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Planning Overview ​

Effective planning ensures YeboLearn ships high-impact features while maintaining technical excellence. Our planning process balances stakeholder needs, technical constraints, and market opportunities.

Planning Philosophy ​

User-Centered Development ​

Every feature starts with a clear user need:

  • Students: Better learning outcomes, engaging experiences
  • Teachers: Efficient content creation, insightful analytics
  • Parents: Progress visibility, value for money
  • Administrators: Platform management, reporting

Competitive Advantage ​

  • AI-First: 15+ AI features, zero African competitors with AI
  • Speed to Market: Bi-weekly releases keep us ahead
  • Quality at Scale: 70%+ test coverage, 99.9% uptime
  • Technical Debt Management: 20% capacity for refactoring

Data-Driven Decisions ​

Metrics That Matter:

typescript
// Feature success metrics
{
  adoption: '% of users engaging with feature',
  retention: 'Impact on user retention',
  performance: 'Revenue or learning outcome improvement',
  technical: 'System impact (load, errors, costs)'
}

Decision Framework:

  1. Does it improve learning outcomes?
  2. Does it differentiate us from competitors?
  3. Can we build it with quality in 2 weeks?
  4. What's the maintenance cost?
  5. Does it align with our roadmap?

Sprint Planning Process ​

Two-Week Sprint Cycle ​

Week 1: Development Sprint

Monday (10 AM - 12 PM): Sprint Planning
├─ Review last sprint's outcomes
├─ Present new features and priorities
├─ Break down stories into tasks
├─ Estimate effort (story points)
├─ Commit to sprint goals
└─ Assign initial work

Tuesday-Friday: Active Development
├─ Daily standups (9:30 AM, 15 min)
├─ Pair programming sessions
├─ Code reviews
├─ Feature testing in dev
└─ Mid-sprint check-in (Wednesday PM)

Week 2: Release Sprint

Monday: Integration & Testing
├─ Features merged to staging
├─ QA validation
├─ Stakeholder demos
└─ Bug fixes

Tuesday-Wednesday: Release Prep
├─ Final testing
├─ Documentation updates
├─ Deployment planning
└─ Release notes preparation

Thursday: Production Release
├─ Deploy at 10 AM
├─ Monitor for issues
├─ Hotfix if needed
└─ Validate in production

Friday: Reflection & Planning
├─ Sprint retrospective (2 PM)
├─ Review metrics and feedback
├─ Backlog refinement
└─ Next sprint preview

Sprint Ceremonies ​

Daily Standup (9:30 AM, 15 minutes)

Format:

  • What shipped yesterday
  • What's shipping today
  • Any blockers

Example:

Sarah: Yesterday I completed the AI quiz generator API. Today I'm
adding rate limiting and writing tests. No blockers.

John: Finished the payment integration tests yesterday. Today I'm
reviewing Sarah's PR and starting the student dashboard refactor.
Blocked on design specs for the dashboard.

Lisa: I'll unblock John by sharing the Figma designs by 11 AM.
Yesterday I finalized the essay grading UI. Today implementing
the feedback display component.

Sprint Planning (Monday 10 AM, 2 hours)

Agenda:

  1. Review last sprint (15 min)

    • What went well
    • What didn't ship
    • Key learnings

  2. Present prioritized backlog (30 min)

    • Product owner explains features
    • Team asks clarifying questions
    • Dependencies identified

  3. Break down and estimate (60 min)

    • Split large features into tasks
    • Estimate effort (story points)
    • Identify technical risks

  4. Sprint commitment (15 min)

    • Select stories to commit
    • Define sprint goal
    • Assign initial ownership

Sprint Retrospective (Friday 2 PM, 1 hour)

Format:

  • What went well? (15 min)
  • What could improve? (15 min)
  • Action items (20 min)
  • Celebrate wins (10 min)

Focus Areas:

  • Process improvements
  • Technical debt addressed
  • Team collaboration
  • Tool and workflow efficiency

Feature Prioritization ​

Priority Matrix ​

High Value + Easy Implementation = DO NOW
├─ AI quiz autogeneration
├─ Student progress dashboard
└─ Mobile app performance boost

High Value + Hard Implementation = PLAN CAREFULLY
├─ Offline mode for rural areas
├─ Advanced AI essay grading
└─ WhatsApp integration

Low Value + Easy Implementation = QUICK WINS
├─ UI polish and animations
├─ Email template improvements
└─ Minor bug fixes

Low Value + Hard Implementation = DON'T DO
├─ Custom theming engine
├─ Advanced social features
└─ Gamification systems

RICE Scoring Framework ​

Reach × Impact × Confidence ÷ Effort = Priority Score

Example:

typescript
{
  feature: "AI Quiz Generator",
  reach: 8000,        // Students/month who'd use it
  impact: 3,          // 1-3 scale (massive impact)
  confidence: 90,     // % confidence in estimates
  effort: 3,          // Person-weeks
  score: (8000 × 3 × 0.9) / 3 = 7200
}

{
  feature: "Custom Theming",
  reach: 1000,        // Few would use
  impact: 1,          // Low impact on outcomes
  confidence: 70,     // Unclear requirements
  effort: 4,          // Person-weeks
  score: (1000 × 1 × 0.7) / 4 = 175
}

Result: AI Quiz Generator scores 40× higher priority

Prioritization Criteria ​

Must Have (P0):

  • Critical bugs in production
  • Payment processing issues
  • Data loss or corruption risks
  • Security vulnerabilities
  • Compliance requirements

Should Have (P1):

  • High-impact AI features
  • Competitive differentiators
  • Major user experience improvements
  • Performance optimizations
  • Platform scalability

Nice to Have (P2):

  • UI polish and refinements
  • Minor feature enhancements
  • Documentation improvements
  • Developer experience tools
  • Analytics and insights

Future Consideration (P3):

  • Experimental features
  • Nice-to-have improvements
  • Low-impact additions
  • Speculative investments

Roadmap Alignment ​

Product Roadmap (Next 6 Months) ​

Q1 2026: AI Foundation

January-March
├─ AI Quiz Generator (Enhanced)
│   └─ Personalization based on student performance
├─ AI Essay Grading (Beta)
│   └─ Real-time feedback and suggestions
├─ AI Study Planner
│   └─ Adaptive scheduling based on progress
└─ Infrastructure
    ├─ Performance optimization
    └─ Monitoring enhancements

Q2 2026: Market Expansion

April-June
├─ M-Pesa Integration (Full Launch)
├─ WhatsApp Bot for Notifications
├─ Offline Mode (Rural Access)
├─ Mobile App Optimization
└─ Multi-language Support (Sesotho, Zulu)

Technical Roadmap Alignment ​

Every Sprint Includes:

  • 60% New features
  • 20% Technical debt
  • 10% Performance and optimization
  • 10% Bug fixes and polish

Technical Initiatives (Next Quarter):

  1. Database Optimization

    • Query performance tuning
    • Caching strategy implementation
    • Connection pool optimization

  2. AI Performance

    • Response time reduction (target: 3s → 1s)
    • Cost optimization (reduce API calls)
    • Prompt engineering improvements

  3. Mobile Experience

    • Progressive Web App enhancements
    • Offline capabilities
    • Load time optimization (<2s)

  4. Developer Experience

    • Improved local development setup
    • Better testing tools
    • CI/CD pipeline optimization

Stakeholder Communication ​

Weekly Updates ​

Engineering Team (Slack, Daily)

markdown
# Dev Update - November 22, 2025

Shipped Yesterday:
✅ AI quiz generator API endpoint
✅ Student dashboard performance improvements
✅ Payment webhook retry logic

Shipping Today:
🚧 Essay grading UI component
🚧 Integration tests for quiz API
🚧 Database migration for analytics

Blockers:
⚠️ Waiting on Gemini API quota increase
⚠️ Design specs needed for student profiles

Product & Leadership (Email, Weekly)

markdown
Subject: Engineering Weekly - Sprint 24 Update

Key Accomplishments:
• AI quiz generator deployed to staging (on track for release)
• Payment processing reliability improved (99.8% → 99.95%)
• Page load times reduced by 30% (3.2s → 2.2s average)

In Progress:
• AI essay grading (75% complete, launching next sprint)
• WhatsApp notification integration (30% complete)
• Mobile app performance optimization (ongoing)

Metrics:
• Deployment frequency: 12 deployments this week
• Test coverage: 73% (↑2% from last week)
• Open bugs: 8 (down from 15)
• Uptime: 99.96%

Next Week Focus:
• Complete essay grading feature
• Production release Thursday 10 AM
• Begin M-Pesa integration

All-Hands Demos (Bi-Weekly, Thursday)

  • Live feature demonstrations
  • Impact metrics and user feedback
  • Technical challenges solved
  • Upcoming priorities
  • Team wins and celebrations

Stakeholder Feedback Loop ​

Sources:

  1. User Feedback

    • Support tickets and feature requests
    • User interviews and surveys
    • Usage analytics and behavior data
    • App store reviews

  2. Business Stakeholders

    • Product owner priorities
    • Sales team insights
    • Marketing campaign needs
    • Executive strategic direction

  3. Technical Stakeholders

    • Security and compliance requirements
    • Infrastructure and cost constraints
    • Platform stability needs
    • Integration partner requirements

Processing:

Feedback Received
    ↓
Logged in Linear (with context)
    ↓
Categorized and Tagged
    ↓
Discussed in Planning
    ↓
Prioritized (RICE score)
    ↓
Scheduled or Backlogged
    ↓
Communicated to Requester

Capacity Planning ​

Team Velocity ​

Historical Velocity (Story Points/Sprint):

Sprint 20: 34 points
Sprint 21: 38 points
Sprint 22: 32 points (holiday week)
Sprint 23: 40 points
Sprint 24: 36 points

Average: 36 points/sprint
Conservative Planning: 32 points/sprint

Capacity Allocation ​

Per Sprint (2 weeks):

Total Capacity: 40 story points
├─ Planned Features: 32 points (80%)
├─ Bug Fixes: 4 points (10%)
├─ Technical Debt: 4 points (10%)
└─ Buffer (unplanned): Built into estimates

Per Developer:

2-Week Sprint = 10 working days
├─ Development: 7 days
├─ Meetings/Planning: 1 day
├─ Code Reviews: 1 day
├─ Learning/Exploration: 0.5 days
└─ Unexpected Issues: 0.5 days

Handling Interruptions ​

Unplanned Work:

  • Critical bugs: Pull from current sprint
  • Urgent features: Negotiate scope or timeline
  • Research/spikes: Time-boxed (max 1 day)
  • Support escalations: Dedicated on-call rotation

On-Call Rotation:

  • Weekly rotation among senior engineers
  • Handle critical incidents
  • Triage urgent bugs
  • Support stakeholder requests
  • Protected from sprint commitments

Planning Tools ​

Project Management ​

  • Linear: Task tracking, sprint boards, roadmap
  • GitHub Projects: Technical work tracking
  • Figma: Design specifications
  • Notion: Documentation and RFCs

Communication ​

  • Slack: Daily communication (#engineering, #product)
  • Email: Weekly updates and formal communication
  • Google Meet: Sprint planning, retros, demos
  • Loom: Async video updates and demos

Metrics and Analytics ​

  • Grafana: Engineering metrics dashboards
  • Google Analytics: User behavior and adoption
  • Sentry: Error tracking and monitoring
  • Linear Insights: Sprint velocity and completion

Best Practices ​

Effective Planning ​

Do:

  • Start with user needs and business value
  • Break large features into deliverable increments
  • Estimate conservatively, deliver incrementally
  • Document decisions and trade-offs
  • Communicate early and often
  • Celebrate wins and learn from misses

Don't:

  • Commit to impossible timelines
  • Ignore technical debt
  • Skip stakeholder communication
  • Overload sprints (leave buffer)
  • Plan in silos (collaborate cross-functionally)
  • Forget to track and adjust

Managing Scope ​

Feature Flags for Large Features:

typescript
// Ship incrementally, control rollout
if (featureFlags.aiEssayGrading.enabled) {
  return <AIEssayGrader />;
}
return <TraditionalGrader />;

MVP Approach:

  1. Define minimum viable feature
  2. Ship and learn from users
  3. Iterate based on feedback
  4. Expand to full vision

Saying No:

  • Focus on high-impact work
  • Explain trade-offs clearly
  • Offer alternatives or compromises
  • Document for future consideration

Common Planning Scenarios ​

Scenario 1: Urgent Bug Mid-Sprint ​

Process:

  1. Assess severity (P0-P3)
  2. If critical, pull from sprint immediately
  3. If not critical, add to next sprint
  4. Communicate impact on sprint goals
  5. Adjust commitments accordingly

Scenario 2: Feature Taking Longer ​

Process:

  1. Identify why (scope, complexity, blockers)
  2. Communicate to stakeholders early
  3. Options:
    • Reduce scope for this sprint
    • Move to next sprint
    • Add resources (pair programming)
  4. Update timeline expectations

Scenario 3: New Opportunity Arises ​

Process:

  1. Evaluate against current priorities (RICE)
  2. Determine urgency (can it wait 2 weeks?)
  3. If truly urgent, negotiate scope trade-off
  4. If not urgent, add to backlog for next planning
  5. Document decision and rationale

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