
2/25/2025
What this post added
This post details how Temporal can be used to build agentic AI workflows, addressing limitations of current frameworks in durability, scalability, and integration. It highlights Temporal's strengths in developer velocity, observability, scheduled execution, durable and resilient execution (handling LLM probabilistic nature and real-world failures), long-running and stateful capabilities, human-in-the-loop support, flexible integration with any LLM/database/service, and centralized orchestration. It provides a typical workflow example and emphasizes Temporal's role as a robust foundation for evolving AI agents.