u/Mexty4I

We recently explored this idea with a Philips Baby Care experience, and it’s a great example of how product information can become much easier and more engaging to use.

Instead of searching through long instructions, parents can quickly find the information they need, explore different topics, and get guidance in a simple, interactive way.

We created this experience with Mexty to show how traditional product documentation can become something people actually want to use.

👶📱 Would you prefer an interactive companion like this or a traditional product manual?

AI has made creating learning content incredibly fast.

We can generate a course outline, quiz, scenario, or activity in minutes.

But I think this creates a new question:

Is producing more content actually the problem we need to solve?

A strong learning experience also needs clear objectives, structured learning paths, meaningful practice, assessment, learner support, data, and continuous improvement.

Instead of treating AI as a course generator, we're trying to connect the whole learning system:

Knowledge → Learning Design → Interactive Experiences → Delivery → Assessment → Data → Improvement

Curious what other L&D people think.

Has AI made you create more content, or has it actually improved the learning system around that content?"

AI has made it incredibly easy to generate quizzes, course outlines, and learning content. But creating content is only one part of the job. There's also:

-reviewing and editing

-managing updates

-assigning learning

-tracking progress

-making sure information is accurate

If you could add one feature to today's AI tools for instructional design or corporate learning, what would it be? I'm curious what people feel is still missing

Something I've noticed is how often new IDs are told:

“You need a portfolio.”

Okay... but what should actually be in it?

A few nice-looking slides probably aren't enough.

I'd rather see how someone thinks: a branching scenario, an onboarding experience, an assessment, meaningful feedback, or something where the learner actually has to make a decision.

You don't necessarily need real client work either. A fictional project can still show how you approach learning design.

For the IDs here who have been through the hiring process: what portfolio piece helped you most when you were starting out?

Creating a course is one thing.

Then someone asks:

“Can we have it in French too?”

And Spanish.

And Polish.

Normally, that can mean a lot of copying, translating, checking, and rebuilding.

We created the learning experience once, then localized the same activity into multiple languages.

Same structure.

Same interaction.

Same learning experience.

Just adapted for different learners.

Of course, AI translation still needs human review, especially when context and terminology matter.

But you don't have to start from zero every time.

Create once. Localize. Review. Done.

For those working with global training: how much time does localization take in your current workflow?

Not your whole job.

Just the repetitive stuff.

For me, this is where AI gets interesting.

Creating a first draft from a document? Sure.

Rewriting something for the tenth time? Absolutely.

Creating variations of an activity? Yes please.

Formatting and restructuring content? Take it.

But deciding what someone actually needs to learn?

Whether a scenario feels realistic?

Whether an assessment is actually measuring the right thing?

That's where I still want a human involved.

What's one part of your L&D/ID workflow you'd happily never do manually again?

AI helps you move faster. You review, edit, improve, and decide what stays.

Because the goal isn't to replace instructional designers.

It's to give them more time for the part that actually requires instructional design.

AI shouldn't make the final learning decisions.

The human still decides

This is something I'm genuinely curious about.

If you wanted to build a branching scenario, would you rather set up all the logic yourself...

or simply describe what you want?

We sometimes call it vibe coding for learning.

AI handles more of the technical work. You still decide whether the learning actually makes sense.

Would you use something like this, or do you prefer building interactions manually?

A lot of learning teams already have an LMS that works perfectly fine for delivery.

The messy part often happens before and around it.

Knowledge in PDFs.

AI in another tool.

Courses in an authoring platform.

Assessments somewhere else.

SCORM packages being passed around.

Analytics in another dashboard

I'm curious: how many different tools are involved between “we need training on this” and a learner actually completing it in your organization?

A learner completed the course.

But what did they actually learn?

Where did they struggle?

Which concept needs a better explanation?

And can they actually apply what they learned?

If learners repeatedly fail the same question, maybe the problem isn't the learner.

Maybe the explanation isn't clear enough.

If everyone leaves at the same point, maybe that section is too long or irrelevant.

If an AI Agent keeps getting the same question, maybe something is missing from the training.

Learning data shouldn't just tell us what learners did. It should help us improve what we built.

What do you actually look at beyond completion rates?

Most LMS usage is driven by mandatory training.

Have you seen examples where learners actually wanted to return and continue learning?

What made the difference?

Organizations spend months selecting an LMS.
Then six months later nobody is using it.
What do you think causes that gap between implementation and adoption?

I don't think most people dislike learning, they dislike the way it's often delivered. Too many workplace courses still feel like:

- endless slides

- long videos

- PDFs nobody reads

- quizzes you forget five minutes later

If you could change one thing about corporate learning, what would it be?

Traditional SCORM courses often rely heavily on quizzes.

But are quizzes really the best way to evaluate learning?

What alternatives are you using?

There's a lot of talk about AI agents lately. Things like:

automatically creating quizzes

updating learning materials

generating reports

answering learner questions

managing repetitive tasks

It sounds useful, but I'm wondering how much of it people would actually trust. If AI agents became part of your L&D workflow tomorrow, what would you let them handle first?

Ten years ago most discussions were about LMS features.

Today it feels like the conversation is shifting toward learner experience.

Do you think content quality now matters more than the platform itself?

"

AI is showing up in almost every authoring platform now.

If you could add one genuinely useful AI feature, what would it be? Not a gimmick. Something that would actually save you time every week. Mine would probably be automatically updating learning content when source documents change.

For me it often feels like the instructional design part is relatively quick.

The real time goes into:

interactions

revisions

updates

publishing

LMS deployment

What's your experience?

AI has made it incredibly easy to generate quizzes, course outlines, and learning content. But creating content is only one part of the job. There's also:

-reviewing and editing

-managing updates

-assigning learning

-tracking progress

-making sure information is accurate

If you could add one feature to today's AI tools for instructional design or corporate learning, what would it be? I'm curious what people feel is still missing.

Imagine you weren't limited by your current LMS or training process. would you still organize learning as a list of separate courses? Or would you build something different maybe longer learning journeys, more practice, coaching, projects, or simulations?

I'm curious how people would design workplace learning if they could start from scratch.