AI-Powered Development with Cursor & Claude Code

From code assistant to AI-native development workflow. This path teaches developers how to use AI tools as true development partners. Learn to design, build, and ship features faster, work effectively in both new and existing codebases, and apply AI in a way that scales across teams. 

By Andy Larkin · AWS APJ Community Hero of the Year 2024

Skill objectives

Chapter 01

Introduction

Welcome to the course. Get an overview of the learning path and what you will be able to do by the end.

Video2min

Course Introduction

Watch the course overview to understand the full learning path structure. 

Chapter 02

Why AI Changes Everything for Developers

Understand the real shift: how LLMs work, the exponential capability curve, and two complementary interaction styles.

Video7min

Why AI Changes Everything for Developers

Watch the video on what changed in AI-assisted development, context windows, agentic tools, and AI strengths and limitations. 

Chapter 03

The Core Skill: Thinking in Prompts

Master the transferable skill: structuring prompts with task, context, constraints, and examples. Learn the difference between prompt engineering and context engineering.

Video10min

The Core Skill: Thinking in Prompts

Watch the video on prompt anatomy, common anti-patterns, context windows, and the distinction between prompt engineering and context engineering. 

Chapter 04

Designing Your Product with AI

Use AI as a thinking and design tool before writing code. Brainstorm, generate mockups, iterate visually, and produce specs in minutes instead of days.

Video10min

Designing Your Product with AI

Watch the live demo: from problem clarification to working Kanban prototype using Claude for brainstorming, domain modeling, and visual mockups. 

Chapter 05

Getting Started with AI Development Tools

Get hands-on with both AI paradigms: Claude Code as an autonomous terminal agent, and Cursor as an AI pair programmer in the IDE.

Video31min

Getting Started with Cursor

Watch the comprehensive demo on Cursor: tab completion, inline editing, chat panel, Agent mode, Plan mode, .cursorrules, rollback, and cost management. 

Video5min

Getting Started with Claude Code

Watch the demo on Claude Code: the agentic loop, natural language prompts, slash commands, piping, and CLAUDE.md context files. 

Chapter 06

Choosing the Right Tool for the Job

Build the judgment layer: when to use Cursor, when to use Claude Code, when to use both, and when to stop using AI entirely.

Video12min

Choosing the Right Tool for the Job

Watch the side-by-side comparison: same feature in Cursor and Claude Code, with honest tradeoff analysis and the recommended combined workflow. 

Chapter 07

Building a Real Feature End-to-End

The flagship module: take a feature from spec to working code using Cursor or Claude Code. See real mistakes, debugging loops, and how they handle cross-file orchestration in a real codebase.

Video9min

Building a Real Feature End-to-End with Cursor

Watch the extended demo building the Sales Pipeline feature in Cursor, including owner assignment, sorting, and how to stay in control of the implementation. 

Video15min

Building a Real Feature End-to-End with Claude

Watch the extended demo building the Sales Pipeline feature with Claude Code, including implementation planning, rollback, prompt refinement, and orchestrating cross-file changes. 

Chapter 08

Working with Existing Codebases

The reality check: explore, understand, and safely modify codebases you did not write. Learn why AI struggles with implicit relationships and how to bridge the gap.

Video9min

Working with Existing Codebases

Watch the demo on The Atomic CRM: adding a feature to an unfamiliar codebase, backfill failures, ambiguity traps, and the explore-first workflow. 

Chapter 09

AI in Your Team's Workflow

Shift from individual productivity to team capability. Set up team context files, define safe change classes, measure impact, and avoid common adoption mistakes.

Video8min

AI in Your Team's Workflow

Watch the lecture on team-level AI adoption: Git integration, team standards as code, ownership zones, change briefs, and strategic takeaways. 

Chapter 10

Final Assessment

Put your knowledge to the test. Complete an interview with an Engineering Manager to demonstrate your understanding of AI-powered development tools and workflows.

Skills: Generative AI Tools, Generative AI

AI Simulation1hAssessment

AI Tools Adoption — Developer Interview

Discuss your understanding of AI-powered development tools with Alex, a senior Engineering Manager. Answer situational questions about configuring AI tools, reviewing AI-generated code, prototyping with AI, and working with legacy codebases. 