AI Coding for Senior Engineers
Learn to operate AI coding agents as precision tools. This course teaches the systematic methodology behind achieving 10x productivity through agent orchestration—from mental models to practical techniques.
Understanding the Tools
Build the mental models to understand how AI agents work.
Introduction to AI Agent-Driven Development
Learn the fundamentals of operating AI agents for autonomous code execution - from understanding LLMs as token prediction engines to avoiding critical operator errors.
Understanding Agents
Learn how LLMs and agent frameworks work together to create autonomous coding agents - from the execution loop to context engineering.
Methodology
Learn the four-phase workflow for effective AI-assisted development.
Four-Phase Workflow
Master the Research → Plan → Execute → Validate workflow that transforms you from a craftsman into an operator who orchestrates AI agents effectively.
Prompting 101
Master the art of prompting AI coding assistants - from clear instruction-based prompting to personas and chain-of-thought techniques.
Grounding: Anchoring Agents in Reality
Learn how to inject reality into the context window through semantic search, sub-agents, and context management techniques.
Practical Techniques
Apply your knowledge with hands-on patterns for real-world tasks.
Project Onboarding
Learn how to codify project context in hierarchical, machine-readable files that transform AI agents from generic code generators into project-aware operators.
Planning & Execution
Learn active context engineering techniques for planning and execution - from grounding in code to evidence-based debugging and parallel agent workflows.
Tests as Guardrails
Learn how to use tests as constraints that prevent AI agents from breaking your system - from the three-context workflow to fast feedback loops.
Reviewing Code
Learn how to conduct effective code reviews of AI-generated code - from fresh context reviews to iterative refinement and PR optimization.
Debugging with AI Agents
Master evidence-based debugging with AI agents - from code inspection and log analysis to closed-loop debugging workflows.
Writing Agent-Friendly Code
Learn how to write code that AI agents can understand and extend - from co-locating constraints to preventing quality drift through strategic code review.
Unlock the Full Course
Sign up for free to access all 9 premium lessons, including methodology and practical techniques for AI-assisted development.