LH127 Roll Away the Stone with Bob Mosher

You know, I've always been pushing the boulder uphill. I think the boulder is going to roll back on us with this.

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Learning.

When Bob Mosher says he's been pushing a boulder up a hill, it calls to mind the myth of Sisyphus. But over the years, Bob has occasionally seemed to me more like a biblical figure, a voice crying in the wilderness. For the best part of 30 years, he's been telling L&D that training and performance are not the same thing, that the real work, enabling people at the moment they need to act, has always been the part we weren't doing. All our courses and systems of record we were solving the wrong problem. People nodded, agreed, said this was undoubtedly the future, and then went back to building courses. And now suddenly the world has changed. AI has arrived. And what Bob has been saying all along, a couple of times on this very podcast, is starting to look less like prophecy and more like something that's actually happening. So Mariana, for those at the back who haven't been keeping up, Who is he?

Hack Facts.

Bob Mosher is founding partner and chief learning evangelist at Apply Synergies, a strategic consulting firm built around the 5 Moments of Need, the performance support framework he co-created with Dr. Conrad Gottfriedson. With over 40 years in the field, including a senior role as global chief learning strategist at Microsoft, Bob has spent his career arguing that training and performance are not the same thing, and that confusing the two is costing organizations dearly. He is co-author of Innovative Performance Support, co-host of the Performance Matters podcast, and a two-time recipient of Lifetime Achievement Awards in the learning and development industry.

In this conversation, Bob gives the most concrete account I've heard of what AI is actually doing inside a live workflow learning practice. The headline number, development time cut by roughly three-quarters, is striking enough, but it's the implications he draws from that which I found most interesting. He also takes a question I put to him fairly bluntly, whether workflow learning after all these years has actually become mainstream, or whether it's just become a shibboleth, something people nod at without really believing, and he doesn't dodge it. And he talks about where The boulder might be going next.

So hi, Bob, it's great to have you on the podcast again. I think we count you a friend of the podcast. You've been on a couple of times. Welcome to The Learning Hack.

It's wonderful to be here, friend. So honored to be back. Looking forward to the dialogue.

Your fame redounds across the seas, but for listeners who may not know you, can you briefly explain how you came to focus on workflow learning in what you do?

Absolutely. Yeah. I've been 43 years at this trade and about halfway through that, 20 years or so in, when I was at a large IT computer training company that some may be able to guess at, I was challenged by the training doesn't feel like it's enough. For how much we spend on you people question. And that thrust me into this journey of the last 20 we'll talk about today, where I really had to go deeper personally and professionally and at the time with my team about, look, is there more to getting people to performance and productivity and ROI than just putting them through training? And that was the beginning of, of where I sit today.

Yeah. So most of this conversation is going to be about kind of catching up since the last time we spoke, because, you know, a certain big technology trend has happened really big since then. But just before we get into that, do you think you can describe the 5 Moments of Need framework, which is, I think, is still a kind of cornerstone of your practice? Give us a quick recap of that, how it underpins your practice.

Yeah, absolutely. And to give it some context, I'll just kind of fall back on my story, right? And that is that when I was challenged with that business question from a business leader, not an L&D person, I journeyed out and found this guy, Dr. Kahn Gottfredson, and his work around the 5 moments of need. And it framed it for me like I think many would argue Kirkpatrick and some of these other frameworks that we throw around helped me understand that the, Kahn was doing research on need-driven learning, contextual-driven learning, experiential learning, which is where I think we all, you know, at least want to go, and workflow learning. And he came up with the 5 moments, which are new and more. This is from the learner's perspective, the performer's perspective. I know nothing about a topic, or I know some and want to learn more. Classic new and more brilliantly met by training. Really very defendable in training. The problem he found is that, and why I was challenged by that person, was because there's more to that. To get people to being proficient, current, productive. And that's apply, solve, and change. And I think in L&D for years, and I know I had my first 20, I thought training covered all those. And I have since learned, and Kahn has taught me, and I think research supports that although training is absolutely a part of the 5 moments, apply, solve, and change are best met and addressed while working, then stepping out to learn. So again, new and more training, apply, solve, and change workflow learning.

Now, when we last spoke, generative AI wasn't really on the horizon. I mean, we've spoken in person since and been to conferences together and so on. But when we last spoke on this podcast, we just didn't have that generative AI around, which has since been such a big explosion, at least in the way it's changed the conversation, although People are beginning to be a bit nervous about when are we going to start to see some results from this? They're out there. It's a bit of a black box. We know people are experimenting and so on. How has its arrival changed the conversation from your point of view when it comes to workplace learning?

Yeah, I think on a broader sense, my friend, I think it has clearly changed the narrative around the build, right? What we often talk about, to peel the onion back a bit more, is inside of the framework of 5 Moments, and I'm very careful with the words, 'cause we don't believe that Five Moments is anything more than what we would call a framework. Frameworks need methodology, frameworks need deliverables, framework need disciplines. Those are the deeper levels of us moving towards applying them. And in what Dr. Gofferson has developed as the ENABLE methodology, which is his ADDIE, I'm sure many listeners will know ADDIE. Right, Kahn's ENABLE methodology is the maturation in his work in Workflow Learning 5 Moments of the ADDIE model. And what I think the very first thing, John, that it jumps to mind, and this is in our work in my company, frankly, is that ADDIE and ENABLE still have two significant elements to them, which is building stuff, getting SMEs time. And in our case, understanding what the workflow is and analyzing the workflow, which is a whole new set of conversations and questions. In design than I came from in eddie. Well, guess what? Pre-generative AI, that was all on my shoulders, on long office meetings with whiteboards or Zoom calls with murals. And the generative side of the build in the methodology, and I think in L&D in general, is remarkable and lets us get to a deliverable quicker, lets us get to other things faster, lets us play. And I think we'll talk about this today. Other roles differently than we frankly have just had time to do. And I know some people are being threatened by the fact that it's attacking the— some of the art of what we've always done. I would argue that that is— if you view yourself by the limitation of the build, you're missing all that we could be doing. And generative AI, number one, has exponentially decreased the development side, SME demand, even ability to correct currency, even the outcome being a little better quality earlier than we could ever do before.

So could you put a bit of specificity about that and the time it saves around creating content in terms of deliverables, stuff that you will send to people to support their learning, and also the SME angle, getting the information out of SMEs.

Happy to do that. So powerful, John. We, in our discipline, if I may use that context of the workflow learning thing, right? In Enable, we have some very important analyses or processes that we hold ourselves accountable to, like any designer would. right? And so they are rapid workflow analysis, just basically figuring out what the workflow is, uh, ahead of, ahead of designing anything. The critical nature of the task you just, you discover in the workflow design, which, which has a huge impact on the build, the builds that come, we'll talk about in a moment. Um, the blend of training and, and workflow support, performance support. Complexity of that, of those tasks, which, which is a part of governing the content, content management, all these other kinds of things. And then lastly, you then put it into a digital coach. We've talked in the past in podcasts, you put in your deliverables and you also decide what then goes into the training deliverable. So you have this blend. John, every single part of that we've seen cut by 3/4, 3/4. And, and so, and your question about the, about the SME, you know, we used to say, okay, look, can I have 3 hours of your time over the next month, maybe 4 or 5 times, you know, and, and that's one SME, not maybe 2 or 3 that you'd love to have.

Yeah.

And by the way, send me all the documentation you have. Do you have SOPs? Do you have a course already? Do you have, Oh my gosh, John, right? And so that was the wrangling of that beast. We have put that into prompting, into tools we're seeing vendors create under the Workflow Learning methodology. And starting the first meeting with a first version of all that done.

Yeah.

That, I know everyone listening doesn't know the methodology intimately, but I'm telling you, friends, that is, the first 2, 3 meetings of our time with these SMEs. We go in now, and in fact, with the ones we know well, we send it ahead of time and go take a look. And we're going to discuss this at our first meeting. And it's insanely— now again, what I want people to listen to, and this is where I hope they take heart, is that would we ever go, at least honestly, I think for the foreseeable future, from the AI output to a deliverable and skip the vetting, you know, no, no, no, no, no, no. Right. That's where the art of design and what we do during those parts comes in. And, and the SME always forgets stuff that's not correct. We left this entire part out once they see it.

Yeah.

And I don't see how AI would do that, including even understanding the context of a workflow.

Yeah.

Right? Which is really hard. I mean, it's, but if I again can go back, the lift in this is months to weeks, days.

It's very new and must snap the necks back a bit for your SME occasionally when you turn up and instead with them expecting to kind of give a brain dump and find that you've already got a brain there they just need to kind of comment on. Do you get any pushback over that? What the, you know, WTF is going on here?

Well, you know what they usually get to, friend, right away, which ultimately happens in a normal RWA anyway, is that I don't really, I'm not as much of a SME as I thought I was. I mean, I don't know, you know, I came in here, I came in here as like the guy or the gal that was gonna be your end-all tip of the sword. Just think about what we used to do in the old days of design, right? So much is being exposed by this, my friend, is that we often got one good SME. And that one good SME represented every worker in the organization. In the course that we built, you know, not let alone workflow learning or anything embedded. Now that we start out with that, what it does, and you're right, they're put on their heels sometimes at first. And this is where this is the art of the narrative is that you have to help them understand that nobody has everything in their head that a senior vice president of sales knows or does. Yeah, right. And so you're right. When they see that list, they're like, holy cow, I only know a fraction of this. "Or I didn't realize half of this existed at all." Or, "There's stuff missing here that our documentation I gave you clearly does not cover that is the real work." But what I love is we always got there, friend. We always got to those obstacles, but we get there in a meeting. One meeting. It's so inspiring, honestly.

And to kind of harp on a hobby horse of mine, I suppose. Sorry, that's a terrible mixed metaphor, harping on a hobby horse of mine, which is the difference between kind of tacit and explicit knowledge.

Yes.

Does this process smoke out a lot of tacit knowledge that just the AI wouldn't have access to?

That's what's so exciting, my friend, is that because of the acceleration, the accuracy of this process with these tools, we arguably did not get to that as much as we probably and responsibly should have. But the time and the SME and the, what Kahn calls the institutional inertia, you know, to tolerate this thing or momentum that would, you know, that just lags on and starts to die. Yeah. Didn't allow us to get to. But boy, we, we, you know, we have an organization that's like, look, you know, and they're like, now that we've seen this, we're losing a lot of people in the coming year. We want to use this process. Forget 5 Moments. Forget— we really need to use this process to capture what those people are leaving with. Think about that. You know, the old exit interview thing where Joe walked out the building and 5 people realized that also half of how we did things left with Joe. And we had no idea. And we had no idea. This is really, and again, what I want your listeners to get excited about is when, since when was L&D seen that way?

Yeah.

You know, we were the course builders or the training department or the, now by this client of ours, we're being seen as this whole HR talent management consultant that's helping them Understand, 'cause AI is scaring people about what will humans do? What will the AI do? Can we get rid of Mary, Bill, Joe? Well, let me ask you a question. Do you really understand what Mary, Bill, and Joe do? Not by their role or their job description, but by, and then let's make some really good decisions around those questions I just went through. That is so far away from, can you design 5 days of training for me on leadership?

Yeah.

I mean, think about that, right? And so, yeah, this is, and this is just the generative side of AI within our work. There's obviously the generative side, or there's the AI side of what we can build now.

Yeah.

You know, as a deliverable.

Yeah. So many issues in that, and I can see that people might be worried, and we hear rumors of a bit of pushback from middle management, the people who've been around a while but, you know, haven't risen to the top team or whatever, but have a lot of that tacit knowledge in their heads. Is that, are they really going to cooperate with this process when they're basically signing their own P45? But it's another whole set of issues. What do you see as the biggest opportunities generative AI brings to performance support and workflow learning? I mean, you've talked about time savings there, but beyond that, and maybe other risks and potential pitfalls that that come with that.

Yeah, yeah. It, it's— here's, here's my biggest thing on that side, friend, is that— and I'm gonna come back to enable, if I may— is that what I was focusing on was the— this E-N is all one letter. A-B-L-E is— it's 5 letters, right? I was focusing on the A-B-L-E, A-B-L part, which is the build, leverage, iterate part. There's always been the E-N on the front, which is engage to align with the business. Right. And the E on the end, which is evaluate, which is also, by the way, the same E as Addie had.

Yeah.

And here's my— here has always been the problem, you guys, for us, is that we are so burdened with the middle letters that our ability to become these performance consultants we want or partner with a business we'd like to be or a seat at the table, or I don't want to be an order taker, all those things we've struggled to get to because we're so darned mired in the build and therefore locked into these deliverables as how the organization sees us as valuable. We are now able, because of this reduction of months to weeks to days, I can go in now on the performance consultant. I've heard performance architect. I've heard all kinds of funky new roles, right? Outlined with this, we can go in now and say, look, what used to be a 3-month build is going to be 1. And can I talk to you? So that's terrific. We saved 2 months. Can I talk to you a little bit on the front end of that? Obviously, we have time to get— be sure that the deliverables, you know, really what we want and engage in this whole other ROI performance consultant business impact. Are we mapping to KPIs? Are you here because this is your own problem or because it matches to the visions of your company and their strategic goals of '26? We never had any of those. We were very rarely invited into any of those conversations. Our ability to evaluate in the backend, analyze data, usage, business impact, AI's ability to crunch data, look through HR systems, look through digital coaches, look through people's performance plans. I mean, it's, it's staggering. Yeah. Right. And so our ability to be more intentional on the evaluate, and by that I mean ROI side, not just do people like the class or, yeah. Yeah. You know, right. Now, if I may, before we go on real quick, is that I do know that for many people listening, those two muscles are extremely weak. If they have them at all, honestly. So I'm not minimizing the lift here on the L&D team side or the ID side or even the learning leader side. But the opportunity, and maybe that kind of bleeds into the obstacle, is we're now coming into areas that we wanted to be in, but frankly may not be very good at yet.

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Well, that's the kind of flip side of it. I mean, overall, it's heartening, it's optimistic. It's a great story about technology enabling us enabling us to do things that we always wanted to do, but just didn't have the time or the money to do. And a lot of that happened with just going to online learning in the early years of the century, allowed people to kind of train and give compliance training at a scale that was absolutely right for the scale that global organizations were achieving with globalization. But would be difficult by face-to-face means. So now here's another thing that comes along and helps us to do what we always wanted to do and get all those things that L&D wanted, being a business partner, seat at the table, consulting, and so on. Are there risks just to the practice of workflow learning? I mean, aside from any of that, are there risks to it that come with AI?

Sure. The ones we're seeing early on are the rate of change. Yeah. Within the platform is hard to keep up with. The risk around us understanding, at least for now, it seems that methodology begets technology has always been a quote that I've lived by back when at TRS-80. Landed in my third grade classroom in 1980. Sorry, a TRS-80? TRS-80 was actually a computer out of Texas Instruments that had a tape drive. Oh yeah. Right? But my point was, that was my first foray into technology and learning. And we screwed up back then because we basically said, well, let's have it do long E and you know, some math flashcards with our kids while instruction happens over here. We didn't integrate it. We didn't apply, you know, learning theory to it in an instructional design so that it became an integrated part of our classrooms. I would argue e-learning in some ways too. So to fast forward is that I think the risk is us not being involved in the IT conversation of AI and the rollout and implementation in a lot of organizations. Right now, a lot I'm talking to John, the IT department's driving that decision, not L&D or even HR. But there are clearly HR, if nothing else, implications of where that will land. And so the risk is not being involved, having a seat at that table and helping with— it's a tool for performance at its core. We are in that business and there's a risk of the train leaving the station without us. Right.

And that's to do with productization, I suppose. Oh my gosh. You're making me think about the conversation we had before we actually started this today, not on the tape, as it were, about the platform we are using, Riverside. And in various ways, we've both got an established workflow. This platform knows nothing about our workflow, and it's helpful to the extent that we can use bits and pieces of what it's offered, but the kind of optimal use and savings in time and so on we could get from this platform is to follow the workflow that it wants us to do. But it's not my workflow and I'm not going to follow its workflow.

And John, this is, you know, I told you I did a recent podcast with a dear friend of ours, Donald Clark. Oh, yes. And if there's a guy that rides this bleeding edge, I don't know many in the world that do like Donald. Right. And he sees the opportunity and he's He's very, I think, very pragmatic about, non-emotional about its impact on L&D and some other things that I totally understand have come with that. At the same time, he's one of the first to throw the red flag about context workflow. It's struggling with really understanding what that is. So what it does is it can bring you into its box. It can bring you into its interpretation. Dare I say, its hallucinization of that, which is really more its inference. It's not so much hallucinating like it wants to be wrong or bad. So there's the mitigation that we have to be sure we're involved in and falls back on the art of design. But we have to be prepared to step into that arena be a part of that conversation. You know, a lot of L&D folks are being closed out, John, just by the simple fact of they have to use Copilot. Yeah. And they have to use Copilot like a user uses Copilot, like not, not in developer levels or any kind of designer stuff with it. They are locked into the people who have it embedded in Word. Yeah. You know, right? And so, so to be allowed into that next circle of trust and that next circle of influence and those decisions being made at the, at the business, those other levels, we have to be ready to step in there. And I would argue that it's not as scary as it sounds because a lot of people know there's a lot they don't know. Yeah. Yeah. You know, so I think they're looking forward to that.

They're looking for the help. Yeah. I think you get the sense that we're going back to a position that has happened occasionally where the tools you use at work aren't as useful as the tools you use at home. There was a point where organizations, you know, there's a point where you get a job because you'd get a great computer to play with. And there's no doubt. And then it changed over and you had all these domestic computers, people like Dell came along and you ended up with better kit at home than you had at work. So at some point you might throw your hands up and say, look, I'm going home for the afternoon to do this 'cause I've got better kit at home. Totally agree. And you can imagine people who can use nothing but, you know, without throwing shade on any marvelous manufacturers like Microsoft, you get into a position where at work you have to use Copilot and you'll go home and use Claude Code and be in the agentic world and so on.

Sure. Yeah. I think the metaphor is brilliant. And I think, you know, you and I have been around long enough, friend, you know, to have seen the evolution of technologies, right? When they come in. Clearly this is one like, I don't know if I've ever seen, but at the same time, let's not, as we say in the States, throw the baby away with the bathwater here. And that there are learnings about technology adoption. That we've seen over, and there's cycles, we've seen over, there's been papers written on this, PhDs over and over again about how this adoption curve works. And you're absolutely right. I mean, it's a, this train is running way ahead. These LinkedIn posts and these papers being written and things on X being posted. And then I go back to my cope, and again, not bashing Microsoft, I go back to the platform I'm allowed to use. And I go, are you, what, what, what? I'm woefully underserved here by my ability. I did an interview recently in one of our podcasts with a wonderful learning leader, super techie guy, PhD in performance support, this stuff, right? And I couldn't wait to ask him, John, how excited he was about AI and what his 2026 plans were. And he paused and I'm like, okay, here it comes. And his answer was, you know what, here's the thing. I've got a training course to get out by February 3rd for onboarding 1,000 sales reps. I'd love to be playing around in this thing. I'd love my people to be experimenting and coming up with things. And he goes, but the reality is I'm juggling the inbox and what I've got to do every day with this tsunami that's coming at us or going away. And I'm being guarded. It was the last thing I expected to hear from this guy because he, to me, is on the far end of the bell curve as far as a learning leader goes or technology and stuff. So we got to be really realistic and watch and still get our juice.

Who is that guy from one of the kind of founder models over Christmas who threw his hands up and says, you know, I'm, you know, among the best coders in the world and I just can't keep up with this stuff.

Hack Facts. John, I think you're talking about Andrej Karpathy, co-founder of OpenAI. He also worked at Tesla and is credited with coining the term vibe coding. On Boxing Day 2025, he posted on X I've never felt this much behind as a programmer. I have a sense that I could be 10x more powerful if I just properly string together what has become available over the last year. Think about that.

That is astonishing, isn't it? It really, really is.

So you trickle down into us, no offense to us, or many who have day jobs, and what are we doing? So I really took heart in the rest of that podcast with this gentleman because he gave a very, I think, balanced response to, I'm going to be in a different place at the end of this year. I really am. And I'm going to own AI within my domain. And I have certain things that I'm challenged with by the organization. But at the same time, I'm not going to be irresponsible. I'm not going to ask my team to do things they can't with tools that won't get them there. And by the way, if I don't have that onboarding course by February, I'm out of a job. Right? So I think those are important things we have to keep in mind in all of this coming at us.

Have the way you design programs and the tools you use or recommend changed with the rise of generative AI? Is it making a big change apart from bits of incremental time saving? Is it making any kind of, has it caused a rethink in how you design programs?

It absolutely has because it's, there's two things that I, that it has because of the time we talked about earlier that have come back on the radar for us. Number one is the digital coach is a deliverable for us. Yeah, we talked about it on our last podcast, right? It is the— as classes to training, e-learning is the training, digital coach, targeted training are to us, because this is what we're paid to do, right? Is what we make in that domain. And it's forcing us to look at what— these things are great to get us to the deliverable, coach, to accelerate SME time and the whole deal. But the digital coach we're making as a deliverable, how should it incorporate chatbots? How should it incorporate, you know, what of the older, if I can use that word, and they're not necessarily old, but what of the older deliverable should we still hold on to and honor and be a part of what we come up with that these remarkable tools can sit on top of or could replace? We're looking hard at that. And here's the irony of the whole thing is I don't see training going away. Nothing has made training go away. And I don't know when it ever will, frankly. I mean, I don't want an airplane pilot getting on an airplane who's been AI'd. At least I don't know if I see that happening for a while, right? And so we're so ingrained to having gone to school at 5 years old. To, to go to this thing, to, to master things we didn't know, that that model, the idea of that model, obviously not the brick and mortar of that model or some of the things, I don't see going away. And the irony is, friend, that because of the lag and other things, we became very myopic on the workflow learning deliverable and very casual, if not frankly didn't even get to, then what does the training look like anymore? Hmm. What is the, what is, what is targeted, as we call it, targeted training? Not, you know, what needs to be trained anymore? What should, what should the training experience be like with these tools now? And what is an instructor's role in that? You know, these types of stuff. And so the deliverable of the workflow we're looking hard at and is changing, chatbot being the easiest low-hanging fruit because that's We all know them and they are a part of what we click into and type into in these things. So we start there. And also the training footprint and the training makeup and design and flow and roles and experience are really being dramatically changed by this influence.

So when you speak about a digital coach here, you're not talking about an off-the-shelf LLM, are you? You're talking about something that kind of is a wrapper, sits upon an existing— Yes. Yeah. Thank you.

Yeah. And I'm glad you pushed back there, John, because this is something that Khan has struggled with for a long time because you gotta call it something, right? You have to have a, and it used to be EPSS. People listening remember that acronym, right? Electronic Performance Support System. Clippy tried at one time in Office, you know, these kinds of things. You know, in the old days we had these things that were on top of our IT systems that would, you know, walk us through filling out fields, right? These kinds of things, right? The digital coach is not necessarily something you find from a vendor. To Khan, it is a construct. Gloria Geary in '91 defined it in her book as an integrated set of systems, right, that advises and coaches through training, through resources, through colleagues on how, you know, that is a digital coach to us, friend. Can you buy some of it? Yep. You know, can you, is there a human element to it like a coach coach? Is that in the construct? Is that in the digital coach experience? It is. So when we talk about, when we use that term, we're talking more about that broader construct, not a thing you'd buy on a website or from a vendor at in an expo.

Yeah, and the important thing is that the information and the knowledge that imparts is, it's accepted as true within the organisation. I'm dancing carefully around things because our standards of truth are kind of being recalibrated, but it's reliable information. It's not just something that gets scraped off the web and thrown back at you with a very confident sounding voice.

It's authoritative information in the judgment of that organization. Well, content management, but right, how long ago single source publishing, you and I are old enough to remember these words being danced around in our industry. These were the beginnings, right? Right. These are the beginning ideas of these things. And LCMS, a learning content management system. Well, LLMs, you know, these tools really harvest those things. Great. But to your point, friend, a lot of those tools and those disciplines are coming back in a big way. Because of your point of just because I can get you in seconds an output to a question that pulled from an LLM either internally, externally, or both, is what I'm looking at correct? So that whole part of this vetting currency, you know, and there are ways to make the AI iterative and checking itself. And was I correct, meaning I, the AI, But again, where do you say, okay, great, I trust that you went through 3 iterations of correcting yourself? I don't know when we sit there realistically, particularly when you're talking about content that's very important to an organization or your sales rep selling correctly or someone acting ethically or morally or not getting us sued, you know, or crashing a plane, right? So, So again, there's a role here, and I think we should take comfort in that that's going to be around for a bit, I think. Again, though, are we ready? Are we seen that way? Do we have a methodology in place that lets us defend doing it right and well and being allowed to play that role? You know, these are questions that we have to be ready to help answer or have an answer for.

To get a bit more specific, obviously you'll be NDA'd up to the hilt, but could you share an example of how AI has made a consequential and measurable difference in a workflow learning project you've worked on? You know, we're aware that people are experimenting. We're aware that there's a kind of, But we don't necessarily hear the results of those experiments because within the workflow, within workplace learning, there just isn't the same kind of obligation to publish that you get in academic spheres or in science. So the experiments that fail won't be written up, and in a way, they're the most instructive. But also some successes will have to be quiet because people don't necessarily want to tip off their competitors within organizations. So we know that more is going on than we really know about. So gold dust for this podcast, I think, is specific examples of how AI has actually worked within an organization. And can you share any of that?

Yeah, of course, it's anecdotal to your point, and it's very early.

Unredacted, no doubt. Yeah, yeah, yeah, yeah.

That's a big word over here right now. Yeah, but it's really, The early results on a handful of projects, and I want to be sure I'm, I'm transparent about sample size here, right, is that the reduction in development time is settling in around the 75% range. Wow. Of what it used to take. Yeah. Yeah. Used to take before the, the early findings around the the integrity of the design appears to be higher because it would have taken longer if, honestly, I think I would ever argue we got to that level because of just the grunt work of getting there and the idea of that project's done, let's move to the next, you know, kind of a thing. And so we're seeing the quality coming back better earlier. Yeah, by a significant amount. And the other thing that we're seeing is a stickiness to these projects because they're out faster. You know, they're more correct, if that's the right way of putting it. And the technology around the digital coach side is better. So all of that rolls up into what were historically adoption obstacles for this discipline as long as I've been at it.

Because I was going to say, this must be cutting down your billable hours.

It is. It is. I mean, and so there's that argument, right? But here's the thing, my friend, and I just spoke for a large training group here where I live, and I said, you guys, I don't know many L&D people who are bored, you know, or who, or who couldn't fill the cup more if the cup wasn't already full. And, and we found the same. It's not that we're lacking for work, it's that we've, we've always been a funnel to being able to do more of it. So it's early on, but right now the, the ability to take on more work, go deeper within a client penetrate beyond one good proof of concept or minimum viable product, um, is stronger initially— I'm choosing my words carefully— then I've been at this 20 years, John. Yeah, right. And so in my 20 years, I've not seen a change like this, this early.

That 75% number is really impressive. And if it was anyone other than you, Bob, I might feel a bit skeptical about that, but I can't believe you're not convinced.

Well, and again, it's in a handful. It's in a hand— Yeah, no, no, no, no, no, no, no. And it's a handful. I almost even leaned back towards 50 when I was saying those words to my friend in the thing, but that wasn't representative. It's better than 50. By a bunch. And so it's an interesting business model to address. At the same time, back to my obstacle thing, you know, and the billable hours stuff, if I can go at that candidly, you got to be careful of being pennywise, pound foolish sometimes, friends, in your work, right? And so there's the You're holding this big fish going, I could eat on, you know, I got, I can be full for days. Eventually the fish goes away. Yeah. Right. And, and so the question becomes, do I want to be fat and happy on a big fish or two? Or what if I can do a lot of fish? You know, what if I can do more for my clients or the— or substituting the organization you work with, you know, obviously many people who listen are part of an L&D team within an organization. I don't think we're going to be without work, but I think we have to embrace it.

How does AI change the role of L&D professionals more generally? What skills should learning leaders be developing now to stay relevant in the AI-driven or AI-assisted environment we're talking about?

Yeah, they, they, well, number one, they have to have a trusted source for AI that they, that they follow, and they have, they have to boil that ocean and calm those waters. I, when I was interviewing Donald and Alfred in my podcast, I asked, I said, look, so where do you guys go for work? You know, we're, we're, if I don't keep up like you, you two do, and Donald, I'm, I never will, he's just remarkable, right? And he gave me like 2, 3 sources, right? Or a You know, or a platform he'd like to stay within. I think in L&D we cast this too broad of a net in trying to read every post or follow every guru or, you know, connect with every person who seems to know what they're talking about. And I'm not, by the way, bashing any of those people, but my advice would be settle on a manageable, trusted resource or 2 or 3. Yeah. And let them do the work for you. 'Cause a lot of them are brilliant. Yeah. And that's what Donald does.

Do you wanna name a few names here? I mean, This is usually my last question, but I've got another one to do after this, so we're going to jump the question order. Nothing wrong with that. You want to name a few names?

Well, right now my two are Donald Clark, honestly. He recently wrote this wonderful book about AI and productivity, which if you don't mind, I'd be happy to promote here. And Josh Cavalier over here in the States came out of the learning— he just wrote a wonderful book on AI and learning. And they're getting up every day to do that as a living. And so, and I know there's others and people who listen will have others, but those are two, as I told a group before, I think if you read those two books and you're sitting at like a 101 level, you'll at least go to 201. Yeah. Maybe even tip into 301. 'Cause you and I both know, my friend, things that Donald writes can percolate for a long time. You know, to catch up to. So I know that's, I don't, I know that that may appear to have blinders on, but my point is pick 2 or 3 of your own then, but make it realistic. And those are my 2 right now. Great.

So where do you think we'll be in 5 years, say? I mean, difficult to really predict 5 months ahead, I've learned that. But workflow learning has failed so far to become really mainstream. I think it's fair to say, even though people have been talking about it a lot, they still continue to talk about it. It's not like it's gone away, but it's something that people nod towards like a holy icon where they don't really still believe in God, but they still kind of have to genuflect when they go into a Catholic church. Sorry, I'm getting a bit autobiographical here. Do you know what I mean? It's become a kind of shibboleth, but people aren't necessarily, it's not really mainstream. We still have totally LMS content, so on. Do you think AI could change all that? Really, really soon? It's going to.

I do believe, I've written about this a couple of times in my own blogs and such, is that I always hoped that other things would be the tipping point of this, John, swinging the other way, because it has been around since '91 when Gloria wrote her book, and it's been around earlier than that. And other things. And so, you know, as a dear friend of mine once said, you know, people aren't going to come to you for red pants if you only sell blue shirts. Yeah. And I've always wanted people to say, well, yes, for red pants, you know. And, and so it is to a point where you're going to have AI natives obviously coming through, right? Not, not not, you know, those, you know, that have sat on the outside and are catching up. And it's going to have a significant influence on roles, responsibilities, and that AI-to-human balance. That's going to elevate the performance conversation in a way that training will not be seen as able to keep up. And that will be the tail that wags the dog, right? Like I said with my friend earlier, that I got on who's probably as innovative about this, his PhD is in performance support. That's what he got a PhD in, yet he's trying to build an onboarding course for sales reps because that's what his SVP of sales sees as the tip of the sword. That this technology is going to change that meter. It's going to move it and That's going to be when people start walking in going, you know what, I don't, I know, I don't even want to ask, talk to you about training. I want to see how you can make Copilot that I'm using in Teams help my sales reps sell better. When someone comes in with that question, then the formula has dramatically changed, you know, so that I do see as being the tipping point. Of this conversation and therefore the adoption and the demand, which is different. You know, I've always been pushing the boulder uphill. I think the boulder's gonna roll back on us with this.

So lastly, we've used one of my last questions, so I hope to give you the other default. What's your karaoke go-to? So I'm sorry to lower the class of the conversation.

I saw this question and thought, oh my God, this is gonna kill him because I know you're pedigree friend and the whole deal. But when you asked that question, you know, I'm a huge Billy Joel fan. Huge Billy Joel. Yeah. Huge Billy Joel. So it's Honesty, it's Piano Man, you know, it's those rabble-rousing, good bar, good pub songs, you know, that people get. It's my genre.

Yeah, yeah. What's that other one? We Didn't Start the Fire? Yeah, yeah.

That was, which by the way is one of his least favorite songs he wrote, by the way. I saw it in a book. Yeah, but it, but yeah, those are Those are my karaoke go-tos.

Uptown Girl. Uptown Girl. Yeah, which I sing that to my wife and she hates me for it. She throws something at me.

There you go. There you go, friend.

Yeah, well, I'm glad we've settled that important question. I am too. Thanks a lot for that, Bob. It's another wonderful chat and I'm already looking forward to our next one and I hope we bump into each other IRL really soon and keep keep pushing that boulder uphill.

Yep. Thank you for giving me a way to do that, friend. I appreciate all you do for our industry and the, and the, and the dialogues you host. These are important. Cheers.

Thanks very much. That's all on the Learning Hack Podcast for this time. Many thanks to our guests and to our sponsors. The Learning Hack is completely independent and transparently funded by sponsorship. It is produced by John Helmer and hosted by him and also me, Mariana. A Synthesia AI avatar. If you want to help others find us, please like, follow, rate, review, and subscribe wherever you get your podcasts or on YouTube.

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Wow, now I finally get it.

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