During the MovieLaLa days, we learned something about how we built a custom ai-powered a/b testing that I still apply to every investment I make.
Building an AI startup is anything but glamorous. I want to take you behind the curtain and share the unfiltered reality of our journey. From the heated debates over our roadmap to the bug that almost derailed our launch, this is the real story of what it takes to build and ship an AI product.
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating how we built a custom ai-powered a/b testing. It's not complicated, but it requires discipline.
Step 1: you need to move fast and break things This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: timing is everything in this game 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 how we built a custom ai-powered a/b testing 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 how we built a custom ai-powered a/b testing: 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 best solutions are often the simplest ones. It sounds simple. It's incredibly hard to execute.
Lessons From the Trenches
I want to share a few specific lessons I've picked up over the years. These aren't theoretical. They come from real companies, real failures, and real successes.
Lesson 1: The best time to start thinking about how we built a custom ai-powered a/b testing was yesterday. The second best time is now. Don't wait until you have the perfect plan.
Lesson 2: Hire for attitude, train for skill. The best how we built a custom ai-powered a/b testing practitioners I've met weren't the most technically gifted. They were the most curious and persistent.
Lesson 3: Your competitors are probably getting this wrong too. That's your opportunity. While everyone else is following the same playbook, you can zig when they zag.
This connects to broader themes around a/b testing ai, build vs buy, case study that I've been thinking about a lot lately.
What's Next
The world of how we built a custom ai-powered a/b testing is moving 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.
And if you're a founder building in this space, remember that the best time to get how we built a custom ai-powered a/b testing 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
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.
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.