6 min read • Guide 153 of 877
Developer Workflow Optimization
Every friction point in a developer's workflow compounds over time. A workflow that takes an extra 5 minutes per task costs hours per week. Optimizing workflows means identifying bottlenecks, eliminating unnecessary steps, and automating everything possible.
Common Workflow Bottlenecks
| Bottleneck | Impact | Solution |
|---|---|---|
| Slow CI | Wait for feedback | Parallelize, cache |
| Manual deploy | Risk, time | Automate fully |
| Long review queue | Blocked work | Review SLAs |
| Unclear requirements | Rework | Definition of Ready |
| Environment issues | Context switching | Docker/containers |
Workflow Mapping
Current State Analysis
WORKFLOW MAPPING EXERCISE
═════════════════════════
STEP 1: Document Current Flow
─────────────────────────────────────
Map every step from task to production:
1. Task assigned in GitScrum
2. Developer reads task
3. Developer asks clarifying question
4. [Wait for answer - avg 4 hours]
5. Create branch
6. Set up local environment
7. [Debug environment issue - avg 30 min]
8. Develop feature
9. Write tests
10. Run tests locally
11. Push code
12. [Wait for CI - avg 15 min]
13. Create PR
14. Request review
15. [Wait for review - avg 12 hours]
16. Address feedback
17. [Wait for re-review - avg 8 hours]
18. Merge
19. [Wait for deploy - avg 2 hours]
20. Verify in production
STEP 2: Identify Wait Times
─────────────────────────────────────
Total active time: 6 hours
Total wait time: 26 hours
Efficiency: 19%
BIGGEST WAITS:
├── Review wait: 20 hours (77%)
├── Answer wait: 4 hours (15%)
└── CI + deploy: 2.25 hours (8%)
Optimized Workflow
OPTIMIZED DEVELOPER WORKFLOW
════════════════════════════
BEFORE CODING:
├── Task has clear acceptance criteria ✓
├── Questions answered before assignment ✓
├── Environment always ready (Docker) ✓
└── Branch auto-created from task ✓
DURING CODING:
├── IDE integration shows task details
├── Tests run on save (watch mode)
├── Linting auto-fixes on save
├── Hot reload for fast feedback
└── AI assistance available
SUBMITTING CODE:
├── Pre-push hooks catch issues
├── CI runs in parallel (<5 min)
├── PR auto-created with template
├── Reviewers auto-assigned
└── Slack notification sent
CODE REVIEW:
├── 4-hour review SLA
├── Small PRs (<200 lines)
├── Auto-approve safe changes
├── Bot handles style issues
└── One approval required
DEPLOYMENT:
├── Merge = auto-deploy to staging
├── Smoke tests run automatically
├── Production deploy triggered
├── Rollback automated if needed
└── Task auto-closed on deploy
Optimization Strategies
Reducing Wait Times
REDUCING WAIT TIMES
═══════════════════
CODE REVIEW BOTTLENECK:
─────────────────────────────────────
Problem: 12+ hour average review wait
Solutions:
├── Review SLA: 4 hours max
├── Smaller PRs: <200 lines
├── Review rotation schedule
├── Pair/mob programming (no PR needed)
├── Auto-approve safe changes
└── Bot for style/formatting
Implementation:
1. Add review time to team dashboard
2. Set up review rotation
3. Slack reminder after 4 hours
4. Track and celebrate improvement
CI PIPELINE BOTTLENECK:
─────────────────────────────────────
Problem: 15+ minute CI runs
Solutions:
├── Parallel test execution
├── Dependency caching
├── Selective test runs (only changed)
├── Faster machines
├── Split into stages
└── Fail fast on obvious issues
Implementation:
1. Profile current pipeline
2. Add caching for dependencies
3. Parallelize test suites
4. Run lint/type check first
5. Target: <5 min for feedback
Automating Repetitive Tasks
AUTOMATION OPPORTUNITIES
════════════════════════
TASK → CODE:
├── Branch naming from task ID
├── Commit message templates
├── PR description from task
└── Automatic task linking
CODE → REVIEW:
├── Auto-assign reviewers
├── Auto-label by file type
├── Auto-run relevant tests
└── Style check automation
REVIEW → DEPLOY:
├── Auto-merge when approved
├── Auto-deploy to staging
├── Automated smoke tests
├── Production deploy pipeline
└── Auto-close task on deploy
EXAMPLE AUTOMATION:
─────────────────────────────────────
# .github/workflows/auto-deploy.yml
on:
pull_request:
types: [closed]
jobs:
deploy:
if: github.event.pull_request.merged
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: ./deploy-staging.sh
- run: ./run-smoke-tests.sh
- run: ./deploy-production.sh
- run: ./update-task-status.sh
Environment Optimization
DEVELOPMENT ENVIRONMENT
═══════════════════════
CONTAINERIZED DEVELOPMENT:
─────────────────────────────────────
# docker-compose.yml
services:
app:
build: .
volumes:
- .:/app
ports:
- "3000:3000"
environment:
- DATABASE_URL=postgres://db/app
depends_on:
- db
- redis
db:
image: postgres:15
volumes:
- db_data:/var/lib/postgresql/data
redis:
image: redis:alpine
BENEFITS:
├── Same env for all developers
├── No "works on my machine"
├── New dev setup in minutes
├── Matches production
└── Easy to reset
FAST SETUP:
─────────────────────────────────────
# New developer onboarding
git clone repo
docker-compose up
# Ready to code in 5 minutes
GitScrum Workflow Integration
Task Workflow Automation
GITSCRUM WORKFLOW AUTOMATION
════════════════════════════
TASK LIFECYCLE:
─────────────────────────────────────
Ready to Start
↓ Developer clicks "Start"
↓ Branch created automatically
↓ Status → In Progress
↓
In Progress
↓ Developer pushes code
↓ PR created (linked to task)
↓
In Review
↓ PR approved and merged
↓ Status → Done automatically
↓
Done
↓ Deployed to production
↓ Archived after 7 days
NO MANUAL STATUS UPDATES NEEDED
INTEGRATIONS:
├── GitHub: PR/commit linking
├── Slack: Notifications
├── CI/CD: Status updates
└── IDE: Task visibility
Best Practices
For Workflow Optimization
- Map before optimizing — Understand current state
- Measure wait times — Data drives decisions
- Automate ruthlessly — Eliminate manual steps
- Reduce batch sizes — Smaller = faster
- Iterate continuously — Never done improving
Anti-Patterns
WORKFLOW MISTAKES:
✗ Optimizing without measuring
✗ Adding steps without removing
✗ Manual processes that could automate
✗ Long review/approval chains
✗ Large batch sizes
✗ Unclear handoffs
✗ Environment inconsistency
✗ Ignoring developer feedback