AI curriculum
Course outline for Agent Architecture and Orchestration
Adding agents can increase coordination failures as well as capacity. Design explicit delegation, communication, and lifecycle rules for a multi-agent application.
About Agent Architecture and Orchestration
Adding agents can increase coordination failures as well as capacity. Design explicit delegation, communication, and lifecycle rules for a multi-agent application.
Agent Architecture and Orchestration Course Objectives
- Compare single-agent and multi-agent architectures.
- Specify delegation and communication contracts.
- Plan recovery and supervision for long-running work.
Pre-requisites
- Familiarity with agent loops and tool use.
- Basic application architecture and programming skills.
Lab Setup
- Computer with a programming runtime and a local test runner.
- Use mock agents or a local model in isolated workspaces; no always-on hosted service is required.
Detailed Course Outline
Proposed modulesModule 1: Architecture choices
- Single-agent systems
- Supervisory agents
- Hierarchical agents
- Multi-agent systems
Practical outcome: Select an architecture for a bounded coordination task.
Module 2: Delegating work
- Coordinator-worker patterns
- Delegation
- Parallel agents
Practical outcome: Define independent work units and merge responsibilities.
Module 3: Agent lifecycle
- Agent communication
- Long-running agents
- Always-on agents
Practical outcome: Specify message, timeout, and supervision rules.
Practical exercise
- Build or simulate a coordinator-worker flow and test a failed worker recovery path.
How we train
Contact us for full course details, including duration, delivery options and lab requirements.
Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.
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