Updated: Aug 30, 2026
No. of Questions: 97 Questions & Answers with Testing Engine
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| Certification Vendor: | Anthropic |
|---|---|
| Exam Name: | Claude Certified Developer – Foundations (CCDV-F) |
| Exam Number: | CCDV-F |
| Available Languages: | English |
| Passing Score: | 720 (scaled score, range 100–1000) |
| Exam Price: | $125 USD |
| Certificate Validity Period: | 12 months from award date |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 53 |
| Related Certifications: | Claude Certified Associate – Foundations (CCAO-F) Claude Certified Architect – Professional (CCAR-P) Claude Certified Architect – Foundations (CCAR-F) |
| Exam Format: | Multiple-choice, Multiple-response |
| Recommended Training: | Anthropic Partner Academy Free Training Official Exam Guide (Version 1.0, July 2026) |
| Exam Registration: | Anthropic Partner Academy Pearson VUE Scheduling |
| Sample Questions: | Anthropic CCDV-F Sample Questions |
| Exam Way: | Online proctored (Pearson OnVUE) or in-person at Pearson VUE test center; Closed-book, identity-verified proctored exam |
| Pre Condition: | No mandatory prerequisites; Recommended: 1–5 years software development experience + 6+ months hands-on Claude/LLM development; Requires membership in Claude Partner Network (free) and eligible organization email |
| Official Syllabus URL: | https://claude.com/blog/four-role-based-claude-certifications |
| Section | Weight | Objectives |
|---|---|---|
| Claude Code | 3.1% | - Claude Code configuration and usage |
| Model Selection and Optimization | 16.8% | - Cost and token optimization - Claude model family characteristics - Latency and performance trade-offs |
| Security and Safety | 8.1% | - AI application security - Guardrails and safety controls |
| Evaluation, Testing, and Debugging | 2.6% | - Output evaluation and validation - Error handling and debugging |
| Agents and Workflows | 14.7% | - Memory and context management - Claude Agent SDK usage - Workflow vs autonomous agents - Agent architecture principles |
| Prompt and Context Engineering | 11% | - Prompt design and structuring - Structured output handling - Context window management |
| Applications and Integration | 33.1% | - Vision capabilities - Claude Messages API - Streaming and Batch API - SDK and third-party integration |
| Tools and Model Context Protocol (MCP) | 10.6% | - MCP server development - Tool integration and usage |
Question 1
Your enterprise has a contract with AWS that requires Claude API calls to flow through Amazon Bedrock rather than the direct Anthropic API. Your team is building a new Claude application and is unfamiliar with this constraint.
How would you build the application?
A. Build the application against the direct Anthropic API now and migrate to Bedrock in a follow-up release once the team has more experience with the Bedrock API.
B. Build two parallel implementations of every call, one for the direct Anthropic API and one for Bedrock, and pick the faster one at runtime.
C. Build the application against the direct Anthropic API and ignore the contractual requirement to route Claude calls through Amazon Bedrock.
D. Configure the application to invoke Claude through the Bedrock-compatible API path while keeping the application's logic provider-agnostic.
Question 2
You are designing a Claude application that maintains user sessions across multi-turn conversations. The product team has asked how the application will handle session lifecycle: when sessions should expire, how state is reset, and how the application avoids carrying stale context into new conversations.
How would you design session lifecycle?
A. Define a single short session timeout that applies across all conversations and treat the timeout as the application's complete session lifecycle mechanism.
B. Define state reset triggers tied to specific application events but apply them across all sessions globally, with no per-session expiration rules.
C. Define explicit session expiration rules, state reset triggers, and rules for starting fresh sessions so stale context does not leak into new conversations.
D. 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.
Question 3
Your agent is processing tasks that take 30 to 60 minutes to complete. Each task has well-defined intermediate checkpoints, and the team wants the agent to be able to resume from the most recent checkpoint if a process is interrupted.
How would you implement this resumability?
A. Run two copies of the agent in parallel for every task and use whichever one finishes first as the source of truth.
B. Increase the agent's timeout to several hours so that interruptions become rare enough to ignore in practice.
C. Restart the task from the beginning whenever a process is interrupted.
D. Apply a checkpointing pattern that persists the agent's intermediate state and reloads that state when resuming an interrupted task.
Question 4
The product team has described a new Claude feature in business terms: "agents should help our analysts produce client memos faster." You need to convert this into actionable technical requirements for the engineering team.
Your first step would be to...
A. Interpret the functional and infrastructure requirements implied by the business goal.
B. Ask the analysts about the current memo production process to see where they think Claude could be introduced as a prompt-driven drafting step.
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. Assess what similar agent-based features have been built internally or in the industry and use those precedents to scope the technical approach.
Question 5
A Claude application is occasionally refusing to answer questions that should be in scope, including questions the application has answered correctly in the past. You want to investigate.
What is the first step of your investigation?
A. Examine traces of the refused requests to identify what triggers the refusal, whether input patterns, system prompt content, or other context.
B. Identify which questions have been refused and compare them against previously answered questions to determine what changed between the successful and refused interactions.
C. Assess whether the refusals cluster around specific input patterns, question types, or time periods by analyzing the distribution of refused requests in the logs.
D. Test whether removing or adjusting those instructions resolves the behavior.
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: D | Question 4 Answer: A | Question 5 Answer: A |
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