Claude Certified Developer - Foundations Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A0

  - Option A correctly separates sampling configuration from context management. Temperature historically controlled the randomness of token selection; it did not increase the number of tokens Claude could accept within a request. Anthropic's current Messages API documentation continues to describe temperature in terms of randomness and, for newer model generations, marks manual temperature control as deprecated. Therefore, changing temperature cannot solve a context-capacity problem. Long transcripts instead require context-engineering techniques. Appropriate approaches include chunking documents, summarizing earlier material, retrieving only relevant sections, or using context editing /compaction so high-value information remains visible while unnecessary material is removed. Anthropic's context-editing guidance explicitly supports summarization and replacement of growing conversation history to keep long-running workloads within usable context limits. B incorrectly conflates generation parameters with context capacity. C may save some tokens but removes persistent application instructions and is therefore architecturally unsound. D modifies an unrelated parameter without addressing the root cause. Relevant Study Guide topics: context windows, token budgets, sampling parameters, summarization, chunking, and context engineering.