Context Window Budgeting: What to Include, What to Cut

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-prompting-context-engineering-creators

1. What is the main idea of "Context Window Budgeting: What to Include, What to Cut"?

   1. Long context windows tempt teams to dump everything in.
   2. Use AI as the final authority for the whole decision
   3. Avoid checking the answer once it sounds polished
   4. Focus only on speed instead of judgment

2. Which concept is most central to "Context Window Budgeting: What to Include, What to Cut"?

   1. context window
   2. context engineering
   3. needle in haystack
   4. token budget

3. Which use of AI fits this topic best?

   1. Solve all problems by adding more context
   2. Let the AI decide what matters without your review
   3. Curate context relevance — included items should each earn their place
   4. Use the answer before checking whether it fits the situation

4. Which limitation should you watch for in this topic?

   1. Curate context relevance — included items should each earn their place
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Solve all problems by adding more context

5. What should a careful learner remember about "Context engineering audit"?

   1. Use AI to draft or organize ideas about context engineering, then verify before acting.
   2. Skip the context so the tool can guess faster
   3. Treat the output as private even after sharing it online
   4. Use the answer without checking the source

6. You want to use AI after this lesson. What is the safest next step?

   1. Act immediately because the AI answer is written clearly
   2. Use AI for drafting and comparison, but verify before publishing or relying on it.
   3. Hide uncertainty so the final answer looks cleaner
   4. Use private or sensitive details before checking permission

7. How should AI output about context engineering be treated?

   1. As proof that no other source is needed
   2. As a replacement for context, consent, or expert review
   3. As a draft or helper output that still needs human judgment and verification
   4. As something that becomes correct when it sounds confident

8. Name one way to verify an AI answer about context engineering.

9. Which action would help you apply "Context Window Budgeting: What to Include, What to Cut" responsibly?

   1. Substitute context for retrieval quality (bad RAG doesn't get fixed by more chunks)
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Test 'lost in the middle' — long contexts can ignore middle content

10. Which choice is a bad use of AI for this lesson?

    1. Substitute context for retrieval quality (bad RAG doesn't get fixed by more chunks)
    2. Curate context relevance — included items should each earn their place
    3. Ask for a plain-language explanation of context window
    4. Compare the answer with a trusted source