Claude Code: Software Engineering with Generative AI Agents

О курсе

Master AI-Assisted Development with Claude Code: From Fear to 1000X Productivity Transform your software engineering practice by learning to work effectively with AI as your development partner. This comprehensive course takes you from initial skepticism about AI coding tools to confidently leveraging Claude Code for dramatic productivity gains. In just the first few lessons, you'll learn to have Claude Code build entire applications in minutes - complete with user interfaces, databases, and business logic. By the end of this course, you'll know how to orchestrate Claude Code working concurrently across multiple git branches, with parallel AI agents developing different features simultaneously and automatically integrating their work. This isn't about getting better autocomplete - it's about fundamentally changing how software gets built. You'll discover how to treat AI as scalable development labor, implement the "Best of N" pattern to generate multiple solution approaches, and establish robust quality assurance processes that ensure AI-generated code meets professional standards. The course covers essential skills like writing effective CLAUDE.md files for project context, creating reusable commands for common workflows, and managing parallel development streams with git worktrees and AI subagents. Through hands-on exercises and real-world examples, you'll learn to overcome the common fears engineers have about AI tools while building practical systems for code evaluation, documentation generation, and feature development. By the end, you'll have a complete toolkit for scaling your development capabilities and a personalized process that fits your workflow. What You'll Learn: - Break free from micromanaging Claude Code and start delegating like a tech lead managing a team of senior developers - Write "big prompts" that get Claude Code building entire features instead of generating single functions you copy-paste - Use the "Best of N" pattern with Claude Code to generate 3-5 versions of every feature and cherry-pick the best parts or versions - Teach Claude Code to critique its own code using contextual rubrics that catch bugs before you ever see them - Master CLAUDE.md files that turn onboarding into autopilot - give Claude Code perfect project context so it writes code that fits your architecture from day one - Build Claude Code command libraries that compress complex development workflows into single prompts (code reviews, feature builds, testing suites) - Train Claude Code through examples so it writes code that matches your team's style without 100-page style guides - Orchestrate parallel feature development with Claude Code working multiple git branches simultaneously while you focus on architecture - Design codebases that scale with AI labor - understand token limits and architect projects for maximum Claude Code efficiency - Deploy Claude Code subagents that work independently on different features in parallel and then have Claude Code perform the merging and integration when they are done - Build your personal AI-first development process that multiplies your output while maintaining code quality - Use multimodal prompting to turn cocktail napkin sketches and whiteboard sessions into complete UI components, architectures, and processes in minutes Real Impact for Developers: - Cut feature development time from days to minutes - Never write boilerplate code again - Get comprehensive test suites written automatically - Have Claude Code handle code reviews and refactoring - Build multiple prototypes before committing to an approach - Scale your personal productivity like you hired a team Who This Is For: Software engineers, tech leads, and development teams ready to embrace AI-assisted coding while maintaining code quality and engineering best practices. Prerequisites: Basic software development experience and familiarity with version control (Git). This course requires a paid subscription that includes Claude Code.

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Dr. Jules White

Professor of Computer Science