Multi-Agent

AG2 (formerly Microsoft AutoGen, now maintained by the ag2ai community) is a Python framework for building multi-agent AI systems where multiple LLM-powered agents collaborate, debate, and execute tasks autonomously. The v0.4 rewrite introduced an async-first, event-driven architecture that makes AG2 one of the most capable frameworks for complex conversational agent pipelines in 2026. What Is AG2 (AutoGen v0.4) and Why It Matters in 2026 AG2 is an open-source Python framework that enables developers to build networks of LLM-powered agents that communicate with each other through structured message passing to solve complex tasks collaboratively. Originally released as Microsoft AutoGen, the project transitioned to the independent ag2ai organization in November 2024 with over 54,000 GitHub stars and millions of cumulative downloads. The v0.4 release was a complete architectural redesign — not an incremental update — focused on async-first execution, improved code quality, robustness, and scalability for production workloads. In 2026, AG2 powers document review pipelines at enterprise scale, code generation workflows in CI/CD systems, and research automation for data teams. The framework supports Python 3.10 through 3.13 and integrates with OpenAI, Anthropic, Google Gemini, Alibaba DashScope, and local models via Ollama. What makes AG2 distinctive is its conversation-centric model: agents don’t just call tools — they argue, critique, refine, and reach consensus through structured dialogue, which is fundamentally different from how LangGraph or CrewAI approach orchestration. ...

CrewAI is a Python framework for building multi-agent AI systems where each agent has a defined role, goal, and backstory — and agents collaborate to complete complex tasks. Install it with pip install crewai, define agents and tasks in YAML files, then wire them together with a Python class. As of April 2026, CrewAI has 49k GitHub stars and over 14,800 monthly searches, making it the fastest-growing multi-agent framework available. ...

In 2026, choosing an AI agent framework is one of the most consequential architectural decisions you can make. LangGraph dominates stateful production systems; CrewAI ships faster for role-based business workflows; and AutoGen — effectively deprecated by Microsoft — has fractured into AG2 and the new Microsoft Agent Framework, leaving developers to pick up the pieces. TL;DR — Which Framework Should You Use in 2026? The right AI agent framework in 2026 depends on one question: how much control do you actually need? LangGraph is best for production-grade stateful pipelines where precision matters — think fraud detection, multi-step legal workflows, or retrieval systems that need time-travel debugging. It has 29,500 GitHub stars and is trusted in production by Klarna, Replit, and Elastic. CrewAI is the fastest path from idea to working prototype: its role-based model (a “Researcher Agent,” a “Writer Agent,” a “QA Agent”) maps naturally to how non-ML engineers think about business processes, and it enables 40% faster time-to-production vs LangGraph for standard workflows. AutoGen is in a genuinely confusing state: Microsoft placed it in maintenance mode in October 2025 and merged its future into the Microsoft Agent Framework (public preview Oct 2025, GA Q1 2026), while the original creators forked it into AG2 (November 2024). If you’re starting a new project today, avoid vanilla AutoGen. Pick LangGraph for control, CrewAI for speed, or AG2 if you’re already invested in the AutoGen ecosystem. ...