Handbook
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AI & Modern Tools
Modern Development Tools
The right tools accelerate development dramatically. Here's what to use.
Modern development tools have transformed what small engineering teams can accomplish. Infrastructure that once required dedicated teams is now available as services. Deployment that took days happens in minutes. Tooling that improves developer experience directly improves velocity and quality. Choosing the right tools and using them well is a significant competitive advantage.
The Modern Stack Philosophy
Services Over Infrastructure
Modern approach:
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Use managed services
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Focus on business logic
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Let others handle infrastructure
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Pay for what you use
Developer Experience Matters
Good DX means:
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Faster iteration
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Fewer errors
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Better code
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Happier engineers
Invest in developer experience.
Build vs. Buy
Default to buy (or use):
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Maintained by experts
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Scales automatically
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Quicker to implement
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Focus on differentiation
Build when:
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Core to competitive advantage
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No good solution exists
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Unique requirements
Development Environment
Code Editors
Modern editors:
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VS Code (dominant)
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JetBrains IDEs
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AI-enhanced (Cursor, etc.)
Features that matter:
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Extensions/plugins
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AI integration
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Language support
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Performance
AI Coding Assistants
Tools like:
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GitHub Copilot
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Cursor
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Claude/ChatGPT
Use for:
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Code completion
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Documentation
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Refactoring
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Problem solving
Local Development
Modern local dev:
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Containers (Docker)
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Local environments that match production
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Fast feedback loops
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Easy setup for new team members
Version Control and Collaboration
Git and Platforms
GitHub, GitLab, or Bitbucket:
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Central to modern development
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More than just code storage
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Project management features
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CI/CD integration
Branching Strategies
Options:
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Trunk-based: Main branch focus, short-lived branches
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Git Flow: Develop, feature, release branches
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GitHub Flow: Simple main + feature branches
Start simple. Add complexity if needed.
Code Review
Good code review:
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Pull requests standard
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Clear review expectations
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Timely feedback
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Constructive comments
CI/CD (Continuous Integration/Deployment)
Why CI/CD Matters
Benefits:
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Automated testing
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Consistent deployment
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Fast feedback
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Reduced manual work
CI/CD Tools
Options:
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GitHub Actions (integrated with GitHub)
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CircleCI
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GitLab CI
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Cloud-native (AWS CodePipeline, etc.)
Pipeline Components
Typical pipeline:
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Build
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Test
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Security scan
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Deploy to staging
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Deploy to production
Deployment Strategies
Approaches:
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Direct: Push to production
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Blue-green: Switch between environments
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Canary: Gradual rollout
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Feature flags: Control feature visibility
Start simple, add sophistication as needed.
Infrastructure and Hosting
Cloud Platforms
Major options:
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AWS (most comprehensive)
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Google Cloud (data/ML strength)
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Azure (enterprise/Microsoft)
For startups, often:
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Vercel (frontend)
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Railway, Render, Fly.io (backend)
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Serverless options
Containers and Orchestration
Containers (Docker):
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Consistent environments
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Easy deployment
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Scalable
Kubernetes:
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Powerful but complex
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Often overkill for startups
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Consider managed services (EKS, GKE)
Serverless
Functions without managing servers:
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AWS Lambda
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Vercel Functions
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Cloudflare Workers
Good for:
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Scaling to zero
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Event-driven workloads
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Simple APIs
Databases
Managed databases:
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Postgres: PlanetScale, Supabase, RDS
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Document: MongoDB Atlas, DynamoDB
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Redis: Upstash, Redis Cloud
Use managed. Don’t run your own databases.
Monitoring and Observability
Why It Matters
You need to:
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Know when things break
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Understand performance
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Debug problems
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Plan capacity
Key Components
Logging: Application logs, structured logging
Metrics: Performance data, business metrics
Tracing: Request flow across services
Alerting: Notification when problems occur
Tools
Common options:
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Datadog (comprehensive)
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Sentry (error tracking)
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LogRocket (frontend monitoring)
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Custom dashboards (Grafana)
What to Monitor
Start with:
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Error rates
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Response times
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Resource usage
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Business metrics
Testing Tools
Testing Types
Unit tests: Test individual functions
Integration tests: Test components together
End-to-end tests: Test full user flows
Performance tests: Test under load
Testing Frameworks
Language-specific:
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JavaScript: Jest, Vitest, Playwright
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Python: pytest
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Go: built-in testing
Test Automation
Automated testing:
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Run on every commit
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Part of CI pipeline
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Gate for deployment
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Coverage tracking
Communication and Documentation
Team Communication
Tools:
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Slack (dominant)
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Discord
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Microsoft Teams
Integrate with development tools.
Documentation
Options:
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Notion (collaborative)
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Confluence
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GitHub/GitLab wikis
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Docs-as-code
Document:
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Architecture decisions
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Setup instructions
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API documentation
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Runbooks
Issue Tracking
Tools:
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Linear (modern, fast)
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GitHub Issues
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Jira (enterprise)
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Asana
Keep close to code when possible.
Choosing Tools
Selection Criteria
Evaluate:
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Does it solve the actual problem?
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Will the team use it?
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What’s the cost (money and time)?
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How does it integrate?
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What’s the lock-in?
Avoiding Tool Sprawl
Too many tools create:
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Cognitive overhead
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Integration challenges
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Cost accumulation
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Maintenance burden
Choose deliberately. Consolidate when possible.
Team Adoption
Tools only work if used:
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Choose tools team will adopt
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Provide training
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Lead by example
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Gather feedback
Building Your Stack
Starter Stack
For most startups:
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Version control: GitHub
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CI/CD: GitHub Actions
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Hosting: Vercel/Railway/Render
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Database: Managed Postgres
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Monitoring: Sentry + basic cloud monitoring
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Communication: Slack
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Docs: Notion or GitHub
Evolving the Stack
As you grow:
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Add sophistication where needed
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Improve observability
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Scale infrastructure
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Specialized tools for new needs
Don’t over-engineer early.
Key Takeaways
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Modern development uses managed services; focus on business logic, not infrastructure
•
Developer experience directly impacts velocity—invest in it
•
Default to buy/use existing tools; build only when core to competitive advantage
•
AI coding assistants are now essential; integrate them into workflow
•
CI/CD is non-negotiable: automated testing, consistent deployment, fast feedback
•
Use managed databases; don’t run your own
•
Monitoring and observability: know when things break, understand performance
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Avoid tool sprawl; choose deliberately, consolidate where possible
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Starter stack for most: GitHub, GitHub Actions, Vercel/Railway, managed Postgres, Sentry, Slack
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Start simple, add sophistication as needed; don’t over-engineer early
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