Building a Multi-Skill AI Agent
Hands-on guide to building an AI agent with multiple skills — architecture, tool design, orchestration, error handling, and a capstone research agent project.
Start Module 01Curriculum
A structured path through the course content.
Agent Architecture Foundations
What multi-skill agents are, the skill abstraction, the runtime loop, and framework selection.
Defining Skills as Tools
Tool schema design, input validation, output contracts, and building retrieval and action skills.
The Reasoning Core
System prompts, skill selection logic, chain-of-thought reasoning, and termination conditions.
State & Memory Across Steps
Working memory, structured state, context window management, and persistent memory.
Task Decomposition & Planning
Breaking tasks into steps, plan-then-execute, adaptive replanning, and dependency graphs.
Skill Orchestration Patterns
Sequential chains, parallel execution, conditional branching, supervisor pattern, and human-in-the-loop.
Error Handling & Recovery
Error taxonomy, retry strategies, graceful degradation, and self-correction.
Testing Multi-Skill Agents
Unit testing skills, integration testing chains, evaluation suites, and regression testing.
Production Deployment
Cost optimization, latency budgets, observability, and scaling agent workloads.
Capstone: Build a Research Agent
End-to-end project — designing, implementing, wiring, and iterating on a multi-skill research agent.