I’m writing a book about the worldview I’ve developed by writing, coding, and living with AI. Last week I published the second piece from it, about how AI will impact science. Here’s the third, about how AI will impact business.—Dan Shipper
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As a young entrepreneur, I once thought of myself as an information processing machine. I got interested in mental models like Clay Christensen’s disruption theory and Ray Dalio's Principles. I took copious notes and spent countless hours organizing them; I felt tremendous pressure to memorize these “rules” so that I could apply them in my business life.
But in doing all this intellectual work, I had a nagging feeling: How would I remember to apply them in the situation that demanded it?
I also saw entrepreneurs around me trying to apply similar rules, with mixed success. It sounds like a bad joke: A Wharton student goes to their first class on negotiation and learns about anchoring, then walks into their next negotiation proposing a price that's 10 times too high because they think it'll properly anchor the potential customer when instead it just pisses them off.
We’re not the only entrepreneurs and capitalists who envy science and rationality and try to apply it to business.
In the late 1700s, Adam Smith, explicitly inspired by Isaac Newton, attempted to discover universal laws of economics—and popularized the idea of the market’s invisible hand. In the early 20th century, Frederick W. Taylor attempted to optimize businesses scientifically, proposing that workers should be studied like machines, with every motion analyzed and improved for maximum efficiency. In the 1970s, Michael Porter’s “Five Forces” framework tried to explain business success as a factor of elementary forces like the bargaining power of suppliers and the threat of new entrants. Christensen’s disruption theory attempted to explain how startups unseat incumbents; his jobs-to-be-done framework is something like an atomic theory for appealing startup opportunities. Eric Reis’s The Lean Startup framed startups as laboratories and entrepreneurs as scientists testing product hypotheses.
We’ve even come to simple, “universal” definitions for the goal of business—maximizing shareholder value—and the fundamental value of businesses: their expected future cash flows.
Why has this way of looking at business been so appealing? First, it is undeniably helpful. Rigorous analytical thinking, reduction, and abstraction are critical to new products and technologies, and to the coordination of people and matter required to operate any kind of business—especially large ones. Second, the total elimination of uncertainty is, for some, the holy grail of business. Guaranteed return, no risk—that would be a great business indeed. An infinite money machine, where all you have to do is pull the lever.
If that’s what you’re looking for—elimination of uncertainty—it is appealing to look for some form of authority to tell you what to do. Science and logic carry the most authority in the modern world. And just like nobody ever got fired for buying IBM, nobody ever got fired for being too scientific, rigorous, and analytical in their thinking.
But as much as reduction and rigorous thinking can be helpful—or even critical—in business, our attempts to turn it into a science like physics are mostly window-dressing, just like our attempts with social sciences in academia.
Many paths to the same result, the same paths to different results
Complex systems like neural networks or human psychology exhibit what’s called equifinality—where many paths can lead to the same result—and multifinality—where the same path can lead to very different results. This applies to business as well.
Take Christensen’s theory of disruption. It mapped quite well to disk drives and steel mills in the late 1980s and early 1990s, where established companies focused on high-end customers while new entrants captured the low end before moving upmarket. However, this pattern doesn't always hold true. Apple's iPhone, for instance, entered at the high end of the market and maintained that position. Netflix started by competing directly with Blockbuster's core business. Disruption theory is useful, but it's less a universal law like gravity and more of a helpful heuristic.
Conversely, copying successful strategies often fails. When JC Penney hired Apple's retail chief Ron Johnson, they attempted to replicate Apple's retail strategy—but the same approach that worked brilliantly for Apple led to disaster for JC Penney.
Business principles are usually anecdotes presented as axioms. Anecdotes—stories—are incredibly valuable. But they get misused when they are assumed to be general laws. In business, what’s most important is to be able to see the landscape clearly for yourself. It’s helpful to know theory and to know history—to take bits and pieces of what has worked for others and apply them to your situation—but usually the best businesses are hard to explain in terms of the past, just like paradigm-shifting scientific ideas are hard to explain in terms of previous theories.
Why is this?
For one, controlled experiments are close to impossible in business. Sure, you can A/B test a headline or a product’s price, but what you choose to test is significantly more important than which test wins. You and I can both use the same A/B testing tool as Mr. Beast to find which YouTube thumbnails will perform better, but Mr. Beast’s will win because he knows the frame or context for a good experiment far better than we do—and what a good frame is must always be partially inexplicit and subject to change.
Beyond that, you can't A/B test major strategic decisions. You can't simultaneously run a company with two different CEOs or expand into two different markets with the exact same resources. The complexity of business environments, with countless variables from market conditions to employee dynamics, makes true scientific experimentation impractical. As a result, cause and effect are very difficult to establish.
For another, business systems exhibit what chaos theorists call “sensitive dependence on initial conditions”—the famous butterfly effect. A small difference in timing, a slight variation in market conditions, or a minor change in team dynamics can completely alter the trajectory of a business decision. These changes can be so small as to be imperceptible; what appears to be the same situation can evolve, over time, into an entirely different outcome.
This points to an even deeper challenge with business laws and principles: They only hold under certain conditions, but those conditions can never be fully specified in advance. Not only does disruption theory not work in the case of the iPhone, but we can't create an exhaustive list of when it will or won't work.
New factors and forces constantly emerge that can invalidate previously reliable principles. Sometimes these are dramatic—like how a global pandemic suddenly made remote-first companies viable in ways that defied conventional wisdom about organizational culture. But often the changes are more subtle: gradual shifts in consumer behavior, technological capabilities, or competitive dynamics that accumulate until, seemingly overnight, old rules no longer apply.
Even more challenging is that the conditions that make a principle work or fail aren't just about external factors but complex interactions between multiple variables. Netflix succeeded by directly competing with Blockbuster because of the specific combination of its team's capabilities, Blockbuster's weaknesses, shifting consumer preferences, and the evolution of broadband infrastructure. Change any one of those variables slightly, and Netflix might not be the dominant streaming platform it is today.
This is why business principles are simultaneously useful and dangerous. They help us make sense of patterns we observe, but the moment we treat them as universal laws, we become blind to what makes them work or fail in any given situation. The key is not to abandon principles entirely, but to hold them loosely—always ready to notice anomalies that signal the game has changed.
Perhaps most challenging of all is the inherent subjectivity in business. Entrepreneurs are encouraged to think objectively about which problems to solve, to do customer research like scientists. But customers rarely tell you directly what to build. Figuring out what people want—really want—calls for grasping two principles from our new worldview: context as priceless and knowledge as participatory. The context of a customer's response is shaped powerfully by what you put in front of them. What you put in front of them is a creative act. And the participatory, creative nature of this process is as essential in business as it is in science, as it is in other areas of life.
This difficulty in creating controlled experiments, sensitivity to initial conditions, vulnerability to hidden exceptions, and the essentially creative nature of new product innovation means that when we call something a “law” of business or a “force,” we’re talking about something inherently different than what we mean when we talk about laws in physics or chemistry. Business "laws" are more like patterns or tendencies that we observe, but they don't have the same predictive power or universal applicability.
So how do we deal with this?
I’m writing a book about the worldview I’ve developed by writing, coding, and living with AI. Last week I published the second piece from it, about how AI will impact science. Here’s the third, about how AI will impact business.—Dan Shipper
Was this newsletter forwarded to you? Sign up to get it in your inbox.
As a young entrepreneur, I once thought of myself as an information processing machine. I got interested in mental models like Clay Christensen’s disruption theory and Ray Dalio's Principles. I took copious notes and spent countless hours organizing them; I felt tremendous pressure to memorize these “rules” so that I could apply them in my business life.
But in doing all this intellectual work, I had a nagging feeling: How would I remember to apply them in the situation that demanded it?
I also saw entrepreneurs around me trying to apply similar rules, with mixed success. It sounds like a bad joke: A Wharton student goes to their first class on negotiation and learns about anchoring, then walks into their next negotiation proposing a price that's 10 times too high because they think it'll properly anchor the potential customer when instead it just pisses them off.
We’re not the only entrepreneurs and capitalists who envy science and rationality and try to apply it to business.
In the late 1700s, Adam Smith, explicitly inspired by Isaac Newton, attempted to discover universal laws of economics—and popularized the idea of the market’s invisible hand. In the early 20th century, Frederick W. Taylor attempted to optimize businesses scientifically, proposing that workers should be studied like machines, with every motion analyzed and improved for maximum efficiency. In the 1970s, Michael Porter’s “Five Forces” framework tried to explain business success as a factor of elementary forces like the bargaining power of suppliers and the threat of new entrants. Christensen’s disruption theory attempted to explain how startups unseat incumbents; his jobs-to-be-done framework is something like an atomic theory for appealing startup opportunities. Eric Reis’s The Lean Startup framed startups as laboratories and entrepreneurs as scientists testing product hypotheses.
We’ve even come to simple, “universal” definitions for the goal of business—maximizing shareholder value—and the fundamental value of businesses: their expected future cash flows.
Why has this way of looking at business been so appealing? First, it is undeniably helpful. Rigorous analytical thinking, reduction, and abstraction are critical to new products and technologies, and to the coordination of people and matter required to operate any kind of business—especially large ones. Second, the total elimination of uncertainty is, for some, the holy grail of business. Guaranteed return, no risk—that would be a great business indeed. An infinite money machine, where all you have to do is pull the lever.
If that’s what you’re looking for—elimination of uncertainty—it is appealing to look for some form of authority to tell you what to do. Science and logic carry the most authority in the modern world. And just like nobody ever got fired for buying IBM, nobody ever got fired for being too scientific, rigorous, and analytical in their thinking.
But as much as reduction and rigorous thinking can be helpful—or even critical—in business, our attempts to turn it into a science like physics are mostly window-dressing, just like our attempts with social sciences in academia.
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Many paths to the same result, the same paths to different results
Complex systems like neural networks or human psychology exhibit what’s called equifinality—where many paths can lead to the same result—and multifinality—where the same path can lead to very different results. This applies to business as well.
Take Christensen’s theory of disruption. It mapped quite well to disk drives and steel mills in the late 1980s and early 1990s, where established companies focused on high-end customers while new entrants captured the low end before moving upmarket. However, this pattern doesn't always hold true. Apple's iPhone, for instance, entered at the high end of the market and maintained that position. Netflix started by competing directly with Blockbuster's core business. Disruption theory is useful, but it's less a universal law like gravity and more of a helpful heuristic.
Conversely, copying successful strategies often fails. When JC Penney hired Apple's retail chief Ron Johnson, they attempted to replicate Apple's retail strategy—but the same approach that worked brilliantly for Apple led to disaster for JC Penney.
Business principles are usually anecdotes presented as axioms. Anecdotes—stories—are incredibly valuable. But they get misused when they are assumed to be general laws. In business, what’s most important is to be able to see the landscape clearly for yourself. It’s helpful to know theory and to know history—to take bits and pieces of what has worked for others and apply them to your situation—but usually the best businesses are hard to explain in terms of the past, just like paradigm-shifting scientific ideas are hard to explain in terms of previous theories.
Why is this?
For one, controlled experiments are close to impossible in business. Sure, you can A/B test a headline or a product’s price, but what you choose to test is significantly more important than which test wins. You and I can both use the same A/B testing tool as Mr. Beast to find which YouTube thumbnails will perform better, but Mr. Beast’s will win because he knows the frame or context for a good experiment far better than we do—and what a good frame is must always be partially inexplicit and subject to change.
Beyond that, you can't A/B test major strategic decisions. You can't simultaneously run a company with two different CEOs or expand into two different markets with the exact same resources. The complexity of business environments, with countless variables from market conditions to employee dynamics, makes true scientific experimentation impractical. As a result, cause and effect are very difficult to establish.
For another, business systems exhibit what chaos theorists call “sensitive dependence on initial conditions”—the famous butterfly effect. A small difference in timing, a slight variation in market conditions, or a minor change in team dynamics can completely alter the trajectory of a business decision. These changes can be so small as to be imperceptible; what appears to be the same situation can evolve, over time, into an entirely different outcome.
This points to an even deeper challenge with business laws and principles: They only hold under certain conditions, but those conditions can never be fully specified in advance. Not only does disruption theory not work in the case of the iPhone, but we can't create an exhaustive list of when it will or won't work.
New factors and forces constantly emerge that can invalidate previously reliable principles. Sometimes these are dramatic—like how a global pandemic suddenly made remote-first companies viable in ways that defied conventional wisdom about organizational culture. But often the changes are more subtle: gradual shifts in consumer behavior, technological capabilities, or competitive dynamics that accumulate until, seemingly overnight, old rules no longer apply.
Even more challenging is that the conditions that make a principle work or fail aren't just about external factors but complex interactions between multiple variables. Netflix succeeded by directly competing with Blockbuster because of the specific combination of its team's capabilities, Blockbuster's weaknesses, shifting consumer preferences, and the evolution of broadband infrastructure. Change any one of those variables slightly, and Netflix might not be the dominant streaming platform it is today.
This is why business principles are simultaneously useful and dangerous. They help us make sense of patterns we observe, but the moment we treat them as universal laws, we become blind to what makes them work or fail in any given situation. The key is not to abandon principles entirely, but to hold them loosely—always ready to notice anomalies that signal the game has changed.
Perhaps most challenging of all is the inherent subjectivity in business. Entrepreneurs are encouraged to think objectively about which problems to solve, to do customer research like scientists. But customers rarely tell you directly what to build. Figuring out what people want—really want—calls for grasping two principles from our new worldview: context as priceless and knowledge as participatory. The context of a customer's response is shaped powerfully by what you put in front of them. What you put in front of them is a creative act. And the participatory, creative nature of this process is as essential in business as it is in science, as it is in other areas of life.
This difficulty in creating controlled experiments, sensitivity to initial conditions, vulnerability to hidden exceptions, and the essentially creative nature of new product innovation means that when we call something a “law” of business or a “force,” we’re talking about something inherently different than what we mean when we talk about laws in physics or chemistry. Business "laws" are more like patterns or tendencies that we observe, but they don't have the same predictive power or universal applicability.
So how do we deal with this?
Seeing business like a language model
We train a language model by feeding it a line of text and asking it to complete the next word given the context. It tries over and over again to complete the next word. And over millions and millions of trials it learns the countless implicit, subtle patterns that govern which word comes next.
Successful founders and executives do something similar. They put themselves repeatedly in the kinds of contexts that they are trying to master. They generate a response to that context and learn from the results. Over years and years and years of trial and error, they learn to build an intuitive awareness that tells them what to do next in important situations.
A simple way of saying this is that most of business is about generating an intuition for the right response to the situation at hand. What might seem, on the surface, like “rules” by which successful founders and executives behave are really only shadows of what those leaders know. And how these rules are applied changes in subtle and important ways in the myriad contexts in which they are used.
It doesn't mean that learning, reading, principles, or any kind of more theoretical knowledge isn't important for business. Instead, when we see like a language model, we understand that learning happens through both experience and theoretical knowledge in tandem. We build our intuition through repeated exposure to real situations, while using principles and mental models to refine our understanding. This dual approach helps us develop a more nuanced grasp of business dynamics, much like how language models improve through both training data and algorithmic refinement. The key is finding the right balance between practice and theory.
It also implies a few ideas for how we should undertake building businesses. (Based on what I’ve just written, you should assume these ideas to be context-sensitive and informed by my own particular experience, rather than universal.)
Context is king
Because what you learn is so sensitive to context, putting yourself in the actual environment that you want to learn about is perhaps the most important skill in business. This is harder than it might seem.
For one, it’s emotionally difficult. For example, if you want to learn how to sell a product, you have to put yourself in front of a customer and risk looking silly. If you want to learn how to come up with ideas that sound crazy but might actually work, you have to invent them repeatedly and execute on them while facing ridicule.
For another, the contexts that you want to learn about are often near-inaccessible. For example, it's hard to access the context of being a CEO of a 10-person startup. You need to play a lot of levels of the game before you get there. You can read accounts of it or can talk to friends about it, but it's truly different when you're in that situation.
You actually need to see the context
Even when you can access a particular context, it can be hard to see.
A common pitfall of knowing a lot about the history of business or seeking lots of advice, or listening to lots of podcasts or keeping up with the latest start-up trends, is that they cloud your ability to see the context in front of you. You end up spending a lot of time trying to be the kind of founder you think you’re supposed to be, trying to build the kind of company that you think you're supposed to build, and usually those models you have in your head are patterned from contexts that are different from yours.
A lot of entrepreneurship is taking the scary step of admitting who you are (which is usually pretty different from the average entrepreneur) and risking looking foolish by observing the context you find yourself in—and responding to that, instead of what you hope is there or think is supposed to be there). You’ll risk failure and looking silly, but in the end, it's the most important ingredient to doing something unique and valuable.
Advice is anecdote
This doesn't mean you should ignore advice or not read business books, though. Instead, look at advice, principles, theories, and frameworks as anecdotes that come from contexts. To the extent the person giving you the advice or the framework comes from a context that's similar to yours, you can take things that seem useful—but you should be on the lookout for when their situation quietly stops resembling yours.
You want the theoretical explanations and stories that you read to connect to and modify the rich history of experiences that are stored in your brain—but you can only do that if the experiences are there to connect to. Otherwise, they’ll connect to other, unrelated things, and you’ll come to the wrong conclusions.
Luckily, the stakes here are low. Pick and choose. Try what you like, and discard the rest. Be wary of those who claim to have discovered fundamental general laws of business. They're usually overselling it.
This is one of the places where literature and biography shine over the austere framework-driven business books you see at the airport. The latter might be easier to get through, but they lack the richness needed to truly help you. Better to seek advice from sources that come with enough context to help you see where and how it might apply.
Find people who feel right
Another corollary to “context is king” and “advice is anecdote” is that it matters who you take advice from. In a best-case scenario, the advice comes from someone like you, just a couple steps further down the road. In a worst-case scenario, it comes from someone who is completely different in terms of personality, values, and style, and you end up aping them instead of doing something that's organically you.
This is a process of feeling. See how you feel with different kinds of people, and what those feelings tend to mean over time. You'll start to feel when people who have a common outlook and a common style—and those are people who can help you. You can also learn a lot from people who are unlike you, but be careful of blindly following their strategies.
Don't do half a push-up
Being in the right context and seeing it clearly, though, isn't enough. In order to truly learn, you have to go from start to finish.
Take another cue here from how language models work: They predict complete tokens one at a time, and they either output the next word/token or they don’t. Similarly in business, partial completion often teaches you very little. You need to experience complete cycles of action to learn the patterns that matter. Twenty half-finished apps on your hard drive is like doing half a push-up or outputting 80 percent of a token. It just doesn’t teach you that much.
Trust your gut
What you're really trying to develop through all of this is your gut. It's an instinctive feel for what to do in any given situation. Your gut has to be developed, yes, and it’s developed through repeated experience. But it’s also developed through self-discovery and self-understanding. Trusting your gut means knowing who you are.
In many ways, the companies that get built are reflections of the entrepreneurs that build them. Apple is not spiritual about design and allergic to compromise without Steve Jobs. Microsoft is not methodical, dominant, and a little nerd-ruthless without Bill Gates.
In many ways, building a company is the process of finding and becoming authentically yourself.
This arises from repeated exposure to reality and repeated self-reflection, not one or the other.
Another way to frame all of what we've said so far is to become your own authority. Master the art of keeping some amount of attention on the world, and some amount of attention on yourself and what you hope to achieve. Be honest with yourself and with the world about what that is, come what may.
Usually that's what all of the theorizing about entrepreneurship is rooted in anyway. As I said at the top, when we're facing uncertainty, which all entrepreneurs have to do, it’s natural to look for some authority to help us resolve it. And for us the most obvious authority is logic and rationality—in the methods of science.
But great entrepreneurs learn to embrace the uncertainty—to use it as a call to creativity and vision, and help them forge ahead and find themselves.
Wayfinding not planning
For all the reasons that we've already discussed, the business world is incredibly difficult to predict. Traditional business planning often falls short because market conditions, technology, and consumer preferences change rapidly. Instead of rigid plans, successful entrepreneurs develop a skill for what the venture capitalist and entrepreneur Reid Hoffman calls wayfinding. (Disclosure: Reid Hoffman is an investor in Every.)
Wayfinding is the art of finding your path in conditions where you can't see very far ahead. Unlike planning, which assumes you can map out the whole journey from start to finish, wayfinding means taking a few steps, looking around carefully, and then deciding your next move based on what you discover.
You might have a general direction in mind—”west toward the mountains”—but the specific path emerges through constant observation and adjustment. Sometimes you backtrack when you hit obstacles; other times you spot an unexpected opportunity and change course entirely. The key is maintaining enough forward momentum to learn from real feedback while staying flexible enough to adapt your route as the landscape becomes clearer.
Buy duration
Another implication is that the longer you can spend doing this and the more time you can give yourself, the higher your chances are of success. This view runs counter to the pervasive Silicon Valley narrative that you should start a company, raise as much money as possible, and find out as quickly as possible whether or not it's going to work (and if it works, go public quickly; if not, crash and burn quickly.)
There are certainly times in business when aggressive moves are critical. Speed is important, too. But you can move quickly from experiment to experiment with a great deal of patience for a long duration of time, and that's different from going all-in on your first hand.
Because of the importance of context and how difficult it is to learn from the most important contexts, the best way to be successful in business is always to buy duration—to give yourself enough time to try building products over and over and over again until something finally works.
There are many paths to God—and success
There's an old Hasidic story about Rabbi Baer of Radoshitz, who asked his teacher, the Seer of Lublin, “Show me one general way to the service of God.”
The Zaddik replied, “It is impossible to tell men what way they should take. One way to serve God is through learning, another through prayer, another through fasting, and so another through eating. Everyone should carefully observe what way his heart draws him to and then choose this way with all his strength.”
If we learn to see business like a language model, we see that it’s ultimately about finding your own particular path. There is no shortcut to this process; you embrace your unique journey while remaining adaptable and open to learning. Some entrepreneurs succeed through methodical analysis, others through bold intuition. Some build slowly and steadily, others create rapid breakthrough innovations. The key is discovering which approach aligns with your authentic self while remaining grounded in market realities.
Just as there are countless paths to enlightenment, there are numerous valid ways to build a successful business and leave your mark on the world.
What comes next
Next week, in my final piece in this series, we’ll explore how creativity and creative work change when you see them like a language model.
Read the first two pieces in this series, about the new worldview enabled by AI and how AI will impact science.
Dan Shipper is the cofounder and CEO of Every, where he writes the Chain of Thought column and hosts the podcast AI & I. You can follow him on X at @danshipper and on LinkedIn, and Every on X at @every and on LinkedIn.
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Great article. Taking copious notes on Principles or Clay Christensen definitely resonates. I also took courses on PM frameworks such as Blue Ocean etc. It's all good stuff post mortem but the reality is with entrepreneurship... wayfinding per Hoffman or iterative testing based on current conditions is the only way to really move one step forward and closer to the desired outcome.
You've made a compelling case for why "laws" of business are not "laws" in any reasonable interpretation of that word. How axioms, etc. repeatedly fail. You've also well-illustrated how approaching business like now do with LLMs, next move prediction, is a compelling alternative. But you're also trying to say the old rules are still useful, and I feel like that case is much less well-illustrated and supported here. You essentially say "they're still useful just like this thing in LLMs" but not really how, nor why they are compelling in addition to the next-move prediction approach.
I would postulate that most - if not all - business rules are essentially bullshit post-hoc justifications made to either make someone sound smarter/make money on their book/consulting service, or made to make everyone feel more secure about the near-chaos that starting and running businesses actually is (most of the time it's probably both). What's the compelling case for that not being so?
I also feel like the ineffable role of seemingly innate differences in intuition (or other business-critical capability such as decisiveness, etc.) isn't well covered here. Do we have confidence that starting conditions and innate ability *for founders* aren't perhaps literally the most important thing? How much of business success analysis is simply survivorship bias being over-intellectualized? Obviously examples like Jobs and Gates are outliers, but both of them seemed to be "who they were" from early on, Jobs with a strong innate intuition and intense opinions about how things should be from the time he was a teenager. Likewise Gates with the traits that made him successful. Now they're extremes, but that doesn't necessarily mean the same things aren't true about many or most founders if you look closely enough... Or maybe not! 😄 But it seems worth addressing in the context of this line of thinking.
My kingdom for an Edit button! 😅
@Oshyan these are great questions.
1. on most or all business rules being essentially bullshit -> I think if you pursue that case to its logical conclusion you end up saying that skill in business is not a thing, and people get where they are purely because of luck. business rules ARE bullshit when they are portrayed as being universal and comprehensive, but they are NOT bullshit when an experienced practitioner (who has an intuitive, tacit sense of what they actually mean and in what contexts they apply) uses them
2. to be sure starting conditions and innate ability for founders are important, but consider the case where Steve Jobs wasn't able to learn ANYTHING after age 22. like, Steve Jobs as an actual LLM. he would obviously not have achieved what he went on to achieve imo
@danshipper Yes, I'm certainly not trying to make the case that experience does not matter at all. Nor am I actually saying with total confidence that starting conditions are the *most* significant predictor, though I think it's an important consideration to raise in this kind of conversation. I'm being a little provocative but with genuine belief in this possibility and interest in the reality, too.
Regarding business rules, in your scenario of an experienced practitioner, how do you separate out the difference between the rules they express/cite/espouse being merely a post-hoc rationalization of their internal understanding (that may or may not map to some reusable truth, and undoubtedly has significant limits without their internal intuition) and the rules actually being something that they followed to reach their success? Did so and so learn about x business rule and then succeed more greatly because of that? Or did they just pick some rules that mapped reasonably well to their understanding of their own success journey when someone asked them how they succeeded?
I'm not saying it's never the case that someone learns one or more useful business rules and then succeeds dramatically because of that, but I'm interested in how much of the time it does happen because entire industries are built around these kinds of beliefs about business rules, market behaviors, etc. and it feels worth questioning.
I resonated with every words you said. I just came out of GSB and I also find it very dangerous to treat business principles - distilled from a particular business leader's personal pattern recognition - biased by their own experience, as the universal principle.
What you said about finding your own path and way finding also resonated a LOT. For me, this means "Founder-Product" fit. Why am "I" doing this? / What does building this mean to "me"? are questions that I often deprioritize until now. In your previous podcast, you shared how you pivoted from a traditional venture-backed model, to prioritize what makes you more you by writing, and shaping your business around it, that was truly remarkable, and empowering.
I find you the exact person who's similar but many steps down the road, would love to connect and buy you a coffee in SF if you are open to share what I'm building.