IBM Building and Managing Agentic Teams

IBM via Coursera Professional Certificate

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Provider

Coursera Professional Certificate
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

12 weeks, 10 hours a week
Sessions

Self-Paced
Level

Beginner

Found in

Overview

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The IBM Building and Managing Agentic Teams Professional Certificate prepares leaders and managers to build, deploy, and govern agentic teams where humans and AI agents collaborate to execute work. Across five progressive courses, you will develop practical agentic team leadership skills covering team design, human-AI collaboration, agent configuration in IBM watsonx Orchestrate, multi-agent workflow orchestration, oversight, accountability, trust, responsible AI, and performance management for hybrid teams. You will apply structured frameworks to allocate tasks between humans and agents, define roles and decision rights using an adapted RACI, design for trust and psychological safety, and configure working agents at a manager-configuration level. Through hands-on labs in IBM watsonx Orchestrate, you will orchestrate multi-agent workflows, connect agents to enterprise tools and data, design human handoffs and escalation paths, and build human-in-the-loop oversight proportional to risk. The program addresses governance through the IBM AI Ethics and Trust Framework, teaching you to operationalize ethical commitments into daily team rituals. The capstone produces an integrated leadership package you can present in interviews, internal reviews, and program proposals. No coding background required.

Syllabus

Course 1: Foundations of Agentic Teams
Course 2: Designing Human-AI Collaboration and First Agents
Course 3: Deploying and Orchestrating AI Agents
Course 4: Oversight, Accountability, Trust, and Responsible AI
Course 5: Performance Management and Capstone Leadership

Courses

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A single working agent is a starting point; the real value comes from coordinated multi-agent workflows that do real work alongside a team. Most leaders lack practical experience orchestrating agents, connecting them to enterprise systems, and designing the handoffs and oversight that keep workflows safe. This course, Deploying and Orchestrating AI Agents, provides that experience. You will orchestrate multi-agent workflows in your own IBM watsonx Orchestrate free-trial instance, apply safety checkpoints, connect agents to enterprise tools and data through pre-built skills, and design human handoffs and escalation paths that preserve oversight, speed, and accountability. You will then build human-in-the-loop oversight proportional to risk and reversibility, including thresholds, cadences, and review queues. By course completion, you will have produced a Working, Supervised Multi-Agent Workflow with integration specifications, a workflow diagram showing handoffs and escalations, a complete oversight scheme, and a test report covering happy-path, edge-case, and exception scenarios.
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Designing a hybrid team on paper is one thing; configuring an agent that actually works is another. Many leaders struggle to move from conceptual understanding to practical team design and hands-on configuration. This course, Designing Human-AI Collaboration and First Agents, bridges that gap. You will apply structured frameworks to allocate tasks between humans and agents, identifying which tasks should remain human-only on judgment, legal, or motivational grounds. Define roles, responsibilities, and decision rights using an adapted RACI framework, and design for trust, psychological safety, and dignity of work within hybrid teams. Then take your first hands-on step: scope a task, write agent instructions, and configure a working agent in a sandboxed IBM watsonx Orchestrate environment at a manager level. By course completion, you will have produced a Hybrid Team Design Package including task allocation, role definitions, decision-rights map, trust-and-safety brief, onboarding plan, and a configured, working first agent with screenshots and a reflection on iteration.
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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.
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Governance documents that gather dust do not protect teams. Most oversight schemes fail not at design time but at adoption, when review queues go unread and accountability matrices are never opened. This course, Oversight, Accountability, Trust, and Responsible AI, builds the governance backbone that keeps agentic teamwork safe, accountable, trusted, and welcomed by the broader organization. You will build accountability structures that work when both humans and agents act, embed oversight into recurring team operating rhythms so it becomes routine practice, and apply trust, transparency, and explainability practices anchored on the IBM AI Ethics and Trust Framework. You will also address ethical risks specific to agentic teams, including bias, manipulation, and dignity-of-work concerns, and survey legal, regulatory, and workforce considerations. By course completion, you will have produced a Governance and Responsible Agentic AI Package with an accountability matrix, operating-rhythm design, trust plan, responsible-AI operating practice, and an external communication statement.
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Running a hybrid team well over time is the real test of agentic team leadership. Most leaders lack frameworks for evaluating human contribution fairly when work is co-produced with agents, coaching hybrid teams, and managing agents through their lifecycle from launch through retirement. This course, Performance Management and Capstone Leadership, addresses those challenges and then integrates the full program into a portfolio-ready leadership artifact. You will define and measure performance with a balanced metric set, evaluate human contribution using an attribution framework, run coaching, feedback, and escalation routines tailored to hybrid teams, and manage the agent lifecycle so performance improves rather than drifts. You will then assemble the capstone leadership package, integrating design, configuration, governance, and performance from across the program into one coherent story with a tiered communication plan, risk-mitigation appendix, and a written elevator pitch, refined through structured peer review.