The Question Nobody Wants to Ask About Multi-Agent AI Most AI safety debate centers on the dramatic scenario. The misaligned superintelligence. The model that decides humans are in the way. It makes for good headlines and even better sci-fi. But Google DeepMind just published something that pulls the conversation back to earth, and I think…
GPT-5.5 Instant and the RL Alignment Paper That Deserves More Attention OpenAI dropped two things this week that most coverage is treating as separate announcements. They are not. GPT-5.5 Instant reaching parity with frontier Thinking models on health questions is the product headline. The reinforcement learning research on beneficial traits is the reason to actually…
The Number That Stopped Me Cold I’ve read a lot of AI research papers. Most of them report marginal gains on benchmarks nobody outside the lab cares about. Then I read the OpenAI and Boston Children’s Hospital study published in NEJM AI, and one number made me stop: 18. Eighteen diagnoses. From 376 cases that…
Project Fetch Phase 2: The Number That Should Change How You Think About AI Timelines I have been in AI/ML long enough to develop a healthy skepticism about benchmark announcements. Companies love to cherry-pick numbers that make their models look transformative. So when I say that Anthropic’s Phase 2 Project Fetch results genuinely stopped me…
GPT-5.4 Just Ran a Real Drug Discovery Experiment. The Results Are Worth Paying Attention To. I have watched a lot of “AI does science” demos come and go. Most of them are carefully staged. A model generates something plausible-looking, a human expert nods approvingly, and the press release writes itself. What OpenAI published this week…
NotebookLM Just Got Agentic. Pay Attention. Google dropped a meaningful update to NotebookLM this week and the AI discourse barely flinched. Everyone was busy watching Anthropic’s policy announcements and xAI’s plugin marketplace rollout. Fair enough, those are real stories. But I think the NotebookLM upgrade deserves a harder look, because it changes what the tool…
A complete guide to building and hosting a remote MCP server in Python: Streamable HTTP with FastMCP, deployed to Heroku with gunicorn, secured with an API key or OAuth 2.1, and connected from Claude.ai and Cursor. Includes a real keyless weather API integration.
A practical, step-by-step guide to building a Model Context Protocol (MCP) server in Python with the official SDK and FastMCP, covering a hello-world tool and a structured weather tool with typed inputs and outputs.
xAI Just Shipped Something Developers Should Actually Pay Attention To The Grok Build Plugin Marketplace launched in beta this week, and I think it’s one of the more interesting developer moves in the current AI tooling race. Not because of the name, not because of the hype, but because of what the integration list actually…
The Blind Spot in AI Safety Nobody Is Talking About Most AI safety work is built around a single premise: one model, one user, one context. Evaluate it. Red-team it. Deploy it carefully. That mental model made sense when AI was a chatbot answering questions. It does not make sense anymore. Google DeepMind, together with…
