This document proposes a low-cost, high-impact strategy to encourage consistent, high-quality feedback from engaged users of ChatGPT and other OpenAI products. Inspired by programs such as Adobe’s “Good Student” recognition and Microsoft’s MVP initiative (albeit with zero operational cost), this suggestion centers around offering a symbolic title or badge to recurring, thoughtful contributors — without any obligations or formal relationship.
Currently, feedback submission channels such as help.openai.com or in-app reports:
- Offer no confirmation, no status visibility, and no feedback loop to the user.
- Leave active contributors uncertain if their input has been received or useful.
- Risk reducing future contributions from thoughtful users due to lack of visible appreciation or acknowledgment.
Moreover, the process lacks a structured way to recognize or retain quality contributors without formal employment.
- A non-operational, symbolic recognition system (e.g., "Community Reviewer", "Power User", or "ChatGPT Insight Contributor")
- Visible only on user profile (if opted-in), or optionally in community boards / email footers.
- No expectation of continued activity or output.
Benefit | Explanation Zero cost | No reward, no support structure, no backend processing. High motivation | Recognition alone is a powerful intrinsic motivator, especially for early adopters or UX-focused contributors. Reputation leverage | Users may list this in CVs, portfolios, or LinkedIn — indirectly boosting OpenAI’s brand. Low risk | No contractual or legal entanglements — purely opt-in and symbolic. Community building | Potential entry point into future invite-only pilot programs or Slack spaces.
- List page of MVP contributors (like GitHub Arctic Vault or Figma Community highlights)
- Light Discord role, Slack tag, or profile badge
- Beta testing pool for UX experiments
Again, none of this is required — the core value lies in title-only, opt-in recognition.
Product feedback is often underutilized or inconsistent in quality. But when engaged users:
- Take time to format markdown reports
- Observe patterns across systems
- Provide multilingual QA context
... it becomes invaluable. Formalizing this into a lightweight recognition structure could:
- Increase retention of such users
- Encourage others to submit meaningful feedback
- Build a layer of trust and pride in OpenAI’s user community
This proposal is not about expanding programmatic infrastructure. It is about psychological momentum — the smallest signal that says, “we see you.”
If OpenAI builds toward a more community-centric feedback ecosystem, this kind of symbolic gesture could be the starting point.