I review hundreds of pitch decks every year. The ones that get don't get screwed when you sell your ai company right stand out immediately.
The M&A negotiation table is a warzone. I'm sharing the tough lessons from selling my own company—the tricks, the tactics, and how to keep from getting steamrolled by corporate development teams who do this for a living.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to don't get screwed when you sell your ai company 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 Framework That Actually Works
I'm going to share the exact framework I use when evaluating don't get screwed when you sell your ai company. It's not complicated, but it requires discipline.
Step 1: most founders overthink this and underspend on execution This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the data tells a different story than your gut Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail don't get screwed when you sell your ai company are the ones that treat it as an ongoing process, not a one-time project.
The Counterintuitive Truth
Here's what surprised me most about don't get screwed when you sell your ai company: 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 customer feedback is the only metric that matters. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
When a founder in my portfolio asks me about don't get screwed when you sell your ai company, 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 due diligence, AI exit strategies, AI startup pivots, AI pitch decks, AI market sizing 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 don't get screwed when you sell your ai company: 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 don't get screwed when you sell your ai company 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
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
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.
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.