Temporal vs. Diagrid Catalyst: Choosing the Right Durable Execution Tool for AI Agents

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Building reliable long-running AI agents requires durable execution platforms that handle failures, prevent duplicate tool calls, and maintain state across crashes. Temporal uses a workflow-and-activity model with broad language support, making it well-suited for teams comfortable writing application logic around its abstractions and replay semantics. Diagrid Catalyst, built on Dapr Workflows, sits beneath existing agent frameworks like LangGraph and CrewAI, offering a governance and execution layer without forcing teams to abandon their current tools. The choice largely depends on team size and structure: single-project teams may prefer Temporal's mature SDK, while platform teams managing multiple agent frameworks benefit from Catalyst's framework-agnostic policy enforcement. Regardless of platform, developers must still design idempotent side effects and define human-in-the-loop checkpoints, as durable execution addresses recovery but does not inherently make tool calls safe.

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