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Open_Ultra_SAST/.kiro/specs
Marius CiepluchandClaude Opus 5 bd3e2fe50f docs(detector-optimizer): the noise is structural, and the optimizer is not the next thing to build
The harness treats the detector as a black box emitting a noisy scalar, and
K runs, majority voting, the measured floor, the regression budget and the
sign test all follow from that. It is the stance you take when you cannot
see inside what you are measuring, and we can.

Temperature is already 0 and thinking is disabled, and 11 of 20 injection
pairs still disagree with themselves. The freedom is in the trajectory --
which files get read, which greps get run -- and we built statistics to
average over it instead of removing it.

Three DSPy constructs attack the source: constraints enforced as predicates
at generation time (we already compute every one of them, after the fact, at
scoring time), typed decomposition of the single ReAct loop into steps whose
deterministic parts we already answer without a model, and best-of-N against
a checkable reward instead of a majority vote that discards the
disagreement. The cheaper the detector model, the more of the return sits
there and the less in prompt evolution -- the opposite of the order this
brief first proposed.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
2026-09-06 15:29:36 +02:00
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