Note Taking
Basic Memory is a knowledge base that you and your AI share. You write notes in markdown. Your AI reads and writes notes through MCP tools. Every note becomes part of a connected knowledge graph that both of you can search, enhance, and build on over time.
This page covers practical note-taking workflows — from quick capture to structured meeting notes to finding things weeks later.
The Two-Way Flow
The core idea: you capture quickly, the AI enhances later. Or the AI drafts something, and you refine it. Notes flow in both directions.
You jot down rough meeting notes:
# Team Meeting - Project Alpha
- Sarah mentioned database issues
- Need to update API docs
- Budget concerns raised by finance
- Next milestone is March 15th
Then you ask the AI to clean them up:
"Enhance my meeting notes for Project Alpha. Add structure, connect to what we already know about the project, and pull out action items."
The AI reads your note, adds semantic observations with tags, links to existing project notes, and creates clear action items with owners. Your raw capture becomes structured knowledge — without you having to do the formatting work.
It works the other way too. You can ask the AI to draft notes from a topic you describe, then you add your own perspective, correct details, or highlight what matters most to you.
Meeting Notes
Meeting notes are the most common use case. Here's the workflow.
During the meeting, capture fast. Don't worry about structure:
# Marketing Strategy Meeting - Q1 Planning
Sarah (Marketing), Mike (Product), Jenny (Sales)
- Q4 conversion rates down 15%
- New competitor launched similar product
- Need to revise messaging strategy
- Sarah wants $50k for ads
- Mike concerned about feature parity
- Follow-up meeting Jan 29
After the meeting, hand it to the AI:
"Clean up today's marketing strategy meeting notes. Structure the discussion points, add action items, and connect to our Q4 performance review and competitor analysis."
The AI transforms your rough notes into something like this:
---
title: Marketing Strategy Meeting - Q1 Planning
type: meeting
tags: [marketing, strategy, q1-planning]
---
# Marketing Strategy Meeting - Q1 Planning
## Meeting Context
- [date] January 15, 2025 #timeline
- [attendees] Sarah (Marketing), Mike (Product), Jenny (Sales) #participants
## Discussion
- [metric] Q4 conversion rates decreased 15% year-over-year #performance
- [context] New competitor launch adding market pressure #competitive
- [proposal] Revise messaging to emphasize unique value props #strategy
- [request] $50k additional advertising budget for Q1 #budget
- [concern] Feature parity gap with competitor #product
## Action Items
- [ ] Sarah: Draft new messaging framework by Jan 22
- [ ] Mike: Assess feature gap and provide development timeline
- [ ] Jenny: Analyze Q4 sales cycle data for conversion insights
- [ ] All: Follow-up meeting January 29
## Relations
- follows_up [[Q4 Performance Review]]
- addresses [[Competitor Analysis - New Market Entrant]]
- informs [[Q1 Marketing Strategy]]
Notice the type: meeting in the frontmatter. Note types help you categorize and filter your knowledge base — meeting, lecture, idea, code-review, or whatever types make sense for your work.
Also notice that the AI used edit_note to enhance your existing note rather than creating a new one. Basic Memory's write protection means the AI won't accidentally overwrite your content — it adds to it.
Learning and Lecture Notes
Same pattern, different context. Capture the key points during a lecture or while reading:
# Quantum Computing - Entanglement
Prof. 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
Then ask the AI to expand:
"Expand my lecture notes on entanglement. Add explanations for each concept and connect to my previous quantum mechanics notes."
The AI fills in the details, adds mathematical context where helpful, and links back to your earlier notes on related topics. You review and add your own questions or insights.
Quick Capture and Idea Parking
Not everything needs structure right away. Use quick notes to park ideas:
"Write a note called 'Ideas - Mobile App Features' with these thoughts: push notifications for habit tracking, gamification with points and badges, social sharing, calendar integration, offline mode."
The AI creates a simple note. Later — maybe days later — you can come back:
"Look at my mobile app feature ideas and flesh them out. Add feasibility notes and connect to our product roadmap."
Ideas grow into plans when you're ready for them to.
Finding Your Notes Later
This is where Basic Memory's search capabilities shine. You don't need to remember exact titles or tags.
Semantic Search
Ask by meaning, not keywords:
"What did we discuss about the authentication redesign?"
"Find notes related to budget concerns."
"What do I know about Sarah's marketing proposals?"
Semantic search finds relevant notes even when your query uses different words than your notes do. If you wrote about "conversion rates declining" and search for "budget concerns," it still surfaces the right meeting notes because they're semantically related.
Metadata Search
For more precise filtering, search by note properties:
"Show me all meeting notes from this month."
"Find notes with action items assigned to Sarah."
"List all notes tagged with q1-planning."
You can combine metadata filters with text search to narrow results further.
Keeping Notes Consistent with Schemas
When you take the same kind of note regularly — meeting notes, lecture notes, one-on-ones — you want consistency. Schemas define what a note type should contain.
"Create a schema for meeting notes that includes attendees, discussion points, decisions, and action items."
Once a schema exists, every meeting note the AI creates follows the same structure. No more forgetting to add action items or attendees.
You can create schemas for any repeating note type:
"Create a schema for lecture notes with course info, key concepts, questions, and connections to previous lectures."
"Create a schema for code review notes with files reviewed, issues found, and suggested fixes."
The AI validates notes against schemas as it creates them, so your knowledge base stays organized without extra effort from you.
Progressive Note Building
Notes don't have to be finished in one sitting. Basic Memory supports an iterative workflow where a note grows over days or weeks.
Day 1 — You create a stub:
"Write a note called 'Project Planning - E-commerce Site' with a note that we need to plan the new site for Q2 launch."
Day 3 — After gathering requirements, you add to it:
"Add requirements to the e-commerce planning note: mobile-responsive design, Stripe payments, inventory management, customer portal."
Day 5 — The AI connects it to existing knowledge:
"Review the e-commerce planning note and add connections to our previous e-commerce projects, Stripe integration docs, and Q2 revenue goals."
Each iteration uses edit_note to append or update sections. The note's history reflects contributions from both you and the AI — and Basic Memory tracks who made each update.
Best Practices
Capture first, structure later. Don't slow yourself down formatting notes during a meeting or lecture. Get the content down, then let the AI do the formatting work.
Use consistent language. If you call your team meetings "standups," stick with that. Consistent terminology helps the AI connect related notes.
Review AI enhancements. The AI is good at structure and connections, but you know the nuance. Read what it adds and correct anything that's off.
Let relations build naturally. You don't need to manually connect every note. As your knowledge base grows, the AI finds and suggests connections through semantic search and the knowledge graph.
Create schemas for repeating formats. If you take the same kind of note more than a few times, define a schema. It saves time and keeps your knowledge base consistent.