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Vibe Coding Is Easy. Production Isn't.
Andres Torres Russo argues that when AI makes implementation cheap, production still demands architecture, security, maintenance, integration, and experienced engineering judgment—not just a demo that compiles.
10 min · 2,311 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
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
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
Seohong Park reproduces four real-robot behavioral cloning quirks in sim: overfitting can help, open-loop beats closed-loop, policies need huge MLPs, and feature scaling still matters under infinite data—all driven by test-time distribution shift.
13 min · 2,876 words
Finding bugs used to be the best part of the job. Somewhere along the way, that changed. Just spawned Codex in the background. I’m hoping I will land a critical by the time I finish writing this. It was a normal day. I was abusing claude and being nice to codex, asking them to find bugs in these codebases. Then, at some point, I stopped and thought: What the hell am I doing?
4 min · 944 words
Building Brand Systems for Humans & Agents Today
Little Plains argues brand kits are becoming dual-native knowledge bases: human-readable guidelines plus agent-readable ~400-token chunks (YAML/JSON/Markdown) so teams and agents share the same positioning and voice.
5 min · 1,226 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
"Vibe coding" is the new "Internet dating"
An analogy between early-2000s internet dating stigma and today's vibe-coding skepticism: both start as jokes, then quietly become how a lot of people actually meet their goals.
1 min · 199 words
The fall of the theorem economyHow AI could destroy mathematics and barely touch it
David Bessis argues AI is exploiting mathematicians' honor-code incentives: when theorems become cheap to produce, prestige-driven theorem economies collapse even if mathematical understanding itself is barely touched.
47 min · 10,783 words
Software is still about thinking
Cursor’s head of design argues AI coding creates an illusion of speed without structure: unclear systems thinking now produces slop at scale, while clear architecture compounds into 100x leverage.
2 min · 468 words
The Graph Will Set You Free: Why Every Creative Tool Is Becoming a Node Canvas
Hirad Sab traces node-based creative tools from Sketchpad to modern AI canvases, arguing graphs are the right abstraction when generation becomes a networked, composable process.
8 min · 1,935 words