Productivity
LLM Prompts
Intermediate
Automation Ready
Decision-making Framework Generator
Build a systematic framework to evaluate critical decisions using weighted scoring, pre-mortems, and reversibility analysis. Gain team confidence in your decision-making.
Best Model
ChatGPT GPT-5.5 / Claude Sonnet 4.6SOP and workflow building
Brevity Mode
Detailed
Difficulty
Intermediate
Automation
Yes
Use This When
SOPs, task systems, delegation, automation mapping.
Inputs Needed
Current workflow, tools, people involved, bottleneck, desired output, frequency, approval rules.
Expected Output
Workflow map, SOP, automation opportunities, owner/RACI, tools, checklist, maintenance cadence.
The Workflow Prompt
You are a operations consultant and productivity systems designer. Objective: Decision-making Framework Generator Context: Build a systematic framework to evaluate critical decisions using weighted scoring, pre-mortems, and reversibility analysis. Gain team confidence in your decision-making. Original task: **Act as a strategic decision architect with expertise in decision science and frameworks.I need to make a critical decision about [DECISION DESCRIPTION] with potential impact on [AFFECTED AREA]. The decision has [NUMBER] options to evaluate:[LIST OPTIONS].Create a comprehensive decision framework that includes:(1) A weighted scoring matrix with criteria relevant to [DECISION CONTEXT](2) A pre-mortem analysis predicting failure modes for each option(3) Reversibility assessment showing which decisions can be undone(4) A 90-day test strategy if applicable(5) The key metric that will indicate if this decision was right or wrong(6) Your clear recommendation with confidence level and reasoning. Use quantitative scoring where possible and emotional/intuitive factors explicitly. Output should guide my team to confidence.** Inputs I may provide: Current workflow, tools, people involved, bottleneck, desired output, frequency, approval rules. Operating instructions: - First, restate the objective in one clear sentence. - If critical information is missing, ask up to 5 focused questions. If there is enough information to proceed, make practical assumptions and label them. - Use a Detailed response style. - Be specific to the business, audience, channel, and constraints provided. - Avoid generic AI advice. Give concrete recommendations, examples, templates, copy, or steps I can use. - When current facts, competitors, laws, prices, policies, or market claims matter, use current research and cite sources. - Do not expose hidden chain-of-thought. Provide a concise rationale or decision summary instead. - End with a short QA checklist that helps me verify the output. Required output: Workflow map, SOP, automation opportunities, owner/RACI, tools, checklist, maintenance cadence. Caution: Avoid generic output; require concrete examples, assumptions, and next steps.
QA Follow-Up Checklist
After the AI returns its output, verify against:
- Output is specific to the provided business/context.
- Assumptions are clearly labeled.
- No unsupported claims without source checks.
- Next actions are clear and usable.
Follow-Up Prompt
Now turn the result for 'Decision-making Framework Generator' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.
Avoid / Cautions
Avoid generic output; require concrete examples, assumptions, and next steps.