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Launching Meta Enterprise Platform
Mark Zuckerberg announces Meta Enterprise Platform as a new major business pillar, bringing Muse, Meta Business Agent, Muse API, and Muse Code to enterprises—led by former MongoDB CEO Chirantan “CJ” Desai as Chief Enterprise Platform Officer.
2 min · 363 words
How Pew Research Center is – and is not – using AI in our work
Pew Research Center outlines internal AI guidelines: surveys stay human-answered, disclosure rules for production use, and careful experimentation while keeping research people-centered.
2 min · 542 words
It’s Time to Investigate the AI Labs
Cal Newport argues frontier AI labs have grown brazen in public messaging about agent harms and extinction risk, and that Congress should investigate rather than let private companies set the narrative.
2 min · 564 words
Small Decisions: Engineering a Leading Model
AWS engineer Marc Brooker recounts building and training a small leading model hands-on—what worked, how it performed, and what the exercise taught him about modern model-building.
9 min · 2,024 words
When I was a freshman at RISD, there was a club fair, and I was drawn to the RISD STEAM table, where I met Carly Ayres and Sayer Pease. They welcomed me with open arms, and I started to learn about things like 3D printers and Arduino. I first learned Processing from Clement Valla, paper electronics from Jie Qi, and then Arduino from Paul Badger. I fell in love, and the fate was more or less sealed when I made my first music synthesizer. Creating a tool that output things I never thought of while making it lit up my heart, and is still why I do the things I do today.…
5 min · 1,063 words
What I believe about the future of software development
Thorsten Ball plants a flag on where software development is headed as AI agents write more of the code: what still matters for engineers, what gets commoditized, and how taste and judgment become the scarce skills.
4 min · 809 words
Russell Sechzer on what's missing in agentic commerce: incomplete financial instructions, who authorizes agents, who pays for work that never becomes a purchase, and the invisible costs behind Muse, Instinct, Stripe, Visa, and AP2.
8 min · 1,882 words
LinkedIn is a soulsucking hole of professionalism and a pit of hell that not even my worst enemy should spend the rest of his days in. It’s this concoction of performative productivity and corpo speak producing cursed artifacts beyond human comprehension. A place where normal human text goes to die and can only be kept alive by an LLM like a radiation protection suit.
4 min · 999 words
Throughout the history of AI, open research has played a critical role in driving progress. Today, many key details of frontier large language models (LLMs) remain proprietary, but open-weights model families— such as DeepSeek, Kimi, and MiMo —continue to provide a valuable window into the development process for modern LLMs.
7 min · 1,609 words
As If Yesterday, in Partly in the Right, I asked where the information comes from when an agent produces a result, and what checks it. Today I have a sharper version of that question, and a new piece of evidence to ask it about.
13 min · 2,972 words
AMD to Acquire World Labs to Advance the Future of AI Compute
AMD announces a definitive agreement to acquire Fei-Fei Li’s World Labs, bringing spatial AI researchers and models in-house to shape future AI hardware, software, and systems.
4 min · 1,011 words
World Labs announces a definitive agreement to join AMD, arguing that scale, reach, and closer hardware partnership are needed to accelerate spatial and physical AI research.
1 min · 218 words
Robert W argues LLM confidence scores are vibe-words, not calibrated probabilities—and outlines RLCD-style approaches that treat hallucination as a solvable measurement and training problem.
7 min · 1,560 words
Pranav Desai catalogs ten visual and copy tells of AI-generated “slop UI”—from rainbow gradients and pulsing badges to glassmorphism and generic hype—and why vibe-coded interfaces often look cheap without a design vision.
4 min · 908 words
What is the date today? what 83 AI models think
We put "What is the date today?" to 83 AI models (GPT, Claude, Gemini, DeepSeek…) at the same time. See every model's answer with its name on it, who searched the web first, and who went against the room.
12 min · 2,726 words
PotemkinOS: an operating system where the model writes the userland
Gabe Ortiz’s joke-with-a-build: a Linux image with no userland—only a kernel, inference engine, C compiler, and eight tools—so the model must invent its own shell, ls, and eventually a Kubernetes facade three villages converge on.
3 min · 699 wordsagent-assisted
AI companies in race to demonstrate their model most threatening to humanity
A satirical Civilian piece on frontier labs competing to look the most existentially dangerous—skewering safety theater and marketing-as-doom.
3 min · 674 words
Hard Stop: Kernel-Level Preemption and Containment for Rogue Agentic Execution
A research write-up proposing Dual-Sided Andon: out-of-band, kernel-boundary preemption and containment for runaway AI agents, arguing application-level kill switches are insufficient.
21 min · 4,848 words
What's wrong with Open Source AI?
Alexine Le Port on the shrinking gap between open-weight and frontier models—and why open-source AI culture is still mostly vibing instead of shipping durable public infrastructure.
3 min · 651 words
What Would A Serious AI Product Look Like?
One of the issues that I have with the current generation of “AI” products is that they do not appear to take their own premises seriously. I look at a plethora of obsequious chatbots claiming to be serious tools for problem solving, and I think, this is not what a problem-solving tool would look like. Even before we get to the tremendous ethical problems with the frontier labs, it is this impression of their composition *as a product* that makes me feel, constantly, whenever I am interacting…
22 min · 5,119 words