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| Section | Weight | Objectives |
|---|---|---|
| Domain 5: Securing and Governing Agentic Workflows | 15% | - Protect against prompt injection and data leakage - Use Model Armor, Agent Gateway, and Agent Registry - Implement authentication and authorization for agents - Monitor audit logs and compliance - Apply governance policies and human-in-the-loop controls |
| Domain 4: Evaluating and Deploying Agentic Workflows | 22% | - Implement continuous evaluation pipelines - Design evaluation datasets and methodologies - Monitor, troubleshoot, and optimize agents in production - Select deployment targets: Agent Runtime, Cloud Run, GKE - Deploy and scale agentic workflows |
| Domain 1: Building Agents Using Low-Code Tools | 13% | - Test and iterate low-code agents - Configure agent triggers, workflows, and responses - Design and configure agents using low-code platforms - Integrate data sources and knowledge bases |
| Domain 2: Using Coding Agents for Application Development | 17% | - Integrate coding agents with development workflows - Select and configure coding agents - Use coding agents in secure sandboxed environments - Manage MCP servers and custom skills |
| Domain 3: Developing Custom Agents | 33% | - Build agents with the Agent Development Kit (ADK) - Implement RAG pipelines and vector retrieval - Integrate enterprise data sources and APIs - Orchestrate multi-agent workflows using MCP and A2A - Implement Agent Identity and permissions - Design agent architectures and model selection - Configure sessions, memory, and state management |
>> New Professional-Agentic-Architect Exam Objectives <<
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NEW QUESTION # 46
You are implementing a custom skill in the Antigravity CLI to automate service deployments. When tasks run in Agent Mode, the CLI does not detect the skill and skips user confirmation before executing deployment commands. You want to enable effective global skill discovery while ensuring human approvals are required for high-risk actions.
What should you do?
Answer: C
Explanation:
The Antigravity CLI discovers global skills from the dedicated user configuration directory: ~/.gemini
/antigravity-cli/skills/ < skill-name > /SKILL.md. The SKILL.md file must include valid YAML frontmatter specifying the skill's name, description, and activation triggers, allowing the CLI's semantic indexing engine to register and expose it across developer projects. For safety governance, high-risk operational procedures (such as production service deployments) must require human confirmation. Executing the CLI without auto- approval flags (omitting -y or --yes) enforces human-in-the-loop validation, causing the CLI to prompt the engineer for explicit confirmation before applying changes. Project-local directories (.agents/skills) do not provide global cross-project skill availability.
Reference: Using coding agents for application development - Antigravity CLI skill discovery, SKILL.md metadata specifications, and human-in-the-loop execution governance.
NEW QUESTION # 47
You are configuring Agent Platform Memory Bank for a wealth management advisor agent deployed on Gemini Enterprise Agent Platform.
During the initial evaluation, you observe that Memory Bank creates duplicate and conflicting memory entries when users update their investment risk tolerance. You need to configure Memory Bank to properly consolidate updated user preferences over time, resolve conflicting information, and restrict memory extraction strictly to relevant personal information and user preferences.
What should you do?
Choose two
Answer: C,E
NEW QUESTION # 48
Your team uses the Antigravity coding agent for both app development and infrastructure as code (IaC) provisioning. Your organization maintains an extensive internal infrastructure style guide that the agent currently includes in its persistent workspace configuration, congesting the context window and degrading reasoning performance during noninfrastructure coding tasks. You need to configure the agent to automatically load and follow the style guide only when infrastructure tasks are initiated.
What should you do?
Answer: B
Explanation:
Persistent workspace configuration files (such as .gemini/rules or global system instructions) load directives into the agent's context window on every turn. Including an extensive IaC style guide across all tasks consumes large token budgets, degrading model reasoning on standard application development tasks.
Packaging the style guide as a custom Agent Skill resolves this context bloat. The skill is defined with a SKILL.md file whose YAML frontmatter specifies explicit activation criteria, keywords, and descriptions.
Antigravity monitors the conversational intent and dynamically injects the skill's detailed style instructions into the active context window only when infrastructure provisioning tasks are detected, keeping unrelated interactions uncluttered.
Reference: Using coding agents for application development - Skill frontmatter activation criteria, context window optimization, and just-in-time instruction loading.
NEW QUESTION # 49
You are establishing team-wide engineering guidelines in an Antigravity workspace for a cloud-native Go project. You want the agent to automatically enforce a set of enterprise architecture conventions on every interaction, while providing a database migration workflow that developers can invoke on demand. You need to structure these customizations using native Antigravity configuration files.
What should you do?
Answer: C
Explanation:
Antigravity organizes workspace guidance into persistent context rules and modular, on-demand capabilities.
Persistent architectural standards, coding conventions, and style constraints are declared within a GEMINI.md file (or inside .gemini/rules/) at the workspace root. The Antigravity engine continuously ingests these markdown rules into the agent's working context, ensuring every code generation and refactoring turn complies with enterprise standards. Conversely, procedural workflows required only intermittently-such as database schema migrations-must not be loaded persistently, as this causes context window congestion.
Instead, they are packaged as custom skills within a dedicated skills directory containing a SKILL.md specification. Developers invoke the skill on demand, allowing the agent to load the migration procedure only when requested.
Reference: Using coding agents for application development - Antigravity workspace configuration, GEMINI.md rules, and modular SKILL.md definition.
NEW QUESTION # 50
You are designing an enterprise multiagent procurement system in Google Cloud. An orchestrator agent processes vendor purchase orders, retrieves contract terms, and invokes downstream tools. Your organization' s security policies require you to stop adversarial prompt injection in vendor documents, and high-risk financial actions must receive explicit compliance officer authorization before execution.
How should you meet these requirements?
Answer: C
Explanation:
Enterprise procurement systems processing external vendor contracts face indirect prompt injection attacks hidden within untrusted purchase orders and contract documents. Implementing dynamic payload inspection via Model Armor security templates at Agent Gateway intercepts ingress user prompts, retrieved document payloads, and egress tool traffic in real time. Model Armor detects adversarial injection patterns and jailbreaks before untrusted tokens reach the foundation model's reasoning loop. Furthermore, to govern high- risk financial actions (such as disbursements or contract sign-offs), the architecture binds human-in-the-loop (HITL) approval policies directly to the sensitive tool definitions within the agent framework. When the orchestrator attempts to invoke a high-risk tool, execution pauses deterministically, requiring explicit authorization from a compliance officer before the transaction executes. Post-execution log sinks alert after unauthorized transactions have already executed, and prompt instructions fail against adversarial attacks.
Reference: Securing and governing agentic workflows - Agent Gateway security, Model Armor injection protection, and tool-level HITL approval policies.
NEW QUESTION # 51
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