mlsanityData to 14 Oct 2026

ChatDev 2.0: A No-Code Multi-Agent Platform for Developing Everything

arXiv 2609.00714 ↗First posted 1 Sep 2026cs.AI cs.CL cs.MAcited by 0

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Large language model (LLM)-based multi-agent systems (MAS) have shown strong potential for solving complex tasks, yet their development forces a tradeoff: code frameworks are expressive but engineering-intensive, while no-code builders simplify authoring but constrain agent interactions to author-defined workflows. We present ChatDev 2.0: DevAll (hereafter DevAll), a no-code platform for building, executing, and inspecting heterogeneous MAS that delivers both high expressiveness and ease of use. In terms of expressiveness, DevAll pairs a declarative executable graph abstraction with a cycle-aware execution engine, so that heterogeneous agents and dynamic and cyclic interactions can be represented and executed within a single framework. For ease of use, an integrated visual interface lets users author, run, monitor, and inspect MAS, including human-in-the-loop steps, entirely without writing code. Experiments demonstrate that DevAll reproduces state-of-the-art MAS across three representative tasks at competitive performance and without task-specific orchestration code, highlighting its effectiveness as a general-purpose platform for LLM-based MAS. DevAll is available at https://github.com/OpenBMB/ChatDev.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 13 of its 32 references that are in the map. First posted on arXiv 1 Sep 2026.

Builds on

13 of 32 references.

Closest ancestors · 3

Same direction, newest first

  1. 2026Graph-of-Agents: A Graph-based Framework for Multi-Agent LLM Collaboration18 Apr
  2. 2024Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks7 Nov
  3. 2024AgentScope: A Flexible yet Robust Multi-Agent Platform21 Feb

Other references · 10

  1. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  2. 2025Why Do Multi-Agent LLM Systems Fail?cited by 604
  3. 2025DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agentscited by 248
  4. 2024MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualizationcited by 102
  5. 2024MindSearch: Mimicking Human Minds Elicits Deep AI Searchercited by 66
  6. 2025METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scalingcited by 34
  7. 2025Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analyticscited by 20
  8. 2025CoDA: Agentic Systems for Collaborative Data Visualizationcited by 15
  9. 2024AI2Apps: A Visual IDE for Building LLM-based AI Agent Applicationscited by 5
  10. 2025TeachMaster: Generative Teaching via Codecited by 1

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026MASFactory: A Graph-centric Framework for Orchestrating LLM-Based Multi-Agent Systems with Vibe Graphing
  2. 2026MAS-Gate: Unlocking Multi-Agent System Lifecycle via Node-Centric Quantification
  3. 2023ChatDev: Communicative Agents for Software Development
  4. 2025Unifying Language Agent Algorithms with Graph-based Orchestration Engine for Reproducible Agent Research
  5. 2024Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimization
  6. 2025AutoMisty: A Multi-Agent LLM Framework for Automated Code Generation in the Misty Social Robot
  7. 2026Decentralized Multi-Agent Systems with Shared Context
  8. 2026Code as Agent Harness