CourseAgentic AI Engineer: The Complete Course · Module 11: Multi-Agent Systems · part 64 of 97
Part 64 · Module 11: Multi-Agent Systems

Lab: Decide whether to split, and prove it

42 min read·13 Oct 2026
Module 11 · Lab · About 75 minutes · Needs: the Module 3 lab's tools.py, and lessons 1, 2 and 3 (one agent first and return_workflow; orchestrate, merge and fan-out by order; TaskSpec, compress, the order lock and the cost ledger)

What you are building

RETURNS-DESK/ AFTER THIS LAB team.py specs, budgets, gate decision.py measure, write docs/ multi-agent-decision tools.py Module 3's, imported BrightCartSystems model 3 tests
The finished piece: two new files of your code (blue) that go through Module 3's tools.py (grey, kept as it was), a decision document and three tests (green).

It is Thursday 4 June 2026, week 8. Dev's whiteboard still shows three agents, and the three lessons have tested every shape on it. This lab turns their answers into code and a written decision. returns_desk/team.py holds the mechanics any split must use: a task spec enforced in code, a subagent loop that charges every model call to an agent, one budget per request, compressed results with a trace id, a read-only brief of the queue, and one writer per order. returns_desk/decision.py measures one agent against the split on R-1001 and writes docs/multi-agent-decision.md from the numbers. Both import Module 3's tools.py and never replace it. Everything at BrightCart is simulated.

The rest of this course is yours to keep

This course is bought on its own, once, and stays readable afterwards, including the parts added to it later.