zlacker

>>simonw+(OP)
I wonder if the era of dynamic programming languages is over. Python/JS/Ruby/etc. were good tradeoffs when developer time mattered. But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go (assuming enough training data on the language ofc; LLMs still can't write Gleam/Janet/CommonLisp/etc.).

Esp. with Go's quick compile time, I can see myself using it more and more even in my one-off scripts that would have used Python/Bash otherwise. Plus, I get a binary that I can port to other systems w/o problem.

Compiled is back?

>>behnam+sj
My intuition from using the tools broadly is that pre-baked design decisions/“architectures” are going to be very competitive on the LLM coding front. If this is accurate, language matters less than abstraction.

Instructions files are just pre-made decisions that steer the agent. We try to reduce the surface area for nondeterminism using these specs, and while the models will get better at synthesizing instructions and code understanding, every decision we remove pays dividends in reduced token usage/time/incorrectness.

I think this is what orgs like Supabase see, and are trying to position themselves as solutions to data storage, auth, events etc within the LLM coding space, and are very successful albeit in the vibe coder area mostly. And look at AWS Bedrock, they’ve abstracted every dimension of the space into some acronym.