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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applications and Integration | 33.1% | - Streaming and Batch API - SDK and third-party integration - Claude Messages API - Vision capabilities |
| Topic 2: Tools and Model Context Protocol (MCP) | 10.6% | - MCP server development - Tool integration and usage |
| Topic 3: Claude Code | 3.1% | - Claude Code configuration and usage |
| Topic 4: Prompt and Context Engineering | 11% | - Context window management - Structured output handling - Prompt design and structuring |
| Topic 5: Agents and Workflows | 14.7% | - Workflow vs autonomous agents - Memory and context management - Agent architecture principles - Claude Agent SDK usage |
| Topic 6: Security and Safety | 8.1% | - AI application security - Guardrails and safety controls |
| Topic 7: Model Selection and Optimization | 16.8% | - Latency and performance trade-offs - Claude model family characteristics - Cost and token optimization |
| Topic 8: Evaluation, Testing, and Debugging | 2.6% | - Error handling and debugging - Output evaluation and validation |
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NEW QUESTION # 54
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?
Answer: D
Explanation:
A is the correct lifecycle architecture. The supplied Claude Certified Developer Foundations item explicitly selects A . A session is a state boundary, so its lifecycle must define when accumulated conversation state remains valid and when that state must be discarded. Anthropic's Managed Agents documentation establishes that a session maintains conversation history across multiple interactions and provides explicit session operations including creation, update, archive, and deletion.
A therefore addresses all three required controls: expiration , reset , and fresh-session creation . Expiration prevents indefinitely retained conversational state. Reset triggers allow the application to clear state when events such as logout, workflow completion, tenant switching, or explicit user reset occur. Fresh-session rules prevent context belonging to an earlier task from influencing a logically unrelated conversation.
B relies exclusively on timeout and does not cover event-driven resets. C places lifecycle correctness on users instead of the application. D applies global reset behavior and omits independent per-session expiration semantics.
Relevant Claude Developer topics: Agent Architecture, session lifecycle, multi-turn state, context boundaries, state reset, stale-context prevention, and session management .
NEW QUESTION # 55
You are setting up Claude Code for a new project repository. Your team has shared coding standards, preferred libraries, and project-specific context that every developer working on the repository should have available when they use Claude Code.
How would you set this up?
Answer: D
Explanation:
Option C is correct. Claude Code uses CLAUDE.md as the standard mechanism for supplying persistent project-level instructions and context. Anthropic's Claude Code documentation states that project instructions can be stored in ./CLAUDE.md or ./.claude/CLAUDE.md and shared with team members through source control. Appropriate content includes coding standards, architectural decisions, project conventions, build/test commands, preferred workflows, and information developers would otherwise need to repeat to Claude during every session. The /init command can also generate an initial CLAUDE.md based on the repository.
A wiki may be valuable for human documentation, but Claude Code does not automatically receive that material as project context. B creates developer-specific configuration and risks inconsistency across the team. D places the information in a human-facing README but does not use Claude Code's purpose-built persistent instruction mechanism.
Therefore, C gives the repository a shared, version-controlled source of Claude-specific project guidance.
Relevant Study Guide topics: CLAUDE.md, project configuration, persistent instructions, repository context, team standards, and configuration management.
NEW QUESTION # 56
Your team's Claude agent has accumulated several customizations that bypass the SDK's defaults, including custom history management, retry logic, and error handling. A new team member has proposed reverting all the customizations to maintain the codebase more easily. The tech lead disagrees and says each customization was added for a reason.
How would you advise the team?
Answer: B
Explanation:
The correct approach is to evaluate each customization independently against both its original requirement and the capabilities currently supplied by the Claude SDK. Custom code has an ongoing maintenance cost, but automatically removing it is unsafe because some modifications may encode genuine application requirements that the standard SDK behavior still does not address. Conversely, automatically retaining every customization can preserve obsolete complexity after the SDK has evolved.
This is particularly relevant because Anthropic's SDKs already provide capabilities that developers might otherwise implement themselves. Official Claude API documentation states that SDKs provide built-in request formatting, error handling, retries, timeouts, and other integration functionality. For example, transient connection, rate-limit, and server errors are retried automatically with exponential backoff.
Therefore, each custom history, retry, or error-management layer should be reviewed for its actual purpose. If an SDK primitive now provides equivalent behavior, removing duplicate code improves maintainability. If the customization still satisfies a distinct requirement, it should remain.
The supplied exam source explicitly identifies D as the intended answer. Relevant topics: Agent Construction, SDK capabilities, abstraction boundaries, technical-debt management, retries, error handling, and agent state management.
NEW QUESTION # 57
A Claude application that worked well in testing is now occasionally returning outputs that mention information not present in the input. The development team initially assumed the model was hallucinating, so they asked you to troubleshoot.
What would you do first?
Answer: C
Explanation:
Option A follows disciplined production debugging: diagnose the actual failure mode before changing architecture or prompts. An output containing unsupported information might indeed be hallucination, but similar symptoms can result from stale conversation state, incorrect retrieval, unexpected tool output, prompt injection, incorrect request construction, or mismatched model/configuration versions.
A production trace should capture the user input, system instructions, relevant conversation history, retrieved content, tool calls and results, model/version, request parameters, response, and identifiers necessary to compare successful and failing cases. This establishes whether the model invented a fact or whether that fact entered context through another path.
B changes the model before establishing causality. C may eventually be useful if the confirmed problem is insufficient grounding, but implementing RAG before diagnosis can hide rather than explain the defect. D similarly changes prompting before verifying that prompt behavior is responsible.
The engineering sequence should be observe, reproduce, classify the failure, form a hypothesis, apply a targeted correction, and validate the correction with evaluations. Relevant Study Guide topics: production troubleshooting, observability, tracing, hallucination analysis, prompt injection, context failures, regression diagnosis, and lifecycle monitoring.
NEW QUESTION # 58
You are building a Claude application that needs to deliver model output to end users as it is generated, instead of waiting for the full response to complete.
The Claude API mechanism you would use is...
Answer: B
Explanation:
Option B is the intended and technically correct answer. The supplied Claude Developer exam source selects streaming responses. Streaming allows the client application to begin receiving output before generation of the complete message has finished, reducing perceived latency for interactive user experiences.
Anthropic's official Messages API documentation states that setting stream: true causes responses to be delivered incrementally through Server-Sent Events (SSE) . Claude can stream text deltas as well as other event types, including structured tool-use and extended-thinking events where applicable. Anthropic's SDKs provide corresponding synchronous or asynchronous streaming helpers.
The application consumes events as they arrive, updates the UI progressively, and then handles the final event or stop reason when generation completes. This architecture is particularly useful for chat interfaces and other latency-sensitive interactive experiences.
A addresses output structure, not progressive transmission. C is designed for asynchronous, throughput- oriented processing rather than immediate user interaction. D reduces processing cost and latency for repeated prompt prefixes but does not itself turn a response into an incremental stream.
Relevant Claude Developer topics: Messages API, streaming, SSE, incremental tokens, latency, event handling, interactive applications, and API response mechanics .
NEW QUESTION # 59
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