Turn raw ideas into traceable themes, distinct concepts, open questions, and evidence-seeking next actions without implying approval. 제공할 내용: Raw brainstorming record, Problem and decision horizon, Clustering and next-step rules. 예상 결과: A deduplicated idea map with provenance, evaluation readiness, experiments, owners, and deferred items.
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맥락 추가
텍스트는 이 브라우저에 유지됩니다. AILesson Prompts는 이를 모델이나 서버로 보내지 않습니다.
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프롬프트
채워지지 않은 필드는 플레이스홀더로 표시되므로 프롬프트를 복사하고 편집할 수 있습니다
Organize the brainstorming record into themes and defensible next steps.
Ideas, IDs, attribution, wording, votes, comments, constraints, corrections, and context:
[ideas]
Problem, users, outcome, horizon, decision, non-goals, evidence, and session authority:
[goal]
Duplicate/theme rules, provenance, vote meaning, criteria, weights, capacity, experiments, owners, and review:
[criteria]
Preserve every idea ID and original meaning before normalizing wording. Separate problem observations, needs, solution ideas, implementation tactics, risks, questions, existing commitments, and out-of-scope items. Cluster by shared mechanism or user outcome, not keyword overlap, and keep meaningful variants separate. Merge only true duplicates while retaining all source IDs and dissent. Treat votes as the supplied signal—interest, not validity—unless rules say otherwise. Do not rank when criteria or weights are missing; use a readiness review instead. For each concept state evidence, assumptions, dependencies, risks, affected users, uncertainty, and smallest test. Distinguish approved actions from proposed next steps, leaving owner/date unassigned when absent. Return: coverage count; normalized idea inventory; theme map; duplicate/variant ledger; contradictions; criteria/readiness table; now/next/later or another authorized portfolio; experiments and research questions; decision/approval gaps; action register; and archived ideas with retrieval rationale.
기본적으로 비공개프롬프트 구성은 브라우저에서 로컬로 이루어집니다. 조직에서 허용하지 않는 한 기밀 정보를 AI 서비스에 입력하지 마세요.
입력에서 결과까지
적용 예시
구체적인 맥락이 이 레시피를 바로 사용할 수 있는 결과로 바꾸는 방법을 확인하세요
실제 입력
Raw brainstorming record
Workshop on reducing missed volunteer shifts. I01 SMS reminder 24h before (6 dots). I02 WhatsApp reminder (4). I03 let volunteers choose reminder channel (8). I04 auto-call elderly volunteers (1; comment warns stereotyping). I05 coordinator dashboard of unconfirmed shifts (7). I06 require confirmation 48h before (5). I07 waitlist auto-fill after decline (6). I08 clearer cancellation button (3). I09 ask why people miss shifts (2). I10 add calendar file to confirmation email (5). I11 SMS at 24h (duplicate wording of I01, 2). I12 coordinators call everyone (0; capacity concern). I13 reminder accessibility review (no vote). Correction: votes indicate participant interest only; 12 participants, multiple dots allowed. No idea approved. Existing email reminder already sends 72h before but delivery/opening not measured.
Problem and decision horizon
Problem observation: 14% of scheduled shifts were recorded as no-show last quarter, but cancellation-recording errors may be included. Goal is reduce avoidable uncovered shifts without increasing unwanted contact or coordinator load. Decide only which evidence or prototypes to pursue in a four-week discovery period, not launch features. Volunteers have varied phone access and consent; elderly is not an approved segment. Out of scope: penalties. Evidence limited to schedule records and coordinator anecdotes.
Clustering and next-step rules
True duplicate = same mechanism, timing, audience, action. Preserve channel/timing variants. Criteria approved but weights not: potential to reduce uncovered shifts, consent/privacy, accessibility, coordinator effort, implementation/test effort, reversibility, evidence gap. Capacity: one researcher and one designer. At most two tests. Product manager approves tests after privacy review. Owners/dates not assigned. Archive remains searchable by ID.
예시 출력
Coverage: 13 IDs accounted for. I01 and I11 are true duplicates and merge with both IDs/votes retained; vote total is not a unique-person count. No item is approved.
Themes: Contact and preference—SMS I01/I11, WhatsApp I02, user-selected channel I03, calendar file I10; I04 is a targeting tactic with stereotyping/consent risk, not a separate need. Confirmation and recovery—I06 confirmation rule, I07 waitlist fill, I05 unconfirmed-shift visibility. Cancellation usability—I08. Discovery and safeguards—I09 investigates cause; I13 is a cross-cutting requirement. High-touch fallback—I12, with explicit capacity concern.
Readiness: all solution themes depend on validating the 14% measure and distinguishing true no-show, late cancellation, and recording error. Votes indicate interest only. I03 is broad and requires consent/channel feasibility; I05 may improve visibility but does not itself fill shifts; I07 has higher operational/privacy complexity; I04 should not proceed with age targeting. Without weights, do not numerically rank.
Two proposed tests, pending product/privacy approval: (1) researcher audits a stratified sample of recorded no-shows and interviews volunteers about causes, channel access, consent, and existing 72h email; evidence is corrected baseline and cause taxonomy; owner/date Unassigned. (2) designer prototypes cancellation/confirmation plus channel choice, testing comprehension and accessible use without sending real messages; compare I03/I06/I08/I13, owner/date Unassigned. Dashboard/waitlist concepts move to Next after baseline; calendar file is Later low-cost candidate; auto-call-by-age is Archived as currently framed but retrievable under I04; call-everyone is Deferred for capacity. Decision gap: product manager and privacy reviewer must approve test scope and assign owners/dates.
효과가 있는 이유
1
Stable idea IDs preserve minority variants and make every summary theme auditable back to the workshop.
2
Readiness and smallest-test fields prevent popular ideas from jumping directly into commitments.
결과 확인
Does every raw idea appear once as retained, merged-with-lineage, deferred, or out of scope?
Are observations, needs, solutions, tactics, risks, questions, and commitments classified distinctly?
Are votes, ranking, approval, ownership, and evidence kept as different concepts?
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What should I prepare before using “Organize brainstorming results and define next steps”?
For “Organize brainstorming results and define next steps,” prepare Raw brainstorming record, Problem and decision horizon, and Clustering and next-step rules. 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 “Organize brainstorming results and define next steps” result not ready to use?
The result is not ready if it does not yet deliver the stated outcome—A deduplicated idea map with provenance, evaluation readiness, experiments, owners, and deferred items—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 “Organize brainstorming results and define next steps”?
The published test record for “Organize brainstorming results and define next steps” lists ChatGPT 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.
ChatGPT
