Course Overview
TOPThis course prepares professionals to design, supervise, and govern AI agents in the workplace using structured, human-in-the-loop methods. Participants work with authentic business artifacts to create safe, repeatable workflows that increase efficiency while protecting human judgment. Learners progress through seven modules covering workflow thinking, supervised agent mode, governance principles, and a full capstone blueprint.
Scheduled Classes
TOPWhat You'll Learn
TOP- Build foundational AI agent literacy, including drafts vs. decisions.
- Map real workplace workflows using business artifacts.
- Apply supervised agent mode to structure multi-step AI workflows.
- Design a complete agent-supported workflow using a standardized template.
- Apply governance principles (Transparency, Oversight, Documentation, Consistency, Proportionality).
- Identify organizational risks and safeguards.
- Produce a review-ready Workplace Agent Blueprint.
Outline
TOPModule 1 – AI Literacy for Professionals
- Understand what AI agents can and cannot do
- Recognize the difference between drafts and decisions
- Explore Email, Meeting, and Research Agents
- Hands-on: Draft vs. Decision analysis using real emails
Module 2 – Workflow Thinking in the Workplace
- Map the path work takes from request to completion
- Identify roles (Requester, Drafter, Reviewer, Approver)
- Distinguish draft steps from decision steps
- Hands-on: Workflow mapping using email or spreadsheet datasets
Module 3 – Supervised Agent Mode
- Shift from one-off prompting to structured agent workflows
- Learn agent roles: Collector, Classifier, Summarizer, Drafter
- Identify human stop-points and escalation steps
- Hands-on: Convert a real AI interaction into a supervised workflow
Module 4 – Template-Based Agent Workflow Design
- Select a real workplace use case and dataset
- Use the full workflow template (inputs, outputs, roles, stop-points)
- Draft a complete supervised agent workflow
- Hands-on: Build your first agent workflow draft
Module 5 – Supporting Work & Learning with Agents
- Distinguish appropriate agent support from substitution
- Analyze meeting summaries and task management examples
- Define safe boundaries for agent behavior
- Hands-on: Support vs. Substitute classification and boundary rules
Module 6 – AI Agent Failure Lab (NEW)
- Examine how AI agent failures occur in real workplace scenarios
- Identify workflow design gaps that lead to errors and harm
- Diagnose missing stop-points, unclear ownership, and governance breakdowns
- Connect failure analysis to the need for structured oversight
- Hands-on: Failure investigation, governance diagnosis, and safeguard design
Module 7 – Governance, Ethics, and Organizational Risk
- Apply governance principles to agent workflows
- Identify risks in Data Cleanup, Knowledge Base, and Research agent scenarios
- Assess transparency, oversight, documentation, consistency, and proportionality
- Hands-on: Governance checklist and workflow improvements
Module 8 – Capstone: Workplace Agent Blueprint
- Select one agent workflow to document fully
- Complete all blueprint template sections clearly and defensibly
- Define governance considerations, risks, and safeguards
- Prepare a review-ready supervised agent workflow
Appendix – Optional Exercises
- Additional enrichment activities by module and agent type
Prerequisites
TOP- Basic computer literacy
- Familiarity with daily workplace workflows
- No AI or programming knowledge required
Who Should Attend
TOP- Operations and Project Managers
- HR and Learning & Development professionals
- Customer Service, IT Support, and Service Delivery roles
- Data/Reporting professionals
- Governance, Compliance, and Quality leaders
- Anyone responsible for improving workflows or using AI safely