I wanted to share my perspective on this. Founders are experts at self-deception, especially when it comes to market size. I'll expose the most common lies and cognitive biases that lead to unrealistic projections and how to ground your numbers in reality.
The Counterintuitive Truth
In AI market sizing, the best practitioners often do less, not more.
The lesson: timing is everything in this game. It sounds simple. It's incredibly hard to execute.
The Reality Nobody Talks About
A lot of the advice on AI market sizing rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that the best solutions are often the simplest ones. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that customer feedback is the only metric that matters. Once they make the switch, everything changes.
What I've Learned From 101 Companies
A few patterns in AI market sizing come up again and again.
The founders who handle AI market sizing well understand that your team matters more than your technology.
The AI Angle
Any discussion of AI market sizing in 2026 has to include AI. As someone who's invested in Anthropic, OpenAI, Scale AI, and Hugging Face, I have a front-row seat to how AI is transforming this space.
The short version: AI makes good practitioners better and bad practitioners worse. It's an amplifier, not a replacement.
Some teams use AI to get far more out of AI market sizing. Others spend heavily on AI that solves the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around AI talent wars, AI due diligence, AI startup pivots, AI exit strategies that I've been thinking about a lot lately.
What's Next
Best practice in AI market sizing is changing fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
If you're building in this space, the best time to get AI market sizing right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
Frequently Asked Questions
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.