eries

Academics have spent the last 15 years attempting to measure these effects, and it's just a very hard measurement problem. There are so many confounding variables. I would say the early evidence is supportive of the thesis, broadly speaking. In the long run, I expect we will eventually be able to speak about this in a much more nuanced way. For example, some of the elements of LS are much easier to test than others, and those have been found to be broadly effective.

This project may take decades, and yet leaders need guidance and useful mental models in the meantime. So, to me, the much more useful data is the literally thousands of founders (and other leaders) who have reported that they have found the framework useful in their own lives and companies. They may all be deluded, of course, but at some point I think we have to acknowledge that _something_ useful is going on here.

In any event, I don't give it that much thought. If a new theory emerges that proves more useful, or if new research gives entrepreneurs new and better tools, I'd be delighted. My only loyalty is to the truth.

We're certainly seeing a lot of speedup for certain kinds of products, and I expect to see far more. But some of these speedups are dramatically overstated because people are measuring only the time to produce the prototype or the cool demo, not actually the time to get through the full build/measure/learn feedback loop. In fact, if you think about it, I think it's pretty clear that it's the learn step of the feedback loop that has always been and will always be the bottleneck.

In terms of good uses for AI to figure out what people want, I really think the best advice is to focus on your own skills and agency. In other words, never ask the AI to make an artifact for you. Instead, ask it to teach you how to make the same artifact.

If you do this over and over again, if you do it step-by-step, having the AI as a teaching companion, critiquing mistakes that you make, breaking the problem down into smaller sub-problems, making sure you've mastered each step before moving on to the next, pretty soon you'll be able to create some really awesome artifacts.

Is this approach, in some sense, "slower" compared to vibe coding everything? Yes. But I think, at least in my experience, this is a go slow to go fast kind of situation. Now I had the benefit of being able to use a completely custom AI rig made by the company I help co-found, Answer.ai (with Jeremy Howard). If you want to learn more about that, you can access it at solve.it.com.

I understand where you're coming from, and if you read the later chapters of the book especially, you may find the book surprising. I won't say more to avoid spoilers.

what else could the answer be? I feel like this is almost overdetermined, but we will have to slog through a lot of gyrations as people try to make some other answer fit...

/salute

I do make critiques of capitalism in the book, but I try to be very careful when using that word, since at this point most people can't even agree on what the word means.

Here are some things that seem to me unequivocally true if we look at the historical record and the data available to us: 1. These kind of value-destroying actions in the name of profit have been going on for a very long time, at least 200 years. 2. The problem seems to be getting worse in recent decades. 3. The problem seems to be highly correlated with the increased financialization of our economies and the advent of a relatively recent set of so-called best practices about how companies should be built, run, and governed. 4. Companies seem to vary widely in the degree to which they are vulnerable to these forces. 5. I think to be learned by studying the companies that have been able to resist-- as a collective set

Those are symptoms. The real question is, what are the deeper causes? I think the book gives a pretty clear and convincing answer, but then again, I wrote it, so you'll have to judge for yourself.

Most of all, I want to restore people's sense of agency to do something about this. We are not helpless in the face of these forces. In fact, we are the originators of them.

Thanks for your kind words. Don't let the mercenaries get you down. They're depressing a lot of us, but they're not here to stay. People always want to judge these trends in the middle of a cycle, but during the hype cycle you can't really tell what's real and what's not. Give it a couple years and then let's revisit, shall we?

It's a really complicated and confusing company to draw lessons from, partly because there are such big ego, larger-than-life people involved doing crazy stuff. A lot of the inner details have not yet been made public, so I don't think we really, really know what was going on behind the scenes. There have been quite a few factional struggles there, and I'm sure you can find bad behavior on all sides. That's not that uncommon when so much money is at stake.

In the book, I try to get into the structure that seems to be stable over long periods of time, which, because I know more about the details, I felt more comfortable illustrating by telling the story of Anthropic. I had to pick one difference that seems to really matter in these so-called complicated structures. It's whether there is one central point of control or more than one, i.e., if there are checks and balances. That when an outside board of trustees has the power to hold the for-profit board accountable to the mission, that seems to produce more stable results.

Check out the research of Steve Thompson at the Copenhagen Business School, who has been a pioneer in developing the data from which these conclusions are drawn.

I am finding this exceptionally difficult, to be honest. It has been nearly impossible (so far) to get traditional media to take the book seriously (there have been a few exceptions). And the perversity of the modern social media algorithms means that it is extremely difficult to get discussions of the book to break through that barrier. I've had people who follow me say their feed is absolutely saturated with content about the book, and others who have no idea the book has come out. The algorithm decides all, having hundreds of thousands of followers is next to useless anymore.

So, to the extent the book is getting attention at all, it's being driven primarily by word of mouth. People who read the book are inspired to become evangelists for it, far more than my prior books. I think this one is more emotionally resonant for folks, and has applicability way beyond founders or even product people. So I'm extremely grateful for all that support.

I've also done a metric ton of podcast interviews, many of which you can watch here: https://howisincorruptiblegoing.com/

But if you look at the view counts on YouTube, you'll see that they are all also suffering from the algorithm's fickle attention. Most have very few views (with a few notable exceptions).

The fundamental question is what the people who work at an org are incentivized to maximize for "whatever it takes." Today, by default, orgs are aligned to maximize shareholder value (even at the expense of long-term viability) but there is nothing natural or logical about this.

Not directly, although many people have pointed me towards his work since the book came out. I look forward to diving in.

If you've been around the ecosystem long enough, you eventually realize how these cycles go. When startups are seen as trendy and a good/easy way to get rich, you get a lot of this gambling behavior in response. When the crash comes (just wait) a lot of those people get flushed out of the ecosystem, and things return to the original motivations: building, exploring, discovery.

I was talking the other day to a Silicon Valley OG and he expressed total disgust to me about the "mercenaries" who have overrun the valley right now and who are destroying the very things that made it great in the first place.

Not sure I agree with your assessment. From my perspective, it’s actually doing well: appropriately funded, its proposal for companies to optionally move quarterly earnings to semi-annual is supported by the SEC, and it trades the same stocks as the other two major exchanges. But it takes time to build something new and innovative.

y not both?

You might be surprised to learn that some of them are, but not if done according to today's so-called "best practices" about how to structure corporations

I know this is a common belief, yet the data doesn't really support it. There are truly exceptions. If you study how they became exceptional, you'll find that they defy so many of the so-called best practices we teach today about how companies should be built, structured, and governed. I don't think this is a coincidence.

Well said on both counts.

Eager to hear what you think after you've had a chance to read it. Do let me know.

In some industries, older entrepreneurs have a big advantage over younger entrepreneurs, so it kind of depends on what you've been doing and what you're good at.

Organizations are organizations in the end, so hopefully you'll find something relevant in the book too.

Thank you. I can't believe it's been this long.

I've talked about this in a couple of recent interviews, and if you can't find one, I'll try to find you the link. This question about what it's like when you're in a platform war and the platforms are like these massive bulldozers is kind of an old bit of entrepreneurial lore that, at least when I first came to Silicon Valley, I was taught many years ago. We haven't had a bona fide platform war in a while, so I think some of that lore has passed out of common memory. Generally speaking, what you want to do is what's called a market resegmentation, where you find some section of the market that the bulldozers are not going to pass over, or where you control the customer because they are loyal to you and you can play the platforms off each other.

But should they want to game the system? Do you want to game the system? If the answer is no, maybe you have some interest in learning how to build a company that would be able to resist that temptation in the future.

Definitely, AI makes certain kinds of MVPs a lot easier to produce, so that's great. Unfortunately, some people are being encouraged to outsource their own thinking to the AI. For them, it doesn't seem to make the learning any faster. In fact, I know some people that it has made the learning quite obviously slower.

Totally fair. I'll pass it along to the team.

What a great metaphor. If I had known about it, I probably would have used it in the book.

I'm not sure I understand what you mean by "what"

I would not think that LLMs would make very good leadership decisions, mostly because they're too malleable and too easy to manipulate. I do think they're very helpful in helping leaders assess their own context and situation and thereby make better decisions.

That sounds very similar to the Alibaba Employee Voting Trust (EVT). That's one of many, many structures that I cover in the book. I would say, in general, one of the reasons that people have a hard time thinking through these structures is that today we treat the leadership/operation side of things as a different discipline/different problem than the governance/structural side of things. In fact, they are two sides of the same coin.

I cover that specifically about Google in the book rather than summarizing the whole thing here. I'll just say that if you read the essays of people that worked at Google for a long time (and then left), you will see some pretty remarkable patterns.

Just look at the evidence. Investor holding periods are going down, and there's less and less correlation between value creation and stock price movements.