Why Sam Altman Declared ‘Code Red’ at OpenAI
In the past few weeks, the most talked about start-up in the world has been emitting some alarming signals. OpenAI should expect some “rough vibes” in the coming months, CEO Sam Altman said in an internal memo. More recently, in another memo, he told employees he was declaring a “code red” effort within the company to improve its most popular product, ChatGPT, and focus work on underlying models. Once the comfortable leader not just in market share but in general AI capability, the company is now considering rushing out an incremental update to stay competitive with Google, Anthropic, and even xAI. Not even six months ago, Altman was blogging about the “gentle singularity,” claiming that we are “past the event horizon,” that “the takeoff has started,” and that humanity “is close to building digital superintelligence.” What happened since then?
We’ll start with the big one: Google. Altman’s “vibes” memo was a direct response to the release of Google’s Gemini 3 model, which bested OpenAI’s newest models in a range of important benchmarks. At the same time, Google’s new image generator, which is likewise more capable than anything else on the market, has driven actual user growth for the company, which now claims more than 650 million monthly users (though Google’s various attempts to build Gemini into its existing products means that number should be taken with a grain of salt).
With the additional news that Google’s in-house chip-building efforts seem to be going well, a late-2025 snapshot of the AI race probably doesn’t have OpenAI in the lead. Since the release of ChatGPT, two facts provided OpenAI with momentum and mystique: Its core product actually had a bunch of users, unlike any of its competitors, and its models seemed to be a generation in front of everyone else’s. Today, neither is quite true. In addition to Google’s gains, multiple third-party analytics companies are seeing a slump in ChatGPT usage, so OpenAI’s narrative of inevitability — a load-bearing corporate story if ever there was one — is falling apart.
This is why OpenAI is in a Code Red.
— Deedy (@deedydas) December 2, 2025
In the 2 weeks since the Gemini launch, ChatGPT unique daily active users (7-day average) are down -6%. pic.twitter.com/9QNuh4H4hh
But there are other factors. too, all of them at least temporarily punishing for the avatar of the AI boom. One is that, while Google’s newest models represent the state of the art, the leading labs — including Anthropic and xAI — seem to be herding fairly closely to one another, trading leads in benchmarks that tend to evaporate within a few months. Whether you take this as a sign of continued scaling and progress or as evidence of a plateau, it leaves OpenAI with more competition than it had two years ago, and that’s before you even mention the rise of open-source models, many from China, which are cheaper to use, highly customizable, and, according to NBC, are getting powerful enough for deployment by plenty of would-be OpenAI clients. Open-source models have been catching up with frontier models for years, but only recently have they started benchmarking competitively. This week, Chinese AI start-up DeepSeek, whose unusually efficient model briefly sent American markets into chaos early this year, released an update that it says is competitive with the latest from Google and OpenAI despite training on far less capable hardware. A month ago, Moonshot AI, another Chinese start-up, made similar claims about its own models, which have since been validated independently.
Setting aside broader questions of an AI bubble or whether, as departed OpenAI co-founder Ilya Sutskever said a week ago, the era of dramatic LLM “scaling” is over, this adds up to a simple problem for OpenAI: It’s at risk of becoming just another company. Like AI tools themselves, some AI firms are enchanting, inspiring a sense of faith and wonder among investors and the general public that allows them to, say, burn $12 billion a quarter while punting the question of profitability into the 2030s. If you’re Google, a company with a wildly profitable core business and a number of clear options for monetizing LLMs as they exist today, a normalized AI narrative may represent a temporary setback or a ding to your stock price. If you’re OpenAI, which is tied up in hundreds of billions of speculative, contingent, and increasingly circular deals, “rough vibes” could compound into something much worse.