Pamela Fox
Microsoft
PELAJARI, SAMBUNGKAN, BANGUN
Siap untuk mulai menggunakan AI dan teknologi terbaru? Microsoft Reactor menyediakan acara, pelatihan, dan sumber daya komunitas untuk membantu pengembang, pengusaha, dan startup dibangun berdasarkan teknologi AI dan banyak lagi. Gabung dengan kami!
PELAJARI, SAMBUNGKAN, BANGUN
Siap untuk mulai menggunakan AI dan teknologi terbaru? Microsoft Reactor menyediakan acara, pelatihan, dan sumber daya komunitas untuk membantu pengembang, pengusaha, dan startup dibangun berdasarkan teknologi AI dan banyak lagi. Gabung dengan kami!
4 Maret, 2026 | 6.30 PM - 7.30 PM (UTC) Waktu Universal Terkoordinasi
Topik: Agen
Bahasa: Inggris
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.
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 our 9-part Python + AI series, which covers LLMs, embedding models, RAG, tool calling, MCP, and more.
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Acara ini adalah bagian dari Python + Agents: Building AI agents and workflows with Agent Framework Series.
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