From Vibe Coding to Spec-Driven Development: Part 4 - Team collaboration and advanced patterns

Table of Contents

  1. Series overview
  2. From solo to team
  3. Section 1: Team workflows
    1. The spec-driven team structure
    2. Workflow #1: Feature branch per user story
    3. Workflow #2: Trunk-based with feature flags
    4. Workflow #3: Mob programming with AI
  4. Section 2: Code review for spec-driven projects
    1. The spec-driven PR checklist
    2. Review automation
  5. Section 3: CI/CD integration
    1. GitHub Actions pipeline
    2. Azure DevOps pipeline
    3. Key differences: GitHub Actions vs Azure DevOps
  6. Section 4: Advanced architectural patterns
    1. Pattern #1: Modular monolith
    2. Pattern #2: Backend for Frontend (BFF)
    3. Pattern #3: Event-driven architecture
    4. Pattern #4: Microservices (proceed with caution)
    5. Choosing the right pattern
  7. Section 5: Scaling strategies
    1. When your application outgrows the initial architecture
    2. Strategy #1: Horizontal scaling
    3. Strategy #2: Caching layers
    4. Strategy #3: Background processing
  8. Section 6: Team communication patterns
    1. Keeping everyone aligned
    2. Pattern #1: Spec review meetings
    3. Pattern #2: Async spec updates
    4. Pattern #3: Decision records
  9. Key takeaways from Part 4
  10. What’s next
  11. Resources
  12. Series navigation

🎯 This is Part 4 of a 5-part series on mastering AI-assisted development.

We’ve covered the individual workflow. Now let’s scale it to teams and production environments.

Series overview

Part Topic Status
Part 1 The problem and the solution
Part 2 Deep dive into the Spec-Kit workflow
Part 3 Best practices and troubleshooting
Part 4 Team collaboration and advanced patterns 📍
Part 5 Case studies and lessons learned Feb 2

From solo to team

Everything we’ve covered so far assumes a single developer working with AI. But real software is built by teams. How does spec-driven development scale?

The good news: Spec-Kit was designed with teams in mind. The artifacts (constitution, spec, plan, tasks) become shared contracts that align everyone—humans and AI agents alike.

The challenge: Multiple developers, multiple AI sessions, multiple opinions. Without coordination, you get chaos.

This post covers three areas:

  1. Team workflows - How multiple developers collaborate
  2. CI/CD integration - Automating validation with GitHub Actions and Azure DevOps
  3. Advanced patterns - Scaling beyond the monolith

Section 1: Team workflows

The spec-driven team structure

In a spec-driven team, roles shift slightly:

Traditional Role Spec-Driven Role Primary Artifacts
Tech Lead Constitution Guardian constitution.md
Product Owner Spec Owner spec.md
Architect Plan Reviewer plan.md, data-model.md
Developer Task Implementer tasks.md, code

Key insight: The constitution becomes your architecture decision record. The spec becomes your product requirements document. These aren’t new artifacts—they’re familiar concepts in a format AI can consume.

Workflow #1: Feature branch per user story

The cleanest approach for teams of 3-8 developers. Each user story (US) gets its own feature branch.

%%{init: {
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    'primaryColor': '#e8f5e9',
    'primaryTextColor': '#1b5e20',
    'primaryBorderColor': '#4caf50',
    'secondaryColor': '#e3f2fd',
    'secondaryTextColor': '#0d47a1',
    'secondaryBorderColor': '#2196f3',
    'tertiaryColor': '#f3e5f5',
    'tertiaryTextColor': '#4a148c',
    'tertiaryBorderColor': '#9c27b0',
    'lineColor': '#546e7a',
    'fontSize': '14px'
  }
}}%%
flowchart LR
    subgraph main["🌳 main"]
        direction TB
        M1[v1.0.0]
        M2[✨ Auth merged]
        M3[✨ Tasks merged]
        M1 --> M2 --> M3
    end

    subgraph us1["🔐 feature/user-authentication"]
        direction TB
        A1["📝 Update spec.md"]
        A2["🗺️ Generate plan"]
        A3["📋 Break into tasks"]
        A4["⚙️ Implement"]
        A5["✅ Tests pass"]
        A6["🔍 PR review"]
        A1 --> A2 --> A3 --> A4 --> A5 --> A6
    end

    subgraph us2["📋 feature/task-management"]
        direction TB
        B1["📝 Update spec.md"]
        B2["🗺️ Generate plan"]
        B3["📋 Break into tasks"]
        B4["⚙️ Implement"]
        B5["✅ Tests pass"]
        B6["🔍 PR review"]
        B1 --> B2 --> B3 --> B4 --> B5 --> B6
    end

    subgraph us3["👥 feature/team-collab"]
        direction TB
        C1["📝 Update spec.md"]
        C2["🗺️ ...in progress"]
        C1 --> C2
    end

    M1 -.->|branch| A1
    M1 -.->|branch| B1
    A6 -->|merge| M2
    M2 -.->|branch| C1
    B6 -->|merge| M3

    style main fill:#e8f5e9,stroke:#4caf50,stroke-width:3px
    style us1 fill:#e3f2fd,stroke:#2196f3,stroke-width:2px
    style us2 fill:#f3e5f5,stroke:#9c27b0,stroke-width:2px
    style us3 fill:#fff3e0,stroke:#ff9800,stroke-width:2px

Process:

  1. Spec Owner creates feature branch with spec changes
  2. Plan Reviewer runs /speckit.plan and reviews architecture
  3. Task Implementer runs /speckit.tasks and implements
  4. PR review validates against constitution
  5. Merge to main with squash commit

Each user story branch follows the same workflow: spec → plan → tasks → implement → review → merge

Workflow #2: Trunk-based with feature flags

For teams practicing continuous deployment (8+ developers).

main (always deployable)
 │
 ├── commit: Add user-auth spec (flag: OFF)
 ├── commit: Implement auth backend (flag: OFF)
 ├── commit: Implement auth frontend (flag: OFF)
 ├── commit: Enable user-auth flag (flag: ON)
 │
 └── (features go live via flag toggles)

Process:

  1. All spec changes go to main immediately
  2. Implementation happens behind feature flags
  3. /speckit.implement generates flag-aware code
  4. QA tests with flag enabled
  5. Flag enabled for all users when ready

Constitution addition for feature flags:

## Feature Flag Requirements

### Implementation
- All new features MUST be behind feature flags
- Flag naming: `feature_{story_id}_{short_name}`
- Default state: OFF in production

### Flag Service
- Use LaunchDarkly / Azure App Configuration / custom implementation
- Flags evaluated server-side (no client exposure of disabled features)

Workflow #3: Mob programming with AI

Surprisingly effective for complex features.

Setup:

  • One screen shared (driver)
  • 2-4 developers watching (navigators)
  • AI assistant running

Process:

  1. Navigator 1 dictates spec requirements
  2. Driver types into AI assistant
  3. Navigator 2 reviews AI output in real-time
  4. All discuss and refine before accepting
  5. Rotate driver every 15 minutes

Why this works: Multiple humans catch AI hallucinations immediately. Knowledge transfers naturally. Everyone understands the codebase.


Section 2: Code review for spec-driven projects

The spec-driven PR checklist

Standard code review isn’t enough. Add these checks:

## PR Review Checklist

### Constitution Compliance
- [ ] Code follows technical constraints
- [ ] Performance targets considered
- [ ] Security requirements addressed
- [ ] No prohibited patterns used

### Spec Alignment
- [ ] Implementation matches user stories
- [ ] All acceptance criteria testable
- [ ] Edge cases from spec handled
- [ ] Error messages match spec exactly

### Plan Consistency
- [ ] Architecture matches plan.md
- [ ] Data model matches data-model.md
- [ ] API contracts match api-spec
- [ ] No undocumented deviations

### AI-Specific Checks
- [ ] No hallucinated dependencies
- [ ] No deprecated patterns
- [ ] Tests actually run (not just generated)
- [ ] No hardcoded localhost/dev values

Review automation

Add a PR template that enforces the checklist:

<!-- .github/PULL_REQUEST_TEMPLATE.md -->

## Summary
<!-- What does this PR do? -->

## Related Spec Section
<!-- Link to spec.md section this implements -->

## Constitution Compliance
- [ ] Reviewed against constitution.md
- [ ] No violations or documented exceptions

## Testing
- [ ] Unit tests added/updated
- [ ] Integration tests pass
- [ ] Manual testing completed

## AI Disclosure
- [ ] AI-assisted code reviewed by human
- [ ] All dependencies verified to exist
- [ ] No TODO/FIXME markers from AI

Section 3: CI/CD integration

GitHub Actions pipeline

For teams using GitHub, here’s a complete pipeline:

# .github/workflows/spec-driven-ci.yml
name: Spec-Driven CI/CD

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

env:
  DOTNET_VERSION: '9.0.x'

jobs:
  validate-specs:
    name: Validate Specifications
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Check spec completeness
        run: |
          # Verify required sections exist
          for section in "User Stories" "Acceptance Criteria" "Edge Cases"; do
            if ! grep -q "## $section" .speckit/spec.md; then
              echo "::error::Missing required section: $section"
              exit 1
            fi
          done
          
      - name: Check for TODO markers
        run: |
          if grep -r "TODO\|FIXME\|XXX" .speckit/*.md; then
            echo "::error::Unresolved TODO markers in specifications"
            exit 1
          fi
          
      - name: Validate constitution compliance
        run: |
          # Check nullable reference types (from constitution)
          if ! grep -q "<Nullable>enable</Nullable>" src/*.csproj; then
            echo "::error::Nullable reference types not enabled"
            exit 1
          fi

  build-and-test:
    name: Build and Test
    runs-on: ubuntu-latest
    needs: validate-specs
    steps:
      - uses: actions/checkout@v4
      
      - name: Setup .NET
        uses: actions/setup-dotnet@v4
        with:
          dotnet-version: $
          
      - name: Restore dependencies
        run: dotnet restore
        
      - name: Build
        run: dotnet build --no-restore --configuration Release
        
      - name: Run tests
        run: dotnet test --no-build --configuration Release --collect:"XPlat Code Coverage"
        
      - name: Check coverage threshold
        run: |
          # Constitution requires 80% coverage
          coverage=$(cat TestResults/*/coverage.cobertura.xml | grep -oP 'line-rate="\K[^"]+')
          if (( $(echo "$coverage < 0.80" | bc -l) )); then
            echo "::error::Coverage ${coverage} below 80% threshold"
            exit 1
          fi

  security-scan:
    name: Security Scan
    runs-on: ubuntu-latest
    needs: build-and-test
    steps:
      - uses: actions/checkout@v4
      
      - name: Run dependency audit
        run: dotnet list package --vulnerable --include-transitive
        
      - name: OWASP dependency check
        uses: dependency-check/Dependency-Check_Action@main
        with:
          project: 'TeamTaskManager'
          path: '.'
          format: 'HTML'

  deploy-staging:
    name: Deploy to Staging
    runs-on: ubuntu-latest
    needs: [build-and-test, security-scan]
    if: github.ref == 'refs/heads/main'
    environment: staging
    steps:
      - uses: actions/checkout@v4
      
      - name: Deploy to staging
        run: |
          # Your deployment script here
          echo "Deploying to staging..."

Azure DevOps pipeline

Many enterprises in the Netherlands and Europe use Azure DevOps. Here’s the equivalent pipeline:

# azure-pipelines.yml
trigger:
  branches:
    include:
      - main
  paths:
    exclude:
      - README.md
      - docs/*

pr:
  branches:
    include:
      - main

pool:
  vmImage: 'ubuntu-latest'

variables:
  dotnetVersion: '9.0.x'
  buildConfiguration: 'Release'

stages:
  - stage: Validate
    displayName: 'Validate Specifications'
    jobs:
      - job: ValidateSpecs
        displayName: 'Spec Validation'
        steps:
          - checkout: self
          
          - task: Bash@3
            displayName: 'Check spec completeness'
            inputs:
              targetType: 'inline'
              script: |
                echo "Checking specification completeness..."
                
                required_sections=("User Stories" "Acceptance Criteria" "Edge Cases")
                for section in "${required_sections[@]}"; do
                  if ! grep -q "## $section" .speckit/spec.md; then
                    echo "##vso[task.logissue type=error]Missing required section: $section"
                    exit 1
                  fi
                done
                
                echo "All required sections present"
                
          - task: Bash@3
            displayName: 'Check for unresolved TODOs'
            inputs:
              targetType: 'inline'
              script: |
                if grep -r "TODO\|FIXME" .speckit/*.md; then
                  echo "##vso[task.logissue type=error]Unresolved TODO markers found"
                  exit 1
                fi
                
          - task: Bash@3
            displayName: 'Validate constitution compliance'
            inputs:
              targetType: 'inline'
              script: |
                # Check nullable reference types enabled
                if ! grep -q "<Nullable>enable</Nullable>" src/*.csproj; then
                  echo "##vso[task.logissue type=error]Nullable reference types not enabled (constitution violation)"
                  exit 1
                fi
                
                # Check for raw SQL (prohibited by constitution)
                if grep -r "ExecuteSqlRaw\|FromSqlRaw" src/; then
                  echo "##vso[task.logissue type=error]Raw SQL detected (constitution violation)"
                  exit 1
                fi

  - stage: Build
    displayName: 'Build and Test'
    dependsOn: Validate
    jobs:
      - job: BuildAndTest
        displayName: 'Build & Test'
        steps:
          - checkout: self
          
          - task: UseDotNet@2
            displayName: 'Setup .NET'
            inputs:
              version: $(dotnetVersion)
              
          - task: DotNetCoreCLI@2
            displayName: 'Restore packages'
            inputs:
              command: 'restore'
              projects: '**/*.csproj'
              
          - task: DotNetCoreCLI@2
            displayName: 'Build solution'
            inputs:
              command: 'build'
              projects: '**/*.csproj'
              arguments: '--configuration $(buildConfiguration) --no-restore'
              
          - task: DotNetCoreCLI@2
            displayName: 'Run tests with coverage'
            inputs:
              command: 'test'
              projects: '**/*Tests.csproj'
              arguments: '--configuration $(buildConfiguration) --no-build --collect:"XPlat Code Coverage" --results-directory $(Build.SourcesDirectory)/TestResults'
              
          - task: PublishCodeCoverageResults@2
            displayName: 'Publish coverage report'
            inputs:
              summaryFileLocation: '$(Build.SourcesDirectory)/TestResults/**/coverage.cobertura.xml'
              
          - task: Bash@3
            displayName: 'Enforce coverage threshold'
            inputs:
              targetType: 'inline'
              script: |
                # Constitution requires 80% coverage
                coverage_file=$(find $(Build.SourcesDirectory)/TestResults -name "coverage.cobertura.xml" | head -1)
                if [ -f "$coverage_file" ]; then
                  coverage=$(grep -oP 'line-rate="\K[^"]+' "$coverage_file" | head -1)
                  threshold=0.80
                  if (( $(echo "$coverage < $threshold" | bc -l) )); then
                    echo "##vso[task.logissue type=error]Coverage $coverage is below $threshold threshold"
                    exit 1
                  fi
                  echo "Coverage: $coverage (threshold: $threshold) ✓"
                fi

  - stage: Security
    displayName: 'Security Scanning'
    dependsOn: Build
    jobs:
      - job: SecurityScan
        displayName: 'Dependency & SAST Scan'
        steps:
          - checkout: self
          
          - task: UseDotNet@2
            inputs:
              version: $(dotnetVersion)
              
          - task: DotNetCoreCLI@2
            displayName: 'Check vulnerable packages'
            inputs:
              command: 'custom'
              custom: 'list'
              arguments: 'package --vulnerable --include-transitive'
              
          # If you have Microsoft Defender for DevOps or SonarCloud
          - task: MicrosoftSecurityDevOps@1
            displayName: 'Microsoft Security DevOps'
            continueOnError: true

  - stage: DeployStaging
    displayName: 'Deploy to Staging'
    dependsOn: Security
    condition: and(succeeded(), eq(variables['Build.SourceBranch'], 'refs/heads/main'))
    jobs:
      - deployment: DeployStaging
        displayName: 'Deploy to Staging'
        environment: 'staging'
        strategy:
          runOnce:
            deploy:
              steps:
                - task: AzureWebApp@1
                  displayName: 'Deploy to Azure App Service'
                  inputs:
                    azureSubscription: '$(azureServiceConnection)'
                    appType: 'webApp'
                    appName: '$(stagingAppName)'
                    package: '$(Pipeline.Workspace)/**/*.zip'

Key differences: GitHub Actions vs Azure DevOps

Aspect GitHub Actions Azure DevOps
Syntax YAML with jobs YAML with stages and jobs
Environments environment: keyword Deployment jobs with environment:
Secrets Repository/org secrets Variable groups, Key Vault
Logging echo "::error::" ##vso[task.logissue]
Artifacts actions/upload-artifact PublishPipelineArtifact task
Approvals Environment protection rules Stage gates and approvals

Pro tip: Many Dutch enterprises use Azure DevOps for the tighter Azure integration, built-in boards, and compliance features. GitHub Actions is simpler for open-source or GitHub-native workflows.


Section 4: Advanced architectural patterns

As your application grows, the monolith from Part 2 may need to evolve. Here’s how spec-driven development adapts to advanced patterns.

Pattern #1: Modular monolith

When to use: Application growing, but not ready for microservices.

Constitution update:

## Architecture: Modular Monolith

### Module Boundaries
Each module is a separate project/assembly with:
- Own data access (no cross-module database queries)
- Public API via interfaces only
- Internal implementation hidden

### Modules
- `TeamTaskManager.Users` - Authentication, profiles
- `TeamTaskManager.Teams` - Team management
- `TeamTaskManager.Tasks` - Task CRUD and workflows
- `TeamTaskManager.Notifications` - Email, push notifications

### Communication
- Modules communicate via defined interfaces
- No direct database access across modules
- Events for async communication (MediatR)

Spec pattern:

## Feature: Task Assignment Notification

**Module**: Tasks (primary), Notifications (consumer)

**Given** a task is assigned to a user
**When** the assignment is saved
**Then** Tasks module publishes `TaskAssignedEvent`
**And** Notifications module sends email to assignee

Pattern #2: Backend for Frontend (BFF)

When to use: Multiple clients (web, mobile, third-party) need different APIs.

Constitution update:

## Architecture: Backend for Frontend

### BFF Services
- `TeamTaskManager.WebBFF` - Optimized for Blazor web app
- `TeamTaskManager.MobileBFF` - Optimized for mobile (future)
- `TeamTaskManager.PublicAPI` - Third-party integrations

### Core Services
- BFFs call shared core services
- Core services own business logic
- BFFs handle client-specific concerns (aggregation, formatting)

Plan pattern:

## API Architecture

### Web BFF Endpoints
Optimized for single-page load:
- `GET /web/dashboard` → Returns user, teams, tasks in one call
- `GET /web/team/{id}` → Returns team with members and recent tasks

### Mobile BFF Endpoints (Future)
Optimized for bandwidth:
- `GET /mobile/sync` → Delta sync since last update
- Compressed responses, minimal payload

### Public API
RESTful, versioned, rate-limited:
- `GET /api/v1/tasks` → Standard REST
- OAuth 2.0 authentication

Pattern #3: Event-driven architecture

When to use: Need loose coupling, async processing, audit trails.

Constitution update:

## Architecture: Event-Driven

### Event Bus
- Use Azure Service Bus / RabbitMQ / MassTransit
- All state changes published as events
- Events are immutable facts

### Event Patterns
- **Domain Events**: `TaskCreated`, `TaskCompleted`, `MemberInvited`
- **Integration Events**: Cross-service communication
- **Event Sourcing**: Optional, for audit-critical features

### Guarantees
- At-least-once delivery (consumers must be idempotent)
- Events include correlation ID for tracing

Spec pattern:

## Event: TaskCompleted

**Published when**: User marks task as complete

**Payload:**
```json
{
  "eventId": "uuid",
  "eventType": "TaskCompleted",
  "timestamp": "2026-01-26T10:30:00Z",
  "correlationId": "uuid",
  "data": {
    "taskId": "uuid",
    "completedBy": "userId",
    "teamId": "uuid"
  }
}

Consumers:

  • Notifications: Send completion email to task creator
  • Analytics: Update team productivity metrics
  • Audit: Log completion event ```

Pattern #4: Microservices (proceed with caution)

When to use: Large team (10+ developers), clear domain boundaries, need independent deployment.

⚠️ Warning: Don’t start with microservices. Extract them from a working monolith when you have clear reasons.

Constitution update:

## Architecture: Microservices

### Services
- `users-service` - Authentication, profiles (owns users DB)
- `teams-service` - Team management (owns teams DB)
- `tasks-service` - Task management (owns tasks DB)
- `notifications-service` - All notifications (stateless)

### Communication
- Sync: gRPC for internal, REST for external
- Async: Azure Service Bus for events
- No shared databases (each service owns its data)

### Deployment
- Each service independently deployable
- Kubernetes for orchestration
- Service mesh for observability (Istio/Linkerd)

### Data Consistency
- Eventual consistency between services
- Saga pattern for distributed transactions
- Outbox pattern for reliable event publishing

Choosing the right pattern

Pattern Team Size Complexity When to Choose
Monolith 1-5 Low Starting out, validating product
Modular Monolith 3-10 Medium Growing, need structure
BFF 5-15 Medium Multiple client types
Event-Driven 5-20 High Async workflows, audit needs
Microservices 10+ Very High Clear domains, independent scaling

The spec-driven advantage: Your constitution documents architectural decisions. When you evolve from monolith to modular to microservices, the spec history shows why.


Section 5: Scaling strategies

When your application outgrows the initial architecture

The Team Task Manager from Part 2 works great for 100 users. What about 10,000? 100,000?

Strategy #1: Horizontal scaling

Constitution update:

## Scaling Requirements

### Stateless Application
- No in-memory session state
- Use distributed cache (Redis) for session
- Any instance can handle any request

### Database Scaling
- Read replicas for query-heavy operations
- Connection pooling required
- Consider read/write splitting at 10k users

Strategy #2: Caching layers

Spec pattern:

## Performance: Task List Caching

**Given** a user views their team's task list
**When** the list was fetched < 30 seconds ago
**Then** return cached result (skip database)

**Cache invalidation:**
- Task created → Invalidate team's task list cache
- Task updated → Invalidate specific task + team list cache
- Team membership changed → Invalidate all team caches

**Cache implementation:**
- L1: In-memory (IMemoryCache), 10 second TTL
- L2: Distributed (Redis), 30 second TTL

Strategy #3: Background processing

Constitution update:

## Background Jobs

### Job Queue
- Use Hangfire / Azure Functions / AWS Lambda
- Long-running operations MUST be async

### Job Types
- Email sending (< 1 minute)
- Report generation (< 5 minutes)  
- Data export (< 30 minutes)

### Retry Policy
- 3 retries with exponential backoff
- Dead letter queue for failed jobs
- Alert on repeated failures

Section 6: Team communication patterns

Keeping everyone aligned

Spec-driven development generates artifacts. Those artifacts need to be communicated.

Pattern #1: Spec review meetings

Weekly, 30 minutes:

  1. Spec changes this week (5 min)
    • What was added/modified/removed?
  2. Plan deviations (10 min)
    • Any architectural decisions that deviated from plan?
    • Update plan.md to reflect reality
  3. Constitution amendments (10 min)
    • Any new constraints discovered?
    • Any constraints that need relaxing?
  4. Next week’s focus (5 min)
    • Which user stories are in flight?

Pattern #2: Async spec updates

For distributed teams:

<!-- In PR description -->

## Spec Changes

### Added
- User story: Password-less authentication (magic links)
- Edge case: Handle expired magic links gracefully

### Modified  
- Authentication flow now supports both password and magic link

### Constitution Impact
- None (existing security requirements cover magic links)

### Reviewers
- @tech-lead - Constitution compliance
- @product-owner - Spec accuracy
- @security-team - Authentication changes

Pattern #3: Decision records

When specs change significantly, document why:

<!-- docs/decisions/004-magic-link-auth.md -->

# ADR-004: Add Magic Link Authentication

## Status
Accepted

## Context
Users forget passwords. Password reset flow has 40% abandonment rate.

## Decision
Add magic link (email-based) authentication as alternative to passwords.

## Consequences
- Positive: Reduced friction, fewer support tickets
- Negative: Email deliverability becomes critical path
- Neutral: Both auth methods coexist

## Spec Reference
- spec.md: Section "Authentication" updated
- plan.md: Email service now critical infrastructure

Key takeaways from Part 4

# Takeaway
1 Teams need workflows - Feature branches or trunk-based, pick one and commit
2 Automate validation - CI/CD should enforce constitution and spec compliance
3 Architecture evolves - Start simple, extract complexity when needed
4 Document decisions - Specs + ADRs = traceable architecture history
5 Communication matters - Artifacts are useless if the team doesn’t read them

What’s next

In Part 5 (next week), we’ll wrap up the series with:

  • Real case studies - Actual projects built with spec-driven development
  • Metrics and outcomes - What improved, what didn’t
  • Lessons learned - Mistakes made, wisdom gained
  • The future - Where AI-assisted development is heading

Resources

Resource Description
Spec-Kit GitHub Official toolkit
GitHub Actions Docs CI/CD for GitHub
Azure Pipelines Docs CI/CD for Azure DevOps
Modular Monolith Architecture pattern guide
ADR Templates Architecture Decision Records

Series navigation


💬 Using spec-driven development with your team?

I’d love to hear your experience. Connect with me on LinkedIn.

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Written by

Hidde de Smet

As a certified Azure Solution Architect, I specialize in designing, implementing, and managing cloud-based solutions using Scrum and DevOps methodologies.

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