- cross-posted to:
- [email protected]
- cross-posted to:
- [email protected]
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As I’m slowly evolving my own flavour of spec driven development, I’m starting to think about the generated code as a secondary artefact where main quality criteria is that it’s doing what it needs to and it’s covered with tests.
I guess my current analogy is that I don’t care about how readable or dry is the assembly code generated by compiler.
I have the specifications and the working code with tests. I can always regenerate it if I need to.
But. I still read the produced code, steer the design and correct the obvious blunders. No vibes.
The LLMs are just somewhere between an averaging and a lossy compression of everything on GitHub. There’s nothing about the current paradigm of “AI” that is going to somehow do better than just rehashing that training set but with the inclusion of various classes of errors.
I think it’s better to view it as spicy search rather than any form of intelligence.
Yeah that’s mostly what i use it for. A way to search for things that i can’t describe well enough for a traditional search engine so I can find out at a glance what it’s name is and if it’s valid for my situation. If it is then I go look up documentation. Any time I’ve stayed in the LLM past that I eventually go down a rabbit hole of wrong ideas that aren’t always obvious until you get a bit too deep and you’ve wasted an hour with an incorrect solution.
The only thing I have found it useful for is book recommendations. I like this book and that book, what other types of books are like these?
Yeah, I do believe it’s a good tool for search, just with the caveat that if it can’t find an answer it makes one up or otherwise kinda just fills in little missing details with noise.
If you treat it as spicy search it works pretty great though.
