Bookmarks

Signal Sources — September 2026

Research & Labs

AI2 Blog
The Allen Institute's own teams write these up, which is why a post about a tutoring model called TutorMoments spends most of its length on when the thing should refuse to help rather than how well it scored. **Cadence:** weekly to biweekly. **Feed:** none
Microsoft Research Blog
Named researchers, not a comms team, describe what they built — pathology foundation models, spatial reasoning in vision-language systems, the occasional detour into physics-flavored ML. Several posts a week, so it's worth skimming rather than reading cover to cover. **Cadence:** several posts a week. **Feed:** https://www.microsoft.com/en-us/research/feed/

Engineering Blogs

Cloudflare Blog
Cloudflare posts almost daily, and the good ones go deep on the plumbing: a recent piece walks through saving petabytes of cache storage by switching compression algorithms, numbers included. Skip the product-launch posts and keep the rest. **Cadence:** near-daily. **Feed:** https://blog.cloudflare.com/rss/
Netflix Tech Blog
Real production detail from a company running recommendation and streaming infrastructure at a scale almost nobody else operates at — a recent write-up on multimodal asset personalization reads like an internal design doc that happened to get published. **Cadence:** weekly to biweekly. **Feed:** https://netflixtechblog.com/feed
Shopify Engineering
The team shipping Shopify's AI shopping assistant writes candidly about what didn't work first — a recent post on compressing agent context to cut cost reads more like a postmortem than a feature announcement. **Cadence:** roughly weekly. **Feed:** https://shopify.engineering/blog.atom
Meta Engineering Blog
This is the infrastructure feed, not Meta's PR-heavy AI blog — network engineers describing things like a custom RDMA transport built to move data between GPUs at training scale. Dense, but it's the closest thing to primary sourcing on how the frontier labs actually wire up their clusters. **Cadence:** roughly weekly. **Feed:** https://engineering.fb.com/feed/

Newsletters

Import AI
Jack Clark has been writing this every week since 2016, longer than most AI newsletters have existed at all, and it still reads like one person's honest reaction to what crossed their desk that week rather than a roundup assembled by committee. **Cadence:** weekly. **Feed:** https://importai.substack.com/feed
The Pragmatic Engineer
Gergely Orosz gets people inside companies to talk on the record about decisions nobody else reports on — Meta's team-size math, a fintech building its own coding agent instead of buying one. Sourced reporting on engineering orgs is rarer than it should be. **Cadence:** about twice a week. **Feed:** https://newsletter.pragmaticengineer.com/feed
Ahead of AI
Sebastian Raschka picks apart one technique per issue — controlling reasoning effort, running coding agents locally — at the level of "here's the mechanism," which makes it slower to read than most AI newsletters and worth it for exactly that reason. **Cadence:** roughly monthly. **Feed:** https://magazine.sebastianraschka.com/feed
Latent Space: AI News
swyx and Alessio compress the day's AI Twitter, Discord servers, and research drops into one digest every weekday morning, which beats doing that scan yourself unless you enjoy it. **Cadence:** daily on weekdays. **Feed:** https://www.latent.space/feed

Changelogs & Release Feeds

llama.cpp Releases
The changelog for the runtime most people actually use to run models on a laptop or phone. Builds land multiple times a day, and quantization or backend changes show up here well before anyone writes a blog post explaining them. **Cadence:** multiple releases daily. **Feed:** https://github.com/ggml-org/llama.cpp/releases.atom
Kubernetes Blog
The people who own each feature write its release note, which is why a post about storage version migration going on by default in 1.37 explains the reasoning, not just the flag name. **Cadence:** several posts a week around releases. **Feed:** https://kubernetes.io/feed.xml
PyTorch Blog
Framework-team announcements on what's landing next in the ecosystem — new releases, conference session recaps, the occasional deep dive into a specific optimization. If you deploy models, this is more useful than the release notes alone. **Cadence:** several posts a week. **Feed:** https://pytorch.org/blog/feed.xml

Practitioners & Independents

Simon Willison's Weblog
Simon posts same-day notes with working code the moment a new model or tool ships, which makes his blog faster than most vendor documentation at answering "does this actually work the way they claim." **Cadence:** near-daily. **Feed:** https://simonwillison.net/atom/everything/
Julia Evans
Julia writes the "how does X actually work" post that should exist for every piece of infrastructure but usually doesn't — a recent one on Django internals is typical: patient, curious, no AI hype anywhere near it. **Cadence:** irregular, roughly monthly. **Feed:** https://jvns.ca/atom.xml

Video & Podcasts

Dwarkesh Podcast
Dwarkesh Patel gets frontier researchers and founders talking for two hours at a stretch, long enough that they stop giving the rehearsed answer. A recent episode on "agent civilizations" gets more technical than most written coverage of the same idea. **Cadence:** roughly weekly. **Feed:** https://www.dwarkesh.com/feed
Practical AI
Less about frontier lab drama, more about what it takes to actually build and ship an agent — Changelog Media's show stays grounded in things a working engineer can use Monday morning. **Cadence:** weekly. **Feed:** https://feeds.transistor.fm/practical-ai-machine-learning-data-science-llm

Benchmarks & Leaderboards

Artificial Analysis
Independent comparisons of model intelligence, speed, and price across every major provider, updated continuously and transparent about how the numbers are produced — closer to a buyer's guide than a marketing chart. **Cadence:** continuous. **Feed:** none
Arena
The team behind the crowdsourced head-to-head model rankings (formerly LMArena) explains its methodology changes as it makes them — new evaluation modes, coding-specific leaderboards — instead of just publishing a score and moving on. **Cadence:** roughly biweekly. **Feed:** none --- *19 sources added this month · 39 on the list. The full archive imports as [bookmarks](../../signal-sources-all-bookmarks.html) or as an [OPML feed bundle](../../signal-sources.opml). Found a dead feed? Reply to the email.*