Building AI features that work in demos but fail in production is common. Temporal provides durability through Workflows (which hold state and orchestration logic) and Activities (which execute external operations). This approach prevents duplicate work when processes restart, enables human-in-the-loop flows with Signals and
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Crossing the threshold #Don’t pay twice for the same model call #Human feedback without losing your way #The tools you bring back: Durable tools with MCP #The transformation #Sort: