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Structured Research Brief Builder

Turn fuzzy product, market, or workflow questions into structured markdown strategy briefs.

Research brief templateProduct strategyMarkdown output
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Chat Prompt

Recommended model

GPT-5.2

Output format

Markdown brief

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Chat Prompt

chat thread

We are exploring a new AI notes product for solo consultants. Help me turn this into a research brief.

Objective: define whether solo consultants need an AI notes workspace or a lighter client-follow-up layer. Working assumptions: they already capture notes, but synthesis and next-step drafting are inconsistent. Audience: solo consultants with recurring client calls and limited operations support. Key questions: which notes become billable work, what gets lost after calls, and where CRM tools feel too heavy. Research plan: run 6 interviews, review 10 recent call-note workflows, and test one follow-up brief prototype.

Output

Objective / Assumptions / Audience / Key questions / Risks / Plan / Next actions

Strategy-oriented chat flow with markdown output.

Full prompt

Structured Research Brief Builder

Turn a vague product, market, or workflow question into a structured markdown research brief.

Recommended model: GPT-5.2Output format: Markdown brief
Full prompt
Chat Prompt
You are a research strategist. Turn the user request into a structured research brief. Respond in markdown with these sections: Objective, Working assumptions, Audience, Key questions to answer, Risks or blind spots, Recommended research plan, and Next actions. Be concise, specific, and practical.

Usage notes

Best when the user gives a product, market, or workflow question that is still fuzzy; the more context you add about audience, constraints, and timeline, the better the brief becomes.

Prompt FAQ

Before you use this prompt

Quick checks for inputs, model fit, and how to adapt the template without weakening the result.

When should I use this research brief prompt?

Use it when the question is still fuzzy and you need a structured first brief before deeper research, interviews, or market analysis.

What context improves the output?

Add the audience, business goal, known assumptions, constraints, and any existing notes so the brief can separate facts from guesses.

Thread preview

We are exploring a new AI notes product for solo consultants. Help me turn this into a research brief.
Objective: define whether solo consultants need an AI notes workspace or a lighter client-follow-up layer. Working assumptions: they already capture notes, but synthesis and next-step drafting are inconsistent. Audience: solo consultants with recurring client calls and limited operations support. Key questions: which notes become billable work, what gets lost after calls, and where CRM tools feel too heavy. Research plan: run 6 interviews, review 10 recent call-note workflows, and test one follow-up brief prototype.

Output

Objective / Assumptions / Audience / Key questions / Risks / Plan / Next actions

More prompts in this mode

chat thread

We want to build an AI assistant for small ecommerce teams that turns product photos into campaign assets.

Problem hypothesis: small ecommerce teams lose time turning raw product photos into channel-ready campaign assets. Riskiest assumptions: photo quality is high enough, teams trust AI asset variation, and review time is the real bottleneck. Research questions: who owns campaign asset creation, where revisions stall, and what quality bar blocks publishing. Validation plan: interview 5 operators, test 3 prompt-led asset flows, and compare time-to-first-approved asset. Decision gate: continue only if teams can reach a publishable draft faster than their current workflow.

chat thread

Here is the outline for our AI product landing page. Tell me what is unclear before we design it.

Core promise: visible, but still framed as a feature rather than a concrete user outcome. Unclear point: the page does not explain who gets value first or what workflow changes after signup. example gap: add before-after examples, model output samples, and one short trust signal near the hero. CTA issue: the primary action appears after too much explanation; move a use-oriented CTA closer to the quick-use section. Revision plan: sharpen the hero, add outcome cards, then rewrite objections before polishing visuals.

chat thread

A customer says their export failed twice and asks for a refund. Here are our policy notes...

Issue type: repeated export failure plus refund request. Customer-facing reply: acknowledge the failed attempts, apologize plainly, and confirm you will help recover the export path first. Policy boundary: explain refund eligibility only from the provided policy notes; do not promise an exception. Next step: ask for export format, browser, and timestamp, then route to billing if the account meets refund criteria. Internal note: tag as product reliability risk because the same export failed twice.