1z0-1145-1 Exam Dumps - Oracle Fusion AI Agent Studio Foundations Associate - Rel 1

Comprehensive and Detailed Explanation:

The External REST tool allows agents to query third-party logistics platforms in real time using defined REST APIs. This tool is specifically designed for cross-application integration, supporting any external service with a standards-compliant API, and returning data directly into the agent workflow.

Oracle documentation details:

“External REST tools facilitate seamless interaction with external systems, enabling use cases like real-time order tracking, status updates, and supply chain event monitoring without leaving the Oracle Fusion ecosystem.”

(Reference: Oracle Fusion AI Agent Studio Integration Guide, 2024, p. 31)

User Session and Document tools do not enable live external integration; Business Object tool is only for internal Fusion data.

Practical takeaway:Use the External REST tool whenever agents must interact with outside systems.

Comprehensive and Detailed Explanation:

The most secure and auditable method is to introduce ahuman-in-the-loop approval stepbefore sensitive data changes are committed. This means agent-initiated updates (such as changes to employee records) are held until reviewed and approved by a designated human manager or administrator, adding a necessary compliance checkpoint.

Oracle confirms:

“Incorporating human approval for sensitive operations is a key security and compliance feature, reducing risk and ensuring regulatory and organizational controls are enforced for critical data changes.”

(Reference: Oracle Fusion AI Agent Studio Security Practices, 2024, p. 33)

Automated alerts (A) and restricted hours (C) are useful but do not provide direct control or prevent unauthorized changes in real time.

Practical takeaway:Always use approval workflows for sensitive, high-stakes data operations.

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.

Comprehensive and Detailed Explanation:

Evaluation test data in Oracle Fusion AI Agent Studio is primarily used to assess the quality and reliability of agent responses. Users upload test inputs and reference outputs to compare actual agent performance against expected results during offline testing phases.

From the Oracle documentation:

“Evaluation sets allow developers to simulate real-world usage by supplying a battery of inputs and expected outputs. This enables objective measurement of agent performance before deployment and helps identify gaps or errors in agent logic.”

(Reference: Oracle AI Agent Studio Testing Guide, “Offline Evaluation with Test Sets,” 2024, p. 18)

Option A is incorrect—evaluation sets do not fine-tune the LLM, and Option C misrepresents their function.

Practical takeaway:Always use uploaded evaluation sets for objective, reference-based agent testing.