Agentic AILangGraphMulti-agentProduction Ready
Agentic AI systems architecture with LangGraph
A field-tested blueprint for orchestrating multiple specialized agents using LangGraph, with reliable tool access, structured memory, and hardened guardrails. Build systems that can reason, collaborate, and recover gracefully in production.
Updated Nov 8, 2025 7 minute read LangGraph production playbook
Core building blocks
01- Router agent for intent detection and delegation across the graph
- Domain specialists for pedagogy, practice, worldview, reflection, and orchestration
- Shared memory layer combining RAG and short-term conversation buffers
- Tool layer for profile/data access, search, transactions, and guardrails
Reliability & governance
02- Deterministic tools with explicit input/output schemas and timeouts
- Evaluation harness with regression suites, telemetry-driven improvements, and red teaming
- Escalation paths and human-in-the-loop checkpoints for high-risk actions
Observability & rollout
03- Trace each turn: prompt, tool calls, outputs, cost, and latency metrics via LangSmith/LangFuse
- Use progressive rollout with feature flags and canary cohorts
- Keep agents narrowly scoped; avoid monolithic “do everything” agents for clarity and safety