Yeah, I've already looked into it, but decided to keep developing it "example driven" for now. Aka I'm playing around with it, and whenever I find something that's broken I keep a note of it and then I pick those notes one by one and implement them. Once the most common things are implemented I will start writing property tests to catch all the edge cases of each feature.
replyI'm saying you can go even further and automate the entire thing using LLMs/agents, it is pretty much the ideal use case: you have a black-box reference implementation to test against; descriptive documentation for what the functions should do; some explicitly supplied examples in the documentation; and the ability to automatically create an arbitrary number of tests.
replySo not only do you have a closed loop system that has objective/automatic pass-fail criteria you also don't even have to supply the instructions about what the function is supposed to do or the test cases!
Obviously this isn't going to be 100% reliable (especially for edge cases) but you should be able to get an enormous speed up. And in many cases you should be able to supply the edge case tests and have the LLM fix it.
(Codex is still free for the next few days if you want to try their "High"/"Extra high" thinking models)
You accidentally raise an interesting point: good, thorough public documentation, once considered a great selling point for your system, now invites automated reimplementation by competition. It would be a shame to see public docs vanish because it turns out they are literally machine readable specs.
reply