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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Applications and Integration | 33.1% | - Message Batches and Prompt Caching - Claude API and Client SDKs - Multimodal and Structured Outputs - API Integration and Application Development - Software Engineering Fundamentals - Streaming, Error Handling and Reliability |
| Topic 2: Tools and MCPs | 10.6% | - Building Custom Tools and MCP Servers - Model Context Protocol - Tool Use and Tool Schemas |
| Topic 3: Security and Safety | 8.1% | - Secure Tool Use and Guardrails - Safety and Responsible Development - Prompt Injection and Untrusted Content - Application Security |
| Topic 4: Prompt and Context Engineering | 11% | - Prompt Engineering - Context Engineering - Context Management and Long-Context Techniques |
| Topic 5: Agents and Workflows | 14.7% | - Agent Construction with Claude - Agent Architecture - Agent Patterns and Frameworks |
| Topic 6: Eval, Testing, and Debugging | 2.6% | - Evaluation, Testing, and Debugging |
| Topic 7: Claude Code | 3.1% | - Claude Code Configuration and Extensibility |
| Topic 8: Model Selection and Optimization | 16.8% | - Performance Optimization - Model Capabilities and Trade-offs - Cost and Latency Optimization - Model Selection |
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NEW QUESTION # 78
Your team uses several plugins across multiple Claude applications, and a recent plugin update introduced a regression. The team had not been tracking plugin versions, so the team cannot easily identify which version was previously working. How would you address this?
Answer: A
Explanation:
Option B is correct because plugin dependencies and releases must be versioned deliberately if the team wants reproducible behavior and a reliable rollback path. Claude Code's plugin documentation supports explicit semantic versions in plugin manifests and marketplace entries, and the plugin system uses the resolved version as part of update detection and caching. Version constraints can also keep dependent plugins on a tested compatible range until the team intentionally upgrades.
The incident happened because the team could not determine which plugin version had previously worked.
Explicit tracking solves that directly: record the version in project configuration, pin known-good releases where stability matters, test upgrades, and change versions through reviewed configuration updates. This creates traceability and makes regression isolation much faster.
Option A removes useful extension functionality instead of managing it. Option C treats third-party change as uncontrollable even though the platform provides version-management mechanisms. Option D automatically moving everything to the latest release increases change frequency and can reproduce the same regression problem.
Therefore, B is the correct configuration-management response. Relevant Study Guide topics: Claude Code plugins, semantic versioning, dependency constraints, reproducible configuration, controlled upgrades, rollback, and configuration management.
NEW QUESTION # 79
Your Claude application's prompt was written months ago and has not been updated. The team has discovered through evals that the prompt produces good results on common cases but underperforms on a specific category of inputs that has grown in volume.
How would you respond?
Answer: B
Explanation:
The correct response is iterative prompt improvement backed by evaluation , making A the appropriate choice. The supplied Claude Certified Developer Foundations material explicitly selects A. When production input distribution changes, a prompt that previously met requirements can become inadequate. The correct engineering response is not to preserve the prompt merely because it once worked; prompts are application components that should evolve with observed workload behavior.
Anthropic's official evaluation guidance describes prompt development as a cycle involving test cases, an initial prompt, iterative testing and refinement, final validation, and deployment. Success criteria should be specific and measurable, and evaluations should include representative cases that expose known failure modes.
The underperforming category should therefore be incorporated into the evaluation set. The team can modify instructions, examples, context organization, or other prompt components, then compare the revised prompt against both the newly important category and existing common cases. This prevents improvement in one segment from silently producing regressions elsewhere.
B avoids the defect instead of correcting it. C risks degrading previously successful behavior. D creates unnecessary architectural fragmentation.
Relevant Claude Developer topics: prompt iteration, evaluation-driven development, regression testing, representative test sets, prompt optimization, and production feedback loops .
NEW QUESTION # 80
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 # 81
You maintain a Claude application that uses Claude Sonnet 4.5 across several production workflows.
Anthropic released Claude Sonnet 4.7, which your evaluation suite shows performing 8% better on your highest-volume task. However, this version produces different output formatting on two of your structured- extraction prompts that downstream consumers parse with regex-based code.
To roll out the upgrade, you would...
Answer: A
Explanation:
Option A is correct because a model upgrade should be treated as a controlled application change, not a simple identifier substitution. Anthropic's evaluation guidance recommends defining measurable success criteria and running task-specific evaluations that mirror real production behavior, including edge cases. Its model-migration guidance likewise recommends testing replacement models before moving production workloads.
Here, the new model improves the highest-volume task but changes output formatting on structured-extraction prompts. That means the migration has both a quality benefit and a compatibility risk. The correct response is to tighten the output contract, re-run evaluations against the parsing/schema boundary, then deploy progressively with a feature flag and a per-workflow rollback path. This limits blast radius and preserves a known-good recovery option.
Option B pushes an unverified behavior change directly into production. Option C makes downstream parsing permissive, which can conceal schema drift instead of enforcing a stable contract. Option D permanently preserves a fragile implementation and discards the measured quality improvement.
Taking the model version stated in the question as the scenario, A is the correct lifecycle strategy. Relevant Study Guide topics: model migration, regression evaluation, structured output, compatibility testing, progressive rollout, rollback, and production change management.
NEW QUESTION # 82
Your Claude application's content policy specifies categories of content it should not produce under any circumstance. The application currently has no mechanism to enforce this policy, and content matching these categories is appearing in the application's output.
How would you enforce the content policy?
Answer: A
Explanation:
Option D is the strongest enforcement design because an unconditional content policy requires an application- level control between model generation and user delivery. Prompt instructions are valuable for steering Claude, but they are probabilistic controls and should not be treated as the sole enforcement mechanism when prohibited categories must never be exposed.
Anthropic's guardrail guidance recommends layered safeguards including screening, validation, monitoring, and filtering rather than relying exclusively on prompts. Its prompt-leak guidance specifically recommends output screening and post-processing, including deterministic techniques such as keyword matching, regular expressions, or other text-processing mechanisms where appropriate.
A improves the probability of policy compliance but cannot guarantee that every generated response will satisfy an externally defined application policy. B explicitly abandons the requirement. C detects violations only after exposure, which is unsuitable when the content must not reach users.
A production architecture can combine system instructions, structured classification, policy engines, deterministic rules, and model-based moderation, but the decisive requirement is enforcement before output delivery. Relevant Claude Developer topics are guardrails, output filtering, content moderation, deterministic enforcement, defense in depth, safe application boundaries, and production Claude application design.
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NEW QUESTION # 83
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