Course Information
Course Overview
Build real-world apps faster using OpenAI Codex as your AI pair programmer, code reviewer, and development assistant
Vibecoding is not about copying AI-generated code — it’s about working with AI the same way real engineering teams work.
In this course, you’ll learn how to build applications using OpenAI Codex as a true AI pair programmer, not as a random code generator. You’ll understand how Codex thinks,
how it maintains context, and how to control it like a disciplined junior-to-mid level engineer inside your development workflow.
Unlike traditional ChatGPT usage, Codex is designed for real software development — it understands repositories, multi-file projects, diffs, constraints, tests, and Git-based workflows. This course teaches you how to use that power correctly.
You’ll learn in this course how to:
Implement features step-by-step
Refactor legacy code safely
Generate meaningful tests
Perform AI-assisted code reviews
Maintain clean architecture and boundaries
Avoid context loss and hallucinated logic
You’ll also master advanced prompting techniques used by professional developers — defining roles, constraints, ownership, deliverables, and commit-by-commit workflows.
By the end of this course, you won’t just “use AI for coding.”
You’ll think like an engineer who collaborates with AI effectively.
This course is practical, workflow-driven, and focused on real development scenarios — exactly how modern developers are starting to build software in 2026 and beyond with confidence and realtime exposure.
Course Content
- 6 section(s)
- 7 lecture(s)
- Section 1 Introduction to OpenAI Codex
- Section 2 Installation of OpenAI Codex
- Section 3 Context Management in Codex
- Section 4 Codex Use Cases
- Section 5 Best Practices for Developers
- Section 6 Git Flow Integration
What You’ll Learn
- Understand the correct mental model of OpenAI Codex, Difference between Codex and normal ChatGPT for coding, How Codex reasons across multiple files and repositories, Using Codex as an AI pair programmer and reviewer, Writing senior-level prompts with roles, constraints, and goals, Implementing features safely without breaking existing code, Generating clean unit and integration tests, Using Codex for refactoring legacy code step-by-step, Managing context effectively to prevent AI confusion, Using Codex in Git-based workflows (branches, diffs, PRs), Avoiding common AI coding mistakes developers make, Turning AI into a quality gate instead of a code spammer