# AI Agents for Government Workflows Course Understanding, Evaluating, and Governing Agentic Tools Canonical URL: ## Overview AI agents represent a new class of artificial intelligence tools capable of planning, acting, and adapting across multiple steps to complete tasks — and they're now shipping in commercial products that government agencies are already evaluating and deploying. This course provides a practical, no-code introduction to agentic AI for the government workforce. Participants learn what AI agents are, how they differ from traditional automation and chatbots, how agentic tools work at a technical level, and how to evaluate whether a specific tool is appropriate for a given government workflow. The course covers the current agentic AI landscape, permission models and security considerations — including prompt injection — and a structured evaluation framework participants can apply immediately. Governance, lifecycle management, and workforce readiness round out the program, aligned with the White House's 2026 National Policy Framework for AI. This course focuses on evaluation, governance, and informed decision-making rather than technical development or coding. ## What you'll learn - Explain what AI agents are and how they differ from automation, chatbots, and decision-support tools - Describe how agentic tools work at a high level — the AI model, planning loop, tool access, and containment boundary - Evaluate whether a specific agentic tool is appropriate for a given government workflow using a structured framework - Identify risks, limitations, and operational warning signs specific to agentic AI systems - Apply human oversight models (HITL, HOTL, HIC) and governance frameworks to agentic tool deployments - Assess organizational readiness for agentic tool deployment using a practical checklist - Identify security considerations specific to agentic tools, including prompt injection and permission models ## Curriculum #### 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 ## Schedule - Jun 17, 2026 8:00am–12:00pm — Live Online - Jul 13, 2026 8:00am–12:00pm — Live Online - Aug 17, 2026 1:00pm–5:00pm — Live Online - Sep 23, 2026 1:00pm–5:00pm — Live Online - Oct 20, 2026 8:00am–12:00pm — Live Online - Nov 10, 2026 1:00pm–5:00pm — Live Online - Dec 1, 2026 8:00am–12:00pm — Live Online ## Instructors ### Bruce Gay — Instructor Bruce is an engaging trainers and program manager who brings 25+ years practical experience to deliver effective and experiential training to students. Able to engage adult learners with a range of backgrounds and professional experiences. Successful at building effective stakeholder relationships and coordinating multi-disciplinary teams for solution delivery. Bruce has over 25 years of project and program management experience across multiple industries. He has a Masters degree from The George Washington University and a B.A. from the University of North Carolina Chapel Hill. Bruce currently runs his own freelance training and consulting business, helping project managers and team leaders improve their business skills, become better leaders, and achieve professional greatness. Bruce is a well-received speaker in the areas of design thinking, project management, cross-team collaboration, and AI tools for projects, and has presented at regional and international conferences. ### Steve Pesklo — Instructor Steve is an energetic trainer who focuses on applying technical concepts to everyday work practices. He is the founder and president of SoftLake Solutions, a company that specializes in providing data and AI applications to identify fraud for Internal Audit, Criminal Investigations, Forensic Accounting, Privacy, and Compliance. Steve brings a large amount of experience across multiple industries and government agencies. He is an expert in implementing large data analysis projects across the world, including Inland Revenue in the UK and Argentina, New Zealand, Africa and across Europe. Previously, he was the manager of Data Architecture and Data Services for a large mortgage company. He is a frequent speaker on data analytics and project management topics and speaks fluent German. He has been teaching at the Graduate School for over 10 years. Steve has an M.B.A. from the University of St. Thomas and a B.S. in Computer Science from California Lutheran University and the Universität Salzburg in Austria. He is certified as a Certified Fraud Examiner (CFE), Project Management Professional (PMP), and a Certified ScrumMaster (CSM). ### Brian Simms — Instructor Brian Simms is a seasoned educator and training leader with extensive experience developing and delivering innovative learning programs in project management and emerging technologies. Over the course of his career, he has designed adaptive learning models that combine instructor-led sessions, live online experiences, and self-paced study, ensuring professionals can access training in flexible and effective ways. His work has emphasized the integration of artificial intelligence into professional development, helping organizations and individuals understand how AI can be applied to solve real-world challenges in leadership, project execution, and decision-making. In addition to his instructional expertise, Brian has guided curriculum development, led large training initiatives, and advanced the use of collaboration tools that improve learner engagement and retention. His depth of experience and forward-looking perspective make him uniquely equipped to prepare federal professionals to navigate the complexities of data, project management, and the transformative potential of AI. ### Clarissa J. Corbin — Instructor Clarissa J. Corbin is an accomplished corporate trainer, project manager, and business consultant with over 25 years of experience designing and delivering impactful learning experiences. As President and CEO of Projections Training Solutions, she partners with federal agencies, private corporations, and international organizations to provide results-driven training in leadership, project management, business analysis, and emerging technologies. Clarissa has trained more than 10,000 professionals worldwide, serving clients such as the DoD, NASA, FEMA, Microsoft, Citibank, PNC Bank, Del Monte, and Symantec. Her expertise has taken her across the globe, leading initiatives in Singapore, China, Japan, South Korea, Africa, Jamaica, Trinidad & Tobago, and St. Thomas, USVI. Known for her ability to engage diverse audiences and create interactive, high-impact sessions, Clarissa equips participants with practical solutions they can apply immediately. At Graduate School USA (GSUSA), Clarissa is regarded as one of the most versatile and trusted instructors. She teaches across multiple programs. She played a pivotal role in redesigning the flagship “Managing for Results” course, while also contributing to the development and review of numerous others. Her contributions have earned her two GSUSA Customer Excellence Awards and a two-year appointment to the GSUSA Instructor Advisory Council, underscoring her commitment to innovation, quality, and learner success. ### Natalya H. Bah — Instructor Natalya Bah has been a part-time instructor at the Graduate School USA for over fifteen years. Natalya teaches across multiple curricula, including Leadership and Management, Project Management, and Human Resources. She has created a curriculum for the school, including Change Management Workshops and project management courses. She has served as an action learning coach, instructor, and facilitator for government leadership programs in the Center for Leadership and Management. Natalya also provides self-assessments and dynamic team-building sessions on behalf of the Graduate School USA. Outside of Graduate School USA, Ms. Bah is a self-employed business owner providing executive coaching, training, and consulting services to the public and private sectors. She created the Define and Achieve Your Goals Process™ and is a certified Birkman Method© Consultant. She received her Master of Science degree in Project Management from George Washington University’s School of Business, where she served as a teaching assistant and received the Project Management Award. She is also a certified Project Management Professional (PMP). ### Michiel Pruijssers Michiel is a Principal Designer and Forward Deployed Engineer at Microsoft's Industry Solutions Engineering Division, where he partners with strategic enterprise customers to architect and ship production AI systems. With over 15 years of experience, he operates at the intersection of user research, design, engineering, and cloud architecture, anchored by deep expertise in machine learning. His career spans senior roles at Snorkel AI, Determined.ai, and earlier Microsoft teams behind foundational AI products including LUIS.ai, Azure Bot Service, and Azure Stack, where he led both customer discovery and platform design for some of the industry's most technically ambitious ML offerings. He pairs rigorous qualitative research with hands-on building, shipping his own production SaaS products in Python while also teaching students through cohort-based AI courses. His instruction is grounded in real practice: what it takes to design, build, and operate AI systems that actually hold up in the wild. ## Pricing **Tuition:** $675