Using LLMs at Oxide

Post by knollimar » Mon, Dec 08, 2025, 2:45 PM UTC

IgorPartola wrote: post #103

mcqueenjordan wrote: post #28

As usual with Oxide's RFDs, I found myself vigorously head-nodding while reading. Somewhat rarely, I found a part that I found myself disagreeing with: > Unlike prose, however (which really should be handed in a polished form to an LLM to maximize the LLM’s efficacy), LLMs can be quite effective writing code de novo. Don't the same arguments against using LLMs to write one's prose also apply to code? Was this structu…

My suspicion is that this is a form of the paradox where you can recognize that the news being reported is wrong when it is on a subject in which you are an expert but then you move onto the next article on a different subject and your trust resumes. Basically if you are a software engineer you can very easily judge quality of code. But if you aren’t a writer then maybe it is hard for you to judge the quality of a pi…

Post by mwcampbell » Mon, Dec 08, 2025, 6:59 PM UTC

dcre wrote: post #279

batney wrote: post #198

Earlier quoted context omitted.

Here it is, rewritten in accessible English: Using Large Language Models (LLMs) at Oxide This document explains how we should think about using LLMs (like ChatGPT or similar tools) at Oxide. What are LLMs? LLMs are very advanced computer programs that can understand and generate text. They've become a big deal in the last five years and can change how we work. But, like any powerful tool, they have good and bad sides…

Thanks, this will be perfect for the team of 6 year olds that work for me.