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Beginner Artificial Intelligence 10 hours Featured

Real-World AI Coding with Dibe: The Tool-Agnostic Workflow for Professional Developers

Master the Practical, Repeatable Process for Using Any AI Coding Tool — Copilot, Claude Code, Cursor, Codex, Cline, and More — on Real Codebases

8 Chapters
34 Lessons
500 min total
Open Access

## Make AI Coding Predictable, Reliable, and Genuinely Productive AI tools can dramatically accelerate software development — but only if you use them the right way. Most AI coding tutorials show magical demos: an app...

What you'll learn

  • Foundations of AI-Assisted Development
  • Define — Scoping Work for AI Success
  • Context Engineering — Feeding AI the Right Information
  • The Dibe Coding Process in Practice
  • Review and Refine — Making AI Code Production-Ready
  • Team Workflows — Scaling AI Coding Across Engineering Teams

+ 2 more chapters below

Engr Mejba Ahmed

Engr. Mejba Ahmed

Course Instructor

Real-World AI Coding with Dibe: The Tool-Agnostic Workflow for Professional Developers

About This Course

Make AI Coding Predictable, Reliable, and Genuinely Productive

AI tools can dramatically accelerate software development — but only if you use them the right way.

Most AI coding tutorials show magical demos: an app generated from one prompt, or a tool that seems to "just work." In real engineering work, these examples rarely hold up.

Projects are complex. Requirements shift. Codebases carry deep, implicit knowledge. If you rely on trial-and-error prompting, output becomes inconsistent, unpredictable, and hard to trust.

This course fixes that.

It is practical and applied: you will learn a step-by-step workflow you can immediately use in real codebases and real tasks — not theory, not hype, not academic abstractions.

You will learn how to collaborate effectively with any AI coding tool — Copilot, Claude Code, Cursor, Codex, Cline, Windsurf, Theia IDE, and others — using a tool-agnostic workflow built for professional software development.

This structured approach is called the Dibe Coding methodology: a practical, repeatable process for getting consistent, high-quality results from AI. Built on real projects. Refined with enterprise engineering teams. Proven to work.

What You Will Learn

  • Work effectively with any AI coding tool (Copilot, Claude Code, Codex, Cline, Cursor, Windsurf, Theia IDE, and more)
  • AI for professional software development on existing codebases where quality matters
  • How to structure your AI coding workflow for consistent, high-quality results
  • When and how to use techniques like context engineering and task engineering
  • Practical follow-up actions to efficiently refine AI-generated code
  • How teams can collaborate and share common AI workflows

What You Will Be Able to Do After This Course

  • Use AI coding with intention and structure, not guesswork
  • Decide when and how AI should help
  • Provide the right context for accurate results
  • Break down tasks into AI-friendly steps
  • Apply a repeatable workflow for reliable output
  • Review and refine AI results quickly
  • Integrate AI into existing, complex codebases
  • Use any AI coding tool more effectively and confidently

What Is Included

  • 34 step-by-step lessons with real coding demos
  • A complete workflow you can use immediately
  • Real-world examples from complex codebases
  • A fully tool-agnostic approach that works with any AI tool
  • Additional tool-specific deep dives for Copilot, Claude Code, Cursor, and Codex
  • Templates, checklists, and practical exercises

Who This Course Is For

  • Developers who want consistent, reliable results from AI
  • Engineers working in real-world, production codebases
  • Tech leads adopting AI tools on their teams
  • Anyone looking for a practical, professional approach to AI-assisted development

Everything taught is practical, tool-agnostic, and ready to apply immediately. Start mastering AI coding today.

Course Curriculum

8 chapters 34 lessons 500 min

2 lessons available to preview

3 Why AI Coding Fails — The Root Causes
14min
4 Introducing the Dibe Coding Methodology
18min
1 Task Engineering — The Skill That 10x Your AI Results
16min
2 Scope Decomposition — Breaking Big Features into AI-Friendly Tasks
15min
3 Writing Specifications That AI Tools Understand
14min
4 Defining Quality Gates Before You Start
12min
1 What Is Context Engineering and Why It Matters
14min
2 Project Context — Teaching AI Your Codebase
16min
3 Task Context — Giving AI Exactly What It Needs
15min
4 Avoiding Context Overload and Token Waste
12min
1 The Coding Example — Setting Up Our Real-World Project
12min
2 Define — Writing the Brief and First Prompt
16min
3 First Review and Decide — Evaluating Initial AI Output
14min
4 Second Review and Decide — Iterating with Precision
13min
5 Third and Fourth Review Cycles — Convergence
12min
6 Final Prompt, Final Review, and Shipping
14min
1 The Art of AI Code Review
16min
2 Refining AI Output — Effective Feedback Patterns
14min
3 Testing AI-Generated Code — Strategies and Tools
15min
4 Handling Technical Debt from AI Code
13min
1 Standardizing AI Workflows Across a Team
15min
2 Shared Context and Knowledge Management
14min
3 Code Review Policies for AI-Generated Code
13min
4 Measuring AI Coding Productivity — Metrics That Matter
12min
1 Dibe Coding with GitHub Copilot
18min
2 Dibe Coding with Claude Code
20min
3 Dibe Coding with Cursor
16min
4 Dibe Coding with Codex, Cline, and Emerging Tools
15min
1 Level 4 Agent Mode — Deep Dive
20min
2 Integrating AI Coding into CI/CD Pipelines
16min
3 Security and Compliance in AI-Assisted Development
14min
4 The Future of AI Coding — Preparing for What's Coming
15min
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