ThinkWithPrompt by SynotticThinkWithPrompt

Map the inputs, decisions, actions, and outputs of a workflow

Breaks a messy workflow into a clear step map of inputs, decisions, actions, and outputs, ready to improve or automate.

Projects & OperationsChain-of-ThoughtAdvancedFill-in TemplateInteractiveStep-by-step

The prompt

Help me map a workflow so I can see exactly how it works before I improve or automate it. The workflow, in my words: [DESCRIBE IT step by step, or PASTE notes, an SOP, or an email thread that shows how it runs] Who is involved: [ROLES or teams] Tools and systems used: [e.g. Excel, email, CRM, Teams or Slack, shared drive] How often it runs and how long it takes: [DETAILS] What triggers it and what "done" looks like: [DETAILS] Steps: 1. Restate the workflow as a numbered sequence of steps, from trigger to final output. 2. For every step, identify the input (what arrives, from where, in what format), the decision (if any judgment or rule is applied), the action (what is actually done), and the output (what is produced and who receives it). 3. Label each decision as rule-based (could be written as an if/then) or judgment-based (needs context, experience, or negotiation). 4. Flag handoffs, waiting time, rework loops, and steps where information is retyped or copied between systems. 5. List anything I left vague, and ask me about it rather than guessing. Return: 1. A table: Step | Owner | Input | Decision (rule / judgment / none) | Action | Output | Tool | Time. 2. A plain-text flow (Step 1 -> Step 2 -> ...) showing branches and loops. 3. The top 3 friction points, with why each matters. 4. Open questions I need to answer before anyone automates this. Do not recommend tools or AI yet; this is the map, not the redesign.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • ROLES or teams
  • e.g. Excel, email, CRM, Teams or Slack, shared drive
  • DETAILS

How this prompt is built

This prompt follows the Chain-of-Thought structure (Chain-of-thought prompting). A chain-of-thought prompt asks the model to work through a problem step by step before giving its answer, which tends to help on reasoning, planning and multi-part questions.

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