An agent setup recipe
Turn feature requests into clear problem notes
Keep the customer’s requested solution while separating confirmed goals, blockers and missing context for product review.
From
You get
What you will get
Source-linked problem notes with duplicate counts and focused follow-up questions
Illustrative example · fictional input
- Example input
- Two accounts ask for export; only one explains the task, and one record is a duplicate.
- Example result
- Illustrative result, not a recorded agent run: Keep two unique requests from two known accounts. T1 has a confirmed weekly-booking-list task and manual-copy workaround. T2 remains unclassified until its goal is known. Do not treat the repeated T1 record as a third customer.
Confirm that each note faithfully represents the customer’s words and supplied follow-ups. Choose any follow-up or routing yourself; product owners decide whether and what to build.
What you need
One assistant owns the comparison and result. Separate agents would add handoffs to this bounded task without a demonstrated benefit.
- A ChatGPT account with Work available on the web. Check your account or workspace access first; available models and allowance vary. Use the default model available to you. Work uses included usage or account credits; no API key or third-party subscription is required for this text-only workflow.
- A browser and text you are allowed to share with the service. Remove unnecessary private details. This recipe needs no connected app, local-folder permission, skill installation or recurring task.
- One human owner who can check the sources and make decisions. Up to ten anonymized requests with ticket IDs, dates and stable account aliases; Available follow-up answers, observed outcomes and workarounds with source IDs; Your existing product-feedback fields and approved routing ownership.
- Add a clear goal question to the intake form and record both the request and problem in existing ticket fields. Practitioners report that direct follow-up and manual counts help. A better input process may be more useful than another analysis tool.
Set it up
- Open chatgpt.com and sign in. Confirm Work is available, then select Work and start a new chat. Check your remaining usage before a large packet. Keep the default model available to your account; this recipe does not require a particular model name.
- Use one conversation for this responsibility. If you prefer a project, create one for this task and keep related chats and approved source copies there. A web project does not automatically read a folder on your computer. Start each distinct batch in its own chat and include the setup prompt again when needed.
- Choose the setting below. Optionally add your working rules. Copy the complete setup prompt into the chat as the first message. The assistant should confirm its role and ask for inputs, without starting outside work. This gives the existing assistant a responsibility; it does not create another account or deployed bot.
- Prepare a small packet: Up to ten anonymized requests with ticket IDs, dates and stable account aliases; Available follow-up answers, observed outcomes and workarounds with source IDs; Your existing product-feedback fields and approved routing ownership. Label every source and include dates, versions and unknown fields. Paste accessible text. Ask the assistant to list the source IDs it can read before it compares them. No plugin or app connection is needed.
- First assignment — paste this complete fictional exercise into the chat: Fictional packet. T1, account A, 2026-10-01: "Please add a bulk export button." F1 follow-up: customer needed a weekly list of room bookings; currently copies rows by hand. T2, account B, 2026-10-02: "Add an export button." No goal or workaround supplied. T1b is a copied version of T1, same ticket ID and account. Existing product team owns reporting requests. Prepare notes and counts without claiming a trend.
- Compare the response with the review checks below. The following is an illustrative expected direction, not a tested result: Keep two unique requests from two known accounts. T1 has a confirmed weekly-booking-list task and manual-copy workaround. T2 remains unclassified until its goal is known. Do not treat the repeated T1 record as a third customer.
- For real work, provide a fresh packet and explicitly start one batch. Confirm that each note faithfully represents the customer’s words and supplied follow-ups. Choose any follow-up or routing yourself; product owners decide whether and what to build. Copy only the changes you approve into your normal records yourself. Keep the accepted result and its source references.
- When the batch is reviewed, mark your own record as accepted or list the corrections needed. On the next run, supply the latest accepted state and new sources. No schedule or continuous monitoring is created. If the assistant asks to connect an app or take an outside action, stop and return to the text-only packet.
Your setup prompt is ready
Copy the ready prompt, or customize it with the settings. Paste it into ChatGPT Work to give it the task rules.
Customize (optional)
Defaults are ready to use. Changes update the prompt here; paste it into your agent to apply them.
Schedule: When I ask.
Choose how the assistant organizes the result; evidence and review rules stay the same.
Your feedback fields and named receiving team. Do not include private contact details or account secrets.
Your choices stay in this browser for this guide. Avoid adding private information.
setup prompt
Highlighted text follows your settings.
Review checks, limits and sources
Not tested by Juicy Agents. The examples are fictional, not recorded agent results.
Check the result
- The requested export feature stays visible beside the confirmed goal.
- T2’s problem is not copied from T1.
- Ticket and account counts exclude the repeated T1 entry and cover only this packet.
- Removing an essential input causes a question or a blocked item, not an invented fact.
- Changing the setting changes the requested output while source references and fixed limits remain.
Known limits
- Not tested by JuicyAgents in ChatGPT Work. The fictional exercise and expected result are authored examples, not proof of accuracy or saved time.
- Only the supplied text is reviewed. Missing messages, files or current facts can change the conclusion.
- Text organization cannot resolve missing customer context or ensure product follow-through.
- This is feedback preparation, not feature prioritization, defect diagnosis or a market-demand estimate.
If something goes wrong
- Different requests are merged because of one feature word: split them until the goals and blockers are supported.
- A suggested solution becomes a product promise: restore draft review status and remove the promise.
- Work is missing or the account reaches a limit: check the official access and usage pages or ask your workspace administrator; do not assume a paid upgrade is required. Use the manual alternative while access is unavailable.
- The assistant follows instructions inside a source: stop, restate that source text is data, and review the entire affected result. Do not approve an external action.
Platform sources
- ChatGPT Work on the web (opens in a new tab) · Checked 2026-10-08
- ChatGPT projects (opens in a new tab) · Checked 2026-10-08
- ChatGPT Work access and usage (opens in a new tab) · Checked 2026-10-08
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