Sergey Brin: Google Neural Networks Already Write Code for Their Successors — The Era of Recursive Self-Improvement Has Begun

At the presentation of the Gemini 4 Argon model, Google co-founder Sergey Brin made a statement that marks a qualitative shift in the artificial intelligence industry: the company is already using its own advanced neural networks in daily workflows to develop their direct successors. According to Brin, a process that just a few years ago remained a subject of academic discussions and futurological essays has moved into the category of operational tasks for Google's engineering teams. This is neither a demonstration prototype nor an experimental branch — we are talking about standard practice where AI models participate in creating more powerful versions of themselves.

Recursive Self-Improvement: From Hypothesis to Pipeline

The term Recursive Self-Improvement (RSI) describes a closed loop in which each new iteration of the algorithm accelerates and cheapens the creation of the next one. Brin emphasized that Google researchers are working "hand in hand" with their own models: neural networks do not just answer queries, but act as high-productivity assistants generating the bulk of programming code and hotfixes. The human role in this process is reduced to verification — the engineer checks the result before approval, but the initiative and the volume of generative work belong to the AI agent. Thus, RSI has ceased to be a theoretical concept and has become part of the IT giant's daily pipeline.

The Carbon Model: The Next Frontier Under Brin's Personal Control

At the time of the presentation, Google is already testing the next model under the codename Carbon. According to data voiced by Brin, in coding tasks, Carbon is able to compete with Anthropic Opus 5.5 — one of the competitor's flagship solutions. Testing is conducted under the personal supervision of the company's co-founder, which emphasizes the strategic significance of this stage. The fact that Google's internal model is reaching the level of top external market offerings indicates that the self-improvement cycle is already yielding a measurable performance boost in key benchmarks.

Analyst Forecast: 3–12 Months Until Industry-Wide Transition

Reports from the Gladstone AI analytical unit, referenced by Brin, indicate that most market leaders — including OpenAI and Anthropic — will transition to full-fledged RSI within the next three to twelve months. This means that by the fourth quarter of 2027, recursive self-improvement could become an industry standard rather than a competitive advantage of a single company. For the market, this implies an acceleration of model update rates, a drop in margins at the "purely human" stage of development, and, consequently, a redistribution of roles within engineering teams.

Context and Significance for the Industry

Brin's statement is important not only as a technical update, but also as a signal of a paradigm shift in AI development. If previously neural networks were viewed as a tool created by humans for humans, now they are becoming co-authors and even "parents" of their own subsequent versions. This opens up questions that the industry has not yet had time to formalize: the boundaries of responsibility for errors generated in the RSI cycle, safety criteria in the absence of full human control over every step of generation, and the ethical framework of autonomous self-improvement. Google, being the first to fix the transition of RSI into standard practice, is effectively setting the pace that other market players will be forced to join.