Android LLM client architecture quiz

A short practice quiz for the Android LLM client architecture post, focused on local versus remote inference, streaming state, context, memory, privacy, cost, and mobile failure modes.

Questions
12
Est. time
~9 min
  1. 01
    Product architecture

    Why does the post argue that an Android AI feature should not be built as a thin wrapper around one model API?

    Options for question 1
  2. 02
    Inference routing

    What is the best way to decide between local and remote inference?

    Options for question 2
  3. 03
    Provider layer

    What is wrong with a provider interface that only exposes ask(prompt): String?

    Options for question 3
  4. 04
    Streaming UI

    In the recommended Compose streaming design, where should raw provider stream events be handled?

    Options for question 4
  5. 05
    Memory and context

    Why should memory be split into transcript, summary, retrieval, preferences, attachments, and provider cache hints?

    Options for question 5
  6. 06
    Privacy policy

    What is the strongest privacy framing in the post?

    Options for question 6
  7. 07
    Provider secrets

    Why should an Android app avoid shipping raw provider secret keys in the APK?

    Options for question 7
  8. 08
    Token budgets

    Which client behavior can create unnecessary AI cost?

    Options for question 8
  9. 09
    Hybrid routing

    Why is fallback from remote to local not always safe?

    Options for question 9
  10. 10
    Failure states

    What should the app do when a stream fails halfway through a useful answer?

    Options for question 10
  11. 11
    On-device models

    What product work comes with on-device model support?

    Options for question 11
  12. 12
    Architecture summary

    What are the three jobs of an Android AI client in the post's simple explanation?

    Options for question 12
Progress
0/12 answered
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