The fallacy of the graph: Why your next agentic workflow should be code, not a diagram

The text argues against using graph-based approaches for building complex, procedural logic in AI applications, particularly agentic ones, and advocates for the use of Durable Execution, which allows developers to write normal, procedural code with "crashless" guarantees. The author emphasizes that graph-based systems often fall short in handling dynamic control flows, data management, error handling, parallelism, and reusability, creating complexity and runtime failures. Durable Execution, however, supports dynamic, data-driven execution, providing incremental execution, state persistence, and fault tolerance, and allows developers to leverage the entire ecosystem of modern software engineering tools, such as source control, testing, CI/CD, and developer tooling. The article concludes that while static graphs may suit simple pipelines, durable code is far superior for dynamic, data-driven agents and cautions against the misconception that visual graphs provide a clearer or more effective representation of procedural logic.