
After managing teams at Mercury, Elevate Security, and now Heard, I've learned that running an engineering organization is less about technology and more about people, systems, and strategy.

#### The Three Pillars

**1. People**
Hiring, developing, and retaining talent. This means creating growth opportunities, providing clear feedback, and building a culture where people want to stay.

**2. Systems**
Processes that scale. From code review to incident response, systems should make good outcomes easy and bad outcomes hard.

**3. Strategy**
Knowing what to build and why. This requires deep understanding of business goals and customer needs.

#### Common Mistakes

- Optimizing for velocity over outcomes
- Building systems before understanding problems
- Neglecting developer experience
- Focusing on technology over business value

#### What Works

- Clear communication of priorities
- Empowering teams to make decisions
- Investing in developer productivity
- Measuring what matters (outcomes, not outputs)

> "Good engineering management is about creating conditions where great work can happen."

#### The Hard Truth

You can't optimize everything. Trade-offs are constant. The key is making explicit decisions about what you're optimizing for and communicating those decisions clearly.



Running an engineering organization


After years of experience in engineering leadership and fintech, I've learned that remote team communication requires careful attention to both technical excellence and human factors.

#### The Challenge

Remote team communication is something I've encountered throughout my career at companies like Mercury, Heard, Ness, and now Pangea. The key is understanding both the technical and human aspects.

#### Key Insights

1. **Technical Excellence**: Whether it's Python, TypeScript, or infrastructure, solid technical foundations matter.

2. **People First**: Engineering is ultimately about people-building systems that serve users and teams that thrive.

3. **Balance**: Finding the right balance between technical depth and practical application.

#### Lessons Learned

- Start with understanding the problem deeply
- Build iteratively and get feedback early
- Invest in both technical skills and soft skills
- Take care of your mental and physical health

> "The best engineering solutions come from understanding both the code and the people who use it."

#### Next Steps

Consider how remote team communication applies to your own work. What can you learn? What can you improve? How can you help others?



Remote team communication


At Cloudentity, I managed an overseas team delivering solutions in Scala and React. Managing distributed teams across time zones requires different skills than managing co-located teams.

#### The Challenges

Distributed teams face:
- Time zone differences
- Cultural differences
- Communication barriers
- Lack of face-to-face interaction
- Coordination overhead

#### What Works

**1. Overlap Hours**
Establish core hours when everyone is available. We had 4 hours of overlap between US and overseas teams.

**2. Async-First Communication**
Default to async (Slack, email, docs) with sync meetings only when necessary.

**3. Clear Documentation**
Write everything down. Don't rely on verbal communication.

**4. Regular Check-ins**
Weekly 1:1s, daily standups, and regular team meetings.

**5. Cultural Awareness**
Understand and respect cultural differences in communication and work styles.

#### Communication Practices

**Daily Standups**
- Async updates in Slack
- Video standup once per week
- Focus on blockers and progress

**Documentation**
- Architecture decisions in ADRs
- API contracts in OpenAPI specs
- Runbooks for operations
- Meeting notes shared immediately

**Code Reviews**
- Clear guidelines and expectations
- Timely reviews (within 24 hours)
- Constructive feedback
- Pair programming when possible

#### Tools

- **Slack**: Daily communication
- **Zoom**: Video meetings
- **GitHub**: Code collaboration
- **Notion**: Documentation
- **Jira**: Project tracking

#### Building Trust

- Be available during overlap hours
- Respond to messages promptly
- Follow through on commitments
- Recognize good work publicly
- Address issues directly

#### Handling Conflicts

- Address issues early
- Use video calls for difficult conversations
- Focus on facts, not assumptions
- Seek to understand different perspectives
- Find win-win solutions

#### Results

- Successful project delivery
- Strong team cohesion
- Good work-life balance for all
- High code quality
- Positive team culture

> "Distance doesn't have to mean disconnection."

#### Lessons Learned

1. Communication is everything
2. Documentation is critical
3. Trust takes time to build
4. Cultural awareness matters
5. Overlap hours are essential



Managing an overseas engineering team


At Heard, I established engineering KPIs tied to company OKRs, increasing feature delivery velocity by 12% and retention by 15%. The key was aligning engineering metrics with business outcomes.

#### The Problem

Traditional engineering metrics (lines of code, commits, velocity) don't connect to business value. We needed metrics that:
- Align with company goals
- Measure outcomes, not outputs
- Drive the right behaviors
- Are actionable

#### Our Approach

**1. Start with Company OKRs**
Understand what the company is trying to achieve.

**2. Map Engineering Work to OKRs**
Connect engineering initiatives to business outcomes.

**3. Define Measurable KPIs**
Create metrics that track progress toward OKRs.

**4. Review Regularly**
Weekly reviews, monthly deep dives, quarterly planning.

#### Example: User Retention OKR

**Company OKR:**
- Increase user retention by 20%

**Engineering Contribution:**
- Reduce time to value (onboarding)
- Improve product reliability
- Fix critical bugs faster

**Engineering KPIs:**
- Time to first value: < 5 minutes
- Uptime: > 99.9%
- Critical bug resolution: < 4 hours

#### KPI Dashboard

```typescript
interface EngineeringKPIs {
  // Feature Delivery
  featureDeliveryVelocity: number; // features per week
  timeToMarket: number; // days from idea to production
  
  // Quality
  bugRate: number; // bugs per feature
  uptime: number; // percentage
  customerSatisfaction: number; // NPS score
  
  // Team Health
  retention: number; // percentage
  engagement: number; // survey score
  burnoutRisk: number; // calculated metric
}

function calculateKPIs(metrics: Metrics): EngineeringKPIs {
  return {
    featureDeliveryVelocity: calculateVelocity(metrics),
    timeToMarket: calculateTTM(metrics),
    bugRate: calculateBugRate(metrics),
    uptime: calculateUptime(metrics),
    customerSatisfaction: metrics.nps,
    retention: calculateRetention(metrics),
    engagement: metrics.engagementScore,
    burnoutRisk: calculateBurnoutRisk(metrics),
  };
}
```

#### Tracking and Reporting

**Weekly Reviews**
- Review KPIs vs targets
- Identify blockers
- Adjust priorities

**Monthly Deep Dives**
- Analyze trends
- Root cause analysis
- Action planning

**Quarterly Planning**
- Set new KPIs
- Align with company OKRs
- Plan initiatives

#### Results

- 12% increase in feature delivery velocity
- 15% increase in retention
- Better alignment with business goals
- More focused engineering work
- Improved team motivation

> "What gets measured gets managed."

#### Lessons Learned

1. Align metrics with business outcomes
2. Measure outcomes, not outputs
3. Review regularly
4. Adjust based on results
5. Keep it simple

#### Common Pitfalls

- Too many metrics (focus on 5-7)
- Vanity metrics (measure what matters)
- Setting and forgetting (review regularly)
- Ignoring context (understand why metrics change)
- Gaming the system (prevent manipulation)



Establishing engineering KPIs tied to company OKRs


At Pangea, we use Cloud Build and GitHub Actions for CI/CD. The pipeline builds, tests, and deploys our services automatically, ensuring quality and speed.

#### Pipeline Stages

1. **Lint**: Check code style
2. **Test**: Run unit and integration tests
3. **Build**: Create Docker images
4. **Security Scan**: Check for vulnerabilities
5. **Deploy**: Deploy to staging/production

#### GitHub Actions Workflow

```yaml
name: CI/CD Pipeline

on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      
      - name: Setup Node.js
        uses: actions/setup-node@v3
        with:
          node-version: '18'
      
      - name: Install dependencies
        run: npm ci
      
      - name: Run linter
        run: npm run lint
      
      - name: Run tests
        run: npm test
      
      - name: Upload coverage
        uses: codecov/codecov-action@v3

  build:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      
      - name: Build Docker image
        run: |
          docker build -t gcr.io/${{ secrets.GCP_PROJECT }}/api:${{ github.sha }} .
      
      - name: Push to GCR
        run: |
          echo "${{ secrets.GCP_SA_KEY }}" | docker login -u _json_key --password-stdin https://gcr.io
          docker push gcr.io/${{ secrets.GCP_PROJECT }}/api:${{ github.sha }}

  deploy-staging:
    needs: build
    if: github.ref == 'refs/heads/develop'
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to staging
        run: |
          gcloud run deploy api \
            --image gcr.io/${{ secrets.GCP_PROJECT }}/api:${{ github.sha }} \
            --region us-central1 \
            --platform managed
```

#### Cloud Build Configuration

```yaml
# cloudbuild.yaml
steps:
  # Build
  - name: 'gcr.io/cloud-builders/docker'
    args: ['build', '-t', 'gcr.io/$PROJECT_ID/api:$SHORT_SHA', '.']
  
  # Test
  - name: 'gcr.io/cloud-builders/docker'
    args: ['run', '--rm', 'gcr.io/$PROJECT_ID/api:$SHORT_SHA', 'npm', 'test']
  
  # Security scan
  - name: 'gcr.io/cloud-builders/docker'
    args: ['run', '--rm', '-v', '/var/run/docker.sock:/var/run/docker.sock', 'aquasec/trivy', 'image', 'gcr.io/$PROJECT_ID/api:$SHORT_SHA']
  
  # Push
  - name: 'gcr.io/cloud-builders/docker'
    args: ['push', 'gcr.io/$PROJECT_ID/api:$SHORT_SHA']
  
  # Deploy
  - name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'
    entrypoint: gcloud
    args:
      - 'run'
      - 'deploy'
      - 'api'
      - '--image'
      - 'gcr.io/$PROJECT_ID/api:$SHORT_SHA'
      - '--region'
      - 'us-central1'

images:
  - 'gcr.io/$PROJECT_ID/api:$SHORT_SHA'
```

#### Best Practices

- Fast feedback (fail fast)
- Parallel jobs when possible
- Cache dependencies
- Security scanning
- Automated rollback
- Deployment approvals for production

> "CI/CD enables rapid, reliable deployments."

#### Lessons Learned

1. Keep pipelines fast
2. Test thoroughly
3. Scan for security issues
4. Automate everything possible
5. Monitor deployments



CI/CD with Cloud Build and GitHub Actions


At lululemon, I led the API-layer team that launched Buy Online, Pick-Up In Store (BOPIS). This feature required real-time inventory synchronization, store location services, and seamless checkout integration.

#### The Challenge

BOPIS requires:
- Real-time inventory visibility
- Store location and availability
- Seamless checkout flow
- Order management system
- Customer notifications

#### Architecture

We built:
- **Inventory API**: Real-time store inventory
- **Location Service**: Store finder and availability
- **Order API**: Create and manage pickup orders
- **Notification Service**: Customer updates
- **Store Integration**: Connect with POS systems

#### Inventory Synchronization

```typescript
class StoreInventoryService {
  async getStoreInventory(
    productId: string,
    storeId: string
  ): Promise<InventoryStatus> {
    // Check cache first
    const cached = await this.cache.get(`inventory:${storeId}:${productId}`);
    if (cached) {
      return cached;
    }
    
    // Fetch from store system
    const inventory = await this.storeSystem.getInventory(storeId, productId);
    
    // Cache for 5 minutes
    await this.cache.set(
      `inventory:${storeId}:${productId}`,
      inventory,
      300
    );
    
    return inventory;
  }
  
  async reserveInventory(
    productId: string,
    storeId: string,
    quantity: number
  ): Promise<ReservationResult> {
    // Reserve inventory in store system
    const reservation = await this.storeSystem.reserve(
      storeId,
      productId,
      quantity
    );
    
    // Invalidate cache
    await this.cache.delete(`inventory:${storeId}:${productId}`);
    
    return reservation;
  }
}
```

#### Store Location Service

```typescript
interface Store {
  id: string;
  name: string;
  address: Address;
  coordinates: Coordinates;
  hours: StoreHours;
  inventory: Map<string, number>;
}

class StoreLocationService {
  async findNearbyStores(
    location: Coordinates,
    radius: number
  ): Promise<Store[]> {
    const stores = await this.storeRepository.findNearby(location, radius);
    
    return stores.map(store => ({
      ...store,
      distance: this.calculateDistance(location, store.coordinates),
    })).sort((a, b) => a.distance - b.distance);
  }
  
  async getStoresWithProduct(
    productId: string,
    location: Coordinates
  ): Promise<Store[]> {
    const stores = await this.findNearbyStores(location, 25); // 25 miles
    
    const availableStores = await Promise.all(
      stores.map(async (store) => {
        const inventory = await this.inventoryService.getStoreInventory(
          productId,
          store.id
        );
        return inventory.available > 0 ? store : null;
      })
    );
    
    return availableStores.filter(Boolean) as Store[];
  }
}
```

#### Order Creation

```typescript
class BOPISOrderService {
  async createPickupOrder(
    customerId: string,
    items: CartItem[],
    storeId: string
  ): Promise<PickupOrder> {
    // Validate store availability
    for (const item of items) {
      const inventory = await this.inventoryService.getStoreInventory(
        item.productId,
        storeId
      );
      
      if (inventory.available < item.quantity) {
        throw new InsufficientInventoryError(item.productId, storeId);
      }
    }
    
    // Reserve inventory
    const reservations = await Promise.all(
      items.map(item =>
        this.inventoryService.reserveInventory(
          item.productId,
          storeId,
          item.quantity
        )
      )
    );
    
    // Create order
    const order = await this.orderRepository.create({
      customerId,
      storeId,
      items,
      type: 'pickup',
      status: 'pending',
      reservations: reservations.map(r => r.id),
    });
    
    // Send notifications
    await this.notificationService.sendOrderConfirmation(order);
    
    return order;
  }
}
```

#### Results

- Successful BOPIS launch
- Real-time inventory accuracy
- Seamless customer experience
- Increased store foot traffic
- Better inventory utilization

> "BOPIS bridges online and physical retail."

#### Lessons Learned

1. Real-time inventory is critical
2. Cache aggressively but invalidate properly
3. Handle inventory conflicts gracefully
4. Provide clear customer communication
5. Monitor store fulfillment rates

