Topic
AutoGen Agent Teams for Research & Automation
11 posts on autogen agent teams for research & automation — part of framework tutorials on the n4n AI blog.
Coordinating AutoGen agent teams across GPT-5.1 and Gemini 3
Hands-on tutorial for engineers coordinating an AutoGen agent team across GPT-5.1 and Gemini 3, with runnable Python code and success checks.
Building a web-research AutoGen team with tool use
A practical step-by-step tutorial for building an autogen web research agent team tool use with live web tools, verifiable output, and OpenAI-compatible models.
Build an AutoGen research team with n4n.ai routing
Build a multi-agent research pipeline with AutoGen and route LLM calls through n4n.ai for fallback and 240+ models via one OpenAI-compatible endpoint.
Automating literature reviews with AutoGen agent teams
Learn how to build a multi-agent AutoGen pipeline that automates literature reviews: search arXiv, summarize papers, and synthesize findings with minimal code.
AutoGen SelectorGroupChat: dynamic speaker selection
AutoGen SelectorGroupChat speaker selection uses an LLM to dynamically route multi-agent conversations. Learn how it works, with code and pitfalls for building robust agent teams.
AutoGen RoundRobinGroupChat explained with an example
RoundRobinGroupChat runs agents in fixed order for predictable multi-agent loops in AutoGen. This autogen roundrobingroupchat tutorial shows code and pitfalls.
AutoGen GroupChat vs SelectorGroupChat: which to use
A practitioner's head-to-head comparison of AutoGen GroupChat vs SelectorGroupChat across capabilities, cost, latency, ergonomics, and limits for engineers building multi-agent systems.
AutoGen agent teams tutorial: building a research crew
Hands-on autogen agent team research tutorial: build a multi-agent research crew with AutoGen, step-by-step code, and real output checkpoints.
AutoGen agent teams: termination conditions explained
A hands-on autogen agent team termination condition tutorial: learn how to control multi-agent loops with clear exit signals and custom predicates.
AutoGen agent teams for report generation and QA
Step-by-step guide to building an AutoGen multi-agent pipeline that researches, drafts, and QA-checks reports with OpenAI-compatible LLM endpoints.
AutoGen agent team tutorial: planner, coder, critic roles
Hands-on AutoGen tutorial: build a multi-agent team with planner, coder, and critic roles using group chat to plan, write, and review Python code.
More topics in framework tutorials
- Choosing an AI Framework by Use Case10
- Framework Tutorials: Legal & Healthcare Document Q&A9
- One Backend, Every Model: Swapping GPT-5, Claude, Gemini & Llama Across Frameworks9
- AutoGen Human-in-the-Loop Workflows8
- LangChain Multi-Model Fallback & Routing8
- AutoGen Getting Started with n4n.ai7
- AutoGen Multi-Agent Conversations & Group Chat7
- Building Chatbots with Vercel AI SDK & Next.js7
- CrewAI Agent Roles & Task Design7
- CrewAI Getting Started with n4n.ai7
- CrewAI Real-World Crew Examples7
- Framework Tutorials: Customer Support Bots7