available intuition for avoiding big risks
Magicoder: Empowering Code Generation with OSS-Instruct
We introduce Magicoder, a series of fully open-source (code, weights, and data) Large Language Models (LLMs) for code that significantly closes the gap with top code models while having no more...
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...
Why your local LLM feels dumber than it is
Quick Introduction We have all been on forums, chats, reddit, discord, youtube, or somewhere and heard “Oh! Model XYZ is AMAZEBALLZ!zomgwtfbbq” then downloaded it (or more likely, some quantized form of it) and said “eww… This sucks!” This post is going to be a rather technical series of experiments to demonstrate the impact of implementation-specific hazards with inference. I will be using the term “reference implementation” to describe the lab that published and offers first-party hosting of ...
Compiling knowledge, not retrieving it: a hands-on deep dive into llm-wiki-compiler
The thesis of this piece is simple and uncomfortable: the problem of making an LLM “remember” what you’ve read isn’t solved with more…
My AI Skeptic Friends Are All Nuts
My smartest friends have bananas arguments about LLM coding.
My AI Skeptic Friends Are All Nuts
My smartest friends have bananas arguments about LLM coding.
Best LLM for Coding 2026 | AI Coding Model Rankings & Benchmarks
Which AI model writes the best code? We rank every major LLM — open and closed source — across SWE-bench, HumanEval, LiveCodeBench, and Terminal-Bench coding benchmarks. Compare the best LLMs for coding, software engineering, and programming.
Coding with LLMs in the summer of 2025 (an update) - <antirez>
What the AI Wizard taught us about LLM code generation at scale - PostHog
You know what’s boring? Writing integrations. It’s a task you’ll do once, but you always need to do it right, which means carefully reading docs…
Wolfram LLM Benchmarking Project
Results from Wolfram's ongoing tracking of LLM performance. The benchmark is based on a Wolfram Language code generation task.
Vibe Password Generation: Predictable by Design - Irregular
LLM-generated passwords appear strong, but are fundamentally insecure. Testing across GPT, Claude, and Gemini revealed highly predictable patterns: repeated passwords across runs, skewed character distributions, and dramatically lower entropy than expected. Coding agents compound the problem by sometimes preferring and using LLM-generated passwords without the user’s knowledge. We recommend avoiding LLM-generated passwords and directing both models and coding agents to use secure password generation methods instead.
Writing Code Is Easy. Reading It Isn’t.
Writing code is easy. Once you have a solution in mind, and have mastered the syntax of your favorite programming language, writing code is easy. Having an LLM write entire functions for you? Even eas
A Complete Guide to LLVM for Programming Language Creators
We'll explain the concepts underlying LLVM IR, and how you can use the LLVM C++ API in your programming language's compiler.
I haven't, but I don't know that it's that kind of model. It's really different than an LLM, since if you want an answer from it you can only ask it multiple choice, true or false ( with confidence ), or "tell me the score of X" questions. So there's no generating proof code or anything directly.
I just came across this paper arxiv.org/abs/2509.22908 which coins the term "vericoding" for using LLMs to generate formally verified code, and presents benchmark results for several languages
A benchmark for vericoding: formally verified program synthesis
arxiv.org
Martin Kleppmann
New blog post! ✨ I argue that AI will make formal verification go mainstream. martin.kleppmann.com/2025/12/08/ai-formal-verifica… Three reasons for this: 1. LLMs are getting increasingly good at writing proofs using proof assistants. This will make formal verification vastly cheaper than it's been to date.
