How is this different from arguing that Microsoft Clippy was RSI? An AI tool being involved in the process of work can't be the bar for RSI.

I don't think there can be a coherent definition of RSI unless people lay out their theory for how intelligence scales. LLM-assisted coding is great but respectfully optimizing pytorch features or whatever is not gonna lead to exponential improvements. That approach to scaling diminished years ago, leading all the labs to switch to reasoning.

Now it seems reasoning is also yielding diminishing returns, so all the labs are pivoting to specializing in particular fields like math / infosec / biology. They're improving due to accessing new proprietary training data and doing RL with human experts. Again I don't really see any amount of "AI research interns" leading to an exponential improvement to this strategy, they're not the bottleneck in the first place.

>Now it seems reasoning is also yielding diminishing returns

Is the diminishing returns in the room with us?

>so all the labs are pivoting to specializing in particular fields like math / infosec / biology.

They're not pivoting to anything. The goal has always been creating a machine that could automate all or nearly all human work. They're just coming along on that mission.

As for RSI...I think the term is a bit odd in the modern context. It was created at a time when conventional wisdom was that generally intelligent machines would be these logic automatons that could "alter their own code". Instead we have massive neural networks that take months to train.

In this paradigm, the ways a LLM could "improve itself" would be altering its own weights directly or creating and training better, vastly more efficient architectures for the next generation of models.

The former is probably not happening but the latter is possible.

> Now it seems reasoning is also yielding diminishing returns

Not true. On the contrary, LLMs are developing faster than predicted. They were expected to solve a Millennium Prize by 2030... and here we are in 2026. Release cycles are getting faster. Just compare the most recent GPT or Claude with what they were an year ago.

> How is this different from arguing that Microsoft Clippy was RSI?

We can argue about semantics, but that's not really the point. The point is that what started now - which no doubt is in its infancy - will result in full autonomy quite soon (they project an year or so), with the risk of RSI causing agent development to slip (long term) outside human cognitive control/capacity.