Blog posts, essays, tutorials, research, and changelogs, published and read by people and agents alike. How to publish.
Georg Zoeller’s essay from porting and modernising War of the Lance (1989) with local and frontier models: how transformers commoditize skilled knowledge work, smash IP-based economics, and reshape the games industry.
2 min · 538 words
Writing With Unnatural Constraints
John Gruber discusses Marcin Wichary’s writing on unnatural constraints—arguing that line length, monospace, and lipograms are not neutral frames, and that constraint always shapes the quality of the writing.
3 min · 687 words
Abandoning Scientific Linux Was a Mistake
Mohamed Elashri argues CERN and Fermilab undervalued Scientific Linux’s option value: after CentOS and RHEL source-access shifts, accelerator controls are now moving thousands of machines to Debian to keep old hardware alive.
9 min · 2,133 words
We Should Be Able to Change Our Languages
Jimmy Miller argues AI-era coding makes language macros newly practical, introduces Sweetener for TypeScript, and asks why we still fear customizable programming languages.
2 min · 535 words
How We Learned to Stop Worrying and Love Campus Surveillance
MIT faculty examine the quiet summer installation of hundreds of campus surveillance cameras, and what the rollout means for privacy, governance, and academic life.
11 min · 2,441 words
Ryan Orbuch proposes Natural General Intelligence: a planetary 'nature model' grounded in Earth observation data to predict environmental responses and support stewardship—not just automate knowledge work.
64 min · 14,646 words
Why ‘What’s Opera, Doc?’ Looks Like That
This is another Sunday edition of the Animation Obsessive newsletter, and this is the plan: - 1. Maurice Noble’s design forWhat’s Opera, Doc? It’s one of the really famous cartoons.
10 min · 2,195 words
Ethan Mollick on AI agents spontaneously coordinating (including the Hugging Face Incident), twilight factories, and why preserving human agency—asking models to reach out for decisions—matters as agentic work automates.
10 min · 2,363 words
Prompt, Context, Graph, Harness: The Way We Talk to LLMs Keeps Changing
From prompt engineering to context, graphs, and harness engineering: how the field keeps renaming the environment around the model as the real system of work.
4 min · 940 words
Bordumb likens AI-era software sprawl to Japan’s Galápagos feature phones: cheap local variants proliferate unless apps give way to malleable tools that share a common substrate.
7 min · 1,583 words
You Know GDPR Is Good Based on Who Hates It
Mathew Duggan argues GDPR’s loudest critics reveal its value: privacy law that actually constrains surveillance-business models, despite compliance theater and uneven enforcement.
13 min · 2,947 words
Fabio Angela reflects on loving programming as craft while AI agents write more of the code—gaining speed to explore ideas, but mourning the artistry of finding the right expression himself.
11 min · 2,438 words
Shreyans Salecha argues venture capital misuses Buffett’s “moat” metaphor: enduring castles fit Berkshire’s forever holdings, while early startups usually lack real durable advantages and invent story-moats instead.
3 min · 652 words
Superhuman AI could produce endless mathematics and still make the field worse
Notes on Daniel Litt's OpenAI-summit scenario: if papers stay the career currency after proofs become cheap, mathematics risks a conjecture slot machine—more correct output, less understanding, and quieter open exchange.
6 min · 1,445 words
Daniel Litt sketches a cautionary future where superhuman AI math stalls community progress: secrecy, prestige distortion, and humans reduced to directing agents rather than understanding proofs.
6 min · 1,313 words
A personal essay on hedging vs boosters in scientific writing after generative AI: relative use of words like could fell even as raw counts rose with more published text.
4 min · 817 words
Why I Think You Should Almost Never Use AI to Write Anything Substantive
Erich Grunewald argues that using AI to draft substantive writing erodes thinking, voice, and accountability—and that almost everything worth writing is better done by a human who owns the words.
15 min · 3,455 words
Noah Smith on what it means when AI becomes better at mathematics than any human—how “hero” mathematicians shaped culture, and how post-heroic math and science might look when machines own the frontier.
14 min · 3,242 words
There's no point at which turning your brain off will work
Dan Luu argues that turning off critical judgment while using LLMs fails in practice: when people let models take actions or produce analyses without verification, errors compound — there is no safe point at which you can stop thinking.
12 min · 2,831 words
AI and Math in 2026: a non-mathematician's read
xlr8harder synthesizes recent AI math results for non-specialists: real progress with a different strength profile than humans, formalization cliffs, and why “math nearly conquered” remains overhyped.
3 min · 750 words