A lot of the complexity people experience in automation is self-inflicted.
It often starts by choosing tools before defining outcomes — asking “what can this tool do?” instead of “what result am I trying to remove manual work from?” When tools come first, workflows grow fast and purpose gets blurry.
Most effective automation only needs three things: a clear trigger, a simple decision, and a reliable outcome. When those are solid, everything else becomes optional.
The better approach is to strip workflows back to their purpose. Build the smallest version that works, observe how it behaves in real use, then add complexity only where friction actually appears.
Automation becomes simpler — and more durable — when it’s treated as an evolving system, not a finished product.