Knowledge worker productivity has become relatively uncoupled from pre-ChatGPT levels, as the hardest technical tasks which these workers did at that point in time in a given working day can now in most cases be carried out autonomously by AI.
Programmers therefore begin to work at a higher level of abstraction, guiding AI workers, managing projects at a higher level.
Meanwhile, much progress is being made in robotics. Full self-driving has been achieved.
And AI has begun making novel breakthroughs. This enables continual learning: the AI’s new discoveries open up many new avenues for further discoveries, which open up many more such avenues, ad infinitum.
Image from a recent OpenAI talk
December 2026
Successful reinforcement learning on the September worker AIs has enabled AI to operate at that higher level of abstraction which software engineers had retreated to. Human knowledge workers are therefore relegated to maintenance work and helping out when the few remaining weak points in these AI systems cause trouble.
The difficulty of progress in AI intelligence relative to human intelligence begins reducing rapidly as time horizons extend beyond a few hours. At horizons of this length, human begin relying on caching tricks, iteration, brute force, etc. rather than, beyond a certain point, making fundamentally more difficult leaps of insight.
Early 2027
Humans are cut out of the loop entirely in knowledge work. The robotics explosion happens. Robots gradually replace humans in physical labour. AI progresses far beyond human-level.
Mid 2027
Humans fully obsolesce. Mind upload is achieved.
Notes
I assume a 3-month METR doubling time. We should expect lower doubling times over time given increased investment in AI, increased contribution by AI to progress, and decreased difficulty per double. Also, OpenAI has communicated that we should expect several major breakthroughs from them in 2026.
We should expect doubling times to decrease even further with time, although in a discontinuous way so it’s impossible to predict with much accuracy when it will happen.
Near-Future Fiction III
September 2026
Knowledge worker productivity has become relatively uncoupled from pre-ChatGPT levels, as the hardest technical tasks which these workers did at that point in time in a given working day can now in most cases be carried out autonomously by AI.
Programmers therefore begin to work at a higher level of abstraction, guiding AI workers, managing projects at a higher level.
Meanwhile, much progress is being made in robotics. Full self-driving has been achieved.
And AI has begun making novel breakthroughs. This enables continual learning: the AI’s new discoveries open up many new avenues for further discoveries, which open up many more such avenues, ad infinitum.
Image from a recent OpenAI talk
December 2026
Successful reinforcement learning on the September worker AIs has enabled AI to operate at that higher level of abstraction which software engineers had retreated to. Human knowledge workers are therefore relegated to maintenance work and helping out when the few remaining weak points in these AI systems cause trouble.
The difficulty of progress in AI intelligence relative to human intelligence begins reducing rapidly as time horizons extend beyond a few hours. At horizons of this length, human begin relying on caching tricks, iteration, brute force, etc. rather than, beyond a certain point, making fundamentally more difficult leaps of insight.
Early 2027
Humans are cut out of the loop entirely in knowledge work. The robotics explosion happens. Robots gradually replace humans in physical labour. AI progresses far beyond human-level.
Mid 2027
Humans fully obsolesce. Mind upload is achieved.
Notes
I assume a 3-month METR doubling time. We should expect lower doubling times over time given increased investment in AI, increased contribution by AI to progress, and decreased difficulty per double. Also, OpenAI has communicated that we should expect several major breakthroughs from them in 2026.
We should expect doubling times to decrease even further with time, although in a discontinuous way so it’s impossible to predict with much accuracy when it will happen.