LLMs pose an interesting problem for DSL designers

So with LLMs making it easier to project back and forth between how programmer sees the task at hand, and the underlying dumb/straightforward code they ain't gonna read anyway, maybe we'll finally get to the point of addressing the actual problem of programming language design, which is that you cannot optimize for every task and cross-cutting concern at the same time and expect improvement across the board - we're already at the limit, we're just changing which time of day/part of the project will be more frustrating.

* Not just English, substitute any other human language into the above

As someone who loves a wide diversity of actively evolving programming languages, it makes me sad to think those days of innovation may be ending. But I hope that's not going to happen.

It has always been the case that anyone designing a new language or adding features to an existing one is acutely mindful of what programming language knowledge is already in the heads of their users. The reason so many languages, say, use `;` for statement terminators is not because that syntax is particularly beautiful. It's just familiar.

At the same time, designers assume that giving users a better way to express something may be worth the cost of asking them to learn and adapt to the new way.

In theory, that should be true of LLMs as well. Yes, a new language feature may be hard to get the LLM to auto-complete. But if human users find that feature makes their code easier to read and maintain, they still want to use it. They will, and eventually it will percolate out into the ecosystem to get picked up the next time the LLMs are trained, in the same way that human users learn new language features by stumbling onto it in code in the wild.

So I'd like to believe that we'll continue to be able to push languages forward even in a world where a large fraction of code is written by machines. I also hope that LLM training cost goes down and frequency goes up, so that the lag behind what's out there in the world and what the LLMs know gets smaller over time.

But it's definitely possible that instead of that, we'll get a feedback loop where human users don't know a language feature even exists because the LLMs never generate code using it, and the LLMs never learn the feature exists because humans aren't writing it.

I have this same fear about, well, basically everything with LLMs: an endless feedback loop where humans get their "information" from LLMs and churn out content which the LLMs train on and the whole world wanders off into a hallucinatory bubble no longer grounded in reality. I don't know how to get people and/or the LLMs to touch grass to avoid that.

I do hope I get to work on making languages great for humans first, and for LLMs second. I'm way more excited to go to work making something that actual living breathing people use than as input data for a giant soulless matrix of floats.