CCDV-F Practice Questions

A.  

Ask the analysts about the current memo production process to see where they think Claude could be introduced as a prompt-driven drafting step.

B.  

Assess what similar agent-based features have been built internally or in the industry and use those precedents to scope the technical approach.

C.  

Examine what model capabilities and tier options are available and determine which best supports the memo drafting workflow described by the product team.

D.  

Interpret the functional and infrastructure requirements implied by the business goal.

A.  

Define explicit session expiration rules, state reset triggers, and rules for starting fresh sessions so stale context does not leak into new conversations.

B.  

Define a single short session timeout that applies across all conversations and treat the timeout as the application's complete session lifecycle mechanism.

C.  

Define explicit session expiration rules but rely on users to start new conversations when they want fresh context, with no automatic reset triggers in the application.

D.  

Define state reset triggers tied to specific application events but apply them across all sessions globally, with no per-session expiration rules.

A.  

Ask the product team to specify quality, latency, and cost targets, then select the model whose tradeoffs best fit those targets.

B.  

Run every Claude model on a representative sample and pick whichever scores best on a generic benchmark.

C.  

Choose a mid-tier model and ship the feature, because mid-tier models work for most use cases without specified targets.

D.  

Choose the largest, highest-capability Claude model, on the grounds that "best results" is most likely to mean highest quality.

A.  

Run Claude API calls in a separate thread pool isolated from the rest of the service so the main event loop is not affected.

B.  

Replace the existing async REST service with a synchronous service to match the call style of synchronous Claude SDK clients.

C.  

Use the Claude SDK's async client and structure Claude calls as awaitable operations alongside the rest of the service's async code.

D.  

Make synchronous Claude API calls and block the async event loop until each call completes before processing the next request.

A.  

Manually inspect every response before downstream processing so a human reviewer catches any malformed JSON before the application passes the response to downstream systems.

B.  

Add output validation that parses Claude's response against the expected schema and treats malformed output as a recognized error path with retry or fallback handling.

C.  

Switch to free-form text output so the application no longer depends on JSON parsing for any of the responses it sends to downstream systems during normal operation.

D.  

Retry the same request repeatedly until valid JSON appears in the model's response, with the retry loop adding delay to the application's response time on affected requests.

A.  

Pass validation failures directly to downstream systems and let each downstream system decide how to handle the malformed output.

B.  

Disable output validation until the underlying cause of validation failures has been identified and addressed in a future release.

C.  

Treat validation failures as a recognized error path that triggers retry, repair, or fallback logic before failing the user request.

D.  

Tell users that validation failures are unavoidable and instruct them to perform manual accuracy checks before relying on outputs.

A.  

Prompt engineering focuses on the model's response, while context engineering focuses on the user's input across many sessions in a long-running multi-step Claude application.

B.  

Prompt engineering is the older term for prompt design, while context engineering is the newer term that has replaced it in modern Claude applications across the industry.

C.  

Prompt engineering shapes individual prompts for specific outputs, while context engineering manages how content flows across turns and steps and takes steps to keep relevant state visible.

D.  

Prompt engineering and context engineering each address content the team gives Claude, but the team can group them under a single workflow because the practices use overlapping techniques.

A.  

Run the agent only during business hours when humans are available to monitor its activity, treating the schedule as the primary control mechanism for destructive operations.

B.  

Add Claude hooks that intercept database operations and apply deterministic checks, such as blocking destructive queries or requiring approval, before the queries execute.

C.  

Switch to a higher-capability Claude model on the grounds that a more capable model is less likely to run destructive queries during normal operation across all requests.

D.  

Add a system prompt instruction telling the agent to be careful with database operations on every request the application handles during normal operation across all incoming traffic.

A.  

Increase the agent's timeout to several hours so that interruptions become rare enough to ignore in practice.

B.  

Apply a checkpointing pattern that persists the agent's intermediate state and reloads that state when resuming an interrupted task.

C.  

Run two copies of the agent in parallel for every task and use whichever one finishes first as the source of truth.

D.  

Restart the task from the beginning whenever a process is interrupted.

A.  

Repeated short-lived HTTP polling requests, where the application opens a new HTTP connection each time it checks for updates.

B.  

A WebSocket, because WebSockets are designed for bidirectional, persistent, real-time communication between the client and the streaming service.

C.  

A single long HTTP request the server holds open indefinitely, with no standard WebSocket framing on the connection.

D.  

File-based communication where the service writes new updates to disk and the application polls the file system for changes.