Engineering knowledge, not course content

Master the CLI, workflows, and core patterns

Understanding agents, delegation, and orchestration

Optimizing context windows and token efficiency

Creating effective project instructions and memory

Writing executable specifications for agents

Creating reusable skills and specialized subagents

Pre/post tool hooks, automation, and guardrails

Model Context Protocol servers and custom tools

Coordinating multiple agents for complex tasks

Git worktrees, parallel branches, and merge strategies

Unit, integration, and E2E tests as agent constraints

Automated review pipelines and quality gates

Isolation, permissions, and vulnerability prevention

Container-based execution environments

Pipelines that verify AI-generated changes

Introducing agents to existing codebases

Observability, tracing, and incident response

Token budgeting and retrieval strategies

Minimizing waste, maximizing value per token

Designing products around agent capabilities

From spec to shipped feature with agents

Rapid prototyping, iteration, and scaling with agents