Agent Engineering
Seven builds that take an agent from a single loop to a coordinated, gated, resumable system. Each part is a working instrument, not a diagram.
AIAI AgentsTool UseTask DecompositionSession ManagementProject
The curriculum
7 parts · read in order- 01
Published Agentic Loops: How an AI Actually Gets Things Done The gap between an AI that talks and an AI that does is a loop your program runs around the model. Here is that loop, built up one idea at a time and traced through a real support request, start to finish. - 02
Published Multi-Agent Orchestration: Building Reliable Hub-and-Spoke Agent Systems Split a hard job across several AI agents and it can get faster or it can get chaotic. The difference is a coordinator that owns the plan, controls what each agent sees, and checks whether the combined result actually answers the request. - 03
Published Subagent Invocation and Context Passing: Wiring a Coordinator to Its Subagents A good multi-agent system is not just the right subagents. It is a coordinator that can actually call them, and handoffs that carry every claim's origin with it. These are implementation problems, not theory problems. - 04
Published Workflow Enforcement and Handoff in AI Agent Systems A better prompt can make a mistake rarer. A gate in your code can make a specific mistake impossible. This project shows where each belongs, and builds a refund tool that refuses to run until its prerequisites are met. - 05 Coming soon Coming soon SDK hooks
- 06 Coming soon Coming soon Task decomposition
- 07 Coming soon Coming soon Session state