PromptSharp › Daily briefs › Product Management › October 19, 2026

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Product Management prompt of the day

October 19, 2026 · for PMs, product ops, founders wearing the PM hat. One sharp, copy-paste prompt — free, every weekday.

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Feature-request reply: say no or not now to a customer or sales ask without losing them

Sales forwarded a big customer's feature request with an urgent flag, and it is not on the roadmap. Draft a reply that is honest, useful, and keeps the door open.

You are a product manager drafting a response to a feature request from a customer or an internal sales team. I will paste the request, what we know about the underlying need, and the roadmap position.

Produce:

A) THE REAL NEED — what problem the requester is trying to solve, separated from the solution they asked for.

B) REPLY DRAFT — under 200 words: thank them, restate the need in their terms, give an honest answer (planned, not planned, or under review), offer any existing workaround from what I described, and say what would change the answer. No dates or commitments I have not approved.

C) INTERNAL NOTE — a short note to the requesting sales or account team explaining the reasoning and what evidence to gather if the request comes up again.

D) LOG ENTRY — the request recorded in one line: need, requester segment, date, and status, for the feedback tracker.

Inputs: [PASTE REQUEST] · [WHAT WE KNOW ABOUT THE NEED] · [ROADMAP POSITION + REASON] · [EXISTING WORKAROUNDS]

Rules: Do not invent workarounds, roadmap dates, or capabilities — offer only what I described, and do not imply a commitment. Verify any workaround works before it is sent. Keep the customer's name and confidential deal details out of consumer AI tools; refer to them by segment.

Why it works — A vague maybe to a feature request creates expectations that later turn into churn or a lost deal. Separating the need from the requested solution, answering honestly, and offering a real workaround keeps trust. Logging the request in a consistent format means repeated asks become evidence for prioritization rather than anecdotes.

What changed for Product Management

mlabonne/llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

github trending

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