LangGraph

LangGraph Evaluation Tutorial: Test Multi-Agent Workflows

Quick summary Evaluate the whole graph: assess answers, routing, tool use, reliability and cost. Use deliberate test cases: cover ordinary requests, edge cases and safe failures. Compare against a baseline: combine offline tests with production feedback. Apply focused human review: use a consistent rubric where judgement matters. LangGraph evaluation turns a convincing multi-agent demo into […]

LangGraph

LangGraph Persistence Tutorial: Checkpoint and Resume Multi-Agent Workflows

Quick summary Checkpoint state: persistence lets a graph pause, recover and continue. Resume the same thread: reuse its identifier and supply the review decision. Design for replay: repeated execution must not duplicate consequential actions. Use durable storage: production needs an appropriate backend and retention policy. LangGraph persistence is what makes a multi-agent workflow safe to […]

AI Agents Artificial Intelligence Software Architecture

Why Final-Answer Evals Leave AI Agent Failures Invisible

Trajectory evaluation shows how a final answer can look perfect while the agent behind it has already failed. Imagine an agent that tells a support team: “The customer record has been updated.” The sentence is clear and reassuring. However, the trace may show a different story. It may select a search tool instead of an […]

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