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Tokens, context and model behavior

Practice: Tokens, context and model behavior

exerciseSelf-paced

Your assignment

Write a prompt with task, input boundary, output shape and an unknown case. Try missing and contradictory input.

Work through it

  1. 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.
  2. Address each of these decisions explicitly: Tokens and context windows, Prompts and grounding, Variability and confidence. Record the assumptions that influence your choices.
  3. 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.
  4. 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.
  5. 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

An expense parser outputs a negative total for a receipt. Valid JSON only proves syntax; your amount and currency checks must reject impossible values.

Completion criteria

You can distinguish formatting success from factual correctness.

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.

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Practice: Tokens, context and model behavior | AI for Android Developers — Fundamentals | Android Engineers