In our latest episode of The Learning Experience Ops Show, Jason met with Zach Wagner, Founder & CEO of BritghtWay AI, an organization that provides AI implementation, training, and support services to help organizations integrate AI into their operations. Zach, a longtime leader in edtech innovation, has spent his career at the intersection of teaching, technology, and human potential.
He joined us to talk about why the next era of education and operations will not be defined by the tools themselves, but by how people learn to adapt, integrate, and think differently about their roles.
Below is the story that emerged from that conversation: a narrative about origins, motivation, responsibility, and what it means to lead in a time when the work itself keeps shifting beneath our feet.
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Where Purpose Begins
Zach’s career roots trace back to a City Year placement in North Philadelphia, where he worked in a seventh-grade special education classroom. It was one of the only rooms with computers, which gave him an early glimpse into how the right tools can change outcomes.
“I saw firsthand just how well designed programs, curriculum, and instruction could really up level students that came in really struggling,” he told us.
That experience, paired with his time at Harvard’s Graduate School of Education, set the course for roles building formative assessment tools, designing critical-skills programs at Everfi, and restructuring access pathways at StraighterLine. Across each chapter, the motivator was consistent: connect thoughtful pedagogy with effective technology in ways that genuinely help learners.
Why AI Needs Intention, Not Assumptions
BrightWay exists because AI adoption is rarely as simple as it seems. Organizations see impressive demos from consumer tools but struggle to translate that performance into their own workflows.
“It is a brain, but it requires the right input to produce the output that is most effective and tailored to your context,” Zach explained.
Two needs come up repeatedly:
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- Tailoring AI to the organization without exposing sensitive data
- Amplifying—not replacing—people, so individual breakthroughs become shared capabilities
Most teams aren’t trying to cut staff. They want more leverage, more consistency, and more operational impact.
For Zach, AI is not about automation for its own sake. It is about enabling people to do more of the work that actually drives value.
Start Simple, Scale Fast
A core BrightWay principle is “start simple, scale fast.” Many AI pilots fail because they aim too broadly or skip foundational alignment.
Zach recommends isolating a single low-value, repetitive step in a workflow, creating a quick win, and expanding incrementally. In content development, for example, a 20-step process becomes manageable when you address one slice at a time.
Just as important is bringing the right people into the process.
Executives define value, managers enable adoption, and frontline contributors must feel included rather than threatened.
Zach put it plainly: AI transformation succeeds when organizations “involve everybody at the right level” and treat change management as essential, not optional.
The Work Shifts, and So Must Roles
AI reduces some work but introduces new responsibilities: maintaining systems, evaluating outputs, staying aware of emerging tools, and adjusting processes over time.
“The work is different,” Zach said. “You’re not going to be working in the same way you were working five years ago.”
Some roles will require deeper comfort with data. Others will require strong editorial instincts to refine AI outputs or debug prompts. And in a twist, people with humanities backgrounds may thrive because precision in language has become a technical skill.
“The output is only as good as the input,” he reminded us.
Adaptability is no longer a bonus, it is the job.
What Organizations Should Build Now
When asked what companies should prioritize today to stay competitive in the next few years, Zach didn’t recommend a single tool. He recommended a capability.
He believes organizations need someone responsible for surfacing, evaluating, and filtering the overwhelming number of new AI tools. With tens of thousands of products built on a few core models, discernment—not procurement—is becoming a strategic advantage.
As Zach put it, the challenge is answering the question “how do you stitch it all together?” and avoid chasing hype.
How AI Will Change Learning
In response to a question from our previous guest about how AI might fundamentally change student learning, Zach linked the shift to mindset.
“We’ll know when students aren’t leaving school with a single track in their mind,” he said, “but are leaving with a flexible mindset.”
For him, the true sign of progress is not widespread AI usage in classrooms, but learners who can adapt quickly, integrate ideas across domains, and treat technology as a tool rather than a crutch.
Learning, in other words, becomes preparation for a world full of unknowns.
A Closing Reflection
Zach’s message is clear: AI itself is not the transformation. The transformation comes from how people and teams adapt, reorganize, and rethink their work.
BrightWay is built on that belief, and so is Zach’s career. Technology will keep evolving, but the organizations that thrive will be those that stay curious, communicate openly, and approach change with intention rather than fear.
The future belongs to teams ready to build for what does not yet exist.
Listen to the full conversation with Zach Wagner on The LX Ops Show or wherever you listen to podcasts.
Podcast Transcript– Jason Gorman with Zach Wagner
Jason Gorman (00:01)
I have known Zach for a long time, going back to our days in EdTech Publishing. And I’m really happy to have him on the show. Over the past 15 years, Zach has been a driving force in educational technology. He’s been leading product innovation at ⁓ places like Everfi, StraderLine, and other companies that have just shaped how millions of students learn across K-12, higher education, and workforce development.
Today, Zach runs Brightway, where he helps mission-driven organizations harness AI to scale their impact, streamline ops, and help stay ahead in a rapidly changing world. Welcome to the Learning Experience Operations Show, Zach.
Zach Wagner (00:43)
Thanks, Jason. So happy to be on the show.
Jason Gorman (00:46)
So glad you’re here. Okay. So before we even hear about what you do, I’m really curious about what got you going? What ignited your interest to do the work, to be in education to begin with?
Zach Wagner (01:00)
Yeah, mean, it really goes back, I think, to my childhood. My grandfather was a counselor in the Philadelphia schools, and I would hear stories about that growing up. I had a lot of other family members in education. And when I was leaving college and thinking about what I wanted to do, I kind of knew that education was a space that I wanted to be in. I didn’t know what I wanted to do within it or how I wanted to really
⁓ you know, make my mark there, but I started in a program city year, is AmeriCorps program at the time. And we did tutoring and mentoring and, you know, volunteering within schools. And I was in a school in North Philadelphia where I had the, had the privilege of really, seeing firsthand just how.
Technology at that point was starting to really make an impact in the classroom in instruction and in pedagogy. I was in a special education classroom, seventh grade class. And it was one of the few classrooms actually that had access to technology, had access to computers, which is a whole different story. This is a low moderate income ⁓ school in a low moderate income community. Since then, obviously more and more schools have
gotten access to technology, but at the time I was in one of the pioneering classrooms, which was an incredible experience because I saw firsthand at that point just how well designed programs, how well designed curriculum, how well designed instruction could really up level students that came in really struggling. And I got to see just how technology could be used.
in pairing with great teaching to really individualize learning. So that kind of, you know, got me really interested in pursuing just this intersection of technology and education. You I was, you grew up as a tinker and as someone that really loved kind of experimenting and, you know, being a first adopter of the new tools and seeing what I could do with them and combine that with my love for education.
that brought me to the Harvard School of Education where I focused in technology, innovation, education. Got really kind of the hands-on, how do you actually build, also how do you design and think about the actual science behind teaching and learning. So great program, catapulted me to where you and I met at Six Rided Marbles, where I was, you know,
Jack of all trades that a lot of everything, not nearly as well as you did anything, but I was project managing and doing learning design and operations from soup to nuts. Just got my hands on a lot of different projects and was able to see a lot of different manifestations of curriculum design as we worked with all these big publishers. And then from there, I joined a small startup after that.
Jason Gorman (03:33)
Yeah.
Zach Wagner (03:56)
where I was, you know, had the ability to help build a formative assessment tool. This was in 2010 or so when mobile technology was first kind of coming onto the scene in classrooms. And we had a quick polling formative assessment tool, so called Socrative, which was able to be used and scaled in some 60,000 classrooms across the country. And
Yeah, from there, and just a long story I realized, but it gets me to where I am here.
So from Socrative, I joined Everfi and there I really was able to, you know, had the privilege of working on these programs that taught students about the critical skills that you just don’t get covered in many classrooms, social, emotional learning, financial literacy, digital wellness, very timely topics at the time and still are. And, you know, I was able to really see
just how when a program is well designed and when you really focus on the areas that students just don’t get in their day to day, you can really spark excitement and interest that isn’t just usually untapped. And so that was where I spent most of my career, most of my journey really kind of working on partnerships that
brought these critical topics and critical skills to schools across the country. And yeah, from there, I was then the Chief Product Officer at Stradiline, where I helped to really ⁓ overhaul the way that they brought higher education content to students that needed affordable alternative pathways to higher education. So, the arc of my career has really been in education and technology in that intersection and really in the kind of
finding the force multiplying connections between these two things that then brought me to starting Brightway.
Most recently, I’ve really been interested in AI, as everyone is, and see that as another one of those, you know, nexus points that I saw back when I started out in education in the classroom, when, you know, new
software was coming on the scene and when mobile technology was coming on the scene. now I see AI as the next lever to really bring education to a much more personalized, individualized, and hopefully impactful place.
Jason Gorman (06:27)
And I know you’re really choosing your work now. So why is it you are doing what you’re doing now? Maybe you can talk a little bit about, would love to hear about your company, would love to hear about who you’re working with, what you’re doing, but why? Why are you doing this? What feels important about it right now?
Zach Wagner (06:42)
Yeah. So I think everyone at this point more or less recognizes that AI is both here to stay and is
There’s a lot of potential for what it can do both good and bad Where I think companies and people are still struggling is just how to do that. Like how do you use AI? Effectively, how do you use it to to really? make
Yeah, make better products, make more, make, make. Yeah, how do you use AI to make better products? I use AI to get them get more out of your your company, your team, your your learners. And. You know, I think it’s a space where, like, there’s a lot of. Like both naval gazing people thinking, we can use it for X, Y and Z.
but then a lot of also kind of like hands flailing as you try it out and then discover it’s not doing exactly what you think it should be doing or, you know, it’s not making the difference that you want it to make. And I think this is most applicable for the companies that often can’t afford also like the, you know, having specialists on their team or in their organizations to really
be the AI experts to really kind of up level their business to get all of the like promised gains of AI out of it, right? And me, know, coming from mission-minded companies and working in nonprofits and really caring a lot about, you know, what I’m producing and what we’re kind of bringing to the world. I thought this is an area where, you know, I could,
add some fuel to companies that really need it, right? That are struggling with how to really implement AI in a way that’s going to be meaningful and helpful and effective for them. So yeah, I mean, what really brought me to this place, I think is just the recognition that AI is here to stay. A lot of companies want to use it and want to realize the gains that have been promised by it.
but don’t have the know-how or the expertise to do that. And I don’t want them to be like victims to the competitive winds because everyone is going to be leveraging AI to move faster, to sell more, to do more.
Jason Gorman (08:59)
Hmm.
Zach Wagner (09:07)
The companies that are going to struggle here are also the ones that need more than any other to know how to implement AI effectively.
Jason Gorman (09:17)
And I imagine you’re probably talking to lots of different organizations. Are there themes, I mean, if you could just identify the top one or two things that you have heard from the organizations you work with about the kinds of things that they feel that they need and can’t do themselves, really need help with, what are those things?
Zach Wagner (09:38)
I think the interesting thing with AI is ChatGBD came out, everyone started using it, and it was kind of a consumer product before anything else. And because of that, people saw this magic box in a way, right? Enter in a prompt and you get a whole essay coming out of it and…
you automatically, I think, go to, OK, I can use this in my business for X, Y, and Z thing. But then once you actually start using it in your context, you discover pretty quickly that it’s not as easy as that, right? Like it’s a brain, but it requires the right input to really produce the output that is most effective and most tailored to your organization, to your context. So what I see, I
a lot of companies still struggling with is how do we make this really tailored to my company? How do we make this tailored to my context without giving away all of our data for training the models? So I think the biggest thing is just tailoring the models that exist that everyone’s using to your company’s context and the knowledge base within your organization.
And then secondarily, I think it’s a matter of not replacing people at all. I don’t, most companies I talk to and people I talk to, they don’t want to replace their team. They don’t want to replace their workers, but they certainly want the leverage of AI. They want to, you know, harvest the gains that an individual is making across their entire team and across their entire company. So I think those are the two main themes that come up, up again and again. Like one, how do I,
make this tailored to my organization and to how do I get the leverage for my team from it.
Jason Gorman (11:31)
So when an organization identifies a new place where they can use AI, where they can put in an automation, what does the path look like from Joey has an idea to it’s on the sprint board, and they’re actually really, really building it, or you’re building it with them? I mean, who?
Who’s involved in that process? Who gets to say yes? Who needs to weigh in? Who gets to say no?
Zach Wagner (12:03)
Yeah, great question. A lot of nuance there and depends a lot on the specific use case. So just to kind of take it at a high level, know, from the jump, we help organizations with their kind of initial audit. Like you have to you have to have a goal in mind and you have to have a
the business value in mind to begin with, right? You can’t just come in there, come in and say, we’re gonna use AI to, you know, automate all of our communication to our entire, you know, our entire list serve of customers. Like that’s too big a problem, right? You have to break it down into something that is more manageable and still, you know, high leverage.
And by that, mean, where we often help companies and individuals is to say, okay, back up. Let’s first define where you think the business value is for AI. And from there, let’s break this down a little bit more to the component parts of that thing. One of the kind of core principles of Brightway is, you know, start simple, scale fast. And by that we mean.
find the most narrow use case that you really can quickly establish a win and quickly start to see the benefits of AI in one part of the maybe massive workflow. And then from there kind of scale to other parts until you take over the whole system, you have a really well-integrated system that combines
humans with AI both serving their purpose. The people to involve, know, the stakeholders are up and down the chain. I think the other misconception or maybe one of the reasons why you see headlines about AI pilots failing and all this wasted time and money in AI that’s not realizing results is because
In a lot of cases, think organizations are still approaching this in a really siloed way. And they’re just taking, know, these, these they’re, you know, they’re conducting these pilots or these experiments in really kind of narrow pockets of the organization without involving all the other people and all the other stakeholders. So the change management pieces is critical in this, right? You have to involve your executive team. They have to be aligned to.
the business value that you are targeting. They have to be the ones that agree to, yes, this being a really important thing that we’re going to leverage AI for. You have to obviously involve the management team because they’re the ones that are going to ultimately be communicating and helping drive the adoption of the tools and of the processes that you’re changing. And then of course, you need the frontline
team and the contributors who are understandably guarded at times. They don’t want this thing to come in that is going to replace them. And you have to really be mindful of the hesitancies there and constantly communicate and truthfully communicate that this is not about replacement. This is about how do you just get more out of
Jason Gorman (15:31)
Hmm.
Zach Wagner (15:35)
your day to day, like how do you free up your time that is going towards otherwise maybe repetitive things to go towards more high value things for the organization. you know, I think the principles are always like start simple, scale fast, involve everybody at the right level, and really make sure that you are incorporating that change management piece into the process.
Jason Gorman (16:03)
I love that you’re talking about communication and culture and starting small. And ⁓ there has been some really interesting literature recently about this. And I think it’s also kind of confusing because there’s a lot of fear about AI taking people’s jobs and what it means for the future of work in general. But once you get something,
going. So once you have a pilot, the pilot is going well, you do have that buy-in. How does a pilot graduate into a durable workflow that just is now part of the organization going forward?
Zach Wagner (16:45)
this is going to sound intuitive and obvious, but it’s really one step at a time, right? I think the critical thing is…
I let’s imagine a content production workflow and the steps throughout that are going to be the research behind the research of the topics that you want to produce content for, the defining of the objectives, the scoping and sequence of all those topics and lessons from start to finish, then the actual content production.
the reviews, the handoffs from one person to the next. So that could be a 20 step workflow that you could map out. And really, what I kind of remind people always is, let’s start with just like a sliver of this workflow. The thing that is the most repetitive and the least valuable piece of it that
we can offload to the technology. And once you have that in place, like let’s not just set it and forget it. Let’s actually benchmark what things look like before and what things look like after. And let’s continue to incorporate our technology and integrate the AI at this step until we feel we’re at a place that it is fully
fully on, right? We’re only using AI for this thing that we said we would only use AI for. And then from there, you can look back at that process from start to finish and identify the other nodes along it where there’s another opportunity for AI to kind of help speed things up, make things more efficient, take some of the responsibility off of the team that could go towards higher value work.
Jason Gorman (18:37)
So this is interesting. think there’s a little bit of a trade-off that’s kind of embedded in your answer there. So on the one hand, there’s time savings of AI. On the other hand, you are introducing into your organization, as I understand what you’re saying correctly. You are introducing a new stream of work which is maintaining the system that you’ve built and continuing to evolve it. And I think about this all the time.
Zach Wagner (18:57)
Yeah.
Jason Gorman (19:04)
I think in my work, I think about what are the trade-offs from of the things that I know how to do that I can do that now AI is helping out with. But that doesn’t come at no expense, mostly in time. Certainly it can happen, there’s money, but it’s time. The time to keep up with what’s possible in the tools, to maintain the tools, to make sure that they’re
Zach Wagner (19:17)
Great. Yeah.
Jason Gorman (19:28)
operating at the level of quality that you want them to. What are the trade-offs that you see? mean, how do you advise your clients about how to manage those trade-offs and to anticipate that there are trade-offs? It’s not just like sprinkling fairy dust over the problem. The problem disappears. It’s just now the work is a little different, hopefully more efficient, but different.
Zach Wagner (19:44)
Yeah. Right.
Yeah.
Yeah, I mean, I think.
The main thing is remind, the work is different, right? I think the thing that we all have to kind of come to terms with and that is still like shaking out is just how different is the work going to be, right? So for anyone that I’m working with, I do come in here, for anyone I’m working with, do…
Jason Gorman (19:59)
Mm-hmm.
Zach Wagner (20:16)
come with the expectation that they’re willing to change the roles a bit, right? They’re willing to adapt to the technology because if you’re not, then you’re just trying to plug a new light bulb in an old grid.
Jason Gorman (20:22)
Yeah.
Mm.
Zach Wagner (20:36)
there needs to be a fundamental rethinking of how work gets done and what roles people have in this equation. Because in many cases, I think it’s turning us more into,
Hopefully it’s upleveling the work that we’re doing and allowing us to think more critically and more strategically and have more time for that. But then the other side of that is then you also have to be a really great editor and manager and delegator of the AI. And you’re not going to be working in the same way that you…
Jason Gorman (21:05)
Mm-hmm.
Zach Wagner (21:11)
were working five years ago, you have to kind of rethink for yourself a little bit as an individual and then as an organization, like what are the roles that I need right now for this new landscape? So I think the trade-off is, you’re right, it’s kind of embedded in the technology and it’s for every organization to kind of think of
for themselves in like the dynamics that they’re in. how do you actually, how do you adapt your workforce for a world that is now moving so quickly, right? That, you know, every day a new tool comes out that can do something that couldn’t be done yesterday. ⁓ And you need people that can stay on top of that and know how to bring that into your organization.
Jason Gorman (21:39)
Mm-hmm.
Yeah.
Zach Wagner (22:03)
And that could be its own role, right? And that’s a role that didn’t exist two years ago or even six months ago. So I think it’s like the trade-offs are going to keep coming faster and faster, honestly. And the organizations that do well, that thrive are going to be the ones that are resilient, that are adaptable, that lean into that change instead of trying to hold out against it.
Jason Gorman (22:11)
Yeah.
Zach Wagner (22:29)
And that’s sort of the, just the mentality that I have going into my conversations with clients and into my kind of the way that I think about, you know, what this means for companies.
Jason Gorman (22:40)
And on the flip side, what are the things that you are intentionally keeping manual, that you just don’t want to have any AI involved with? What are the things that maybe your clients have come to you with, with ideas of things that they want to do where you say, maybe just let the humans keep doing that for now?
Zach Wagner (22:57)
Yeah, I think the strategy piece, and by that I mean the only you know your company and its purpose, its vision, its mission, its values better than anyone. I know Brightway is better than anyone. I certainly know it better than AI. What I’m not going to delegate to AI to claw to GPT is, you
help me think through the five-year strategy for Bright Way and how I navigate this space and how I think about where my value prop is. That’s something I feel like you could delegate that to AI certainly, but that’s something I think you need to internalize for yourself. So I’d say the distinction I draw, I guess, or the
like first principle I use is what do I really need to internalize and think critically for myself about in order to have a really strong point of view perspective on this so that when and if I do engage AI in some of the component pieces of it, right, if I engage AI to help me come up with like a brand strategy, I need to have a really strong idea about what my brand is about and what my
Jason Gorman (23:47)
Hmm.
Mm-hmm.
Zach Wagner (24:11)
what my, you know, what my organization’s about.
Jason Gorman (24:14)
That’s great. It leads me to a question that I had for you about strategy.
For me, I feel like my crystal ball is broken. I can’t, a really hard time thinking about what my job will be like in three years. It just feels like, may as well be 100 years, right? It feels so, so far away. But when you think about AI strategy or product strategy for a client,
organization, somebody that you work with. What’s something that many or most organizations should be building now, should be thinking about right now to avoid really being left behind in two to three years?
Zach Wagner (24:58)
I’m trying to think of how to frame this, but.
Here’s something I struggle with right now that I’m thinking about, like, how do I do this better? Which could give some perspective into what I think is going to be important for companies. And that is just the, how do you stay on top of everything? Right? At the end of the day, there’s only like three big players in AI. There’s open AI, Google, Meta, maybe a little bit of X.
Jason Gorman (25:17)
Mm.
Zach Wagner (25:30)
give or take, Anthropic, everything is built on top of those models. But there’s 30 plus thousand tools that have been built on top of those models in the past two and a half years, right? And they all do different things, the same things, some do, you you have like a hundred tools that create video and some are better than the others and some are cheaper than the others and…
Jason Gorman (25:35)
Mm-hmm.
Yeah. Yeah.
Zach Wagner (25:57)
There’s so many considerations that go into how do you assess which thing is right for your organization and how do you just stay on top of all the developments in this? I think about how do I form an AI advisory, just a person that can just be watching for the new developments and assessing, scoring things objectively as possible, saying, here’s the things that
Jason Gorman (26:14)
Hmm.
Zach Wagner (26:26)
are important and the signal and here’s everything else that’s the noise. Because I think a lot of people and companies are going to struggle with going down rabbit holes, like trying to use a tool that at the end of the day doesn’t bear out its promises. So I think in the old model where you have just like a few big SaaS companies that do everything,
you’re now gonna have thousands of companies that do very specific things and how do you stitch that all together?
Jason Gorman (26:58)
That’s a surprising answer to me, and I love it.
I thought that you were gonna say there was some fundamental process or some fundamental thing that every organization should look at and start to put something in place now. But I love that you turned to instead to talk about building an internal human, additional human capacity, right? To help kind of stay ahead as much as we can.
to stay ahead of this tsunami of tools that just runs over us. mean, that’s kind of how it feels to me. My answer?
I think my answer is similar in that it is maybe human, a little more human focused too, which is that I think now’s a very, very good time to look at existing jobs and skill trees and think about how those things might change over the next couple of years. And I don’t think we know exactly how they’ll change, but I think if we put on kind of more of a
Zach Wagner (27:52)
Hmm.
Jason Gorman (28:00)
a hat where we think in terms of probabilities for the future. If somebody’s a learning experience designer, there’s some probability that they’re gonna need to have a lot more facility with data in a deeper way than they have before. That they’re going to need to be able to understand
really deeply some of these things about prompting that makes a model behave a certain way, this or that. I’ve had experiences where I’ve built big complicated prompts and just they keep doing weird things. And then I’ll go back and I’ll just find the two words in there that was confusing it. And I think just developing that skill, it’s like debugging, but with language.
finding those things. These are skills we don’t have. never learned, nobody ever taught me how to do that. And I think figuring some of those things out is going to be critical, but really hard to know which ones are the right ones.
Zach Wagner (29:00)
Well, that’s also an interesting… One of the things I think a lot about is also like, who’s really well equipped to use AI? And I think it’s paradoxical because you’d expect it to be the really technical people. But actually I think it’s the people that come from liberal arts backgrounds and the humanities, people that really understand like the precision of language and why that’s really important, especially for like…
generative AI, we’re not talking about agentic AI and like building automations, but when it comes to prompting and getting content from an LLM that is somewhat within the bounds of what you were envisioning, the people that are going to be really good at that are the people that read a lot, that write a lot, that actually are really strong with language.
the output is only as good as the input.
Jason Gorman (30:00)
Yeah, I’m feeling better and better these days about my English literature major.
Zach Wagner (30:04)
Yeah, exactly. That’s right. Yeah,
we all we were all taught to told that our our my philosophy degree wasn’t going to pan out to anything, but there you go. Yeah.
Jason Gorman (30:12)
Right now useless. Yeah, here we
are. All right, I feel like that we’ve showed them ⁓ I have a thing that I do at the end of these conversations where I ask people One question that they want the next guest to answer. So
Zach Wagner (30:20)
Yeah.
Jason Gorman (30:33)
Let me get your question. Let me see if you have a question. What is a question you just want to ask an interesting person? Actually, I can tell you the next person I’m going to talk to ⁓ is an entrepreneur. He teaches entrepreneurship. It be a question you’d want for that person.
Zach Wagner (30:48)
trying to think of a question I need answered from an entrepreneur professor, which are plenty.
I guess just generally, how do we see startup culture and…
what different skills and mindset does it take to be a successful entrepreneur now than it did 10, 15 years ago?
Jason Gorman (31:11)
That’s great.
Terrific. All right, so let me give you a question. This came from Brick Meyer. Brick is involved in a company called HeatSpring. I don’t remember his exact title, but HeatSpring makes training specifically for people in clean energy technology. So these are really training people to build stuff in the green economy. Here’s Brick’s question.
Looking beyond the current AI hype, when will we know that student learning has fundamentally changed because of AI? And what might be evidence of that change?
Zach Wagner (31:49)
wow. That’s a good one.
Jason Gorman (31:50)
That’s a good one.
Zach Wagner (31:52)
I think we’ll know when.
Students are not just…
leaving school with the expectation that they can do the work that is available today, but
it gets back to, you know, first principles. Can they adapt? Can they be resilient? Can they pivot and pick up new skills and knowledge? And can they do that rapidly as the time calls for? So evidence of that, I think, is
seeing students who can approach.
today’s questions in really novel, thoughtful, critical ways that are not just repeating something they’ve read or they heard about, that they’re able to put together a lot of different domains in their answers and in the way that they approach the world. So, at the end of the day, think we’ll know when students aren’t
leaving school with a single track in their mind and a siloed, this is the domain I’m going to have expertise in, but really leaving with flexible mindset, looking at AI and technology less as replacement, more as another tool in their toolbox to navigate ever-changing waters.
Jason Gorman (33:19)
That’s great. Zach, thank you so much for joining. Really appreciate it. This has been ⁓ Zach Wagner on the Learning Experience Operations Show. Thanks again for joining us. Maybe we’ll do this again sometime. I’d love that. All right. Thanks, Zach. Bye.
Zach Wagner (33:23)
Thank you.
Awesome. Thanks so much for having me. This was fun.
Bye.