Why It’s So Hard to Adopt New Skills

Hannah Clark: You are listening to The Product Manager podcast, presented by The CPO Club. Make sure to subscribe and check out cpoclub.com for more exclusive content.

Before we begin, you need to know that this is a really important episode for everyone in product to hear. Not just because it will help you gain new skills, but because it addresses a crucially important factor that impacts the effectiveness of every aspect of your organization — learning. Because when you think about it, everything from your leadership approach, to your product's onboarding flow, to your GTM strategy, connects to how good your organization is at understanding how people learn new habits and skills. And let's be honest, in at least one of those areas, most companies are not nailing it. But after recording the episode you're about to hear, I am convinced that the best-kept secret to success is to think like a teacher.

My guest today is Maxine Anderson, the Co-Founder and CPO of Arist, a text-based learning platform. Before Maxine was a founder, she was a teacher. And I am not exaggerating when I say that I was blown away by the brilliant simplicity of Arist as a concept. What I really want you to hear is Maxine's profound understanding of how people learn, and not only how deeply it connects to an organization's most important markers of success, but how costly it is to miss the mark. You'll hear why more information doesn't equal more learning, the opportunities for improving stakeholder and customer outcomes that most companies miss, and the role of generative AI in changing how we learn, teach, and get results. Let's jump in.

Oh, by the way, we hold conversations like this every week, so if this sounds interesting to you, why not subscribe? Okay, now let's jump in.

Welcome back to The Product Manager podcast.

Maxine, thank you for making time to talk to us today.

Maxine Anderson: Yeah, sure. I'm super excited.

Hannah Clark: So can you tell us a little bit about your background and how you got to where you are today?

Maxine Anderson: So I actually started out teaching in rural Oregon where I was building educational programs with almost zero resources, and I was trying to figure out how you can create impact through educational experiences on students, like the impact that teachers make on students, which I felt was very personalized.

And so in that experience, I saw how broken access to learning was and how traditional education mediums didn't really address person to person needs. So fast forward to college. I co-founded Arist with my two friends in college who were also working in the education nonprofit space. To say, basically solve the same problem, but at scale, which was always what I was trying to do, which is how do you get the right skills or information to people without the overhead of the classroom, a learning management system or a traditional educational program, essentially.

And so that's how I came to Star Arist. We just found that a majority of someone's life is in the workforce, and so enterprise learning is where we can make the most impact.

Hannah Clark: Yeah, that makes total sense and it's such a cool mission as well. So I wanna know a little bit more about kind of how you guys put your minds together to think about the concept for Arist.

And actually maybe you can walk us through a little bit how it works 'cause I think it's just such an innovative product.

Maxine Anderson: Yeah. Put simply how our product works is we deliver information and learning to people through messaging tools that they use every day. So text. Slack, Microsoft teams in the workplace, Microsoft teams and text and Slack are used a lot, you know, for people out in the field or really anyone like text is super accessible and so delivering, learning that way is, ends up being really effective and we have an end-to-end platform for creation delivering analytics.

With AI built in throughout that entire experience to really help change how organizations do learning for this way of working now, which is changing a lot.

Hannah Clark: Yeah, I think it's just such a cool, and like I'm such a fan of product that really kind of comes back to the existing competencies and functionalities that we are already familiar with and kind of expands on those in ways that are innovative.

So I do wanna talk a little bit about barriers that you people face in general with learning. And you kind of mentioned a few with the kinds of examples of folks that you and your colleagues were working with, but I think in general there's certain barriers to learning that all of us kind of encountered, and especially in the work at enterprise learning space.

So what did you kind of discover that kinda led you to think about this alternative way of delivering information?

Maxine Anderson: Yeah, great question. I think I'll talk about like, you know, in product we talk about like aha moments. So in terms of barriers, like I realized in my education experience, like as a teacher, especially in rural Oregon.

Learning isn't always about content, it's really about like context. And what I mean by that is I was trying to educate some of these students on like financial literacy training and honestly, they're just like embarrassed to go to class or they don't have time to sit like between work and school.

Like they're not gonna sit through like hours of video training. And so. I think that I realized that like there's so much information, we're in an information age, or at least we're like moving outta that, but like we were for so long, the barrier isn't like knowledge, it's like psychology and like context of like how to make it possible for someone to learn.

And a lot of traditional formats actually make those barriers worse. While like I found that Arist, you know, me and my co-founders all had different aha moments like. We basically couldn't get over the fact of like how simple Arist was as a solution for such a complex set of problems like education. Once you start digging into like the educational system and how people learn and like, it's just really complex and I was overwhelmed by that like out of high school and I found it so motivating how simple Arist like where you just deliver information to people over text, you have the opportunity to automate it and give it to people right when they need it.

I just found that how simple it was like so contagious as an idea. And I think that my co-founders experienced something simply like it was the first moment I heard Michael share with me. 'cause you know, we lived in entrepreneurship, living community and shared with me like, oh yeah, I'm sending information to students in Yemen over text about like entrepreneurship.

That's the only way to reach them. I'm like, everyone uses text. How is that not used as a learning medium? I asked him, like, I, I literally asked him like, oh, what technology are you using for that? And he is like, no, I'm just like texting people manually. And I was like, how does that not exist? It's such a simple, overlooked solution to like, education, which has like a lot of complex challenges basically that don't put the learner first in my opinion.

Hannah Clark: I tend to agree with you. I'm curious when you say traditional learning mediums sort of. Amplify almost some of these challenges. What do you mean by that? I'm kind of curious about some examples where the traditional style is kind of not really meeting learners halfway.

Maxine Anderson: Yeah. I mean in, in two places, right?

So like, when I work more in traditional education, schools themselves are barriers. Like if you think about, you know, I experienced this in rural Oregon, sometimes students wouldn't show up to class, right? Like having to go to school is a barrier. The other barrier is like the school has mixed incentives.

They have a lot of things like just organizationally that they're stressed about. Like the business model of schools is difficult. Teachers aren't paid enough. They have state regulations, they have to meet federal regulations. And so like the learner ends up becoming last actually, which is sad but true.

Right? So that's one example. The example in that, like that we always say in like enterprise learning is. On average, it takes like seven clicks to get into the learning you need to access, right? You have to open a website, you have to log in, you have to click into a video, you have to start it. You have to approve some like security approval thing.

By the time you get there, you're like, okay, gotta run and like pick up my kids or walk my dog, or whatever, right? And so that's just like a simple example, but it is, there's a lot of barriers to like just getting the information you need to like do your job, right? Or to like perform or learn better.

Hannah Clark: I do think that there is like a lot to be said about kind of taking these existing behaviors and just kind of building on them rather than kind of asking of people to sort of reinvent the wheel when you're trying to teach them something.

There's the thing you want them to learn, but then there's also the how to get there and carving out time for all of that.

Maxine Anderson: You know, I always say technology should like reduce complexity, especially as product people like wanna build or engineers wanna build like the fanciest products and like it's amazing and beautiful, but it's like but is anyone gonna even be able to like engage with it or use it, right? So yeah, I think that's a really important principle.

Hannah Clark: Yeah, absolutely. So we talked a little bit beforehand and you've mentioned sort of this idea of having two to three things that most people really need to know about a specific topic.

How does that kind of principle inform how you deliver content on Arist? And just like your approach to learning in general.

Maxine Anderson: Like I mentioned, we wanna reduce like the barrier or access to like what people really need to know. And we want people to get information that they actually need at the right time.

And so we believe that the gap really in how organizations work today. So like you, good, you know, sales reps, for example, they drown in playbooks, in frameworks and they're required to go through all the training. It's amazing content. But when they're about to walk into a meeting. What are the two things they need to know to say in that meeting to win the deal or move it forward?

Right? They don't need 200 pages before that meeting, right? And so there is a place for more in-depth, more in-depth coaching, et cetera, but there's a gap in like solutions and learning out there that isn't solving for like what the most important things to know are. And we've truly seen that training in organizations and just in general isn't broken because the content is bad by any means.

It's because it's not designed around people's mo like the moment of need. Right. And actually one of our clients is redesigning, like moving away from skills and capabilities to like more of a product mindset, which is like what are the jobs to be done on like an average weekly basis when they interact with tools and that's helping them like integrate AI more, which is interesting.

Just to give another example. One of our clients is like one of the oldest insurance companies in the world, and they were struggling with training service reps to increase like CSAT scores. Basically, they adopted Arist to try to solve the problem, and a lot of their learning designers were like, no way.

We cannot reduce information by this much. We can't make it 1200 characters, which is like the forcing function we put into our product. And they honestly fought against it a lot. We said, okay, just try our AI tool, like try to write it short. And they actually came back saying like, that was a really good exercise because I realized how much of the training we were giving call center reps.

They're just not gonna read, especially in like their day to day and it's actually not like super critical. And so they push it out and they increased like CSAT scores by, I think it was like 20% or something from like a three lesson course because they just were able to like actually narrow down parts information.

And like still like six months later I met again with them. They said, I still like any tool I use, I put way less information because of Arist. So yeah, I think the forcing function of like, what do people actually need to know? And it applies in marketing and learning, like in a lot of it's just like human psychology, like people can only consume so much.

Hannah Clark: What comes to mind for me is user onboarding. Like how many times have you had an onboarding experience where it's just like, oh my gosh, I feel like I'm reading a tome just to get to the first feature. You know, like, exactly. So I feel like, you know, if you're, if you work in user onboarding and you're listening to this podcast, please take to heart.

Users can only take so many pieces of information at once. So, yeah, I think this is a really good principle to embody and this is something I think that is useful in all forms of communication as well, because I think we have a tendency to think, not just in product, but in general, that by over-explaining or providing all the information up front that we are giving everybody what they need.

Often I think that tends to backfire. So I think this is a, such a, like it is a cool exercise to just review any form of communication or learning and pare it down to like the absolute minimum. Okay. Let's talk a little bit about just the idea of, now that we've talked about consuming content, getting people to actually put it into practice, like now that you've delivered the information, how do you kind of ensure that the actual skill that you're trying to deliver is in place?

Maxine Anderson: A couple things we look at, so we've done our own research on what drives. So like most learning tools track things that I call our, like leading metrics of potential behavior change, which are like, okay, you completed a course, or like you got a certification for a skill, right? It's like, okay, they're more likely to perform better.

Right? We look at a couple things like one, we look at confidence lift, so our AI evaluates if someone's like confidence and like ability to like talk about the subject has changed throughout the course. And then we basically show confidence lift. And we pull data from other systems that basically measure if a change has happened.

So an example for like a sales rep could be like gong basically their confidence in like following this messaging framework increased. And in gong we pull like they have like insights and they have like pillars of like what reps are like saying in meetings and so we can like pull that. Basically provide it back to admin and say, okay, you like, after this course, within 10 days, these pillars on like success rate, like shifted basically.

So we're always trying to, like, we're trying to change behavior like just in organizations of how admins and like I should say, like enablement leaders and leadership delivers training internally that they think first of like, what is the actual like business problem or business outcome that we're trying to solve.

Versus like taking in an like incoming like training request and then like saying someone has a skill. And so like with our tool also, we're trying to change the behavior of how like needs are fulfilled in our organization so that leaders have a pulse on all the data in their organization and can rapidly close gaps that exist versus having a long lead up time on these analysis, taking in a bunch of requests, prioritizing them, and then missing, you know, like 75% of closing those gaps.

And you know, something we've also learned is like, and any of our clients will tell you this is like most other teams that go to central like learning and development teams or HR to like solve the problem. They basically are like. A lot of times the prom's not training, like they actually don't need more enablement.

It's that like the messaging framework doesn't make sense or like people need more time with their manager. Right? Like sometimes the problem and the solution's not learning actually sometimes, even though organizations default to it. So it's like your sales team's struggling. It's like everyone's like, oh gosh, like now we're gonna go through like, you know, a four hour meeting on like how to pitch this better.

And it's like, well it's not actually like. Probably gonna solve the problem. So that's what we see in organizations is like, just back to your original question, is that the way that we track performance is like, we do work really closely with leaders and we're trying to like make that more automated and with like agent AI and pulling information from different systems to like really prove that enablement and like targeted actions or like that are, you know, sent as nudges to people through Arist are actually like driving a change in how they behave or how they perform in their jobs.

So we're always trying to work towards that wholly grail of measuring success because most learning tools just like candidly, they just like can't get there. And so like what's used as a default instead is like certifications or other things that like point to like potential change of behavior.

Hannah Clark: Another thing that I think is really interesting about the delivery method of Arist is this element of. Personalization and being able to kind of emulate to some extent the experience of being taught directly by a teacher. And I think that the social aspect and the relationship aspect of learning is something that I think also is kind of missed by a lot of the traditional corporate training methodology.

You know, the online courses and that kind of thing that are very content focused but are kind of void of having that more of like a relational aspect. So was that kind of a part of how you guys conceived of it or have you kind of noticed anything that's kind of interesting or a byproduct of having this approach that does kind of emulate more of a personal connection?

Maxine Anderson: Yeah I dunno if I can speak to the personal connection as much. There was like a phase of tools like three years ago that was like social learning and like every, like you, it seems like you're learning from your manager and I think that like, it's valid, but we actually try to abstract a way like.

That component and gamification for like the same reason, which is that if we believe that you give someone like only what they need and then they like trust that you're giving them what they need to perform well, that you don't need to like layer in those other things. What I will say though, and is what like goes with what you're saying is that people share a lot more over text, like open-ended and the learning experience can be personalized and more when it's a one-to-one relationship.

I think what we mastered with Arist is that it's an at scale learning solution, but you're creating one-to-one experiences. Most learning tools are like made in it for enterprise or like at scale solutions, but it's like everyone's is very much the same and it is through like a platform, which in itself makes it feel less personable.

It's different than like, we're not like personifying like another person in a company necessarily, but I do see what you're saying and like it makes a big difference. And that's what I meant by like the context, like also psychological safety. And like just sharing anything, like people go through courses and it's like, okay, if like an exec is asking you as a new manager what you're struggling with, like you probably have a lot of reasons you don't wanna share, but like over a text, if the course is gonna help you and it's like made for you, that's gonna change the way you respond and like probably help you more 'cause you're more vulnerable.

Hannah Clark: Yeah, absolutely. And there's that conversation element that I think just kind of facilitates more just open-ended learning. I haven't personally used the platform, so, you know, maybe I wanna, I don't wanna step too far in a turn, but I just think it's a really amazing delivery method. Okay. So tell me a little bit about how AI has sort of figured in, you know, where are you guys seeing AI in terms of like the story of your product right now, and kind of where do you see that sort of fitting in general at this kind of, I would maybe even call this kind of a next generation method of education.

Maxine Anderson: So I'll say like what we're not solving, but I think is valid, like there are a lot of like AI role playing and coaching and adaptive learning tools out there. I think we've realized that basically a lot of the reason that learning ends up not being like learner focused, or I should say employee focused or like the employees not at the center, is because of honestly, like how messy the administrative overload and burden is.

Across teams and organization to coordinate to get effective enablement out there. And so what we've decided to tackle is like essentially changing the way that an organization approaches doing learning from like a top down approach, right? So the first thing I'll say there is that like one of our early observations was like, okay, most people do wanna learn in an organization, but they don't pull learning, right?

Why is that? Because it's not built for the way they need and whatever, right? But there's also not many tools out there that are built other than compliance learning, that are built for like pushing, learning based on like organizational intelligence. So the first layer is like, you assume humans have that.

The second layer is like, okay, if AI and automation were like really well embedded into your, like all the tools in your organization, effectively, you should be able to push learning to people when they need it. So we are like an AI enablement tool and what we say is like. Or like the solution to like instant enablement in your organization?

I don't mean just like sales enablement. I mean we use enablement broadly for like learning anything that helps people perform better basically. So our AI does everything from understanding needs an organization to creating it and then analyzing if there's performance gaps. What we've found is that entire process is shifting.

So historically in organizations like large enterprise, you know, you have business unit functions like a CRO, Chief Revenue Officer, and they have to go to, like, they have all these new sales reps, the new sales onboarding program, they either have like an enablement team on their team, which a lot of sales teams do.

But let's say you're like an ops team, you have to go to like central learning and development. It goes into their queue. Then they basically do like an expanded needs analysis on it. So then they interview like hundreds of ops people, or I dunno, ops leaders get insights and then they say, okay, great. Now we have all these insights.

Now as humans, which we know takes a while to process, we're gonna process this information, decide what to do. Now we're going to create training. Now it has to go through all the approval processes, which is a lot of back and forth. And now after it's gone through all the approval processes, we're gonna come back.

Now we have to like translate it and version it for different groups in the organization. And then we're gonna launch it and then we're gonna like try to get people to adopt it. Right? So that whole process takes like 40 weeks, like minimum, right? Woo. What's changed completely and like where Arist fits in is that businesses are changing faster than ever before because it's so much, especially tech companies, but other companies as well, because it's so fast to build product now that like the rest of the company literally can't keep up.

And so basically these companies have like all this revenue potential and they're just like bleeding money. Like one of a really well known like tech companies, one of our clients, they just iPod and they like keep shipping features, like AI features, keep shipping features.

They literally just can't keep up. And so like their support reps aren't enabled. Their sales reps are saying the wrong things. They aren't driving like success of those AI tools. And so like, it's a huge gap. And so what we're realizing and fitting in is that like. Arist like end-to-end solution is basically like an orchestration engine on understanding like, okay, this is what we're working towards.

Right? And like what we're helping our clients with is like, this release is coming up, it's like in, you know, writing launch. Now we're gonna pull notes from all the relevant tools like, you know, the commit the gi, you know, from GitHub or like linear notes or whatever it is. Jira, you know, anything from there.

And then basically like spin up content and like basically create versions based on the different teams, get quick approval and send it out. So like AI also needs to know like when to get human approval. But you can imagine that then that makes like people in that organization, in a tech company or whatever, rather than being maybe like a learning designer specialist, they're basically like being the human approver or like pointing it in the right direction based on like business challenges.

So they become more of like an orchestrator. Rather than like maybe a specialist in their job is kind of the way that we're seeing it change. And so like workflows just have to change completely, and that's like very painful in a large enterprise. So there's just tons of problems right now with that.

But like you can tack on a million AI features to like, you know, other learning tools that exist that are like traditional corporate learning tools, but it just doesn't change the way that people work enough to like actually meet the needs of organizations today. And so that's why we took like a ground up approach to building like a tool that is optimized around like business outcomes versus like how humans do the work today.

Hannah Clark: Yeah, and I really resonate also with this idea of people becoming more orchestrators. I think that we've discussed that before on the show. We've kind of thrown around this idea of ai kind of, actually, kind of in a way building people's management skillset, because you're sort of acting more in the mindset of a people manager when you're directing agents, for example, or when you're kind of reviewing and kind of guiding information, rather than just sort of building from scratch and kind of, you know, throwing spaghetti at the wall.

So I think that's kind of interesting how like we're seeing this kind of in multiple different verticals how this kind of effect of Yeah, orchestration and guiding things and kinda refining rather than having to kinda build, interpret, do all of these things manually. I think that's might be the biggest thing in, in all AI advancements lately.

So now that we're kind of at this point in the company, what would you say has been the most significant lesson like this is, it sounds like quite a journey for you. You know, this all started from your experiences in rural Oregon and now you know you're working with enterprise clients and this has been like a relatively short period of time, if I'm not mistaken.

In the last several years that you've been working in your capacity, what have you learned that you think is like the most impactful that you would want other people, other founders, other people in the education space to know?

Maxine Anderson: Yeah, I think whether it's called education, learning, enablement, whatever it is, like I always view it, the goal is that you're helping someone realize their potential to accomplish what they want in life.

Basically, like that's the purpose of it, right? If it's in a job, it's performance. If it's in like high school, you want them to be able to like go out into the world and get what they want out of their life, right? So I think that is the goal, and I think what I've learned is that is not accomplished through the best content in the world.

It's accomplished through providing the right context to the learning and by basically like bumping into problems. Right? And that sounds weird, but like even technology should get people to do that. Like don't sit and like consume three hours of video training, right? Like people need to, and this is done, but like.

Anyone building technology or implementing whatever it is like should really focus on like how do you get people to like bump into problems a little bit more like practice? And that's when it like really sticks in their head. And how do you create that experience in context when it's like needed the most?

Right? I always talk about like podcasts are the party example for me. I love listening to podcasts. I listen to all the time. Like 10% of them like drive me to like change anything. And it's because I like happen to listen to it. Like the day before I faced that problem or like that night, I like listened to the podcast and I faced a problem earlier in the day.

And so like I think context is like super important and creating that context for people is really important. I also. I think it's interesting and like curious people and like you can learn knowledge, but like, you know, our goal with our technology at least is not like for people to just learn. It's for people to like actually change their behavior, perform better, like feel the impact of that learning.

So I think it's like, you know, great content is totally necessary, but I think it's just like what we've learned is just not what drives people to like actually. Gain a new skill or something is like, it's just not, it's just not through content. I know people who like consume the most content ever on like product management and like still struggle with like the day-to-day of like how to get something like actually out there.

Right? So I think it's just like human behavior, like needs practice and it needs like, you need to like provide that context so that people can like actually, you know, understand and like utilize the content basically.

Hannah Clark: I completely agree. We actually, we were for a long time hosting panel events and kinda like live events.

And over, over time we were kind of figuring out like, how do we make these better? How do we make these more useful? And one of the things that we kind of thought we would experiment with was doing something that was a lot more hands-on. So we ran a vibe coding workshop and it was a similar format where we would have a facilitator still leading it, we would still have hosts and that kind of thing.

But what we did was we told people to come prepared with a few of these different supplies, have some accounts built, kinda already have a platform in mind, or a concept that they wanted to try to prototype. And just by making the format more following along, rather than just listening and taking in all this information that without context can be very abstract.

We got way better participation levels. We got way better people. I guess as far as the percentage of people that stayed throughout the entire thing, people who gave us great feedback about how many skills that they actually retained. It was just night and day. So I yeah, like firsthand, I can say that context piece is super, super, super critical.

Maxine Anderson: Yeah. And one response is like, there's just nothing more frustrating. Like, have you ever heard someone say something like, so intelligent? You're like, okay, stick it in my mind. I'm gonna use that in my next meeting. And like, you just forget it. You're like, oh, like I was gonna like come to this meeting.

So smart. Like I, I heard the best tidbit from someone, like there's value to that, but like, there's an opportunity with ai, like just being able to generate content on the fly to like give people information. Like if you add good automation, integrated data. When they need it. And that's like so powerful.

Like that's like an, it can be a serious engine for an organization. So yeah, I'm excited to see how it changes learning.

Hannah Clark: Same to here, and I'm a little bit disheartened to hear that this actually means that homework is actually valuable. Oh, no. Anyway, thank you so much for joining us today, Maxine.

This was a really fun chat. Where can listeners follow your work online and find out more about Arist as well?

Maxine Anderson: Yeah, so we're at www.arist.co. I post a lot on LinkedIn about what learning and reinventing learning organizations for the future of work looks like. So I'm at Maxine Anderson on LinkedIn.

Hannah Clark: Cool. Well thank you so much for being here.

Maxine Anderson: Yeah, thank you.

Hannah Clark: Next on The Product Manager podcast. Now that you know how people learn, our next episode is all about how people buy. We'll be digging into buyer psychology and the small tweaks you can make to your customer touch points that boost conversion, drive adoption, and fill the cracks in your growth strategy.

You don't wanna miss this one. So subscribe now to jump in with us next time.