Timeline

Published Where Do Codex's Cached Tokens Come From?, a note explaining why Codex can report millions of cached tokens after a run even when the actual prompt context is much smaller. The useful bit is that Codex's append-only agent loop keeps earlier messages as an exact stable prefix, so cache hits accumulate across repeated model calls in the same session.

I published Smart AI Token Consumption as a note on matching model choice to task complexity instead of defaulting to the biggest model. It captures the split I keep using in practice: light models for mechanical work, stronger reasoning only when the problem actually needs it.