Comparison of AI Coding Tools
As you probably know I am a big advocate of emerging techs and I love to try new things. I am also lazy and I like to be as much efficient and productive with my time as possible 
Also, maybe because I saw the business of my father collapsing as he was not getting up to date with new technologies. Both my mom and my dad were COBOL developers.
My mom later had to become a teacher in Tech and my dad after opening his software development and education business had to close it. Both of my parents were one of the first ones to use and have PCs in my hometown, Santos.
In 2018, I participated in a Machine Learning Workshop where I created an iOS app that used AI to replace facial expressions with emojis and from that day until today I have worked in AI projects and now more than ever this is part of my daily routine.
I have seen this transition in tech happening 2 times before:
- One with my parents ages ago when they became obsolete and not competitive in the market
- Second when people were learning about Test Automation and loads of Testers stayed as manual QA.
“AI is your today’s competitive advantage”
| Tool | Code Export | Ease of Maintenance | Pricing | Key Features | Best For | Disadvantages |
|---|---|---|---|---|---|---|
| Lovable.dev | Yes | High | Free $20 / month $50 / month $100 / month | Text-to-web app generation, Supabase integration, Easy publishing | Quick prototyping, MVP validation | – Limited customisation after code generation. – May struggle with complex, domain-specific applications. |
| Replit | Yes | Medium | Free $20 / month | AI-powered code completion, Interactive AI chat, Complete app generation | Beginners, Educational purposes | – Produce generic solutions, requiring manual refinement. – Limited scalability for enterprise-grade projects. |
| Bolt.new | Yes | High | Free $20 / month $50 / month $100 / month $200 / month | AI code generation, Manual code editing, Package support, Deployment integration | MVP prototyping, Experimentation | – Framework compatibility issues might arise for advanced projects. – Deployment integrations may not suit all use cases. |
| AWS PartyRock | Limited | Medium | Free daily usage | No-code AI app building, Integration with AWS services | Small businesses, Non-technical users | – Limited code export capabilities restrict flexibility. – Heavy reliance on AWS ecosystem; less suitable for multi-cloud strategies. |
| GitHub Copilot | Yes | High | Free $4 / user / month $21 / user / month | Advanced code generation, Multi-language support, IDE integration | All developer levels | – Known to produce incorrect or insecure code in some scenarios. – Requires human oversight to validate outputs. – Subscription costs may be prohibitive for some users. |
| Qodo | Yes | High | Free $15 / user / month $45 / user / month | Full-stack development support, Real-time collaboration | Advanced developers, Complex projects | – Integration complexity with existing workflows. – Requires skilled personnel for effective use. |
| A0.dev | Yes | Medium | Free $20 / month | Mobile AI code generation, | MVP prototyping, Experimentation | – Can introduce code vulnerability and security issues – Only for Mobile Apps |
| Cursor | Yes | High | Free $20 / month $40 / month | Code optimisation and refactoring suggestions | Developers looking for AI-assisted coding within a familiar VS Code-like environment | – Difficulty in navigating intricate dependencies and architectures – Potential security concerns due to uploading local code to cloud services |
| Cline | Yes | High | Free | Real-time development support within IDEs | Complex debugging scenarios and large-scale refactoring | – Requires expertise to effectively guide and validate AI suggestions, especially in backend development – Continuous review necessary to maintain code standards |
| Codeium | Yes | High | Free $15 / month $60 / month | Multi-language support, AI chat function, Code explanation | Individual developers | – Struggles with domain-specific requirements and complex workflows. – Free tier lacks advanced features required by teams or enterprises. |
Features and Considerations
Lovable.dev
- Offers quick prototyping and MVP validation capabilities
- Integrates with Supabase for backend and database features
- Provides easy publishing and sharing options
Replit
- Includes AI-powered tools like Agent and Assistant
- Offers a complete development environment with real-time collaboration
- Suitable for educational purposes and quick experimentation
Bolt.new
- Supports popular frameworks like Astro, Vite, Next.js, and more
- Allows manual code editing after AI generation
- Simplifies deployment with Netlify integration
AWS PartyRock
- Designed for no-code AI app development
- Leverages Amazon Bedrock for access to various foundation models
- Cost-effective solution for small businesses to experiment with AI
GitHub Copilot
- Deep integration with the GitHub ecosystem
- Powered by advanced language models (GPT-4o and Claude 3.5 Sonnet)
- Offers built-in security scanning and best practices recommendations
Qodo
- Specializes in full-stack development support
- Provides advanced context understanding across multiple files
- Offers integrated testing and documentation generation
Codeium
- Supports over 70 programming languages
- Provides context-aware code suggestions
- Offers a free tier with many excellent features for individual developers
A0.dev
- Ideal for quickly generating React Native apps or UI components from basic descriptions
- The Component Generator allows for the fast creation of individual UI components or screens.
- The generated React Native projects can be extended and integrated with other tools, APIs, or libraries.
Cursor
- Smaller coding tasks and projects
- Teams seeking strong collaboration feature
- Rapid prototyping and initial code generation
Cline
- Integration testing and system-level operations
- Developers who need flexible context management and model switching
- Front-end tasks and design challenges
- Projects requiring runtime debugging and end-to-end testing capabilities
What Developers think about it ?
- Code Quality Concerns: The generated code not always adhere to best practices, be maintainable, or scale well.
- Example: Seasoned developers might spend more time refactoring than coding from scratch.
- Example: Seasoned developers might spend more time refactoring than coding from scratch.
- Lack of Customization: AI tools may not fully capture complex or unique requirements, requiring additional effort to adjust.
- Over-Reliance Risks: Relying heavily on AI can create dependency issues, making developers less adept at solving problems manually.
- Privacy and Intellectual Property: Concerns about the security and data uploaded to these tools.
Overall, devs generally see AI coding tools as valuable for speeding up development and prototyping, which is also my opinion.
I have been exploring and using AI coding tools heavily and I can only recommend, this avoids you to spend money and time building something that you can easily test before you scale into a product.
The devs also emphasise that these tools are best used as assistants rather than replacements, requiring careful oversight and customisation to ensure high-quality and maintainable code.
