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Anthropic economists compare survey answers from US adults and Anthropic staff on how AI will reshape the economy. Both expect rapid progress, but staff expect much more: 91% versus 39% expect a Nobel-level AI discovery by 2030, and over half of staff versus 5% of US workers expect AI to do at least 80% of their own work by then.
19 min · 4,297 words
Amazon uses AI to monitor union risk in UK warehouses
openDemocracy reports that internal Amazon documents made public in a Canadian court case describe Atlas, an in-house AI forecasting tool that draws on 'hundreds of data points' including social media and staff feedback to predict union activity at warehouses in the US, Canada and UK.
6 min · 1,341 words
How employment is changing at Anthropic
Anthropic economists study how AI has restructured work inside Anthropic: hiring shifted away from junior technical roles as AI agent hours grew to outnumber employees six to one by August, output per person rose as staff adopted new tools, and human attention became the bottleneck. The paper ends with lessons for other employers.
23 min · 5,401 words
Working at the frontier shapes expectations for the future
Anthropic introduces two Oct 16 reports: how AI is changing hiring and work inside Anthropic (fewer junior hires, agents outworking employees, human attention as the bottleneck), and a survey showing staff expect far faster AI progress than US adults while reasoning about AI and jobs in a similar way.
2 min · 559 words
Should college be free? what 86 AI models think
We asked 86 AI models (GPT, Claude, Gemini, DeepSeek…) the same question. 72% picked No. See every answer, who searched the web, and who dissented.
14 min · 3,121 words
Lessons learned building Fronteira
Alcides Fonseca describes building Fronteira, an MCP proxy that acts as a behavioral firewall, logging tool calls across MCP servers and enforcing logic-based policies against lethal-trifecta attacks. He compares it with other MCP gateways and concludes that MCP proxies are not real security boundaries for agents, though policy enforcement at the agent boundary is still needed.
7 min · 1,592 words
Evolving the cloud-native foundation for the next generation of AI
Microsoft Azure describes how it is advancing cloud-native infrastructure so organizations can build, run, and optimize applications and agents at scale for the next generation of AI workloads.
7 min · 1,552 words
How to Formalize All of Mathematics
A guest post by Jeremy Avigad, Kevin Buzzard, Johan Commelin, Rémy Degenne, Kim Morrison, Oliver Nash and Adam Topaz. Responding to calls to formalize all of mathematics now that AI proves theorems well, the authors say a coordinated effort could expand discovery if done well but do lasting damage if rushed, and lay out their concerns and experiences with AI and formalization.
10 min · 2,382 words
The math that OpenAI keeps for itself
Daniel Paleka on what OpenAI's flood of AI-proved math results conspicuously skips—especially cryptography—and why the gaps matter for research priorities before the field's incentives shift further.
5 min · 1,192 words
Classic 68000 Macintosh programs from the 1980s and '90s reverse-engineered and rebuilt for modern macOS, with notes on how AI-assisted reverse engineering made the ports practical.
2 min · 380 words
We fine-tuned a 235B model on four GPUs. Then we didn't need it.
Vertexcover's Savitha Suresh recounts fine-tuning Qwen3-235B-A22B-Thinking for document entity classification on four GPUs: Axolotl, Unsloth, FSDP+QLoRA and LlamaFactory setups failed before DeepSpeed ZeRO-3 with CPU offload worked, lifting F1 by 7.6 points, before newer open models made it unnecessary.
7 min · 1,541 words
Introducing Glimpse: Visual thinking that stays grounded
Elorian introduces Glimpse, a research-preview visual thinking model that reasons directly with visual evidence: it zooms into regions, rewatches video intervals, tracks objects through motion and uses multimodal tools and subagents. Elorian reports frontier-level multimodal benchmark results at $0.60/$3.00 per million input/output tokens.
12 min · 2,751 words
Basis researchers show how LLMs can invent a programming language, write an interpreter, and prove that the interpreter follows the language's rules—arguing that shipping a verified interpreter is becoming a practical unit of AI-generated software, not just generated code snippets.
19 min · 4,264 words
Reflection releases the weights of Beam, its first open-weight model, a 501B-parameter sparse Mixture-of-Experts with 23B active parameters, on Hugging Face under Apache 2.0, with a model card and safety technical report. The post covers early developer demos, BF16/FP8/NVFP4 builds, the open-source Mirror CLI harness, fine-tuning and RL recipes, and more than 40 launch partners.
6 min · 1,393 words
AI is driving a boom in modestly successful software projects
Sean Goedecke answers the question of where all the AI-built software is by comparing install counts across about twenty marketplaces, plugin registries and modding platforms between 2022-24 and 2025-26. He finds 2x to 20x more new software overall, roughly 2x more modestly successful projects, and no growth in wildly successful ones, then speculates on why.
4 min · 1,008 words
Why harnesses matter for energy efficiency
Neuralwatt CEO Chad Gibson analyses a month of agentic traffic and finds the agent harness calling a model shapes GPU energy use: uncached input ranged from 1.6% to 11.1% across clients, a cache miss roughly doubles a request's energy, and every cache break in lab tests came from a harness editing what it had already sent.
14 min · 3,236 words
Welcome Beam: a 501B open model you can own, customize, and scale
context window of 1M tokens, and is released under the Apache 2.0 license. Beam is focused on coding and agentic use cases. It is for teams that want a frontier-scale model on their own hardware, infrastructure, or cloud, and want to customize it to their own use cases. Beam ships with its own dedicated open source Rust based harness that delivers the best performance from the model.
18 min · 4,113 words
Revisiting some of my priors about OpenClaw
Geoffrey Huntley revisits earlier skepticism about OpenClaw and explains what changed in his thinking about the open agent platform.
5 min · 1,209 words
How worried should we be about extinction risk from AI?
Fields Medallist Timothy Gowers reflects on Jacob Tsimerman's pivot to AI safety and argues carefully about extinction risk, timelines, and what mathematicians can usefully do.
34 min · 7,782 words
What is a forward deployed engineer, and do you need one?
Denys Zaichenko explains what forward deployed engineers actually do inside customer teams, how they differ from solutions engineers, and when a company needs one.
6 min · 1,404 words