Oracle AI for Fusion Cloud CX: AI Agent Studio Developer Training Ed 1 — Lesson 1: AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries

Learning Objectives

• Translate a realistic requirement into an executable approach for AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries.
• Use AI agent use-case canvas and architecture design to verify completeness, access, and process behaviour.
• Explain how to recover safely when an agent use case lacking a clear human escalation boundary occurs.

Detailed Topics

• AI Agent Studio architecture
• Agent use cases
• Personas
• Intents
• Tools
• Grounding
• And security boundaries
• Decision ownership, prerequisites, and acceptance evidence for AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries
• Relevant access, data, integration, performance, recovery, and support considerations

Instructor Demonstration

The demonstration traces AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries from requirement through execution and review. Learners see where evidence should be collected, how AI agent use-case canvas and architecture design supports verification, and which warning signs demand investigation.

Hands-On Exercise

Complete a guided task covering AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries. After establishing a working baseline, reproduce “an agent use case lacking a clear human escalation boundary,” isolate the responsible setting or data condition, apply a reversible fix, and update AI agent use-case canvas and architecture design with before-and-after proof.

1. Define the requirement and identify dependencies before changing the environment.
2. Create a baseline result that can be compared with later changes.
3. Reproduce the exception and test one hypothesis at a time.
4. Complete the evidence record and obtain peer or instructor review.

Scenario Analysis

• Clarify the business trigger, affected roles, required records, and acceptable result for AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries.
• Compare at least two implementation or correction choices and identify which evidence would distinguish them.
• Decide how AI agent use-case canvas and architecture design should be reviewed, approved, retained, and handed to the next owner.

Troubleshooting Guidance

Avoid editing multiple settings at once when troubleshooting AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries. Preserve the failing example, review AI agent use-case canvas and architecture design, and verify whether “an agent use case lacking a clear human escalation boundary” is the root cause. After remediation, repeat the transaction, confirm downstream effects, and record any monitoring action.

Validation Checklist

• Prerequisites and role permissions for AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries have been confirmed before execution.
• The result agrees with the expected values documented in AI agent use-case canvas and architecture design.
• Exceptions are explained with evidence rather than hidden by manual correction.
• The final record names the approver, monitoring point, and next improvement action.

Lesson Outcome

Learners can apply AI Agent Studio architecture, agent use cases, personas, intents, tools, grounding, and security boundaries, explain the decisions made, and defend the result with AI agent use-case canvas and architecture design.