continuous-learning-v2

Continuous Learning v2

Overview

A learning system that extracts patterns from completed sessions, scores them by confidence, and evolves high-confidence instincts into durable skills. Unlike v1's stop-hook pattern, v2 uses instinct-based learning with confidence scoring and evolution.

When to Use

• After completing a significant feature or fix
• When you've discovered a pattern worth remembering
• When a session revealed a non-obvious solution
• Before starting similar work to apply learned instincts

Instinct Lifecycle

1. Discovery

When a pattern is encountered during work:

Pattern: [What was discovered]
Context: [When this applies]
Confidence: [0.0-1.0 based on evidence]
Evidence: [What proves this works]

2. Validation

Before storing an instinct:

• Pattern has been verified in at least one successful outcome
• Context is specific enough to avoid false positives
• Confidence score is justified with evidence
• No conflicting instincts exist

3. Storage

Instincts are stored with:

instinct:
  name: "descriptive-name"
  pattern: "what to do"
  context: "when to apply"
  confidence: 0.85
  evidence: "why this works"
  created: "2026-01-15"
  usage_count: 3
  success_rate: 0.95

4. Evolution

When an instinct reaches thresholds:

• Confidence > 0.9 AND usage_count > 5 AND success_rate > 0.9 → Promote to skill
• Confidence < 0.5 AND usage_count > 3 → Deprecate
• Confidence unchanged after 30 days → Review

Confidence Scoring

Score	Meaning	Action
0.9-1.0	Proven pattern, multiple successes	Promote to skill candidate
0.7-0.9	Strong pattern, some evidence	Use with confidence
0.5-0.7	Plausible pattern, limited evidence	Use cautiously, verify
0.3-0.5	Weak pattern, speculative	Note but don't rely on
0.0-0.3	Unproven, likely incorrect	Discard

Import/Export

Export Instincts

# Export all instincts to JSON
# Format: [{name, pattern, context, confidence, evidence}]

Import Instincts

# Import instincts from JSON
# Merge with existing, update confidence on duplicates

Anti-Rationalization Table

Excuse	Counter
"I'll remember this pattern"	Human memory is unreliable. Document it now with context and evidence.
"This is too specific to be useful"	Specific patterns become general skills through evolution. Start specific, generalize later.
"I don't have time to document"	2 minutes now saves 2 hours of rediscovery later. Use the instinct template.
"The confidence score is subjective"	Confidence is a starting point. Usage and success rates provide objective data over time.

Imported from continual-learning/continual-learning (MIT, cursor/plugins)

Continual Learning

Keep AGENTS.md current by delegating the memory update flow to one subagent.

Trigger

Use when the user asks to mine prior chats, maintain AGENTS.md, or run the continual-learning loop.

Workflow

1. Call agents-memory-updater.
2. Return the updater result.

Guardrails

• Keep the parent skill orchestration-only.
• Do not mine transcripts or edit files in the parent flow.
• Do not bypass the subagent.