AI Agents for Workflows (Self-Paced)

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