If an AI outline ignores the strongest source material, start by preserving one representative example. It gives the investigation a concrete reference and makes the eventual correction easier to judge.
Find the likely cause
The prompt requests a generic structure before reviewing evidence.
Treat this as an explanation to verify against the actual work. Look at the input, the relevant decision, and the final result together. If the evidence does not support this diagnosis, investigate the mismatch before applying a convenient but unrelated fix.
Make the targeted correction
Build the outline around the available examples and findings.
A strong outline orders the questions a reader must answer to move from confusion to a useful conclusion.
Check that the repair worked
Ensure the most useful evidence has an appropriate place in the argument.
Repeat the check on the final version that the reader or customer will encounter. An approved draft, a preview, and a published result can differ; the acceptance decision should concern the version people actually use.
Prevent the next related failure
A separate issue to watch for is this: aI outlines contain headings that say almost nothing. Rewrite headings to state the decision, explanation, or action in each section.
Monitor the useful outcome
Measure missing sections and structural revisions identified during drafting and review.
Keep a short record of the original symptom, the evidence behind the diagnosis, and the result of the acceptance check. That record makes the solution reusable when the same condition appears again, without assuming that every superficially similar problem has the same cause.