Dzone iconDzoneSep 25, 2026 ~1 min source read

One Agent, Two Runtimes: Defining State Ownership Between Temporal and LangGraph

Combining Temporal and LangGraph creates a deceptively simple question: which runtime owns the state of the agent? Both preserve execution progress, but they preserve different kinds of progress.

One Agent, Two Runtimes: Defining State Ownership Between Temporal and LangGraph
Read original More from Dzone

Share this story

Send the public story page.

Useful takeaways from this story.

Combining Temporal and LangGraph creates a deceptively simple question: which runtime owns the state of the agent?

Deployment language, storage backend, model provider, and hosting topology remain unspecified assumptions.

Both preserve execution progress, but they preserve different kinds of progress.

Building the complete brief

The page is ready to read now. The fuller skim-friendly version will appear here automatically.

The useful part

Combining Temporal and LangGraph creates a deceptively simple question: which runtime owns the state of the agent? Both preserve execution progress, but they preserve different kinds of progress. Treating those mechanisms as interchangeable creates ambiguous recovery semantics.

How it works

  • Production integration therefore needs explicit authority for business progress, agent working state, and the handoff between them.
  • Continue-As-New can carry cached task results into the next Workflow Run.
  • Deployment language, storage backend, model provider, and hosting topology remain unspecified assumptions.

What to take from it

The current Temporal LangGraph integration narrows the problem.

Keep reading in the app

Open the app view to save this story, compare related coverage, and continue from the same source.

Open in app