CCAR-F Context and Reliability Practice Question
Exhibit
{
"model": "claude-3-5-sonnet-20240620",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Below is the company handbook...",
"cache_control": {"type": "ephemeral"}
},
{
"type": "text",
"text": "How do I request PTO?"
}
]
}
]
}Refer to the exhibit. A developer is implementing the provided JSON structure to optimize an HR chatbot. What is the primary reliability benefit of using the 'cache_control' parameter in this context?
⚠ Common exam trap
Many students incorrectly assume the 'cache_control' parameter directly alters model creativity or token generation limits, confusing caching mechanics with generation parameters.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
It reduces latency for subsequent requests using the same content block.
The 'cache_control' parameter enables prompt caching, which is vital for reliability in production. By caching the 'company handbook' block, the developer ensures that subsequent queries about the same document are processed much faster. This reduces the variability in response times and prevents the model from needing to re-parse massive datasets for every individual user interaction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It forces the model to ignore any previous conversation history.
Why it's wrong here
Cache control does not clear the conversation history; rather, it identifies specific blocks of content that should be stored for reuse. The model still perceives the entire message chain as part of the context window, assuming the history is provided in the messages array as required by the API.
- ✓
It reduces latency for subsequent requests using the same content block.
Why this is correct
The ephemeral cache allows Claude to skip the heavy computation required to ingest the first part of the prompt in future calls. This leads to significantly faster response times (lower time-to-first-token), which is a critical component of system reliability and user experience in real-time chat applications.
- ✗
It automatically updates the handbook when the source file changes.
Why it's wrong here
Prompt caching is a manual implementation at the API level and does not feature automatic synchronization with external files. If the handbook changes, the developer must send a new request with the updated text and a new cache marker to ensure the model is working with the most current information.
- ✗
It encrypts the handbook text to prevent model hallucinations.
Why it's wrong here
Caching and encryption are distinct concepts; while Anthropic maintains high security standards, the cache_control feature is for performance and cost optimization. It does not provide an encryption layer for the text content, nor does it directly alter the model's tendency to hallucinate beyond providing consistent context.
About these practice questions
This CCAR-F question is part of Courseiva's 271-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCAR-F practice question is part of Courseiva's free Anthropic certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the CCAR-F exam.