Thibault Sottiaux, who is responsible for OpenAI's Codex and ChatGPT core products, posted that the pre-release code freeze has basically disappeared; in the future, code may even be generated online upon request and under constraints.

Sottiaux, known publicly as Tibo, currently oversees core products and platforms, covering both Codex and ChatGPT, and reports to Greg Brockman. He has become a public face in the developer community for frequently resetting Codex usage limits after failures. A recent interview with Pragmatic Engineer clarified that he was involved in creating Codex, with the CLI written in open-source Rust, aiming to run proxy instances on massive cloud hosts.

Codex is reported to be one of OpenAI's fastest-growing revenue lines. The product path is an open-source orchestration layer that can connect to multiple models, rather than being locked to proprietary weights; the team has publicly supported linking subscription limits to other programming proxy tools. It continues to compete with Anthropic's Claude Code in the separation of shell and model: the same model can be swapped with a different shell, allowing benchmarks to be rewritten.

"Code freeze" refers to the discipline of freezing submissions during traditional release windows, only fixing blocking defects. Tibo describes it as outdated, effectively acknowledging that proxies have compressed patches, regressions, and release notes into the same pipeline. The next step of "on-demand online generation" transforms repositories from pre-written texts into instant products under constraints—constraints becoming a harder interface than branching strategies.

This is not a new feature announcement, but a philosophy of release: static snapshots give way to regenerable code. Safety and reproducibility will shift from "a certain git hash" to "can a certain set of constraints regenerate the same behavior?"

In market mechanisms, buyers are enterprises and individuals writing millions of lines of patches daily using proxies, while sellers are model companies that incorporate generation, testing, and release into the same quota; funds flow from ChatGPT's paid tiers to tokens and cloud execution. Beneficiaries are orchestration layers that can turn constraints into products, while those under pressure are traditional release managers who rely on frozen windows to control quality and compliance audits that depend on fixed binaries. The event-driven nature comes from the penetration rate of proxy coding, rather than a specific version number.

No exchange data available. What can be verified is the spokesperson's position and the existence of open-source repositories, not a census of "freezes have disappeared in all companies."

Source: Public Information