HIA 101
AI makes it easy to get an answer. The harder part is knowing why the answer looks the way it does, where it can fail, and what needs to be checked before you use it.
Learn what AI can do, how to direct it, and what to check before you use the output.
Learn how to draft, organize, summarize & think with AI.
Apply context & standards to improve AI performance.
Learn how to catch errors before they affect your work.
HIA 101 gives professionals a clearer model of how AI behaves, then connects that understanding to the work they already do.
A plain language overview of how AI behaves, why it gets things wrong, & what to check before using the output.
How to give AI enough context, direction, constraints, & examples to produce something useful.
Learn how to revise & reshape AI output instead of accepting the first response. You’ll improve the quality of the work through clearer direction & stronger review.
Common use cases for writing, planning, summarizing, organizing complex information, & creating first drafts.
What to watch for with privacy, accuracy, & overreliance. How to detect & reduce hallucinations.
Build repeatable skills you can apply across different tasks, tools, & types of work.
HIA 101 focuses on the decisions that shape useful AI work: how you frame the request, what context you provide, how you review the output, and when a human check is required. The goal is a working foundation you can carry into writing, analysis, planning, and other professional tasks.
The seminar draws from HIA’s use of AI across business development, operations, HR, legal, project management, and risk management work. We focus on the choices that improved output, the failure modes that created rework, and the review habits professionals need before using AI more broadly.
Maybe. Using AI and understanding it are not the same thing. If you already understand how AI works, why it gives uneven answers, how to guide it, and where its limits are, you may be ready for Prompting I.
Most tools are marketed around features: faster drafts, summaries, meeting notes, search, automation. Those can be useful, but they do not explain the deeper issues that affect your results: how these systems are built, why they miss things, why they sound confident when they should not, why context has such a strong effect, and why the economics behind the models impact performance.
HIA 101 is for people who want the foundation underneath better use, not just another set of tips. If AI still feels random, overconfident, generic, or harder to control than it should, this class is probably the right place to start.
Because AI is easy to try and harder to understand.
Most people can open ChatGPT, Claude or Copilot and get something back. The harder part is knowing why the answer worked, why it failed, what to change, and when the output needs a human check.
The companies building these tools usually talk about features. They do not spend much time explaining the constraints, tradeoffs, architecture, or economic incentives that shape how the tools behave. HIA 101 explains the essentials in plain English so you can use AI with clearer expectations and better control.
It is practical. The class explains the basics only so you can use AI more effectively in professional work.
You will learn why AI gives incorrect answers, how to give it better direction, and how to avoid wasting time fixing output that missed the point. You will also understand an important reality: AI is designed to produce useful responses, not perfect ones. That difference affects any work that carries your name.
No. This class is built for experienced professionals, including leaders, managers, and senior individual contributors who want a clear foundation without technical jargon.
If you lead people, review work, or make decisions, you need to understand enough about AI to know where it helps, where it fails, and what kind of human oversight is still required. The point is not to teach you your job. The point is to help you understand how AI fits into the work you already know how to do.