I believe the majority still doesn't understand the momentous threshold humanity is facing.
Anthropic itself states quite clearly that even if development ceased entirely, if all development were frozen, they would still witness massive societal changes:
"Even if model capabilities were frozen at today’s level, we would expect major changes to occur in the world. (...) And we are still early in the diffusion of today’s models into the wider economy, where a 100-person company can increasingly do the work of a 1,000-person one, because each employee will sit atop a pyramid of agents."
But there's no question of stagnation. Anthropic itself still maintains that development has exceeded its own internal assumptions. Take that statement seriously for a second and consider it. Although Anthropic models internally and assumes exponential development, even this trajectory lags behind actual development, which is even faster.
"It's happening faster than we thought, and the implications deserve greater attention."
and
"The rate at which AI models improve is accelerating. The length of tasks that they can reliably complete on their own has been doubling roughly every four months, up from an earlier trend of doubling every seven months. In March 2024, Claude Opus 3 could complete software tasks that take humans about four minutes to complete. A year later, Claude Sonnet 3.7 managed tasks that took about an hour and a half. A year after that, Claude Opus 4.6 managed 12-hour tasks.1 If this trend holds, tasks that take a skilled person days could come into range this year.
So again: there can be no question of standing still.
The models are not only getting better, they can also work autonomously for longer. Certainly numerous breakthroughs are still needed, context window is still a problem. But the most likely direction is that the models themselves will find the solutions to the underlying problems. This opens up unforeseen possibilities, and Demis Hassabi's statement that the golden age of science is not a dream, not a utopia, but a purposeful reality, is now confirmed.
And finally, it's not just Anthropic, but also OpenAI, that sees this development, considers it feasible, and is moving forward.
Most people don't know what's coming. But one thing is certain: it's coming even faster than expected. And it will be even bigger.
Myth was just the beginning.
Holy moly, Anthropic is getting very serious about recursive self-improvement!
One word: acceleration.
Insane blog article.
Tl;dr:
•We are close to an AI capable of fully autonomously designing and building its own successor
•They stress this isn’t here yet and isn’t inevitable, but could arrive sooner than most institutions are ready for
•Anthropic engineers now ship on average 8x as much code per quarter as they did in 2021–2025
•Task length AI can reliably complete is doubling roughly every 4 months (up from every 7 months)
•Opus 3 (Mar 2024) handled ~4-minute tasks; Sonnet 3.7 (a year later) ~90-minute tasks; Opus 4.6 (a year after that) 12-hour tasks
•SWE-bench went from low single digits to saturated in two years; CORE-bench (research reproduction) went ~20% to saturated in 15 months
•METR found Claude Mythos Preview could work “at least” 16 hours, at the top of what they can currently measure
•As of May 2026, Claude authored 80% of code merged into Anthropic’s codebase (low single digits before Claude Code launched in Feb 2025)
•A March 2026 poll of 130 research staff: median respondent estimated ~4x output with Mythos Preview
•One April 2026 example: Claude shipped 800 fixes cutting a class of API errors 1,000x, work an engineer estimated would have taken a human four years
•Claude-written code quality: worse than human in late 2025, roughly at parity now, expected to be strictly better within the year
•On the hardest open-ended tasks, Claude’s success rate hit 76% in May 2026, up 50 points in six months
•Code-speedup test: Opus 4 averaged ~3x speedup (May 2025), Mythos Preview ~52x (April 2026); a skilled human needs 4–8 hours to hit 4x
•In an AI-safety research project, Claude agents recovered 97% of a performance gap (vs ~23% for two human researchers in a week), over 800 compute-hours and ~$18K
•On picking the better “next step” in research sessions, the best model beat the human choice 51% (Nov 2025, Opus 4.5) rising to 64% (April 2026, Mythos Preview)
•Human comparative advantage, for now: research taste and judgment, i.e. choosing which problems matter and when an approach is a dead end
Three possible futures
•The trend stalls (S-curve), but today’s capabilities still diffuse widely; they consider this least likely
•Compounding efficiency gains, with humans still setting direction; 100-person firms doing the work of 10,000 ; they think this is the likely path
•Full recursive self-improvement, where AI builds its successors and pace is set by compute; the alignment outcome here is what they’re least certain about