IBM killed the LangChain vs LangGraph debate in under 10 minutes
Martin Keen reduces the decision to one rule:
Straight-line AI workflow? Use LangChain
AI that must loop, remember, and adapt? Use LangGraph
Key timestamps:
00:00:38 LangChain: build LLM apps by chaining functions in sequence
00:03:19 LangGraph: build stateful multi-agent systems for nonlinear workflows
00:05:42 The side-by-side comparison
00:07:05 The real split. LangChain moves forward. LangGraph can loop and revisit previous states
00:08:07 Why state changes everything
00:08:48 The decision rule. Sequential tasks vs systems that continuously interact and adapt
Most developers treat these as competing frameworks
IBM shows they are different layers of the same stack
LangChain gives you the building blocks
LangGraph gives those blocks memory and control flow
Save these timestamps before building your next AI agent
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