Maximum Guardrails: Building Production Systems with AI at Lightning Speed
Maximum Guardrails: Building with AI at Scale
The Problem: AI can generate code fast. Too fast. Without guardrails, you ship bugs at the speed of light.
The Solution: Maximum guardrails. Make it impossible to ship bad code.
The Philosophy
AI assistants (Claude, Cursor, ChatGPT) can 10x your development speed. But only if you have systems that prevent them from 10x-ing your bugs too.
Traditional approach:
Write code → Hope it works → Fix bugs in production → Repeat
Maximum guardrails approach:
Write code → Can't commit bad code → Can't deploy broken code → Ship with confidence
The Guardrail Stack
1. Type Safety (Layer 1)
TypeScript strict mode is non-negotiable.
// tsconfig.json
{
"compilerOptions": {
"strict": true,
"noImplicitAny": true,
"strictNullChecks": true,
"noUncheckedIndexedAccess": true
}
}
Why: AI often generates any types. Strict mode catches this immediately.
2. Linting (Layer 2)
ESLint with zero warnings policy.
// eslint.config.js
export default {
rules: {
'no-console': 'warn',
'no-unused-vars': 'error',
'@typescript-eslint/no-explicit-any': 'error',
}
}
Pre-commit hook:
# .husky/pre-commit
npm run lint
npm run format:check
npm run check-types
If ANY of these fail, commit is blocked.
3. Testing (Layer 3)
Test everything AI generates.
// Unit tests (fast feedback)
describe('Payment processor', () => {
it('should validate amount is positive', () => {
expect(() => processPayment(-100)).toThrow();
});
});
// Integration tests (real scenarios)
describe('Checkout flow', () => {
it('should create order and process payment', async () => {
const order = await createOrder({ amount: 1000 });
const payment = await processPayment(order.id);
expect(payment.status).toBe('succeeded');
});
});
// E2E tests (user journeys)
test('customer can complete checkout', async ({ page }) => {
await page.goto('/checkout/test-product');
await page.fill('[name="email"]', 'test@example.com');
await page.click('button[type="submit"]');
await expect(page).toHaveURL('/success');
});
Coverage requirement: 80% minimum. No exceptions.
Architecture Guardrails
1. Monorepo Structure
Turborepo for enforced boundaries.
// turbo.json
{
"pipeline": {
"build": {
"dependsOn": ["^build"], // Can't build if deps fail
"outputs": ["dist/**", ".next/**"]
},
"test": {
"dependsOn": ["build"], // Can't test unbuildable code
"cache": false
}
}
}
Why: AI can't accidentally create circular dependencies or break builds.
2. Shared Packages
Force code reuse, prevent duplication.
packages/
├── @repo/auth # One auth system
├── @repo/database # One database client
├── @repo/ui # Shared components
└── @repo/validation # Shared Zod schemas
Rule: If code is used in 2+ places, it MUST be a package.
3. Feature Flags
Ship incomplete features safely.
// lib/feature-flags.ts
export const FEATURES = {
NEW_DASHBOARD: false, // Hide until ready
WEBHOOKS_UI: false, // API works, UI doesn't
BETA_PROCESSOR: false, // Test in staging first
} as const;
// Use in code
{canUseFeature('NEW_DASHBOARD') && <NewDashboard />}
Why: Ship fast, enable features when ready. No big bang deployments.
CI/CD Guardrails
Automated Quality Gates
GitHub Actions pipeline that blocks bad deploys:
# .github/workflows/ci.yml
name: Maximum Guardrails
on: [push, pull_request]
jobs:
quality:
steps:
- name: Type Check
run: npm run check-types
# Blocks if types are wrong
- name: Lint
run: npm run lint
# Blocks if code style is wrong
- name: Test
run: npm run test
# Blocks if tests fail
- name: Build
run: npm run build
# Blocks if build fails
- name: E2E Tests
run: npm run test:e2e
# Blocks if user flows break
deploy:
needs: quality # Can't deploy if quality fails
steps:
- name: Deploy to Vercel
run: vercel deploy --prod
Result: Can't deploy broken code. Physically impossible.
Pre-commit Hooks
Local guardrails before code even reaches CI:
// .husky/pre-commit
#!/bin/sh
npm run lint-staged
npm run check-types
// package.json
{
"lint-staged": {
"*.{ts,tsx}": [
"prettier --write",
"eslint --fix",
"vitest related --run"
]
}
}
Developer experience: Fix issues in seconds, not after CI fails.
Documentation Guardrails
.cursorrules File
Teach AI your standards once, enforce forever.
# .cursorrules
## Type Safety First
- Always use TypeScript with strict mode
- No `any` types allowed
- Explicit return types for functions
## Testing Requirements
- Unit tests for all business logic
- Integration tests for API endpoints
- E2E tests for critical user flows
- Minimum 80% coverage
## Code Patterns
✅ GOOD: Functional components
❌ BAD: Class components
✅ GOOD: Server Components by default
❌ BAD: Everything 'use client'
Result: AI follows YOUR rules, not its training data.
Real-World Results
With guardrails:
- Shipped 2 production apps in 48 hours
- 257 tests passing (87% coverage)
- Zero TypeScript errors
- Zero ESLint warnings
- Build time: 4.9 seconds
- Deployed with confidence
Without guardrails:
- Would still be debugging type errors
- Tests would be "TODO"
- Code quality would be inconsistent
- Deploy would be terrifying
The Mistake: Too Much Documentation
We generated 79 documentation files in 2 days.
Why? Because we optimized for AI agent handoffs, not human understanding.
Learning: Document for humans. AI can figure it out.
The Key Insight
Speed without guardrails = chaos at scale.
AI can generate 1000 lines/hour. But if 200 of those lines are bugs, you're moving backwards.
The math:
- Traditional dev: 100 lines/hour, 90% correct = 90 good lines
- AI without guardrails: 1000 lines/hour, 70% correct = 700 good lines + 300 bugs
- AI with guardrails: 800 lines/hour, 95% correct = 760 good lines + automated bug prevention
Guardrails let you go faster safely.
Building Your Own Guardrails
Start with these 5:
- TypeScript strict mode (catches type errors)
- ESLint + Prettier (enforces style)
- Pre-commit hooks (blocks bad commits)
- CI/CD pipeline (blocks bad deploys)
- Feature flags (ships incomplete features safely)
Then add:
- Code generators (consistent patterns)
- Shared packages (force reuse)
- .cursorrules (teach AI your standards)
- Documentation templates (consistent docs)
- Architecture decision records (explain why)
The Result
We shipped production-ready code at AI speed with human quality.
Not because AI is perfect. Because we made it impossible to ship imperfect code.
Built: 2 production apps in 48 hours Tests: 300+ passing Bugs in production: 0 (so far) Deploy confidence: 100%
The future is fast. Make sure it's also correct. 🚀
Resources
Build fast. Build right. Build with guardrails.