Small Models Have Arrived
For the past few weeks, I've been playing with gpt-5.6-luna . It is shockingly capable, fast, and smart. I regularly see it do ~100 tps, and rip around my codebase, email, and knowledge base.
The latest blog posts to take off on Hacker News. 3,090 posts.
For the past few weeks, I've been playing with gpt-5.6-luna . It is shockingly capable, fast, and smart. I regularly see it do ~100 tps, and rip around my codebase, email, and knowledge base.
Everyone is using Obsidian for AI, or wants to use it to become more productive. But I think it's a dead end.
The important question about AI-assisted programming isn't who writes the code. It's who understands the system.
Six approaches to retrieval-based AI, from minimal to elaborate
TL;DR: 62% as of September 2026. This is up from ~40% in February.
| Read on LessWrong | Comment on HN | Large language models often take actions running on one computer (via an agentic harness such as Claude Code or Codex), however the LLMs’ responses to prompts are computed on a different computer with GPU access.
Who is the AI villain we should be angry at?
The need for ongoing friction in long-term skill formation.
It was a summer holiday, sometime in the late 1990s. I was a young kid, around 8 or so. My dad had taught me the rules of chess before and we played from time to time. But this time was different: As we were about to start he stood up and walked away from the board, sitting down in a chair across the room and facing…
How Varkos was built: a low-latency AI companion that plays Skyrim with you, follows complex instructions and evolves through shared experiences.
I'm a designer and creative technologist based in Brooklyn, NY.
Fable’s price ended the free lunch of ever-cheaper frontier models. Now we have to think about which model gets which work.
The first time I tried to use an LLM to speed up coding was in mid-2025. I was not impressed. I was working on libadbmdns back then, an mDNS implementation in Rust. The code produced would not even compile.
Nobody in the comments is real
A look at AI Chip Architectures. NVIDIA, AMD, TPUs, Trainium, Groq, Cerebras.
Claude goes above and beyond what is asked and guesses what you might want. Codex does what you tell it and stops at the first sign that it might be done. Ten impressions from a week of using Codex more.
I built an (almost) fully self-hosted, sandboxed, agentic software factory.
Recently I've been catching myself having these little moments at work, when I'm trying to read a document someone has sent me and my brain somehow refuses to analyze it. It feels like I'm reading it, but I'm unable to focus on its content. I sat down to analyze these situations and realized they all have a common…
Trying to obfuscate the web is a bad, pointless idea
The Pine Time is a $27 smart watch that runs open source firmware. I’ve had one sitting in the back of a drawer for a...
Solid core + capability-based sandboxes + LLMs = Users with superpowers
The Long Arc of History Bends Towards Social Democracy
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I'm about as pro-AI as you can be, but this is becoming a pet peeve of mine (and I'm not alone). That's why I love the AI;DR acronym as my new solution for ignoring the walls of slop.
Friday’s big release was Qwen 3.8 27B, an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba’s Qwen research lab. I’ve been looking forward to this one: 27B is an …
It’s unacceptable for a tool to sacrifice an iota of clarity, coherence, meaning, quality, etc. for the purpose of embedding hidden clues within the text to suggest its provenance. The idea that anything other than *my* needs should factor into the generation of text *for me* is patently offensive.
Reasoning scores climb while per-token compute drops. Labs are stripping world knowledge out of models, and I think that's the right trade.
The key advantage may not be superior reasoning, but a virtually unlimited symbolic working memory.