AI Development Patterns: What Actually Works

August 5, 2025

Pixel art illustration of a modern office filled with multiple desks, computer monitors displaying blue screens, office chairs, books, paperwork, and numerous potted plants scattered throughout the space.

After building 30+ repositories with AI coding tools, I’ve learned one thing: raw AI power without structure creates spectacular messes. Whether you’re using ChatGPT, Cursor, or Claude Code, success depends on patterns—not prompts.I’ve been experimenting with these patterns for months, watching what works and what fails. The AI Development Patterns repository captures what I’ve learned, organized into three categories that actually solve real problems. Each pattern follows a standardized specification—this consistency ensures you can measure outcomes and adapt patterns reliably across projects.

Source: AI Development Patterns: What Actually Works | AI Native Dev

Right now it seems clear that the practice of Software Engineering is being transformed by AI. Though just want AI native software engineering looks like is very much an open question. It’s unlikely to look like one particular thing.

Here Paul Duvall explores patterns he’s come across while working on dozens of such projects.