When AI Code Breaks: Design System Patterns That Survive Vibe Coding

Vibe coding is intoxicating. You describe what you want, the AI writes it, you see it render in real time, you describe the next thing. An hour in, you have a working product. Two hours in, something breaks and you have no idea why. Three hours in, you’re debugging code you didn’t write, don’t fully understand, and can’t trace back to the prompt that created it.

This is the vibe coding crash. And it happens to everyone who doesn’t have architectural guardrails in place. Here are the design system patterns that prevent it.

The Root Cause: Context Drift

Every AI model has a context window — the amount of information it can hold while generating code. As you generate more code in a session, earlier decisions drift out of context. The AI forgets the naming convention it used for the first component. It forgets the state management pattern it established. It introduces a second way to fetch data because it doesn’t remember the first way.

By hour two, you have a codebase with three conflicting patterns — all generated by the same model in the same session. This is context drift, and it’s the primary failure mode of vibe coding.

Pattern 1: Locked Tokens

A locked token is a design decision that’s documented in a single file and imported everywhere. Colors, spacing scales, typography scales, border radiuses — all defined in one tokens.ts file.

When the AI generates a new component, it imports from the tokens file. It can’t drift because the source of truth is explicit and immutable. It can’t decide that this button should be #0066FF when the tokens say the primary color is #0623DA, because the AI reads the import and uses the token.

Without tokens, AI generates inline hex values and hardcoded pixel values. Within a single session, you’ll end up with three shades of “blue” and four different spacing systems. Tokens prevent this entirely.

Pattern 2: Component Contracts

Every component has a TypeScript interface that defines exactly what it accepts and what it renders. This interface is the contract. The AI generates code that satisfies the contract, and the TypeScript compiler enforces it.

interface CardProps {
  title: string;
  description: string;
  variant: 'default' | 'featured' | 'compact';
  image?: string;
  onClick?: () => void;
}

When the AI generates a page that uses the Card component, it can’t pass props that don’t exist. It can’t forget a required prop. It can’t use a variant that hasn’t been defined. The contract catches drift at compile time, before it becomes a runtime bug.

Pattern 3: Single Source Layout Components

Layouts drift fast. The AI generates a three-column grid with grid-cols-3 gap-8 on one page and grid-cols-3 gap-6 on another. By the fifth page, every grid has different gaps, different max-widths, and different breakpoints.

The fix: layout components. A <Grid cols={3}> component that always uses the same gap, max-width, and responsive behavior. The AI doesn’t write grid CSS — it composes layout components. The visual consistency is maintained because the decisions are encapsulated in the component, not scattered across pages.

Pattern 4: Pattern File as AI Context

I keep a PATTERNS.md file in every project root. It documents the three most important architectural decisions: how data is fetched, how state is managed, and how components are composed. When I start a Cursor session, this file is in context.

The file is 30–50 lines — short enough for the AI to read entirely, specific enough to prevent drift. It says things like: “Data fetching uses the service pattern. Each entity has a service file in /services. Services export async functions that return typed data. Components call services through custom hooks.”

Without this file, the AI invents patterns. With it, the AI follows patterns. The difference in code quality over a multi-hour session is dramatic.

Pattern 5: Incremental Commits

This isn’t a design system pattern — it’s a workflow pattern that saves design systems from vibe coding damage. Commit after every successful feature. Not at the end of the session. After every feature.

When the AI introduces a bug at hour two, you don’t need to debug — you git diff against the last working commit and see exactly what changed. If the change is too tangled to fix, you revert the commit and try again with better context.

I commit every 15–20 minutes during a vibe coding session. Each commit is a checkpoint I can return to. This turns “debugging AI code I didn’t write” into “reverting to a known good state and trying a different approach.”

Pattern 6: Snapshot Tests for Visual Regression

AI-generated code changes look correct when you’re staring at the component you asked it to modify. It’s the components you didn’t ask it to modify that break. A CSS change cascades. A shared utility function gets modified. A type definition gets widened.

Visual snapshot tests catch these regressions. After each vibe coding session, I run snapshots against the full component library. Any unexpected visual change gets flagged immediately — before I’ve spent another hour building on a broken foundation.

The Survival Checklist

1. Design tokens in a single importable file
2. TypeScript interfaces for every component
3. Layout components, not inline grid CSS
4. PATTERNS.md in context for every AI session
5. Git commit every 15–20 minutes
6. Visual snapshot tests after each session

Vibe coding isn’t going away. It’s too productive to abandon. But without these guardrails, it produces code that looks right and falls apart under maintenance. The design system is what turns AI-generated code from disposable prototypes into maintainable products.