a disaster. You know, that one failed for lots of reasons, mostly around personal hubris, you know, I believed because we were on the cover of Wired magazine that we must be geniuses when in fact, you know, no, we were, you know, our marketing was great. And, and, you know, out of that failure, I actually sat down and, and actually started, some of the basics of what we now call lean.

Trying to understand what were the hypotheses that we were actually thinking about, how to test, you know, products early, how to do pivots when the data said, no, the customers aren't over here. They're over here or, or no, they only care about features, 3, 7, 12 engineering stop building them. So I took those lessons out of that debacle and actually was pretty strategic about it.

And I think I, I don't want to make it sound easy out of the failure of what was called rocket science. Um, I was coming home and, and going to bed at 4pm. until my wife said, I think that's a sign of depression. it was the first time in 21 years that, you know, I didn't want to go to work.

And after that, I just kind of said, okay, you know, what did we learn from that? So, so I think a good number of founders, if they're thoughtful, you know, and I went through the 12 steps of first, you blame your co founders, then you blame your investors, then you blame, no, it truly is, and then you come to grips with, well, no, your card says CEO.

I kept looking at the card and went, you know, regardless of what everybody else did, my, you know, I didn't raise my voice enough and I'm meaning raise my objections to my investors or change the strategy or whatever. But there's one is of, of coming to grips with it. But the, but I think what happened to me was I actually thought about, well, what was wrong with the model of actually building a startup at the time.

And, and that's where some of these lean processes came. And, you know, nowadays it's not a big deal, but when Epiphany went public in that bubble at the turn of the century, we had $120 million of revenue in 3 years, real revenue, and an $8 billion market cap. And I think a good chunk of it was obviously a world class team, my co founders, Ben Wegbreit, and we brought in the CEO of KPMG, Roger Siboni, who built, world class execution things on top of, you know, the craziness we had built.

But I think it was based on, on the, out of the ashes came that success. 

Brett: do you think that's the case for most founders where the 2nd or 3rd company works because they had learned something foundational that they then apply?

Steve: I was in two startups early in my career. Most of them lost in the mist of time, but one was called convergent technologies and the founder Allen Michaels took that from zero to $400 million bucks when that was real money in the, in the 1980s, incredibly successful, had all the characteristics of Elon and somebody else: dysfunctional, crazy, you know, insane, but the most exciting place in the world to, to work.

And so fast forward a couple of years, he starts another startup. And by the way, he was out in front of customers all the time. He was listening. He was pivoting. His company started as one thing and ended up in another by the time I got there. And his second company. He was the successful CEO.

Guess where he was spending his time, in front of customers? Hell no. He was wining and dining investors. And who was spending time in front of customers? I was. What was I finding? The product we were building wasn't one that people wanted, but they were telling us they wanted something different. What do you think the founders said?

Hey, yeah, I raised money based on these promises. Get back to work and try to sell this stuff. so there's another model where the founder goes into, well, I was a genius in the first one, therefore, I don't need to do all this stuff again. It was obviously my insight. When, in fact, what they didn't realize it was their customer insight that they had been learning from, thought they didn't need that anymore, said it was all because they were smart, and, and created the company in a pretty spectacular way.

So there, no, there's no guarantee that founders will learn from their previous successes or failures. 

But I've kind of found that is if you could force people and force, I don't mean force bad, but actually get them to think about on a logical basis, what did you learn and really kind of bring those to the front.

What are you going to do different? You know, how are you going to operate this thing in a way that those lessons were not just you burn someone else's cash, but that you learned a lot of things. And, and I've kind of found this, if you can't draw it on a whiteboard, or you can't teach it to someone, you're probably, you probably haven't learned it.

Brett: Is what you were sharing about sort of the dynamic of a founder that does have a company that works and then struggles to have another company work. Is that sort of your crystallized thinking on. Basically the question of why aren't there more successful multi time founders? Where you kind of have this pattern of somebody has a ton of success. There's also a selection bias problem, which is if you worked like crazy for a decade to make something really work, a lot of people just don't have the energy to go do that again. And so they don't even try to do it. But there are surprisingly few folks who have built more than one company that matters.

Steve: you know, I think A, luck has a lot to do with it. B, hubris has a lot to do with it. That is, you're not as hungry again. you know, back to your last point, I remember the reason why I retired is I started something with, um, I don't know if you know who J. B. Straubel was. He was the CTO of, Tesla.

Well, JB and I and, uh, Scott Andrews, uh, started a car company, which eventually became Tesla. And I did that for six weeks with him until I realized I couldn't get it up again. There was no way. I went to jump on red eyes like I used to. I had a family, I had kids, you know, I had whatever. And I just, I was honest with them.

I said, I can't do this. Not because I didn't think starting a car company at the turn of the century was a good idea, but there was no way I wanted to put that energy into that. JB eventually found, uh, you know, the first founders, the real founders of Tesla, and did the company, but, you know, we, I still have the original slot.

So for me personally, I ran into that as well as, and my test, actually, I get it down to a test that investors should think about. Is you want to ask the founder from a successful company, how many red eyes were you on that is the be able to jump on a plane for, in fact, just to be clear, you know, here we are in San Francisco.

I remember calling people up in New York and saying, hey, I'm going to be across the street, you know, having a meeting tomorrow. Are you around? Can you grab 10 minutes? If they said yes, I would jump on a red eye and take that meeting. I mean, I was relentless. That's the test. You want to ask 2nd and 3rd time founders.

All right. Can you, can you look me in the eye and tell me you still could do that? And my answer was no, there's no way I want to do that. Too much money, too many commitments. I'm getting too old. It's exhausting, et cetera. so I, I think that's, you know, not only passion, it's just kind of like, are you relentless and, you know, will you win at all costs?

And I don't mean, you know of killing people, but win at all cost of, win at all costs of putting all, all you have in it. And I remember what an advantage that was, you know, showing up is still like 80 percent of the game. Showing up where other competitors weren't showing up and just being - I remember sitting in people's office cold calling where they say, no, no, no, he won't see you.

No, no, no. You don't have a meeting. Well, I'm not leaving till he does. I can't tell you how many times I, I did. And 1 out of 20, I, you know, I'd get a meeting and get an order. I remember at Epiphany, one of our biggest deals on our, on our red herring was the logo of Microsoft. And I got that deal because I saw they had an RFP out for some system and, and I realized mine was perfect for it.

But of course, if you haven't helped write the RFP, meaning a request for proposal, the odds of winning it are pretty low. But I managed to to get in there only because the guy who, who wrote it laughed at me and said, Steve, there's no way you're going to win this thing. Don't even bother. Oh, man, you never do that to me when I was an entrepreneur.

Don't laugh because I managed to figure out how to get someone to call Bill Gates because that was the other thing I did was I had an advisory board of potential chess pieces, and one of them was Gordon Bell, who was a mentor of mine who ended up being able to pick up the phone and call Bill. That was a 12 million deal for us that ended up on, as I said, on our red herring.

So, if you're not prepared to still be relentless. To give the same amount of energy and time and out of the building stuff and whatever, if you think you're going to delegate this now, you know, you should be on the advisory board or be a, you know, something else, or it's time to go home or be a, be a professor at Stanford.

I mean, it's a, it's a good gig.

Brett: It seems like a lot of people have some sort of issue with this idea that it just takes an unreasonable amount of intensity over a very, very long period of time. And I think it is, it's just total nonsense. There's no existence proof of anyone building, doing anything that's outlier in art and music and sports, but specifically building companies.

It's just completely unreasonable what has to happen to create something out of nothing that then grows into something that generates a billion in free cash flow or whatever sort of proxy metric you have.

Steve: You want irrational people, and if you're not going to be irrational, you ought to consider you're competing with irrational people. So let's say, well, I can't do that. I don't want to put that amount of energy. Well, explain to me how you're going to compete with people who are irrational because that's who they are.

Whether you are or not, that's who you're competing with. If we said we're not investing, if we've all agreed there was an arms control treaty with VCs that said we're only going to invest in healthy people, then that would be fine.

But we invest in crazy people, who in fact will put everything, including family and fortune and fame, on the line for doing this thing. Not because most of them want to make money, that's your job, but because they're truly passionate about creating something that the world's never seen and having people use or whatever.

I mean, that's why I did it for the first six startups until it dawned on me that I ought to be making more money than you guys. And then figured out how to structure those things. 

Brett: Is there anything that comes to mind about sort of that delicate tension when you think about outlier founders? Where you kind of have this intense, strongly held point of view on what needs to happen in the future, but at the same time, you kind of have to connect with what is happening today. And it seems like a delicate balance.

Steve: Well, I think the best example that's been publicly articulated is Elon's wants to populate Mars. you know, in doing that, he needed to create, you know, a rocket. Then he needed to create a rocket that had economies of scale. So, therefore, it had to be reusable. And then, you know, he needed rocket designers and have other.

So he hired Mueller and then. The reusable part is they discovered convex optimization algorithms at Stanford. And so that's how they figure out where to shut off the thrust. And then they went, well, wait a minute. It's we, there aren't enough commercial payloads to even make this profitable. So what if we created our own, you know, ecosystem and therefore we got Starlink, which now you know, generates revenue. So by the way, none of it has to do with Mars, right? It's all like this, whatever. Now he might get, oh, but now we need to go to the moon because NASA, you know, like, oh, so why don't we create something with bigger payloads? So we'll create Starship. I don't think he's probably lost sight of Mars, but I think there's a lot more steps than he first, if you remember, at least the apocryphal story says, all he wanted to do was put a plant, a green plant on Mars with a camera.

I think he's gotten a long way from there, but I, I think if you asked him eventually, he'd still say, yeah, I still want to get to Mars. so you discover as you get more mature in your business, that there might be ultimate paths, if he said, I was just building a giant moon, uh, Mars rocket, I think he'd be out of business.

I think he had a profound belief loosely held that said, well, wait a minute. There are these ultimate steps to get there. 

Brett: So expand on that a little bit more, and it obviously kind of connects with a lot of your ideas about building companies. But I, I do think that one of the things that's in very short supply isn't necessarily kind of a vision for the future, but it's the bridge, right? I think that X is going to happen in the future.

There's an opportunity for Y. Very few people have the ability to then assemble the steps to ultimately get to something that's 5, 10 or 20 years away. and so what comes to mind for you? 

Well you know this is when you have a world-class board. A world-class advisory board, 

that helps young founders or not so young founders 

Steve: actually think about

great we want to get here. How do we actually think of the pieces of getting here? And how do we make money for both the company?

And it's investors simultaneously with, you know, 1 of the things we haven't done well in the entrepreneurship ecosystem is write enough actual. And I use the word because I hate them case studies that actually describe reality rather than, you know, Sally is sitting by the window thinking if you've ever read any HBR case studies, none of them really are about product market fit or MVP's or long term strategy. They're all, you know, God knows what they are now I'm talking about the investing side, a good job as an industry in, um, in teaching, we do a world class job in investing, and we make enough money.

So we don't think we have to teach. But I also now have value that it wouldn't take much to actually start building and writing about extended lessons. I think Y Combinator has done a good job on the front end. If you look at their startup school videos and some of the others, et cetera, but I think what you're talking about is, how do I extend this thing into a company that last, you know, pass my fund or whatever that are actually lasting companies. And what are some lessons of, uh, of companies have done that? You know, it's very funny that two Elon companies, Tesla and SpaceX, are now in their, what, second decade and doing that and, and are potentially profitable.

Amazon and Bezos, another example, you know, until the founder gets bored and tired and distracted. I think it's happened with both of them, right? One with Twitter and the other with God knows what. But those are examples of, I mean, remember, Amazon started as a book company, right? It's like, what? Look at the original ads.

I mean, and look at all the pivots and gee, look at AWS and all the other things that, that they did. that was a profound belief loosely helped, you know, Tesla started as they were making the Model S, but Elon will tell you, he had a, or actually they started with a Sportster and then the Model S and then the, the disaster of the X, because somebody wanted a toy car with gull wings and whatever, but then figured out how to get back on track with the three and the Y.

And I think the cyber truck will be another model X, but, but still they created an entire industry. They moved the planet on those. So I think we could do a better job of, of explaining to founders who get to the first product market fit. Is here's the strategies for not just product line extensions, but in fact, the classic probably in our, in the tech industry is what jobs did in the, when it came back.

Right. It was the, you know, the iPod, the, you know, the iPhone, the, the app store, the retail stores, the, you know, I mean, these were successive reinventions of a computer company that is the equivalent of Amazon as a book company, you know, Amazon still sells books and Apple still says sells desktop computers, but that's not where their business is.

How did they do that? What did they see? Uh, how did they put the pieces together? Did they understand that all on day one? No way, you know, Jobs always wanted a closed ecosystem. So the first iPhone had no app store, it was, I was going to give you everything you need and screw and screw if you didn't need it.

You know, but things evolve and, you know, grudgingly and whatever. 

Brett: I also think there's a lot of people, a lot of people who are building companies that the first act works and they actually don't know why, or they tell themselves a story about why it worked. But the element of luck or market timing or external variables, they didn't know. And so they're not able to sort of mechanize that in any way and bring any repeatability.

So you end up with most companies, which just tend to be 

1 trick ponies where their 1st thing is their only thing.

Steve: Because we have no framework for evaluation, right? There's no commonly understood or agreed on either investor framework or academic framework about why. And so we tell these apocryphal stories about, gee, that's too bad it was a one trick pony, but instead of saying, well, let's just put these five characteristics.

Now, what happened? , .

Oh, when the founder starts showing up at, you know, at political events rather than focused on their business or their, their charitable, whatever. No, I want you insanely focused on X or Y. Well, you've just decided that you're, you know, you're successful. You can now afford to do these other things. And this goes back to that insane focus on the business.

You know, my favorite is of somebody I consider a friend decided to move out of state because he wanted to do something different and then no is no longer in the city where his business is. Guess, guess what happened? You know, his business is kind of petering out because he's paying attention to other things.

Very 

Brett: hard to do that over a very long period of time. I think that most of the successful founders start out with kind of this deep interest in the core thing that they're doing. Relating to what they're doing for the customer and at some point, money, power and fame takes over and you get invited to some particular political thing.

And then you're in a room with powerful people and then you start to say, well, how do I get into more rooms with powerful people? It's I think it is very hard to be that focused on a specific thing over a very long period of time.

Steve: Here's the part is that there are successful models where you bring in, you know, new CEOs. Um, you know, I sit on 

a 

technical advisory board of probably the best example of a company that's done that for 50 years called applied materials. We're not a household name unless you're in the semiconductor business, but no one would be able to make chips without their equipment.

They are the machines that make the semiconductors that TSMCs and others buy along with ASML, and KLA and Lamb and Tokyo Electron. That's the entire business. They've had five or more world class CEOs that took over from the founder. And the latest, the latest one has the same passion and intensity of any founder I've ever seen.

I mean, get in a room and I want to buy a wafer fan piece of equipment. I mean, it's just really amazing. And he's, you know, he's passionate, he's driven, he's on airplanes, he's whatever. So it is possible for boards to kind of look for that same passion and genius and drive. Um, it's just rare and boards have, and here's the mistake that happens all the time, is that instead, I've seen this a million times.

So, the founder had, wants to go or is timing out or whatever, and the number twos decide, well, it's my time. Obviously, the board's going to pick me. Well, guess what they were world class number twos and almost never are world class number ones, you know, we could argue is Tim Cook Steve Jobs? No. Was it the right time for Tim Cook.

We could argue that but look what Steve Ballmer did to Microsoft Bomber was a world class number two, and by the way, in all accounts for revenue and stock price, he was excellent. Microsoft revenue kept going up and their stock price kept going up under Steve Ballmer. He missed. He basically took Microsoft operating system share from 98 percent to probably 2 percent today.

Right? If you now count mobile devices, right, they're just irrelevant because he was so focused on extending the Windows ecosystem. They missed mobile. They missed search. They missed, you know, take the whole list. It wasn't that he was a bad CEO. He wasn't a visionary CEO when in fact technology was moving so fast.

You needed to do what Jobs did at Apple, which was actually reinvent the company literally multiple times. and this is a trap that boards of public companies fall into is well. If you don't appoint the number two, then they're going to leave. Right? Well, now all of a sudden I have a gap of the number ones retiring and my best number twos, you know, want to like go somewhere else.

Now, what do you do? And so it's really a conundrum for a world class companies that have had world class founders who want to do something else. But as I said, in applied materials, uh, the current CEO is exactly as I could imagine a passionate startup founder, except he's running a $20 billion company.

Brett: What do you make of Satya and his success? Probably the best example of a non founder taking over a 

business for the last 

20 years. 

Steve: Taking over a company that no one would have remembered their name. You know, the whole pivot out of Windows and into the cloud and, was just genius. And he did it in a way that was, uh, you know, I'm sure was wrenching for some people inside, but from the outside.

Almost looked like the resurrection of, you know, it's just an amazing job. And I think it's an example of somebody who wasn't beholden on that track I mean the problem is when you're in it think about what outsiders bring is just a they're not beholden to any any dogma and any doctrine that the company might have had internally, and they're able to look around and say, well, windows is great.

I'm glad you guys spent 20 years building it, but it's irrelevant for, you know, these other new things we need to be in and yes, it needs to be a core part of what we're doing, but it needs to be a part of rather than the driver. And, and I think it took an outsider to do that. I think when Sam Altman came into, you know, Y Combinator the same thing, you know, Paul Graham and his, his wife, Jessica built something spectacular.

Sam took it to the next level and then open AI did something that, you know, no one expected Sam or was I didn't to do, which was, you know, basically, you know, create anti gravity. I don't have to tell you and your listeners, you know, generative AI and AI in general. It's kind of like inventing electricity.

It's probably like inventing electricity, air, and water all at the same time. You know, I lived through a couple of revolutions personally. I've been there when we invented microprocessors. I was in the room or in the, in some of the rooms when we invented the Internet, we were one of the first enterprise software companies to use a browser, um, you know, telecom revolution.

This is one of those major changes, you know, I was there when like we were trying to put computers into offices where executives didn't believe it or not executives didn't type. They'd have their secretaries write their email for them and then print it out to read it. This is one of those moments. It's not only a platform.

It'll be embedded in everything we do. And for both investors and startups, it's going to be in a confusing time. Because the, the fundamental nature of the technology and what it could do is changing literally week by week. It's hard to keep score. So when you think you've invented something next week, it might be part of an integral part of Open AI's tool set, right?

So, you know, you thought you invented a product. It turns out it's a feature of someone else's platform. And gee, you think you had great access to data and now all of a sudden you're being sued by, you know, Hollywood, you know, or something else. So, so it's a wonderful time to both be an investor, um, and an entrepreneur in this space.

Brett: What does it take to build a really incredible company in this new paradigm? And do you think it tends to look like the last 20 years 

or very different?

Steve: Yeah, so from an entrepreneur's point of view, this is the one where you definitely need to remember whoever you took money from, their business model is now yours. Particularly, they're interested in, you know, either flipping this thing as fast as possible and driving its valuation as high as possible.

And hopefully make as much money, which may or may not mean staying into the end, especially AI platforms and AI applications are the hottest, you know, for a while, the hottest areas in a fairly depressed, you know, investor space, you know, your job as an entrepreneur is to make sure you understand what your investor's intent is.

And then number 2 is make sure you're building something that is defensible and not a feature of someone else's platform. because this is one of those risky and, and great opportunity times. so can AI enable? It's just like when the web came out, right? Everybody was doing client server, but now all of a sudden, can I, like, web enable a ton of things?

Or was my feature set just going to be a feature of Netscape or Microsoft Internet Explorer at the time? So I think that the opportunity is just amazing. There are piles of data that people haven't looked at. There are piles of applications that it doesn't take much imagination to figure out how to enable.

And more importantly, the entire lean method is going to be end to end enabled by AI. That is, you know, let's just take a very simple example in e commerce. I could now today buy pretty perfect advertising data, you know, it just insert dollars. I could buy demographic geographic, you know, data about almost anybody.

Well, once I have that data set, why do I need to get out of the building? you know, I could start doing customer discovery on by creating artificial personas and doing not only A/B test aid, a million tests on that, building MVPs and automatically creating a websites with, you know, auto generated content and testing those.

And human beings might be inserted in different parts of actually validating some of these results, and I could actually use that to create a, you know, a venture deck out of the end of it. Here's the million experiments I've run, not just five. I didn't get out and talk to 100 people. I talked to 100, 000 by running these, you know, simulations.

So I think the whole nature of lean, at least in markets where you have pretty accurate data is going to be changed fairly rapidly in the next two years. In fact, that's going to be a pretty good. Enterprise platform. If someone wants to build that end to end package, I've already seen people building pieces of it.

But I think to me, the ultimate, the ultimate piece of enterprise software that people will build on top of is someone's going to make a set of packages of that. 

Brett: The point about defensibility is an interesting one, because it's one that is always clear in retrospect. And at times it's hard to figure out at the point of origin, I think specifically sort of in the context of AI, this is the thing that everybody's talking about and thinking about. how do you actually action on that?

Right, there's a small subset of companies that I think obviously have a compounding advantage or moat. Back in the day, if you were building a social network, it's very clear if you could get to scale because of network effects, it would be quite defensible. But in this age of figuring out what is going to be owned by call it the top three foundation model providers versus a standalone business that can grow over the next decade seems very tricky.

Steve: First of all, yeah. You know, from the investor's point of view, it's like, well, it's the greater fool theory. Can I, can I invest in something interesting and flip it before someone else, you know, embeds it in the, in the foundational model. But more importantly, I think the, the test here, and I, you guys know this, and I assume most of your startups is.

Can I get a hold of some unique data sets that, could be a defensive moat? You know, I'll give you a good example. A couple of years ago, one of my students, partnered, uh, uh, with the, the guy who owned all the clinical prostate data at UCSF and created Artera AI, which I think just raised, I don't know, 90 some odd million dollars to make, uh, FDA approved prostate cancer tests.

And they had access to unique data set to do that. There must be thousands of those unique piles of data running around the country, whether they're in health, and certainly the place that's pretty obvious is health care data, where there's a ton of disconnected clinical trials and other data that might be useful.

But also in the enterprise, whether it's supply chain data or other places, I would just assume that the platforms themselves are going to get, you know, still move at incredible speed for the next year or 2. in fact, this feels like 2 things I've seen in the past. One is in the beginning of the PC era,

personal computers weren't fast enough to run real world class applications. So companies that had, for example, electronic design automation software, built their own workstations, literally think of them as high performance desktop computers. But literally, in that time, those first 5 years, PCs finally became fast enough, and then companies were kind of stuck with having built their own hardware.

Now, like, how to make the transition to personal computers. But, but there was an awkward time where those PCs still weren't fast enough, but they were kind of fast enough, but other startups have started on the PCs. So that's kind of the platform transition I think we're going to see with some of the

the generative of AI stuff, some of it's good enough, but gee, it requires, you know, having access to a million, you know, like NVIDIA chips versus, you know, spending a ton of money on the cloud or something else. But at the same time, some of those models are going to become a heck of a lot more efficient and now being able to run on something a lot cheaper and faster.

It's just looking, I think, at some of those things that happened in the past, as I said I could think about actually three or four of those transitions, where in, as you said, in hindsight, you would have said, oh, yeah, well, let me just draw that hardware curve. Uh, yeah, you need to build your own workstations if you want to do it now, but like, don't invest in a factory for that, because pretty soon, the price of PCs and its power are going to come up.

And, and the same was true with multiple things on the web, multiple things in semiconductors. That's one. Two is the, if you want to be on a, or want to be a platform, that's a whole nother game. you know, this is starting to look a lot like, you know, the operating system wars or, or even better, the internet browser wars.

you know, innovation was incredibly fast when it was a competition between Netscape and, and Microsoft. And when Netscape went out of business, innovation stopped. So I sure hope OpenAI, Google, and Facebook, and even Apple continue to slug it out at some point. Because if they don't, innovation will die in the browser, like the browser did, it will die in generative AI.

It looks like it's going to continue for a while because it's an arms race. And that arms race is actually great for innovation. Though, in this case, it might, it might kill the human race, but that's another conversation about safety of this stuff. But, but the arms race competition between these companies who are,

you know, Microsoft essentially wants to kill Google and open AI, I think, wants to kill everybody. And, you know, I think that competition is going to make the platforms incredibly feature rich in a way we can't even imagine over the next year. Just look what's happened since January, for God's sake. Durability really is finding niches and data sets that, you know, that, and I've seen a million of these now that there are places and that you could go for not just great demos, but for great productivity or solving real problems that people don't even realize they're sitting on those data sets.

I think they're, you know, just like when we, started creating data warehouses back in the last part of the 20th century, there was a big business in just ETL, you know, cleaning up data. I think we're going to find a whole new business in cleaning up, you know, existing data sets and making them useful to, to build AI models on top of them.

Um, people will be stunned to think about all the data they were running big data analytical tools on now are actually much more useful for running a large language model.

Brett: Now, that 4 steps to the epiphany was written quite some time ago. What are the things that you're even more sure of? And are there things that you've updated your thinking on as it relates to a bunch of the original insights in the book.

Steve: One of the things that stunned me is a how long it took to get adopted and how hard it is even still today for people to actually practice it rather than talk about it. And two is. I, I am stunned and embarrassed that it's still around, because enough people now tell me that some of the principles actually are foundational, meaning, yeah, I thought that it was nice.

It's going to be a fad and someone else is going to, you know, reinvent it and whatever, much like I did to, you know, how to write a business plan. But in fact, getting out of the building and actually, you know, MVPs and pivots and you know, my work, Eric Ries' work and Osterwalder's work kind of is the basis of, at least if you're thoughtful about entrepreneurship, how you think about the lean startup.

So I guess, first of all, let me tell you the biggest surprise that's still around and maybe because it is kind of foundational, but what's really changed is, um, certainly in the, in the pandemic, I discovered that no, 100 percent of customer discovery doesn't need to be done on purpose in person. That at least the first level is if you could see someone's pupils dilate via zoom, at least the first level of discovery.

It's in fact, much more effective to do. You could probably do 20x more versions of discovery via zoom and then go meet people. And so that gives you a force multiplier in a way that, if it wasn't for the pandemic, I wouldn't have believed, but actually practiced and saw, not in a, not a replacement for getting out of the building, but a

force multiplier for where to get out of the building and how. You know, I think since we started, you know, agile was kind of understood, but, but now it's just an integral part of what people do. You know, agile and lean are tightly coupled in a way that, um, allow you to do things with speed and urgency that, um, just wasn't possible before.

One of my first things I wrote in the first Four Steps to the Epiphany, which I said, well, this is applicable to everything but life sciences, and of course three years later, I was teaching a course at UCSF for therapeutics, devices, diagnostics, and, and digital health. And then a year after that, the NIH adopted it.

Um, so, so that was wrong. It turns out, no, I can't accelerate the development of drugs, but I could test the hypotheses of all parts of the business model about regulators and reimbursement. And, and, you know. CBT codes and the rest that most technical founders didn't have a clue about. And so we were able to teach that the other surprise is that, you know, the, the class that I built out of this called the lean launchpad at Stanford got adopted by the US government. It's now called the National Science Foundation I-Core, innovation core. It's taught in 100 universities. The NIH version is still being taught in Maryland. And then we created a version for the Department of Defense called hacking for defense. It's taught in 60 universities in 3 countries.

So the methodology was not only adopted by entrepreneurs, it's kind of been adopted on how to commercialize most of science in the United States. That's been a positive surprise. But as I said, I, I believe eventually what will obsolete it is not another theory, but, um, maybe a lot of AI thrown at the process.

if I was, honestly, if I was doing another startup, that would be the one I would do. Was take the methodology and build a piece of end to end enterprise software, at least as the vision and maybe start it with different modules for each part and then target some of the easy ones, starting with e commerce and moving to some of the harder ones where you have sparser of data sets or proprietary data sets and basically if I'm correct, these are foundational principles, figure out how to use technology in a way that's never been applied before. 

Brett: What was the founding story of The Four Steps to the Epiphany? What, what was going on that led to that crystallization and ultimately the book?

Steve: So, as I mentioned, I started practicing some of this in my. Last company called Epiphany, actually was the name of the company. The founding story of, The Four Steps to the Epiphany was I had retired and, and thought that the world really needed my memoirs.

And I had structured my memoirs to, kind of, and I started writing 

them. 

And I started doing it chronologically. Here's company X, you know, and then I, at the end of each one of those vignettes, I wrote something called the lessons learned. Here are the bullets and the next company and, you know, whatever.

And I remember I was up skiing with my wife and daughters and they were out on the slopes. And I brought a computer and I still have the document. I was up to page 80 and the hair stood up on the back of my neck. I realized that there was a pattern here I had never seen. The companies that I actually spent time with customers, I did really well at, or, you know, or somebody had spent time, and the companies where we just went and executed because we got funded the plan and VC said we were geniuses because they wrote a check and therefore the kind of canonical model was here, you know, go to alpha test, beta test, first customership and, and do we have enough room to store all the bags of money?

But that wasn't true. And I realized I never saw that before and then realized my, my investors weren't telling me to do that. They were telling me to write a business plan and go execute the plan and managing to the plan and every board meeting now come here and you're not doing X or Y. No one was asking about what did you learn?

I realized that I could kind of take all the things I had done when we, when they had worked. And by then I was sitting on other people's advisory boards and a couple of public company boards and as seeing this, not only through my startups, but in others, And that was the basis. Literally, that meant, was there's a pattern here.

And that basically, that there's a pattern here, is probably one of the only three things I was good at, um, in my entire career. I've been great at ingesting an enormous amount of data and liking it, meaning I read a lot. I am incredibly curious, but I do run this neural net in the back. Um, and every once in a while, something will come out about patterns.

About business or opportunities or whatever, and this was 1 of them that neural net just went off that said, wait a minute. There's a pattern here. And by the way, it was a pretty lonely 3 or 4 years. no one believed it. Why? They were making a ton of money. It was the bubble, you know, like, whatever. But then, um, Eric Ries, who, uh, I invested in his company when, uh, went, uh, uh, on his board, became the first practitioner, and then he kind of fell in love with the idea, and then others, and I started teaching it at Berkeley, and then got, as I said, started teaching these classes.

Brett: From that moment that you were sort of collecting your thoughts on that ski trip. what then did you do to sort of end up with this sort of set of ideas and frameworks that people could then go do something with?

Steve: I think within a month or two, I had a slide set of slides on what became customer discovery. And then when I met Eric, he slapped me on the head and said, well, Steve, we don't use waterfall engineering anymore in software. We use agile and then realized that agile and customer development were the two pieces.

And then, about a year or two later, I'm teaching this class. Now I convinced Berkeley to allow me to create a new class. By the way, I did it again with Jerry Engel and then again did it with at Stanford with Tom Byers and Kathy Eisenhardt. Tina Seelig invited me to teach there. I've had this enormous opportunity to take these ideas and turn them into classes.

Then ran into Alexander Osterwalder, who created the business model canvas, and then those three pieces. The canvas for articulating hypotheses and then, you know, customer discovery and agile for building MVPs and pivots and getting out of the building. That is essentially the 20 year foundation of lean, and but the core tenants of are still the same.

That's why I said, I've been surprised that this was not a better version of how to write a business plan. It was a radical break. It created essentially modern entrepreneurship where it says there are no facts inside the building. So get the hell outside. And the other version of this is there's no way you could be smarter than the collective intelligence of your potential customers as smart as you are. Those things I think are pretty lasting and are true. If they were enforced in a board meeting of like, not only do we want to see your engineering status and whatever, but we want to hear about your customer discovery journey or your validation journey ,and tell us about the MVPs you're building and show it to us and tell us what you've learned to get here, not just tell me how smart you are now. I want to hear the journey and every board meeting. Well, if you build that cadence, then all of a sudden you'd have practitioners as CEOs, rather than people who are giving lip service to it. And as I said, maybe, maybe it doesn't even take an hour. In 20 minutes we could come up with a set of questions at various stages of a startup that builds this cadence of customer discovery.

Brett: Good place to end. Thanks so much for a fun conversation. I really appreciate it.

Steve: Thank you, Brett. This went in places I never thought it'd go.