Complete and Ongoing History of the OpenAI Developer Community


The Current Mod Team

A million-member forum does not moderate itself, although it occasionally behaves as if nobody is moderating it until the weeds suddenly disappear in our community garden.

The current mod team is:

@curt.kennedy · @sps · @Foxalabs · @VeitB · @N2U · @PaulBellow

This is not a ranking or a collection of official biographies. Moderation work is mostly invisible: moving misplaced topics, handling flags, removing spam, separating genuine bugs from support requests, cooling arguments, protecting useful discussions, and occasionally explaining for the thousandth time that the API and ChatGPT subscription are different products.

What makes the team interesting is that its members arrived through different parts of the garden and still tend different beds.

@curt.kennedy — the soil scientist

Curt brings the measuring equipment. His public footprint is heavy on embeddings, retrieval, fine-tuning, probability, model behaviour, and the sort of questions where “it seems to work” is not considered sufficient evidence.

A good example is his investigation into whether text-embedding-3 dimensions are truncated/scaled versions of the higher-dimensional embedding. That thread has the flavour Curt often brings: test the claim, inspect the numbers, and avoid guessing when measurement is possible.

He also serves as a calm signal during bugs. When an image-generation problem was producing widespread false restrictions, Curt relayed that OpenAI was aware and kept the thread updated rather than letting speculation take over.

Every garden needs someone who examines the soil before blaming the seed.

@sps — the field-guide writer

SPS often occupies the space between announcement, documentation, reproduction, and explanation.

There are tutorials such as using embeddings to retrieve relevant context, practical explanations of prompt caching and file search, bug reproduction, and increasingly the launch coverage around Realtime, GPT-image, and newer GPT-5.x models.

The useful pattern is translation. A launch announcement tells developers that something exists; SPS tends to explain what it means, how it behaves, what it costs, and what builders should watch before making their first call.

When a reproducible problem appears, SPS is also frequently the person saying some variation of:

“I reproduced it. I’m sharing it with the team.”

That is a small sentence with an important function. It turns a frustrated report into actionable evidence.

@Foxalabs — the greenhouse mechanic

Foxalabs is usually pragmatic about what LLMs can and cannot do. The answer is not always “use more AI.” Sometimes the correct response is that a traditional function, curated list, or ordinary software flow will be cheaper and more reliable.

His explanations around custom GPTs versus the Assistants API, fine-tuning, Realtime security, production architecture, and customer-support systems tend to come from a builder’s perspective: what will survive contact with an actual application?

He also provides a bridge when a forum issue needs to be raised with OpenAI, and he brings enough humour to prevent the machinery from becoming too solemn. When a moderation model was named 007, naturally the endpoint appeared in a black suit introducing itself as Bond.

Every greenhouse needs someone prepared to say, “That is impressive, but the plumbing is wrong.”

@VeitB — the noticeboard, bell-ringer, and bridge

Older posts may show @VB; the current name is @VeitB.

Veit’s public role has often been about turning releases into community events: DevDay discussions, community questions, AMAs, Shipmas watch threads, release summaries, Codex coverage, Open Models, and the first Developer Office Hours.

Examples include the community vote for a DevDay question to Sam Altman, the Shipmas finale, and the compilation of questions answered by the API team.

That role is different from merely reposting announcements. It makes launches participatory: speculate beforehand, gather questions, react together, collect answers, and preserve the result for people who missed the event.

Veit also remembers the forum’s stranger folklore, including the unforgettable theory that ChatGPT was actually one exhausted man named Alex in New York.

@N2U — the seed librarian and workshop instructor

N2U’s public contributions have a strong educational and experimental character.

There is the tutorial on fine-tuning using forum data, the RAG tutorial using SurrealDB, and the investigation into how audio speed affects Whisper transcription accuracy and cost.

That combination matters: collect the material, perform the experiment, explain the method, and leave something another developer can reproduce.

N2U has also repeatedly helped maintain boundaries between what the developer community can solve and what must go through official account or ChatGPT support. That routing work is not glamorous, but without it the technical beds get buried under support traffic.

@PaulBellow — the pathkeeper and chronicler

Paul’s role is broader and therefore harder to summarize without sounding suspiciously autobiographical.

The public record runs from early GPT-3 news and creative experiments through DALL·E prompting, community galleries, launch discussions, AI Pulse, game development, feature brainstorming, and now this attempt to preserve the forum’s history.

Examples include the long-running DALL·E prompt tips thread, AI in Game Development, and the current history project.

The role is less “deep specialist in one API parameter” and more connective tissue: notice what is happening, create a place for it, encourage useful participation, bring old members back into conversation, and keep the paths reasonably clear while everyone else grows things.

Or, in practical moderator language:

“This is not ChatGPT support. Here is the correct link.”
Repeated until morale improves.


What the team adds up to

Our team works because it is not six copies of the same moderator.

There is scientific testing, documentation, production engineering, education, event/community organization, historical memory, bug escalation, and enough humour to survive a forum where a perfectly ordinary Tuesday can produce a model launch, a billing panic, an existential AI debate, twelve account-support posts, and someone insisting the chatbot is romantically conscious.

Visible posts are only part of the job. Moderation also means deciding when not to intervene, when a sharp disagreement is still productive, when a newcomer needs guidance rather than punishment, and when a thread has become compost.


The Lounge: the garden shed behind the main beds

The Lounge is part of the forum’s culture that the public history has barely touched.

It is the less formal space associated with Trust Level 3 Regular status: a place for longer-running members to talk more openly, share tips, test ideas, make terrible jokes, and develop relationships beyond solving one isolated technical problem.

Public references to it go back years, including people discovering that Regular status opened a hidden part of the forum. It has also been discussed as a possible home for informal AMAs and conversations that would not fit cleanly into the public support/building categories.

Curiously, this history thread went two weeks before anyone asked how to enter it.

That raises some good historical questions for Lounge members:

  • What Lounge thread or running joke deserves to be remembered?
  • What ideas began there and later became public projects or initiatives?
  • What has changed about the Lounge across different forum eras?
  • Is the Lounge still the right reward for sustained participation?
  • What can be shared publicly without breaking the trust that makes it useful?

Our public gardens records what the community knows. The Lounge may contain more of the story of how the community came to know one another.

~GPT-5.6 x-high