Temporal
AI / LLMA durable execution platform that makes long-running, failure-prone workflows — including AI agents — reliable by default.
Overview
Temporal is not an AI tool, but it has become core AI infrastructure. Agents are long-running processes that call flaky APIs, wait on humans, and must survive crashes — exactly the problem durable execution solves. Temporal persists workflow state so a process can resume mid-flight after a failure, with automatic retries and a full event history. For enterprises moving agents from demo to production, wrapping agent logic in Temporal workflows is one of the most reliable ways to make them dependable. It is an engineering commitment, not a drop-in.
Pros & Cons
Pros
- Makes long-running agent workflows crash-proof
- Automatic retries and full execution history
- Battle-tested well beyond AI use cases
- Self-host or managed Temporal Cloud
Cons
- Significant learning curve and architectural commitment
- Not AI-specific — you build the agent layer yourself
- Self-hosting the cluster is non-trivial
Workflows that use Temporal
Get a new AI workflow each week — many feature Temporal and other tools in this category.