zlacker

There's a huge caveat i don't see often, which is that it depends on your language for programming. IE. AI is reallllly good at writing Next.js/Typescript apps, but not so much Ruby on Rails. YMMV

>>mattwa+(OP)
I agree with this. People who are writing Python, Javascript, or Typescript tell me that they get great results. I've had good results using LLMs to flesh out complex SQL queries, but when I write Elixir code, what I get out of the LLM often doesn't even compile even when given function and type specs in the prompt. As the writer says, maybe I should be using an agent, but I'd rather understand the limits of the lower-level tools before adding other layers that I may not have access to.

>>el_mem+A1
My hunch is that to exploit LLMs one should lean on data driven code more. LLMs seem to have a very easy time to generate data literals. Then it's far less of an issue to write in a niche language.

Not familiar with Elixir but I assume it's really good at expressing data driven code, since it's functional and has pattern matching.

>>el_mem+A1
I think for some languages like Clojure and Elixir, it's just so easy to get to the level of abstraction you need to write your business logic that everyone does so. So the code does not have any commonalty with each other. Even when using the same framework/library.

But for Python, JS, etc,... it's the same down to earth abstraction that everyone is dealing with, like the same open a file, parse a csv, connect to the database patterns.