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vips7Ltoday at 5:18 AM2 repliesview on HN

If you don’t know what library to use in your specific language, do you think you know enough to have an LLM generate most of it?


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neerajsitoday at 5:37 AM

I just joined a new team and have been using copilot with opus models.

We have our core code in a weird dialect of C and rust. C I know well, but not rust. Our tests are in Python. The pipeline descriptions are in Yaml.

Outside of the core code there are so many arcana to learn. Writing syntactically and semantically correct yaml/Python test code would be a nightmare. The Agents have flaws, but they provide a huge leg up in improving the tests.

And they are great at providing a first pass review of the core code before bothering a human reviewer. Lastly we run some of our test failures through AI triage, which often enough finds the root cause or rules out simple failures.

This shows up in a higher checkin rate. I'm curious to see whether this will lead to quality end product since we have more support for the more manually written and reviewed core product code.

simianwordstoday at 5:22 AM

YES. This line of thought is exactly why people are still skeptical of LLM's.

LLM's are directionally right and if their answer "fits" then I take it at face value.

I wrote a blog detailing the computational difference between "generation" and "verification" and why it matters for LLM's: https://simianwords.bearblog.dev/the-generation-vs-verificat...

As an example: I asked the LLM "synonym for "provides" that also means "places" on you" and it gave me 5 answers and I immediately knew the right one was "confers". How? It just fits. Just like most things.

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