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Release Notes - v1.1.2 (Development Preview)

Release Date: 2026-01-08 Type: Development Preview Status: v1.2 Phase 1 in progress

🎯 What's New

This release showcases active v1.2 development with experimental features and comprehensive design documentation for the upcoming intelligence enhancements.

Experimental: Usage Tracking System

Status: ⚠️ Preview / Observation Mode - Not production-ready

The foundation for v1.2's adaptive learning system is now in place:

# Tracks what Claude actually uses vs what's injected
from usage_tracker import UsageTracker

tracker = UsageTracker(mode='observe')
# After 50 turns → switches to 'learn' mode
# Automatically adjusts keyword weights based on usefulness

What it does:

  • Tracks which .claude/*.md files are injected each turn
  • Monitors which files Claude actually reads/edits
  • Maps documentation to source code relationships
  • Calculates usefulness scores (0.0 to 1.0)
  • Will learn optimal keyword weights after sufficient data

Components:

  • scripts/usage_tracker.py - Core tracking logic
  • scripts/usage-track-stop.py - Stop hook integration
  • Integration in context-router-v2.py

Current status:

  • ✅ Infrastructure complete
  • ✅ Stop hook configured
  • ⏭️ Collecting data (needs 50 turns for learning)
  • ⏭️ Validation pending

v1.2 Architecture & Roadmap

Comprehensive documentation for upcoming features:

Self-Maintaining Documentation System:

  • Foraging Agent - Auto-discovers important files, generates .claude/*.md docs
  • Doc Refiner Agent - Keeps existing docs synchronized with code changes
  • Usage-driven intelligence - Both agents query usage tracker to focus on what matters

Design Documents Added:

  • V1.2_INTELLIGENCE_ROADMAP.md - Complete v1.2 plan (4 phases)
  • RALPH_LOOP_INSIGHTS.md - Design philosophy (iterate → measure → learn)
  • .claude/modules/usage-tracker.md - Tracking system design
  • .claude/modules/foraging-agent.md - Discovery agent design
  • .claude/modules/doc-refiner-agent.md - Maintenance agent design
  • .claude/modules/unified-agent-architecture.md - How agents work together

Phase Roadmap:

  • Phase 1 (Weeks 1-2): Usage Tracking - 85% complete
  • Phase 2 (Weeks 3-4): Semantic Matching - Planned
  • Phase 3 (Weeks 5-6): Predictive Pre-loading - Planned
  • Phase 4 (Weeks 7-9): Self-Maintaining Docs - Designed, not implemented

📊 Progress Reports

Detailed progress documentation included:

  • V1.2_PHASE1_PROGRESS.md - Phase 1 development log
  • INTEGRATION_PROGRESS.md - Integration status and metrics
  • SESSION_SUMMARY.md - Latest development session notes

🔧 Technical Changes

Modified Files

scripts/context-router-v2.py:

  • Added usage tracker integration (injection logging)
  • Added learned keyword weight loading
  • Applies weights during attention calculation
  • Graceful fallback if tracker unavailable

~/.claude/settings.json:

  • Added usage-track-stop.py to Stop hooks
  • Runs automatically after each conversation turn

New Files

Core Tracking:

  • scripts/usage_tracker.py (540 lines)
  • scripts/usage-track-stop.py
  • scripts/add-usage-tracking-hook.py

Documentation:

  • 4000+ lines of design specifications
  • Complete v1.2 architecture
  • Ralph Loop philosophy and patterns

Data Files (Auto-generated)

When usage tracking is active:

  • .claude/usage_stats.json - Per-file statistics
  • .claude/usage_history.jsonl - Turn-by-turn log
  • .claude/keyword_weights.json - Learned weights (after 50 turns)
  • .claude/learning_progress.txt - Human-readable progress

⚠️ Important Notes

Experimental Features

Usage tracking is in PREVIEW mode:

  • Infrastructure is complete and functional
  • Currently in observation/data collection phase
  • Learning mode activates automatically after 50 turns
  • No breaking changes to existing functionality
  • Can be disabled by removing stop hook

Not Included in This Release

v1.2 features still in development:

  • Semantic matching (Phase 2)
  • Predictive pre-loading (Phase 3)
  • Foraging agent (Phase 4A)
  • Doc refiner agent (Phase 4B)

These are fully designed but not yet implemented.

Compatibility

Requires:

  • Python 3.8+
  • Claude Code (current version)
  • Existing .claude/ setup from v1.1

Backward compatible:

  • All v1.1 features still work
  • Usage tracking is opt-in via stop hook
  • No changes to core routing logic

🎓 Design Philosophy: Ralph Loop

This release embodies the Ralph Loop pattern (inspired by Geoffrey Huntley):

Iterate → Measure → Learn → Refine → Repeat

Not: "Design perfect system, then implement" Instead: "Build foundation, observe real usage, learn from data, iterate"

Applied to v1.2:

  1. Built usage tracking → observe what matters
  2. After 50 turns → measure usefulness scores
  3. Learn keyword weights from data
  4. Refine routing based on learning
  5. Converge when weights stabilize

This is adaptive intelligence through iteration, not one-shot optimization.

📈 Metrics & Success Criteria

Phase 1 Targets (When Complete)

Injection Rate:

  • Baseline (v1.1): ~45% (estimated)
  • Target (v1.2): >75%
  • Metric: Percentage of injected files that are actually accessed

Budget Utilization:

  • Target: 70-90% of context budget used effectively
  • Metric: Ratio of accessed files to injected files

Learning Convergence:

  • Target: <150 turns to stable weights
  • Metric: Weight changes <2% over 50 turns

Manual Effort:

  • Target: 80% reduction in manual keyword tuning
  • Current: 100% manual configuration

Current Status

  • Infrastructure: ✅ Complete
  • Data collection: 🔄 In progress (~14 turns collected)
  • Learning: ⏭️ Waiting for 50-turn trigger
  • Validation: ⏭️ Pending sufficient data

🚀 Next Steps

For Users

If you want to experiment:

  1. Install stop hook: python3 scripts/add-usage-tracking-hook.py
  2. Use Claude Code normally for 50+ turns
  3. Monitor .claude/usage_stats.json for usefulness scores
  4. Check .claude/learning_progress.txt for learning updates

If you want to wait:

  • Stay on v1.1.1 until v1.2 is production-ready
  • Follow development in GitHub discussions
  • Watch for v1.2.0 stable release (8-10 weeks)

For Development

Ongoing work:

  • Collecting real usage data from claude-cognitive development
  • Validating tracking accuracy and usefulness calculations
  • Testing learning trigger at 50-turn mark
  • Measuring quantitative improvements

Next phases:

  • Phase 2: Semantic matching (embedding-based file relevance)
  • Phase 3: Predictive pre-loading (anticipate next files needed)
  • Phase 4: Self-maintaining docs (autonomous agent system)

📝 Changelog

Added

  • ⚠️ Experimental usage tracking system (observation mode)
  • Complete v1.2 architecture documentation (4000+ lines)
  • Ralph Loop design philosophy and patterns
  • Usage tracker core (usage_tracker.py)
  • Stop hook integration (usage-track-stop.py)
  • Learned keyword weight application
  • Auto-generated data files (usage_stats.json, usage_history.jsonl)

Changed

  • context-router-v2.py: Added usage tracking integration
  • ~/.claude/settings.json: Added stop hook (via installer)
  • Documentation: Extensive v1.2 roadmap and design specs

Experimental

  • All usage tracking features marked as preview/testing
  • Self-maintaining documentation agents (designed, not built)
  • Adaptive learning system (foundation laid, learning pending)

🙏 Acknowledgments

Design Inspiration:

  • Ralph Loop pattern: Geoffrey Huntley's continuous AI agent technique
  • Usage-driven architecture: Real behavior over synthetic benchmarks

Development Approach: This release demonstrates development transparency:

  • Show work in progress
  • Document design before implementation
  • Iterate based on real usage
  • Learn from actual data

📞 Feedback & Discussion

Found issues? Open an issue at: https://github.com/GMaN1911/claude-cognitive/issues

Have ideas? Start a discussion: https://github.com/GMaN1911/claude-cognitive/discussions

Want to contribute? See design docs in .claude/modules/ for Phase 2-4 plans

Version: 1.1.2 (Development Preview) Status: v1.2 Phase 1 in progress Timeline: v1.2.0 stable release expected in 8-10 weeks

🤖 Generated with Claude Code