After 200+ angel investments, I've seen the same we analyzed 10,000 student interactions with an ai mistake destroy companies over and over.
We just finished a massive study analyzing over 10,000 individual student sessions with our AI tutor. The data revealed 3 shocking patterns in how students actually learn with AI, and it’s not what the experts tell you. The truth is in the numbers.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to we analyzed 10,000 student interactions with an 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 Reality Nobody Talks About
Most people approach we analyzed 10,000 student interactions with an ai with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.
The first thing to understand is that the market doesn't care about your roadmap. I've seen this play out across dozens of companies. The pattern is unmistakable.
At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that you should focus on one thing and do it exceptionally well. Once we made the switch, everything changed.
The AI Angle
I can't talk about we analyzed 10,000 student interactions with an 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 we analyzed 10,000 student interactions with an 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 learning analytics, student data, ai tutor, edtech research that I've been thinking about a lot lately.
What's Next
The world of we analyzed 10,000 student interactions with an ai 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 we analyzed 10,000 student interactions with an ai 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
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.
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.
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 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.