In Session 5 of our Python + Agents series, we’ll go beyond workflow fundamentals and explore how to orchestrate *advanced, multi‑agent workflows* using the Microsoft Agent Framework.
This session focuses on patterns that coordinate multiple steps or multiple agents at once, enabling more powerful and flexible AI‑driven systems. We’ll begin by comparing **sequential vs. concurrent execution**, then dive into techniques for running workflow steps in parallel.
You’ll learn how fan‑out and fan‑in edges enable multiple branches to run at the same time, how to aggregate their results, and how concurrency allows workflows to scale across tasks efficiently.
From there, we’ll introduce two multi‑agent orchestration approaches that are built into the framework. We’ll start with **handoff**, where control moves entirely from one agent to another based on workflow logic, which is useful for routing tasks to the right agent as the workflow progresses.
We’ll then look at **Magentic**, a planning‑oriented supervisor that generates a high‑level plan for completing a task and delegates portions of that plan to other agents.
Finally, we'll wrap up with a demo of an E2E application that showcases a concurrent multi-agent workflow in action.
Prerequisites: To follow along with the live examples, sign up for a free GitHub account. If you are brand new to generative AI with Python, start with [our 9-part Python + AI series](https://aka.ms/pythonai/rewatch), which covers LLMs, embedding models, RAG, tool calling, MCP, and more.
📌 This event is a part of a series, learn more here: https://aka.ms/PythonAgents/YT
Microsoft Agent Framework: https://learn.microsoft.com/agent-fra...
Chapters:
0:00 Introduction to Advanced Multi-Agent Workflows
4:05 Recap: Agentic Workflows
7:36 Concurrency and Fan-Out/Fan-In Patterns
11:43 Aggregation Patterns
25:56 Conditional Routing with Concurrency
30:09 Built-in Workflow Orchestrations: Concurrent Builder
33:12 Magentic Builder: Planning and Progress Management
46:39 Handoff Orchestration: Dynamic Routing
57:18 Full-Stack Application Demo
1:01:32 Conclusion and Next Steps
#microsoftreactor #learnconnectbuild
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