Embracing the “Vibe Coding” Movement: Lessons from AI-Driven Development
I’ve recently embarked on an exciting journey with the “Vibe Coding” movement, letting AI handle 90% of my code. It was a game-changer—until it wasn’t.
Key Takeaways:
- Project Highlights: Built a Free Video Watermark Remover over a weekend.
- Reality Check: Faced crippling costs from inefficient AI code.
- Lesson Learned: Paying for compute time even when tasks fail can be devastating.
Innovative Fixes:
- Instead of upgrading to expensive hardware, I implemented a CPU Pre-processing Layer.
- Video is normalized to 720p @ 30fps before processing, saving resources and reducing costs.
By blending creativity with systemic architecture, I turned an initial failure into a scalable solution.
💡 Join the conversation about efficient AI coding—share your experiences and insights!
