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Contextual AI Computing
AI that understands the full context of user activity over time rather than requiring explicit prompts for each interaction
How It Works
System continuously monitors user behavior and screen activity to build contextual understanding, then proactively suggests or executes relevant actions
Components
Implement continuous context monitoring across user devices
Build temporal understanding of user patterns and workflows
Create proactive suggestion engine based on context
Design simple trigger mechanism (like command+enter)
Ensure data persistence across sessions and applications
When to Use
When building AI assistants or productivity tools where user intent can be inferred from behavioral patterns and context
When Not to Use
For privacy-sensitive applications or when users prefer explicit control over AI interactions
Anti-Patterns to Avoid
Example
“User is working on a presentation and needs to find a nearby doctor - instead of opening ChatGPT and typing a prompt, they press command+enter and AI automatically suggests local doctors based on their location and calendar availability”
Related Knowledge
Personal Software Development Framework
Build software primarily for yourself first, then find others who share your specific needs rather than trying to build
pick a daily habit to serve narrow wedge use case
Successful mobile apps focus on specific daily behaviors within narrow market segments rather than broad solutions
It's not going to be what you build as much as what you don't build
With AI making everything buildable, success will come from choosing what NOT to build rather than capability limits
Vibe coders should build single killer features rather than complex multi-feature platforms
Success probability increases with focused scope - if you can't make a simple tool with auth, payment, and email work, y