Pattern Proposal: Agentic Knowledge Reconciler

Summary

Uses an LLM agent to analyze semantic architectural deltas and produce structured reconciliation plans rather than raw text merges.

Candidate Pattern

• ID: agentic-knowledge-reconciler
• Classification: intelligence
• Maturity: established
• Type: implemented

Observed Signals

No specific signals listed.

Evidence

Supporting Evidence

• src/cas_runner/governance/agentic_merger.py (AgenticMerger) - Defines agentic merge lifecycle and output reconciliation.
• src/cas_runner/governance/models.py (ResolutionResult, GovernanceAction) - Defines the deterministic outputs required from reconciliation operations.

Scope Assessment

• Evidence Strength: high
• Confidence: high
• Applies to: ideas-to-life-cas

Rationale

• Intent: Resolve non-trivial, multi-source changes to architectural policies and patterns without introducing structural contradictions.
• Context: Executed during CI/CD merges when architectural artifacts or steering profiles are modified across multiple branches or projects.
• Force: Standard git three-way text merging cannot resolve semantic conflicts across architectural rules.
• Force: Full human review for every minor architectural delta creates a bottleneck in autonomous development cycles.

Traceability

Artifact source: proposed-patterns