Several parts of this idea have already been proposed separately in the community: submitting feedback from ChatGPT, AI-generated summaries, duplicate detection, voting, routing, and status tracking.
This proposal is not intended to claim that each of those elements is new. What I would like to suggest is connecting them into one consent-based, conversation-native workflow:
Conversation → Recognition → Summary → Approval → Similarity Search → Join or Create → Structured Submission → Support → Tracking
The current problem
Many useful product ideas, UX problems, and feature requests arise naturally while people are using ChatGPT.
A user might say that an important list should be pinnable, that a workflow needs a dedicated button, that a state should persist across a long project, or that an existing subscription does not fit a particular type of user.
These can be valuable product insights, but they often remain inside the conversation. The user currently has to recognize the feedback opportunity, find the right channel, rewrite the idea, search for related requests, and decide whether to create a new topic or join an existing one.
That friction means that many potentially useful ideas are probably never submitted in a structured form.
The proposed workflow
1. Optional feedback recognition
ChatGPT could optionally recognize when a conversation contains a reasonably clear product problem or improvement idea.
It could ask:
“This sounds like potentially useful product feedback. Would you like me to prepare a short, standalone summary for you?”
This would only be an offer. The user could decline, and proactive suggestions could be disabled entirely so that they do not become frequent or disruptive.
Nothing would ever be submitted automatically.
2. An AI-generated summary that the user controls
With the user’s permission, ChatGPT could prepare a structured draft containing fields such as:
- Product area
- Problem
- Suggested improvement
- Use case
- Expected benefit
- Platform
- Frequency or impact
The user would see the exact content intended for submission. They could edit it, clarify it, ask ChatGPT to regenerate it, or cancel it.
The workflow would continue only after explicit approval.
3. Similarity search before creating a request
Before creating anything new, the system could search for semantically similar existing requests.
It could show likely matches and briefly explain how each one overlaps with, or differs from, the new proposal.
The AI should not silently merge requests or decide that two ideas are identical. It should only recommend possible matches. The final choice should remain with the user, or with a moderator when necessary.
4. Join an existing request or create a new one
If a suitable request already exists, the user could:
- support it;
- add a new use case;
- report that the issue also occurs on another platform;
- add accessibility, technical, or UX details;
- explain the impact in their own workflow.
If none of the suggested matches adequately covers the idea, the user could create a separate request.
This could reduce duplicate topics without erasing meaningful differences between related needs.
5. Structured submission
The final feedback could enter the system in a consistent, processable format. This could make it easier to categorize requests, group related ideas, detect recurring problems, route feedback to the relevant product area, and evaluate frequency and impact.
The user would not need to understand the internal category structure or know how to write a perfect feature request. ChatGPT would help structure and route the feedback while keeping the user in control.
6. Support that adds useful information
Community support should not be limited to simple “+1” replies.
Alongside supporting an idea, users could contribute structured details. The system could then show not only how many people want something, but also the situations, platforms, accessibility needs, and workflows in which the problem occurs.
Popularity should remain only one signal. A large vote count should not automatically outweigh a less popular but serious accessibility, safety, or reliability problem.
7. Transparent but realistic status tracking
Users could optionally follow requests they submitted or supported.
Possible statuses might include:
- Submitted
- Needs More Information
- Under Review
- Planned
- Not Planned
- Released
These statuses should appear only when they are backed by a real, maintained process. An automatically displayed “Under Review” label would be misleading if no actual review had taken place.
This would not require OpenAI to publish a detailed roadmap or promise that every request will be implemented. Even a small number of reliable statuses could reduce the feeling that feedback disappears into a black hole.
Privacy and user control
The original conversation should never be forwarded automatically.
The core safeguards should be:
- The workflow is optional.
- The user sees the exact payload before submission.
- Submission requires explicit confirmation.
- By default, only the approved summary is sent, not the full conversation.
- The system can warn about personal or sensitive information.
- The user can edit or cancel before submission.
Spam, incorrect clustering, and operational cost
Making submission easier could also increase low-quality feedback. Rate limits, quality checks, trust levels, and human moderation may therefore still be necessary.
Similarity search will not be perfect either. Users should always be able to explain why their proposal is meaningfully different from an existing request.
Status tracking is useful only if it is connected to a genuine product or feedback-management process. Otherwise, it could create false expectations instead of trust.
What makes this different?
Previous community topics have already proposed individual parts of this system, including feedback submission from ChatGPT, AI-assisted summaries, structured feedback, routing, duplicate detection, community voting, and status tracking.
The distinction here is the complete lifecycle:
Recognize → Summarize → Approve → Search → Join/Create → Submit → Support → Track
ChatGPT would not merely help fill out a feedback form. It would become an intelligent, user-controlled bridge between natural conversations and a structured product-feedback system.
Related community discussions
This concept builds on several ideas that have already been discussed separately:
- Allow Users to Submit and Vote on Feature Ideas Directly Inside ChatGPT
- Suggestion: Dedicated App for Sharing Feedback and Ideas
- Feature Request: Let ChatGPT Submit Product Feedback from the Conversation
- Proposal: AI-Assisted Product Feedback Pipeline
- Idea: AI-Assisted Routing for Developer Community Feature Requests
- Transparent, User-Driven Feedback System for ChatGPT
The goal is not to repeat those proposals, but to explore how their strongest elements could work together as one coherent workflow.
Disclosure: The text of this proposal and the accompanying concept image were created with AI assistance and then reviewed and approved by me. The image is an unofficial community concept, not an existing OpenAI interface or product roadmap.