AI should enrich pages, not fill them with generic text

AI should enrich pages, not fill them with generic text

For data-driven pages, use AI on the parts that benefit from synthesis: grouping similar records, spotting outliers, turning raw attributes into short comparisons, and drafting microcopy around filters or tables. Do not ask it to “write the page” from scratch.

A safe workflow:
• keep one row = one fact
• generate only missing explanations, summaries, and labels
• force every sentence to reference fields in the dataset
• reject any line that could fit a different page with no edits

The best pages usually have a clear split: structured data stays untouched, while AI adds a thin editorial layer. That layer can explain patterns, compare categories, or answer likely user questions in 1-2 sentences. If the model starts inventing context, trends, or benefits that are not in the data, the page is too loose.

Good AI use cases are narrow: alt text for charts, short intros for tables, “what to look for” notes, and FAQ snippets based on known fields. Bad use cases are broad: long summaries, sales copy, and any paragraph that repeats the same point in different words.

Use AI to make the page easier to read, not louder. If a sentence does not improve scanning, selection, or trust, cut it.