Most AI pipelines are graphs. Graph engineering treats them that way

The article argues that while prompt engineering and loop engineering treat the model call as the unit of work, most production AI pipelines are really graphs of steps whose dependencies, parallelism, duration and cost can be derived before running. It describes deriving edges from prompt references to other steps' outputs, using structured output as the graph's type system, and lessons from building a compiler and scheduler for such pipelines.