Of course you can build dynamic AI agents with Temporal

Temporal is a robust platform for building AI agents, contrary to misconceptions that its requirement for deterministic workflows limits its use with non-deterministic AI models like large language models (LLMs). While Temporal workflows must be deterministic to ensure reliability and recoverability from failures, the activities within these workflows, such as LLM operations, can be non-deterministic. This separation allows AI agents to dynamically make decisions and adapt their paths using LLMs without compromising durability. By recording decision histories, Temporal enables AI agents to resume operations seamlessly after crashes, making it ideal for long-running tasks. Companies like OpenAI and Replit utilize Temporal to power sophisticated AI agents, demonstrating its capability to handle dynamic, unpredictable AI behavior while maintaining reliable execution.

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