Anthropic CCAR-P Dumps - Pass Claude Certified Architect - Professional Exam in 2026

Project-scoped configuration is the appropriate mechanism for repository-specific settings that must remain consistent across collaborators. Claude Code recognizes `.claude/settings.json` as the shared project settings file and `.mcp.json` as the project-level MCP server configuration. When these files are committed to source control, every engineer receives the same definitions through the repository's normal clone, pull, review, and versioning workflow.

Anthropic's scope hierarchy distinguishes project configuration from user and local configuration. Files under the user scope apply to one engineer and are not automatically shared. Operating-system environment variables are also workstation-specific and require separate configuration management. Managed settings can be distributed centrally, but they are primarily intended for organization-wide security policies and controls that must be enforced by administrators; they are less appropriate when the configuration belongs specifically to one repository.

Shared configuration should contain server definitions and environment-variable references, but not plaintext credentials. Each engineer can resolve required secrets through an approved local secret mechanism while retaining identical server names, transports, arguments, and non-sensitive settings. Project MCP servers also remain subject to workspace trust and approval controls before execution.

Study Guide references/topics: [Claude Code configuration scopes](https://docs.anthropic.com/en/docs/claude-code/settings); project-scoped MCP servers; `.mcp.json`; repository-based operational standardization; secure secret separation.

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Regulatory assessment must begin by establishing scope. Option B determines whether the regulation applies by examining processed data, affected jurisdictions, users, and deployment purpose. Without this analysis, clause mapping could apply irrelevant obligations or omit applicable ones. Option E establishes the platform's existing compliance capabilities, including audit records, retention controls, access governance, data residency, and compliance-export functionality. Anthropic's Trust Center provides control and certification information, while the Compliance API supports programmatic access to activity and governance records. Options A and D occur after regulatory clauses have been mapped and gaps identified. Option C follows prioritization and approval of remediation actions.

Study Guide references/topics: Regulatory applicability; compliance affordance inventory; control mapping; gap assessment; residual risk; remediation sequencing.

Package 1 is designed for security and compliance review because its threat model identifies relevant threats and attack paths, its residual-risk register documents the risks remaining after controls, and its control-mapping table connects safeguards to organizational or regulatory requirements. Package 2 is designed for the product manager because delivered capabilities and roadmap dependencies directly support prioritization, release planning, sequencing, and lifecycle ownership. An engineering implementation team would ordinarily need component diagrams, interface contracts, configuration schemas, deployment instructions, and operational runbooks rather than primarily risk-governance artifacts. An executive sponsor generally needs a concise outcome, cost, risk, and decision summary instead of feature-level dependency details. Effective architecture communication must therefore adapt the content and level of detail to each audience's responsibilities and decision rights.

The absence of company-specific training does not establish unbiased behavior. A foundation model may reflect demographic associations or unequal treatment patterns originating from pretraining data, model behavior, prompt framing, retrieval content, or the surrounding decision workflow. Because candidate screening can materially affect employment opportunities, the complete system must be evaluated across relevant protected groups before deployment. Appropriate measures include selection-rate differences, false-positive and false-negative rates, calibration, intersectional slices, and human override patterns. Disclosure that AI is used does not replace empirical fairness testing. Protected-class labels need not have been explicit in training data for proxy variables or inferred attributes to produce disparities. Provider policies similarly do not validate a customer's specific implementation. Anthropic system cards document discriminatory-bias evaluations, reinforcing the need for application-level testing. Claude model system card

Credentials must never be supplied as prompt content. Prompts can be retained in traces, debugging output, caches, or logs, and model output may inadvertently expose included secrets. Credentials should instead be resolved server-side through an approved secret store or delegated authentication mechanism. Option C is also a serious gap because post-response RBAC occurs after unauthorized data has already entered model context. Authorization must be enforced before retrieval and prompt construction. Options A, D, and E describe appropriate controls: least-privilege service identities, per-user scoped OAuth, and encrypted transport. Anthropic's prompt-leak guidance recommends excluding unnecessary sensitive information, while Claude Code security relies on permission-based enforcement rather than natural-language instructions alone. Reduce prompt leak