Free Lesson
Multi-Agent AI Systems: When They Help and How to Build Them
30 min
Nov 11, 2026 11:00 AM
What you'll learn
Decide whether a task needs more than one agent
Weigh what several agents add, such as independent views and parallel work, against cost and latency.
Choose a design for a multi-agent system
Compare independent agents with aggregation, a supervisor that reconciles, and specialist pipelines.
Combine and check what the agents produce
Learn how to merge disagreeing answers and verify the result before the system acts on it.
Why this topic matters
Splitting a task across several AI agents can improve results, and it also multiplies cost, latency and the ways a system can fail. This lesson covers when several agents beat one, the common designs (independent agents with aggregation, a supervisor, a pipeline of specialists), and how to combine their answers and check them, with a working multi-agent system as the example.
