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🧠 AI fundamentals for developers: iOS interview questions

1. AI, machine learning, neural networks and LLMs: what's the difference? Junior PRO
2. How an LLM generates text: tokens, attention, temperature Middle PRO
3. Tokens and the context window: how they're counted and what happens on overflow Junior PRO
4. Why do models "hallucinate" and how do you live with it? Junior PRO
5. Reasoning models and extended thinking: when does a "thinking" model pay off? Middle PRO
6. Multimodality: images, screenshots and audio — what can you give a model? Middle PRO
7. Embeddings and RAG: how a model answers from your documents Middle PRO
8. Fine-tuning, prompting or RAG: which to choose, and what is LoRA? Senior PRO
9. How the model market works and how to choose a model for a task Middle PRO
10. What is a prompt and what makes a good one? Junior PRO
11. System prompt and history: how does the model "see" a conversation, and why do long chats degrade? Junior PRO
12. Prompting techniques: few-shot, planning, self-checks, clarifying questions, JSON Middle PRO
13. Prompt recipes and templates: a library, slash commands and skills Middle PRO
14. What are tokens in terms of money and limits? Junior PRO
15. How to save tokens: from context to prompt caching Middle PRO
16. How to give AI context on a large project without overloading the window? Middle PRO
17. How to evaluate AI answers: compiler, tests, model comparison, your own eval set Senior PRO
18. Prompt anti-patterns and common mistakes, including leaking secrets Junior PRO
19. What is an AI agent and how does its loop work? Junior PRO
20. MCP (Model Context Protocol): what is it and how do you connect servers? Middle PRO
21. How do you write your own MCP server? Middle PRO
22. AI agents in the terminal: Claude Code, Codex and others Junior PRO
23. AI through a UI: chats, AI editors and IDE extensions Junior PRO
24. AI in Xcode 27: how do you connect agents, ChatGPT, Claude and local models? Junior PRO
25. Connecting third-party models: API keys, OpenAI-compatible APIs, rate limits Middle PRO
26. How do you run a model locally on a Mac: Ollama, LM Studio, MLX Middle PRO
27. Which AI models exist in 2026, and how do you pick one for code? Junior PRO
28. How do you build AI into an iOS app: Foundation Models, Core AI and cloud APIs Middle PRO
29. AI agent security: prompt injection, permissions, sandboxes, supply chain Senior PRO
30. Which AI should you use for an app icon, and how do you get it App Store-ready? Junior PRO
31. Images and illustrations for your app and marketing: which generators, and how to keep a consistent style? Junior PRO
32. AI for UI design and mockups: what can Figma AI, Stitch, and other generators actually do? Middle PRO
33. Which AI is best for implementing a design, and how do you get decent SwiftUI? Middle PRO
34. How do you connect an AI agent to Figma via MCP? Middle PRO
35. Figma → AI → Xcode: what does the full workflow look like? Senior PRO
36. Generating development assets: what makes sense to hand to AI, and what doesn't? Junior PRO
37. Xcode Cloud in depth: workflows, ci_scripts, variables and pricing Middle PRO
38. iOS CI on GitHub Actions: tests, caching, signing and TestFlight Middle PRO
39. AI in CI: PR review, release notes, failure triage and auto-fixes Senior PRO
40. What an AI software factory is and what actually works in 2026 Middle PRO
41. A mini-factory for an iOS project: from issue to TestFlight Senior PRO
42. Risks of AI automation and how to roll it out gradually Senior PRO