2024​

• January 23, 2024 - Code execution is now by default inside docker container
• January 25, 2024 - AutoGenBench -- A Tool for Measuring and Evaluating AutoGen Agents
• January 26, 2024 - AutoGen with Custom Models: Empowering Users to Use Their Own Inference Mechanism
• February 2, 2024 - Anny: Assisting AutoGen Devs Via AutoGen
• February 11, 2024 - FSM Group Chat -- User-specified agent transitions
• February 29, 2024 - StateFlow - Build State-Driven Workflows with Customized Speaker Selection in GroupChat
• March 3, 2024 - What's New in AutoGen?
• March 11, 2024 - AutoDefense - Defend against jailbreak attacks with AutoGen
• May 24, 2024 - Agents in AutoGen
• June 21, 2024 - AgentEval: A Developer Tool to Assess Utility of LLM-powered Applications
• June 24, 2024 - Enhanced Support for Non-OpenAI Models
• July 25, 2024 - AgentOps, the Best Tool for AutoGen Agent Observability
• October 23, 2024 - Unlocking the Power of Agentic Workflows at Nexla with Autogen

2023​

• April 21, 2023 - Does Model and Inference Parameter Matter in LLM Applications? - A Case Study for MATH
• May 18, 2023 - Achieve More, Pay Less - Use GPT-4 Smartly
• June 28, 2023 - MathChat - An Conversational Framework to Solve Math Problems
• July 14, 2023 - Use AutoGen for Local LLMs
• October 18, 2023 - Retrieval-Augmented Generation (RAG) Applications with AutoGen
• October 26, 2023 - AutoGen's Teachable Agents
• November 6, 2023 - Multimodal with GPT-4V and LLaVA
• November 9, 2023 - EcoAssistant - Using LLM Assistants More Accurately and Affordably
• November 13, 2023 - AutoGen Meets GPTs
• November 20, 2023 - How to Assess Utility of LLM-powered Applications?
• November 26, 2023 - Agent AutoBuild - Automatically Building Multi-agent Systems
• December 1, 2023 - AutoGen Studio: Interactively Explore Multi-Agent Workflows
• December 23, 2023 - AgentOptimizer - An Agentic Way to Train Your LLM Agent
• December 29, 2023 - All About Agent Descriptions