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159 points jbredeche | 2 comments | | HN request time: 0.526s | source
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cuttothechase ◴[] No.45532033[source]
The fact that we now have to write cook book about cook books kind of masks the reality that there is something that could be genuinely wrong about this entire paradigm.

Why are even experts unsure about whats the right way to do something or even if its possible to do something at all, for anything non-trivial? Why so much hesitancy, if this is the panacea? If we are so sure then why not use the AI itself to come up with a proven paradigm?

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torginus ◴[] No.45533296[source]
LLMs are literal gambling - you get them to work right once and they are magical - then you end up chasing that high by tweaking the model and instructions the rest of the time.
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vidarh ◴[] No.45533984[source]
Or you put them to work with strong test suites and get stuff done. I am in bed. I have Claude fixing complex compiler bugs right now. It has "earned" that privilege by proving it can make good enough fixes, systematically removing actual, real bugs in reasonable ways by being given an immutable test suite and detailed instructions of the approach to follow.

There's no gambling involved. The results need to be checked, but the test suite is good enough it is hard for it to get away with something too stupid, and it's already demonstrated it knows x86 assembly much better than me.

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1. typpilol ◴[] No.45536228[source]
The best way to get decent core I've found is test suites and a ton of linting rules.
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2. vidarh ◴[] No.45538153[source]
Absolutely true re: ton of linting rules. In Ruby for example, Claude has a tendency to do horrific stuff like using instance_variable_get("@somevar") to avoid lack of accessors, instead of figuring out why there isn't an accessor, or adding one... A lot can even be achieved with pretty ad hoc hooks that don't do full linting but greps for things that are suspicious, and inject "questions" about whether X is really the appropriate way to do it, given rule Y in [some ruleset].