Vibe Coding Use Cases: What Actually Works vs Waste of Time
I tested this.
What works well with vibe coding?
Works well: landing pages (100% shipped), internal tools (100%), SaaS MVPs (66%), Chrome extensions (75%). These projects have well-defined scopes and standard patterns. The AI handles the boilerplate. I handle the business logic.
What is a waste of time?
Waste of time: mobile apps (33% shipped), real-time systems, multiplayer features, any project with complex state management across multiple clients. The AI consistently generates broken synchronization logic. I tried building a chat app. Three attempts. Three failures.
How do you evaluate new tools?
Evaluate new tools by: building one small feature (not the whole app), checking code quality (hardcoded secrets?), checking integration ease (does the code fit your existing patterns?), and checking iteration speed (can you fix what the AI gets wrong?).
Works: landing pages, internal tools, SaaS MVPs, extensions. Waste: mobile apps, real-time, multiplayer, complex state. Evaluate tools with one small feature first.
The 33% success rate on mobile apps is not a coincidence. AI consistently fails at mobile because the frameworks (React Native, Flutter) involve complex state management and platform-specific code that the AI does not handle well. If mobile is your target, be prepared to write significant amounts of code yourself.
Steps.
AI tools are powerful but require human judgment and careful oversight at every step of the development process. I learned this lesson the hard way after several production incidents caused by trusting AI output without verification. Review every change before merging to main. Test every feature with real edge cases, not just the happy path that the AI assumes. Never trust AI-generated code in production without thorough verification. These habits will prevent the production incidents that I experienced in my early days of vibe coding. The extra few minutes spent on review and testing pay for themselves many times over in prevented issues and cleaner codebases that are easier to maintain and debug over the long term.
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