Paper readings, concepts, working notes, and ideas worth capturing.
A complete operating framework for building toward frontier AI research — grounded in OBI (Outcomes, Behaviors, Insights), the Theory ⇌ Reality loop, and the diffusion model of learning. Covers daily behaviors, expertise compounding, research DNA, and the three convergence bets.
Note to self: the 300-day objective, the daily shippable artifact protocol, and a hard audit of whether the current setup is sufficient.
You already have an MS from Columbia. What you don't have — and what no university offers — is an MS in Research Engineering. The reasoning behind the framing, the long-run practice, and the strategic logic.
Two of the most common titles in industry ML teams. They sound similar, get conflated constantly, and the difference matters enormously when you're choosing a path. Here's the full breakdown.
The gap between finishing a paper and being able to implement it is enormous. Notes on why.