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Why you can’t create a real SaaS just by vibe coding — lessons from building 20+ apps
r/SaaS
7/2/2025
SAAS TOOLS
| SaaS | URL | Category | Features/Notes |
|---|---|---|---|
| bolt.new | http://bolt.new | AI-assisted development | Syncs local code with AI through GitHub |
| lovable | Not specified | AI-assisted development | Not specified |
| consoleIq | Not specified | AI log analyzer | Not specified |
| redesignr.ai | http://redesignr.ai | AI redesign generator | Converts GitHub repo to documentation site |
| usetriage.com | https://usetriage.com | AI-assisted development | Built with auth, Slack integration, admin panel |
| Mazaal AI | Not specified | AI-assisted development | Helps map out logic beyond UI scaffolding |
| atsynct.com | http://atsynct.com | Project management | AI assistance in breaking down tasks |
| ColorCraft.AI | https://ColorCraft.AI | AI-assisted development | Built with RBAC, auth, DB, analytics, etc. |
| talkform.org | Not specified | AI-assisted development | Built by non-technical product manager |
USER NEEDS
Pain Points:
- AI-generated code doesn't scale for real features like user auth, billing, usage metering
- Constant rewriting needed to match architecture and fix component communication
- New features break existing AI-generated flows
- Spending more time cleaning up than building forward
- AI lacks context for complex systems
- Security vulnerabilities in AI-generated code
- Difficulty integrating real data and workflows
Problems to Solve:
- How to efficiently transition from prototype to production-ready SaaS
- How to implement complex features (auth, billing, RBAC) with AI assistance
- How to maintain code quality and architecture with AI tools
- How to avoid technical debt from rapid prototyping
- How to ensure security in AI-generated code
Potential Solutions:
- Use AI for prototyping and UI scaffolding only, then rebuild on proper stack
- Break down projects into small, well-defined tasks for AI
- Create detailed PRDs and discuss with AI before coding
- Use AI as an assistant for specific code blocks (API endpoints, UI elements)
- Combine AI with professional development skills
- Implement test-driven development practices
- Use project management tools with AI task breakdown assistance
GROWTH FACTORS
Effective Strategies:
- Rapid prototyping to validate ideas quickly
- Iterating based on user feedback
- Leveraging AI for productivity boosts in development
- Focusing on product-market fit before scaling
Marketing & Acquisition:
- Not explicitly discussed in the thread
Monetization & Product:
- Pricing models not discussed
- Importance of building beyond prototypes to real features (auth, billing)
- Need for proper architecture to support scaling
- Product-market fit requires moving beyond simple prototypes
User Engagement:
- Using prototypes to gather user feedback
- Community discussions about best practices for AI-assisted development
- Sharing lessons learned from building multiple projects