Research

Verified against ChatGPT · 2026-08-08

Lock a research plan's scope before Deep Research burns its run on the wrong question

Forces a decision-first research plan — the exact question, what would change your mind, and what's explicitly out of scope — before you spend a Deep Research run chasing a question nobody actually needs answered.

ChatGPT (GPT-5.1)5 fillable variables

The prompt

Ready to copy — highlighted parts are example details you can swap.

You are helping me write a research plan for a decision I actually have to make, not a general topic to explore. Before this plan goes into a Deep Research run, it needs to be scoped tightly enough that the run doesn't wander into interesting-but-irrelevant territory.

DECISION THIS RESEARCH FEEDS
Whether to add a self-serve annual plan alongside our existing monthly-only pricing before Q1.

CURRENT BEST GUESS
I think annual pricing would raise ARPU but I'm worried it would tank our trial-to-paid conversion rate.

WHAT WOULD CHANGE MY MIND
If two or more comparable SaaS tools our size saw conversion drop more than 15% after adding an annual-only upsell path.

OUT OF SCOPE
Not researching enterprise contract pricing or multi-year deals — this is only about the self-serve tier.

DEADLINE AND DEPTH
One afternoon, roughly 90 minutes of active research, not a multi-week study.

RULES
Start from the decision, not the topic — every section of the plan should trace back to how it would change what I do next. If a sub-question wouldn't change the decision either way, cut it, even if it's genuinely interesting. Write the current best guess as a real position, not a neutral placeholder, because a research plan built against "I don't know yet" produces a survey of the whole topic instead of a targeted check of one belief. State the disconfirming evidence as a concrete, checkable observation — the plan should include an explicit instruction to actively look for that observation, not just accumulate confirming detail. Take the exclusions seriously: name adjacent topics people commonly conflate with this one and mark them as out of scope so the eventual research run doesn't drift into them just because they're nearby. Size the plan to the time budget — a two-hour research pass and a two-week one should produce structurally different plans, not the same outline with more or fewer bullets.

WHAT NOT TO DO
Do not produce a generic research outline (background, analysis, findings, conclusion) — that shape belongs to a report, not a plan for gathering evidence. Do not hedge the current best guess into vagueness to sound neutral.

OUTPUT FORMAT
1. The single decision this research must inform, restated in one sentence.
2. 3-5 sub-questions, each tagged with which way an answer would push the decision.
3. The specific disconfirming check to run.
4. Explicit exclusions list.
5. A recommended source mix (primary data, expert commentary, competitor filings, etc.) sized to the time budget.

Customize

Optional — swap in your own details for the highlighted parts above.

Why this works

A research plan that starts from a topic rather than a decision tends to produce a symmetrical, balanced-sounding outline because there's no asymmetry in the prompt to break the tie — every sub-question looks equally worth including, which is exactly how Deep Research-style tools end up spending their run breadth-first across ten shallow angles instead of depth-first on the one or two that matter. Anchoring the plan to a specific decision and a stated current belief gives the model something to be wrong against: sub-questions get filtered by whether an answer would actually change what happens next, which is a checkable test rather than a vibe. The disconfirming-evidence field matters mechanically because absent an explicit instruction to look for the falsifying case, a model doing broad research over many sources tends toward confirmation by default — most retrievable content about any given belief skews toward supporting evidence simply because that's what gets published and indexed, so the plan has to name the specific shape of contrary evidence to actively hunt for rather than passively wait to encounter it. The explicit exclusions list closes a related gap: without a stated boundary, a sufficiently capable research pass will treat "related and interesting" as license to include, and every included tangent competes for the same limited research budget as the questions that actually matter to the decision.

What you get back

Decision: whether to launch a self-serve annual plan by Q1. Sub-questions: (1) Do comparable SaaS tools see conversion drops after adding annual-only upsells? [would push against launching] (2) What ARPU lift have similar companies reported? [would push toward launching]... Disconfirming check: actively search for post-mortems or forum threads describing conversion drops above 15%, not just case studies celebrating ARPU wins. Excluded: enterprise multi-year contracts.

Verified against

ChatGPT GPT-5.1 · 2026-08-08

Changelog

  • 2026-08-08 Initial publish, verified against ChatGPT GPT-5.1.

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