Your assignment
Classify six proposed app features as deterministic, predictive or generative. Explain the cheapest adequate solution for each.
Work through it
- Start from the scenario below and write the expected behavior before changing code. If this is a design exercise, produce a diagram or decision table; for an implementation exercise, create a small reproducible project or test fixture.
- Address each of these decisions explicitly: Rules, ML and generative AI, Training versus inference, The three Android AI workflows. Record the assumptions that influence your choices.
- Reproduce the ordinary case and the failure described in the scenario. Use controlled inputs or fake dependencies where a live service would make the result unpredictable.
- Compare the observed result with your expected behavior. Fix the underlying decision or implementation when they differ; do not change the expected outcome merely to hide a failure.
- Save the evidence and explain what remains unverified. A simulated service failure demonstrates application handling, but does not establish real-device or provider compatibility.
Scenario to test
A notes app can sort by date without AI. Summarizing an unstructured note may benefit from a model. Deleting notes must still use ordinary application authorization.
Completion criteria
You can explain inference and identify a feature that should not use a model.
Submit the diagram or relevant code, the inputs used, the observed result and a short explanation of the tradeoff. Include at least one ordinary case and one boundary or failure case.
Review your work
- Could another learner reproduce the result from your notes?
- Does the evidence prove the completion criterion, or only that a tool ran?
- Which assumption would change your design if it proved false?
Continue only when you can explain the result independently. The final project will combine these decisions.