continuous-learning-v2

Capture recurring code review patterns by documenting them as confidence-scored instincts with context, counter-cases, and evolution history. This transforms recurring judgments into reusable project-specific decision patterns that evolve with real evidence.

Prevent knowledge loss by building an instinct-based learning loop that scores and evolves project-specific decision patterns. Tracking instincts from observation to validation makes improvements measurable rather than anecdotal, keeping guidance aligned with team practices.

Track confidence for architecture patterns by moving instincts through defined evolution pipeline stages: observation, hypothesis, validation, and canonicalization. This structured validation process ensures API design rules are backed by growing project evidence.

Yes, you can enforce API design rules by integrating instincts via on-code-review hook checklists. These structured hooks apply captured decision patterns at key decision points, improving consistency across features and contributors.

Yes, continuous learning governance works without external dependencies. It requires structured documentation of context, pattern content, confidence scoring, and evolution stages to capture team conventions consistently across any team size.

Avoid using an instinct-based learning loop when your team lacks the discipline for structured documentation of context and counter-cases. Without consistent activation through hooks and checklists, confidence scoring becomes anecdotal rather than measurable.