Durable Execution and the Infrastructure Powering AI Agents

Key Takeaways

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  Durable execution requirements are surging as AI agents transition from simple interactive chats to long-running, multi-step autonomous processes that require persistent state management.

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  Infrastructure scale challenges are intensifying because background-running agents create distributed systems problems at a complexity level that did not exist in the industry two years ago.

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  Enterprise adoption patterns show industry leaders like OpenAI and Snap are utilizing Temporal to ensure recoverability and reliability in high-stakes features like Codex and story processing.

Episode Description

Sarah Wang, general partner at a16z, and Raghu Raghuram, managing partner at a16z, speak with Samar Abbas, CEO of Temporal, about how durable execution became the infrastructure layer behind the world's most used AI agents. They cover why long-running agents need state management and recoverability, how Temporal powers OpenAI's Codex and Snap's story processing, and why the shift from interactive to background agents is creating distributed systems problems at a scale that didn't exist two years ago.