The classic VC line “ideas are a dime a dozen” was true in a world where execution was scarce, slow, and expensive. In that regime, the idea itself mattered less than the team’s ability to grind through years of uncertainty and operational friction.
AI changes that regime.
We are approaching an inflection point where execution is increasingly cheap, fast, and commoditized. Code, design, copy, analysis, even early go-to-market are no longer the bottleneck they once were. If execution is no longer scarce, then the old wisdom collapses — and with it the framing of what actually creates value in a startup.
This connects directly to the article’s distinction between “painful problems” and contradictions. Painful problems live inside the existing frame. They assume the world is correctly explained and ask how to optimize within it. In an AI world, those problems will be attacked by thousands of teams simultaneously, because cheap execution makes incremental improvement easy and crowded.
Breakthroughs, by contrast, come from identifying where reality and conventional thinking have diverged — where something works (or fails) that should not, according to the dominant explanation. That is not an execution problem. It is a perception problem.
What becomes valuable, then, is not “the idea” in isolation, and not execution in the classical sense, but the ability to:
• identify a real inflection in the world,
• notice the contradiction it creates with prevailing beliefs,
• form a new explanatory model that makes the anomaly make sense,
• and articulate it as a coherent narrative or movement that others can align around.
AI doesn’t eliminate the value of ideas; it shifts the value toward a very specific kind of idea: one that re-frames reality rather than optimizes within it.
If both ideas-as-features and execution-as-labor are commoditized, what remains scarce is agency grounded in insight — the willingness and ability to act on a non-consensus explanation of the world before it is socially validated. That is exactly what the article describes as the monopoly window.
@Mike Maples, Jr you nailed it! "Most see noise, or an exception that seems OK to ignore. But one person sees a crack in the foundation of how everyone thinks. The difference isn’t better eyesight. It’s a different way of seeing.
“Notice what other people don’t see.” - Rick Rubin
I like the Deutsch reference from The Beginning of Infinity: “patches” protecting bad explanations. I've been applying Deutsch's epistemology to product development for years, and your framing of contradictions vs. conventional pain is the cleanest articulation I've seen of why much product advice fails. Pain points keep you inside the current frame while contradictions reveal that the frame is wrong.
What I've been working on is this: If bad explanations of reality create startup opportunities, what's the explanatory theory of product development itself? What causes products to succeed or fail?
My answer: Everybody agrees that successful products solve the right customer problems right. But most product teams can't distinguish customer problems (actual situations people face) from solutions (current approaches to those situations). They collect pain points and feature ideas, but both of them are solution-shaped. Pain points indicate poor fit between existing solutions and the underlying problems, and features ideas are solutions.
When you spot a contradiction, you have found evidence that the prevailing explanation is wrong. The next step is building a better explanation, which first requires understanding the actual problem space the contradiction revealed. That’s not about imagination: it requires systematic investigation. If you know how to systematically look at problems independently of any solutions, you can reason about what an optimal solution must look like - from outside the current frame.
I’m curious if this resonates with how you think about what founders do after they find the crack in the rules.
We are moving from innovation as domination to innovation as governance. If execution and capital are abundant, then the future belongs to those who can design explanations that remain true when incentives are stripped away. Restraint is essential - and this is where age is an advantage :-). Great article.
Reading your piece, it immediately struck me that the cognitive framing you are describing is exactly how my autistic brain works...it sees everything as systems (literally everything that exists, from the smallest to the largest spatial and temporal scales, are layers of systems), notes when a system error occurs, and investigates the reason for the error to better understand the system's functioning, boundary constraints, network connections, efficiencies, resource utilization, etc. Being a "systems thinker" is what Simon Baron-Cohen describes in his 2006 paper titled "Two new theories of autism: hypersystemising and assortative mating" ( https://www.researchgate.net/publication/7400359_Two_new_theories_of_autism_Hyper-systemising_and_assortative_mating ). He lays out a 7-level "systemising mechanism" scale where the "sweet spot"—highly analogous to the cognitive framing your piece advocates for—is in the SM-4 to SM-5 part of the range (which is where I sit).
I am grateful to have this particular manifestation of autism, but it is a razor-sharp, double-edged sword. I won't blather on about why that is so. My point in sharing this information is to suggest that systems-thinking autistics in the SM-4/5 range could be a huge asset in the VC/startup world because they are already neurologically wired in a beneficially adaptive way.
I've created a mental framework that helps me analyze and see problems and investigate solutions where others overlook. Let me apply it to this post. value is created Ideas and solutions follow a life cycle ranging from "genesis" through "custom build" and "product" to "commodity". The "value" of an idea or solution can be invisible or visible depending on the observer frame of mind, but there is a need.
What I am describing is Wardley Map which a great tool for what described Mike described in this post. I have found it to be a great tool for abstract thinking using AI to uncover invisible value that others don't see or think is impossible to solve. I've created a cognitive framework to uncover problems and solutions. AI makes execution a "commodity" value now has shifted to the "genesis/custom build" ideation phase of technology. Mike I'd like to see your ideas formalized using Wardley Map analysis.
Great explanation -- this is why I always kinda hated "the mom test" way of verifying problems exist. What do you think? If you have a solution to a reality everyone is ignorning, a Mom test won't even reveal that there is a problem...
I guess it's find at identifying real problems, "hotels are too far away / expensive," but can very much limit the solution if the founder tries to solve those problems within today's way of thinking.
Anyway... may I challenge on your core idea? ... is this actually true? Do "the best startups" all think outside the box?
Harder-to-vary might swap "best" startups for "largest market cap"... and if you went through a list of largest market cap stocks today, would their origin story all follow this rule of a a solution to a contradiction in the way most people view the world?
Or would a good chunk of them just be conventional problem-solvers?
I really enjoyed this, thank Mike. The idea that progress comes from challenging the explanation of reality — not just optimizing within it — feels especially true in practice.
The classic VC line “ideas are a dime a dozen” was true in a world where execution was scarce, slow, and expensive. In that regime, the idea itself mattered less than the team’s ability to grind through years of uncertainty and operational friction.
AI changes that regime.
We are approaching an inflection point where execution is increasingly cheap, fast, and commoditized. Code, design, copy, analysis, even early go-to-market are no longer the bottleneck they once were. If execution is no longer scarce, then the old wisdom collapses — and with it the framing of what actually creates value in a startup.
This connects directly to the article’s distinction between “painful problems” and contradictions. Painful problems live inside the existing frame. They assume the world is correctly explained and ask how to optimize within it. In an AI world, those problems will be attacked by thousands of teams simultaneously, because cheap execution makes incremental improvement easy and crowded.
Breakthroughs, by contrast, come from identifying where reality and conventional thinking have diverged — where something works (or fails) that should not, according to the dominant explanation. That is not an execution problem. It is a perception problem.
What becomes valuable, then, is not “the idea” in isolation, and not execution in the classical sense, but the ability to:
• identify a real inflection in the world,
• notice the contradiction it creates with prevailing beliefs,
• form a new explanatory model that makes the anomaly make sense,
• and articulate it as a coherent narrative or movement that others can align around.
AI doesn’t eliminate the value of ideas; it shifts the value toward a very specific kind of idea: one that re-frames reality rather than optimizes within it.
If both ideas-as-features and execution-as-labor are commoditized, what remains scarce is agency grounded in insight — the willingness and ability to act on a non-consensus explanation of the world before it is socially validated. That is exactly what the article describes as the monopoly window.
@Mike Maples, Jr you nailed it! "Most see noise, or an exception that seems OK to ignore. But one person sees a crack in the foundation of how everyone thinks. The difference isn’t better eyesight. It’s a different way of seeing.
“Notice what other people don’t see.” - Rick Rubin
This is exactly what I needed to forge ahead with my new idea in 2026 🙌
Thank you 🙏
I like the Deutsch reference from The Beginning of Infinity: “patches” protecting bad explanations. I've been applying Deutsch's epistemology to product development for years, and your framing of contradictions vs. conventional pain is the cleanest articulation I've seen of why much product advice fails. Pain points keep you inside the current frame while contradictions reveal that the frame is wrong.
What I've been working on is this: If bad explanations of reality create startup opportunities, what's the explanatory theory of product development itself? What causes products to succeed or fail?
My answer: Everybody agrees that successful products solve the right customer problems right. But most product teams can't distinguish customer problems (actual situations people face) from solutions (current approaches to those situations). They collect pain points and feature ideas, but both of them are solution-shaped. Pain points indicate poor fit between existing solutions and the underlying problems, and features ideas are solutions.
When you spot a contradiction, you have found evidence that the prevailing explanation is wrong. The next step is building a better explanation, which first requires understanding the actual problem space the contradiction revealed. That’s not about imagination: it requires systematic investigation. If you know how to systematically look at problems independently of any solutions, you can reason about what an optimal solution must look like - from outside the current frame.
I’m curious if this resonates with how you think about what founders do after they find the crack in the rules.
We are moving from innovation as domination to innovation as governance. If execution and capital are abundant, then the future belongs to those who can design explanations that remain true when incentives are stripped away. Restraint is essential - and this is where age is an advantage :-). Great article.
Mike,
Reading your piece, it immediately struck me that the cognitive framing you are describing is exactly how my autistic brain works...it sees everything as systems (literally everything that exists, from the smallest to the largest spatial and temporal scales, are layers of systems), notes when a system error occurs, and investigates the reason for the error to better understand the system's functioning, boundary constraints, network connections, efficiencies, resource utilization, etc. Being a "systems thinker" is what Simon Baron-Cohen describes in his 2006 paper titled "Two new theories of autism: hypersystemising and assortative mating" ( https://www.researchgate.net/publication/7400359_Two_new_theories_of_autism_Hyper-systemising_and_assortative_mating ). He lays out a 7-level "systemising mechanism" scale where the "sweet spot"—highly analogous to the cognitive framing your piece advocates for—is in the SM-4 to SM-5 part of the range (which is where I sit).
I am grateful to have this particular manifestation of autism, but it is a razor-sharp, double-edged sword. I won't blather on about why that is so. My point in sharing this information is to suggest that systems-thinking autistics in the SM-4/5 range could be a huge asset in the VC/startup world because they are already neurologically wired in a beneficially adaptive way.
Chris Gaskins
I've created a mental framework that helps me analyze and see problems and investigate solutions where others overlook. Let me apply it to this post. value is created Ideas and solutions follow a life cycle ranging from "genesis" through "custom build" and "product" to "commodity". The "value" of an idea or solution can be invisible or visible depending on the observer frame of mind, but there is a need.
What I am describing is Wardley Map which a great tool for what described Mike described in this post. I have found it to be a great tool for abstract thinking using AI to uncover invisible value that others don't see or think is impossible to solve. I've created a cognitive framework to uncover problems and solutions. AI makes execution a "commodity" value now has shifted to the "genesis/custom build" ideation phase of technology. Mike I'd like to see your ideas formalized using Wardley Map analysis.
Great explanation -- this is why I always kinda hated "the mom test" way of verifying problems exist. What do you think? If you have a solution to a reality everyone is ignorning, a Mom test won't even reveal that there is a problem...
I guess it's find at identifying real problems, "hotels are too far away / expensive," but can very much limit the solution if the founder tries to solve those problems within today's way of thinking.
Anyway... may I challenge on your core idea? ... is this actually true? Do "the best startups" all think outside the box?
Harder-to-vary might swap "best" startups for "largest market cap"... and if you went through a list of largest market cap stocks today, would their origin story all follow this rule of a a solution to a contradiction in the way most people view the world?
Or would a good chunk of them just be conventional problem-solvers?
honestly i love the topic but despise the use of the statistical model in writing about it
I really enjoyed this, thank Mike. The idea that progress comes from challenging the explanation of reality — not just optimizing within it — feels especially true in practice.