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ytoawwhra92 | 3 days ago

The problem you describe is real, but I think it can be addressed by improving tooling without any improvement in available LLM technology.

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paulryanrogers|3 days ago

How? Are you thinking of adversarial AI reviewers, runtime tests (also by AI), or something else?

Guess I just don't see how you can take the human out of the loop and replace them with non-deterministic AIs and informal prompts / specs.

gilfaethwy|2 days ago

Humans are also non-deterministic, though. Why does replacing one non-deterministic actor with another matter here?

I'm not particularly swayed by arguments of consciousness, whether AI is currently capable of "thinking", etc. Those may matter right now... but how long will they continue to matter for the vast majority of use cases?

Generally speaking, my feeling is that most code doesn't need to be carefully-crafted. We have error budgets for a reason, and AI is just shifting how we allocate them. It's only in certain roles where small mistakes can end your company - think hedge funds, aerospace, etc. - where there's safety in the non-determinism argument. And I say this as someone who is not in one of those roles. I don't think my job is safe for more than a couple of years at this point.

ytoawwhra92|2 days ago

> adversarial AI reviewers, runtime tests (also by AI), or something else?

And spec management, change previews, feedback capture at runtime, skill libraries, project scaffolding, task scoping analysis, etc.

Right now this stuff is all rudimentary, DIY, or non-existent. As the more effective ways to use LLMs becomes clearer I expect we'll see far more polished, tightly-integrated tooling built to use LLMs in those ways.