There has been rather a lot of doomsaying (and perhaps astroturfing) lately about LLMs as the end of computer programming. Much of the discussion has been lacking nuance, so I’d like to add mine. I see claims from one side that “I used $LLM_SERVICE_PROVIDER to make a small throwaway tool, so all programmers will be unemployed in $ARBITRARY_TIME_WINDOW”, and from the other side flat-out rejections of the idea that this type of tool can have any utility.1 I think it best sheds light on these claims to examine them in the context of another field that’s been ahead of the curve on this: translation.
Translating non-trivial codebases with Claude
I don’t think it’s [me writing about LLMs] likely to happen anytime soon: I prefer to write about things that I’m excited about.
Copyrightability of LLM-generated code: Can we license “vibe code” into Free Software? - FSFE
The use of large language models (“LLMs”) has exploded in recent years, including in the generation of source code. But even as their usage gains popularit...
Notes on how to use LLMs in your product.
Pretty much every company I know is looking for a way to benefit from Large Language Models. Even if their executives don’t see much applicability, their investors likely do, so they’re staring at the blank page nervously trying to come up with an idea. It’s straightforward to make an argument for LLMs improving internal efficiency somehow, but it’s much harder to describe a believable way that LLMs will make your product more useful to your customers.
Things we learned about LLMs in 2024
A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past …
Dan Shipper 📧 on Twitter / X
this is true and is a big reason why you don’t need to be a highly technical researcher to use LLMs in surprising and novel ways https://t.co/TuxNzXzToU— Dan Shipper 📧 (@danshipper) July 27, 2025
Alex Veremeyenko on Twitter / X
what are large language models actually doing?i read the 2025 textbook "Foundations of Large Language Models" by tong xiao and jingbo zhu and for the first time, i truly understood how they work.here’s everything you need to know about llms in 3 minutes↓ pic.twitter.com/OeYLuU3cWh— Alex Veremeyenko (@alex_verem) July 26, 2025
chad/whichlang
What programming language do LLMs default to when you don't tell them? A small benchmark.
If you don't run your own LLM proxy, how the fuck do you even know whats going on?
I think the title captures the idea fully but I'll dig into it because this ain't Twitter. You're working an idea, a piece of code, or a multibillion a year SaaS app which is probably saving the world. Maybe you're automating the cloning process of grabbing
Illusions of Understanding from Outsourcing Thinking to LLMs
Some illusions of understanding are an inevitable part of the research process, while others can be avoided or overcome by careful critical thinking and observation. We are facing an increased risk of avoidable illusions as more research activities are delegated to large language models (LMM). LLMs can be useful but they cannot think, and their use can undermine our thinking and understanding. Thinking for ourselves is hard and error prone but worthwhile - and there are no shortcuts to understanding.
Isn't the fundamental problem that LLM's don't actually understand anything (as ... | Hacker News
My 2 month active experience with ChatGPT-4 gave me the following takeaways:
Brandon Stewart on Twitter / X
1/ New @Nature! We study how powerful institutions shape the information environment for LLMs. Commercial LLM training is opaque, so we trace a path from state-coordinated media -> training data -> model responses. pic.twitter.com/5LdFvzbFaf— Brandon Stewart (@b_m_stewart) May 13, 2026
Lincoln Michel on Twitter / X
This was my read on AI from the beginning and it proved very true. Whatever hypothetical benefits LLMs have (and they have some), their main use is to waste everyone's time wading through slop. Longer colleague powerpoints. More spam emails. More slop clogging up all the systems. https://t.co/2gtGfqf7KF— Lincoln Michel (@TheLincoln) September 21, 2026
LLMs are bullshitters. But that doesn't mean they're not useful.
Note: This is a personal essay by Matt Ranger, Kagi's head of ML In 1986, Harry Frankfurt wrote On Bullshit. He differentiates a lying from bullshitting: Lying means you have a concept of what is true,...
The two worlds of programming: why developers who make the same observations about LLMs come to opposite conclusions
Writing at the end of the world, from Hveragerði, Iceland
I feel like using LLMs to flag intent/semantics mismatches (eg do var names seem to match what you actually do) or indirect violations of API contracts or whatever as a supplement to static analysis to produce *better* code would be at least as high impact, and it's like 1% of the discourse
Vibe Coding
AI assisted programming resources
TeamoRouter
dmmulroy/anti-slop
Introducing Radial: Agent orchestration on the Atmosphere
ARCHITECTURE.md
Codifying a ChatGPT workflow into a malleable GUI
WeSight - Run CLI Agents from One Desktop App
