Recursive Self-Improving AI — the technology that could allow machines to iteratively enhance their own intelligence — has evolved from Alan Turing's theoretical "Child Machine" to working prototypes like the Darwin Gödel Machine. Every system today remains a bounded self-improver, but the gap between bounded and unbounded RSI may be the most consequential frontier in human history.

From I.J. Good's intelligence explosion to Schmidhuber's Gödel Machine, Sakana AI's Darwin Gödel Machine, its crimson successor, and the labs racing to close the loop. Introduction: The Loop That Changes Everything Recursive self-improvement (RSI) is the idea that an AI system could improve the process by which it improves itself — a feedback loop where each generation of the system gets better at building the next. It's the mechanism at the heart of most "intelligence explos

Everyone is building the next big model. Almost nobody is building the next intelligence. There's a foolish, unspoken consensus in AI right now: if human-level AGI is coming, it'll come from frontier labs training bigger LLMs and wrapping them in better harnesses. That assumption is short-sighted — and almost certainly wrong. LLMs are powerful tools. They are components of AGI systems, and scaffolding for building them. But they cannot be the core of human-level intelligence.

For years, recursive self-improvement has been one of AI's most debated theoretical milestones — the point at which a system becomes capable of making itself meaningfully smarter without human intervention. Most researchers treated it as a distant horizon. Weco AI just published evidence suggesting it may already be in the rearview mirror. The company's AIDE² system, detailed on the Weco blog, achieved something researchers have long theorized but rarely demonstrated experime