Posts
Notes to self
-
Why Agents Make Good Actors
Published: at 11:00 AMAI agents are stateful, long-running, and mostly idle. That's not a quirk — it's a specification. The actor model was built for exactly this shape of work.
-
An introduction to reinforcement learning
Updated: at 11:00 AMThe orientation for working engineers before the rest of the series goes into algorithm internals. What RL is, the vocabulary, the Bellman idea, when to reach for it, and a map of the five posts.
-
Designing environments for RL
Updated: at 11:00 AMMost RL writing is about algorithms. In practice, environment design — the state, action, and reward decisions that sit between your system and the algorithm — is where projects succeed or fail. This is the part that almost never gets covered.
-
Inside the Bellman loop: how value actually propagates
Published: at 07:00 PMBellman equations are usually introduced recursively, and the recursion misleads programmers. The runtime is closer to iterative graph relaxation — value sweeping backward through a state graph until it stops moving.