5 Steps to Building AI Agents That Actually Work(US)
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AI agents are everywhere right now.
But most agents operate at the knowledge or task layer. They retrieve information. They trigger simple actions.
Real enterprise work is different.
It runs across complex systems like SAP, ServiceNow, Workday, Oracle Fusion, NetSuite, and enterprise databases, and across processes like order management, procure-to-pay, month-end reconciliation, RMA processing, and customer support operations.
These workflows span multiple systems, approvals, validations, and operational controls. They require secure access, orchestration across applications, reliable execution, and governance over how AI interacts with critical systems.
In this Product Hour, we’ll explore why many agent approaches struggle to deliver value—and what it takes to run enterprise agents in production. You’ll see how to build agents that connect AI with enterprise apps, APIs, and data to execute multi-step workflows with guardrails, approvals, resilience, and full operational visibility.
What will you learn?
- Where most AI agents get stuck
- Key agentic patterns for enterprise workflows
- Enterprise design principles for reliable agents
- Agents in action: real business use cases
- What’s next for enterprise AI agents