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spec(learned-decision-engine): brief and requirements for review

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Maintainer direction: A/B testing to extrapolate detection instead of hard-coding
it, and a trained decision engine. Instruments become signal producers; labels
from ground truth with provenance; a simple calibrated engine with population
folds; experiments as plane Runs; extrapolation with intervals, checked once on
frozen v3; the engine is what scan/pre-push/plane report.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
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Marius Ciepluch
2026-09-30 17:59:06 +02:00
co-authored by Claude Opus 5.5
parent ff51bb517d
commit afde23d3cf
3 changed files with 172 additions and 0 deletions
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.kiro/specs/learned-decision-engine/spec.json
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{
"feature_name": "learned-decision-engine",
"created_at": "2026-09-30T14:00:00Z",
"updated_at": "2026-09-30T14:00:00Z",
"language": "en",
"phase": "requirements-generated",
"approvals": {
"requirements": {"generated": true, "approved": false},
"design": {"generated": false, "approved": false},
"tasks": {"generated": false, "approved": false}
},
"ready_for_implementation": false
}