My vibe-coded investment portfolio tracker
Can AI really replace developers? I put this question to the ultimate test by building the same investment portfolio tracker across 6 different AI coding platforms. What I discovered will change how you think about AI-powered development.
đŻ The Challenge: One App, Six Platforms
I tasked each platform with building a comprehensive investment portfolio tracker with these exact requirements:
The Benchmark App:
Real-time data integration for Bitcoin, Ethereum, Nasdaq stocks, global equities, and ETFs
Interactive dashboard with account overview, 12-month performance tracking
Dual visualization via line charts (portfolio value over time) and pie charts (asset allocation)
Transaction management system with buy/sell functionality
Cash account integration with automatic balance updates
Complete transaction history in chronological order
Mobile-responsive design with modern dark theme
Each platform got the identical prompt. No technical specifications. No second chances.
đ The Results That Shocked Me
1st Place: Caffeine AI (7.7/10) đĽ
The dark horse that came out of nowhere! This platform absolutely nailed the user experience with fast generation, solid reliability and mostly functional app after the initial prompt.
Pros
Simple and easy-to-use interface
Entire app runs on blockchain which makes it more secure
All-in-one (persistent storage, authentication, one-click deployment)
Cons
Alpha version, not yet released to general public
Lacks some features (code editing/export, file upload)
UI design quality a bit behind competitors
2nd Place: Firebase Studio (7.2/10) đĽ
Google's offering brought moderate results after the initial prompt. A few features were working but needed more prompts to fix the remaining issues.
Pros
For beginners and advanced users
Full IDE support with Gemini models
Great customization and available features
Cons
More complex for beginners
3rd Place: v0 (6.3/10) đĽ
With Vercel's version, I needed three attempts and manual bug fixing to run the preview. UI quality is high but needs more work to make it fully functional.
Pros
Easy to use
Good app quality
Rich features (code export, database integrations, deployment on Vercel)
Cons
Very simple code editor
Slow code generation
4th Place: Replit (6.0/10)
The coding giant delivered solid fundamentals but lacked the polish for production-ready apps. After the initial prompt, none of the features worked but the app dashboard looked great.
Pros
Ease of use
Supported features (file uploads, prompt enhancer, deployment, database)
Great UI design in apps
Cons
Very slow code generation
Vendor lock in to Replit
None of the prompted features worked
5th Place: Lovable (5.5/10)
Despite the charming name, this platform struggled with prompt alignment and complex feature integration. Gave the simplest app version of the tested platforms.
Pros
Easy to use and has all the necessary features
Cons
Donât allow code edit or export in free version
Slow code generation and low app quality
Apps are always public in free mode
6th Place: Bolt.new (FAIL)
The platform that made me almost rage quit. Complete breakdown on core functionality - couldn't spin up the app.
No rating. Consumed all the tokens for the day without a visual result.
đ The Score Breakdown
Here's how each platform performed across critical developer metrics:
Metric | ||||||
|---|---|---|---|---|---|---|
Ease of Use | 8 | 6 | 7 | â | 7 | 9 |
Speed of Generation | 4 | 7 | 5 | â | 5 | 9 |
App Quality | 6 | 6 | 5 | â | 7 | 7 |
Supported Features | 7 | 9 | 7 | â | 7 | 6 |
Customization/Flexibility | 5 | 8 | 4 | â | 6 | 6 |
Scalability/Reliability | 6 | 7 | 5 | â | 6 | 9 |
Total Average | 6.0 | 7.2 | 5.5 | FAIL | 6.3 | 7.7 |
đĄ Key Takeaways
đš Features: Most platforms offer similar features, with Firebase Studio allowing editing the code in a web IDE.
đš The Reliability Gap: Security is nonexistent in most of the apps. Upgrading after its live is difficult without losing user data. Caffeine AI is a promising counterpart due to its decentralized architecture, integrated authentication system, and data persistence.
đš Great for Rapid Prototyping and MVPs: AI coding tools are rapidly evolving, but theyâre not ready to replace seasoned developers. However, theyâre powerful for rapid prototyping and MVP development.
More Resources
Blog: In-depth articles on AI workflows and practical strategies for growth
AI Tool Collection: Discover and compare validated AI solutions
Consultancy: Explore AI potential or make your team AI-fit
Agency: Production-ready AI implementation services
