engineercodex
Joined 3 years ago
Joined 3 years ago
Rather, I prefer to view LLMs as a junior dev that submits PRs that pass presubmits and other verifiable, programmatic checks. A human dev then reviews the PR manually. In this case, the LLM + its processing is used to make sure that no BS is sent out of review - only potential improvements.
Some of my comments within the article are more aspirational than realistic in this case, and I've made edits to reflect that.
I want to clarify that I view this LLM as a junior dev that submits PRs that pass presubmits and other verifiable, programmatic checks. A human dev then reviews the PR manually. In this case, the LLM + its processing is used to make sure that no BS is sent out of review - only potential improvements.
In no scenario should it's auto-generated code be auto-submitted into the codebase. That becomes a nightmare really fast.
PS. Big fan of this person’s recent blog posts. He’s been on a roll!
Happy to listen to any constructive feedback if you have any, though!
This article is less of a summary of a paper and rather commentary on what the results of the paper entails. After all, Hacker News is meant for discussion :)
I will say though that I do believe that I still stand by the "exponentially more valuable" portion. I think the fact that LLMs can fluke their way into "hitting a jackpot" in terms of test coverage is exactly why they're so valuable. When you have something constantly trying out different combinations, if it hits even one jackpot, like in the paper, it's extremely valuable to the team. It's a case that could have been either non-obvious or simply too tedious to write a test for manually. I think there's tremendous value in that, especially speaking as someone who has spend way too much time simply figuring out how to test something within a Big Tech codebase (F/G) when I already knew what to test.
I didn’t “slap” any date on top of the article. 2 Oct 2023 is the date I published my article. (This is how blogs on the Internet work.)
The first line of the article says that this all happened in 2012. I’m not sure I could get any clearer there.
The “GPT distillation” phrase is pretty rude. Anyone reading the article can see the difference between it and the presentation. Every “hand-drawn” image in the article is created by me in Excalidraw, and any images from the presentation are sourced with a very clear link to the presentation.
If you have any constructive feedback, I am happy to listen and take it into account.
Otherwise, I’m not really a fan of the rudeness. Thanks.
This was an article meant to resurface learnings from something that happened a decade ago, with added images and a clear distillation so that somebody doesn’t have to watch the 45 minute presentation to understand what happened.
I’m sorry you didn’t like it.
But I hope you can see the value I’m trying to provide here, as someone myself who doesn’t really have the time to sit through hour-long presentations to learn something.
Watch some YouTube videos or read some CS articles.
If you have a project idea, break down the next steps into tiny actionable tasks and draw out how you would implement certain features.