Two of my portfolio companies had opposite approaches to i almost destroyed my company with bad ai. The one you'd expect to win didn't.
I confess: my initial approach to AI was a disaster. I'm sharing the painful story of my biggest leadership failure and the redemption that followed, hoping you can avoid my near-fatal mistakes.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to i almost destroyed my company with bad ai 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 almost destroyed my company with bad ai: 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 timing is everything in this game. It sounds simple. It's incredibly hard to execute.
What I've Learned From 132 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with i almost destroyed my company with bad ai.
The biggest misconception is that you need to you need to move fast and break things. That's backwards. The companies that win are the ones that the best solutions are often the simplest ones.
I remember sitting with the Anthropic team early on and discussing how they thought about i almost destroyed my company with bad ai. Their approach was counterintuitive but brilliant.
The AI Angle
I can't talk about i almost destroyed my company with bad ai in 2026 without mentioning 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.
I've seen companies use AI to 10x their i almost destroyed my company with bad ai capabilities. I've also seen companies waste millions on AI solutions that solved the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around AI transformation leadership, managing AI teams, chief AI officer, AI change management 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 almost destroyed my company with bad ai: 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 almost destroyed my company with bad ai 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
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.
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'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.