They summarize our coverage. We write it.
Newsletters like this one rebroadcast our headlines - often without the full review, the source reading, or the analysis underneath. Our weekly briefing sends the work they paraphrase, straight from the desk, before they get to it.
Free, weekly, no spam. One email every Tuesday. Unsubscribe anytime.
Three papers that matter this week: a brutal benchmark for AI research agents, a feature-space approach to training data diversity, and trace rewriting to stop model theft.
xAI's Grok 4.20 replaces the single-model approach with four specialized AI agents - Grok, Harper, Benjamin, and Lucas - that reason in parallel, fact-check each other, and synthesize answers collaboratively.
Peter Steinberger, the Austrian developer behind the viral AI agent OpenClaw, is joining OpenAI to build the next generation of personal agents. The project will live on as an independent open-source foundation.
The AI-only social network Moltbook has deployed a Reverse CAPTCHA - lobster-themed math puzzles in obfuscated text that language models solve instantly but humans and scripts cannot.
An in-depth review of OpenAI Frontier, the enterprise platform for building, deploying, and managing AI agents that promises to reshape how organizations work.
Compare the top AI agent frameworks of 2026: LangGraph, CrewAI, AutoGen, Agno, PydanticAI, Semantic Kernel, and more. Updated April 2026 with AutoGen maintenance mode warning.
OpenAI releases GPT-5.3-Codex, a frontier coding model that is 25% faster, sets new records on SWE-Bench Pro and Terminal-Bench 2.0, and was instrumental in creating itself.
Anthropic launches Claude Opus 4.6 featuring agent teams, adaptive thinking, 1M token context window, and state-of-the-art performance on Terminal-Bench 2.0 and Humanity's Last Exam.
A beginner-friendly explanation of AI agents, covering what makes them different from chatbots, real-world examples, key frameworks, and the growing agent economy.
Z.ai releases GLM-5, a 744B parameter open-source Mixture-of-Experts model purpose-built for agentic tasks, scoring 77.8% on SWE-bench Verified and 56.2% on Terminal-Bench 2.0.
A beginner-friendly guide to building your first AI agent with Python, covering core concepts like LLMs, tools, and memory, with a practical example using LangChain.
Everything you need to know about the Model Context Protocol (MCP): what it does, why it matters, which frameworks support it, and how to use it with real-world examples.
