“This course contains the use of artificial intelligence”

Build real AI-powered developer systems—not just prompts.

This hands-on course teaches you how to design, build, and deploy Claude-powered coding agents that go far beyond basic autocomplete or chat-based coding. Instead of treating AI as a tool you “talk to,” you’ll learn how to engineer structured AI workflows that can generate code, run tests, debug issues, write documentation, and support real-world development processes.

The course begins by shifting your mindset from simple prompting to AI system design. You’ll understand what makes Claude uniquely powerful for coding—its reasoning ability, long context handling, and structured outputs—and how to leverage those strengths to build reliable workflows. You’ll learn how to transform messy requirements into precise instructions, design effective system prompts, and create repeatable development loops like Spec → Code → Test → Iterate.

From there, you’ll move into building agentic coding systems. You’ll integrate Claude with tools such as file systems, APIs, and code execution environments to create multi-step agents that can plan, act, and improve their own outputs. You’ll implement patterns like ReAct (Reason + Act) and Plan-and-Execute, and build reusable developer copilots that can automate tasks like debugging, refactoring, pull request generation, and documentation.

The course goes beyond demos and into production-ready AI engineering. You’ll learn how to design systems that are reliable and safe, including how to implement evaluation pipelines using LLM-as-a-judge, create test-driven AI workflows, and add guardrails to prevent hallucinations and enforce output quality. You’ll also explore observability, logging, and performance optimization so your systems can scale beyond experiments.

Throughout the course, you’ll complete hands-on labs where you build real systems, including:

A Claude-powered coding assistant
A GitHub pull request generator
A bug-fixing agent with tool usage
A documentation automation system

Finally, you’ll bring everything together in a capstone project, where you design and build a complete AI coding system from scratch. You’ll define a real developer problem, build an agent that generates and tests code, integrate evaluation and guardrails, and present your system with architecture, demo, and business impact. This becomes a portfolio-ready project that demonstrates true AI engineering capability.

This course is designed for developers who want to move beyond tutorials and build real AI systems that deliver value. By the end, you won’t just know how to use AI—you’ll know how to engineer it into your workflow, your products, and your career.