Neo Kim Profile picture
Aug 21, 2025 7 tweets 3 min read Read on X
I struggled to merge code until I learned the pull request workflow: Image
1. Merge Request
↳ Write code on a separate git branch to isolate changes.
↳ Get instant review and suggestions using the CodeRabbit VSCode extension.
↳ Commit code with a clear commit message and push it to the remote repository.
↳ Open a pull request from the current branch into the target branch.Image
2. Continuous Integration Pipeline
↳ Run automated checks on the code, such as unit tests and linting, to ensure code correctness.
↳ Tag one or more relevant team members to ask for review. Image
3. Code Review
↳ Get a summary of code changes, issues, and auto-fix suggestions using CodeRabbit.
↳ Reviewer checks the changed files and leaves constructive feedback. Image
4. Code Update
↳ Fix the code to address the review comments.
↳ Upload changes to the same pull request and make sure automated checks pass again.
↳ Reply to the reviewer's comments and resolve open discussions. Image
5. Continuous Deployment
↳ Reviewer approves the pull request.
↳ Pull request gets merged into the target branch and triggers continuous deployment.
↳ CD pipeline builds and deploys the change to the staging environment.
↳ Once the staging tests pass, the change gets released to production.Image
Remember, having more pairs of eyes is good for code reviews.

But code reviews shouldn't slow down the development process.

What else would you add? Image

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More from @systemdesignone

Jan 6
I struggled with GIT until I learned these 19 commands: Image
1 git add

↳ It lets you add changes from the working directory into the staging area.

2 git commit

↳ It lets you save a snapshot of currently staged changes in the local repository, with a message. Image
3 git push

↳ It lets you upload commited changes from the local repository to a remote repository.

4 git fetch

↳ It lets you download changes from a remote repository, without applying them locally. Image
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Nov 27, 2025
I stopped wasting time testing AI tools that didn’t fit, so I built my own in minutes on OnSpace.

An AI Cars Tuning Studio.

Whatever ultra-specific function you want, you can create it exactly the way you imagine. Image
Image
Instead of wasting hours searching, testing, and getting paywalled, you can create the exact tool you want on OnSpace.

(Tailored to your needs and problem.)
The Cars Tuning Studio I created is a good example.

I needed a tool that could generate variations, visual tuning ideas, and custom designs fast… so I made one. And it works exactly how I want.
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• They use a microservices architecture to build S3

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• They store metadata in a key-value database and cache it for high availability

• They store data on mechanical hard disks to save costs

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