Growth Engineering Skill

Infrastructure and patterns for product-led growth, experimentation, and conversion optimization.

Feature Flag Systems

Implementation Pattern

// lib/feature-flags.ts
import { PostHog } from 'posthog-node';

const posthog = new PostHog(process.env.POSTHOG_API_KEY!);

interface FeatureFlags {
  'new-onboarding-flow': boolean;
  'pricing-experiment': 'control' | 'variant-a' | 'variant-b';
  'ai-suggestions': boolean;
}

export async function getFlag<K extends keyof FeatureFlags>(
  key: K,
  userId: string,
): Promise<FeatureFlags[K]> {
  const value = await posthog.getFeatureFlag(key, userId);
  return value as FeatureFlags[K];
}

// Usage in component
const showNewOnboarding = await getFlag('new-onboarding-flow', user.id);

Feature Flag Best Practices

• Short-lived flags: Remove after experiment concludes (< 2 weeks)
• Long-lived flags: Ops toggles for gradual rollouts, kill switches
• Never nest feature flags (creates exponential complexity)
• Clean up stale flags monthly
• Log flag evaluations for debugging

A/B Testing Infrastructure

Experiment Design

// lib/experiments.ts
interface Experiment {
  id: string;
  name: string;
  variants: {
    id: string;
    weight: number; // 0-100, must sum to 100
  }[];
  targetAudience: {
    percentage: number; // % of users included
    filters?: Record<string, unknown>;
  };
  primaryMetric: string;
  secondaryMetrics: string[];
  minimumSampleSize: number;
  startDate: Date;
  endDate?: Date;
}

// Track experiment exposure
function trackExposure(experimentId: string, variantId: string, userId: string) {
  analytics.capture({
    event: '$experiment_started',
    distinctId: userId,
    properties: {
      $experiment_id: experimentId,
      $variant_id: variantId,
    },
  });
}

Statistical Significance

• Minimum sample size: Calculate before starting (use Evan Miller calculator)
• Don't peek: Set duration upfront, don't stop early on promising results
• Sequential testing: Use if you must check early (adjusts p-values)
• Minimum detectable effect: Define what improvement matters (e.g., 5% lift)

Product-Led Growth Patterns

Activation Metrics

Viral Loops

// Referral system pattern
interface Referral {
  referrerId: string;
  referredEmail: string;
  status: 'pending' | 'signed_up' | 'activated' | 'converted';
  rewardGranted: boolean;
}

// Track referral funnel
function trackReferralStep(referralId: string, step: Referral['status']) {
  analytics.capture({
    event: 'referral_step',
    properties: { referralId, step },
  });
}

Conversion Optimization

• Reduce friction: Minimize form fields, enable social login
• Social proof: Show user counts, testimonials, logos
• Urgency: Trial countdown, limited-time offers (use sparingly)
• Value demonstration: Interactive demos, free tier with clear upgrade path
• Personalization: Onboarding flow based on use case selection

Growth Metrics

Experimentation Platforms

Related Resources

• ~/.claude/skills/product-analytics/SKILL.md - Analytics and tracking
• ~/.claude/agents/product-analytics-specialist.md - Analytics agent
• ~/.claude/skills/authentication-patterns/SKILL.md - Auth for PLG

Measure everything. Experiment constantly. Remove what doesn't work.