In this module, you will understand what an AI agent actually is from a manager’s perspective, without descending into engineering detail. You will see how agents perceive context, reason about goals, take actions through tools, and remember relevant state, learn to distinguish agents from chatbots, RPA bots, and full software systems, and form a clear-eyed view of where agents reliably outperform humans and where they predictably fail. The labs have you classify and re-frame sample tasks by their fit for an agent.

In this module, you will take a manager-level tour of the platform your teams will likely run on. You will explore IBM watsonx Orchestrate from a team leader’s point of view, make sense of the broader IBM agentic AI architecture in plain English, and learn where a manager rather than a developer actually shapes what gets built. The labs have you explore a self-service watsonx Orchestrate free-trial environment as a team-manager user and reflect on the capabilities you would prioritize first.

In this module, you will make your first concrete design decision: which team topology fits the work in front of you. You will learn a small number of practical topologies that recur in real agentic deployments, match a topology to the nature of the work and its risk profile, weigh the trade-offs each topology forces between speed, control, and learning, and recognize hybrid and evolving topologies. The labs have you propose a topology for a provided team and then redesign it under a different one to expose the trade-offs.

In this final module, you will assemble everything from Modules 1 through 4 into a cumulative project: an Agentic Team Readiness and Topology Brief. The deliverable describes a real or realistic team and its work, assesses which areas could plausibly run as an agentic team within twelve months, addresses stakeholder misconceptions and concerns, and proposes a team topology with a platform-readiness reflection. The module closes with a wrap-up featuring an SME interview, a day-in-the-life view of an Agentic Operations Lead, and a bridge into the design work of Course 2.