The LLM Critics Are Right. I Use LLMs Anyway.
I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.
The LLM Critics Are Right. I Use LLMs Anyway.
I almost agree with all of the LLM critics, yet I still use LLMs a lot. I know this sounds like I am delusional, but I don't think I am alone with it.
Announcing Burn-LM (alpha): LLM Inference Engine
We're happy to announce the Burn-LM, an LLM inference engine based on Burn! The goal is to support any large model, LLM, VLM, and others, for inference but also for training (pre-training, post-training, and fine-tuning).
Your LLM Doesn't Write Correct Code. It Writes Plausible Code.
One of the simplest tests you can run on a database:
Various LLM smells
Looks like this ended up on the HN front-page: HN Thread Late last year I started writing a math blog and decided to use LLMs to polish/enhance my writin...
LLM APIs are a Synchronization Problem
Maybe the LLM message APIs should be rethought as a synchronization problem.
I accidentally turned LLM memory into program analysis :: pwning.systems
Why I stopped trying to give LLM agents a better memory and instead built Lemmalog, a Datalog engine that maintains an agent's knowledge as analysis state, with provenance, retractions and incremental evaluation, plus what happened when I benchmarked it on LongMemEval and LoCoMo.
Andrew Ho on Twitter / X
Not really observations that others before me haven’t made, but:- Despite the seemingly magical nature of LLMs, reflection over a >3 month timescale suggests my total productivity hasn’t increased by over 100%, or perhaps even by over 50%, and a lot of time is actually wasted…— Andrew Ho (@andrewho03) September 3, 2026
There's Something Fundamentally Wrong With LLMs
LLMs aren't trained on the "vast majority of speech," experts warn, a major blind spot that could have sweeping consequences.
The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities (Version 1.0)
The most important thing when working with LLMs
Blog post: The most important thing when working with LLMs by Steve Klabnik
I didn't expect to get so tired of reading LLM output.
