LangGraph for Agent State and Control Flow

A graph makes the agent's next step explicit: continue, retry, request review or finish. It is useful when the workflow needs stateful branches rather than a single prompt-response call.

#State, nodes and edges

State contains the objective, relevant observations, artifacts and current status. A node reads state and returns updates. An edge selects the next node, either unconditionally or through routing logic.

For a coding assistant, a useful graph is:

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read task -> inspect files -> propose patch -> validate patch
                                           | pass -> review -> finish
                                           | fail -> revise, if budget remains
                                           | exhausted -> report blocker

The diagram is a design example. A box named “validate” must execute a real check; a model saying the code looks correct does not replace tests.

#Make the loop bounded

Store the attempt count and check it in the router. Add a global time and usage budget as well as a graph recursion limit. Do not let a failing quality check cause unlimited regeneration.

Use typed state and clear node contracts. If several nodes update the same field concurrently, define how updates combine. Keep a failure distinct from a successful node that returned an empty result.

#Pause and resume safely

A checkpointer records graph state. An in-memory implementation is for development; restart recovery needs durable storage. Authorize access to the thread before loading its state.

Pause before consequential actions with the proposed operation visible to the reviewer. Resume with the intended decision, then recheck any data that may have changed. An external operation can succeed before checkpointing fails, so action handlers still need idempotency and reconciliation.

For a deterministic, runnable graph example without a model provider, see the LangGraph tutorial.

Official Graph API↗