User Guide

This comprehensive guide will help you master Thought Ledger’s decision memory system and make the most of your private AI assistant.

Understanding Decision Memory

Decision memory is Thought Ledger’s core feature. It’s the accumulated knowledge of your decisions, their contexts, and their outcomes that helps you make better choices over time.

How It Works

Capture: Record decisions as you make them
Context: Store relevant information and reasoning
Analysis: AI identifies patterns and connections
Retrieve: Find relevant past decisions when needed

The Decision Workflow

1. Creating a New Decision

Basic Decision Entry

Click “New Decision” in the main interface
Title: Give your decision a clear, descriptive name
Context: Add relevant background information
Options: List the choices you’re considering
Get AI Assistance: Let Thought Ledger provide insights

Rich Context Entry

For better AI assistance, include:

Timeline: When this decision needs to be made
Stakeholders: Who will be affected
Constraints: Budget, time, or resource limitations
Goals: What you’re trying to achieve
Past Similar Decisions: Reference related choices

2. AI-Assisted Decision Making

What the AI Provides

Historical Context: Similar decisions you’ve made
Pattern Recognition: Your decision-making tendencies
Risk Assessment: Potential outcomes based on your history
Blind Spot Identification: Areas you might be overlooking

Interacting with AI Insights

Ask Questions: “What did I decide last time I faced this?”
Request Context: “Show me decisions related to budget constraints”
Seek Patterns: “Am I consistently underestimating timelines?“

3. Recording Your Decision

The Decision Record

When you finalize your choice, Thought Ledger captures:

Your Selection: Which option you chose
Reasoning: Why you made this choice
Confidence Level: How sure you feel about the decision
Expected Outcome: What you think will happen
Follow-up Needed: Any required actions

Outcome Tracking

Set reminders to track decision outcomes:

Short-term: Check results in 1 week
Medium-term: Review in 1 month
Long-term: Evaluate in 3-6 months

Advanced Features

Decision Search & Retrieval

Search Methods

Keyword Search: Find decisions by specific terms
Context Search: Search by situation or constraints
Timeline Search: Find decisions from specific periods
Pattern Search: Look for recurring decision types

Smart Filters

By Outcome: Filter successful vs unsuccessful decisions
By Confidence: Find high or low-confidence choices
By Domain: Search specific areas (work, personal, technical)
By Stakeholder: Find decisions affecting specific people

Pattern Analysis

Decision Patterns

Thought Ledger identifies:

Recurring Scenarios: Similar situations you face
Success Factors: What leads to good outcomes
Risk Indicators: Warning signs from past decisions
Biases: Personal tendencies in decision making

Personal Insights

Strengths: Areas where you consistently make good choices
Growth Opportunities: Skills or knowledge to develop
Timing Patterns: When you make your best decisions
Collaboration Effects: How others influence your choices

AI Chat Interface

Conversational Queries

Ask natural language questions:

“What should I consider when choosing a new framework?”
“Show me my decisions about budget constraints”
“Am I too risk-averse in technical choices?”

Contextual Assistance

Current Decision Help: AI assistance while making decisions
Historical Analysis: Review past decision patterns
Future Planning: Get insights for upcoming choices

Best Practices

Decision Quality

Good Decision Habits

Be Specific: Clear titles and context help future retrieval
Include Constraints: Document limitations and requirements
Track Outcomes: Follow up on decision results
Learn from Patterns: Regularly review your decision history

Context Richness

Add these elements for better AI assistance:

Emotional State: How you felt during the decision
External Factors: Market conditions, team changes, etc.
Time Pressure: Whether the decision was rushed
Information Quality: How complete your knowledge was

Privacy & Security

Data Protection

Local Storage: All data stays on your device
No Cloud Sync: Your decision memory never leaves your machine
Encryption: Sensitive decisions are encrypted at rest
Access Control: Optional password protection for sensitive decisions

Backup Strategies

Regular Exports: Export your decision database periodically
Version Control: Keep historical versions of your decision memory
Cross-device Sync: Manual sync between your devices (if needed)

Integration with Workflows

Development Decisions

Technical Architecture: Framework and language choices
Code Review Decisions: Accept/reject criteria
Deployment Decisions: Release timing and rollback plans

Business Decisions

Hiring Decisions: Team composition and role definitions
Product Decisions: Feature prioritization and roadmap
Financial Decisions: Budget allocation and investments

Personal Decisions

Career Choices: Job opportunities and skill development
Learning Decisions: What to study and when
Life Planning: Major life changes and their impacts

Troubleshooting Common Issues

AI Not Providing Helpful Insights

Add More Context: Rich context improves AI assistance
Check Model Size: Larger models provide better insights
Review History: More decisions = better pattern recognition

Decision Memory Not Growing

Regular Usage: Consistent decision recording builds memory
Varied Context: Different decision types improve learning
Outcome Tracking: Complete the decision loop with results

Search Not Finding Relevant Decisions

Better Keywords: Use specific, descriptive search terms
Check Context: Search by situation rather than just keywords
Review Tags: Ensure decisions are properly categorized

Ready to become a decision memory expert? Start applying these techniques to build a rich, useful decision history that will serve you for years to come.