01 / AI ENGINEERING
AI Engineering
Foundation
By topic
Agents & Orchestration
8 articlesBuilding agents that ship, not demo: anatomy, orchestration patterns (single-loop to LangGraph graphs), tools and actions, and the production discipline — composed across Agentforce, LangGraph, Claude, and MCP.
Grounding & Retrieval
8 articlesConnecting models to your knowledge: RAG done right — chunking, embeddings, retrieval quality — across Agentforce retrievers over Data 360 and external vector stores. The foundation an agent’s answers stand on.
Prompting & Context Engineering
8 articlesSteering models reliably: system prompts, instructions, context windows, structured output, and prompt caching. The craft that turns a capable model into a dependable component.
Evaluation & Observability
8 articlesKnowing it works — and stays working: evals, test sets, LLM-as-judge, tracing, regression, and the monitoring that catches a silent degrade before a customer does.
Production & Governance
8 articlesShipping and operating AI: cost, latency, guardrails, PII and safety, human-in-the-loop, accountability, and deployment. The gap between a demo and an AI that runs on Monday morning.