1z0-1145-1 Oracle Fusion AI Agent Studio Foundations Associate - Rel 1 Questions and Answers

Comprehensive and Detailed Explanation:

Oracle best practices require that, before publishing a new agent:

(C)Design time/offline testingis performed, using evaluation sets, to verify that all workflows and responses behave as intended

(D)System prompts and topicsare reviewed and adjusted to ensure accuracy, clarity, and alignment with organizational goalsFrom Oracle documentation:

“Thorough pre-publication testing and configuration review are mandatory steps, ensuring robust, error-free deployments that meet both functional and compliance requirements.”

(Reference: Oracle Fusion AI Agent Studio Deployment Checklist, 2024, p. 16-18)

Other options are either not required or not relevant to the deployment workflow.

Practical takeaway:Always test and review configuration before agent publication.

Comprehensive and Detailed Explanation:

Reasoning agents in Oracle Fusion AI Agent Studio are designed for higher-order tasks: they can plan, optimize, and execute multi-step workflows. In contrast, Answer Agents are intended for contextual question-and-answer tasks, offering direct responses based on user input.

According to Oracle:

“Reasoning agents employ advanced workflow capabilities, enabling them to chain multiple actions and optimize outcomes based on user-defined objectives. Standard Answer Agents are focused on providing contextual guidance, leveraging AI to address specific user queries without workflow automation.”

(Reference: Oracle Fusion AI Agent Studio Agent Types Overview, 2024, p. 13-14)

Options A and C misstate agent functions.

Practical takeaway:Choose Reasoning Agents for complex workflows; Answer Agents for direct Q&A.

Comprehensive and Detailed Explanation:

Secure and up-to-date data retrieval in Oracle Fusion is best achieved by configuring the agent to access business objects within Fusion itself, where data governance, security policies, and real-time updates are enforced.

From the official documentation:

“Business objects in Fusion Applications are subject to strict security and data freshness guarantees. Agents configured to interact directly with these objects inherit these protections, ensuring all data retrieved is current and appropriately secured.”

(Reference: Oracle Fusion AI Agent Studio Data Security Guide, 2024, p. 28)

Other methods either obscure data, risk data loss, or weaken security.

Practical takeaway:Always utilize native business object access for secure, real-time data.

Comprehensive and Detailed Explanation:

Agent tracing in the Metrics Reporting Dashboard allows users to examine every step of an agent’s execution—including prompts, responses, input/output data, and timing—at a granular level. This detailed tracing helps diagnose logic issues, analyze user interactions, and fine-tune performance.

Oracle documentation states:

“The agent trace log offers a transparent, step-by-step view of agent activity, making it invaluable for root-cause analysis and optimizing agent logic and user experience.”

(Reference: Oracle AI Agent Studio Diagnostics and Monitoring, 2024, p. 23)

Tracing does not alter permissions or roles; it is a diagnostic, not a configuration, feature.

Practical takeaway:Use agent tracing to debug, audit, and optimize agent performance.

Comprehensive and Detailed Explanation:

Fusion’s role-based access controls (RBAC) are the definitive method for managing agent access to sensitive information. By configuring RBAC, developers ensure that each agent’s permissions mirror those of the intended users, preventing unauthorized data access or manipulation.

Oracle’s documentation states:

“Role-based access control is enforced at both the user and agent levels, ensuring that data exposure aligns strictly with security policies and user responsibilities within the enterprise.”

(Reference: Oracle Fusion Security Administration Guide, 2024, p. 12-14)

System prompts and folder permissions provide context or content restrictions, not security enforcement at the data level.

Practical takeaway:Always audit and configure RBAC settings when deploying agents for sensitive tasks.

Comprehensive and Detailed Explanation:

ThePersonal and Employment Details Agentis designed to provide managers with direct conversational access to employee records, along with the ability to initiate HR transactions (such as promotions) through deep link generation and seamless workflow integration.

Oracle documentation:

“The Personal and Employment Details Agent is the default template for HR self-service, empowering managers with instant data access and actionable HR transaction pathways in a single conversational UI.”

(Reference: Oracle Fusion AI Agent Studio OOTB Agents Catalog, 2024, p. 14)

Other agents focus on notifications, benefits, or leave—not transactional employee management.

Practical takeaway:Choose Personal and Employment Details Agent for unified HR operations.

Comprehensive and Detailed Explanation:

Multi-agent solutions are deployed for complex, multi-step business processes where different agents perform specialized roles (e.g., approvals, notifications, escalations), and must coordinate to achieve an end-to-end result.

Oracle states:

“Multi-agent orchestration is recommended when processes involve multiple domains or require sequential and conditional hand-offs, ensuring modularity, reusability, and optimal automation.”

(Reference: Oracle Fusion AI Agent Studio Orchestration Guide, 2024, p. 51)

Single-function or simple data lookup tasks do not require this level of orchestration.

Practical takeaway:Use multi-agent architectures for scalable, cross-functional automation.

Comprehensive and Detailed Explanation:

Oracle AI Agent Studio is built around a modular framework of agent teams, tools, templates, and topics.

Agent teams: Enable collaborative design, testing, and management of agents.

Tools: Extend functionality—such as data access, communication, or external integration.

Templates: Provide starting points for common business use cases.

Topics: Define the conversational and functional boundaries of each agent.From Oracle’s documentation:

“The architecture is centered on reusable templates, customizable topics, and pluggable tools, all organized and governed by agent teams for enterprise scalability.”

(Reference: Oracle Fusion AI Agent Studio Overview, 2024, p. 7-8)

Options A and B mention unrelated or partial features.

Practical takeaway:Leverage the full modular system for rapid agent deployment and customization.

Comprehensive and Detailed Explanation:

Latency measures the time it takes for the agent to respond, which directly impacts user experience. Token count reflects how much data is processed and helps gauge the cost of running the agent, as Oracle’s AI services are often billed per token.

According to Oracle:

“Monitoring latency ensures users are not left waiting, maintaining satisfaction and engagement. Tracking token usage provides transparency regarding processing costs, which is vital for budgeting and operational efficiency. Together, these metrics help optimize both agent performance and cost management.”

(Reference: Oracle AI Agent Studio Metrics and Reporting, “Latency and Token Analytics,” 2024, p. 11)

Accuracy is tested separately; latency and tokens are about speed and cost.

Practical takeaway:Regularly monitor both latency and tokens to balance user satisfaction and operational expenses.