Over-engineering your automations is just as bad as not building them

The most reliable workflows I have built are also the simplest ones. One trigger, clean data transformation, one output. No branching logic that requires three LLM calls to resolve something a basic conditional would handle in milliseconds.

The temptation when you get comfortable with agents is to add complexity because you can. Parallel execution, dynamic routing, multi-model chains. Sometimes that is the right call.

Most of the time it is overhead that makes the system harder to debug and slower to run. Before adding an AI layer, ask whether a deterministic function solves the problem. If it does, use that. Reserve the agent layer for tasks that actually require reasoning and context, not ones that just need a formatted output.

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Over-engineering your automations is just as bad as not building them