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AI systems

7 post(s) tagged with AI systems.

What It Takes to Build Production-Ready LangGraph Systems

What It Takes to Build Production-Ready LangGraph Systems

A production-oriented checklist for LangGraph systems: deterministic tests, evaluations, parallel workflows, control flow, and observability.

Command vs Send in LangGraph: Choosing the Right Primitive

Command vs Send in LangGraph: Choosing the Right Primitive

When to use Command for control flow and Send for data parallelism in LangGraph, with practical testing examples for each.

Testing Parallel LangGraph Workflows Without Losing Control

Testing Parallel LangGraph Workflows Without Losing Control

How to test LangGraph fan-out, Send-based parallel work, aggregation, and branch failure behavior without relying on output guessing.

How to Structure LangGraph Tests That Actually Scale

How to Structure LangGraph Tests That Actually Scale

How to structure LangGraph tests into unit, graph, and failure layers so the suite stays useful as the workflow grows.

Stop Testing AI Outputs. Start Testing State

Stop Testing AI Outputs. Start Testing State

A better way to test LangGraph workflows by treating the graph as state transitions instead of judging final answer text.

Progress Indication with LangGraph and CopilotKit

Progress Indication with LangGraph and CopilotKit

A practical pattern for rendering progress cards in CopilotKit chat while LangGraph runs long-running agent workflows.

When LangGraph Fails, Your UX Shouldn’t: Designing Graceful Error Handling

When LangGraph Fails, Your UX Shouldn’t: Designing Graceful Error Handling

A practical pattern for routing LangGraph failures to a user-facing error handler without breaking the user experience.