# What's the difference between a LangGraph workflow and a LangGraph agent?

A workflow's control flow is code you wrote; an agent's control flow is a decision the model makes at runtime. In a LangGraph workflow, edges are predetermined: you decided in advance which node runs after which, so the graph always follows one of a fixed set of paths. In an agent, the model itself decides which tool to call or which node to go to next, so the same graph can take a path nobody wrote down in advance.

That difference is what changes what needs grading. A workflow's paths are enumerable, so you can write one eval per path and know you've covered the graph. An agent adds a decision you can't enumerate in advance: whether the model picked the right next step given what it had seen so far, [the same kind of check a mis-routed handoff needs in any multi-agent system](/answers/failure-modes/what-is-inter-agent-misalignment). Grading a workflow means checking each node's output; grading an agent means also checking the routing decision itself.

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Sources:
- LangChain docs: Workflows and agents: https://docs.langchain.com/oss/python/langgraph/workflows-agents (fetched 2026-09-16)

Source: https://tessary.ai/answers/langgraph-evals/langgraph-workflow-vs-agent
More on Langgraph evals: https://tessary.ai/answers/langgraph-evals
From Tessary, agent reliability for AI agents in production: https://tessary.ai