Build a source-aware research plan

Auteur: AILesson5 min de préparationTesté avec:ChatGPTClaudeGeminiRévisé: 2026-08-28

Réponse rapide

Plan what to investigate, where to look, and how to separate evidence from inference. Fournir: Research topic, Decision this research should support, Scope and constraints. Résultat attendu: A research plan with questions, source hierarchy, and evidence rules.

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Create a research plan for this topic:
[topic]

The research must support this decision:
[decision]

Scope and constraints:
[limits]

Produce:
1. The decision-relevant questions, ordered by importance
2. A source hierarchy that prioritizes primary and current sources
3. Suggested search queries for each question
4. What evidence would confirm or weaken each possible conclusion
5. A table for recording claim, source, publication date, evidence, and confidence

Do not answer the research questions yet. Flag time-sensitive claims that will require current verification.
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De l'entrée au résultat

Un exemple détaillé

Voyez comment un contexte concret transforme cette recette en résultat utilisable.

Entrée réelle

Research topic
Whether a 35-person remote design agency should replace its current video-meeting tool with an AI meeting assistant that records, transcribes, and summarizes client calls.
Decision this research should support
Recommend whether to run a paid pilot, and define the minimum consent, privacy, security, and workflow requirements that a pilot product must meet.
Scope and constraints
Cover clients and staff in the EU and UK. Compare at most three products. Use no more than two working days for desk research. Prioritize sources published or updated within the last 12 months. Do not evaluate transcription accuracy through hands-on testing yet.

Exemple de sortie

1. Decision-relevant questions

  1. What consent and notification controls exist for recording EU and UK participants?
  2. How does each provider process, retain, delete, and train on recordings and transcripts?
  3. Which security controls and contractual commitments can be verified?
  4. Can administrators enforce the required settings across the agency?
  5. Does the workflow support client calls without unacceptable friction or hidden cost?

2. Source hierarchy

  1. Current product documentation, privacy notices, data-processing agreements, subprocessors, security pages, and pricing pages.
  2. EU and UK regulator guidance and applicable official legal texts.
  3. Current trust-center audit reports or certifications.
  4. Reputable independent analysis for context only; reviews and forums may suggest questions but should not establish compliance.

3. Suggested searches

  • Consent: [product] recording consent EU UK notification controls
  • Data use: [product] privacy DPA retention deletion AI training transcripts
  • Security: [product] trust center SOC 2 ISO 27001 encryption subprocessors
  • Administration: [product] admin disable recording retention policy SSO
  • Workflow and cost: [product] pricing meeting bot client consent integrations 2026

4. Evidence tests

A pilot is strengthened by documented participant notification, configurable retention and deletion, a suitable DPA, verifiable security controls, centralized administration, and transparent pricing. It is weakened by ambiguous training use, uncontrollable bot entry, missing regional terms, unverified security claims, or costs that cannot be bounded. Transcription quality remains unresolved because hands-on testing is excluded.

5. Evidence log

ClaimSourceDateEvidenceConfidence
Requirement or product claimDirect URL or documentPublished or accessed dateRelevant passage or settingHigh/Medium/Low

Current verification required: pricing, feature availability, subprocessors, retention controls, certifications, privacy terms, and regulator guidance.

Pourquoi cela fonctionne

  1. 1

    It anchors research to a decision instead of collecting interesting facts.

  2. 2

    The source hierarchy and evidence table make later conclusions traceable.

Vérifier le résultat

  • Does every research question change or inform the decision?

  • Are primary sources preferred for product behavior, prices, and policies?

Utilisez-la en toute confiance

Questions fréquentes

Des réponses pratiques sur le bon moment pour utiliser cette recette, ce qu’il faut fournir et les cas où une vérification humaine reste nécessaire.

What should I prepare before using “Build a source-aware research plan”?

For “Build a source-aware research plan,” prepare Research topic, Decision this research should support, and Scope and constraints. Replace placeholders only with information you can verify. If a detail is unknown, preserve that uncertainty explicitly instead of asking the model to infer it.

When is the “Build a source-aware research plan” result not ready to use?

The result is not ready if it does not yet deliver the stated outcome—A research plan with questions, source hierarchy, and evidence rules—from the supplied evidence, or if it relies on unresolved assumptions, missing approvals, or invented details. Use the checks as release gates: revise the source inputs or assign a named, authorized reviewer instead of polishing an unsupported output.

Which AI tools have recorded tests for “Build a source-aware research plan”?

The published test record for “Build a source-aware research plan” lists ChatGPT, Claude, and Gemini as of 2026-08-28. This confirms recorded runs, not guaranteed compatibility or identical results in later product versions. For another tool or version, keep every constraint visible and repeat the result checks before use.

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