Lessons
Concept pages that answer the SE/SA question — when do I choose this, what does it cost, and how do I explain it? — organized by the four-layer map. Where the labs teach by doing, lessons teach by deciding.
🎯 L1 · Apps & Agents
The application layer — where most engineering work sits. These pair with Labs 01–03.
- RAG Patterns — naive → hybrid → rerank, and when to go further
- Agent Architectures — hub-and-spoke, and why not a swarm
- Context Engineering — the bigger lever than prompt wording
- MCP and A2A — the protocols that connect agents to tools and each other
🏛️ L4 · Architecture & Governance
- Reference Architectures — pilot, agentic, and platform tiers, and which one matches a customer's stage
- Guardrails and Governance — NIST AI RMF, the EU AI Act, and ISO 42001 are a method, a law, and a certification — not the same thing
🗂️ L3 · Classic MLOps & Data
- The MLOps↔LLMOps Bridge — LLMOps extends MLOps, it doesn't replace it
🔜 Later layers
- L2 · LLMOps & infra — serving, quantization, vector DBs, gateways, observability (Phase 3+)
- L3 · Classic MLOps & data — the MLOps↔LLMOps bridge (Phase 4, in progress)
🔗 Links
- The Four-Layer Map — the structure these follow
- Labs — the hands-on counterpart
- Decision Frames — the build-vs-buy calls these inform