Linting Rules for AI Coding: Cursor and Claude Code Setup

AI coding assistants can write software at incredible speeds, but without proper boundaries, they often introduce technical debt and inconsistent formatting. By establishing robust linting rules, you can guide these AI agents to generate clean, standard-compliant code on their very first attempt. This text-based course teaches you how to configure static analysis tools to act as automated guardrails for AI-driven development. You will learn to write custom rules, leverage modern configurations, and structure AI-specific instructions to ensure that code contributions remain maintainable, consistent, and secure. What you'll learn: - Understand the foundational concepts of linting and how static analysis guides AI code generation - Configure ESLint flat configs to enforce style guides and catch errors before the AI commits code - Create custom rule files such as .cursorrules to feed context-specific instructions directly to AI agents - Apply automated formatting tools to instantly clean up AI-generated blocks - Integrate linting checks into local development workflows to streamline your review process You will start with the core concepts of static analysis before diving into practical configuration files and AI-specific prompt rules. The course concludes with strategies for integrating these guardrails into your daily coding workflow. This course is designed for developers of all levels who want to leverage AI coding assistants safely and efficiently, with no prior linting configuration experience required. Start building a smarter, safer AI-assisted development environment today.