Most of what you've read about i sold my ai company for $100m+. here is wrong. I know because I believed it too, and it cost me.
Selling my AI company was the hardest and most rewarding thing I've ever done. I'm pulling back the curtain on the 5 non-obvious strategies I used to maximize our valuation and secure a life-changing exit.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to i sold my ai company for $100m+. here are fundamentally flawed. Not slightly off. Fundamentally flawed.
The root cause is usually one of three things:
- Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
- Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
- Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The Counterintuitive Truth
Here's what surprised me most about i sold my ai company for $100m+. here: the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that the data tells a different story than your gut. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
When a founder in my portfolio asks me about i sold my ai company for $100m+. here, I usually 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 startup pivots, AI competitive moats, AI due diligence that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about i sold my ai company for $100m+. here: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at i sold my ai company for $100m+. here share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
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.
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.
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 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.