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Using LLMs at Oxide

(rfd.shared.oxide.computer)
694 points steveklabnik | 2 comments | | HN request time: 0s | source
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thundergolfer ◴[] No.46178458[source]
A measured, comprehensive, and sensible take. Not surprising from Bryan. This was a nice line:

> it’s just embarrassing — it’s as if the writer is walking around with their intellectual fly open.

I think Oxide didn't include this in the RFD because they exclusively hire senior engineers, but in an organization that contains junior engineers I'd add something specific to help junior engineers understand how they should approach LLM use.

Bryan has 30+ years of challenging software (and now hardware) engineering experience. He memorably said that he's worked on and completed a "hard program" (an OS), which he defines as a program you doubt you can actually get working.

The way Bryan approaches an LLM is super different to how a 2025 junior engineer does so. That junior engineer possibly hasn't programmed without the tantalizing, even desperately tempting option to be assisted by an LLM.

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1. dicytea ◴[] No.46180957[source]
It's funny that I've seen people both argue that LLMs are exclusively useful only to beginners who know next to nothing and also that they are only useful if you are a 50+ YoE veteran at the top of their craft who started programming with punch cards since they were 5-years-old.

I wonder which of these camps are right.

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2. Mtinie ◴[] No.46181204[source]
Both camps, for different reasons.

For novices, LLMs are infinitely patient rubber ducks. They unstick the stuck; helping people past the coding and system management hurdles that once required deep dives through Stack Overflow and esoteric blog posts. When an explanation doesn’t land, they’ll reframe until one does. And because they’re confidently wrong often enough, learning to spot their errors becomes part of the curriculum.

For experienced engineers, they’re tireless boilerplate generators, dynamic linters, and a fresh set of eyes at 2am when no one else is around to ask. They handle the mechanical work so you can focus on the interesting problems.

The caveat for both: intentionality matters. They reward users who know what they’re looking for and punish those who outsource judgment entirely.