Building the Credit System for My AI Prompt Optimizer

A developer built a credit management system for an AI Prompt Optimizer, implementing plan-based credit allocation, automatic daily resets, and PostgreSQL-based credit deduction. The system integrates with Next.js and Supabase, and the developer learned about PostgreSQL functions, triggers, and row-level security during the process.

Today I completed one of the core backend features of my AI Prompt Optimizer: the credit management system. At first, I thought it would be as simple as decrementing a counter. It turned out to be much more than that. What I implemented Plan-based credit allocation Free & Pro ready Automatic daily credit reset for free users Database-level credit deduction using PostgreSQL functions Credit validation before processing optimization requests Proper handling when users run out of credits Integrated everything with Next.js and Supabase What I learned Building a SaaS isn't just about AI models or UI. A lot of the complexity comes from business logic. While working on this feature, I learned more about: PostgreSQL Functions Triggers Foreign Keys Row Level Security RLS Supabase RPC Designing a scalable credit system It took several iterations and a lot of debugging, but seeing everything work together was worth it. Next up: payment integration, history improvements, and preparing for the beta launch. Building in public, one feature at a time. 🚀