Temporal & AI: Agent Memory & Execution State

Warrick — Wed, 11 Nov 2026 14:55:00 +0000

Memory is what the agent knows: the context the model sees right now, plus anything you carry across runs in a store you own. Execution state is what the system knows: where the work stood when something went wrong. A memory store can bring back what the agent knew, but it can't tell a new process where to pick up.

In this first episode of Temporal & AI, I built a customer support refund agent in plain Python. It asks the customer two questions, looks up the order and decides to issue the refund. Then I kill its Worker one step before it calls Stripe.

Without Temporal: the loop loses its place, the answers are gone, and the customer has to start the return over.

With Temporal: the same loop runs as a Workflow. A new Worker picks up the same Workflow and resumes right at "issue refund" without asking a single question twice.

🎥 Watch the episode: https://youtu.be/cXKQkrgn-TE

🧪 Run it yourself (offline by default, no keys needed): https://github.com/temporal-community/agent-memory-and-state

The full write up, with architecture and gotchas, lives in the Temporal docs.

DEV Community: Warrick

Temporal & AI: Agent Memory & Execution State