Hello Mihir!
I'm truly excited to connect with you.
I have the PRO subscription for Google AI Studio, and I'm looking to build scalable SaaS models using a low-code/no-code (or "vibe coding") approach.
My strengths lie in a strong design sense and solid execution strategies, and I have a backlog of innovative ideas ready to go. My preferred stack involves Firebase for the backend infrastructure.
The key challenge I face is with the AI itself: while I've been proficient in prompt engineering for the last two years, I've noticed a recent decline, with the models often becoming "lazy" or generic, which hinders my SaaS concept execution.
My core question is this:
What are the best practices, architectural patterns, and PRO-specific advantages I can leverage to robustly and effectively integrate the Gemini API with Firebase (especially Cloud Functions/Firestore) to overcome this "lazy AI" problem and reliably deliver high-quality, non-generic output for my SaaS applications?