# Advanced Prompt Design & Reasoning Strategies for Government Professionals (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/advanced-prompt-design-reasoning-strategies-for-government-professionals-self-paced>

## Overview

This advanced course is designed for government professionals who already understand the fundamentals of AI prompt engineering and want to move beyond basic prompting into precision prompt design and reasoning control.

Building on the concepts introduced in [AI Prompt Engineering for the Government Workforce](https://www.graduateschool.edu/courses/ai-prompt-engineering-for-the-federal-workforce), this course focuses on how expert users design prompts intentionally - not just to generate responses, but to control reasoning, surface uncertainty, reduce errors, and improve reliability in complex government use cases.

Participants will learn how to design multi-prompt systems, apply self-critique and adversarial prompting, manage ambiguity and uncertainty, and evaluate AI outputs using comparative techniques. The emphasis is on advanced cognitive strategies, not tools or automation, making the course fully tool-agnostic and applicable across government roles.

## What you'll learn

- Design multi-prompt systems that break complex tasks into controlled reasoning stages 
- Apply self-critique and adversarial prompting to identify weaknesses and reduce AI errors 
- Use constraint-first prompting to control scope, exclusions, and acceptable outputs 
- Prompt AI systems to surface uncertainty rather than guess or hallucinate 
- Evaluate AI outputs using comparative prompting and confidence calibration techniques 
- Optimize prompts for clarity, efficiency, and repeatability without sacrificing quality

## Curriculum

#### Module 1: Prompt Architecture & Multi-Prompt Systems

- Explain the difference between single-prompt tasks and multi-prompt reasoning systems.

- Decompose complex work into discrete prompt roles.

- Design a coordinated set of prompts that each serve a specific reasoning function.

#### Module 2: Reasoning Control Through Self-Critique & Adversarial Prompting

- Use self-critique prompts to identify weaknesses in AI outputs.

- Apply adversarial prompting to surface gaps, risks, and assumptions.

- Improve output quality without adding new source material.

#### Module 3: Constraint-First Prompting & Uncertainty Control

- Design prompts that explicitly control scope, exclusions, and failure conditions.

- Instruct AI to surface uncertainty instead of guessing.

- Reduce hallucinations by shaping acceptable behavior in advance.

#### Module 4: Comparative Prompting & Prompt Optimization

- Use comparative prompting to identify weaknesses and inconsistencies.

- Evaluate outputs by analyzing disagreement across prompts.

- Optimize prompts for efficiency without degrading output quality.

## Instructors

### 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).

## Pricing

**Tuition:** $675