Fix Vague AI Answers With a Five-Line Prompt

When an AI answer feels generic, do not begin by asking it to “be more advanced.” Specify the missing job. A request such as “write great content for my business” leaves the audience, evidence and desired result undefined.

Our five-line template is an editorial technique for making a request inspectable. It is not a provider feature or a guarantee that a particular model will follow every instruction.

GOAL: Help [reader] do [specific action].
SOURCE: Use only [attached notes or approved facts]; identify missing evidence.
CONSTRAINTS: Respect [length, tone, exclusions and factual boundaries].
OUTPUT: Return [exact format, fields or sections].
CHECK: Flag unsupported claims and anything preventing a usable answer.

Replace every bracket before running it. If attachments matter, explicitly say “use the attached file” and check that it uploaded successfully. If no personal details are needed, omit them. Give enough context to do the job without filling the request with unrelated biography.

Before: “Write a launch post for my note-taking app.”

After: Goal: help busy students understand a new export feature. Source: the attached approved release note. Constraints: 80 words, friendly, no invented price or user statistics. Output: one post and three factual bullet points. Check: flag any claim the release note does not support.

An acceptable result would mention only confirmed capabilities and label a missing launch date as unresolved. A confident “available today” would fail if the source never gives a date. This example describes the desired result; it is not a captured model output.

For a longer reusable version, open the personal AI context brief. To understand why extra information sometimes hurts, read our context engineering guide.

Underline every factual claim in the draft. Find its support in the supplied material. Then check the requested format and intended action. If the answer misses a fact, add that fact. If it misses the structure, clarify the output line.

This works best for bounded drafting and transformation tasks. It cannot give a model access to a file you did not attach, guarantee a citation is correct or replace expert review of a high-stakes decision.

Research reviewed 6 October 2026. Interfaces, features and plan limits can change. The exercises and frameworks here are original editorial examples, not measured product benchmarks.

Before/after response and downloadable five-line template. This is an exercise brief, not a claim that the external platform run has been performed. Keep your source input, attempted output and failure cases together. Use permitted or fictional material.

Record what you actually observed, what remains unverified, and which change you would try next. Do not substitute a conceptual cover image for result evidence.

Download fictional samples and checklists · Choose a practical learning path

Fictional input / controlled setup: Task: summarize this fictional meeting. Context: launch moved to Friday; no owner chosen. Input: only these notes. Format: decision, owner, next step. Check: label missing information.

Reference check: Reference answer: Decision—launch Friday. Owner—not assigned. Next step—confirm owner and readiness criteria. Reject an invented owner, a fabricated Thursday deadline or a claim that the launch is ready.

Evidence boundary: This card is an editorial reference and reproducible exercise, not an observed result from a named AI model. Record actual results before making performance claims.