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vendor/ruvector/docs/adr/coherence-engine/ADR-CE-007-threshold-autotuning.md

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+# ADR-CE-007: Thresholds Auto-Tuned from Production Traces
+
+**Status**: Accepted
+**Date**: 2026-01-22
+**Parent**: ADR-014 Coherence Engine Architecture
+
+## Context
+
+Fixed thresholds become stale as:
+- System behavior evolves
+- New edge types are added
+- Domain characteristics change
+
+Manual tuning is expensive and error-prone.
+
+## Decision
+
+**Thresholds auto-tuned from production traces with governance approval.**
+
+Process:
+1. **Collect traces**: Energy values, gate decisions, outcomes
+2. **Analyze**: SONA identifies optimal threshold candidates
+3. **Propose**: System generates new PolicyBundle with updated thresholds
+4. **Approve**: Required approvers sign the bundle
+5. **Deploy**: New thresholds become active
+
+Constraints:
+- Auto-tuning proposes, humans approve
+- Changes tracked in audit log
+- Rollback supported via new PolicyBundle
+
+## Consequences
+
+### Benefits
+- Thresholds adapt to changing conditions
+- Governance maintained (human approval required)
+- Historical analysis enables data-driven decisions
+
+### Risks
+- Bad traces lead to bad proposals
+- Approval bottleneck if too many proposals
+
+## References
+
+- ADR-014: Coherence Engine Architecture, Section 6
+- ADR-CE-015: Adapt Without Losing Control