

If LLMs aren’t going to reach a point where they outperform a junior developer who needs too much micromanaging to be a net gain to productivity, then AI’s not going to be a net gain to productivity, and the only productive way to use it is to fight its adoption, much like the only way to productively use keyboards that had a bunch of the letters missing would be to refuse to use them. It’s not worth worrying about obsolescence until such a time as there’s some evidence that they’re likely to be better, just like how it wasn’t worth worrying about obsolescence yet when neural nets were being worked on in the 80s.










There’s a pretty good reason to think it’s not going to improve much. The size of models and amount of compute and training data required to create them is increasing much faster than their performance is increasing, and they’re already putting serious strain on the world’s ability to build and power computers, and the world’s ability to get human-written text into training sets (hence why so many sites are having to deploy things like Anubis to keep themselves functioning). The levers AI companies have access to are already pulled as far as they can go, and so the slowing of improvement can only increase, and the returns can only diminish faster.