1z0-1145-1 Questions and Answers

Comprehensive and Detailed Explanation:

To automate the order-to-cash process in Oracle Fusion AI Agent Studio, the agent must access structured invoice data (via Business Object tools) and send out those invoices to customers (via the Email tool). The Business Object tool allows the agent to interact securely and efficiently with transactional data in Fusion Applications, ensuring all invoice information is accurate and up to date. The Email tool then automates outbound communication, generating and delivering invoice documents to customer email addresses.

Oracle documentation clarifies:

“Combining Business Object tools and the Email tool enables end-to-end automation of transactional processes—from data extraction and transformation to automated customer communications.”

(Reference: Oracle Fusion AI Agent Studio Tools Integration Guide, 2024, p. 59)

Other options either involve irrelevant tools or miss the integration required for this use case.

Practical takeaway:Always pair data access (Business Object) with communication (Email) for end-to-end workflow automation.

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:

Oracle provides aprebuilt narrative reporting agent template(B) to simplify and automate financial report generation. Teams can further streamline outputs by customizing thesystem prompt(D) to ensure the agent’s narrative aligns with company standards in tone, detail, and content.

Oracle documentation:

“Prebuilt templates and prompt customization enable finance teams to automate narrative report generation rapidly, supporting consistency and compliance with internal standards.”

(Reference: Oracle Fusion AI Agent Studio Reporting Automation Guide, 2024, p. 40-41)

Multi-language and data visualization changes are advanced customizations, not primary streamlining features.

Practical takeaway:Use templates and prompt tuning for fast, standardized report automation.

Comprehensive and Detailed Explanation:

Oracle Fusion AI Agent Studio provides pre-built templates that serve as foundational blueprints for common business scenarios. Selecting and customizing a relevant template enables rapid configuration, extension, and integration—supporting both external (via External REST tool) and internal (via Business Object tool) data requirements.

Oracle documentation:

“Pre-built templates accelerate deployment and ensure best-practice workflows, allowing teams to extend functionality and integrate diverse data sources with minimal manual effort.”

(Reference: Oracle AI Agent Studio Templates Guide, 2024, p. 10)

Building from scratch is time-consuming; generative services do not deliver agent workflows; email is not core to the requirement.

Practical takeaway:Always start with a template for hybrid data and workflow needs.

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.

Comprehensive and Detailed Explanation (Exact Extract from Oracle documentation):

To ensure agents generate customer communications that reflect the company’s specific tone, Oracle Fusion AI Agent Studio enables users to tailor both the topics and the system prompts in agent templates. Creating additional topics (Option A) allows the agent to handle a broader range of customer interaction scenarios, ensuring communication is both contextually relevant and aligned with company standards. Modifying the system prompt (Option D) is critical—this is where users can specify not just instructions, but explicit preferences for language, tone, and manner of response. According to the Oracle Fusion AI Agent Studio documentation:

“System prompts define the agent’s personality, communication style, and response format. By specifying company-preferred tone and language in the system prompt, organizations ensure consistent messaging across all customer touchpoints. Topics, meanwhile, extend the agent’s conversational coverage, enabling it to address organization-specific scenarios and maintain the desired tone in diverse situations.”

(Reference: Oracle Fusion AI Agent Studio Implementation Guide, “Customizing Agent Templates for Branding and Communication,” 2024 release, p. 32-33)

Options B and C would restrict the agent’s abilities or disable essential functions, which is not aligned with the goal.

Comprehensive and Detailed Explanation:

Comparative analysisin Oracle Fusion AI Agent Studio allows you to objectively evaluate new agent versions against previous ones using identical input and reference sets. This identifies changes in logic quality, correctness, and efficiency, ensuring measurable improvements before broader rollout.

Oracle documentation:

“The comparative analysis tool is essential for continuous agent improvement, supporting controlled A/B testing and quantitative assessment of new agent logic.”

(Reference: Oracle Fusion AI Agent Studio Testing Guide, 2024, p. 23)

Semantic search and document tool are not comparison features for agent logic.

Practical takeaway:Use comparative analysis to validate and demonstrate agent enhancements.