Vibe coding was quite innovative, according to Codex.
Hasegawa from the Service Reliability Group (SRG) of the Media Management Division (@rarirureluis)is.
#SRGThe Service Reliability Group primarily provides comprehensive support for the infrastructure surrounding our media services, focusing on improving existing services, launching new ones, and contributing to open-source software (OSS).
This article is a report on my experience using vibe coding with Codex.
Introduction
In recent years, AI-powered development support tools have been attracting attention.
Among these, a new development style called "vibe coding" is attracting attention.
I have been using the Agent mode of Cursor, an AI code editor, for work purposes.
Recently, the OpenAI Codex became available within our team, so I tried using it to experiment with vibe coding.
This article explains what Vibe Coding is and describes my experience using Vibe Coding with the Codex.
What is vibe coding?
First, let me explain vibe coding.
Vibe coding is a programming paradigm proposed by computer scientist Andrej Karpathy.
This system works by having a programmer provide a few sentences of instructions (prompts) in natural language to a Large-Scale Language Model (LLM), which then generates the software.
In this approach, the programmer's role shifts from manually writing code to guiding, testing, and refining AI-generated source code.
According to IBM, the goal of vibe coding is to create an AI-powered development environment where AI makes suggestions in real time, automates tedious processes, and generates a standardized codebase structure.
This approach, which involves "writing the code first and refining it later," is said to align with agile principles such as rapid prototyping and iterative development.
Vibe coding in Codex
This time, I used OpenAI's Codex to experience vibe coding.
Codex is a cloud-based software engineering agent developed by OpenAI.
You can perform many tasks in parallel, such as feature development, answering questions about the codebase, fixing bugs, and proposing pull requests.
I don't think there's a clear difference from Cursor's Agent mode.
(Autonomously exploring the codebase, planning, and making complex codebase changes)
Incidentally, my Cursor Rule includes the following to ensure that the code is searched reliably:
I feel that the difference between having "Search related files if necessary" and not having it is quite significant.
What impressed me most about using Codex was how easy it was to create a pull request (PR) with just one click, without having to configure detailed special instructions like "Rules" in Cursor.
Cursor will not create pull requests using GitHub MCP unless explicitly instructed otherwise.
The changes we tried this time involved modifications to the sitemap.xml file of the English version of the portal site you are currently viewing.
All the code is written in Cursor Agent and almost entirely using vibe coding.
The details are as follows, and it's so complex that we would give up on implementing it without AI.
Instructions
While deliberately reviewing the code generated by vibe coding goes against the spirit of vibe coding, I did so for this article, and I think it's good code that's easy to read.
Although it wasn't mentioned in the instructions, it's great that they also updated the README.md file.
In most cases, this is not written for Cursors (it will be done if you have written the aforementioned Cursor Rule).
In conclusion
I personally found Vibe coding using the Codex to be "quite good" and a very innovative experience.
By having AI handle the majority of the coding, developers may be able to focus on higher-level design and problem-solving.
Of course, reviewing and testing AI-generated code is essential, but I felt that vibe coding is a powerful tool in the early stages of development and prototyping.
I hope that AI development support tools like Codex will continue to evolve, and that vibe coding will become a more common development style in the future.
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