From prototype to production-ready agentic AI solution: A use case from Grid Dynamics

This post details Grid Dynamics' migration of a deep research agent from a LangGraph/Redis/Kafka architecture to Temporal. Key contributions include: demonstrating Temporal's ability to manage complex agent state directly within workflows, eliminating the need for external state stores like Redis; showcasing the simplification of error handling and retry logic through declarative `RetryPolicy` configurations, reducing custom code; and highlighting how Temporal's durable execution addresses challenges with exactly-once processing, stale state, and graceful resumption after long pauses, leading to a more scalable and maintainable solution.