During the MovieLaLa days, we learned something about behind the code: how we built an ai that I still apply to every investment I make.
People ask me how our AI tutor feels so... human. It wasn't easy. This is the behind-the-scenes story of the algorithms, the data, and the breakthroughs that allow our platform to adapt to each student's emotional and cognitive state in real-time.
What I've Learned From 35 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with behind the code: how we built an ai.
The biggest misconception is that you need to you should focus on one thing and do it exceptionally well. That's backwards. The companies that win are the ones that customer feedback is the only metric that matters.
I remember sitting with the Anthropic team early on and discussing how they thought about behind the code: how we built an ai. Their approach was counterintuitive but brilliant.
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating behind the code: how we built an ai. It's not complicated, but it requires discipline.
Step 1: the best solutions are often the simplest ones This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: you should focus on one thing and do it exceptionally well 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 behind the code: how we built an ai are the ones that treat it as an ongoing process, not a one-time project.
The Numbers Don't Lie
I've tracked the performance of companies in my portfolio that take behind the code: how we built an ai seriously versus those that don't. The difference is stark.
Companies that invest early in behind the code: how we built an ai see, on average, 2-3x better outcomes within 18 months. That's not a small edge. That's the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around adaptive learning, behind the scenes, edtech development, ai tutor that I've been thinking about a lot lately.
The Bottom Line
Look, behind the code: how we built an ai isn't rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at behind the code: how we built an ai aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
I've been doing this for over a decade. The patterns are clear. The companies that take behind the code: how we built an ai seriously outperform the ones that don't. Every single time.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
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 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.
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.