What Are AI Coding Standards?

AI coding standards are structured guidelines that tell AI coding tools how to generate code for your specific repository.

Why standards matter for AI-generated code

Without explicit guidance, AI coding tools generate code based on general patterns from their training data. This leads to:

Inconsistent code style across files
Wrong framework patterns (e.g., using Pages Router in a Next.js App Router project)
Missing error handling or validation specific to your stack
Security anti-patterns that your project specifically avoids

How AI coding standards differ from traditional linting

While linters (ESLint, Prettier) enforce formatting and catch syntax errors, AI coding standards operate at a higher level of abstraction. They guide architectural decisions, framework conventions, and data flow patterns that linters can't enforce.

Aspect	Linter	AI Standards
Formatting	Enforces	Not needed
Syntax errors	Catches	Prevents
Architecture	Limited	Full guidance
Framework patterns	Not applicable	Specific rules
Data flow	Not applicable	Detailed
Security	Basic	Context-aware

Example: Before and after

Without standards, an AI tool might generate a client component that fetches data directly. With standards, it knows to use a Server Component instead.

// Without standards: "use client"; export default function UserProfile() { const [user, setUser] = useState(null); useEffect(() => { fetch("/api/user").then(...) }, []); return <div>{user.name}</div>; }

// With standards: export default async function UserProfile() { const user = await getUser(); return <div>{user.name}</div>; }

Get started

Ready to generate standards for your repository? Paste your package.json and get repository-aware AI coding standards in seconds.

Generate Standards