Guides, insights, and best practices for turning AI prototypes into production applications
AI-generated code can help you launch fast, but not every messy codebase needs a full rewrite. Use this decision framework to decide whether to refactor, harden, partially rebuild, or rewrite your AI-built app before it becomes expensive to maintain.
Cursor can help you build a working app fast, but performance problems often appear when real users arrive. Learn why Cursor-built apps slow down past 100 users and how to fix database queries, API calls, caching, frontend rendering, AI usage, and deployment bottlenecks before growth breaks the product.
Your first paying customer changes everything. Before someone pays for your AI-built app, make sure the product is secure, stable, usable, monitored, and ready to support real business expectations. Use this production checklist to review auth, payments, data, onboarding, support, monitoring, and launch risk before charging customers.
AWS is powerful, but it can feel overwhelming for vibe coders and AI-first founders. This guide explains how to deploy an AI-generated app on AWS without becoming an AWS expert, using simple managed services, safe defaults, deployment checklists, monitoring, and production-ready patterns.
AI-generated apps can be built fast, but without monitoring, production problems stay invisible. Learn how to add practical monitoring to your AI-built app in one afternoon, including error tracking, uptime checks, logs, performance monitoring, API alerts, AI usage tracking, and deployment visibility.
Replit is great for building and testing apps fast, but production apps often need stronger hosting, security, scaling, database control, and deployment workflows. Learn when to migrate from Replit and how to do it safely.
