The Ultimate Guide to Generative AI for L&D (with Examples & Prompts)

A Quick Primer on Effectively Using Generative AI

Before you dive into prompts and use cases, here are a few key principles to help you work with AI instead of against it:

1. Treat it like a teammate.

AI does best when you guide it the same way you’d onboard a new employee. Give it context, goals, and examples of what “good” looks like. Then, review its work and offer feedback—it learns from your adjustments.

2. Be clear about your audience and outcomes.

If you wouldn’t hand a lesson to a learner without defining who it’s for or what it’s supposed to achieve, don’t hand that same vagueness to AI. Include details about your learners, tone, learning objectives, and delivery format in every prompt.

3. Build in layers.

Ask AI to tackle one task at a time—objectives first, then lesson plans, then content. It’s easier to refine small, focused outputs than to fix one giant, messy draft. Once you’re happy with its style and accuracy, you can safely scale up to full lessons.

4. Protect your data.

Before you upload anything into an AI tool, take a moment to think about what’s inside your files. Many AI platforms store or use your inputs to train future models, which means anything you share could end up outside your control. That’s why it’s important to protect your data—and your learners’—from unnecessary exposure. Avoid uploading confidential course materials, learner information, or customer examples into public tools. Instead, use enterprise-approved or closed AI environments that keep your content private. When in doubt, anonymize your data by replacing real names, emails, or company references with placeholders before sharing.

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7 Use Cases and Prompts for Generative AI in Learning & Development

While this is by no means meant to be an exhaustive list, here are some ways you could leverage generative AI in meaningful ways for L&D:

1. Generate learning objectives.

Learning objectives are the backbone of good instructional design, but they’re also time-intensive to create. AI can save you a good deal of time here—when given the proper clarity and context. Give the AI your content, tell it who’s learning and their current skill level, and ask what people should actually be able to do after learning. 

That last part matters most: skills and actions, not just facts, make a learning objective stick.

Generate Learning Objectives Prompt: 

You are an instructional designer. Generate high-quality, measurable learning objectives based on the information below. Follow these requirements carefully.

1. Context & Audience

• Topic: [insert topic or link to source material]
• Audience: [describe the learners]
• Current skill/knowledge level: [beginner/intermediate/advanced]
• Delivery format: [e.g., eLearning module, instructor-led training, microlearning, workshop]

2. Instructional Design Requirements

When generating objectives, follow these rules:

1. Use measurable action verbs aligned with Bloom’s Taxonomy (avoid vague verbs like “understand,” “know,” or “learn”).
2. Objectives must be learner-centered, focusing on what the learner will do, not what the instructor will cover.
3. Each objective should describe:
   
   • The skill or knowledge being demonstrated,
   • The conditions under which learners will perform, and
   • The criteria for successful performance (where appropriate).
4. Include 3–6 learning objectives, grouped by cognitive level if relevant (e.g., foundational → applied → analytical).
5. Ensure objectives directly reflect the desired performance outcomes of the learning experience.

3. Output Format

Provide:

A. Summary of overall learning goal
B. A list of learning objectives, formatted as:

• Objective [#]: Measurable action verb + specific performance + condition + criteria (if applicable)
• Include Bloom’s level in parentheses after each objective.

4. Quality Check

Before finalizing the objectives, evaluate them using this checklist:

• Are they measurable?
• Do they describe observable learner behavior?
• Are they actionable and realistic for the stated format and duration?
• Do they ladder together logically from foundational to advanced?
• Are they free of jargon and overly complex phrasing?

After evaluation, provide a "Quality Review Summary" explaining any adjustments you made.

2. Outline lesson plans.

Once you’ve nailed the objectives, it’s time to map out how learners actually get there. Think of a lesson plan as your GPS—it helps you chart the best route from “what they need to learn” to “what they’ll be able to do.” Generative AI can draft that route for you in minutes. Feed it your objectives and source material, tell it the delivery method (e.g., training, on-demand modules) and length of the learning experience, and ask it to outline a logical flow of topics, activities, and assessments. You’ll still want to check the pacing and add your human touch, but AI can save you hours by turning a blank page into a ready-to-edit roadmap.

Outline Lesson Plans Prompt: 

You are an expert instructional designer. Create a structured lesson plan outline using proven learning science principles. Follow the instructions below very carefully.

1. Input & Context

Use the details below to design the lesson plan:

• Topic: [insert topic or source material]
• Audience: [describe learners and context]
• Current knowledge/skill level: [beginner/intermediate/advanced]
• Learning objectives:
  
  • [insert objective 1]
  • [insert objective 2]
  • [insert objective 3]
• Delivery format: [e.g., eLearning module, workshop, virtual instructor-led, microlearning]
• Estimated duration: [insert length – e.g., 20 min microlearning, 60 min session, multi-module course]

2. Instructional Design Requirements

Design the lesson plan using these evidence-based principles:

A. Backward Design

• All content, activities, and assessments must directly support the listed learning objectives.

B. Cognitive Load Management

• Chunk content into sections that move logically from foundational to applied.
• Avoid unnecessary complexity, jargon, or cognitive overload.

C. Scaffolding

• Introduce simpler concepts first, then gradually deepen complexity.
• Provide opportunities for practice, reflection, and reinforcement.

D. Engagement & Active Learning

Include multiple activity types such as:

• Guided practice
• Scenario-based activities
• Discussions or reflection prompts
• Micro-assessments or knowledge checks

3. Required Lesson Plan Structure

Your output must include the following sections:

1. Lesson Title
2. Lesson Overview: a short summary of what learners will accomplish.
3. Prerequisite Knowledge
4. Learning Objectives (restate them clearly, grouped by Bloom’s level)
5. Lesson Sequence/Outline (the main section)
   
   • Break into major sections with sub-steps:
     
     • Introduction / activation of prior knowledge
     • Core concepts and instruction
     • Examples and demonstrations
     • Guided practice
     • Independent practice
     • Knowledge checks / formative assessment
     • Reflection or discussion
     • Summary and reinforcement
6. Instructional Strategies Used (explain why the sequence works)
7. Assessment Alignment: show how each lesson segment ties to objectives.
8. Estimated Timing by Section
9. Materials or Resources Needed

4. Output Format

Provide your output in a clean, structured outline using Markdown:

• Use clear headings (H2 / H3 / H4).
• Use bullet points for steps and activities.
• Label each activity with its purpose (e.g., reinforcement, application, comprehension check).

5. Quality Review

Before finalizing the plan, run a quick self-check:

• Is the sequence instructionally logical?
• Does each section connect directly to a learning objective?
• Are the activities varied and pedagogically sound?
• Is the lesson appropriate for the stated duration and format?
• Would this flow reduce cognitive overload for the learner?

Provide a short “Quality Review Summary” at the end, describing what you ensured or adjusted.

3. Create assessments.

If learning objectives are the “what” and lesson plans are the “how,” assessments are the “did it work?” part of the equation. Generative AI can take your objectives or lesson content and spin up quiz questions, knowledge checks, or reflection prompts in seconds. Just feed it your source material, specify the format you want (multiple choice, short answer, scenario-based, etc.), and ask it to align each question to a specific objective. 

‍Beware: You’ll still need to review for accuracy and nuance. AI is notorious for writing either too easy or way too hard questions, but it’s a huge time-saver for getting that first draft on the page.

Create Assessment Prompt: 

You are an expert instructional designer and assessment specialist. Create high-quality assessment items that directly align to the learning objectives below. Follow all instructions carefully.

1. Input & Context

Use the details provided to design the assessment:

• Topic: [insert topic or source material]
• Audience: [describe learners and context]
• Skill/knowledge level: [beginner/intermediate/advanced]
• Learning objectives:
  
  • [insert objective 1]
  • [insert objective 2]
  • [insert objective 3]
• Assessment format requested:
  
  • (Choose one or more: multiple choice, scenario-based multiple-choice questions, short answer, reflection, case study, performance task, simulation prompt, etc.)
• Number of questions needed: [insert number]

2. Assessment Design Requirements

Follow these instructional design and assessment principles:

A. Alignment (Backward Design)

• Every question must map directly to one specific learning objective.
• State which objective each item aligns to.

B. Bloom’s Taxonomy

• Use action verbs aligned to the cognitive level of each learning objective.
• Vary levels if appropriate (e.g., recall → comprehension → application → analysis).

C. Quality of Questions

For multiple-choice questions, ensure:

• Clear, concise stems
• One unambiguously correct answer
• Plausible distractors that avoid giveaways or trivial differences
• No use of “All of the above” or “None of the above” unless pedagogically justified
• Avoid trick questions, double negatives, or unnecessary complexity

For scenario-based items:

• Use realistic, context-rich situations
• Require learners to apply skills, not repeat facts

For performance tasks:

• Provide clear criteria for success
• Make tasks observable, measurable, and tied to desired performance outcomes

D. Fairness & Accessibility

• Use inclusive language
• Avoid cultural references, jargon, or idioms unless necessary
• Keep reading level appropriate to the learners

3. Required Output Structure

Provide the assessment in the following structure:

A. Assessment Overview

• Purpose
• Cognitive levels targeted
• How the assessment supports the learning objectives

B. Assessment Items

For each question, provide:

1. Question stem
2. Answer options (if multiple choice)
3. Correct answer
4. Explanation/rationale for the correct answer
5. Aligned learning objective
6. Bloom’s level

For scenario-based or performance tasks, include:

• Scenario description
• Task prompt
• Evaluation rubric or success criteria

4. Quality Review (AI Self-Check)

Before finalizing, evaluate your assessment using this checklist:

• Does every item align directly to an objective?
• Are all correct answers clearly correct?
• Are distractors plausible and instructionally meaningful?
• Are cognitive levels appropriate and varied as needed?
• Are questions free of bias and unnecessary complexity?
• Is the reading level appropriate for the audience?

Provide a short “Quality Review Summary” explaining any adjustments you made.

4. Craft learning content tied to learning outcomes.

Once your objectives and assessments are in place, it’s time to build the content that actually helps learners get there. Generative AI can help you move from outline to draft fast by turning bullet points into explanations, examples, or even short scenarios. The trick is to anchor every prompt to a specific learning outcome. For example: “Write a short paragraph explaining this concept to a beginner learner,” or “Create a scenario that helps the learner practice this skill.” 

Create Learning Content Prompt: 

You are an expert instructional designer. Create clear, learner-friendly learning content aligned to the learning objectives below. Follow all instructions carefully.

1. Inputs to Use

Use the following information to generate the learning content:

• Topic: [insert topic or source material]
• Audience: [describe learners]
• Current skill level: [beginner/intermediate/advanced]
• Learning objectives:
  
  • [insert objective 1]
  • [insert objective 2]
  • [insert objective 3]
• Delivery format: [e.g., eLearning, workshop, microlearning, video script, facilitator guide]
• Desired tone/style: [e.g., conversational, formal, authoritative, simple]
• Length requirement: [short explanation, 2–3 paragraphs, full lesson section, etc.]

2. Instructional Design Requirements

Follow these principles:

A. Backward Design

• All content must directly support a specific learning objective.
• Identify which parts of the content align to which objectives.

B. Cognitive Load Management

• Use plain language.
• Chunk information into digestible sections.
• Use examples, analogies, or visuals (described textually) to simplify complex topics.

C. Scaffolding

• Start with foundational concepts.
• Progress to applied or analytical concepts.
• Provide guided steps before asking learners to do something independently.

D. Adult Learning Principles

Include:

• Relevance (“why this matters”)
• Real-world use cases
• Problem-centered explanations
• Opportunities for reflection or self-connection

E. Engagement

Include elements such as:

• Short scenarios
• Micro-examples
• Step-by-step walkthroughs
• Reflection questions
• Try-it-yourself moments

3. Required Output Structure

Produce the learning content using the structure below:

A. Section Title

A short, clear title.

B. Introduction

• Brief overview of the topic
• Why this topic matters
• How it connects to the learning objectives

C. Core Content

Organize into clearly labeled subsections, such as:

1. Key Concepts Explained
2. Examples & Demonstrations
3. Step-by-Step Breakdown
4. Common Mistakes or Misconceptions
5. Best Practices or Tips

D. Applied Learning

• A scenario, mini case study, or example where learners use the concept
• OR a short activity ("Try This")

E. Reflection or Self-Check Questions

2–4 questions that reinforce comprehension.

F. Objective Alignment

At the end, show how each part of the content supports the learning objectives.

4. Quality Review (AI Self-Check)

Before finalizing, evaluate the content using this checklist:

• Is the content accurate, concise, and aligned to the objectives?
• Does it follow a logical instructional sequence?
• Will the reading level be appropriate for the audience?
• Are examples clear and relevant?
• Does the content avoid jargon, bias, and overly technical phrasing?
• Is cognitive load kept manageable?

Provide a short “Quality Review Summary” describing final improvements made.

5. Ensure content relates to assessments (and vice versa).

Ever finish building a course and realize half your quiz questions don’t actually connect to what you taught? Same same. Generative AI can help spot those gaps by comparing your learning content and assessments side by side. Feed it both, and ask: “Are all assessment questions covered in the content?” or “Which sections of content don’t tie to a measurable objective or question?” It can flag misalignments, missing coverage, or even suggest where to add a quick example or knowledge check. 

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Some teams have found this especially useful for quality control, catching stray questions or filler content before the course goes live. The result? Tighter, more purposeful learning that measures what actually matters.

Connect Content and Assessments Prompt: 

You are an expert instructional designer and assessment specialist. Review the learning content and assessments below, and check for alignment to the learning objectives. Follow the instructions carefully.

1. Inputs

Provide:

• Learning objectives:
  
  • [insert objective 1]
  • [insert objective 2]
  • [insert objective 3]
• Learning content:
  [paste your content or sections/modules]
• Assessment items:
  [paste quiz questions, knowledge checks, scenarios, performance tasks, etc.]
• Audience & level:
  [describe learners and their skill level]

2. Your Task

Evaluate alignment using instructional design best practices:

A. Backward Design & Constructive Alignment

For each learning objective:

• Check whether the content sufficiently teaches the skills/knowledge.
• Check whether the assessments accurately measure those skills/knowledge.
• Identify any gaps, mismatches, or misalignment.

B. Bloom’s Taxonomy Analysis

• Compare the cognitive level of each objective vs. each assessment item.
• Flag places where assessment demands a higher or lower cognitive level than the objective requires.

C. Coverage Check

• Identify which content sections are not assessed and may not need to be included.
• Identify which assessment questions test concepts not covered in the content.

D. Validity & Quality

• Evaluate whether assessments measure what they claim to measure.
• Flag ambiguous items, unclear stems, or weak distractors.
• Identify overly complex or unfair questions.

3. Required Output Structure

Provide your analysis in the structure below:

A. Summary of Overall Alignment

Short overview of how well content and assessment match the goals.

B. Objective-by-Objective Alignment Table

For each learning objective, provide:

• Objective
• Relevant Content Sections (cite exact paragraphs or bullets)
• Relevant Assessment Items (list corresponding question numbers)
• Alignment Quality (High / Medium / Low)
• Comments & Needed Adjustments

C. Misalignment & Gap Analysis

List:

• Assessment questions not supported by content
• Content sections not tied to any objective or assessment
• Cognitive level mismatches
• Missing coverage or missing questions
• Redundant or unnecessary content

D. Recommendations

Provide specific, actionable suggestions such as:

• Rewrite or adjust specific assessment items
• Add or revise content to support an objective
• Remove extraneous content
• Adjust cognitive level of questions
• Add missing practice or explanations

E. Optional: Improved or Rewritten Elements

If helpful, rewrite:

• Misaligned content
• Assessment questions
• Learning objective revisions
• Missing questions needed for coverage

4. AI Self-Check (Quality Review)

Before finalizing, verify:

• Are all objectives addressed by both content and assessment?
• Are Bloom levels consistent?
• Are recommendations specific and actionable?
• Did I avoid inventing content not provided by the user?

Provide a brief “Quality Review Summary” at the end.

6. Fix tone across an entire course.

Many education teams employ multiple instructional designers who work collaboratively on new course content. While this can speed up development, it can also make it obvious that different people wrote different parts. Generative AI can help smooth out those seams. Feed it your full course or a few sample modules, then ask it to unify tone, reading level, or style—whether you want it to sound more conversational, more formal, or just consistent. 

You can even give it a reference paragraph that represents your preferred tone and say, “Match the rest of the course to this style.” It’s like having an editor who works at lightning speed, helping your content feel cohesive and on-brand from start to finish.

Fix Tone Across a Course Prompt: 

You are an expert instructional designer and editorial stylist. Your task is to review the following course content and ensure consistent tone, voice, readability, and style across all sections. Follow the instructions below closely.

1. Inputs

Provide the following:

• Course content:
  [Paste all modules, lessons, or sections]
• Target audience:
  [Describe learners and context]
• Desired tone/style:
  (Examples: conversational, formal, friendly expert, coach-like, simple & clear, professional but warm)
• Reference sample (optional):
  Paste a paragraph or module that represents the ideal tone, and instruct: “Match the rest of the course to this tone.”
• Reading level goal:
  (e.g., 8th grade, professional-level, plain language)

2. Your Task

Review and revise the content using instructional and editorial best practices:

A. Tone & Voice Consistency

• Maintain the same tone across all modules
• Keep voice (first/second/third person) consistent
• Ensure emotional tone matches learning intent (supportive, encouraging, authoritative, etc.)

B. Style Consistency

• Align on sentence structure, pacing, and clarity
• Standardize terminology and naming conventions
• Ensure consistent use of examples, scenarios, or analogies (e.g., all workplace-based vs. mixed contexts)

C. Readability & Cognitive Load

• Simplify overly long sentences
• Remove jargon unless necessary
• Reduce repetition
• Maintain clarity without diluting instructional rigor

D. Accessibility & Inclusion

• Use inclusive, bias-free language
• Avoid idioms and culturally specific references
• Maintain a reading level appropriate to the stated audience

3. Required Output Structure

Produce the following output:

A. Revised, Tone-Consistent Course Content

Rewrite the content so all modules match the desired tone and the reference sample (if provided).

B. Tone & Style Guide for This Course

A brief guide describing:

• Tone description
• Voice guidelines
• Sentence structure norms
• Preferred terminology
• Dos and Don’ts
• Example phrases that “fit” the tone

C. Change Summary

A concise explanation of:

• Tone issues you identified
• How you corrected inconsistencies
• Any terminology standardized across sections
• Where you simplified or clarified content

4. AI Self-Check (Quality Review)

Before finalizing, evaluate:

• Does every section sound like it was written by the same person?
• Is the tone aligned with the stated audience and learning goals?
• Is the reading level consistent?
• Is terminology standardized?
• Are any sections still noticeably different in voice or style?

Provide a “Quality Review Summary” explaining final adjustments you made.

7. Review content quality.

Even the best teams need a second pair of eyes. You can use generative  AI to review draft content and provide feedback on clarity, accuracy, and engagement. Paste in a section of your course and ask: “What’s working well here, and what could be clearer or more engaging?” or “Does this explanation match the stated learning objectives?” You can even ask it to check for things like reading level, accessibility, or jargon. While AI feedback won’t replace a full peer review, it’s a quick way to catch issues early and make sure your content feels polished, consistent, and learner-friendly before you hit publish.

Review Content Quality Prompt: 

You are an expert instructional designer and learning science reviewer. Your task is to analyze the draft content below and provide structured, actionable feedback to improve clarity, accuracy, and engagement. Follow the instructions carefully.

1. Inputs

Provide:

• Draft learning content:
  [Paste your draft section or module here]
• Learning objectives:
  [Insert relevant objectives to assess alignment]
• Audience:
  [Describe learners and their level]
• Desired tone/style:
  (Examples: conversational, formal, coach-like, simple, friendly expert)

2. Your Review Criteria

Evaluate the content using the following instructional design principles:

A. Clarity

• Identify unclear sentences, confusing explanations, or overly complex language
• Flag jargon, acronyms, or terms that need simplification or definition
• Ensure content follows a logical sequence and supports cognitive load management
• Check the reading level for appropriateness

B. Accuracy

• Identify factual issues, logical inconsistencies, or mismatches with source material
• Make sure examples and explanations correctly represent the concepts
• Verify that each section aligns with the stated learning objectives
• Ensure terminology is used consistently

C. Engagement

• Identify sections that may feel dry, passive, or overly dense
• Suggest opportunities to add:
  
  • micro-examples
  • scenarios
  • reflection questions
  • visuals (described textually)
  • interactive elements
• Flag repetitive content or places where pacing drops

D. Inclusivity & Accessibility

• Check for inclusive, bias-free language
• Identify opportunities to improve accessibility and readability
• Flag idioms, cultural references, or metaphors that may exclude learners

3. Required Output Structure

Provide your analysis in this structure:

A. High-Level Summary

A brief overview of strengths and major areas for improvement.

B. Detailed Feedback by Category

Organize feedback into:

• Clarity
• Accuracy
• Engagement
• Inclusivity & Accessibility
• Alignment to Learning Objectives

For each category, list:

• What is working well
• What needs improvement
• Specific examples from the text
• Concrete, actionable revision suggestions

C. Suggested Revisions or Rewrites

Provide improved versions of:

• unclear sentences
• inaccurate explanations
• weak examples or scenarios
• low-engagement sections

D. Optional: Enhanced Version of the Full Section

If instructed, rewrite the full content using the feedback provided.

4. AI Self-Check (Quality Review)

Before finalizing your feedback, verify:

• Did you avoid adding new factual content not provided by the user?
• Are suggestions specific, not vague?
• Did you check alignment to objectives?
• Is the feedback actionable and tied to learning science principles?
• Does the tone of feedback remain constructive and supportive?

Provide a short “Quality Review Summary” explaining your final checks.

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Common Generative AI Mistakes &
How to Avoid Them

Generative AI is powerful, but it’s not perfect. Here are some pitfalls to watch for (and simple ways to avoid them):

1. Hallucinations.

Have you ever asked ChatGPT something and you could tell the output was not the right answer? That’s called an AI hallucination. 

It happens because generative AI models are trained to recognize and continue patterns. As a result, they’ll often “fill in the blanks” even when they don’t have the right information. The result? Confidently wrong answers presented as fact.

This is where humans play a vital role. Many teams using AI for content creation employ a human-in-the-loop (HILT) model, where someone reviews each output for quality, accuracy, and consistency before it’s published. 

2. Bad distractor questions.

Doug Pietrzak, Founder of FreshCognate, noticed that while generative AI is great at coming up with new questions and identifying correct answers, it struggles to create good distractor questions.

Distractors are those incorrect (but plausible) options in multiple-choice questions that test deeper understanding. Because AI doesn’t truly grasp truth versus near-truth, its distractors often miss the mark or give away the answer.

To fix this, use AI to create the initial draft of assessment questions, then manually review or edit distractors for realism and challenge.

3. Treating AI output as “good enough.”

AI can help you move a lot faster, but don’t make the mistake of thinking that “fast” equals “finished.” Even when the content looks clean, it may not be instructionally sound or accurate.

Treat the first draft as a starting point. Ask AI to iterate, refine, or expand sections. Then do a human review for clarity, flow, and accuracy, especially around skills, terminology, or brand language.

4. Ignoring bias and accessibility.

AI learns from the internet, which means it sometimes repeats stereotypes or uses examples that exclude certain groups. It can also create overly complex language or visuals that aren’t accessible to all learners.

In your prompt, ask AI explicitly to check for inclusive language, plain readability, and accessibility (e.g., “Make sure this content is written at an 8th-grade reading level and includes diverse, inclusive examples.”). Then review with a DEI and accessibility lens before publishing.

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How We Built Creator Agent
to Do This Work for You

You can apply everything in this guide to any AI tool. Or you can use one built specifically for learning.

When we set out to build Creator Agent, our goal was to create a true learning design assistant. The kind that helps you generate complete, effective learning experiences. That meant starting from a different foundation. Instead of training Creator Agent to write “good-sounding” copy, we trained it to think like an instructional designer.

Early in development, we brought in experts in learning science and instructional design to help us define what “good” really means. Together, we built detailed rubrics — scorecards for the quality of the AI output — that covered everything from how clearly learning objectives were written to how well content flowed, to whether assessments truly measured what they were supposed to.

Those experts graded Creator Agent’s early outputs using those rubrics. When the AI missed the mark, we went deeper, refining the underlying system prompts and logic. Over many iterations, that process helped us train Creator Agent to understand the relationships between learning objectives, content, and assessment.

Creator Agent now follows a structured design sequence that mirrors proven instructional design frameworks:

1. Identify learning goals.
2. Understand the target audience.
3. Generate measurable objectives.
4. Draft a structured content outline.
5. Produce lesson-level content.
6. Create assessments tied back to the original objectives.

Each step is aligned with Bloom’s Taxonomy and grounded in cognitive science, ensuring the output isn’t just faster, it’s pedagogically sound.

We tested Creator Agent with customers in a beta program, collected feedback, and refined it further. If a course draft was too generic, we tightened the guidance. If assessments weren’t well aligned, we revisited the logic that connects objectives to questions. We also honed the tone of the output — making it sound more natural and learner-friendly — and trained the AI to be concise, cutting unnecessary repetition while keeping the instruction clear. 

The outcome is an AI instructional design assistant that doesn’t need you to be a prompt engineer. With Creator Agent, the learning science is already baked in. You bring your source material — a video, a document, a set of notes — and the system guides you through a complete instructional design process.

So yes, you can use other tools to build learning experiences with AI. But with Creator Agent, you don’t have to start from scratch. It’s like having an instructional designer sitting beside you, keeping your goals, your learners, and your outcomes in focus, every step of the way.

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See It For Yourself

You’ve read about how it works—now watch it in action. Give Creator Agent a spin and see how fast it can turn your ideas into structured, effective learning. Take the Product Tour →