Status: Roadmap | 2026-06-19 | Q3 2026 Target
| Domain | Current Lessons | Q3 Target | Gap |
|---|---|---|---|
| RAG | 24 | 35+ | +11 |
| DevOps/Infrastructure | 18 | 30+ | +12 |
| Multi-Agent Coordination | 8 | 20+ | +12 |
| LLM Fine-tuning | 3 | 15+ | +12 |
| Database & Query | 5 | 12+ | +7 |
| Total | 58 | 112+ | +54 |
- Chunking strategies for Chinese text (vs English)
- Hybrid search tuning (BM25 + vector weight calibration)
- Weaviate/LanceDB migration pitfalls
- Cross-encoder reranker memory management
- Query expansion failure modes
- Embedding cache invalidation
- SQLite vs PostgreSQL for metadata filtering
- Streaming RAG with async generators
- Guardrail design for RAG answers
- Evaluation dataset creation
- A/B testing retrieval strategies
- Docker Compose network race conditions
- K8s liveness probe misconfiguration
- Terraform state locking issues
- GitHub Actions matrix strategy edge cases
- Self-hosted runner security hardening
- Nginx reverse proxy WebSocket timeout
- PostgreSQL connection pooling exhaustion
- Redis memory policy eviction
- Prometheus recording rules cardinality explosion
- Docker build cache invalidation debugging
- SSH key management automation
- CI/CD pipeline secret rotation
- Agent state synchronization conflicts
- Context window overflow handling
- Agent-to-agent deadlock detection
- Shared tool invocation race conditions
- Message queue backpressure
- Agent heartbeat/timeout recovery
- Parallel tool execution ordering
- Agent memory consolidation strategies
- Inter-agent dependency resolution
- Leader election for task assignment
- Rate limiting across multiple agents
- Agent task queue prioritization
- LoRA rank selection guidelines
- Dataset format conversion pitfalls
- VRAM estimation for fine-tuning
- QLoRA vs LoRA tradeoffs
- Overfitting detection during training
- Evaluation set contamination
- Multi-GPU training data parallelism issues
- Gradient checkpointing OOM
- Mixed precision training instability
- Fine-tuning for code generation
- Instruction dataset curation best practices
- Model merging conflicts
- SQL JOIN vs subquery performance traps
- Index design for time-series data
- Connection leak detection
- Deadlock diagnosis in PostgreSQL
- Query plan analysis for slow queries
- Pagination offset performance degradation
- JSONB vs relational schema tradeoffs
| Phase | Focus | Method |
|---|---|---|
| Phase 1 (Jul) | RAG + DevOps (23 lessons) | Batch create via harvester + contribute |
| Phase 2 (Aug) | Multi-Agent + Database (19 lessons) | Ring-4 bounty + community contributions |
| Phase 3 (Sep) | LLM Fine-tuning (12 lessons) | Expert contributions + LLM-assisted generation |
Use Log Harvester CLI to accelerate creation:
# Harvest from error logs
python3 search_knowledge.py --harvest --from-file <error-log>
# Or contribute via wizard
python3 scripts/contribute.py --wizard- Ring-4 Newcomer Track — Translate/verify/tag tasks
- Lesson Checklist — Quality standards