Managing AI Collaboration
Part of the Vibe Coding: Multi-Agent Engineering course
In the last three lessons you designed a team of agents, gave each one a role, and learned to hand work between them with a clean handoff. Now you put the team to work on a single piece of the product at the same time. The goal of this lesson is to get several agents to build one feature together without stepping on each other, with you as the coordinator in the middle.
Shared context is the one common understanding every agent works from: the goal you are building toward, the plan you agreed on, and what is already done. On a real team this lives in a shared document. With agents, it lives with you, because each agent knows only what you put in front of it. ...
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Start this lessonManaging AI CollaborationWhat you'll learn
- Shared context: the one common understanding all agents work from (the goal, the plan, what is done)
- Planning: agreeing the approach before anyone starts building
- Communication: relaying one agent's output to the next as clean input
- Reviews: one agent checking another's work before it counts as done
- Iteration: looping build, review, refine instead of one-shotting a feature
- Driving one small feature through planner, developer, and reviewer as the coordinator
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All lessons in this course
12 lessons- 1Thinking Like an Engineering Leader20 min
- 2Creating Specialized AI Agents20 min
- 3Giving Every Agent a Role20 min
- 4Managing AI Collaboration30 min
- 5AI Code Reviews30 min
- 6AI Project Management20 min
- 7AI DevOps30 min
- 8AI Security Teams30 min
- 9AI Operations30 min
- 10Building Your Own AI Workflow20 min
- 11Scaling AI Teams20 min
- 12Becoming an AI Engineering Leader45 min
