ThinkWithPrompt by SynotticThinkWithPrompt

Get a slow client to send feedback and approvals on time

Messages and a timeline-impact note that move a stalled client approval forward without sounding passive-aggressive.

Email & Workplace CommunicationFew-ShotStandardLegalPlanFill-in Template

The prompt

A client is holding up my project by not giving feedback or approvals. Help me get it moving. What I'm waiting on: [DELIVERABLE, decision, content, or access] When it was due and when I sent it: [DATES] Follow-ups I've already sent: [WHAT and WHEN] Impact of the delay: [on launch date, my other commitments, cost] What my contract says about delays: [e.g. timeline shifts, rescheduling fees, or "nothing"] Relationship: [new, long-standing, key account] Give me: 1. A likely reason for the stall (too busy, unsure how to give feedback, internal disagreement, lost interest) and how that changes my approach. 2. A short follow-up that makes responding easy: a specific question, a default option, or a 15-minute call to review together. 3. A timeline-impact message that states the new dates if feedback arrives by a set date, factual and calm, with no blame. 4. A "silence means approval" or pause option I can offer, if my contract supports it, worded fairly. 5. A message to the client's sponsor if my contact has gone quiet, without going over their head rudely. 6. One change to my process (e.g. feedback deadlines in the SOW, consolidated feedback from one person) to stop this happening on the next project. Use the dates I gave. Don't threaten fees my contract doesn't include.

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

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What to fill in

  • DELIVERABLE, decision, content, or access
  • DATES
  • WHAT and WHEN
  • on launch date, my other commitments, cost
  • e.g. timeline shifts, rescheduling fees, or "nothing"
  • new, long-standing, key account

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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