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Production Patterns: Multi-Agent, Memory & Observability
Architect enterprise multi-agent systems with langgraph-supervisor, multi-tier persistent memory tables, real-time LangSmith tracing, and golden dataset trajectory evaluations.
Module Content
Multi-Agent Systems and Supervisor Patterns
When one agent isn't enough. Coordinator patterns for systems with specialized workers. FIND_VIDEO: search 'multi-agent system supervisor LangGraph tutorial' — recommended channel: LangChain / CrewAI / Sam Witteveen. Aim for 11 min or under.
Quiz: Supervisor Coordination & Handoffs
Multi-agent isn't free. Know when it helps, when it hurts, and what patterns work in production.
Case 4 — Hierarchical Multi-Agent Research System
Three specialized agents coordinated by a supervisor. The classic multi-agent pattern done right.
Memory Architecture — Short-Term, Working & Semantic
What memory means for an agent and how to give it the right kind. FIND_VIDEO: search 'agent memory short term long term LLM' — recommended channel: LangChain / Mem0 / James Briggs. Aim for 10 min or under.
Quiz: Multi-Tier Agent Memory Design
Three memory types, three implementation patterns. Pick the right combination for your agent.
Case 5 — Cross-Session Long-Term Memory Agent
Beyond short-term conversation context. Build an agent that remembers users across sessions.
Production Tracing & Observability with LangSmith
The production observability layer. Without it, debugging multi-step agents is brutal. FIND_VIDEO: search 'LangSmith LangGraph observability tutorial' — recommended channel: LangChain. Aim for 10 min or under.
Quiz: LangSmith Telemetry & Span Analysis
LangSmith + streaming + structured logging. The three pieces that make agents debuggable at scale.
Offline Evaluations, Golden Datasets & LLM Judges
Evals for agents are harder than for simple LLM calls. Here's what actually works. FIND_VIDEO: search 'LLM agent evaluation testing tutorial' — recommended channel: LangChain / DeepLearning.AI. Aim for 10 min or under.
Quiz: Agent Benchmarking & Trajectory Eval
Three levels of agent eval: trajectory, final-answer, and component. Use all three for production-grade testing.