In my last year of university, I made a decision that shaped everything that followed.  I chose to become a Forward Deployed Engineer (FDE) instead of a traditional software engineer, and joined Palantir

The gap between what AI researchers know and what the rest of the world hears about is getting wider. New architectures, new scaling results, and new claims about what's possible seem to arrive weekly. But the conversations that matter most still tend to happen behind closed doors: researchers challenging assumptions, questioning dominant narratives, wrestling with what these systems can and can't actually do. Those exchanges happen in labs, over coffee, between people who've spent years thinking deeply about these problems.

Fifteen years ago, I made a bet. I walked away from a finance career and threw myself into data science. Moneyball was in cinemas, HBR was talking about it - I was hooked. Was it because it was supposed to be the "sexiest job of the 21st century"? Sure, a little. But beyond the hype, I was fascinated by something deeper: the idea that you could derive general laws from real-world experience rather than impose them on it.

Since launching Fundamental two weeks ago, the most common reaction has been a combination of relief and excitement that someone has finally decided to bring the AI revolution to tabular data.