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.
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.
Course Content
- Introduction to OpenAI Codex –> 1 lecture • 14min.
- Installation of OpenAI Codex –> 1 lecture • 29min.
- Context Management in Codex –> 1 lecture • 20min.
- Codex Use Cases –> 1 lecture • 17min.
- Best Practices for Developers –> 1 lecture • 16min.
- Git Flow Integration –> 2 lectures • 57min.
Requirements
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.