Co-founder & CAIO |All Hands AI (OpenHands)
Built OpenHands (69K+ stars), the leading open-source AI software development agent. Invented CodeAct (ICML 2024) for code-based agent actions.
Biography
Xingyao Wang (born 1999, Fujian, China) is the Co-founder and Chief AI Officer of All Hands AI, building OpenHands -- the leading open-source AI software development agent with 69,000+ GitHub stars and 300+ contributors. He is a PhD candidate in Computer Science at the University of Illinois Urbana-Champaign, advised by Prof. Heng Ji and collaborating with Prof. Hao Peng. He earned his B.S. in Computer Science and Data Science from the University of Michigan, where he graduated with University Honors and received an Honorable Mention for the CRA Outstanding Undergraduate Researcher Award. His research focuses on AI agents that interact with computers through code, assist humans, and continuously self-improve. He is the first author of the foundational CodeAct paper (ICML 2024), which proposed using executable Python code as a unified action space for LLM agents -- the architectural insight that underpins OpenHands. He co-founded All Hands AI in 2024 alongside Robert Brennan (CEO) and Graham Neubig (CMU professor), raising $5M seed led by Menlo Ventures / Anthology Fund (Anthropic) and $18.8M Series A led by Madrona. Previously interned at Google Research, Microsoft, ByteDance, and Tencent.
The leading open-source AI software development agent (69K+ GitHub stars, 300+ contributors). Autonomously solves software engineering tasks end-to-end -- writing code, running commands, and browsing the web in sandboxed environments. First open AI agent to surpass 50% on SWE-Bench Verified.
ICML 2024 Oral paper proposing executable Python code as a unified action space for LLM agents, achieving up to 20% higher success rates than JSON/text alternatives. The foundational architecture behind OpenHands.
ICLR 2024 benchmark for evaluating LLMs in multi-turn interaction with tools and language feedback, providing a rigorous framework for assessing agent capabilities across iterative problem-solving.
Training framework for software engineering agents and verifiers (ICML 2025). Provides environments for training and evaluating AI agents on real-world software engineering tasks.
A composable and extensible SDK for building production-grade AI agents, providing the building blocks for multi-agent orchestration and tool integration.
ICLR 2024 paper on customizing LLMs by creating and retrieving from specialized toolsets, enabling dynamic tool creation for novel tasks.
Instead of AI demanding constant attention, I prefer autonomous AI that solves problems independently.
When it comes to dev tools, open source generally wins.
We're building open source AI agents that can tackle all the toil involved in an engineer's day-to-day work, so developers can focus on what they do best -- creative problem-solving.
Xingyao's deep empathy for the developer creates the perfect storm to tackle this market.
Research generated March 19, 2026