Thinking
Notes on AI engineering, mathematical foundations, and the shifting landscape of what it means to build intelligent systems.
The Systems Thinking Gap: What Happens When the Code Works But the System Doesn't
AI agents generate correct functions faster than ever. The hard part is knowing how those functions connect, what state they share, and why the whole thing falls apart at the edges.
The Evaluation Gap: Why 'It Works' Isn't Engineering
Most AI portfolios demonstrate that something runs. Few demonstrate that it works correctly. As models get better at generating code, the ability to evaluate outputs rigorously becomes the critical differentiator.
Why Mathematical Foundations Matter More as Coding Agents Commoditize Implementation
As AI coding agents reduce the cost of writing software to near-zero, the scarce skill becomes knowing what to build and why it works. Applied mathematics is the durable advantage.