Cursor AI Coding Setup: Agents That Check Their Own Work

This is the Cursor AI coding setup I use in real projects: agents, skills, quality gates, code review, QA, hooks, and sync scripts to make AI coding agents more reliable. GitHub repo: https://github.com/radzionc/cursor-config Most AI coding workflows fail because the agent writes code and immediately says “done.” My setup is built around the opposite idea: before AI reports work as complete, it should verify the work like a real developer would — with tests, project checks, code review, and QA. In this video I walk through my personal Cursor configuration, including: - Quality gates for tests, type checks, linting, dead-code checks, code review, and QA - Dedicated code reviewer and QA agents - Browser-based QA workflows - Real browser and MetaMask testing setup - Email QA tooling - Reference-codebase workflows - Handoff workflows for follow-up tasks - PR and CI fixing workflows - Hooks and sync scripts for using the same setup across machines This is not a toy demo. It is the AI development workflow I use every day as a software engineer. If you find it useful, please star the repo — it helps more developers discover it. Open to senior frontend / web3 engineering opportunities: https://resume.radzion.com #Cursor #AICoding #CursorAI #SoftwareEngineering #DeveloperTools #TypeScript #WebDevelopment #Web3