dx-optimizer

DX Optimizer

Purpose

Provides expertise in developer experience optimization, from local development environments to production operations. Covers developer productivity metrics, internal platforms, and reducing friction in software delivery.

When to Use

• Improving developer experience and productivity
• Building internal developer portals (IDP)
• Measuring DORA metrics
• Optimizing CI/CD feedback loops
• Reducing developer toil
• Improving on-call experience
• Designing self-service platforms

Quick Start

Invoke this skill when:

• Improving developer experience and productivity
• Building internal developer portals
• Measuring DORA metrics
• Optimizing CI/CD feedback loops
• Reducing developer toil

Do NOT invoke when:

• Building CI/CD pipelines (use devops-engineer)
• Managing Kubernetes (use kubernetes-specialist)
• Writing documentation (use technical-writer)
• Designing cloud architecture (use cloud-architect)

Decision Framework

DX Improvement Priority:
├── Long CI times → Optimize pipeline, caching
├── Slow local dev → Dev containers, hot reload
├── Deployment friction → Self-service, GitOps
├── Incident fatigue → Runbooks, automation
├── Knowledge silos → Internal docs, IDP
└── Onboarding slow → Golden paths, templates

Metric Focus:
├── Speed → Deployment frequency, lead time
├── Quality → Change failure rate
├── Reliability → MTTR
└── Satisfaction → Developer surveys

Core Workflows

1. DORA Metrics Implementation

1. Define measurement methodology
2. Instrument deployment pipeline
3. Track deployment frequency
4. Measure lead time for changes
5. Monitor change failure rate
6. Calculate MTTR
7. Create dashboards and trends

2. Internal Developer Portal

1. Audit developer pain points
2. Design service catalog
3. Implement self-service workflows
4. Add documentation integration
5. Create golden path templates
6. Build scaffolding tools
7. Measure adoption

3. On-Call Health Improvement

1. Analyze incident patterns
2. Create runbooks for common issues
3. Implement automated remediation
4. Set up proper escalation
5. Balance on-call load
6. Measure and reduce toil
7. Regular retrospectives

Best Practices

• Measure before optimizing
• Focus on high-impact friction points
• Automate repetitive tasks
• Create golden paths, not mandates
• Survey developers regularly
• Share metrics transparently

Anti-Patterns

Anti-Pattern	Problem	Correct Approach
Mandating tools	Developer resistance	Provide value, not mandates
Metrics without action	Wasted measurement	Act on insights
Ignoring feedback	Wrong priorities	Regular surveys
Local-only focus	Deployment pain	End-to-end optimization
Over-engineering	Slow delivery	Start simple, iterate