On "Research acceleration: The view inside OpenAI"

OpenAI's pushing the "recursive self-improvement" narrative hard, and it's worth questioning whether this is actual technical progress or sophisticated marketing for a capability that doesn't clearly exist yet. The framing suggests they've cracked some fundamental problem in AI development—that models can now improve themselves in a scalable, repeatable way—but the gap between that claim and what they're demonstrating in practice remains massive and largely opaque. For practitioners, this matters because it shapes how you think about competitive timelines and capability ceilings; if RSI is real and working, the game changes, but you're betting on claims from a company with every incentive to sound further ahead than it is. Treat it skeptically until you see the actual evidence, not the essay.