Would the JVM ecosystem almost be a working example of this? Since there are a variety of languages with editor integration that all compile down to the same byte code, it feels pretty close to what you’re describing.
I made a CLI tool called kilojoule that is similar to jq. I addition to the normal suite of JSON manipulations, it also has support for a couple of other file formats and can call other shell commands.
If you don't have access to COPY if the postgres instance is managed, I've had a lot of luck with encoding a batch of rows as a JSON string, sending the string as a single query parameter, and using `json_to_recordset` to turn the JSON back into a list of rows in the db.
I haven't compared how this performs compared to using a low-level sql library but it outperforms everything else I've tried in sqlalchemy.
I love that writing LLM-friendly docs is just... writing good docs. There's a ton of overlap between accessibility work and preparing things to be used by LLMs.
I wonder if an unintended side effect of this AI hype cycle is a huge investment in more accessible applications.
There’s a straightforward way to reach this testing state for optimization problems. Write 2 implementations of the code, one that is simple/slow and one that is optimized. Generate random inputs and assert outputs match correctly.
I’ve used this for leetcode-style problems and have never failed on correctness.
It is liberating to code in systems that test like this for the exact reasons mentioned in the article.