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📊 AI Resource Efficiency Checklistt

🎯 Purpose

A one-page checklist to help GetCimple's 3-person team assess and optimize resource usage for AI features, ensuring smart allocation of time, money, and attention.

💰 Cost Assessment

Before Implementation

  • Estimated monthly API costs: $__
  • Development time budget: _ hours
  • Maintenance time per month: _ hours
  • Cost per user served: $__

Cost Thresholds (Red Flags)

  • ❌ Monthly AI costs > $100 for MVP
  • ❌ Development time > 16 hours (2 days)
  • ❌ Monthly maintenance > 4 hours
  • ❌ Cost per user > $5/month

Cost Optimization Checks

  • ✅ Using cheapest model that works (Haiku vs Sonnet)?
  • ✅ Caching responses for common queries?
  • ✅ Rate limiting to prevent runaway costs?
  • ✅ Using n8n workflows instead of custom code?

⏱️ Time Investment

Development Time Reality Check

  • Can we build MVP in <2 days? (If no, break down further)
  • Do we understand the AI API well? (If no, add learning time)
  • Is the integration straightforward? (If no, consider simpler approach)
  • Can we reuse existing patterns? (Check implementation-patterns.md)

Time Optimization Strategies

  • ✅ Starting with existing n8n templates?
  • ✅ Using AI patterns we've implemented before?
  • ✅ Copying workflows from similar features?
  • ✅ Planning for iterative improvement vs perfect first version?

🧠 Cognitive Load Assessment

Team Capacity Check

  • Are we already working on 2+ major features? (If yes, defer)
  • Do we have bandwidth for debugging AI quirks?
  • Can we handle additional support questions?
  • Will this create ongoing decision fatigue?

Complexity Indicators (Warning Signs)

  • ⚠️ Requires training or fine-tuning models
  • ⚠️ Needs complex prompt engineering
  • ⚠️ Involves chaining multiple AI calls
  • ⚠️ Requires domain expertise we don't have

📈 Value Justification

User Impact Metrics

  • Time saved per user per week: _ minutes
  • Number of users affected: _
  • Total time saved across users: _ hours/week
  • Value of time saved: $_ per week

Value Thresholds

  • ✅ Saves users >15 minutes per week each
  • ✅ Affects >50% of active users
  • ✅ Value of time saved > Cost of implementation
  • ✅ Reduces support questions or manual work

🔧 Technical Resource Check

Infrastructure Requirements

  • Uses existing APIs/services? (Anthropic, n8n, Supabase)
  • Fits within current hosting? (Cloudflare Workers)
  • No new dependencies or services?
  • Can leverage existing authentication?

Maintenance Considerations

  • Auto-scales without manual intervention?
  • Has clear error handling and fallbacks?
  • Monitoring/alerts set up?
  • Documentation for future team members?

🚨 Resource Warning Signs

Stop Implementation If:

  • 🛑 Combined scores indicate >20 hours total work
  • 🛑 Monthly costs would exceed $50 for <numerous users
  • 🛑 Requires learning new frameworks or tools
  • 🛑 Can't clearly explain value to users in one sentence
  • 🛑 Team is already stretched on 3+ concurrent projects

Proceed with Caution If:

  • ⚠️ Implementation time 8-15 hours
  • ⚠️ Monthly costs $25-50
  • ⚠️ Affects <30% of users
  • ⚠️ Value is primarily "nice to have"

✅ Green Light Indicators

Ideal AI Feature Characteristics:

  • 🟢 Implementation time <8 hours
  • 🟢 Monthly costs <$25
  • 🟢 Uses familiar tools (n8n, Claude API)
  • 🟢 Saves users significant time weekly
  • 🟢 Fits existing workflows seamlessly
  • 🟢 Can start simple and improve incrementally

📋 Pre-Implementation Checklistt

Before starting any AI feature:

  • Cost-benefit analysis completed and favorable
  • Implementation approach selected from patterns
  • Success metrics defined (time saved, user satisfaction, etc.)
  • Fallback plan if AI fails (manual process, simpler alternative)
  • Resource budget approved by team
  • Integration points identified and tested

🎯 Quick Decision Matrix

Factor Weight Score (1-5) Weighted Score
User time saved 3x _ _
Implementation simplicity 2x _ _
Cost efficiency 2x _ _
Team capacity fit 2x _ _
Maintenance burden 1x _ _
Total **_**

Scoring Guide:

  • 5: Excellent (major time savings, very simple, very cheap)
  • 3: Good (moderate benefits, reasonable effort/cost)
  • 1: Poor (minimal benefits, complex, expensive)

Decision Thresholds:

  • Score 30+: Implement immediately
  • Score 20-29: Implement if capacity allows
  • Score <20: Defer or find simpler approach

💡 Remember

The best AI feature is one that users love and doesn't stress the team. When resource allocation is unclear, start smaller or defer until it is.