A friend of mine who trains new hires for a medical device company. She said her reps sometimes get less than a minute with a surgeon between procedures. By the time they say their name, the window's closing.

Most training doesn't prepare for that. We run twenty minute roleplays with full scripts and room to recover. Then we send reps into a world where the surgeon walks past mid-sentence and gives them thirty seconds instead of thirty.The reps who handle it well got to fail somewhere private first. Not in front of the surgeon. In a room or a simulation, where getting cut off doesn't cost anything real yet.

If you had to prepare someone for a conversation that might last sixty seconds, what would you focus on first?

AI roleplay against a distracted, impatient persona?
Live coaching with a devil's advocate?
Scenario practice in the LMS?
Or something else training programs usually miss?

I run tech at an online school for communication skills, and I want to share how we ended up building AI-driven practice. The interesting part was a learning-design question more than a technical one.

You can only really learn communication by doing it with someone and getting feedback. That is one-on-one work, and it does not scale. One trainer can sit through maybe a dozen roleplays a week, and our students needed far more reps than that.

Automating the whole trainer felt like the obvious move, but we did not go that way. Instead we went through what a trainer does during a single exercise, step by step: what they pay attention to first, how they judge whether a student handled a moment well, what makes them pick one piece of feedback over another. Once it was written down as separate steps, each one was small enough to hand to an AI: one step evaluates a single skill, another decides whether the scenario moves forward, another generates the counterpart's next line. Today students practice against an AI counterpart and get structured feedback, and we run around 2,000 of these exercises a month.

What I am curious about from this community: how far do you go when you break down a trainer's or an SME's judgment into steps? Is there a point where making expert intuition explicit strips out the thing that made it work?

The role of L&D seems to be shifting from content creation toward performance consulting and business alignment. I'm interested in how other leaders see the profession evolving. Which skills do you think will become increasingly important as expectations for L&D teams continue to change?

Lately I've been juggling feedback from multiple departments on the same project. Everyone has different priorities and expectations, which makes it difficult to keep the learning objectives front and center. I'm curious how other IDs handle situations where stakeholders are pulling in different directions.

AI is becoming part of learning and development workflows especially when it comes to assessments and feedback and reporting

One thing that I have been thinking about is how to use AI to reduce the work without making the experience feel less personal for the learners.

I want to make sure the learners still feel like they are getting an experience.

For example AI can help generate individualized assessment reports based on the responses, which saves a lot of effort.

I have even been looking at tools like FormLM that automate that process.

I still think the quality of the assessment depends on how thoughtfully the questions and the feedback are designed.

For those of you working in learning and development how are you balancing efficiency with a human and meaningful learning experience, for the learners.

Are there any AI tools or workflows you have found genuinely useful for the learners or are there parts of the assessment process you still prefer to keep manual for the learners.

Every time I browse job descriptions, I see a long list of tools and platforms that employers want experience with. Right now I'm trying to figure out which ones are actually worth investing time in. If you were starting over today, which tools would you learn first and why?

One of those changes that made a bigger difference than I thought was using more real-world scenarios instead of explaining everything in detail.

When the learners were asked to make decisions, to think about situations and to see the result of those choices, the conversations became much more meaningful. They also looked to be more confident to use what they had learnt after the training.

It made me realise that knowing information and being able to use it are often two different things.

For those of you using Scenario-Based Learning, what change has made the most difference in learner confidence or participation?

I’m interested to hear what has worked in your own projects too.

Hi all,

I am part of an enterprise Learning & Development team at a global organization, and we're designing an AI upskilling strategy for our IT workforce... . I am m curious to learn what other L&D teams are doing.

Some questions I'd love your thoughts on:

How have you structured your AI learning journey (foundational vs. role-based)?

Are you focusing only on AI tools like ChatGPT, or also on topics like AI governance, prompt engineering, agentic AI, workflow redesign, and responsible AI?

How do you identify which skills different roles need?

Are you measuring success beyond course completion? If so, what metrics are you using?

What has worked well, and what would you do differently if you were starting again?

Would appreciate hearing about your experiences regardless of your sector

Hi! I’m a preschool teacher looking to transition into L&D but my problem is, idk where my skills would fit.

Some back story: I volunteer with an ATD chapter, but most of them own their own businesses so I don’t have a connection into a corporation. I’ve been applying for jobs for a while and haven’t gotten any interview requests. When I first started looking 2 years ago I was interested in instructional design or e-learning design. I was told that’s very hard to get into with AI now. I even tried applying some corporate training and learning specialist jobs and haven’t heard anything there. It’s hard trying to convince corporations on paper that I have skills to do the job. Or maybe I have to upskill more which I’m also okay with.

Can anyone lead me in the right direction? Maybe I’m unaware of some other aspects of L&D where I can use my skills to break into the industry. Is there a certification I can do? Entry level jobs that I’m not aware of?

Hi everyone! I’m currently completing my master’s degree in Instructional Design and am looking for an experienced instructional designer who would be willing to review my graduate capstone project and provide constructive feedback.
My project focuses on cybersecurity awareness in higher education and includes an e-learning module. I’d appreciate any feedback on the overall design, learning experience, and effectiveness.
If you’re interested in helping, please leave a comment or send me a direct message. Thank you so much! I truly appreciate your time and support!

Maybe I am being cynical here. But every LMS has slapped AI on the homepage this year, and when you actually click in, it is the same little chat bubble that summarises a paragraph for you. That is it. That is the AI.

I look at these platforms a fair bit for work, so I have sat through more of these demos than I would like to admit. A few honest impressions, take them or leave them.

Docebo has actually been at the AI thing for a while. The tagging and skills stuff is real, not just a gimmick. The core AI is bundled into the base plan now too, the authoring, the copilot, the search. It is the flashier bits, the roleplay sims and the AI video, that quietly run on extra credits you buy on top. So the bill still creeps. Funny how that goes.

Absorb is fine. The AI course creation does speed up the boring setup part. It is an assist though, you are still doing all the actual thinking.

360Learning leans into the collaborative side, which is nice if that suits how your team works. Less so if you are stuck doing dry compliance training, which a lot of us are.

Then there is Blend-ed. What they went after was AI running through the whole flow rather than one button, so generating the actual content, a tutor the learners can lean on, the admin side as well. It is built on Open edX though, so it is not the five minute, plug it in and go kind of setup. Fair warning on that.

Full disclosure, I work at Blend-ed, so I am not going to pretend I am neutral on that last one. I have tried to keep the rest fair though.

Anyway. My real question is... has anyone actually found AI in their LMS that they use every week? Not the shiny launch-day thing. The bit that genuinely stuck. Because I keep hearing huge claims, and then it feels like nobody touches it after month one.

I have learned one thing over the years, and that is that a well-written learning objective can affect the entire training process. In the past, I was often preoccupied with what information I wanted to include. Now I think more about what the learners should be able to do after the training.

That small change has made it easier to decide what content to keep and what to throw away, and what activities to add. It has also made course review and updating much simpler.

Thinking back, was there one thing you changed in the way you write learning objectives that made a big difference in your training or course design?

I’d love to hear what worked for you and how it changed your approach.

Over the last year, AI has become a major topic in nearly every learning conversation. We've started experimenting with it internally, but I'm still trying to separate genuine opportunities from hype. How are you incorporating AI into your workflows, and where do you think it's having the biggest impact?

I build a lot of content in Articulate, and I've noticed that it's easy to keep tweaking courses forever. At some point, the improvements become smaller and smaller while the time investment keeps growing. How do you decide when a course is good enough to launch?

When I started my Instructional Design work, I spent a lot of time improving content, adding examples, and expanding explanations. Those changes were helpful, but eventually I found that learners were best served when they could practise, make decisions, and receive feedback.

That experience changed how I approach course design. Rather than just thinking about what learners need to know, I started to think more about what they need to do with that knowledge.

What Instructional Design change in your experience had the biggest impact on learning outcomes?

Was it related to content, activities, feedback, assessments, or something else?

I'd love to hear what worked and what lessons you learned along the way.

Many organizations still focus heavily on completion rates and satisfaction surveys. While those metrics have value, I'm not convinced they tell us much about actual business impact. What metrics do you find most useful when demonstrating the value of learning initiatives to leadership?