Cursor helps you write code 10x faster. But here’s the problem:...
Prajwal Tomar@PrajwalTomar_
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Mar 27, 2025
~2 min read
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Cursor helps you write code 10x faster.
But here’s the problem:
Fast code = fast bugs.
And when you’re pushing PRs daily, manual reviews quickly become the bottleneck.
Here’s how I’ve solved that using AI-powered code reviews ↓
But here’s the problem:
Fast code = fast bugs.
And when you’re pushing PRs daily, manual reviews quickly become the bottleneck.
Here’s how I’ve solved that using AI-powered code reviews ↓
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1/ I build MVPs fast.
Cursor, Supabase, Lovable the whole stack is built for speed.
But once you move this quickly:
• PRs stack up
• Review cycles lag
• Bugs creep in
And no matter how good AI gets, bad code still ships if you don’t review it properly.
Cursor, Supabase, Lovable the whole stack is built for speed.
But once you move this quickly:
• PRs stack up
• Review cycles lag
• Bugs creep in
And no matter how good AI gets, bad code still ships if you don’t review it properly.
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2/ I tried slowing down. Didn’t work.
So I switched to automating reviews without compromising on depth.
Now every PR gets:
• A clear summary
• File-by-file walkthrough
• Context-aware comments
• Suggested fixes I can apply or discuss
It feels like having a senior engineer on standby.
So I switched to automating reviews without compromising on depth.
Now every PR gets:
• A clear summary
• File-by-file walkthrough
• Context-aware comments
• Suggested fixes I can apply or discuss
It feels like having a senior engineer on standby.
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3/ I’d been looking for a review tool that could actually keep up.
Most tools I tried were either too noisy or felt disconnected from the codebase.
After testing a bunch, I landed on @coderabbitai and it’s been the most balanced so far.
It doesn’t just run a single LLM. It layers in linters like ESLint and Ruff, security checks, and even data from tools like Sonar and Codacy.
The result?
Less noise. Smarter suggestions. And reviews that feel like they understand what you’re building.
Most tools I tried were either too noisy or felt disconnected from the codebase.
After testing a bunch, I landed on @coderabbitai and it’s been the most balanced so far.
It doesn’t just run a single LLM. It layers in linters like ESLint and Ruff, security checks, and even data from tools like Sonar and Codacy.
The result?
Less noise. Smarter suggestions. And reviews that feel like they understand what you’re building.
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4/ I can also chat with it directly inside the PR.
If I disagree, I explain and it responds, updates its logic, or searches the web for clarification.
The review becomes a conversation not a wall of generic comments.
If I disagree, I explain and it responds, updates its logic, or searches the web for clarification.
The review becomes a conversation not a wall of generic comments.
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5/ It’s smart enough to learn over time.
Every suggestion I accept or reject helps it improve.
It adapts to my coding style, my stack, and the way my team works.
That learning loop is what makes it truly valuable.
Every suggestion I accept or reject helps it improve.
It adapts to my coding style, my stack, and the way my team works.
That learning loop is what makes it truly valuable.
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6/ Bonus:
It generates missing API docs, and even unit tests with one prompt.
All packaged as separate PRs so nothing gets lost in the noise.
It even handles formatting and summaries, things I usually put off till later.
It generates missing API docs, and even unit tests with one prompt.
All packaged as separate PRs so nothing gets lost in the noise.
It even handles formatting and summaries, things I usually put off till later.
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7/ I also like how customizable it is.
I can switch review styles depending on the project. Chill for early builds, assertive for production code.
That flexibility is key when you’re working across different clients and teams.
I can switch review styles depending on the project. Chill for early builds, assertive for production code.
That flexibility is key when you’re working across different clients and teams.
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8/ If you’re using Cursor or any AI-first stack, this should be part of your flow.
When you generate more code, you need smarter reviews.
CodeRabbit keeps my quality high while letting me move fast.
When you generate more code, you need smarter reviews.
CodeRabbit keeps my quality high while letting me move fast.
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9/ I no longer need dedicated reviewers on every project.
We merge faster, ship better, and spend less time chasing bugs post-launch.
It’s the only reason I’m able to scale without sacrificing quality.
Bookmark this if you’re shipping fast with AI.
We merge faster, ship better, and spend less time chasing bugs post-launch.
It’s the only reason I’m able to scale without sacrificing quality.
Bookmark this if you’re shipping fast with AI.
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10/ Final thought:
AI helps you code faster.
But without a strong review layer, you’re just accelerating risk.
- Cursor to build.
- CodeRabbit to review.
That’s the system that helps me ship secure, scalable MVPs at speed.
AI helps you code faster.
But without a strong review layer, you’re just accelerating risk.
- Cursor to build.
- CodeRabbit to review.
That’s the system that helps me ship secure, scalable MVPs at speed.
