Start with the first failure, not the final symptom
When a workflow run fails, the most useful question is: “Where did the behavior first go wrong?” That is usually more helpful than focusing on the final broken step, because later failures are often just the result of an earlier bad input or bad decision.A practical debugging order
Use this sequence:- confirm the trigger input
- find the first step that did not behave as expected
- inspect that step’s inputs and outputs
- check whether the problem is logic, mapping, or connection-related
- retest after fixing one thing at a time
Common causes of failed runs
Most failures come from a short list of patterns:- wrong or missing connection
- required fields not configured
- data shape mismatch between steps
- branch logic that sent the workflow down the wrong path
- AI output that was not suitable for the next step
Avoid changing too much at once
When a run fails, it is tempting to edit several parts of the workflow immediately. Try not to. Fix one likely cause, then retest. If you change several things at once, you lose clarity about what actually solved the problem.Use failed runs as design feedback
A failed run does not just tell you something is broken. It often tells you something about the workflow design. For example:- the trigger may be too broad
- the workflow may need an earlier condition
- the data handoff between steps may be too fragile
- the AI step may need a clearer task