The current way AI helps build better AI is more accurately described as an "autocatalytic effect"—using AI as a tool to accelerate development (e.g., creating GPU kernels). This is distinct from the sci-fi concept of "recursive self-improvement" (RSI), where a system holistically creates a better version of itself.

The AI development cycle of experimentation and bottleneck-solving is already a form of recursive self-improvement. Kyle Corbitt argues this loop is currently constrained by human intelligence. Once AIs become better at directing this process, progress will accelerate rapidly.

Fears of AI's 'recursive self-improvement' should be contextualized. Every major general-purpose technology, from iron to computers, has been used to improve itself. While AI's speed may differ, this self-catalyzing loop is a standard characteristic of transformative technologies and has not previously resulted in runaway existential threats.

The most transformative aspect of AI may be its ability to automate its own research and development. This creates a recursive improvement cycle—an "intelligence explosion"—where progress accelerates exponentially, compressing decades of innovation into a much shorter period.

The concept that AIs can build better AIs, creating an accelerating feedback loop, is no longer theoretical. Leaders from Anthropic, OpenAI, and Google DeepMind have publicly confirmed they are actively using current AI models to develop the next generation, making RSI a practical engineering pursuit.

The path to recursive self-improvement won't start with an AI discovering principles from scratch. Instead, it will begin by automating the process of incorporating the latest human-driven progress. AI labs will turn their recent bug fixes and discoveries into new training environments, effectively distilling the last few months of human R&D into the next model.

Unlike any prior tool, AI can be directly applied to improve its own creation. It designs more efficient computer chips, writes better training code, and automates research, creating a recursive self-improvement loop that rapidly outpaces human oversight and control.

Companies like OpenAI and Anthropic are not just building better models; their strategic goal is an "automated AI researcher." The ability for an AI to accelerate its own development is viewed as the key to getting so far ahead that no competitor can catch up.

The expert inside view is that RSI will likely manifest as another significant acceleration in AI capabilities—a "kink" in the progress curve—rather than a sudden, discontinuous singularity. This informs a more measured, though still urgent, approach to planning.