Your Agents Should Be Durable (sponsored by Temporal)Building AI agents is easy — making them production-ready is hard. Crashes, API failures, and state management are just a few challenges when moving from PoC to production. Learn how durable execution with Temporal makes it simple to build reliable agents that run for days, weeks, or months, using a code-first approach developers love.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Durable execution for agents — state persistence, retries, long-running operations measured in days or weeks. Code-first.
Why it matters
Naive agent code is fragile. Crashes lose state. Retries become infinite loops. Long-running workflows fail in nasty, partial ways.
The hard parts
Distributed state is genuinely hard. Agents amplify the hardness because they have non-deterministic decision points throughout the workflow.
Playbook moves
(1) Use durable execution for any agent that runs >5 min OR has external side effects. Don't roll your own. (2) Design workflows assuming any step might fail and retry; test that. (3) Make "human review" an explicit, durable workflow step, not an ad-hoc pause.
The surprise
The most useful Temporal pattern for agents isn't retry — it's the ability to *pause* an agent for human review and *resume* hours or days later without state loss. This is the missing primitive in most agent frameworks. Once you have it, "human in the loop" becomes practical at scale; without it, HITL is a constant battle against state expiration.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.
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Changelog
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