DeepSeek V3.5 coding

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-modelx-deepseek-v35-builders

1. What is the main idea of "DeepSeek V3.5 coding"?

   1. DeepSeek V3.5 is the open-weights model that keeps punching above its weight class on coding benchmarks at a fraction of the cost.
   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 "DeepSeek V3.5 coding"?

   1. open weights
   2. DeepSeek V3.5
   3. coding
   4. MoE

3. Which use of AI fits this topic best?

   1. Let the AI decide what matters without your review
   2. Use the answer before checking whether it fits the situation
   3. MoE architecture with small active parameter count
   4. Use the first answer without checking it

4. What should a careful learner remember about "Know who runs the servers"?

   1. Use AI to draft or organize ideas about DeepSeek V3.5, 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

5. 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 the AI answer as a draft, then check it against a reliable source.
   3. Hide uncertainty so the final answer looks cleaner
   4. Use private or sensitive details before checking permission

6. How should AI output about DeepSeek V3.5 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

7. Name one way to verify an AI answer about DeepSeek V3.5.

8. Which action would help you apply "DeepSeek V3.5 coding" responsibly?

   1. Use the tool to avoid thinking through the tradeoff
   2. Keep going even if the output conflicts with a trusted source
   3. Use the first answer without checking it
   4. Open weights under a permissive license