AI wrapper scrutiny — AI-powered apps with minimal native value may face rejection

Apple issued explicit guidance in 2023–2024 that apps must provide lasting value beyond a thin AI API wrapper. An app consisting of a text input, an LLM API call, and a text output display — with no system prompt specialization, no caching, no offline capability, and no native device integration — is functionally equivalent to accessing the underlying model through a web browser. Both stores are actively scrutinizing AI apps under this lens. NIST AI RMF MAP-1.5 classifies thin-wrapper deployment as a governance gap because the developer has minimal insight into or control over the AI's behavior relative to the app's stated purpose.

Add at least one of the following to distinguish the app from a web-equivalent AI interface before submission:

• Offline response caching: Store recent AI responses in SQLite or AsyncStorage so the app is useful without a network connection
• Native device integration: Feed camera input, voice, calendar events, or HealthKit data into the AI prompt to provide context a web interface cannot
• Personalized memory: Persist user preferences, prior session context, or domain-specific settings that shape AI behavior over time
• Structured multi-step workflow: Replace the open-ended chat interface with a guided flow that breaks a complex task into discrete native steps

// src/config/ai.ts — minimal domain specialization
const SYSTEM_PROMPT = `You are a [specific domain] expert assistant.
Context: The user is [specific persona/use case].
Scope: Answer only questions about [narrow domain]. Decline off-topic requests.`;

Domain-specific system prompts are table stakes — a generic GPT wrapper with no prompt engineering provides no value a user cannot get from ChatGPT.com directly.