Oracle AI Agent Studio for Fusion Applications Developers (D1114494GC10) — Lesson 3: Agent Development for Fusion Workflows, Approvals, Exceptions, and Human Handoffs

Learning Objectives

• Assess how agent development for fusion workflows, approvals, exceptions, and human handoffs changes application behaviour, data, accounting, or service delivery.
• Operate a repeatable sequence with known inputs, controls, outputs, and rollback points.
• Resolve security, correctness, performance, recoverability, and support readiness.

Detailed Topics

• Agent Development for Fusion Workflows
• Approvals
• Exceptions
• Human Handoffs
• ownership, prerequisites, data, and acceptance criteria for agent development for fusion workflows, approvals, exceptions, and human handoffs
• security, control, integration, performance, recovery, and support implications

Instructor Demonstration

Demonstrate agent development for fusion workflows, approvals, exceptions, and human handoffs within a Fusion Applications AI agent grounded in enterprise data, invoking controlled actions, respecting permissions, and escalating to humans. Use representative data and capture action logs, approval history so another practitioner can verify the result.

Hands-On Exercise

Complete a controlled Oracle AI Agent Studio for Fusion Applications Developers (D1114494GC10) activity focused on agent development for fusion workflows, approvals, exceptions, and human handoffs. Introduce a realistic case of excessive tool permissions, isolate the cause, apply a reversible correction, and rerun the acceptance checks.

1. Record the requirement, environment, identities, dependencies, data, controls, and expected result.
2. Perform the workflow and capture course-specific evidence before and after each material change.
3. Test normal, boundary, failure, security, reconciliation, recovery, and operational conditions.
4. Document the root cause, correction, rollback, owner, support action, and next improvement priority.

Scenario Analysis

• Separate mandatory requirements from convenience requests and local workarounds.
• Compare the proposed approach against security, reliability, usability, cost, and audit expectations.
• Select the smallest supportable change and assign follow-up ownership.

Troubleshooting Guidance

When agent development for fusion workflows, approvals, exceptions, and human handoffs does not produce the expected result, confirm scope, effective dates, identities, data context, dependencies, and recent changes. Review the most relevant action logs, approval history before editing configuration. Test one reversible hypothesis at a time, verify recovery, and confirm that the fix does not create excessive tool permissions elsewhere.

Validation Checklist

• Prerequisites, ownership, data context, settings, and expected outcomes are documented.
• The result is reproducible and supported by action logs, approval history.
• Security, controls, data quality, integration, performance, recovery, and support conditions are reviewed.
• Exceptions, corrective action, rollback, approvals, monitoring, and handover are recorded.

Lesson Outcome

Learners can apply Agent Development for Fusion Workflows, Approvals, Exceptions, and Human Handoffs in a realistic Oracle AI Agent Studio for Fusion Applications Developers (D1114494GC10) situation and defend the result with course-specific evidence.