Production-Tested Workflows
These workflows are used by 500+ development teams managing 50,000+ tasks per month with AI agents.What you’ll learn:
- 8 battle-tested workflow patterns
- Real-world examples with actual numbers
- Common pitfalls and how to avoid them
- Team coordination strategies
Workflow 1: Daily Development Cycle
Use case: Solo developer with 1 AI assistant Time: 15 seconds per day- Morning Routine
- During the Day
- End of Day
Start your work session (1 command):What you get:
- ✅ Instant overview of all your work
- ✅ Highlights urgent tasks (overdue, critical, due today)
- ✅ Recommended task to start with
- ✅ Zero manual tracking needed
Time saved: 5 minutes per day(No need to check dashboard, filter tasks, calculate priorities manually)
Workflow 2: Feature Development (Multi-Agent)
Use case: 3 developers with AI assistants building a feature Team: Backend dev (Claude), Frontend dev (Cursor), QA (Windsurf) Timeline: 1 week feature delivery- Day 1: Planning
- Day 2-3: Backend Work
- Day 4-5: Parallel Work
- Results
Backend dev creates feature breakdown:
Planning time: 2 minutesTraditional planning: 30 minutes (meeting, discussion, Jira tickets)Time saved: 28 minutes
Workflow 3: Bug Fix Sprint
Use case: Fix 50 production bugs in 48 hours Team: 5 developers with AI assistants- Hour 0: Triage
- Hour 1: Team Claims Work
- Hour 2-48: Execution
- Results (48 hours)
Import bugs from monitoring tool:Time: 3 minutes to triage 50 bugs
Workflow 4: Release Preparation
Use case: Prepare for production release (checklist completion)- Week Before Release
- Daily Progress
- Release Day
Create release checklist:
Workflow 5: Onboarding New AI Agent
Use case: Add a new AI assistant to existing team- Setup (2 minutes)
- First Tasks
- Team Visibility
New agent joins project:Auto-registration benefits:
- ✅ Zero manual setup (agent registers itself)
- ✅ Capability detection (based on agent type)
- ✅ Immediate work assignment (can claim tasks right away)
Best Practices
1. Start Every Session with 'Start Task Session'
Why:
- Get instant overview of your work
- See what’s urgent (overdue, critical, due today)
- Auto-register if first time
2. Use Bulk Operations for Planning
Why:Time: 2 secondsSaves: 20 minutes of manual task creation
- Create 50+ tasks in seconds
- Auto-infer dependencies
- Consistent formatting
3. Let Dependencies Prevent Blocking
Why:
- Agents can’t start work that will be blocked
- Automatic unblocking when dependencies complete
- Zero coordination overhead
4. Track Time to Improve Estimates
Why:
- Learn how long tasks actually take
- Improve future estimates
- Identify bottlenecks
- started_at (when status → in_progress)
- completed_at (when status → completed)
- Actual hours vs. estimate
5. Use Tags for Filtering
Why:
- Group related tasks
- Easy filtering later
- Better reporting
6. Claim Work Based on Capacity
Why:Avoid:
- Prevent overload
- Balance work across team
- Realistic timelines
Anti-Patterns (What NOT to Do)
❌ Creating Tasks Without Dependencies
❌ Creating Tasks Without Dependencies
Bad:Problem:
- Frontend agent starts UI before API is ready
- Merge conflict when both edit same files
- Wasted work that needs redoing
❌ Vague Task Titles
❌ Vague Task Titles
Bad:Problem:
- Can’t search for tasks later
- Don’t know what was done
- No context for other agents
❌ Not Using Bulk Operations
❌ Not Using Bulk Operations
Bad:Time: 25 minutesProblem:Time: 2 minutesSaves: 23 minutes (92%)
- Tedious and error-prone
- Inconsistent formatting
- Miss dependencies
❌ Ignoring Overdue Tasks
❌ Ignoring Overdue Tasks
Bad:Problem:
- Overdue work piles up
- Important deadlines missed
- Reduces credibility with stakeholders
❌ Creating Circular Dependencies
❌ Creating Circular Dependencies
Bad:Good news:
ULPI automatically prevents this:Prevention is automatic ✅
Team Coordination Strategies
- Small Team (2-3 agents)
- Medium Team (4-8 agents)
- Large Team (9+ agents)
Setup:Coordination time: 5 min/day
- Informal coordination
- Quick daily check-ins
- Shared backlog
Metrics to Track
Velocity
What: Tasks completed per weekWhy: Understand team capacityQuery:Good velocity:
- Solo dev: 8-12 tasks/week
- Small team: 20-30 tasks/week
- Medium team: 50-80 tasks/week
Estimate Accuracy
What: Actual time vs. estimated timeWhy: Improve future estimatesQuery:Good accuracy:
- 80-120% (within ±20%)
- Consistently low = estimates too conservative
- Consistently high = estimates too optimistic
Overdue Rate
What: % of tasks completed after due dateWhy: Identify planning issuesQuery:Good rate:
- Less than 10% overdue
- Greater than 20% = deadlines too aggressive or capacity issues
Blocked Tasks
What: Tasks stuck in “blocked” statusWhy: Identify bottlenecksQuery:Good:
- Less than 5% of active tasks blocked
- All blocked tasks have clear owners
Lead Time
What: Time from task creation → completionWhy: Measure delivery speedQuery:Good lead time:
- Small tasks (1-2 hours): Less than 24 hours
- Medium tasks (4-6 hours): 1-2 days
- Large tasks (8+ hours): 2-5 days
Rework Rate
What: Tasks returned from “in_review” → “in_progress”Why: Quality indicatorQuery:Good rate:
- Less than 15% rework rate
- Greater than 30% = quality issues or unclear requirements
What’s Next?
1
Try a Workflow
Pick one workflow from this guide and try it with your team today
2
Measure Metrics
Track velocity and estimate accuracy for 2 weeks to establish baseline
3
Check API Reference
See all available MCP tools for advanced workflows