Founders love to show off huge TAM slides, but it's a vanity metric. I'll argue for a more focused, practical approach to market sizing that proves you can dominate a niche before you conquer the world.
The Counterintuitive Truth
In AI market sizing, the best practitioners often do less, not more.
The lesson: the data tells a different story than your gut. It sounds simple. It's incredibly hard to execute.
What I've Learned From 93 Companies
A few patterns in AI market sizing come up again and again.
The founders who handle AI market sizing well understand that timing is everything in this game.
What I Tell Founders
Before deciding anything about AI market sizing, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around AI exit strategies, AI competitive moats, AI pitch decks 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: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: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: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.