I think this is the wrong path in LLM and SWE optimizations:

1) Programming language training happens by volume, and the amount of JS/TS/python out there, and the rate it's growing at - is causing a training effects loop, which means for a few generations of models, these will be the best performing languages. Will be hard for a contender to spin up.

2) At some point, if we plateau on productivity - then efficiency improvements will happen, which will open a door for programming languages that maintains productivity, but is 10x cheaper on cost.

3) I think more immediate gains are at the cloud level. IMO, one of the reasons Google cloud is performing better(along with firebase) is much better overall CLI experience, leading to a pleasurable experience developing against it. This part of the market is ripe - whoever builds a most LLM friendly cloud has a shot of shooting up. Hence projects like exe.dev, and whatever cloudflare and vercel are trying. It would be good to have some shakeup in the cloud world.

Anyway, this is where my thoughts are currently.