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Cognitive Sectors

Different information needs different lifespans. The Memory Module organizes memories into 5 cognitive sectors, each with appropriate decay rates.
Your brain doesn’t treat “yesterday’s lunch” the same as “your wedding day.” Neither does the Memory Module.

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Quick Reference

SectorHalf-LifeDecayBest For
Episodic46 daysFastTime-bound events (meetings, bugs, deployments)
Semantic139 daysSlowFacts & concepts (API docs, definitions)
Procedural87 daysMediumHow-to knowledge (processes, tutorials)
Emotional35 daysVery FastSentiment & feedback (morale, satisfaction)
Reflective693 daysVery SlowStrategic insights (architecture decisions, “why we did this”)

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1. Episodic

What

Time-bound events & experiencesHas specific “when” and “where”Examples: Meeting notes, bug investigations, deployments

Decay

Half-life: 46 days (medium-fast)Week 1: Fresh, highly relevant Week 4: Still useful Week 12: Fading Week 24: Mostly forgotten
Use for:
  • Meeting notes and decisions
  • Bug investigation logs
  • Deployment records
  • Customer interaction logs
  • Project milestone events
  • Incident reports
Examples:
  • Standup
  • Bug Investigation
  • Support Call
"Daily standup - Jan 25, 2025
- Marcus: Finished auth refactor PR #234
- Sarah: Blocked on DB migration
- Aisha: Starting memory docs
Next standup: Jan 26"

Sector: episodic
Why: Specific date/time, useful short-term, less relevant after sprint

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2. Semantic

What

Facts, concepts & general knowledgeTimeless informationExamples: API docs, definitions, configurations

Decay

Half-life: 139 days (slow)Month 1: Fresh Month 3: Still strong (0.85) Month 6: Moderate (0.65) Year 1: Fading (0.40)
Use for:
  • API documentation and references
  • Technical definitions
  • Company policies
  • Product feature descriptions
  • Configuration settings
  • Integration docs
Examples:
  • API Docs
  • Product Knowledge
  • Technical Concepts
"Our REST API uses JWT bearer tokens.
Tokens expire after 30 days inactivity.
Header: Authorization: Bearer {token}

Generate: POST /api/auth/token
Refresh: POST /api/auth/refresh"

Sector: semantic
Why: Timeless factual information, referenced frequently

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3. Procedural

What

How-to knowledge & processesStep-by-step instructionsExamples: Deployment processes, coding patterns, tutorials

Decay

Half-life: 87 days (medium)Week 2: Fresh Month 2: Still reliable (0.80) Month 4: Need refresh (0.60) Month 6: Update needed (0.45)
Use for:
  • Deployment procedures
  • Setup guides
  • Troubleshooting steps
  • Coding patterns
  • Configuration workflows
  • Testing procedures
Examples:
  • Deployment
  • Setup Guide
  • Troubleshooting
"Production deployment process:
1. Run tests: npm run test
2. Build: npm run build
3. Tag: git tag v{version}
4. Push: git push origin v{version}
5. Deploy: vercel --prod
6. Verify: Check /health endpoint
7. Monitor: Watch logs for 10min"

Sector: procedural
Why: Step-by-step process, needs occasional updates

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4. Emotional

What

Sentiment & feedbackFeelings, morale, reactionsExamples: Customer frustration, team morale, satisfaction

Decay

Half-life: 35 days (very fast)Day 1: Fresh Week 2: Fading (0.70) Week 4: Mostly gone (0.50) Week 8: Very faint (0.25)
Use for:
  • Customer sentiment
  • Team morale tracking
  • User satisfaction
  • Frustration points
  • Positive feedback
  • Emotional context
Why fast decay: Sentiment changes quickly, old emotions less relevant Examples:
  • Customer Feedback
  • Team Morale
  • User Reaction
"Acme Corp frustrated with API rate limits.
Expressed urgency - blocking their launch.
Tone: Frustrated but professional.
Resolution: Upgraded plan, now satisfied.

Sentiment: Frustrated → Satisfied"

Sector: emotional
Why: Sentiment snapshot, less relevant after resolution

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5. Reflective

What

Strategic insights & decisionsThe “why” behind choicesExamples: Architecture decisions, lessons learned, retrospectives

Decay

Half-life: 693 days (very slow)Month 6: Still 0.95 Year 1: Still 0.85 Year 2: Still 0.70 Year 3: Still 0.60
Use for:
  • Architecture decisions
  • Technology choices
  • Lessons learned
  • Strategic pivots
  • Post-mortems
  • “Why we did this”
Why slow decay: Strategic insights remain valuable for years Examples:
  • Architecture
  • Lesson Learned
  • Tech Choice
"Why we chose microservices over monolith:

Context: Scaling to 100+ developers across teams
Decision: Microservices architecture
Reasoning:
- Team autonomy (deploy independently)
- Technology flexibility (right tool per service)
- Fault isolation (one service down ≠ all down)

Trade-offs accepted:
- Increased operational complexity
- Distributed system challenges
- Network latency between services

Date: Jan 2024"

Sector: reflective
Why: Strategic decision that informs future architecture choices

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Choosing the Right Sector

Decision tree: 
Is it about feelings/sentiment?
  → Emotional (fast decay)

Is it a time-bound event?
  → Episodic (medium-fast decay)

Is it a step-by-step process?
  → Procedural (medium decay)

Is it a fact or definition?
  → Semantic (slow decay)

Is it strategic insight or "why"?
  → Reflective (very slow decay)
When in doubt:
  • Events with dates → Episodic
  • Timeless facts → Semantic
  • How-to guides → Procedural
  • Strategic reasons → Reflective

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Sector Comparison

AspectEpisodicSemanticProceduralEmotionalReflective
QuestionWhen/Where?What is it?How to do it?How did it feel?Why did we do it?
TimeframeSpecific dateTimelessPeriodicShort-livedLong-lasting
ExampleBug fix Jan 15API uses JWTDeploy: 7 stepsCustomer happyWhy microservices
Decay46 days139 days87 days35 days693 days
UpdateRarelyWhen facts changeWhen process changesOftenRarely

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Auto-Classification

The system can auto-classify based on content: 
store_memory({
  content: "Fixed payment bug on Jan 20...",
  sector: "auto"  // System detects: episodic (has date, event)
})

store_memory({
  content: "API authentication uses JWT tokens...",
  sector: "auto"  // System detects: semantic (factual, timeless)
})

store_memory({
  content: "Deploy process: 1. Build 2. Test 3. Push...",
  sector: "auto"  // System detects: procedural (step-by-step)
})
Override when needed: 
store_memory({
  content: "Why we chose React...",
  sector: "reflective"  // Manual: strategic decision
})

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Best Practices

Be Explicit

Specify sector when storing✅ Good:
store_memory({
  content: "...",
  sector: "reflective"
})
❌ Risky:
store_memory({
  content: "..."  // Auto-classify may guess wrong
})

Match Content to Sector

Write for the sectorReflective: Include “why” and context
"Why we chose X:
Context: ...
Reasoning: ...
Trade-offs: ..."
Episodic: Include date/time
"Meeting notes - Jan 25, 2025
Attendees: ...
Decisions: ..."

Use Reflective for Decisions

Strategic choices = ReflectiveNot episodic (will fade too fast) Not semantic (not just facts)✅ “Why we chose microservices…” → Reflective ❌ “We use microservices” → Semantic

Emotional for Sentiment Only

Pure sentiment = EmotionalNot for facts about sentiment✅ “Customer frustrated about X” → Emotional ❌ “Customer satisfaction score: 8.5” → Semantic

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Next Steps

Decay & Reinforcement

How salience changes over time

Best Practices

Optimize memory usage

Workflows

Put sectors to work
Different memories need different lifespans. Choose the right sector, let the system handle the rest.