Collaborative note-taking where AI and humans work together to capture, enhance, and connect information in real-time
Basic Memory transforms note-taking into a collaborative process where both you and AI can read, write, and enhance notes together. The semantic knowledge graph means every note becomes part of a connected web of understanding that grows smarter over time.
# Team Meeting - Project Alpha- Sarah mentioned database issues- Need to update API docs- Budget concerns raised by finance- Next milestone is March 15th
AI reads your note and enhances it:
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You: "Clean up and expand my meeting notes, connecting to our existing project knowledge"AI: [Reads your raw notes and creates:]- Structured semantic observations with tags- Connections to existing project documentation- Action items with clear ownership- Links to related technical issues and timelines- Enhanced context from previous meeting notes
You: "Create detailed notes from this lecture recording about machine learning"AI: [Creates structured notes with:]- Key concepts with semantic tags- Technical details and explanations- Connections to existing AI knowledge- Questions for further exploration
You read and add personal insights:
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# Machine Learning Fundamentals - Lecture Notes[AI-generated technical content...]## My Thoughts and Questions- [insight] This connects to what I learned about neural networks last month #personal-connection- [question] How does this apply to the project I'm working on? #application- [confusion] Need to understand the math behind gradient descent better #learning-gap## Relations- builds_on [[Neural Networks Basics]]- applies_to [[Current Work Project]]
# Marketing Strategy Meeting - Q1 Planning## AttendeesSarah (Marketing), Mike (Product), Jenny (Sales)## Key Points- Q4 conversion rates down 15%- New competitor launched similar product- Need to revise messaging strategy- Budget discussions - Sarah wants $50k for ads- Mike concerned about feature parity
After the meeting (AI enhances and connects):
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You: "Enhance these meeting notes and connect them to our existing marketing and product knowledge"AI: [Transforms into structured knowledge:]- Semantic observations with business impact tags- Connections to previous quarter performance data- Links to competitor analysis notes- Action items with deadlines and owners- Relations to product roadmap and marketing strategy
Result - enhanced collaborative note:
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---title: Marketing Strategy Meeting - Q1 Planningtags: [marketing, strategy, q1-planning, performance-review]---# Marketing Strategy Meeting - Q1 Planning## Meeting Context- [date] January 15, 2024 #timeline- [attendees] Sarah (Marketing), Mike (Product), Jenny (Sales) #participants- [purpose] Q1 strategy planning and Q4 performance review #meeting-type## Performance Analysis- [metric] Q4 conversion rates decreased 15% year-over-year #performance-decline- [context] Market pressure from new competitor launch #competitive-pressure- [impact] Revenue targets missed by $200k in Q4 #financial-impact## Strategic Discussions- [proposal] Messaging strategy revision to emphasize unique value props #strategy-shift- [request] $50k additional advertising budget for Q1 #budget-request- [concern] Product feature parity gap with new competitor #product-gap- [priority] Need coordinated marketing-product response #cross-team-coordination## Action Items- [ ] Sarah: Draft new messaging framework by Jan 22 #action-item- [ ] Mike: Assess feature gap and provide development timeline #action-item- [ ] Jenny: Analyze Q4 sales cycle data for conversion insights #action-item- [ ] All: Follow-up meeting scheduled for Jan 29 #next-steps## Relations- follows_up [[Q4 Performance Review]]- addresses [[Competitor Analysis - New Market Entrant]]- informs [[Q1 Marketing Strategy]]- affects [[Product Roadmap Q1]]- requires [[Budget Planning Q1]]
# Quantum Computing Lecture - EntanglementProf. Martinez - Physics 451- Quantum entanglement = spooky action at distance- Bell's theorem proves local realism is wrong- EPR paradox - Einstein didn't like this- Applications in quantum teleportation- Measurement collapses entangled state
After lecture (AI expands and connects):
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You: "Expand these lecture notes with detailed explanations and connect to my existing physics knowledge"AI: [Creates comprehensive note with:]- Detailed explanations of each concept- Mathematical foundations where relevant- Historical context and key experiments- Connections to previous quantum mechanics notes- Questions for further study- Relations to quantum computing applications
# Notes from "Thinking, Fast and Slow" - Chapter 3## Key Ideas- System 1 vs System 2 thinking- Cognitive ease affects judgment- Availability heuristic leads to biases- Examples: lottery numbers, recent events
AI enhances with connections:
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You: "Expand these book notes and connect them to my existing knowledge about psychology and decision-making"AI: [Enhances with:]- Detailed explanations of each concept- Real-world examples and applications- Connections to behavioral economics notes- Links to personal decision-making experiences- Questions about practical applications
The semantic structure enables powerful search and context loading:
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You: "Load context about all our Salesforce integration projects"AI: [Searches semantic graph and finds:]- Technical challenges from previous integrations- Code patterns and solutions that worked- Client requirements and common requests- Budget and timeline patterns- Team expertise and resource needs
The knowledge graph automatically suggests unexpected connections:
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You: "I'm taking notes on urban planning principles"AI: [While creating the note, suggests connections to:]- Software architecture patterns (similar design principles)- Psychology notes about human behavior in spaces- Economics research on local development- Environmental studies about sustainable cities
# Ideas - Mobile App Feature## Random Thoughts- Push notifications for habit tracking- Gamification with points/badges- Social sharing of achievements- Integration with calendar apps- Offline mode for data entry[AI later enhances with feasibility analysis, technical requirements, and market research connections]
You: "I recorded my thoughts during my commute. Clean up this transcript and turn it into structured notes"AI: [Processes voice transcript into:]- Cleaned up text with proper punctuation- Organized thoughts by topic- Semantic observations with tags- Connections to existing projects and ideas- Action items extracted from rambling thoughts
Note evolves through multiple AI-human iterations:
Day 1 - Human starts:
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# Project Planning - New E-commerce SiteNeed to plan the new e-commerce site for Q2 launch
Day 2 - AI adds structure:
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# Project Planning - New E-commerce Site## Timeline- [milestone] Q2 launch target #timeline- [phase] Discovery and planning - January #project-phase- [phase] Design and development - Feb-March #project-phase- [phase] Testing and launch - April #project-phase
You: "I started researching renewable energy storage. Continue this research and create detailed technical notes."AI: [Reads your initial notes and:]- Expands on battery technologies- Adds grid-scale storage solutions- Connects to energy policy research- Identifies key research papers and companies- Creates comprehensive technical overview
AI drafts, human personalizes:
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You: "You created great notes on meditation techniques. Add my personal experiences and what works for me."[Human adds personal insights, preferred methods, and specific outcomes to AI's comprehensive overview]
Round 1: Human captures raw meeting notesRound 2: AI structures and enhances with contextRound 3: Human adds personal insights and reactionsRound 4: AI connects to broader strategic implicationsRound 5: Human adds action items and next steps
You: "Create notes for the team retrospective meeting"AI: [Creates template based on:]- Previous retrospective formats and questions- Current project status and challenges- Team dynamics and recent feedback- Goals and metrics being tracked- Suggested improvements from past retros
# Code Review - User Authentication Module## Issues Found- Password validation too weak- No rate limiting on login attempts- SQL injection vulnerability in user lookup- Missing input sanitization
AI enhances with technical details:
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AI adds:- Specific code line references- Security vulnerability classifications- Connections to security best practices notes- Similar issues found in previous reviews- Recommended fixes with code examples
# DevCon 2024 - Day 1 Notes## Keynote - Future of Web DevelopmentSpeaker: Sarah Chen- Web Assembly becoming mainstream- JAMstack architecture patterns- Edge computing changing everything
AI expands with comprehensive coverage:
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AI enhances with:- Detailed explanations of technical concepts- Connections to existing web development knowledge- Links to speaker's previous work and papers- Integration with current project implications- Questions for further research
# Paper Notes - "Attention Is All You Need"## Main Contribution- Transformer architecture replaces RNNs- Self-attention mechanism- Parallelizable training- Better performance on translation tasks
AI creates comprehensive analysis:
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AI adds:- Mathematical foundations of attention- Comparison with previous sequence models- Impact on subsequent research and applications- Connections to other AI architecture notes- Implementation considerations and code examples
You: "Load context for tomorrow's project planning meeting"AI: [Searches knowledge graph and provides:]- Previous meeting notes and action items- Current project status and blockers- Team member updates and capacity- Related decisions and requirements- Suggested agenda items based on outstanding issues
You: "Review today's notes and create a summary of key insights and next steps"AI: [Analyzes day's notes and creates:]- Summary of main themes and decisions- Outstanding questions and action items- Connections to broader goals and projects- Suggestions for tomorrow's priorities
You: "Analyze this week's notes and identify patterns, progress, and planning needs"AI: [Reviews week's knowledge creation and provides:]- Progress tracking against goals- Emerging themes and insights- Knowledge gaps requiring attention- Connections between different work streams- Strategic implications and recommendations