In September 2023, I published an article titled “99 ChatGPT Prompts for Instructional Designers.“ At the time, generative AI was still new to most Learning & Development professionals. Many of us were exploring what ChatGPT could actually do—summarize research, write scripts, translate eLearning, create quizzes, generate learning objectives, and accelerate content development.

The response was overwhelming.

Thousands of L&D professionals experimented with those prompts, adapted them to their own work, and discovered that AI could eliminate hours of repetitive effort.

But AI has evolved.

More importantly, our understanding of how to use AI has evolved.

Three years ago, the biggest question was:

“What can ChatGPT create for me?”

Today, the better question is:

“How can AI help me solve better business problems?”

That shift changes everything.

The Prompt Era Is Ending

Don’t misunderstand me.

Prompts still matter.

A well-written prompt will always produce better results than a vague one.

But prompts alone are no longer the competitive advantage.

Anyone can ask AI to:

Write a script.
Create a quiz.
Generate learning objectives.
Translate a module.
Produce a storyboard.

Those have become basic capabilities.

The real differentiator today isn’t writing prompts.

It’s designing AI workflows.

L&D Is Moving Beyond Course Development

For decades, Learning & Development has been measured largely by its ability to create learning.

Courses.

Workshops.

eLearning.

Videos.

Job aids.

Knowledge libraries.

AI can now produce much of that content in seconds.

If our value was simply creating content, AI has fundamentally changed the economics of our profession.

Fortunately, content was never supposed to be our real value.

Our real value has always been improving performance.

That requires far more than asking AI to write another lesson.

The New Role of AI

Modern AI should help us think before it helps us build.

Instead of asking:

“Write learning objectives.”

We should begin with:

“Interview me until you understand the business problem.”

Instead of asking:

“Create a course.”

We should ask:

“Determine whether training is even the right solution.”

Instead of creating more content faster…

…we should create better capability systems.

From Prompts to Workflows

A workflow is simply a sequence of prompts designed to solve an entire business problem—not just produce a single output.

Here’s an example.

Old Prompt

Write five learning objectives for customer service training.

Modern AI Workflow

Step 1

Interview me to understand the business problem.

Step 2

Identify the desired business outcome.

Step 3

Determine whether the issue is caused by knowledge, skill, motivation, process, technology, leadership, or environment.

Step 4

If training is appropriate, define the capability gap.

Step 5

Recommend the best intervention.

Step 6

Create measurable learning objectives.

Step 7

Design practice activities.

Step 8

Recommend success measures.

Notice the difference.

The objective is no longer creating content.

The objective is improving performance.

The New AI Workflows Every L&D Professional Should Master

Rather than memorizing hundreds of isolated prompts, I recommend building workflows across the entire L&D lifecycle.

1. Business Diagnosis

Before creating anything:

Clarify stakeholder requests.
Identify business outcomes.
Separate symptoms from causes.
Determine whether training is appropriate.
Identify performance barriers.
Recommend alternatives to training.

2. Performance Analysis

Use AI to:

Build performance maps.
Identify critical tasks.
Analyze decision points.
Map workflow friction.
Identify environmental barriers.
Prioritize capability gaps.

3. Learning Design

AI can help:

Build curricula.
Design scenarios.
Create simulations.
Generate role plays.
Produce coaching guides.
Design spaced practice.
Create decision-based learning.

4. Assessment Design

Move beyond multiple choice.

Use AI to create:

Realistic scenarios.
Judgment exercises.
Performance tasks.
Case studies.
Reflective activities.
Adaptive assessments.
Coaching conversations.

5. Performance Support

Sometimes the best training isn’t training.

AI can help create:

Job aids.
Decision trees.
Checklists.
AI assistants.
Knowledge bases.
Embedded workflow support.
Just-in-time guidance.

6. AI Productivity

Let AI eliminate repetitive work.

Examples include:

Research synthesis.
SME interview preparation.
Course conversion.
Content summarization.
Accessibility improvements.
Translation.
Video scripts.
Voice-over scripts.
Image generation.
Presentation creation.

7. Learning Analytics

Use AI to help answer questions like:

What should we measure?
Which KPIs matter?
Which metrics are vanity metrics?
What does success look like?
How do we build executive dashboards?
What evidence demonstrates capability improvement?

8. Executive Communication

AI can help prepare:

Executive briefings.
Board presentations.
Investment proposals.
Change strategies.
Stakeholder updates.
Business cases.
Risk assessments.

9. AI Governance

Responsible AI use has become essential.

Build workflows that:

Protect confidential information.
Identify hallucinations.
Flag compliance risks.
Verify sources.
Improve prompt quality.
Ensure human review.
Document decision making.

10. Continuous Improvement

After implementation, AI can help:

Analyze learner feedback.
Identify trends.
Recommend improvements.
Compare versions.
Detect performance gaps.
Generate enhancement plans.

AI Doesn’t Replace Instructional Designers

It raises the standard.

The best instructional designers have never been the fastest people at writing content.

They’ve been the people who asked the best questions.

AI now handles much of the writing.

Our competitive advantage becomes:

Better diagnosis.
Better thinking.
Better systems.
Better judgment.
Better business alignment.

That is far more valuable than producing another PowerPoint.

The Future Isn’t Prompt Engineering

The future is Capability Engineering.

Organizations don’t need more content.

They need:

Better decisions.
Better capability.
Better performance.
Better systems.
Better measurement.
Better governance.

AI should help us build those.

My Challenge to the L&D Community

When I wrote 99 ChatGPT Prompts for Instructional Designers in 2023, the goal was simple:

Help instructional designers save time.

Today, I believe our goal should be much bigger.

Use AI not simply to create learning faster…

…but to help organizations perform better.

That means moving beyond prompts.

Beyond courses.

Beyond content.

Toward a future where Learning & Development becomes the architect of organizational capability.

And I think that’s a future worth building.

What AI workflows have become indispensable in your work?

I’d love to hear how your use of AI has evolved since those early days of prompt experimentation. The most valuable ideas often come from practitioners solving real problems, and I suspect the next generation of L&D innovation will be built by sharing those workflows—not just individual prompts.

From Prompt Lists to AI Workflows: The Next Evolution for Learning & Development