My own personal AI development setup, workflow, and tooling
Meet Foundry: An AI Startup that Builds, Evaluates, and Improves AI Agents
The Open-Source Toolkit for Building AI Agents v2
An opinionated, developer-first guide to building AI agents with real-world impact
trycua/acu
A curated list of resources about AI agents for Computer Use, including research papers, projects, frameworks, and tools.
AI agents team up in Agent Laboratory to speed scientific research
Johns Hopkins University and AMD have developed Agent Laboratory, a new open-source framework that pairs human creativity with AI-powered workflows.
The Agentic Systems Series - The Agentic Systems Series
Welcome to the complete guide for building AI coding assistants that actually work in production. This comprehensive three-book series takes you from fundamental concepts to implementing enterprise-ready collaborative systems.
browser-use/browser-use
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
10 things I learned from burning myself out with AI coding agents
Opinion: As software power tools, AI agents may make people busier than ever before.
Collaborative AI Engineering: One Dev, Two Dozen Agents, Zero Alignment — Maggie Appleton, GitHub
The Rise of Agent Experience (AX)
Introduction to Agents
Discover what actually works in AI. Join millions of builders, researchers, and labs evaluating agents, models, and frontier technology through crowdsourced benchmarks, competitions, and hackathons.
Generative AI in a Nutshell - how to survive and thrive in the age of AI
The 2025 AI Agent Index Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu.
The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu
The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
Agentic AI systems are increasingly capable of performing professional and personal tasks with limited human involvement. However, tracking these developments is difficult because the AI agent ecosystem is complex, rapidly evolving, and inconsistently documented, posing obstacles to both researchers and policymakers. To address these challenges, this paper presents the 2025 AI Agent Index. The Index documents information regarding the origins, design, capabilities, ecosystem, and safety features of 30 state-of-the-art AI agents based on publicly available information and email correspondence with developers. In addition to documenting information about individual agents, the Index illuminates broader trends in the development of agents, their capabilities, and the level of transparency of developers. Notably, we find different transparency levels among agent developers and observe that most developers share little information about safety, evaluations, and societal impacts. The 2025 AI Agent Index is available online at https://aiagentindex.mit.edu
Got to talk at @aidotengineer.bsky.social conf last week about the need for collaborative AI engineering. All our current coding agents are single player. We're trying to scale up individual productivity, but creating tons of alignment problems in the process. We have no good tools for...
