There’s a moment Dan Streeter describes that will sound familiar to almost anyone in the learning and development space.
It was November 2022. He sat down at his computer, saw a small news item about something called ChatGPT, and opened it out of curiosity. He asked it to build a scope and sequence. It did. He asked it to take those learning objectives and generate a storyboard. It did. He asked it to revise the storyboard, expand it from 20 slides to 30, then build a script from a single slide. Each time, it delivered.
“Literally my jaw is dropping. I thought: we are in such trouble.”
And then, almost immediately, the other feeling arrived.
“You’ve got to be kidding me. This is so cool.”
Both reactions were right. And holding that tension, of genuine alarm and genuine excitement, is what has shaped how Dan Streeter thinks about AI, learning, and the profession he has spent his entire adult life inside.
Dan is the CEO of Mission Fuel AI, an instructional design company that builds e-learning almost exclusively for associations, often on a revenue share basis. But his path to that role is anything but straight.
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From Checked Out to On Fire
Dan’s relationship with education started badly.
In middle school, he put his hand up in class and asked why they were learning binary numbers. The teacher’s answer was simple: “The county says you’re going to learn it, so you’re going to learn it.” That was enough. Dan was done.
“All my middle school and high school experiences were just a misery,” he says, partly because of his own attitude, and partly because the system wasn’t built for a kid like him. By the time he got to college, he could barely read or do basic math.
Then two things happened at once. He took a public speaking class. And he got involved with a mentorship program, where he was matched with a 14-year-old named Rob, who had stolen cars, been involved in gangs, and was heading nowhere good.
Working with Rob, something clicked. He was good at this. He cared about it. And he realized he wanted to become a teacher.
“I have been on fire for education since I was 21 years old.”
What followed was a career that took him through the full spectrum of education, high school classroom teacher, VP of sales for a workforce development firm, K-6 principal, middle school principal, and eventually into the world of e-learning. By the time ChatGPT arrived, Dan had lived inside education in almost every form it takes. He knew exactly what he was looking at.
The Gap Between How and Should
Dan’s company, Mission Fuel, has a core model built on a simple but powerful idea: use AI to dramatically accelerate e-learning production, enough to change the economics entirely.
Where traditional e-learning projects might run at hundreds of hours of production time per finished hour of content, Dan’s team has driven those numbers down significantly. A project that once cost $200,000 might now cost $60,000. And crucially, that opens the door to clients who could never before afford serious learning programs.
“We now don’t have to be focused only on those big companies. Now the ticket size is less, but I can do ten of them.”
That’s the democratization argument at the heart of Mission Fuel’s mission, not volume for its own sake, but access. Associations and smaller organizations that have always needed high-quality learning but couldn’t justify the investment can now get it.
But Dan is careful to separate two questions that often get collapsed into one. He keynotes around 40 times a year, and one of the core messages he carries into every room is this:
“I’m the guy who’s going to show you how. I am not the guy who tells you that you should.”
That distinction matters more than it sounds. He uses a simple example. He could theoretically work with a tool that can align headshots to create consistent-looking group photos. He could, in theory, go to someone’s social media, grab their image without asking, and feed it in. The capability exists. But that doesn’t make it right.
As AI tools grow more powerful, ethical judgment becomes a bigger part of the job, not a smaller one. And with a federal government that has signaled it won’t be putting the brakes on AI development, the responsibility falls back on practitioners. Dan is also candid about where the hard questions remain genuinely unanswered, particularly around copyright, when someone uploads a published book they don’t own into an AI system and uses it to generate proprietary content.
“Where do we draw the line when it comes to IP? There’s not a great answer right now.”
He doesn’t pretend otherwise. That intellectual honesty is part of what makes him worth listening to.
The Trust Problem Nobody Is Talking About Enough
One of the most striking exchanges in the conversation comes when Dan and host Jason Gorman start talking about what AI-generated video is about to do to our sense of reality.
Dan describes a Google-recognized project where two people watched what they believed was the same video at the same time. Because of their different emotional reactions, the system served them two completely different experiences, and neither person knew it.
He also describes airport technology that displays personalized information on a shared screen, visible only to the person it’s intended for. It sounds futuristic. It’s already real.
“In the next five years, there will be more video of me that is not real than real,” Dan quotes Gary Vaynerchuk as saying. And Vaynerchuk said it matter-of-factly, not with alarm.
For L&D professionals, this creates a specific and urgent responsibility. Jason frames it this way: the learning professions have always sat in the seat of pushing back on clients when a proposed approach raises ethical flags, when something feels like a dark pattern, when a design might manipulate rather than serve the learner.
That role is becoming more critical, not less, as the tools to shape perception and emotional response become cheaper and more accessible. The question of whether a learning experience is genuinely serving the learner or subtly steering them is no longer abstract. It’s a design decision that practitioners face every time they build.
We Cannot Remove the Human from Human Learning
There’s a version of the AI-in-learning conversation that treats the learner as a variable to be optimized. Feed in a profile, get out a personalized path. Automate the delivery. Scale indefinitely.
Dan doesn’t buy it.
“You cannot remove the human from human learning.”
This isn’t nostalgia. It’s a design principle grounded in his years inside classrooms. The most powerful application of AI in learning isn’t replacing the instructor or eliminating the relationship between learner and content. It’s making that relationship more responsive at the exact moment it’s needed.
He describes a warehouse worker who stalls on a task they don’t know how to complete. Instead of stopping work, hunting for documentation, and starting over, the right piece of learning surfaces in context, right then. That’s just-in-time learning done well. AI makes it genuinely possible.
But he goes further. He describes a future where a learning module isn’t just delivered to a learner, it’s built for that specific learner, based on their professional background, their existing knowledge, and the precise gaps they need to close. Someone with twenty years in L&D needs to encounter material differently than someone in their first year. Right now, the content is largely static. It doesn’t have to be.
“We know that you likely have this background. These are the five things that Dan needs. Let’s build the learning right then and there.”
That’s where the field is heading. And it requires both better systems integration, L&D tools still largely don’t talk to one another, and a clear-eyed view of what learning is actually for.
AGI Was 30 Years Away. Now It’s Five.
One of the sharpest observations Dan makes comes when the conversation turns to timelines.
When ChatGPT launched in late 2022, the expert consensus on artificial general intelligence, the point at which AI matches or exceeds human intelligence across domains, was roughly 30 years out. Now many of those same experts are saying five.
Why the dramatic compression? Dan’s answer is simple and worth sitting with.
“You’ve now unleashed a tool to seven billion people, all of whom have cell phones. You’ve released the most powerful tool on top of the most powerful tool in human history.”
The acceleration isn’t just coming from labs and research teams. It’s coming from billions of people using the tools every day, generating data, finding edge cases, and pushing capabilities in directions no single organization could have anticipated. IBM has now assembled a dedicated AGI team whose explicit job is to figure out how to make AGI work and identify when it arrives.
Dan is honest that he doesn’t know what comes after. When artificial superintelligence arrives, a single system smarter than all humans combined, he says plainly: “It will eliminate the vast majority of white-collar jobs. Where do we go? I don’t have an answer.”
But that uncertainty doesn’t paralyze him. It clarifies the work.
The Great Displacement Is Coming. So Is the Great Reskilling.
Dan is a tech optimist, and he’ll tell you that directly. But he’s not a naive one. He has two sons in their early twenties. One wants to be an actor. He thinks about what happens when the first AI actress gets signed to work around the clock at unlimited scale, and what that means for everyone who has trained for those roles.
The honest answer is that displacement is coming, and it’s already visible. Amazon is projected to dramatically reduce its workforce not through mass layoffs but through attrition, simply not filling roles as AI absorbs them. The pattern will repeat across industries.
“There’ll be the great displacement. But then there’ll be the great reskilling.”
That transition is where Dan believes L&D professionals have a role that is both critical and underappreciated. Someone has to build the learning that helps people move from the jobs that are disappearing to the ones that are emerging. Someone has to do it well, at scale, and in a way that genuinely works.
He frames the difficulty clearly: if this transition happened over fifty years, it would be painful but manageable. At five to ten years, the speed is what makes it hard. The content of the reskilling challenge isn’t unusual. The pace is.
The Most Important Job on the Planet
Near the end of the conversation, Dan said something that stopped the room.
“We have the most important job on the planet right now. We were built for this moment.”
It’s a bold claim. But the logic holds. One well-designed piece of learning, built on sound principles and delivered at the right moment, can change what someone is capable of. Multiply that across industries, across a workforce navigating one of the most disorienting transitions in modern history, and the stakes become very real.
Dan’s old school principal used to say that one bad teacher does more damage than one bad brain surgeon, because a surgeon destroys one brain at a time while a bad teacher destroys thirty. L&D professionals operate at even greater scale.
The tools are more powerful than they’ve ever been. The need is more urgent than it’s ever been. And the people who understand how to use those tools in the genuine service of learning, not just content delivery, are exactly who this moment requires.
That’s the opportunity Dan Streeter is building toward. Not to replace human learning, but to make more of it possible, for more people, in more places, than anyone thought was feasible just three years ago.
Listen to the full conversation with Dan Streeter on The LX Ops Show or wherever you listen to podcasts.
Podcast Transcript– Jason Gorman with Dan Streeter
Jason Gorman (00:00)
This Learning Experience Operations show is all about how we operate as learning professionals and how that’s changing, where we’ve been, where we are right now, and where we might be in the future. And my guest today has been in this profession, like I have, for a while, and in the last couple years has pivoted in the most AI forward way I’ve seen of all of the people that I’ve talked to. ⁓
And right now, of course, people are just hungry to understand what the possibilities are in this space with AI in the learning professions. And Dan Streeter, who’s joining me now, is not just thinking about what to do. Dan, you are pushing the boundaries as hard as anyone I’ve met. You are the CEO of Mission Fuel. We’ve known each other for a few years.
That’s all you gave me to say about you in your introduction. And just that last sentence. Normally I’m reading out where people went to school and anyway. But thank you for coming on and doing this with me.
Dan (00:59)
Yeah.
good to tell you all that stuff.
You gotta, hey Jason, it’s truly a pleasure and I remember the first time that you and I spoke several years ago and you were just getting Jackrabbit, you know, really going and it’s been so neat to be able to see your success over the last several years and so it’s wonderful to be on the podcast with you and so thank you very much for that, for the opportunity.
Jason Gorman (01:28)
I appreciate that. That’s wonderful. Well, so we are going to start off with some lightning round questions. And they are what we’re going to have time to go deeper into any of these things if we want to. But these are meant to be too quick, just a warm up for you and I. All right. So the first thing, what is the 30 second elevator pitch that you give about what you do?
Dan (01:44)
That’s a deal.
Got it, well, see if I can keep it to less than 30 seconds. We are Mission Fuel. We’re an instructional design company. We build online learning almost exclusively for associations. And we do it on a project fee basis. And we also do it on a revenue share basis. But truthfully, the underlying sort of rhythm or the ⁓ theme is mission is really to be able to democratize e-learning in a way that’s never been done before in human history.
Jason Gorman (01:56)
All right.
Dan (02:22)
And so we just simply do that through associations and through e-learning. ⁓
Jason Gorman (02:27)
Love it. Okay, next question.
What do you love the most about your work?
Dan (02:34)
Oh my gosh, well first off, I love my team. We have the best team possible and I love the people. And that’s the part that I really enjoy a great deal of. this is now my second iteration of a company that I started way back in 2013 called Impart. That company was acquired in 2020 by a group called Blue Sky eLearn. That’s actually how you and I met Jason was through Blue Sky eLearn. I operated as an entrepreneur for three and a half years and then
Jason Gorman (02:58)
Yes, yes it is.
Dan (03:04)
And then at the end of that, then I started Mission Fuel in August of 2023. So I love the change. I love the rapid pace of it. I love the people. ⁓ And I love making the straight lines out of spaghetti soup, right? I love being able to create a clear vision out of just a mess of ideas. And so ⁓ for me, there’s so much to love about what we do.
Jason Gorman (03:31)
This actually feeds perfectly into my next lightning round question, which is like when you’re really locked in, in the zone, at work, what are you most likely to be doing?
Dan (03:43)
So for me, I’m on a sales call because of course I’m a sales oriented CEO and so that’s really what I do. And I used to be the guy who would plunk away at a storyline file, right? And I was the guy who would sit down and be able to try to figure out storyboards and try to figure out how to build a scope and sequence. I still do a little bit of that work, but the vast majority of the stuff that I do is really in building client relationships.
Jason Gorman (03:45)
Hmm.
Dan (04:12)
and building relationships like with you. Those are the sort of things that I primarily do. And if you find me sort of in the zone, that’s really where I’m at, is ⁓ I’m in a wonderful sales call or I’m meeting with a client or I’m meeting with you and just purely building relationships.
Jason Gorman (04:28)
All right, well, we’re gonna stay in the zone this whole show. I’m very excited about that. Okay, next question. And this is a question really about what you are doing right now with Mission Fuel. What was the event or moment that inspired you to do what you’re doing right now?
Dan (04:31)
That sounds perfect.
Oh
my gosh, well there were two moments that actually occurred. So I’m going to take the, this will be a somewhat long short story. I’ll try to make it as as possible. I was a student in middle school and when I put my hand one day in middle school, I said, hey, why are we learning this? By the way, we were learning about binary numbers, which is like totally fits right here, right? The one zero one zero one zero one, right? And then you had to like logarithm it and figure it out. And I put my hand on like, this is so dumb. Like, why are we learning this? Remember this is like
Jason Gorman (05:09)
Yeah.
Dan (05:15)
1985 and the teacher said, the county says you’re gonna learn it so you’re gonna learn it. I was just done. I was just done with education just period right from there. That was like a pivotal moment for me that that was it. All my middle school and high school experiences were just a misery because partly because of my attitude towards it and partly because the system was not set up for a kid like me to be able to be successful. So fast forward that when I got into college.
Jason Gorman (05:22)
Ha
Dan (05:43)
⁓ I barely could read, I could barely do math. I mean was just awful for me. so somehow, someway, I happened to take a public speaking class and at very same time I happened to get involved with a group called the Jacobs Center.
Jason Gorman (05:47)
Hmm.
Dan (05:57)
and I got a mentee, His name was Rob, and Rob was 14, had stolen a couple cars, and been involved in drugs and gangs and the whole thing. And then I had a chance to learn, like, I love the kid thing, and I love the public speaking thing. I think I got something. I think I could become a teacher. And I was on fire for education. And I have been since on fire, since I was 21 years old, and well, guess I was 20 at the time.
Jason Gorman (06:17)
Wow.
Dan (06:24)
when things just absolutely turned around for me. And since then, my whole life, my whole career has really been about education, whether I was a principal at a school or whether I was in the classroom or in this world, it’s really given me just a gigantic blessing that’s allowed for that to happen. So that was incident number one. Number two was November, 2022. And November, 2022 is when Chat-GPT hit the scene.
Jason Gorman (06:46)
Mm-hmm.
Dan (06:50)
And I happened to sit down on my computer one day, this little thing popped up on the news, said, hey, chat GPT. I was like, what’s chat GPT And I was just curious by nature. And so then I popped that open, and the first thing that happened, I thought, it’s over. It’s over. Instructional design, the way that we thought about it all of these years, it’s now done. Everything from the learning objective creation, to the storyboarding, to even the graphic design, like all of it is over.
And that moment for me was such a dramatic shift to be able to say, we have to literally reskill an entire industry, but it’s not just our industry, it’s the world. The whole world will be impacted by this. for me, it wasn’t just the moment in middle school, was this moment, my first interaction with Chat GPT
Jason Gorman (07:40)
You’re kind of doing my job for me because at least this couldn’t have led better into my next question, maybe, which is, what are you most anxious about for the future?
Dan (07:44)
Thank
So for the future, I have two boys, both of them, I have three kids total. I have a stepdaughter who is 30 and then I have two boys that are 19 and 21. I’m afraid for their jobs. I’m afraid for what the world is gonna look like here very shortly. I’ve got one that I’m not concerned about because he’s an outdoor kid. He’s gonna make it no matter what because it’s not reliant on the technology. But I’ve got another one that wants to become an actor.
And here just, I assume very shortly, there’ll be the very first AI actress that will be signed to an agreement. Who can work 24-7, 365? You can produce multiples of her, unlimitedly. You know, and all of a sudden we have Tilly Norwood. What happens? What happens to the actress of the world? And what happens to, you know, instructional designers of the world, voiceover artists, graphic designers? Like, that is the thing that keeps me awake at night to be able to think about what happens next.
from my kid that are out there in the world. So those are the things I’m worried about. My stepdaughter, by the way, is a writer. ⁓ Same thing, brilliant writer. And what happens now?
Jason Gorman (08:49)
Mm-hmm. Mm-hmm.
Marvelous. All right. Well, we’re going to roll into our full questions now. So we’re, of course, we’re going to talk a lot about Mission Fuel And before we do that, though, I really just, would love, you actually mentioned a couple of things that you’ve done along the way in your career. And I’m really curious to hear about a couple of jobs that set the stage for what you do now.
Dan (09:23)
Yes, that’s a great question. So I was a high school teacher for a number of years. I actually quit teaching three separate times, which is sort of crazy. One time to be able to go out on a professional bowlers tour, one time to be able to get a raise in the corporate world because I thought that’s what I was needing to do. And then the third time was because my oldest son was born, Zach. And so when that happened, had been in the classroom for, gosh, a total of seven and a half years. And so that definitely helped sort of like
create my notion of what it meant to be a teacher, but I had the advantage of actually to sit down and do the work. And I was curious enough about things like the internet and those sort of things that I was fairly tech forward kind of at the time. And then in addition to that, ⁓ had that my second job or second big job was I was the vice president of sales for a temporary employment service. So I had the high school side.
And then I had the post-secondary side, or not post-secondary, but the workforce development side. And I did that for a number years, actually a total of eight years. And then from there, I became a principal of a school. And so then I understood the elementary side. So I was a K-12 or K-6 principal. And then I became the principal of a middle school. And so then when I had that, then I had the full spectrum, literally peak, pre-K, all the way to workforce development and everything in between.
Jason Gorman (10:23)
Mm-hmm.
Dan (10:47)
And so I have this sort of weird eclectic kind of background, but it’s all focused in on education and specifically how we start literally at the very, very beginning and where exactly we end up in terms of the, you know, that our workforce as a whole. So it’s kind of a kind of a neat, neat, background. It’s fun.
Jason Gorman (11:06)
You know, I have not spent enough time with your LinkedIn profile because I was totally unaware that you were a school principal and a teacher. As many times as we’ve spoken, that has never come up. I did not know this about you. I’m so glad we’re having this conversation. And the last question that I have today, down the road when we’re getting close to being done,
The last person I interviewed, ⁓ his name is Tom Driscoll and he owns a company called EdTech Teacher. So he does teacher training, that’s his business. And I ask every guest to give me a question for the next guest. And so it’s kind of interesting. He gave you a question from very much a kind of a K12 frame, which is really his universe. Anyway, I’m looking forward to that. But let’s go, let’s move through this the way I had intended from the top.
Dan (11:35)
Yeah.
Jason Gorman (11:58)
This really is a show for people in the trenches in the learning professions. And when I say learning professions, I really mean this in a broad sense. It could be a teacher. It could be a university professor. It could be somebody in L &D. It could be somebody who’s creating…
programming for a nonprofit organization and they’re a team of one. There are so many, as you know, there are lots of permutations of what we do and I really want this to be for anybody in this universe.
And I say that because I kind of want this to be, it’s okay if we get a little nerdy and in the weeds. So I just wanted, it’s like a preamble for the question, which is for people like us, how do you describe what you do at Mission Fuel?
Dan (12:50)
For people like us, the nerdy people?
Jason Gorman (12:52)
For people
like us, yeah, what’s the nerdy version of what you do at Mission Fuel?
Dan (12:57)
Got it. So we
accelerate the process of e-learning development so much so that we have the ability to operate on a revenue share basis. And that’s really what we do. And we use artificial intelligence in order to make it happen. That’s sort of the more nerdy version ⁓ of it. I would also say that we as a profession, specifically that we as Mission Fuel are really out to be able to help
folks to be able to make this transition. ⁓ And not just in our world, not just in the L &D world, but as I said earlier, every profession is gonna be touched by the thing that we do. And so, or by AI, I should say. And so therefore, we have gotta be able to step into that in terms of re-skilling. And so we will be the agent that will allow for the opportunity for human beings to be able to make this transition when it comes to the AI revolution. It is here, it is fully upon us.
We’re seeing layoffs, know, like Amazon is an example, right and left that are occurring. And now we’ve got to be able to figure out how do we as L &D professionals step into that space and become the heroes of the day.
Jason Gorman (14:08)
Yeah, Amazon, what is the New York Times story? They’re gonna lay off half a million or they’re not going to hire half a million people. It’s like 75 % of their workforce ultimately is gonna be downsized. So.
Dan (14:14)
So right. Yeah.
That’s right.
That’s right. And they’ll just
slowly but surely do it based on attrition, right? They’ll just say, we just are going to just wait on hiring. We’ll just sort of fill the roles and everything else will be done. And then over the course of time, that 600,000 will eventually be zero, right? Or as minimal as possible.
Jason Gorman (14:25)
Yeah.
Yep.
Right.
So you said that what you’re doing is accelerating the work of learning design, what learning professionals do. Could you just kind of go a level deeper? Which of the things are being accelerated? What are the things you’re focused on?
Dan (14:56)
Yeah, I would say that everything we are doing is really about process and we think about how can we use AI first to be able to do this particular item. Now, I’m not saying that we’re eliminating human beings. That is not the case at all because we’re able to employ the same amount of human beings, but at the same time, we’re able to produce 10x more, which is really what the world needs right now. The world needs more of the
Jason Gorman (15:18)
Mm-hmm.
Dan (15:23)
the learning that allows for us to be able to be sort of super niche oriented, right? We now don’t have to be just focused on those big companies that can go out there and spend $20,000 on an in-learning module. Well, now the ticket size may be less, right? So let’s imagine that that same ticket size goes from 200,000 to 60,000, but now it’s that I can take that 60,000, I can do 10 of them. That’s gonna be one of the biggest differentiators. And for us,
Jason Gorman (15:37)
Yeah.
Mm-hmm.
Dan (15:50)
as we have driven down the cost of e-learning to the point where we can say, look, we’re willing to be able to take a risk on whether or not this thing is going to be able to be sold for a particular industry. It really makes sense to be able to do. It is hard. I’m going to tell you right now that all the AI tools are wonderful and they are good. There is a difference being able to use ChatGPT to be able to produce a storyboard or to be able to take a body of knowledge and put it into a GPT project.
Jason Gorman (16:05)
you
Dan (16:19)
and then turn out a storyboard or turn out a scoping sequence or any of that. There’s a wild difference between that and automation. And that, I think, is sort of a misnomer is that I think that with just generic sort of tools that we use, whether it’s gamma or 11 labs or whatever, you can generally speaking get it down to 60 or 70 hours of time per hour of e-learning that you can really get it down to and make it good. But then…
Jason Gorman (16:26)
Mm-hmm.
Mm-hmm.
Dan (16:48)
then it becomes harder. And I think that that’s gonna be the barrier for now that people will really struggle to be able to overcome. And eventually that will be overcome entirely, but at least for the time being, that’s where we are.
Jason Gorman (16:50)
Mm-hmm.
You mentioned that moment in November 2022, is that right? 2022. Chat GPT-3, I think it was, was released. This was the big public release. And you said a little bit about this, but I’d like to hear more because it sounds like you had a very immediate vision of what the future might slash will.
Dan (17:13)
yeah, that’s right.
Jason Gorman (17:35)
has looked like as soon as you saw it. And I’m curious, ⁓ could you talk more about what you saw just at first? What was the thing that you saw that really flipped that switch for you?
Dan (17:52)
Yeah, so that’s a great question. I don’t exactly remember the project that I was working on, but I happened to ask it ⁓ really about scope and sequencing. And I said, can you build me a scope and sequence? And then it did. And I thought, ⁓ And then I thought, okay, we’ll take these three learning objectives and build a scope and see it and then ⁓ build a storyboard for me. And then it did.
And I didn’t quite like it. And I said, well, can you revise it and then make it, you know, into like 30 slides rather than 20? And then it did. And I thought, ⁓ And then I said, OK, well, take this one slide and build a script from it. And then it did. And I thought, no. And then when I really started to get into it and I was like, OK, let’s go ahead and take this bit of bit of knowledge and then build me a storyboard based on the diagram that I give you. And it did it. And I thought.
no, Jason. I mean, literally my jaw is dropping and I thought, no, we are in such trouble. And because, you know, at the time I’m responsible for a team about this size ⁓ at Blue Sky. We’re similar in size now to what we were over at Blue Sky. so I think, holy cow, every job now is at stake on my team.
And we were already at the time using AI voiceover and we had already sort of gone down that road. So I had known a fair amount about kind of the AI space and I had been reading up on articles that there was stuff about to come out and all that sort of thing. But nothing prepared me for that moment when I thought, oh, no. Because then, but then I was at the same time, I was excited about it. I like, you got to be kidding me. This is so cool. We can go ahead and then we can use this.
to be able to then build the voiceover and it shrinks up our time of production. And I can still charge the same amount, right? What I didn’t anticipate was how quickly this has occurred, Jason. mean, when you think about your own team and what do you see as being the biggest change that you’ve seen over the course of the last, even six months to a year that has occurred that you’re like, my gosh, I never thought that would happen when it comes to AI.
Jason Gorman (19:46)
Mm-hmm.
Yeah.
The biggest thing. I would say I’m most.
Once I understood what CHAT GPT did, and like you, for me, I had to get my hands on it, and I think that, ⁓ I think you and I had similar pasts. Look, I came up doing things. I was making things, I was building courses. You’ve done that work. So we both have been in the trenches making stuff.
I think as I matured in my career, there were lots of technologies that I didn’t really have to use to understand. Somebody could just describe what it does and I understood. It made sense inside my framework of how technologies work. But that is just not the case with AI. mean, until I really, really started using it, which is exactly what you described a minute ago, you asked it to do this thing. It blew you away. You asked it to do the next thing.
Until you really do that for your own use case, it’s really quite hard to understand what it’s capable of and what the potential is. I think everybody’s had that experience now. ⁓ A year ago, I’m not sure a lot of people had, but I think now most people have. ⁓ So I guess I’m not so surprised when it has come to text generation. I feel like I have anticipated those things, or I did early.
The things to me that have been quite shocking have been the very rapid developments in ⁓ in audio and video. It’s just happened really, really fast. The video models were so terrible just two years ago. I mean, really laughable, laughable, bad. And now they’re really good. And now my, you know, I’ll come home and my kid will be like, here’s this funny thing on TikTok. I’m like, that looks very real.
And I can just because of this one little pixelated thing that’s happening here, I can tell that it isn’t. And this is going to be true for the next month. And then we’re never going to be able to figure it out again. I just didn’t think we would get to this place this fast. So to me, the video is the one that’s really blown me away.
Dan (21:59)
That’s right.
I would agree with you on that. And I think that especially in the next few years, it’s going to be incredibly difficult to be able to discern what is real and what is not. And ⁓ the notion of deep fakes or any of that kind of piece will absolutely come out. And so I was watching a video by Gary Vaynerchuk and he said, in the next five years, there will be more video of me that is not real than real.
And he’s like, I’m all over the place, right? I’m all over the place. And he said, it’s already that way now, right? There’s so many videos of him that are not real, but still, it’s just incredible. And I think that the ability to be able to produce content in that fashion will either A, drive us to it or B, drive it away from us or it will increase the silo that we’re currently in, It’s sort of like screaming into the well.
Jason Gorman (22:35)
That’s really true. He’s all over the place. Yeah.
Dan (23:01)
and the algorithm will just simply continue to be able to feed us because ultimately it will be literally just in time learning that we will do in just in time video as an example. There was a group that won this award and I want to see it was from Google and there was like 400 projects that they assessed. And one of those projects that won was two people watched the same video at the same time. But because of their emotional reaction to the video, it presented them two separate items.
Jason Gorman (23:12)
Yeah.
my.
Dan (23:32)
but they didn’t know it. Like they could not tell that it was two separate videos, right? So imagine you’re watching this same video, but you’re having the two wildly different experiences. That’s where we’re going. Have you been to, I think it was in, I want to say it was not Dallas. I can’t remember, was walking down an airport once and they have this big screen that’s up on the deal and it’s like, want to know where your airline is? And I was like, oh yeah, so I walk on over there and I’m like.
How does this work? And he’s like, well, show me your pass. I said, okay. He’s look up and it tells you what it is. And then he says, ask that person if they can see it. And then they look up and they can’t see it. I’m like, how did you do that? Yeah, it was just unreal. It’s just unreal. So that’s the sort of thing that I think is just uncanny. And I think about the world like there’s a tool called soul machines.
Jason Gorman (24:10)
What? my God.
Dan (24:22)
that terrible name, but really kind of a crazy, crazy tool. And it has the ability to see you. And of course you can speak to it. And it’s basically a video-based chatbot. Very cool. And yet at the same time, it’s like, well, what happens to all those customer service folks? you know, I, yeah, it’s, yeah, another story, I guess. Yeah.
Jason Gorman (24:42)
Yeah. Well, there’s,
I mean, I think there’s just for me, as you were going through your answer, there’s a whole stripe of really giant unanswered governance and ethics questions. Right, if so, the machines can read how we’re feeling. There is a giant opportunity for us to be taken advantage of.
and manipulated and led into places that we never intended to go. And I ⁓ think we should all take that really seriously. And to bring it back to the learning professions, I think this is one of our critical roles going forward. I don’t know how you feel about this, but I really feel like for a long time, we’ve had to sit down with clients and say, OK, you’re telling me you want to do this. I’m not sure that’s a good idea.
Right? Why don’t we do it maybe a little differently? Because it could have these privacy implications. It could have these… This is a little bit of a dark pattern, or it could be something that isn’t quite serving learners in the way that we’d like to. We’ve always kind of been in that seat. I think that role gets more important going forward. And I don’t know, as you’ve been doing your work, how do you think about…
safety and risk and governance with the tools that you’re creating.
Dan (26:07)
I’m so glad that you said that because I do a fair amount of keynoting around the country and I’ll present probably 40 times this year. And one of the slides that I happen to have on my presentation says the following thing. It says, ⁓ I’m the guy who’s going to show you how. I am not the guy who tells you that you should. Right? So there’s a difference between how and should.
Jason Gorman (26:28)
Hmm.
Dan (26:31)
And I think it’s super important that people understand that just because you can do something doesn’t mean that you should do it. And so as an example of that, ⁓ this is simple example, is that I use this tool called FOTOR to go ahead and to basically make headshots of groups. So FOTOR is F-O-T-O-R, if everyone checked it out. Very cool, has a really neat headshot feature, basically, and it can align headshots together. So everybody basically looks the same. Well, I can.
go out to their social media posts without them aware, grab it, download it, reproduce it, put it in there, right? I can’t do that. Should I is the question. And I think that by all rights, that’s not right. That’s not right to be able to go out there and to be able to take that image without their knowing and so on. Now that being said, I think ⁓ that we’ve got to make sure that even the most basic example like that, that we do keep in mind that the still has got to be an ethical conversation.
And at the same time, have a federal government that says that it’s going to be unlimited, right? We are not going to put the brakes on AI at all because basically we are in an AI defense race. subsequently, we’re not going to put the brakes on. And so now we’re running into the piece of, well, what about copyright? Well, fortunately, when I take a look at something like a chat TV team, it’s pretty good in respect to its ability to be able to take content and turn it into other content. But where I really struggle is I’m like,
Jason Gorman (27:56)
Mm-hmm.
Dan (27:58)
Okay, people go take a book that’s currently in publication that is not theirs. And then they go ahead and then they upload that digital book to be able to make it a part of their proprietary piece. And then they reproduce something from that. That just doesn’t seem fair to me. so, yeah, that’s the part that I struggle with ⁓ a bunch is, you know, where do we kind of draw the line when it comes to IP? And there’s not a great answer that’s right now about it.
Jason Gorman (28:04)
Yeah.
No, without attribution. Yeah.
Dan (28:26)
And I just think that any, especially from a federal government standpoint, there’s no breaks that are gonna be put on it. ⁓ Because number one, you couldn’t keep up. By the time you and I get them debating whether or not we should or how we should be able to do it, it’s over. The next thing has already come along and broken through that barrier.
Jason Gorman (28:49)
so next question is you are involved in a lot of things and you’ve been solving problems as we all do when we run a business. ⁓ What is the big thing that you’re working on now? What’s the, like, what’s one thing that you’re trying to do better right now?
Dan (29:07)
⁓ wow, that’s a great question. I would say that we are number one, just simply refining our processes. ⁓ We have a stellar team that I think is refining that to the nth degree. While most tools will sort of get us 80 % of the way there, we are trying to be able to figure out how to take that 80 % and make it 90 and then that 90 to 99 and then eventually to 100%. I think that that’s one thing that we’re definitely working on.
Jason Gorman (29:14)
Hmm.
Dan (29:37)
I think the other thing that we’re working on is integrations between systems. Is that, is the L and D systems were not built to be able to talk to one another. So Storyline does not talk directly to a learning management system, right? But what if we had that ability to be able to have a Storyline like tool that then had the ability to connect with others? Or maybe with Storyline itself that had that ability? I don’t know.
point being is that the ability to have tools that talk to one another, I think would be absolutely critical to be able to have. I think in addition to that is the notion of just-in-time learning, I think is something that I would really like to be able to figure out a way to solve. So, for example, we go out there and we make an update to a ⁓ particular document, internal, and then we turn around and we take that document and it automatically then updates a piece of learning.
Jason Gorman (30:17)
Mm-hmm.
Dan (30:28)
And so, and I think that that would be sort of like this incredible panacea what’s possible when it comes to e-learning and really where we’re headed is as a whole. I think the other part that’s really fascinating is when we take a person like, you take me, I’ve been involved in L &D for a long, time, and that learning needs to be directed to me in a different fashion than somebody who’s brand new, right? But right now, it’s static and it’s all the same.
Jason Gorman (30:51)
Hmm.
Dan (30:57)
Or what if we had the ability to not do it that way? That instead, we could literally build it based on your profile. We know that you likely have this background and I could predict these are the five things that you need. These are the five things that Dan needs. Let’s go ahead and build the learning right then and there that’s going to be delivered to you. That would be cool. Those are the sort of big things that we’re trying to figure out how to solve.
Jason Gorman (31:17)
That’s really interesting. And it actually brings to mind two other conversations I’ve had on this podcast. ⁓ One’s with Brick Maier He ⁓ is a director of learning design. I don’t remember his exact title, but for a company that’s involved that’s in the clean energy space, it’s a workforce training organization. And the other is the person I mentioned before, Tom Driscoll.
One of things ⁓ that came up in both of those conversations was this idea that the things that we’re delivering are going to be part of a larger experience that the learner’s having. So the question that I asked to Tom, I think, was something along the lines of ⁓ something about personalized learning and should all learning be personalized? And he really…
chafed at that question. I was quite surprised because he said, he said, it’s fine. There’s a place for that. But learning’s very social. We need like a week. He said, I’m really worried about a situation in which we are sticking people in, in, in a one-on-one relationship with a machine. And they’re, they’re just getting their personalization from the machine. When
we should be taking advantage of the rich opportunities students should have to work with each other and to be interacting with their teacher. So I’m curious how you are, I suppose, how are you thinking about where a solution like that that is a just-in-time tool
How do you think, what is that, if you just think about like the future, a future workforce environment, right, where some people have to do continuous on-the-job learning, what is the bigger picture where that solution fits?
Dan (33:19)
So that’s a great question. So here’s my notion about teachers is that the number one job of a teacher is to be able to meet the student where they are. And so if that’s the case, AI can do that better than most teachers can typically in terms of academic oriented items. Now, we also can, of course, now include social emotional pieces in there as well.
Jason Gorman (33:28)
Mm-hmm.
Dan (33:45)
I’m not saying that we should go out there and replace teachers. I do believe that we have the ability to be able to use AI to be able to augment learning in a way that we could have never have done before because we can identify gaps that we could have have found before. We can ⁓ identify talents that we could have never have found before because of the use of AI allows for us to be able to do it.
when it comes to the workforce side, it’s very similar, Jason. So essentially I’ve got my, let’s imagine that just have the warehouse, right? So I’ve got the Amazon warehouse and here I am. I need to be able to know how to do a specific thing and I can go ahead and I get stalled, right? I’m there for a minute. I’m trying to be able to figure it out. And then the next thing you know, it actually pops up and it says, hey, you’ve got, it seems like you’re struggling with how to do this. Would you like a video on how to do it? I mean, we can get down to that level of things.
Jason Gorman (34:19)
Mm-hmm.
Dan (34:39)
which is pretty remarkable. It allows for us to be more efficient, allows for us to be more effective, and ultimately it allows for us to be able to focus on the things that allow for us to be great. Because we as human beings, when we think about sort of like Maslow’s hierarchy of means, mean, ultimately our basic means are met for the most part, right? And now this allows for us to be able to have the space necessary to allow for us to truly think, like to truly become to a degree self-actualized in a way
we could have never have imagined before. People say that I’m a tech optimist and I would say that I am a tech optimist. And part of that reason is because this leap that we’re about to take is going to be incredibly difficult because of the speed that it’s going to happen. If this happened over 50 years, it’d be a totally different story. But we’re talking about five, 10 years. That’s what’s gonna make it difficult. But on the other end of this, I do believe that we have the ability now to be able to provide
for each other and provide to be able to serve ourselves in a way that we could never have possibly imagined ⁓ because of artificial intelligence.
Jason Gorman (35:48)
Well, the other end, how far away do you think the other end is?
Dan (35:52)
This is a good question. ⁓ I have no idea. I think that this is going so incredibly quickly. When AI ⁓ originally came out, when ChatGPT originally came out, they thought that AGI, artificial general intelligence, was approximately 30 years away. Now they’re saying it’s five. Because remember, you’ve now unleashed a tool to seven billion people, all that have cell phones.
Right? And so you’ve released the most powerful tool on top of the most powerful tool in human history. And no wonder it’s evolving the way that it is. Because now everybody now has access to a tool that is limitless that we never thought in a million years could be. So for me, Jason, I think that I don’t know the answer. Like I literally read an article this morning that IBM came out with a, it has a new team basically called the AGI team.
Jason Gorman (36:26)
Mm-hmm.
Dan (36:49)
And their whole job is to effectively go through and figure out how to be able to make AGI work, right? And to be able to identify when it occurs. And so this is the time when we’re talking about now that artificial intelligence is smarter than any human. And we’re assembling a team around this so you know it’s close. And then when we get to artificial super intelligence and we have one machine basically that’s smarter than all of people on planet Earth combined.
Then what? You know, it will eliminate the vast majority of white-collar jobs. So where do we go? That’s a great question, and I don’t have an answer.
Jason Gorman (37:26)
I don’t want to scare anybody listening to this, but.
If you want the scary version of this vision, did you read the ⁓ Project 2027 paper that came out a couple months ago? So there are these AI researchers that had worked inside major open AI or similar AI.
Dan (37:37)
No, I read this, no.
Jason Gorman (37:47)
and they use the best available research to project out possible futures, near-term futures with AI. I think they’re a little, 2027’s a little early for some of the things they’re predicting, but they give you like two alternate futures. One works out pretty well, the other one not so much. And I think…
Dan (38:07)
Yes.
Jason Gorman (38:14)
I don’t know that I buy those two as the, you know, like we’re locked into one of those futures. But to me, it helped me understand the potential perils of a super intelligence. I think anybody who’s listening, if you wanna, it reads like sci-fi. It’s actually quite, it’s quite compelling and interesting. It’s a good read, but it’s a little scary. And I think everything you just described is, could be closer than we think.
we might not even know when it happens and when we cross the threshold. And when it does happen, it could be orders of magnitude smarter than we are. And that is its own pickle. And I would say maybe ⁓ a topic too big for this show. ⁓
Dan (39:02)
Well, I’m happy to imagine. But I see that there’s a video,
I know the book you’re talking about, there’s a video that does the same thing. It basically describes that piece, and you’re right, the one ending, not so great. ⁓ But yeah, and I think that, you know, now that we’re heading into this new robotics era, if you’ve been keeping up ⁓ with the robotics piece, is that China is producing hundreds of thousands of robots, and we’re not quite keeping pace around that.
Jason Gorman (39:23)
Yeah, I have.
Dan (39:31)
But in addition to that, robots are very close to being able to build other robots. So now you combine artificial intelligence along with that ability to have robots and driving down the cost of production of those same robots. we’re at 600. I think it’s like $1,600 is like an entry level robot. That’s affordable for most families, right? And that is the most basic of models now that’s pretty adept and pretty capable. Where does this go?
Jason Gorman (39:51)
Yeah.
Dan (39:59)
Where does it go? think that Elon Musk predicted that there will be 10 billion robots on the planet in the next, I think, I want to see it’s the next five years. Maybe it’s 10 years. It’s 10 billion. More robots than people.
Jason Gorman (40:08)
What? ⁓ my God.
More robots than people. Holy smokes. All right. Well, I’m going to get to my last question. This has been, we keep going, but I’ll get to my last question here. This is from Tom Driscoll. So again, he runs EdTech Teacher. And here’s his question. And I think you could answer, and maybe you want to answer this twice, maybe one with your K-12 hat on and one with your workplace learning mission fuel hat on. So here’s the question.
Now that AI tools are so pervasive and useful, how has that changed the nature of the interaction with the learner? Has it enhanced or changed the learner experience?
Dan (40:52)
Great question. think it’s both. I think it’s enhanced and it’s hurt at the very same time. I think without intelligent, really thoughtful approaches, AI becomes the crutch that people rely on and then they end up with words like delve 45 times in an e-learning, but it doesn’t help anyone, right? The human still must be in the loop. You still need to rely on subject matter experts to be able to determine is the learning valid or not.
Jason Gorman (41:10)
Yeah.
Dan (41:21)
You cannot remove the human from human learning. I think that that’s number one thing. So we can never sacrifice efficiency for effectiveness. And I think that that’s part of it. On the same vein, when I have the ability to create a tool in a simple chatbot that we can produce for $20 a month, then we can supply to learners that are preparing for an exam.
Jason Gorman (41:40)
Mm-hmm.
Dan (41:47)
that in a really simple way to basically provide them all the domains, all the questions, all of the, it have it do that. yeah, now all of a sudden everybody has in the palm of their hand, the Princeton Review. So in that way for me, I think about like the acceleration of the dramatic acceleration of e-learning or of learning of human beings on the planet. I don’t believe that it is dumbing down the planet. I think it’s the opposite of that.
Jason Gorman (42:00)
Mm-hmm.
Mm.
Dan (42:16)
because now
we have the ability to truly have access to learning in a way that I never could have imagined before. If I want to learn coding, I can’t. And if I want to be able to learn about instructional design, I can’t. And if I want to be able to know about some other crazy printing press thing, I can’t. And so now, truly, the options are limitless in a way that we never could have possibly imagined, even just three years ago.
Jason Gorman (42:32)
Yeah.
Dan (42:42)
And so when I think about this notion of that we’re gonna lose jobs, make jobs, to have jobs be the same, I think it’s gonna be hard for a while here as we make this transition. But as we do, there’ll be basically the great layoff or ⁓ the great displacement, right? There’ll be the great displacement that’s gonna occur. But then as we go, there’ll be this great reskilling that’s gonna occur. And when that great reskilling happens, then we will officially sort of make this transition.
Jason Gorman (43:01)
Mm-hmm.
Dan (43:11)
Bring it all back to L &D. That’s the reason why we exist. We exist to be able to help those folks figure out a way to be able to make this transition. I firmly believe we have the most important job on the planet right now. We were built for this moment and we need to able to figure out how to be able to help others to be able to make this transition. We know how to make great e-learning. They need that e-learning. Our job is to make the most effective use of the tools that are available and AI is the best one out on the market right now.
Jason Gorman (43:15)
Mm-hmm.
You just said something that I haven’t heard anybody say in our industry yet, which is we have the most important job in the world right now. It’s very interesting. That’s the soundbite for this episode, clearly, but I appreciate the frame of the criticality of learning. Obviously, this is just a central.
Dan (43:48)
We do.
Bye.
Jason Gorman (44:08)
part of what it has always meant to be a human being. But given the context of where we are and how the world is changing, it’s hard to disagree that it’s in the conversation as the most important job. So thank you for saying that.
Dan (44:26)
Yeah, so I had a school principal who was a mentor of mine who I loved and she used to say that one bad teacher is worse than a brain surgeon, one bad brain surgeon. And she said the reason for that is because one bad brain surgeon destroys one brain at a time, whereas one bad teacher destroys 30 at a time or 150 at a time. We as L &D professionals, we have the ability to serve
thousands and thousands of people. think about all the e-learning that we do. is in front of tens of thousands of people every single day. We have the power to be able to make an impact that no one else on the planet has because we understand how to be able to develop e-learning and deliver it in a way that allows for people to be able to grow and to be successful.
Jason Gorman (45:02)
Yes.
There is literally no better way to end this episode. So we’re just gonna stop here. Thank you so, so much for doing this. I really appreciate it, Dan.
Dan (45:26)
Jason, anytime, and I feel like I spoke a lot. Next time I’m asking you the questions.
Jason Gorman (45:30)
All right. All right. It’s a deal.
Dan (45:33)
Thank you.