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might need to add another parameter into the function or reformulate, will look into this. |
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Been using continuous-learning-v2 for a while and the instinct architecture is genuinely well-designed (confidence scoring + auto-load at SessionStart works better than I expected). Your X posts about ECC have been good reading too. Both have shifted how I think about a few things.
One thing I noticed in v2: the decay rule in agents/observer.md line 148 (
-0.02 per week without observation) appears to be implemented as a prompt instruction to the Haiku observer agent. That works conceptually, but it makes the decay behavior harder to reason about, test, or dry-run. Since time-based decay is basically mechanical, I wonder if it should be handled outside the observer prompt.The local change I tried was to split the two concerns currently bundled in observer.md:
mtimeas the last-evidence timestamp and applies a flat per-week decay.One thing I am less sure about is the decay rate itself. The current -0.02 per week rate seems to carry an implicit assumption that if a user has not seen a pattern recently, the instinct is probably stale. That may be true for some workflows, but it feels weaker now. I find myself working across more stacks and domains thanks to coding agents, and I doubt I am the only one. In that setting, “I have not touched this domain in three months” may mean variety is up, not that the instinct is wrong. A more aggressive decay can end up penalizing rare butvalid instincts rather than stale ones.
A few open questions before I turn this into a PR:
Happy to send a small PR if this direction lands.
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