framework-selection

To choose your agent architecture, evaluate whether your project needs simple chains best handled by LangChain, or complex graph control requiring LangGraph. A structured decision table maps specific project requirements to the correct framework layer.

You need Deep Agents middleware when your project requires full-featured agent orchestration rather than simple chains or complex graph control. This framework selection process ensures appropriate complexity management during initial architectural planning.

Yes, you can mix agent frameworks by using Deep Agents as an orchestrator for specialized LangGraph subagents. This layer mixing approach allows you to combine full-featured middleware with complex graph control.

The best way to plan AI agent architecture is to apply a standardized decision-making process that evaluates project requirements against LangChain, LangGraph, and Deep Agents capabilities before implementing agent logic or middleware.

LangGraph does not replace LangChain but provides complex graph control for agent design when simple chains are insufficient. The framework selection process determines if your task requires LangGraph's advanced capabilities or LangChain's simpler architecture.

Agent framework selection fails when complexity scales if you mismatch architectural layers, such as using simple chains for tasks requiring complex graph control. Evaluating requirements against LangChain, LangGraph, and Deep Agents prevents this.