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Experimental Pattern

This is an emerging architecture pattern. Example apps coming soon as we explore this approach.

Mobile-First Native Architecture

AI that fits your pocket—sensors, cameras, always-on

What is it?

Architecture designed specifically for mobile constraints and capabilities: battery life, intermittent connectivity, rich sensors (camera, GPS, motion), and platform-specific APIs like iOS Shortcuts and Android Intents.

This pattern treats mobile devices as more than small desktops—they're sensor-rich, always-with-you computing platforms with unique interaction models shaped by app stores and platform conventions.

💡 Key Insight

"Mobile isn't just small desktop—it's sensors everywhere, intermittent connectivity, and expectations shaped by app stores. Mobile AI must embrace constraints as features."

Tradeoffs

Advantages

  • Rich sensor access (camera, GPS, motion, biometrics)
  • Platform integration (Shortcuts, Intents, widgets)
  • Always-with-you form factor
  • App store distribution channels
  • Push notifications for engagement

Tradeoffs

  • Battery constraints limit AI frequency
  • App store approval processes
  • Platform fragmentation (iOS vs Android)
  • Smaller screens limit UI complexity
  • More restrictive sandboxing than web

Technical Deep Dive

Architecture

Mobile-first architecture balances on-device AI for responsiveness with selective cloud calls for power, using platform-specific optimizations for battery life.

  • •Platform: React Native, Flutter, or Swift/Kotlin native
  • •AI Layer: On-device inference (Core ML, TensorFlow Lite) + selective cloud
  • •Sensors: Camera, GPS, accelerometer, microphone, NFC
  • •Offline: Local DB with background sync queue

When to Use This Pattern

  • ✓Need camera, GPS, or motion sensors
  • ✓Always-available assistant use cases
  • ✓Offline-first critical (travel, remote work)
  • ✓App store distribution acceptable
  • ✓Push notifications enhance experience

When NOT to Use This Pattern

  • ✗Can work well in browser
  • ✗Rapid iteration needed (app store delays)
  • ✗Cross-platform support is secondary
  • ✗Desktop-class power needed

Example App Concepts

LensWithOtto

Coming Soon

AR shopping assistant using camera and visual AI

JourneyWithOtto

Coming Soon

Travel companion leveraging GPS and local AI

FitWithOtto

Coming Soon

Fitness coach using motion sensors and AI guidance

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