CortexGraph Use Cases¶

Based on the repository documentation and architecture, here are the appropriate use cases for CortexGraph:

1. Personal AI Assistant Memory¶

Scenario: You regularly chat with Claude about various topics - Remember your preferences (coding style, communication preferences, dietary restrictions) - Recall past decisions and their reasoning - Track ongoing projects and their status - Remember personal context (family names, pet names, important dates)

Example: "I prefer tabs over spaces" gets saved once, reinforced over time, and Claude remembers it months later without you repeating it.

2. Software Development Assistant¶

Scenario: Using Claude for coding across multiple projects - Remember architecture decisions and rationale - Track bugs you've encountered and solutions - Recall library preferences and why you chose them - Remember API patterns you've established - Track tech debt and future refactoring notes

Example: Claude remembers you prefer React hooks over class components, your ESLint config preferences, and that one weird TypeScript issue you solved last month.

3. Context Switching for Developers¶

Scenario: Jumping between multiple codebases/projects - Aggressive forgetting for ephemeral context - Quick recall of project-specific conventions - Remember which commands to run for each project - Track environment setup quirks

Example: Set shorter decay (1-day half-life) so context from Project A fades quickly when you switch to Project B, preventing confusion.

4. Research & Learning¶

Scenario: Using Claude to learn new topics or conduct research - Build a knowledge graph of concepts and their relationships - Remember key insights from papers/articles - Track questions to explore later - Link related concepts across domains - Spaced repetition naturally surfaces concepts that need review

Example: Learning Rust - Claude remembers the ownership rules you struggled with and brings them up when relevant, strengthening that memory through use.

5. Writing & Content Creation¶

Scenario: Working on long-form content with Claude - Remember style guidelines and tone preferences - Track character details for fiction writing - Recall research findings relevant to your topic - Remember audience preferences and feedback - Track ideas for future articles

Example: Writing a blog series - Claude remembers your target audience, writing style, and callbacks to previous posts without you re-explaining each time.

6. Personal Knowledge Management (PKM)¶

Scenario: Building a second brain with Obsidian integration - Auto-generate Obsidian notes from conversations - Link memories to your existing note structure - Automatic tagging and entity extraction - Build connections between conversation insights and permanent notes - Search across both ephemeral and permanent knowledge

Example: Your Obsidian vault becomes enriched with conversation insights that auto-promote to permanent notes when they prove valuable over time.

7. Preference-Heavy Applications¶

Scenario: Any domain where user preferences matter a lot - Design preferences (color schemes, layouts) - Workflow preferences (automation preferences, tool choices) - Communication style (formal vs casual, emoji usage) - Accessibility needs (screen reader usage, keyboard shortcuts)

Example: Claude remembers you're colorblind and always suggests colorblind-friendly palettes without asking.

8. Long-Term Projects & Planning¶

Scenario: Multi-month projects with Claude as a collaborator - Track project goals and evolution - Remember stakeholder feedback - Recall past iterations and why they changed - Monitor progress milestones - Link related sub-projects and dependencies

Example: Building a SaaS product over 6 months - Claude remembers your MVP scope, feature requests you've deferred, and technical constraints.

Scenario: Shared memory store for team AI interactions - Document team conventions and decisions - Build institutional knowledge graph - Remember common problems and solutions - Track who knows what (entity linking) - Create searchable decision log

Example: Team members can query why certain architectural decisions were made, with memories strengthening as multiple people reference them.

10. Domain-Specific Expertise¶

Scenario: Using Claude in specialized domains - Medical/Healthcare: Remember patient interaction patterns (anonymized) - Legal: Track case precedents and reasoning - Education: Remember student learning patterns - Finance: Recall market analysis insights - Scientific Research: Build knowledge graphs of experiments and findings

Example: A researcher remembers which experiments failed and why, preventing repeated mistakes.

11. Adaptive AI Behavior¶

Scenario: You want Claude's behavior to adapt over time - Natural spaced repetition - memories in danger of forgetting surface naturally - Cross-context detection - memories used in multiple domains get stronger - Automatic importance weighting - frequently-used memories survive - Graceful forgetting - ephemeral context naturally fades

Example: Claude stops asking about your Python version after the 5th conversation where it's mentioned and used.

When NOT to Use CortexGraph¶

❌ High-security secrets - Use proper secret management (see docs/security.md) ❌ Regulated data (PHI, PII) - Compliance concerns unless properly configured ❌ Real-time high-throughput - Designed for assistant conversations, not APIs ❌ Exact recall requirements - Temporal decay means memories can be forgotten ❌ Multi-user production systems - Single-user design (as of v0.5.3)

Configuration for Different Use Cases¶

From docs/configuration.md and src/cortexgraph/config.py:1:

For Development (fast context switching)¶

{
  "decay_half_life_hours": 24,
  "forget_threshold": 0.1,
  "review_lower_bound": 0.2
}

For Research/Archival (long retention)¶

{
  "decay_half_life_hours": 168,
  "forget_threshold": 0.03,
  "promote_threshold": 0.5
}

For Personal Assistant (balanced)¶

{
  "decay_half_life_hours": 72,
  "forget_threshold": 0.05,
  "promote_threshold": 0.65
}

Bottom Line¶

CortexGraph is best for individual knowledge workers who want their AI assistant to remember context across conversations, with memory dynamics that feel natural rather than robotic. It's particularly powerful when combined with Obsidian for building a hybrid ephemeral/permanent knowledge base.

The temporal decay ensures Claude doesn't get confused by outdated context, while the reinforcement mechanics ensure important information naturally persists.