AI Coding for Real Engineers by Matt Pocock is an advanced AI-assisted software engineering program designed for developers who want to move beyond simple AI code generation and learn how to build, manage, and scale real-world software projects using Claude Code, AI agents, workflows, planning systems, and modern engineering practices.
Unlike beginner AI coding courses that focus on prompts and shortcuts, this program teaches developers how to integrate AI into professional software development workflows, allowing them to build features faster, manage complex codebases, automate engineering tasks, and collaborate effectively with AI agents.
Built around practical implementation, real engineering scenarios, and production-level development systems, the course provides a complete framework for using AI as a true software engineering partner.
What’s Included
Inside AI Coding for Real Engineers, you’ll get access to:
- Complete Claude Code Engineering System
- Repository Setup Frameworks
- AI Development Workflows
- Agent-Based Engineering Systems
- Plan Execute Clear Methodology
- Context Engineering Frameworks
- Multi-Agent Development Systems
- PRD Creation Frameworks
- Codebase Exploration Systems
- Research & Prototyping Workflows
- GitHub Integration Training
- Kanban & Project Management Systems
- AI Skills & Automation Frameworks
- Office Hours Recordings
- Code & Materials Resources
What You’ll Learn
By completing this program, you’ll learn how to:
- Set up Claude Code for professional development
- Build and manage AI-assisted coding workflows
- Use AI agents to execute development tasks
- Navigate large codebases efficiently
- Create better Product Requirement Documents (PRDs)
- Build features using structured AI planning systems
- Automate repetitive engineering work
- Implement multi-agent development processes
- Manage GitHub-based AI workflows
- Scale software projects using AI engineering practices
Complete Course Breakdown
Module 1 – Claude Code Foundations
Build a strong foundation for AI-assisted software engineering.
Topics include:
- Repository setup
- Claude Code configuration
- Development environments
- Engineering workflow foundations
- Terminal-based AI interaction
Module 2 – Context Engineering
Learn how to provide AI systems with the context required for high-quality development output.
Topics include:
- Context management
- IDE integration
- Session management
- Constraint handling
- Effective AI communication
Module 3 – Codebase Exploration
Understand large projects quickly using AI.
Learn:
- Repository navigation
- Architecture analysis
- Dependency discovery
- System understanding
- AI-assisted code investigation
Module 4 – Agent-Based Development
Discover how AI agents can perform engineering tasks autonomously.
Topics include:
- Subagents
- Agent workflows
- Task delegation
- Multi-agent collaboration
- Agent orchestration systems
Module 5 – Plan Execute Clear Framework
Master one of the core engineering methodologies taught inside the program.
You’ll learn:
- Planning systems
- Execution workflows
- Validation processes
- Iterative development
- Task completion frameworks
Module 6 – Agent Skills & Memory Systems
Build reusable AI capabilities.
Topics include:
- Agent skills creation
- Writing skills
- Memory systems
- Knowledge retention
- Skill-based automation
Module 7 – Product Requirements & Planning
Learn how to create engineering documentation AI can execute effectively.
Inside this module:
- PRD generation
- Feature planning
- Multi-phase roadmaps
- Tracer bullet methodology
- Technical documentation systems
Module 8 – Advanced AI Engineering Workflows
Implement advanced software development frameworks.
Topics include:
- Progressive disclosure
- Multi-context planning
- Validation loops
- Feedback systems
- Development automation
Module 9 – Refactoring & Code Quality
Improve software quality using AI-assisted development.
Learn:
- Red-Green Refactoring
- Code cleanup
- Architecture improvements
- Maintainability frameworks
- Technical debt reduction
Module 10 – GitHub & Project Automation
Build automated engineering pipelines.
Topics include:
- GitHub Issues integration
- Backlog management
- Task automation
- AI project execution
- Workflow orchestration
Module 11 – Research & Prototyping
Use AI to accelerate product development.
Learn:
- Technical research
- Rapid prototyping
- Feature validation
- Experimentation workflows
- Product exploration systems
Module 12 – Designing AI-Friendly Codebases
Create systems that work effectively with AI.
Topics include:
- Modular architectures
- Context-aware development
- AI-readable code structures
- Maintainable project organization
- Engineering best practices
Why This Course Stands Out
Most AI coding courses focus on:
- Prompt engineering
- Simple code generation
- Beginner automation
AI Coding for Real Engineers focuses on:
- Real software engineering
- Production-level workflows
- AI agent orchestration
- Codebase management
- Development automation
- Team-scale engineering systems
The result is a practical framework that helps developers build faster while maintaining professional engineering standards.
Key Benefits
- Accelerate software development
- Improve code quality
- Reduce repetitive engineering work
- Build scalable AI workflows
- Learn professional AI engineering systems
- Master Claude Code effectively
- Automate development processes
- Improve project planning and execution
- Work more efficiently with large codebases
Who This Course Is For
- Software Engineers
- Full-Stack Developers
- Backend Developers
- Frontend Developers
- Engineering Managers
- Technical Founders
- SaaS Builders
- AI Developers
- Product Engineers
- Advanced Programmers
About Matt Pocock
Matt Pocock is widely recognized as one of the leading educators in modern software development, TypeScript, and developer tooling. Through practical teaching and real-world engineering frameworks, he helps developers build production-ready systems using modern technologies and workflows.
Why You’ll Love AI Coding for Real Engineers
- Real engineering workflows
- Practical Claude Code implementation
- Agent-based development systems
- Production-focused training
- Modern software engineering practices
- GitHub and automation integration
- Scalable AI workflows
- Advanced developer strategies
Final Thoughts
AI Coding for Real Engineers – Matt Pocock is a comprehensive AI engineering program designed for developers who want to leverage Claude Code, AI agents, automation systems, and structured engineering workflows to build software more effectively.
By combining context engineering, agent orchestration, planning frameworks, GitHub automation, codebase management, and advanced development systems, this program provides a complete roadmap for integrating AI into professional software engineering.
If you’re serious about becoming a high-performance developer in the AI era, this course offers one of the most practical and advanced frameworks available today.
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