--- title: Your Next iOS System Design Interview Won’t Ask About... description: Mobile system design interviews are evolving to include LLM infrastructure topics like semantic caching, vector search, and embedding pipelines. Unlike... canonical: https://daily.dev/posts/your-next-ios-system-design-interview-won-t-ask-about-image-caches-it-ll-ask-about-semantic-ones--wff6gfzb2 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Your Next iOS System Design Interview Won’t Ask About Image Caches. It’ll Ask About Semantic Ones. | daily.dev og:description: Mobile system design interviews are evolving to include LLM infrastructure topics like semantic caching, vector search, and embedding pipelines. Unlike... og:url: https://daily.dev/posts/your-next-ios-system-design-interview-won-t-ask-about-image-caches-it-ll-ask-about-semantic-ones--wff6gfzb2 og:image: https://api.daily.dev/og/posts/WfF6GFzb2.png og:image:alt: Your Next iOS System Design Interview Won’t Ask About Image Caches. It’ll Ask About Semantic Ones. og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Your Next iOS System Design Interview Won’t Ask About Image Caches. It’ll Ask About Semantic Ones. **[Medium](https://daily.dev/sources/medium_js)** · 6 min read · 0 upvotes · 0 comments ## Summary Mobile system design interviews are evolving to include LLM infrastructure topics like semantic caching, vector search, and embedding pipelines. Unlike traditional image caches that use byte equality, semantic caches use cosine similarity between embeddings — introducing new failure modes where a cache can confidently return a wrong answer. A working Swift demo (SemanticCacheKit) illustrates key design decisions: handling undefined cosine similarity via optionals, actor isolation to prevent race conditions, and the critical insight that similarity thresholds are model-relative calibration artifacts, not universal constants. Swapping an embedder without recalibrating the threshold can silently collapse hit rates or produce false hits. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Implementing Semantic Caching Using Spring AI](https://daily.dev/posts/implementing-semantic-caching-using-spring-ai-anojohlzl) · Baeldung · 4 upvotes · 0 comments - [Semantic caching thresholds and why they matter](https://daily.dev/posts/semantic-caching-thresholds-and-why-they-matter-qlfdqvdeb) · portkey · 1 upvotes · 0 comments - [Semantic memory search for AI agents](https://daily.dev/posts/semantic-memory-search-for-ai-agents-rulp67gur) · Redis · 0 upvotes · 0 comments --- Tags: [#ios](https://daily.dev/tags/ios), [#swift](https://daily.dev/tags/swift), [#vector-search](https://daily.dev/tags/vector-search), [#embeddings](https://daily.dev/tags/embeddings) [View this post on daily.dev](https://daily.dev/posts/your-next-ios-system-design-interview-won-t-ask-about-image-caches-it-ll-ask-about-semantic-ones--wff6gfzb2) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Your Next iOS System Design Interview Won’t Ask About Image Caches. 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