It always starts simple: you write a bit of workflow logic to handle a specific case. But as requirements grow and more people need to configure or extend it to support complex flows, that simple script turns into a tangled, brittle system. We faced this firsthand- every new condition, exception, or contributor made things harder to manage. We moved from fully coded logic, to a dynamic but fragile database setup, to eventually designing our own structured DSL for defining workflow recipes. Each step solved one problem and exposed another. What we landed on was a structure flexible enough to scale—and, unexpectedly, precise enough for AI to contribute meaningfully. This talk is the story of that evolution, and the practical takeaways for anyone designing configurable workflow systems that are meant to last.