Nguyễn Thành Sơn

I've used ROMA to build a multi-agent system for handling complex data analysis in my AI research project, and wow, this is truly the 'backbone' that the open-source community has been craving! What I love most is the recursive hierarchical structure—it intelligently breaks down large tasks into smaller subtasks, allowing sub-agents to coordinate smoothly without any messiness. The full transparency is a huge plus: I can trace every step, debug effortlessly, and explain results to my team without any guesswork.Compared to other frameworks like LangChain or AutoGen that I've tried, ROMA stands out in speed and scalability—it handles sophisticated tasks twice as fast while maintaining high accuracy, especially when integrating external tools. The modular design is incredibly flexible, making it easy to customize agents without messy coding. Even though it's newly launched, the docs are crystal clear, and the GitHub repo is super active, giving me the confidence to deploy it straight to production.The only improvement I'd suggest: Add a few more detailed benchmark examples for newbies. Overall, if you're building multi-agent systems, ROMA is the top choice—high-quality open-source, free, and packed with potential for the future of AGI. Highly recommend!