AI Coding for Real Engineers by Matt Pocock

AI Coding for Real Engineers by Matt Pocock

AI Coding for Real Engineers by Matt Pocock is an advanced developer training program designed to help software engineers integrate AI coding assistants like Claude Code into real-world production workflows. Rather than focusing on “vibe coding” or blindly delegating work to AI, this course teaches a structured engineering approach that combines human judgment, software architecture, planning, testing, and automation to build high-quality software faster and more reliably.

Built around practical workflows used in production environments, the course shows developers how to manage AI agents, create effective planning systems, implement feedback loops, automate development tasks, and maintain code quality while leveraging modern AI tools.

What You’ll Learn

Inside AI Coding for Real Engineers, you’ll learn how to:

• Use Claude Code effectively in production environments
• Build reliable AI-assisted development workflows
• Manage large codebases with AI agents
• Create engineering-focused planning systems
• Write effective PRDs and implementation plans
• Build feedback loops that improve code quality
• Use custom AI skills and agent steering
• Implement human-in-the-loop development workflows
• Run autonomous AFK coding agents safely
• Design AI-friendly software architectures
• Reduce technical debt while increasing productivity
• Balance automation with engineering judgment

What’s Included

This program includes:

• Claude Code Fundamentals
• AI-Assisted Engineering Workflows
• Context Management Systems
• AGENTS.md Implementation Framework
• Custom Skills Development
• PRD & Planning Frameworks
• Multi-Phase Project Execution
• Feedback Loop Systems
• Human-in-the-Loop Processes
• AFK Agent Automation
• Research & Prototyping Workflows
• Office Hours Recordings
• Community Access
• Course Repository
• Lifetime Access

Complete Course Breakdown

Module 1: Getting Started with Claude Code

Build a solid foundation before implementing advanced workflows.

Topics include:

• Claude Code Overview
• Session Management
• Terminal Prompting
• IDE Integration
• Version Navigation
• Running Bash Commands
• Permission Systems

Learn how Claude Code operates and how to use it effectively inside real projects.

Module 2: Understanding AI Engineering Fundamentals

Learn the principles behind effective AI-assisted development.

Topics include:

The Constraints of LLMs

Understand limitations and strengths.

Context Window Management

Keep AI operating efficiently.

Subagents

Delegate work while maintaining context.

Codebase Exploration

Navigate large projects effectively.

Non-Deterministic Outputs

Manage AI unpredictability.

Explore → Build → Clear Loop

Create repeatable development workflows.

This module establishes the engineering mindset required to work successfully with AI tools.

Module 3: Agent Steering & Control

Learn how to guide AI agents effectively.

Topics include:

AGENTS.md Files

Create project-specific guidance systems.

Progressive Disclosure

Reduce token waste while improving results.

Agent Skills

Build reusable workflows.

Automatic Memory Systems

Maintain long-term project context.

Custom Instructions

Teach agents how your team works.

You’ll learn how to transform AI from a generic assistant into a specialized engineering partner.

Module 4: Planning Large Projects

Master AI-assisted project planning.

Topics include:

Writing Effective PRDs

Generate high-quality project requirements.

Feature Decomposition

Break large projects into manageable tasks.

Multi-Phase Planning

Execute projects beyond a single context window.

Tracer Bullets

Validate architecture before committing to full implementation.

Execution Strategies

Move efficiently from planning to production.

This section focuses on engineering decisions rather than simple code generation.

Module 5: Feedback Loops & Quality Control

Learn how to build trustworthy AI workflows.

Topics include:

Feedback Loop Design

Create self-correcting systems.

Test-Driven Agent Workflows

Improve reliability through testing.

Red-Green-Refactor

Adapt classic software practices for AI development.

Pre-Commit Validation

Catch issues before they enter production.

Quality Assurance Skills

Automate code review processes.

These systems help ensure AI-generated code meets production standards.

Module 6: AFK Agents & Automation

Learn how to automate development safely.

Topics include:

AFK Agent Systems

Allow agents to work autonomously.

Sandboxing

Protect production environments.

GitHub Issue Automation

Connect agents directly to task backlogs.

Automated Branch Management

Create safer autonomous workflows.

Queue-Based Development

Allow agents to process tasks independently.

This module demonstrates how AI can become a true productivity multiplier without sacrificing quality.

Module 7: Human-in-the-Loop Engineering

Balance automation with human oversight.

Topics include:

HITL Workflows

Maintain control over critical decisions.

Research Systems

Use AI for investigation and discovery.

Prototyping

Rapidly test ideas before implementation.

Kanban-Based Planning

Replace rigid planning with adaptive workflows.

AI-Friendly Architecture

Design codebases that agents can understand.

Learn when to automate and when human judgment remains essential.

Core Engineering Skills Covered

The course emphasizes skills that remain valuable regardless of AI tool changes:

• Communication
• Anticipation
• Planning
• Task Decomposition
• Delegation
• System Design
• Quality Assurance
• Parallelization
• Software Architecture
• Engineering Judgment

These skills are presented as the foundation of successful AI-assisted software development.

What Makes This Course Different

Most AI coding courses focus on generating code quickly.

AI Coding for Real Engineers focuses on:

Engineering → Planning → Steering → Feedback Loops → Automation → Quality Assurance

This approach teaches developers how to use AI responsibly while maintaining professional software engineering standards.

Key Benefits

• ✅ Learn Claude Code from a production engineering perspective
• ✅ Build scalable AI-assisted workflows
• ✅ Improve code quality with automation
• ✅ Reduce technical debt
• ✅ Master planning and architecture systems
• ✅ Implement autonomous AI agents safely
• ✅ Create reusable AI skills and workflows
• ✅ Learn modern engineering practices
• ✅ Access recordings and community support
• ✅ Lifetime access to all materials

Who This Course Is For

This course is ideal for:

• Software Engineers
• Full-Stack Developers
• TypeScript Developers
• Senior Engineers
• Technical Leads
• Engineering Managers
• SaaS Developers
• AI-Assisted Developers
• Startup Engineers
• Anyone using AI coding tools professionally

About Matt Pocock

Matt Pocock is a highly respected software educator and TypeScript expert known for making complex engineering concepts easy to understand. Through his courses, workshops, and educational content, he has helped thousands of developers improve their software engineering skills and modern development workflows.

Final Thoughts

Matt Pocock – AI Coding for Real Engineers provides a practical framework for integrating AI coding assistants into professional software development. By combining timeless engineering principles with modern AI workflows, the course helps developers build faster, maintain quality, reduce technical debt, and create reliable, scalable systems.

Get Matt Pocock – AI Coding for Real Engineers today.

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