mlsanityData to 7 Oct 2026

AutoGen Studio: A No-Code Developer Tool for Building and Debugging Multi-Agent Systems

arXiv 2408.15247 ↗First posted 9 Aug 2024cs.SE cs.AI cs.CLcited by 20

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Multi-agent systems, where multiple agents (generative AI models + tools) collaborate, are emerging as an effective pattern for solving long-running, complex tasks in numerous domains. However, specifying their parameters (such as models, tools, and orchestration mechanisms etc,.) and debugging them remains challenging for most developers. To address this challenge, we present AUTOGEN STUDIO, a no-code developer tool for rapidly prototyping, debugging, and evaluating multi-agent workflows built upon the AUTOGEN framework. AUTOGEN STUDIO offers a web interface and a Python API for representing LLM-enabled agents using a declarative (JSON-based) specification. It provides an intuitive drag-and-drop UI for agent workflow specification, interactive evaluation and debugging of workflows, and a gallery of reusable agent components. We highlight four design principles for no-code multi-agent developer tools and contribute an open-source implementation at https://github.com/microsoft/autogen/tree/main/samples/apps/autogen-studio

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 7 of its 12 references that are in the map. First posted on arXiv 9 Aug 2024.

Builds on

7 of 12 references.

References · 7

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  3. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  4. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
  5. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  6. 2023Augmented Language Models: a Surveycited by 398
  7. 2023TaskWeaver: A Code-First Agent Frameworkcited by 85

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 7; 2026: 10.

20 papers.

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  1. 2025A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectivescited by 27
  2. 2024Challenges in Human-Agent Communicationcited by 11
  3. 2025From Conversation to Orchestration: HCI Challenges and Opportunities in Interactive Multi-Agentic Systemscited by 9
  4. 2024Good Parenting is all you need -- Multi-agentic LLM Hallucination Mitigationcited by 7
  5. 2025GeoFlow: Agentic Workflow Automation for Geospatial Taskscited by 7
  6. 2026DiLLS: Interactive Diagnosis of LLM-based Multi-agent Systems via Layered Summary of Agent Behaviorscited by 7
  7. 2024Data Analysis in the Era of Generative AIcited by 6
  8. 2026AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systemscited by 6
  9. 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gapcited by 6
  10. 2025SwarmSys: Decentralized Swarm-Inspired Agents for Scalable and Adaptive Reasoningcited by 5
  11. 2026MAS-PromptBench: When Does Prompt Optimization Improve Multi-Agent LLM Systems?cited by 4
  12. 2025Transduction is All You Need for Structured Data Workflowscited by 3
8 more
  1. 2025VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agentscited by 0
  2. 2025Agentic Meta-Orchestrator for Multi-task Copilotscited by 0
  3. 2026Don't Vibe Code, Do Skele-Code: Interactive No-Code Notebooks for Subject Matter Experts to Build Lower-Cost Agentic Workflowscited by 0
  4. 2026Agents in the Wild: Where Research Meets Deploymentcited by 0
  5. 2026TraceGrant: A Contract-Governed Security Framework for the Task-Effect Lifecycle of Networked LLM Agentscited by 0
  6. 2026Dr. Claw: An AI Scientist Workspace for Vibe Researchcited by 0
  7. 2026Bioinfoysis Technical Reportcited by 0
  8. 2026Understanding Issues, Causes and Solutions in Open-Source LLM-based Multi-Agent Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Interactive Debugging and Steering of Multi-Agent AI Systems
  2. 2025AgentMesh: A Cooperative Multi-Agent Generative AI Framework for Software Development Automation
  3. 2024CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technology
  4. 2026Developing LLM-based Multi-Agent Systems in Software Engineering: A Mixed-Method Experience Report
  5. 2026ADK Arena: Evaluating Agent Development Kits via LLM-as-a-Developer
  6. 2025Simpliflow: A Lightweight Open-Source Framework for Rapid Creation and Deployment of Generative Agentic AI Workflows
  7. 2024Experimenting with Multi-Agent Software Development: Towards a Unified Platform
  8. 2025AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents