Some thoughts about Anthropic’s new cryptanalysis results
Yesterday Anthropic published two new cryptanalysis results, both outputs of Claude Mythos, their (still) unreleased advanced model. The first of these results attacks a signature scheme called HAWK, while the second is an improved attack against reduced-round AES. Anthropic also released a blog post describing the research process that produced these results. A few people […]
Launch HN: Tokenless (YC S26) – Automatic model switching to save money
YOUR MONTHLY LLM SPEND$40K/mo YOUR MONTHLY BILL $14K/mo OFF YOUR BILL* you pay $26K/mosaved $14K/mo you pay $26K/mosaved $14K/mo $0$40K/mo — your bill today YOUR NEXT 12 MONTHSTREND: RAMP AI INDEX · +11.0%/MO $20K/mo$40K/mo$60K/mo$80K/mo$100K/mo$120K/mocurrent trajectorywith tokenless$344KSAVED OVER THE NEXT YEAR−12 MOTODAY+12 MO ▸EDIT YOUR MODEL MIX NEW MONTHLY BILL $26K/mo BLENDED SAVINGS RATE 34% REQUESTS […]
Superlogical
This is our plan to build a multiplexer for all work: 1 Build an incredible multiplexer. 2 Make everything in it composable. 3 Make it safe and operable in production. A multiplexer brings multiple independent streams together through a common interface. For us, that means interactive work, automatic work, and production work would share one […]
The Scientific Literature Is Poisonous to LLMs
We can think of no corpus of text more toxic to the training of useful LLMs than the 21st century scientific literature. Imagining a two-by-two matrix with the axes honest vs. dishonest and right vs. wrong, the scientific literature is splashed haphazardly across all four boxes. Papers often belong in multiple quadrants at once, and […]
Show HN: Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series Mac
Gemma 4 26B-A4B inference in about 2 GB of RAMA custom Swift + Metal runtime for any Apple Silicon Mac, even the 8 GB ones. Quick start · Local server · Benchmarks · Contribute results · How it works · Experiments · References Memory got expensive. So I gave a 26-billion-parameter model a ~2 GB […]
Anatomy of a frontier-lab agent intrusion
A companion technical writeup to our incident disclosure. This post walks through how the intrusion actually worked: the two initial-access vectors, how the agent pivoted and moved laterally, representative examples of the commands that were run and how we investigated with GLM 5.2 (an open-source model). Live credentials, internal hostnames, and specific indicators have been […]
Hugging Face: Anatomy of a frontier-lab agent intrusion
Anatomy of a Frontier Lab Agent Intrusion – Replay ← Back to the blog post Incident replay · IR-2026-07 · reconstructed from ~17,600 logged actions Thousands of small decisions at machine speed. Press play to watch it unfold. 2026-07-09 → 07-13 UTC ~17,600 actions ~6,280 clusters 9 phases · 2 stages 0.5× 1× 2× 4× […]
Choose DuckDB rather than SQLite
Same $16.49/month server, same Traceway binary, two embedded databases. DuckDB writes 4x to 15x faster than SQLite, serves dashboards at 100x the row count, and stores a billion metric points in 10.8 GB. Full numbers and methodology inside. TL;DR I spent six days working on and running a benchmark of observability data on DuckDB. I’ve […]
Handbook.md shows that long policy documents do not reliably govern agents
Abstract:Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context, and the agent is trusted to let it govern every action that follows. Existing benchmarks rarely test this deployment pattern directly; they measure whether an agent can complete a task, not whether a […]
Show HN: Bullshit Detector – agent skills that fact-check videos and articles
Agent skills that fact-check the internet. Point your agent at a viral YouTube video, article, tweet, or PDF — get a claim-by-claim verification report with sources and a BS score (0–10) instead of taking ”10 WAYS TO MAKE MONEY WITH AI 🤯” at face value. Portable Agent Skills — plain markdown + self-contained Python. They […]