After 200+ angel investments, I've seen the same what i learned investing $1m in robotics startups mistake destroy companies over and over.
A personal look at my journey investing in robotics startups.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to what i learned investing $1m in robotics startups 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 what i learned investing $1m in robotics startups: 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 market doesn't care about your roadmap. It sounds simple. It's incredibly hard to execute.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to what i learned investing $1m in robotics startups.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on what i learned investing $1m in robotics startups. I've seen plenty fail because they moved too slow.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. This sounds obvious but you'd be amazed how many founders build their what i learned investing $1m in robotics startups strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around humanoid robots, warehouse robots, drone AI, Figure AI 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 what i learned investing $1m in robotics startups: 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 what i learned investing $1m in robotics startups 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 would you do differently looking back?
I'd move faster on the things that were working and cut the things that weren't sooner. Most founders, myself included, hold onto failing strategies too long because of sunk cost. Speed of learning is everything.
Can these results be replicated?
The specific numbers will vary, but the underlying patterns and principles are transferable. The key is understanding the context behind the results, not just copying the tactics. Every company has unique constraints that shape what works.
What was the biggest challenge in this case?
Almost always, the biggest challenge is people and alignment, not technology or strategy. Getting the right team focused on the right problem is harder than any technical challenge I've encountered.
How long did it take to see results?
Most meaningful business results take 3-6 months to materialize. Anyone promising overnight success is selling something. The companies in my portfolio that grew fastest were the ones that stayed patient and consistent.