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Estimation Model & Optimization (VEMO)

The AI Productivity & Cost Placebo

You feel 2x faster. Reality: 10-15% gains with 22% hidden costs you don't see.

AI code churns 3x more than human code, delivery stability drops 7%, and rework costs mount silently.

What developers perceive as productivity gains, your metrics reveal as mounting technical debt.
See Your Hidden Costs →
PERCEPTION
REALITY
Perceived Speed Improvement
What You Feel
2x
→
Actual (Research)
15%
AI Code Churn Rate
Human Code
~20%
→
AI Code
~61%
Delivery Stability
Expected
0%
→
Actual Change
-7.2%
100%
COST VISIBILITY
+
22%
HIDDEN COST
Sources: Industry Research Studies • GitClear • DORA (Google Cloud)

Why Your Estimates Are Always Wrong

Traditional estimation models (velocity, story points, Function Point, COCOMO) were built for human developers. They break with AI-generated code.

Legacy Metrics
📊
Sprint Velocity
Story points per sprint
🚀
Features Shipped
Number of features deployed
✅
Initial Quality
Code quality at first commit
😊
Dev Satisfaction
How developers feel about speed
⚡
Time to First Commit
How fast code is written
🔄
Cycle Time
Time from commit to deploy
VEMO Metrics
🔄
Code Churn Rate
How often code gets rewritten
⏱️
Review Overhead
Extra time reviewing AI code
📈
Technical Debt
Accumulating maintenance burden
🔧
Post-Deploy Fixes
Bugs caught after deployment
🔍
Duplicate Code
AI-generated redundant patterns
🤖
AI Code Percentage
How much code is AI-generated
⚠️
The Estimation Blindspot: Your sprint planning uses velocity that ignores 60% code churn, 30% rework time, and compounding technical debt. Every estimate is wrong from day one — timelines slip, budgets balloon, and nobody knows why.

How Hidden Costs Compound Over Time

Two simultaneous crises unfold when estimation models ignore reality

Wave 1
Wave 2
Wave 3
VELOCITY:
32 pts/sprint
  • Celebrating wins
  • Bold commitments
✓ Success
→
28 pts/sprint
  • Slowing down
  • More rework
⚠ Concern
→
18 pts/sprint
  • Fighting debt
  • Major delays
🔥 Crisis
TEAM SKILLS:
  • Strong fundamentals
  • Code review rigor
  • Mentoring juniors
✓ Healthy
→
  • Accept AI blindly
  • Copy-paste habits
  • Skipping reviews
⚠ Erosion
→
  • Can't debug alone
  • Senior eng quit
  • Innovation stalls
🔥 Collapse

How VEMO Fixes Estimation

A new estimation model built for the AI development era

🔍
Capture
Intercepts all AI-generated code at commit time
🧠
Analyze
Measures quality, churn, duplicates, and maintainability
📊
Reveal
Shows you the hidden costs your velocity metrics miss
📈
Optimize
Provides actionable insights to reduce waste and improve ROI

What VEMO Measures

Everything that matters for AI development costs

Quality Metrics
  • ▸ Code churn rate (%)
  • ▸ Duplicate code generated
  • ▸ Code complexity scores
  • ▸ Test coverage gaps
  • ▸ Static analysis violations
Time Metrics
  • ▸ Review overhead time
  • ▸ Rework cycles
  • ▸ Time to production-ready
  • ▸ Integration time
  • ▸ Debugging time
Cost Metrics
  • ▸ Total cost of ownership (TCO)
  • ▸ Hidden cost multiplier
  • ▸ Rework cost per sprint
  • ▸ Technical debt accumulation
  • ▸ Opportunity cost of delays

Proven Results

Real teams eliminating hidden costs with accurate estimation

10-person team reported 40% velocity gains with AI. VEMO revealed the reality: 15% gains with 22% hidden costs. After implementing VEMO governance, they achieved 8% sustained gains with zero hidden costs.
22% → 0%
Hidden Costs Eliminated
3 months
Time to Payback
8% Sustained
True Productivity Gain

See Your Hidden Costs

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