Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
Evals Skills for Coding Agents
Hamel Husain publishes evals-skills—agent skills for AI product evaluation covering audit, error analysis, synthetic data, judge prompts, evaluator validation, and RAG evals, distilled from work with dozens of companies.
3 min · 585 words
Better prompt caching for GPT-6
OpenAI explains GPT-6 prompt-caching improvements: higher cache hit rates, new diagnostics, explicit breakpoints, and controls aimed at cutting latency and inference cost.
3 min · 623 words
Unreal Labs introduces Unreal Agent, an agent harness claiming up to 40% cost savings versus Codex on production workloads and coding/science benchmarks, with details on architecture and evaluation.
5 min · 1,071 words
Carson Gross argues that Markdown has become a first-class source artifact for LLM-built software systems, and that treating it like code in /src follows the same locality and clarity principles as HTML-in-/src.
6 min · 1,398 words
Software 2.0 writes Software 1.0
Jochem Gietema argues that as coding models improve, prediction tasks once handled by trained deep learning models can instead become ordinary code—'codification' where Software 2.0 writes Software 1.0.
3 min · 791 words
Tackling Robotics with (V)LM Agents
Nishanth J. Kumar surveys recent demos and ideas around GPT-6 and other vision-language models solving robotics tasks—summarizing approaches and offering thoughts on what works and what still breaks.
10 min · 2,304 words
Getting the most out of Opus 5.5 in Claude and Claude Code
Addy Osmani shares practical prompting, long-run steering, and verification tips for Anthropic’s Opus 5.5 model in Claude apps and Claude Code.
11 min · 2,449 words
OpenAI introduces GPT-6.1 Sol, positioning it as near-Astra intelligence at a fraction of the price, with notes on capabilities, availability, and how it fits the GPT-6.1 family.
4 min · 805 words
Claude Opus 5.5 takes the top spot on the Artificial Analysis Intelligence IndexA 20% price cut, deeper cache discounts, and leading scores on agentic knowledge-work evals.
Artificial Analysis’s first look at Claude Opus 5.5: Intelligence Index score of 58 at max effort, parity with GPT-6 Astra on Terminal-Bench 4.0, stronger agentic knowledge-work results, and Anthropic’s $4/$20 pricing with cheaper cache reads.
3 min · 609 words
I asked Meta’s Muse for its filesystem and it sent me 6.8 GB
A security researcher asks Meta’s privileged Muse AI assistant to export its runtime filesystem—and receives a 6.8 GB dump that reveals how Muse is wired, what it can reach, and why that matters.
7 min · 1,501 words
Let the model talk. Don't let it touch the money.
Destiny Ezenwata on the hard boundary in CreditWithBleon: the LLM may converse freely, but money-moving steps stay in deterministic code—and why that line has held in production.
8 min · 1,743 words
Self-hosting LLM models for software development
Kévin Maschtaler on running medium-sized open LLMs on AWS Spot EC2 for day-to-day software work—what stacks, costs, and performance looked like versus a personal Claude subscription.
7 min · 1,719 words
MiMo-V2.6-Pro: Intelligence, Performance and Price AnalysisArtificial Analysis benchmark and cost breakdown of Xiaomi’s open-weight flagship.
Artificial Analysis’s model page for Xiaomi MiMo-V2.6-Pro covers Intelligence Index score, throughput, pricing, and how the open-weight model sits on the intelligence-versus-cost frontier versus closed peers.
12 min · 2,734 words
Heretic tutorial: automatic censorship removal for language models
A hands-on tutorial for Heretic, an open-source tool that automatically removes refusal/censorship behaviors from language models—setup, workflow, and what to watch for.
7 min · 1,688 words
SpaceXAI announces Grok 4.7: what is new in the model release, where it improves, and how to access it—from the official x.ai news post.
3 min · 645 words
Transformer Explainer: LLM Transformer Model Visually Explained
Georgia Tech’s Polo Club walks through GPT-2’s Transformer stack—embeddings, multi-head attention, MLP, sampling—with an interactive in-browser model for learning how next-token prediction works.
4 min · 827 words
Open Source Maintainership in an LLM world
A couple of weeks ago I spoke about this topic at KC OSS Happy Hour and I wanted to turn the general ideas into a post I can point people at who are suffering from this problem. My slides were pretty good, if I do say so myself, so I grabbed the best images and put them into this post where appropriate.
4 min · 867 words
It Was the Harness, Not the Model — 90% of ItFive agents, one local model, one frozen PNG-decoder suite: most failures were finishing, false passes, and loop guards
Greg Herlein's controlled study runs five coding agents on the same local Qwen coder for a held-out PNG decoder suite. ~90% of failures were harness problems (turn caps, early 'done', false-pass self-tests); a bigger quantization fixed none of them.
2 min · 467 words
NobodyWho shows a local, 25-line Python sketch of Jev-style decision models: load a small GGUF, score labeled choices from logits, and print calibrated-looking probabilities without sending data to an API.
2 min · 419 words
Epoch AI finds the cost of a given level of AI performance has fallen about 47% per quarter since 2023—roughly 13× per year—faster than DNA sequencing, compute, batteries, or electricity, across math, science, and skill-game benchmarks.
40 min · 9,215 words