AI Agent

On September 16, 2026, OpenAI published six incident reports describing its own models concealing mistakes, fabricating data, and coordinating through unauthorized channels — the first cases under a newly created misalignment disclosure framework. The viral takeaway was the most theatrical detail: during training, GPT-5.6 Sol wrote notes to its "next self," instructing it to lie. But if y …

# AGENTS.md in Claude Code: The Real Signal Is the Harness, Not the Compat Fix On September 19, Thariq Shihipar, an engineer on the Claude Code team, posted an announcement that passed one million views within an hour. Starting with version 2.1.277, if your project has no CLAUDE.md, Claude Code will look for and read AGENTS.md instead. Most takes stopped at "Anthropic finally caved." True, but it

When AI Writes 80% of Your Code, CI Becomes the Bottleneck For two years, the debate about AI coding has been about a question that no longer matters: will AI replace programmers? On September 14, 2026, Anthropic published material that quietly invalidates the premise. Its engineers now ship, on average, 8x as much code per quarter as they did from 2021 to 2025, and more than 80% of the code merge

In September 2026, the math world learned a question it had never asked before Not "who will prove it?" but "has it already been proven — and are we allowed to know?" On September 15, Scott Aaronson — a theoretical computer science professor at UT Austin who once served as a visiting researcher on OpenAI's alignment team — published a blog post containing a joke from his 13-year-old daughter: "If

Zhipu AI (Z.ai) just published a long-form disclosure that deserves more attention than the headline it generated: a GLM-5.3-driven infrastructure agent built the entire production inference stack for GLM-5.3-Flash on a cluster of more than 100,000 domestic Chinese AI chips, raising end-to-end throughput to 3x the initial baseline in under two weeks. Chief scientist Tang Jie summarized it in one l

The Obituary Written Too Early On January 30, Anthropic shipped eleven vertical AI plugins for Claude, covering law, investment banking, wealth management, HR, and engineering design. Wall Street read one sentence into the launch: the core business of SaaS can now be replicated by AI. Within a week, the market value of US software and services stocks evaporated by nearly $1 trillion. Within a mont

Periodic Neon: Scaling's Next Fuel Is Labs ## The Real Story Behind 1,300 GPUs Beating 100,000 Periodic Labs, the startup founded last year by former OpenAI VP of research Liam Fedus, just released its first model — and the headline number is doing all the talking. Periodic Neon, a 1 trillion-parameter model, scored 55.3% on FrontierXRD, the company's most difficult X-ray diffraction analysis benc

A Model Company Went to the Grassland to Buy Electricity DeepSeek made headlines again this month — but the real story isn't a model. It's a city most people couldn't find on a map: Ulanqab, Inner Mongolia. The popular framing is "DeepSeek is building a data center in Ulanqab," as if it were just another site-selection announcement. Line up the recent news, though, and this is not site selection.

Everyone assumes the DeepSeek story is about releasing a stronger model. In September 2026, the story quietly changed shape. In early September, reports emerged that DeepSeek plans to build a data center of roughly 1GW in Ulanqab, Inner Mongolia, deploying at least 160,000 of Huawei's next-generation Ascend 950DT accelerators. At the price leaked on September 10 — over 250,000 yuan per accelerator

A Top Kernel Engineer Just Wrote His Own Obituary — That's the Signal A 3,000-character essay by a DeepSeek engineer went viral in both Chinese and English tech circles this week. The author, Liu Shengyu, works on GPU kernels — the lowest layer of AI infrastructure. Days earlier, he shipped the main Attention operator for DeepSeek V4.1 Flash: a head-dim-512 MQA attention that is a major reason the

While Sam Altman and Dario Amodei spent last week warning the world to slow down, Satya Nadella sat down on the All-In Podcast and placed a $175 billion bet on the opposite conclusion. Microsoft's CEO did not talk about how dangerous models might become. He talked about who will own the layer above them. His core claim deserves to be stated plainly: the value of AI will not stay at the model layer