Intermediate course
Get Better at Prompting and Reviewing AI Responses
Learn how to fix your prompts, stop AI workslop, and deal with hallucinations to get quality results from AI
Intermediate
Course facts
- Last updated 05/2026
- Instructor: Nicolle Merrill
- prompting, review and practical AI use
What you'll learn
Practical outcomes
- Define what quality AI outputs look like in your work
- Evaluate which factors impact AI outputs
- Evaluate AI outputs
- Spot and navigate most common hallucinations in AI outputs
- Practical ways to improve your prompts at work
- Apply different prompt techniques to prompts to improve quality of outputs
- Select and add data to your prompts to personalize outputs
- Define the jobs to be done so AI understand what you actually need
Curriculum
6 sections • 34 lectures • 2h 37m total length
Overview of the Prompting Workflow7 lectures • 27min
- Behind the question: How do I get better at prompting?01:45
- The five factors that affect your prompt outputs05:13
- Demo: Same prompt, different models03:40
- Activity: Compare outputs between models01:28
- Demo: AI tool memory types06:03
- Activity: Get to know your system memory settings01:51
- The prompting workflow: Define, Prompt, Evaluate, Iterate06:32
Define the job to be done4 lectures • 20min
- Why we define the work before we prompt07:34
- Defining the job to be done05:17
- Defining "good" before you start05:58
- Activity: Define what good looks like for a work task01:14
Write better prompts10 lectures • 55min
- Prompt skill levels: From vague requests to well-defined tasks07:14
- Demo: Three ways to write prompts that improve your outputs09:40
- Demo: Prompt techniques to guide and improve your AI outputs10:30
- Activity: Level up an existing prompt00:51
- The missing pieces that improve all prompts: context and criteria06:27
- Adding and selecting the right data as prompt context08:19
- Activity: Sort the data02:50
- Prompt power moves: Get AI to clarity before answering05:05
- How to choose the right prompting technique03:01
- Activity: Rework your best prompt00:51
Evaluate AI outputs4 lectures • 27min
- Diagnosing what's wrong with outputs by naming the problem07:31
- The most common reasons outputs fail, from easiest to hardest to spot01:19
- Spotting the most common hallucinations in work tasks10:49
- Rewriting prompts to reduce hallucinations07:46
Improve your outputs and prompts (Iteration)4 lectures • 18min
- The iteration loop: Giving specific, actionable feedback to the model11:53
- Activity: Iterate on the prompt00:44
- Using the iteration process helps you write better prompts02:59
- Knowing when to stop iterating and do it without AI02:41
Prompt design and reuse5 lectures • 11min
- Using prompt templates and libraries to make prompting easier03:36
- Using AI to write a prompt02:41
- Using AI to create your own prompt templates and libraries02:19
- Activity: Use AI to create 20 prompts for your job00:35
- Wrap up: Your AI learning journey ahead01:33
Who it is for
- People already using AI at work
- Managers coaching their teams on prompting and producing quality AI results
- Anyone who wants to improve the quality of their AI outputs
Course description
Overview
Employees are using AI tools to create low-effort, passable looking work that ends up creating more work for their coworkers. We define AI workslop as AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task. Of 1,150 U.S. based full-time employees across industries, 40% report having received AI workslop in the last month. It occurs mostly between peers, but 18% of workslop is also sent to managers by direct reports, and 16% of AI workslop comes from managers to their teams, or even from higher up than that. Harvard Business Review, AI-Generated “Workslop” Is Destroying Productivity Take this course to make sure your AI work isn't workslop. You'll learn how define and refine prompts that create quality outputs in your daily work. This is an intermediate AI course, designed for people who use AI regularly at work but need help improving the quality and consistency of their AI responses. This course skips basic prompting tips (because you've learned that already) and shows you how to write stronger prompts and fix what's not working to get quality AI responses you can actually use at work. You’ll learn how to: Follow an easy prompt workflow: A simple workflow: Define → Prompt → Evaluate → Iterate Evaluate which factors create quality AI outputs (hint: it's not just writing prompts!) Define the jobs to be done/work tasks so AI understands what you actually need Add different prompt techniques and levels to prompt building blocks to get responses are structured and usable Evaluate AI responses instead of guessing if they’re “good” Spot and navigate hallucinations Iterate to improve responses instead of starting over Use AI to help you write better prompts faster, build reusable prompts, prompt libraries for your job Practical ways to apply this to real work tasks At the end this course, you'll also get a personalized snapshot of where your AI skills stand and suggestions to move forward. The goal of this course is to get you from “this is kind of helpful” to “this is actually usable.”
Instructor
Nicolle Merrill
Nicolle Merrill AI Literacy Skill Instructor When I first learned about AI, I was completely lost. It was 2017 and everything was made for engineers and data scientists. I was not either of those things and all the content was boring, jargon-filled, and mostly not useful. I swore that if I ever learned AI well enough to teach it to people, I'd make it far more interesting. So here we are! I spent 8 years building enterprise AI products in HR, FinTech, and DevOps, where I worked as a conversational AI designer and later, a prompt engineer. Then I decided to launch my own training firm, Boring AI, specifically for teaching AI skills to non-technical learners. Since 2022, I've taught over 25,000 people across 20+ countries. My goal is to help you learn AI without needing a technical background or boring you to death. My teaching style is hands-on, beginner-friendly, and most importantly jargon-free. My training focuses on real-world practice rather than theory so you can quickly apply what you learn. You're not going to get the history of ML or transformers. I'm not going to give you the hype either. Instead, I'll teach you the applied AI skills and approaches that keep you up-to-date in a rapidly changing workplace. Best of all, you're not getting the same generated content you'd get from an LLM. You can use AI to learn about AI, but sometimes you need a human to make sense of it all. So all of my courses are designed from questions asked by employees like you about generative AI. That means each lesson contains answers about using AI at work that are relevant for your job right now. Outside of Udemy courses, I work with mid-size companies to build AI upskilling programs for non-technical teams and run work redesign sprints. I'm also professor at Porto Business School where I teach executives in digital transformation and generative AI product development to MBA students. Before working in AI, I was as a career coach at Yale School of Management. I wrote a book on upskilling for an AI-driven workplace, called Punch Doubt in the Face: How to Upskill, Change Careers, and Beat the Robots. As a result, I'm always thinking about to teach you the most relevant AI skills that prepare you to navigate a changing workplace and career.
