Overview

This course introduces you to agentic AI tools and the ways they can fit into workplace workflows. You'll learn how these tools actually work, how to figure out whether they're a good match for different tasks, and how to put them to use responsibly with human oversight, accountability, and compliance in mind.

Syllabus

Module 1: Understanding AI Agents

What AI agents are and how they differ from automation, chatbots, and decision-support tools
Core characteristics of AI agents: goal-driven behavior, multi-step execution, autonomy, and context-awareness
The agentic AI landscape today: desktop agent tools, enterprise agent platforms, developer tools, and AI assistants with tool access
How agentic tools work under the hood: the AI model, planning loop, tool access, and containment boundary
Live demonstration of an agentic tool performing a multi-step government workflow task
Human oversight roles: human-in-the-loop, human-on-the-loop, and human-in-command
Common misconceptions and key risks, including prompt injection
Current federal AI policy direction and its implications for government agencies

Module 2: Evaluating Agentic Tools for Government Work

The evaluation mindset: understanding the workflow before evaluating the tool
Identifying agent roles in a workflow: intake, analysis, recommendation, and escalation
The Agent Evaluation Blueprint: goal, trigger, inputs, actions, boundaries, and oversight
Permission models and data access: folder-level vs. organization-wide, network access, and least privilege
Prompt injection: what it is, how it works, and why agentic tools are uniquely vulnerable
Questions to ask before saying yes: a practical pre-approval checklist
Hands-on activity: evaluate a realistic agentic tool proposal for a government workflow

Module 3: Where Agentic Tools Fit — and Where They Don't

Appropriate use cases: case triage and routing, document analysis and extraction, internal coordination, and monitoring and alerts
High-risk or inappropriate uses of agentic tools in government
Operational risks: over-automation, over-reliance, and rubber-stamping
Drift: data drift, concept drift, and objective drift — and how to detect them
Early operational warning signs that an agentic tool may be failing
Hands-on activity: red team a deployed agentic tool scenario to identify risks and recommend action

Module 4: Governing Agentic Tools in Your Organization

Why governance is essential — and why no centralized federal AI regulator is coming
Governance vs. technical controls: policies, oversight bodies, and accountability structures
Legal, ethical, and procurement considerations: FedRAMP, ATO, vendor data handling, and records retention
Security for agentic tools: access controls, prompt injection defenses, anomaly monitoring, and incident response
Lifecycle management: design, pilot, deploy, monitor, update or retire — including regulatory sandbox alignment
Performance monitoring and metrics: accuracy, override rates, equity indicators, and user satisfaction
Workforce readiness and change management: role clarity, training on tool limitations, and avoiding fear and over-trust
Deployment readiness checklist: a practical gate review before any agentic tool goes live
Hands-on activity: conduct a readiness gate review for a proposed agentic tool deployment