Comment by jamienk | Hacker News Reader

Comment by jamienk | Hacker News Reader

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This article is NOT like the Dodo or Newton ones. The Dodo author was an expert in Dodos. The Newton one was by a Newton expert. In those cases, it was the relentlessness of the AI that found edge cases that were interesting.

But Here, the start is "What field should I approach and what questions should I ask?"

But this is NOT the same!

When I watch my non-tech friends vibe-coding, I'm struck by how they are so ignorant of basic tech stuff, but little tiny bubbles of "experience" start to percolate in them after a while. Things like "wait, I think this project has weird dependencies that are going to cause trouble when I move it to my office machine" or "hold on, the mobile version doesn't share the same text with the desktop version?"

It is much less interesting to have an attitude of "I don't know or care, just give me a 'result'" vs "Aha! I see where we could apply this in a productive way!"

This is like the Anthropic people feeling like they found many many "very important" Linux bugs https://www.youtube.com/watch?v=NnV_cWeoo5Q - hint: no.

When it's something you know about, the overstating is obvious! It's only when you don't know about things that shallow work (or slop) feels significant.

Many faults with this argument.

1. You don't need to be an expert in domain A to comment on that domain, this is credentialism that AI itself is dissolving

2. the fact that your non-technical friends can vibe code this much itself is a proof of (1)

3. the proof that Anthropic didn't find important linux bugs is strange when they did find small vulnvs that could be chained to create real exploits - that's how most attacks were made in the past

4. OpenAI recently dropped 400 proofs solving some of the most important problems in mathematics without any expert in those fields which is a great counter example to you

You are staying on the surface with your examples. Dig into any and see the interesting complexities emerge. It's fine to have a surface-level acquaintance with many things (no one can be expert in all). But then you don't have "the right" to make pronouncements. It's like reading a newspaper article about something you've never heard about before (e.g., Turkish political parties) and thinking you now know that field.

AI operated by people who know nothing about Turkeye asking broadly "how do I solve the current Turkish political problems" will not get far fast. They might be impressed fast. This is not an argument against AI helping think through things in various ways.

I don't think it's a question of credentialism. It's about being easily impressed.

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