Project State & Progress

Last Updated: 2026-01-28 Current Status: Phase 4 complete with gap closure - all personality learning gaps fixed and verified

Current Position

Aspect	Value
Milestone	v1.0 Core (Phases 1-5)
Current Phase	04: Memory & Context Management
Current Plan	Complete (Phase 4 gap closure finished)
Overall Progress	5/15 phases complete
Progress Bar	███████░░░░ 30%
Model Profile	Budget (haiku priority)

Key Decisions Made

Architecture & Approach

Local-first design: All inference, memory, and improvement happens locally — no cloud dependency
Second-agent review system: Prevents broken self-modifications while allowing auto-improvement
Personality as code + learned layers: Unshakeable core prevents misuse while allowing authentic growth
v1 scope: Core systems only (model interface, safety, memory, conversation) before adding task automation

Phase 1 Complete (Model Interface)

Model selection strategy: Primary factor is available resources (CPU, RAM, GPU)
Context management: Trigger compression at 70% of window, use hybrid approach (summarize old, keep recent)
Switching behavior: Silent switching, no user notifications when changing models
Failure handling: Auto-start LM Studio if needed, try next best model automatically
Discretion: Claude determines capability tiers, compression algorithms, and degradation specifics
Implementation: All three plans executed with comprehensive model switching, resource monitoring, and CLI interface

Phase 3 Complete (Resource Management)

Proactive scaling strategy: Scale at 80% resource usage for upgrades, 90% for immediate degradation
Hybrid monitoring: Combined continuous background monitoring with pre-flight checks for comprehensive coverage
Graceful degradation: Complete current tasks before switching models to maintain user experience
Stabilization periods: 5-minute cooldowns prevent model switching thrashing during volatile conditions
Performance tracking: Use actual response times and failure rates for data-driven scaling decisions
Implementation: ProactiveScaler integrated into ModelManager with seamless scaling callbacks

Recent Work

2026-01-26: Created comprehensive roadmap with 15 phases across v1.0, v1.1, v1.2
2026-01-27: Gathered Phase 1 context and created detailed execution plan (01-01-PLAN.md)
2026-01-27: Configured GSD workflow with MCP tools (Hugging Face, WebSearch)
2026-01-27: EXECUTED Phase 1, Plan 1 - Created LM Studio connectivity and resource monitoring foundation
2026-01-27: EXECUTED Phase 1, Plan 2 - Implemented conversation context management and memory system
2026-01-27: EXECUTED Phase 1, Plan 3 - Integrated intelligent model switching and CLI interface
2026-01-27: Phase 1 complete - all models interface and switching functionality implemented
2026-01-27: Phase 2 has 4 plans ready for execution
2026-01-27: EXECUTED Phase 2, Plan 01 - Created security assessment infrastructure with Bandit and Semgrep
2026-01-27: EXECUTED Phase 2, Plan 02 - Implemented Docker sandbox execution environment with resource limits
2026-01-27: EXECUTED Phase 2, Plan 03 - Created tamper-proof audit logging system with SHA-256 hash chains
2026-01-27: EXECUTED Phase 2, Plan 04 - Implemented safety system integration and comprehensive testing
2026-01-27: Phase 2 complete - sandbox execution environment with security assessment, audit logging, and resource management fully implemented
2026-01-27: EXECUTED Phase 3, Plan 3 - Implemented proactive scaling system with hybrid monitoring and graceful degradation
2026-01-27: EXECUTED Phase 3, Plan 4 - Implemented personality-driven resource communication with dere-tsun gremlin persona
2026-01-28: EXECUTED Phase 4, Plan 7 - Enhanced SQLiteManager with metadata methods and integrated ContextAwareSearch with comprehensive topic analysis
2026-01-28: EXECUTED Phase 4, Gap Closure Plan 1 - Fixed missing AdaptationRate import for PersonalityLearner initialization
2026-01-28: EXECUTED Phase 4, Gap Closure Plan 2 - Implemented SQLiteManager methods (get_conversations_by_date_range, get_conversation_messages) for personality learning data pipeline

What's Next

Phase 4 complete: All memory and context management systems implemented with metadata integration. Ready for Phase 5: CLI Interface and User Interaction. Phase 4 accomplishments:

SQLite database with full conversation and message storage ✓
Vector embeddings with sqlite-vec integration ✓
Semantic search with relevance scoring ✓
Context-aware search with metadata-driven topic analysis ✓
Timeline search with date-range filtering ✓
Progressive compression with quality scoring ✓
JSON archival system for long-term storage ✓
Smart retention policies based on importance ✓
Comprehensive metadata access for enhanced search ✓

Status: Phase 4 complete - 4/4 plans finished.

Blockers & Concerns

None — Phase 4 complete with all gaps closed. Memory and context management with progressive compression, JSON archival, smart retention, personality learning with pattern extraction and layer creation, and complete VectorStore implementation fully functional. All personality learning gaps fixed and verified.

Phase 4 Final Status: ✓ COMPLETE (16/16 must-haves verified, verification score 100%)

Configuration

Model Profile: budget (prioritize haiku for speed/cost) Workflow Toggles:

Research: enabled
Plan checking: enabled
Verification: enabled
Auto-push: enabled

MCP Integration:

Hugging Face Hub: enabled (model discovery, datasets, papers)
Web Research: enabled (current practices, architecture patterns)

Session Continuity

Last session: 2026-01-28T18:29:27Z Stopped at: Completed 04-06-PLAN.md Resume file: None

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