I Tried to Train Meta-Cognition Into a 1.5B Model. The Results Are... Honest.
Disclaimer: This is an experiment log, not a peer-reviewed paper. Single human subject (me). Non-blind scoring. All statistical caveats spelled out. Proceed accordingly.
The thing I kept noticing
I use Claude Code daily. A lot. And there's this pattern I couldn't stop seeing: I'd start a session, everything would be great, then somewhere around the 30-minute mark Claude would start... drifting. Same task, same instructions, but the outputs would veer. It'd forget the plan. It'd chase a tangent. It'd rewrite code it had already written.
The standard fix is external scaffolding — CLAUDE.md files, session checkpoints, memory hooks. And that works. I've built an elaborate one myself. But it burns context window. Every self-check, every memory load, every "are we still on track?" costs tokens. At some point the scaffolding eats the house.
