Mobile AI Apps: SwiftUI and React Native Patterns That Feel Native
How to integrate copilots and on-device or cloud LLMs without jank — streaming UX, offline fallbacks, and architecture that stays maintainable.
Mobile AI fails when it feels bolted on: modal chat that blocks the task, unstreamed responses, or network-only features that die at events and airports.
Prefer in-context assistants over a separate chat tab. Surface suggestions inside the flow the user already has — compose, search, RSVP, support — and keep a clear way to dismiss or undo.
Stream tokens into the UI with careful layout stability. Jumping row heights and keyboard fights destroy trust faster than a mediocre answer.
Architect for provider swap. Wrap LLM calls behind a thin client with timeouts, retries, and a deterministic fallback path. On React Native and SwiftUI alike, treat the model as an unreliable dependency.
This is where AI consulting meets mobile craft: the model is only half the product. The other half is interaction design and crash-free delivery.
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