Ready-to-use templates for AI-optimised content structure. Each template puts the answer first — the pattern LLMs use to decide what to cite.
Large language models parse content to find the most directly useful answer to a user query. Studies show that LLMs weight the first 50–80 words of a passage 4–8x more heavily than the rest of the document when deciding whether to cite it. BLUF structure aligns your content with this retrieval pattern — putting the answer exactly where the model looks first.
The templates above follow three rules. The answer comes first. The answer is specific (numbers, names, ranges — not vague generalisations). Supporting detail comes after in a separate sentence or paragraph so the model can extract cleanly.