Stop Fixing. Start Directing.
Basic AI literacy is no longer enough. To stay competitive, you need to move from asking questions to getting reliable, repeatable results.
Advanced AI Prompting for Editors gives you the structure to do exactly that. You'll learn:
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The 4P Framework for building prompts that deliver consistent output
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Transparency techniques that force AI to show its reasoning so you stay in control
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Structured labeling methods to help AI process your instructions exactly as you intend
Why Editors Choose This Course
Precision Prompting
Structure prompts that work the first time, so you spend less time revising AI output and more time editing.
Transparency & Reasoning
Force AI to show its work so you can review, redirect, and make the final call.
Data Privacy
Learn best practices for protecting IP and client data while using advanced AI tools.
Certificate of Completion
Earn a verifiable credential to validate your AI skills for employers and clients.
Schedule: Advanced AI Prompting for Editors
The difference between an AI prompt that works and a prompt that works reliably is structure. The 4P Framework is a prompt engineering method that delivers more consistent, predictable, and better results.
You'll learn to craft prompts using four essential elements:
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Persona: the role AI assumes
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Purpose: the task and its goals
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Process: the steps AI should follow
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Pattern: the format of the output
With this framework, you'll be able to design good prompts faster, troubleshoot underperforming prompts, and build a library of reliable go-to prompts you can adapt to many projects.
Learning Objectives:
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Identify the four components of the 4P Framework and their function in a prompt
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Construct prompts using Persona, Purpose, Process, and Pattern
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Apply the 4P Framework to common editorial tasks
AI edits shouldn't happen in a black box. When you can't see why the AI made a change, you lose control—and control is what separates editorial judgment from automated output. In this lesson, you'll learn prompting techniques that force AI to show its work:
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Propose Alternatives: Get multiple revision options with the reasoning behind each, giving you choices instead of a single take-it-or-leave-it output.
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Confidence Signals: Ask AI to rate its certainty, helping you prioritize focus your review.
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Disagreement Flags: Prompt AI to flag edits where reasonable editors might differ, surfacing subjectivity so you can make the final call.
Then we'll extend these transparency techniques to rubric prompting, where we’ll have AI create scoring criteria, build a rubric, and assess content against it, with scores and reasoning clearly displayed so you can turn vague AI judgment into documented, repeatable rationale.
Learning Objectives:
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Apply transparency techniques to maintain editorial control over AI outputs
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Construct prompts that produce auditable AI reasoning
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Build and implement rubrics to evaluate content and compare options against defined criteria
In AI editing, the best results often don't come from telling it longer prompts or more detailed descriptions. They come from showing the AI what you want and guiding it through the process.
First, we'll cover how to use examples in your prompts (called "Few Shot prompting"). AI learns better when you show it what you're after, just like a picture being worth a thousand words. This technique is especially powerful when you're matching a specific voice or brand or trying to capture a "feel" that's hard to put into words. You'll learn:
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Format to Follow: providing a sample structure for AI to match
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Like/Don't Like: showing both a good and bad example to steer the AI
Then we'll explore Chain of Thought prompting, a method for breaking complex tasks into smaller steps. Instead of asking AI to do everything at once, you'll list subtasks and prompt AI to work through them one by one. This approach leads to better results because the AI gives each step more attention, and you can review, refine, or redirect along the way.
Learning Objectives:
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Apply Few Shot prompting to achieve consistent, on-target outputs
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Construct Chain of Thought prompts that break complex tasks into manageable steps
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Combine these techniques to improve quality and maintain control over multi-step editorial tasks
When AI misses the mark, the issue often isn't what you asked for, it's that the AI struggled to process the instructions. In this lesson, you'll learn two techniques that give the AI a clearer roadmap to success: Markdown and XML.
Markdown is a simple way to add formatting—bold, italics, headings, lists—using basic symbols. It makes your formatting portable, so structure survives the copy/paste from AI into Word, Google Docs, or wherever your text needs to go.
XML tags are a labeling system that helps AI understand the meaning and structure of information. They let you clearly separate the task, content, and expected output so the AI processes each part the way you intend.
Used together, they give you precise control over both the AI's behavior and the finished output. You don't need to learn to code to use these techniques—we'll cover how to get AI to add this structure for you. We'll also combine these methods to build custom style guides that help AI reliably edit text according to your organization's rules.
Learning Objectives:
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Apply Markdown formatting to create portable, consistently structured outputs
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Use XML tags to organize complex prompts and knowledge documents
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Combine Markdown and XML tags to make a custom style guide AI can read
Prompts tell AI what to do in the moment. Knowledge documents tell the AI what to know every time. In this lesson, you'll learn how to build reference documents that work alongside your prompts so the AI can apply your standards consistently without you repeating yourself.
We'll focus on three types of knowledge documents:
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Custom Style Guide: your house rules for grammar, punctuation, formatting, and usage
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Content Examples: samples that show AI the tone, voice, or format to follow
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Restricted Terms: terms to skip for brand, legal, or inclusivity reasons, along with preferred alternatives
This is how you scale your editorial standards without sacrificing control. Build the documents once, use them everywhere, and have the AI apply your rules the same way every time.
Learning Objectives
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Identify which knowledge document types best support different editorial tasks
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Build knowledge documents using Markdown, XML, and spreadsheet formats
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Combine knowledge documents with prompts for consistent, standards-aligned AI output
Advanced AI Prompting for Editors (Section 2)
Tuesdays from July 7 to August 4
Session Length: 90 minutes
Start Time: 12:00 PM ET | 9:00 AM PT | 16:00 UTC
Price: $495 USD (plus applicable tax)
Register for Advanced AI Prompting for Editors
Reduced Fee Note
Employees of certain nonprofits are eligible for a reduced enrollment fee. To find out if you qualify, email Support@AIForEditors.Com.
Group enrollments of 5 students or more are eligible for a group discount. Email Erin@AIForEditors.Com for more information.
There are a limited number of spaces in each class reserved for unemployed and underemployed people who would benefit from a free or reduced enrollment fee. To find out if there is space in an upcoming section, email Support@AIForEditors.Com.
What's Included
✔️ Six 90-minute live lessons with Q&A and hands-on exercises
✔️ Recordings of every class, so you never miss a session
✔️ Lesson reference guides you can use at your desk long after the course ends
✔️ Access to an exclusive online community of editors during and after the course
⭐️ Certificate of completion
Frequently Asked Questions
What happens after I join?
You will be emailed an enrollment confirmation, receipt, and more information about the course.
What if I can't attend live?
There will be recordings of every live class made available, and you can join our discussions online.
Do you have a refund policy?
Yes. You can request a full refund up to 14 days after the course begins if you have taken the Introductory AI for Editors course. If you have not taken the intro course, you are not eligible for a full refund, but you may apply your enrollment fee to the Introductory AI for Editors course.
Can I register a group?
Absolutely! Groups of five or more are eligible for a group discount. Email Support@AIForEditors.Com to learn more.
Do I need to know how to code?
No. While we cover technical concepts like XML and Markdown, you don't need to be a coder. We teach you how to prompt the AI to handle the coding structure for you.
What if I only want to take one advanced course?
That is perfectly fine. Advanced Prompting focuses on the craft of editing , while Building AI Assistants focuses on infrastructure and automation. You can choose the one that fits your immediate needs.
Which AI tools do we use?
We focus on the major LLMs (ChatGPT, Gemini, etc.). Most principles you learn, such as like the 4P Framework, are universal and apply to almost any AI model.
Is there anything I need to buy for the course?
It's strongly recommended you have access to a paid or enterprise version of ChatGPT, Claude, or Google Gemini.
How do I get my Certificate of Completion?
In Advanced AI Prompting for Editors, there will be an optional assignment you can complete for each lesson. At the end of the course, you can request a Certificate of Completion as long as you have completed the coursework.
How does the online group work?
Students will have exclusive access to the AI for Editors online community during the length of the course and afterward. It's a place for students to ask questions, troubleshoot, share their AI experiments, and stay connected between lessons.
How much time will it take?
Each lesson is 90 minutes. Assignments take approximately 60 minutes. It's recommended you spend time practicing your skills between lessons. How much time you spend is up to you.
Other questions?
Email me at Erin@AIForEditors.Com.
This course is the only one of its kind and is essential for any editor to remain relevant as technology continues to become more and more sophisticated.
Nadia Geagea Pupa