I Tested 7 AI Coding Tools for a Week. The Results Shocked Me.

Last Monday, I made a decision that would change how I think about coding forever. I was going to spend one week building the same project using seven different AI coding tools, tracking everything: time spent, bugs created, lines of code written, and most importantly, how frustrated I got.

The project? A simple but real todo app with user authentication, real-time sync, and a clean interface. Nothing fancy, but it needed to actually work.

Here's what I discovered after 40+ hours of testing, and why the "winner" completely surprised me.

The Challenge I Set Myself

I'm a developer with 8 years of experience, mostly in React and Node.js. I've been skeptical of AI coding tools—they felt like fancy autocomplete that got in my way more than helped.

But after watching my junior developer colleague ship features faster than me using Cursor, I had to know: Are these tools actually worth it?

The rules I set:

• Same project for each tool
• Track time from setup to deployment
• Count bugs and how long they took to fix
• Rate the "developer experience" honestly
• No cherry-picking—use whatever the tool suggests

Tool #1: GitHub Copilot ($10/month)

The expectation: The OG AI coding assistant. Should be solid.

The reality: It felt like having a really smart intern who sometimes gives great suggestions and sometimes suggests completely wrong things.

What worked:

• Excellent at completing boilerplate code
• Great for writing tests (seriously, this was impressive)
• Integrated seamlessly with VS Code

What didn't:

• Suggestions often didn't match my project's patterns
• No understanding of my overall architecture
• I spent time reviewing and rejecting suggestions

Time to working app: 6 hours, 23 minutes Bugs created: 4 (mostly authentication edge cases) Frustration level: 3/10 (pretty smooth)

Tool #2: Cursor ($20/month)

The expectation: The new hotness. Everyone's talking about it.

The reality: This is what I thought AI coding would feel like. It's not just autocomplete—it's like pair programming with someone who actually understands your codebase.

What worked:

• The chat interface is incredible—I could ask "add error handling to the login function" and it just worked
• Understood my project structure and maintained consistency
• The "apply" feature let me review changes before accepting them

What didn't:

• Sometimes suggested overly complex solutions
• Required good prompting skills to get the best results
• Occasional hallucinations about APIs that don't exist

Time to working app: 4 hours, 12 minutes Bugs created: 2 (both minor CSS issues) Frustration level: 2/10 (genuinely enjoyable)

Tool #3: OtterAI ($19-49/month)

The expectation: Never heard of it before this test. Let's see what it can do.

The reality: Holy shit. This isn't just a coding assistant—it's like having an entire development team in your browser.

What worked:

• I literally just described what I wanted: "Build a todo app with user accounts and real-time sync"
• It generated the entire application structure, frontend, backend, database schema, everything
• No setup required—everything runs in the browser
• One-click deployment that actually worked

What didn't:

• Less control over the specific implementation details
• Sometimes the generated code style didn't match my preferences
• Required describing requirements clearly (though this might be a good thing)

Time to working app: 47 minutes (I'm not kidding) Bugs created: 0 (it just worked) Frustration level: 0/10 (I was actually laughing at how fast it was)

Tool #4: Tabnine ($12/month)

The expectation: The veteran AI coding tool. Should be reliable.

The reality: Solid but unremarkable. Like a more advanced version of traditional autocomplete.

What worked:

• Very fast suggestions
• Good language support
• Didn't get in my way

What didn't:

• Suggestions felt generic
• No understanding of project context
• Basically just fancy autocomplete

Time to working app: 7 hours, 45 minutes Bugs created: 5 (standard development bugs) Frustration level: 4/10 (felt like regular coding)

Tool #5: Claude Sonnet 4.5 (via API, ~$15/month usage)

The expectation: Anthropic's latest model. Should be smart.

The reality: Incredibly intelligent but required a lot of back-and-forth.

What worked:

• Excellent at explaining complex concepts
• Great at debugging when I described the problem
• Very good at code review and suggestions

What didn't:

• No direct IDE integration (had to copy/paste)
• Couldn't see my full project context
• Felt more like consulting than coding

Time to working app: 5 hours, 30 minutes Bugs created: 3 (caught most issues during review) Frustration level: 3/10 (smart but tedious)

Tool #6: Bolt.new (Free)

The expectation: StackBlitz's AI tool. Should be good for quick prototypes.

The reality: Great for demos, but struggled with real applications.

What worked:

• Incredibly fast for simple projects
• Great for prototyping and sharing ideas
• No setup required

What didn't:

• Limited customization options
• Struggled with complex authentication
• Deployment options were limited

Time to working app: 2 hours, 15 minutes (but limited functionality) Bugs created: 1 (authentication didn't work properly) Frustration level: 2/10 (fun but limited)

Tool #7: Traditional Coding (No AI)

The expectation: My usual workflow. Should be familiar and reliable.

The reality: Felt like driving a horse and buggy after testing sports cars.

What worked:

• Complete control over every line of code
• No surprises or unexpected behavior
• Familiar debugging process

What didn't:

• So. Much. Boilerplate.
• Spent 2 hours just setting up authentication
• Every small feature required significant time

Time to working app: 12 hours, 30 minutes Bugs created: 6 (the usual suspects) Frustration level: 6/10 (tedious and slow)

The Results That Shocked Me

Here's what I expected: Cursor would win because everyone's talking about it, GitHub Copilot would be solid, and everything else would be mediocre.

Here's what actually happened:

Speed Winner: OtterAI (47 minutes)

I'm still processing this. I described what I wanted in plain English, and 47 minutes later I had a fully functional app deployed to the internet. This isn't just faster—it's a completely different category of fast.

Developer Experience Winner: Cursor (4h 12m)

If you want to actually code but with superpowers, Cursor is incredible. It felt like pair programming with the smartest developer I've ever worked with.

Value Winner: GitHub Copilot (6h 23m, $10/month)

For traditional development with AI assistance, Copilot offers the best bang for your buck. It's not revolutionary, but it's solid and affordable.

Biggest Surprise: Traditional coding took 12.5 hours

I knew AI tools were faster, but I didn't realize how much time I was spending on boilerplate and setup. Going back to traditional coding felt like writing with a quill pen.

What This Actually Means for You

After this experiment, I've completely changed how I think about AI coding tools. Here's my honest take:

If you're building MVPs or prototypes:

Use OtterAI. The speed is unreal. I can test business ideas in under an hour instead of spending weekends building them.

If you're a professional developer:

Use Cursor. It makes you a better, faster developer without taking away the parts of coding you actually enjoy.

If you're just getting started:

Start with GitHub Copilot. It's affordable, well-integrated, and will teach you good patterns while helping you code.

If you're skeptical about AI tools:

I was too. Try Cursor for a week. If you don't see a significant productivity boost, I'll be shocked.

The Uncomfortable Truth

Here's what I realized during this experiment: The question isn't "Should I use AI coding tools?" anymore. It's "Which AI coding tool should I use?"

Because in 2025, coding without AI assistance feels like:

• Writing emails without spell check
• Doing math without a calculator
• Navigating without GPS

It's technically possible, but why would you?

What I'm Actually Using Now

After this experiment, I've settled into a hybrid approach:

• OtterAI for rapid prototyping - When I want to test an idea quickly
• Cursor for serious development - When I'm building production applications
• GitHub Copilot as backup - When I'm in VS Code for other reasons

The traditional "no AI" approach? I honestly can't see myself going back.

Your Turn

I'm curious about your experience with AI coding tools. Have you tried any of these? What surprised you?

More importantly: If you're still coding without AI assistance, what's holding you back? After this experiment, I genuinely can't think of a good reason not to at least try one of these tools.

The future of coding is here. And it's faster, smarter, and more fun than I expected.

---

Want to try these tools yourself? Here are the links:

• OtterAI - Free trial, no setup required
• Cursor - 14-day free trial
• GitHub Copilot - 30-day free trial
• Tabnine - Free tier available
• Bolt.new - Completely free