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IBM

Foundations of Agentic Teams

IBM via Coursera

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Overview

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Leaders across industries face growing pressure to integrate AI agents into their teams, yet most lack a working mental model of what an agentic team actually is or how it differs from traditional automation. This foundational course, Foundations of Agentic Teams, builds that model from the ground up. You will study what AI agents are, how they perceive context, reason about goals, take actions, and remember state, and learn to distinguish them from chatbots, RPA bots, and traditional software. A manager-level tour of IBM watsonx Orchestrate and the broader IBM agentic AI architecture establishes platform fluency, clarifying which decisions belong to the manager and which to the platform team. You will examine real-world examples of agentic teams across customer service, knowledge work, operations, and software delivery, and then make your first design decision: choosing a team topology that fits the work, the risk profile, and the organizational context. By course completion, you will have produced an Agentic Team Readiness and Topology Brief for a real or realistic team.

Syllabus

  • Why Agentic Teams Now
    • In this opening module, you will build an accurate picture of what is changing in how organizations get work done and why managers are the linchpin of the shift to agentic teams. You will trace the move from human-only teams to AI-augmented teams to agentic teams, study real examples of hybrid human-AI teams across customer service, knowledge work, operations, and software delivery, and separate the reality of AI agents from the media hype that derails team conversations. The labs have you audit a team operating rhythm for agentic opportunities.
  • Anatomy of an AI Agent
    • 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.
  • The IBM Agentic AI Stack and watsonx Orchestrate
    • 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.
  • Team Topologies for Hybrid Teams
    • 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.
  • Cumulative Project and Course Wrap-Up
    • 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.

Taught by

Starweaver

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