September 16, 2025 • 28 mins
Every product manager obsesses over leadership styles, onboarding flows, and GTM strategies—but what if the biggest differentiator of success comes down to something much simpler? Learning. In this episode, Hannah Clark sits down with Maxine Anderson, Co-Founder and CPO of Arist, a text-based learning platform that flips traditional corporate education on its head.
Maxine started her career in rural Oregon classrooms, where she saw firsthand how inaccessible and ineffective most learning environments were. That experience sparked the idea behind Arist: meeting people where they already are, through tools like SMS, Slack, and Teams. What follows is a candid conversation about why more content doesn’t equal more learning, the real barriers that keep employees from growing, and how AI is reshaping not just education—but how organizations function.
Resources from this episode:
- Subscribe to The CPO Club newsletter
- Connect with Maxine on LinkedIn
- Check out Arist
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Hannah Clark (00:00):
You are listening to The Product Manager podcast,
(00:02):
presented by The CPO Club.
Make sure to subscribe andcheck out cpoclub.com for
more exclusive content.
Before we begin, you needto know that this is a
really important episode foreveryone in product to hear.
Not just because it willhelp you gain new skills,
but because it addresses acrucially important factor
that impacts the effectivenessof every aspect of your
(00:23):
organization — learning.
Because when you think aboutit, everything from your
leadership approach, to yourproduct's onboarding flow, to
your GTM strategy, connectsto how good your organization
is at understanding how peoplelearn new habits and skills.
And let's be honest, in atleast one of those areas, most
companies are not nailing it.
But after recording theepisode you're about to
(00:45):
hear, I am convinced that thebest-kept secret to success
is to think like a teacher.
My guest today is MaxineAnderson, the Co-Founder
and CPO of Arist, atext-based learning platform.
Before Maxine was afounder, she was a teacher.
And I am not exaggerating whenI say that I was blown away
by the brilliant simplicityof Arist as a concept.
What I really want you tohear is Maxine's profound
(01:06):
understanding of how peoplelearn, and not only how
deeply it connects to anorganization's most important
markers of success, but howcostly it is to miss the mark.
You'll hear why more informationdoesn't equal more learning,
the opportunities for improvingstakeholder and customer
outcomes that most companiesmiss, and the role of generative
AI in changing how we learn,teach, and get results.
(01:27):
Let's jump in.
Oh, by the way, we holdconversations like this
every week, so if thissounds interesting to
you, why not subscribe?
Okay, now let's jump in.
Welcome back to TheProduct Manager podcast.
Maxine, thank you for makingtime to talk to us today.
Maxine Anderson (01:43):
Yeah, sure.
I'm super excited.
Hannah Clark (01:45):
So can you tell us a little bit about
your background and how yougot to where you are today?
Maxine Anderson (01:49):
So I actually started out teaching in rural
Oregon where I was buildingeducational programs with
almost zero resources, and Iwas trying to figure out how
you can create impact througheducational experiences on
students, like the impact thatteachers make on students, which
I felt was very personalized.
And so in that experience,I saw how broken access to
(02:12):
learning was and how traditionaleducation mediums didn't really
address person to person needs.
So fast forward to college.
I co-founded Arist with mytwo friends in college who
were also working in theeducation nonprofit space.
To say, basically solve thesame problem, but at scale,
which was always what I wastrying to do, which is how do
you get the right skills orinformation to people without
(02:36):
the overhead of the classroom,a learning management system
or a traditional educationalprogram, essentially.
And so that's how Icame to Star Arist.
We just found that a majorityof someone's life is in the
workforce, and so enterpriselearning is where we can
make the most impact.
Hannah Clark (02:51):
Yeah, that makes total sense and it's
such a cool mission as well.
So I wanna know a little bitmore about kind of how you guys
put your minds together to thinkabout the concept for Arist.
And actually maybe you can walkus through a little bit how it
works 'cause I think it's justsuch an innovative product.
Maxine Anderson (03:04):
Yeah.
Put simply how our productworks is we deliver information
and learning to peoplethrough messaging tools
that they use every day.
So text.
Slack, Microsoft teams in theworkplace, Microsoft teams
and text and Slack are used alot, you know, for people out
in the field or really anyonelike text is super accessible
and so delivering, learningthat way is, ends up being
(03:25):
really effective and we havean end-to-end platform for
creation delivering analytics.
With AI built in throughoutthat entire experience to really
help change how organizations dolearning for this way of working
now, which is changing a lot.
Hannah Clark (03:40):
Yeah, I think it's just such a cool, and
like I'm such a fan of productthat really kind of comes back
to the existing competenciesand functionalities that we
are already familiar withand kind of expands on those
in ways that are innovative.
So I do wanna talk a little bitabout barriers that you people
face in general with learning.
And you kind of mentioneda few with the kinds of
(04:00):
examples of folks that youand your colleagues were
working with, but I thinkin general there's certain
barriers to learning that allof us kind of encountered,
and especially in the workat enterprise learning space.
So what did you kind of discoverthat kinda led you to think
about this alternative wayof delivering information?
Maxine An (04:18):
Yeah, great question.
I think I'll talk aboutlike, you know, in product we
talk about like aha moments.
So in terms of barriers, likeI realized in my education
experience, like as a teacher,especially in rural Oregon.
Learning isn't alwaysabout content, it's
really about like context.
And what I mean by that isI was trying to educate some
(04:40):
of these students on likefinancial literacy training
and honestly, they're just likeembarrassed to go to class or
they don't have time to sitlike between work and school.
Like they're not gonnasit through like hours
of video training.
And so.
I think that I realizedthat like there's so much
information, we're in aninformation age, or at least
we're like moving outtathat, but like we were for
so long, the barrier isn'tlike knowledge, it's like
(05:01):
psychology and like contextof like how to make it
possible for someone to learn.
And a lot of traditionalformats actually make
those barriers worse.
While like I found thatArist, you know, me and
my co-founders all haddifferent aha moments like.
We basically couldn't getover the fact of like how
simple Arist was as a solutionfor such a complex set of
(05:22):
problems like education.
Once you start digging intolike the educational system and
how people learn and like, it'sjust really complex and I was
overwhelmed by that like outof high school and I found it
so motivating how simple Aristlike where you just deliver
information to people overtext, you have the opportunity
to automate it and give it topeople right when they need it.
I just found that howsimple it was like so
(05:44):
contagious as an idea.
And I think that my co-foundersexperienced something simply
like it was the first momentI heard Michael share with me.
'cause you know, we livedin entrepreneurship, living
community and shared with melike, oh yeah, I'm sending
information to studentsin Yemen over text about
like entrepreneurship.
That's the onlyway to reach them.
I'm like, everyone uses text.
How is that not usedas a learning medium?
(06:05):
I asked him, like, I,I literally asked him
like, oh, what technologyare you using for that?
And he is like, no, I'm justlike texting people manually.
And I was like, howdoes that not exist?
It's such a simple,overlooked solution to like,
education, which has likea lot of complex challenges
basically that don't put thelearner first in my opinion.
Hannah Clark (06:21):
I tend to agree with you.
I'm curious when yousay traditional learning
mediums sort of.
Amplify almost someof these challenges.
What do you mean by that?
I'm kind of curious about someexamples where the traditional
style is kind of not reallymeeting learners halfway.
Maxine Anderson (06:35):
Yeah.
I mean in, in two places, right?
So like, when I work more intraditional 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 toschool is a barrier.
The other barrier is like theschool has mixed incentives.
They have a lot of thingslike just organizationally
that they're stressed about.
(06:57):
Like the business modelof schools is difficult.
Teachers aren't paid enough.
They have state regulations,they have to meet
federal regulations.
And so like the learner endsup becoming last actually,
which is sad but true.
Right?
So that's one example.
The example in that, likethat we always say in like
enterprise learning is.
On average, it takes like sevenclicks to get into the learning
you need to access, right?
You have to open a website,you have to log in, you
(07:19):
have to click into a video,you have to start it.
You have to approve somelike security approval thing.
By the time you get there,you're like, okay, gotta run
and like pick up my kids orwalk my dog, or whatever, right?
And so that's just like a simpleexample, but it is, there's a
lot of barriers to like justgetting the information you
need to like do your job, right?
Or to like performor learn better.
Hannah Clark (07:40):
I do think that there is like a lot to
be said about kind of takingthese existing behaviors and
just kind of building on themrather than kind of asking
of people to sort of reinventthe wheel when you're trying
to teach them something.
There's the thing you want themto learn, but then there's also
the how to get there and carvingout time for all of that.
Maxine Anderson (07:57):
You know, I always say technology should
like reduce complexity,especially as product people
like wanna build or engineerswanna build like the fanciest
products and like it'samazing and beautiful, but
it's like but is anyone gonnaeven be able to like engage
with it or use it, right?
So yeah, I think that's areally important principle.
Hannah Clark (08:13):
Yeah, absolutely.
So we talked a little bitbeforehand and you've mentioned
sort of this idea of havingtwo to three things that
most people really need toknow about a specific topic.
How does that kind ofprinciple inform how you
deliver content on Arist?
And just like your approachto learning in general.
Maxine Anderson (08:31):
Like I mentioned, we wanna reduce like
the barrier or access to likewhat people really need to know.
And we want people to getinformation that they actually
need at the right time.
And so we believe thatthe gap really in how
organizations work today.
So like you, good, you know,sales reps, for example,
they drown in playbooks, inframeworks and they're required
(08:52):
to go through all the training.
It's amazing content.
But when they're aboutto walk into a meeting.
What are the two thingsthey need to know to say
in that meeting to win thedeal or move it forward?
Right?
They don't need 200 pagesbefore that meeting, right?
And so there is a place formore in-depth, more in-depth
coaching, et cetera, but there'sa gap in like solutions and
learning out there that isn'tsolving for like what the most
(09:14):
important things to know are.
And we've truly seen thattraining in organizations
and just in general isn'tbroken because the content
is bad by any means.
It's because it's notdesigned around people's
mo like the moment of need.
Right.
And actually one of our clientsis redesigning, like moving away
from skills and capabilitiesto like more of a product
mindset, which is like what arethe jobs to be done on like an
(09:35):
average weekly basis when theyinteract with tools and that's
helping them like integrateAI more, which is interesting.
Just to give another example.
One of our clients is likeone of the oldest insurance
companies in the world, andthey were struggling with
training service reps toincrease like CSAT scores.
Basically, they adopted Aristto try to solve the problem,
and a lot of their learningdesigners were like, no way.
We cannot reduceinformation by this much.
(09:57):
We can't make it 1200characters, which is like
the forcing function weput into our product.
And they honestlyfought against it a lot.
We said, okay, justtry our AI tool, like
try to write it short.
And they actually came backsaying like, that was a really
good exercise because I realizedhow 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 actuallynot like super critical.
(10:18):
And so they push it out andthey increased like CSAT scores
by, I think it was like 20%or something from like a three
lesson course because theyjust were able to like actually
narrow down parts information.
And like still like six monthslater I met again with them.
They said, I still like anytool I use, I put way less
information because of Arist.
So yeah, I think the forcingfunction of like, what do
people actually need to know?
And it applies in marketing andlearning, like in a lot of it's
(10:39):
just like human psychology, likepeople can only consume so much.
Hannah Clark (10:43):
What comes to mind for me is user onboarding.
Like how many times have youhad an onboarding experience
where it's just like, ohmy gosh, I feel like I'm
reading a tome just toget 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'relistening to this podcast,
please take to heart.
Users can only take so manypieces of information at once.
So, yeah, I think this isa really good principle to
(11:04):
embody and this is somethingI think that is useful in
all forms of communication aswell, because I think we have
a tendency to think, not justin product, but in general,
that by over-explaining orproviding all the information
up front that we are givingeverybody what they need.
Often I think thattends to backfire.
So I think this is a,such a, like it is a cool
exercise to just review anyform of communication or
(11:27):
learning and pare it down tolike the absolute minimum.
Okay.
Let's talk a little bit aboutjust the idea of, now that
we've talked about consumingcontent, getting people to
actually put it into practice,like now that you've delivered
the information, how doyou kind of ensure that the
actual skill that you'retrying to deliver is in place?
Maxine Anderson (11:47):
A couple things we look at, so we've done our
own research on what drives.
So like most learning toolstrack things that I call
our, like leading metrics ofpotential behavior change,
which are like, okay, youcompleted a course, or like
you got a certificationfor a skill, right?
It's like, okay, they're morelikely to perform better.
Right?
We look at a couple thingslike one, we look at confidence
(12:08):
lift, so our AI evaluatesif someone's like confidence
and like ability to liketalk about the subject has
changed throughout the course.
And then we basicallyshow confidence lift.
And we pull data from othersystems that basically measure
if a change has happened.
So an example for like asales rep could be like gong
basically their confidencein like following this
(12:29):
messaging framework increased.
And in gong we pull like theyhave like insights and they
have like pillars of like whatreps are like saying in meetings
and so we can like pull that.
Basically provide it backto admin and say, okay, you
like, after this course,within 10 days, these
pillars on like successrate, like shifted basically.
So we're always trying to, like,we're trying to change behavior
like just in organizations ofhow admins and like I should
(12:53):
say, like enablement leadersand leadership delivers
training internally that theythink first of like, what
is the actual like businessproblem or business outcome
that we're trying to solve.
Versus like taking in anlike incoming like training
request and then likesaying someone has a skill.
And so like with our tool also,we're trying to change the
behavior of how like needs arefulfilled in our organization so
(13:13):
that leaders have a pulse on allthe data in their organization
and can rapidly close gapsthat exist versus having a
long lead up time on theseanalysis, taking in a bunch of
requests, prioritizing them,and then missing, you know,
like 75% of closing those gaps.
And you know, something we'vealso learned is like, and any
(13:34):
of our clients will tell youthis is like most other teams
that go to central like learningand development teams or HR
to like solve the problem.
They basically are like.
A lot of times the prom's nottraining, like they actually
don't need more enablement.
It's that like the messagingframework doesn't make sense
or like people need moretime with their manager.
Right?
Like sometimes the problem andthe solution's not learning
actually sometimes, even thoughorganizations default to it.
(13:56):
So it's like your salesteam'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, wellit's not actually like.
Probably gonnasolve the problem.
So that's what we see inorganizations is like, just
back to your original question,is that the way that we track
performance is like, we do workreally closely with leaders and
we're trying to like make thatmore automated and with like
agent AI and pulling informationfrom different systems to like
(14:19):
really prove that enablementand like targeted actions or
like that are, you know, sentas nudges to people through
Arist are actually like drivinga change in how they behave or
how they perform in their jobs.
So we're always trying towork towards that wholly
grail of measuring successbecause most learning tools
just like candidly, theyjust like can't get there.
And so like what's used asa default instead is like
(14:41):
certifications or otherthings that like point to like
potential change of behavior.
Hannah Clark (14:46):
Another thing that I think is really interesting
about the delivery methodof Arist is this element of.
Personalization and being ableto kind of emulate to some
extent the experience of beingtaught directly by a teacher.
And I think that the socialaspect and the relationship
aspect of learning issomething that I think also
is kind of missed by a lotof the traditional corporate
(15:06):
training methodology.
You know, the online coursesand that kind of thing that are
very content focused but arekind of void of having that more
of like a relational aspect.
So was that kind of a partof how you guys conceived
of it or have you kind ofnoticed anything that's kind
of interesting or a byproductof having this approach that
does kind of emulate moreof a personal connection?
Maxine Anderson (15:28):
Yeah I dunno if I can speak to the
personal connection as much.
There was like a phase of toolslike three years ago that was
like social learning and likeevery, like you, it seems
like you're learning from yourmanager and I think that like,
it's valid, but we actuallytry to abstract a way like.
That component and gamificationfor like the same reason, which
is that if we believe that yougive someone like only what
(15:48):
they need and then they liketrust 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, andis what like goes with what
you're saying is that peopleshare a lot more over text,
like open-ended and thelearning experience can be
personalized and more whenit's a one-to-one relationship.
I think what we mastered withArist is that it's an at scale
(16:10):
learning solution, but you'recreating one-to-one experiences.
Most learning tools are likemade in it for enterprise or
like at scale solutions, butit's like everyone's is very
much the same and it is throughlike a platform, which in itself
makes it feel less personable.
It's different than like, we'renot like personifying like
another person in a companynecessarily, but I do see
what you're saying and likeit makes a big difference.
(16:32):
And that's what I meantby like the context, like
also psychological safety.
And like just sharing anything,like people go through courses
and it's like, okay, if likean exec is asking you as a new
manager what you're strugglingwith, like you probably have a
lot of reasons you don't wannashare, but like over a text, if
the course is gonna help you andit's like made for you, that's
gonna change the way you respondand like probably help you more
(16:52):
'cause you're more vulnerable.
Hannah Clark (16:54):
Yeah, absolutely.
And there's that conversationelement that I think just
kind of facilitates morejust open-ended learning.
I haven't personally usedthe platform, so, you know,
maybe I wanna, I don't wannastep too far in a turn, but
I just think it's a reallyamazing delivery method.
Okay.
So tell me a little bit abouthow AI has sort of figured in,
you know, where are you guysseeing AI in terms of like the
(17:16):
story of your product right now,and kind of where do you see
that sort of fitting in generalat this kind of, I would maybe
even call this kind of a nextgeneration method of education.
Maxine Anderson (17:28):
So I'll say like what we're not solving, but
I think is valid, like there area lot of like AI role playing
and coaching and adaptivelearning tools out there.
I think we've realizedthat basically a lot of the
reason that learning endsup not being like learner
focused, or I should sayemployee focused or like the
employees not at the center,is because of honestly, like
(17:50):
how messy the administrativeoverload and burden is.
Across teams and organizationto coordinate to get effective
enablement out there.
And so what we've decided totackle is like essentially
changing the way that anorganization approaches
doing learning from like atop down approach, right?
So the first thing I'll saythere is that like one of our
(18:12):
early observations was like,okay, most people do wanna learn
in an organization, but theydon't pull learning, right?
Why is that?
Because it's not builtfor the way they need
and whatever, right?
But there's also not many toolsout there that are built other
than compliance learning, thatare built for like pushing,
learning based on likeorganizational intelligence.
So the first layer is like,you assume humans have that.
(18:32):
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, youshould be able to push learning
to people when they need it.
So we are like an AI enablementtool and what we say is like.
Or like the solution tolike instant enablement
in your organization?
I don't mean justlike sales enablement.
I mean we use enablementbroadly for like learning
(18:53):
anything that helps peopleperform better basically.
So our AI does everythingfrom understanding needs
an organization to creatingit and then analyzing if
there's performance gaps.
What we've found is thatentire process is shifting.
So historically in organizationslike large enterprise, you
know, you have business unitfunctions like a CRO, Chief
Revenue Officer, and theyhave to go to, like, they have
all these new sales reps, thenew sales onboarding program,
(19:15):
they either have like anenablement team on their team,
which a lot of sales teams do.
But let's say you're likean ops team, you have
to go to like centrallearning and development.
It goes into their queue.
Then they basically do like anexpanded needs analysis on it.
So then they interview likehundreds of ops people, or I
dunno, ops leaders get insightsand then they say, okay, great.
Now we have all these insights.
(19:35):
Now as humans, which we knowtakes a while to process,
we're gonna process thisinformation, decide what to do.
Now we're going tocreate training.
Now it has to go through allthe approval processes, which
is a lot of back and forth.
And now after it's gone throughall the approval processes,
we're gonna come back.
Now we have to like translateit and version it for different
groups in the organization.
And then we're gonna launchit and then we're gonna like
try to get people to adopt it.
(19:56):
Right?
So that whole process takes like40 weeks, like minimum, right?
Woo.
What's changed completely andlike where Arist fits in is
that businesses are changingfaster than ever before because
it's so much, especially techcompanies, but other companies
as well, because it's so fastto build product now that
like the rest of the companyliterally can't keep up.
(20:16):
And so basically thesecompanies have like all this
revenue potential and they'rejust like bleeding money.
Like one of a really well knownlike tech companies, one of
our clients, they just iPodand they like keep shipping
features, like AI features,keep shipping features.
They literallyjust can't keep up.
And so like their supportreps aren't enabled.
Their sales reps aresaying the wrong things.
They aren't driving likesuccess of those AI tools.
And so like, it's a huge gap.
(20:36):
And so what we're realizingand fitting in is that like.
Arist like end-to-endsolution is basically like
an orchestration engine onunderstanding like, okay, this
is what we're working towards.
Right?
And like what we're helpingour clients with is like, this
release is coming up, it's likein, you know, writing launch.
Now we're gonna pull notes fromall the relevant tools like,
you know, the commit the gi,you know, from GitHub or like
(20:57):
linear notes or whatever it is.
Jira, you know,anything from there.
And then basically like spinup content and like basically
create versions based on thedifferent teams, get quick
approval and send it out.
So like AI also needs to knowlike when to get human approval.
But you can imagine that thenthat makes like people in
that organization, in a techcompany or whatever, rather
than being maybe like a learningdesigner specialist, they're
(21:19):
basically like being the humanapprover or like pointing it
in the right direction basedon like business challenges.
So they become more oflike an orchestrator.
Rather than like maybe aspecialist in their job
is kind of the way thatwe're seeing it change.
And so like workflows justhave to change completely,
and that's like very painfulin a large enterprise.
So there's just tons ofproblems right now with that.
But like you can tack on amillion AI features to like, you
(21:42):
know, other learning tools thatexist that are like traditional
corporate learning tools, butit just doesn't change the
way that people work enoughto like actually meet the
needs of organizations today.
And so that's why we tooklike a ground up approach
to building like a tool thatis optimized around like
business outcomes versus likehow humans do the work today.
Hannah Clark (21:59):
Yeah, and I really resonate also
with this idea of peoplebecoming more orchestrators.
I think that we've discussedthat before on the show.
We've kind of thrown aroundthis idea of ai kind of,
actually, kind of in a waybuilding people's management
skillset, because you'resort of acting more in the
mindset of a people managerwhen you're directing agents,
for example, or when you'rekind of reviewing and kind of
(22:21):
guiding information, ratherthan just sort of building from
scratch and kind of, you know,throwing spaghetti at the wall.
So I think that's kind ofinteresting how like we're
seeing this kind of in multipledifferent verticals how
this kind of effect of Yeah,orchestration and guiding
things and kinda refiningrather than having to kinda
build, interpret, do allof these things manually.
I think that's might bethe biggest thing in, in
(22:43):
all AI advancements lately.
So now that we're kind of atthis point in the company,
what would you say has beenthe most significant lesson
like this is, it sounds likequite a journey for you.
You know, this all startedfrom your experiences in
rural Oregon and now you knowyou're working with enterprise
clients and this has been likea relatively short period of
time, if I'm not mistaken.
(23:04):
In the last several yearsthat you've been working in
your capacity, what have youlearned that you think is
like the most impactful thatyou would want other people,
other founders, other peoplein the education space to know?
Maxine Anderson (23:15):
Yeah, I think whether it's called education,
learning, enablement, whateverit is, like I always view
it, the goal is that you'rehelping someone realize
their potential to accomplishwhat they want in life.
Basically, like that'sthe 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 theworld 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
(23:37):
that is not accomplished throughthe best content in the world.
It's accomplished throughproviding the right context to
the learning and by basicallylike bumping into problems.
Right?
And that sounds weird, butlike even technology should
get people to do that.
Like don't sit and likeconsume three hours of
(23:57):
video training, right?
Like people need to, andthis is done, but like.
Anyone building technologyor implementing whatever it
is like should really focuson like how do you get people
to like bump into problems alittle bit more like practice?
And that's when it likereally sticks in their head.
And how do you create thatexperience in context when
it's like needed the most?
Right?
I always talk aboutlike podcasts are the
(24:18):
party example for me.
I love listening to podcasts.
I listen to all the time.
Like 10% of them like driveme to like change anything.
And it's because I likehappen to listen to it.
Like the day before I facedthat problem or like that
night, I like listened tothe podcast and I faced a
problem earlier in the day.
And so like I think contextis like super important and
creating that context forpeople is really important.
I also.
(24:39):
I think it's interesting andlike curious people and like
you can learn knowledge, butlike, you know, our goal with
our technology at least is notlike for people to just learn.
It's for people to likeactually change their behavior,
perform better, like feelthe impact of that learning.
So I think it's like, youknow, great content is totally
necessary, but I think it'sjust like what we've learned
is just not what drivespeople to like actually.
(24:59):
Gain a new skill or somethingis like, it's just not, it's
just not through content.
I know people who likeconsume the most content ever
on like product managementand like still struggle
with like the day-to-day oflike how to get something
like actually out there.
Right?
So I think it's just like humanbehavior, like needs practice
and it needs like, you need tolike provide that context so
that people can like actually,you know, understand and like
utilize the content basically.
Hannah Clark (25:21):
I completely agree.
We actually, we were for along time hosting panel events
and kinda like live events.
And over, over time we werekind of figuring out like,
how do we make these better?
How do we makethese more useful?
And one of the thingsthat we kind of thought
we would experiment withwas doing something that
was a lot more hands-on.
So we ran a vibe codingworkshop and it was a similar
format where we would havea facilitator still leading
(25:43):
it, we would still havehosts and that kind of thing.
But what we did was we toldpeople to come prepared with a
few of these different supplies,have some accounts built, kinda
already have a platform inmind, or a concept that they
wanted to try to prototype.
And just by making theformat more following along,
rather than just listeningand taking in all this
(26:03):
information that withoutcontext can be very abstract.
We got way betterparticipation levels.
We got way better people.
I guess as far as thepercentage of people that
stayed throughout the entirething, people who gave us great
feedback about how many skillsthat they actually retained.
It was just night and day.
So I yeah, like firsthand, Ican say that context piece is
(26:24):
super, super, super critical.
Maxine Anderson (26:26):
Yeah.
And one response islike, there's just
nothing more frustrating.
Like, have you ever heardsomeone say something
like, so intelligent?
You're like, okay,stick it in my mind.
I'm gonna use thatin my next meeting.
And like, you just forget it.
You're like, oh, like I wasgonna like come to this meeting.
So smart.
Like I, I heard the best tidbitfrom someone, like there's
value to that, but like,there's an opportunity with
ai, like just being able togenerate content on the fly to
(26:47):
like give people information.
Like if you add goodautomation, integrated data.
When they need it.
And that's like so powerful.
Like that's like an, itcan be a serious engine
for an organization.
So yeah, I'm excited to seehow it changes learning.
Hannah Clark (27:00):
Same to here, and I'm a little bit
disheartened to hear thatthis actually means that
homework is actually valuable.
Oh, no.
Anyway, thank you so muchfor joining us today, Maxine.
This was a really fun chat.
Where can listeners followyour work online and find
out more about Arist as well?
Maxine Anderson (27:12):
Yeah, so we're at www.arist.co.
I post a lot on LinkedIn aboutwhat learning and reinventing
learning organizations forthe future of work looks like.
So I'm at MaxineAnderson on LinkedIn.
Hannah Clark (27:23):
Cool.
Well thank you somuch for being here.
Maxine Anderso (27:25):
Yeah, thank you.
Hannah Clark (27:28):
Next on The Product Manager podcast.
Now that you know how peoplelearn, our next episode is
all about how people buy.
We'll be digging into buyerpsychology and the small
tweaks you can make to yourcustomer touch points that
boost conversion, driveadoption, and fill the cracks
in your growth strategy.
You don't wanna miss this one.
So subscribe now to jumpin with us next time.
You are listening to The Product Manager podcast,
(00:02):
presented by The CPO Club.
Make sure to subscribe andcheck out cpoclub.com for
more exclusive content.
Before we begin, you needto know that this is a
really important episode foreveryone in product to hear.
Not just because it willhelp you gain new skills,
but because it addresses acrucially important factor
that impacts the effectivenessof every aspect of your
(00:23):
organization — learning.
Because when you think aboutit, everything from your
leadership approach, to yourproduct's onboarding flow, to
your GTM strategy, connectsto how good your organization
is at understanding how peoplelearn new habits and skills.
And let's be honest, in atleast one of those areas, most
companies are not nailing it.
But after recording theepisode you're about to
(00:45):
hear, I am convinced that thebest-kept secret to success
is to think like a teacher.
My guest today is MaxineAnderson, the Co-Founder
and CPO of Arist, atext-based learning platform.
Before Maxine was afounder, she was a teacher.
And I am not exaggerating whenI say that I was blown away
by the brilliant simplicityof Arist as a concept.
What I really want you tohear is Maxine's profound
(01:06):
understanding of how peoplelearn, and not only how
deeply it connects to anorganization's most important
markers of success, but howcostly it is to miss the mark.
You'll hear why more informationdoesn't equal more learning,
the opportunities for improvingstakeholder and customer
outcomes that most companiesmiss, and the role of generative
AI in changing how we learn,teach, and get results.
(01:27):
Let's jump in.
Oh, by the way, we holdconversations like this
every week, so if thissounds interesting to
you, why not subscribe?
Okay, now let's jump in.
Welcome back to TheProduct Manager podcast.
Maxine, thank you for makingtime to talk to us today.
Maxine Anderson (01:43):
Yeah, sure.
I'm super excited.
Hannah Clark (01:45):
So can you tell us a little bit about
your background and how yougot to where you are today?
Maxine Anderson (01:49):
So I actually started out teaching in rural
Oregon where I was buildingeducational programs with
almost zero resources, and Iwas trying to figure out how
you can create impact througheducational experiences on
students, like the impact thatteachers make on students, which
I felt was very personalized.
And so in that experience,I saw how broken access to
(02:12):
learning was and how traditionaleducation mediums didn't really
address person to person needs.
So fast forward to college.
I co-founded Arist with mytwo friends in college who
were also working in theeducation nonprofit space.
To say, basically solve thesame problem, but at scale,
which was always what I wastrying to do, which is how do
you get the right skills orinformation to people without
(02:36):
the overhead of the classroom,a learning management system
or a traditional educationalprogram, essentially.
And so that's how Icame to Star Arist.
We just found that a majorityof someone's life is in the
workforce, and so enterpriselearning is where we can
make the most impact.
Hannah Clark (02:51):
Yeah, that makes total sense and it's
such a cool mission as well.
So I wanna know a little bitmore about kind of how you guys
put your minds together to thinkabout the concept for Arist.
And actually maybe you can walkus through a little bit how it
works 'cause I think it's justsuch an innovative product.
Maxine Anderson (03:04):
Yeah.
Put simply how our productworks is we deliver information
and learning to peoplethrough messaging tools
that they use every day.
So text.
Slack, Microsoft teams in theworkplace, Microsoft teams
and text and Slack are used alot, you know, for people out
in the field or really anyonelike text is super accessible
and so delivering, learningthat way is, ends up being
(03:25):
really effective and we havean end-to-end platform for
creation delivering analytics.
With AI built in throughoutthat entire experience to really
help change how organizations dolearning for this way of working
now, which is changing a lot.
Hannah Clark (03:40):
Yeah, I think it's just such a cool, and
like I'm such a fan of productthat really kind of comes back
to the existing competenciesand functionalities that we
are already familiar withand kind of expands on those
in ways that are innovative.
So I do wanna talk a little bitabout barriers that you people
face in general with learning.
And you kind of mentioneda few with the kinds of
(04:00):
examples of folks that youand your colleagues were
working with, but I thinkin general there's certain
barriers to learning that allof us kind of encountered,
and especially in the workat enterprise learning space.
So what did you kind of discoverthat kinda led you to think
about this alternative wayof delivering information?
Maxine An (04:18):
Yeah, great question.
I think I'll talk aboutlike, you know, in product we
talk about like aha moments.
So in terms of barriers, likeI realized in my education
experience, like as a teacher,especially in rural Oregon.
Learning isn't alwaysabout content, it's
really about like context.
And what I mean by that isI was trying to educate some
(04:40):
of these students on likefinancial literacy training
and honestly, they're just likeembarrassed to go to class or
they don't have time to sitlike between work and school.
Like they're not gonnasit through like hours
of video training.
And so.
I think that I realizedthat like there's so much
information, we're in aninformation age, or at least
we're like moving outtathat, but like we were for
so long, the barrier isn'tlike knowledge, it's like
(05:01):
psychology and like contextof like how to make it
possible for someone to learn.
And a lot of traditionalformats actually make
those barriers worse.
While like I found thatArist, you know, me and
my co-founders all haddifferent aha moments like.
We basically couldn't getover the fact of like how
simple Arist was as a solutionfor such a complex set of
(05:22):
problems like education.
Once you start digging intolike the educational system and
how people learn and like, it'sjust really complex and I was
overwhelmed by that like outof high school and I found it
so motivating how simple Aristlike where you just deliver
information to people overtext, you have the opportunity
to automate it and give it topeople right when they need it.
I just found that howsimple it was like so
(05:44):
contagious as an idea.
And I think that my co-foundersexperienced something simply
like it was the first momentI heard Michael share with me.
'cause you know, we livedin entrepreneurship, living
community and shared with melike, oh yeah, I'm sending
information to studentsin Yemen over text about
like entrepreneurship.
That's the onlyway to reach them.
I'm like, everyone uses text.
How is that not usedas a learning medium?
(06:05):
I asked him, like, I,I literally asked him
like, oh, what technologyare you using for that?
And he is like, no, I'm justlike texting people manually.
And I was like, howdoes that not exist?
It's such a simple,overlooked solution to like,
education, which has likea lot of complex challenges
basically that don't put thelearner first in my opinion.
Hannah Clark (06:21):
I tend to agree with you.
I'm curious when yousay traditional learning
mediums sort of.
Amplify almost someof these challenges.
What do you mean by that?
I'm kind of curious about someexamples where the traditional
style is kind of not reallymeeting learners halfway.
Maxine Anderson (06:35):
Yeah.
I mean in, in two places, right?
So like, when I work more intraditional 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 toschool is a barrier.
The other barrier is like theschool has mixed incentives.
They have a lot of thingslike just organizationally
that they're stressed about.
(06:57):
Like the business modelof schools is difficult.
Teachers aren't paid enough.
They have state regulations,they have to meet
federal regulations.
And so like the learner endsup becoming last actually,
which is sad but true.
Right?
So that's one example.
The example in that, likethat we always say in like
enterprise learning is.
On average, it takes like sevenclicks to get into the learning
you need to access, right?
You have to open a website,you have to log in, you
(07:19):
have to click into a video,you have to start it.
You have to approve somelike security approval thing.
By the time you get there,you're like, okay, gotta run
and like pick up my kids orwalk my dog, or whatever, right?
And so that's just like a simpleexample, but it is, there's a
lot of barriers to like justgetting the information you
need to like do your job, right?
Or to like performor learn better.
Hannah Clark (07:40):
I do think that there is like a lot to
be said about kind of takingthese existing behaviors and
just kind of building on themrather than kind of asking
of people to sort of reinventthe wheel when you're trying
to teach them something.
There's the thing you want themto learn, but then there's also
the how to get there and carvingout time for all of that.
Maxine Anderson (07:57):
You know, I always say technology should
like reduce complexity,especially as product people
like wanna build or engineerswanna build like the fanciest
products and like it'samazing and beautiful, but
it's like but is anyone gonnaeven be able to like engage
with it or use it, right?
So yeah, I think that's areally important principle.
Hannah Clark (08:13):
Yeah, absolutely.
So we talked a little bitbeforehand and you've mentioned
sort of this idea of havingtwo to three things that
most people really need toknow about a specific topic.
How does that kind ofprinciple inform how you
deliver content on Arist?
And just like your approachto learning in general.
Maxine Anderson (08:31):
Like I mentioned, we wanna reduce like
the barrier or access to likewhat people really need to know.
And we want people to getinformation that they actually
need at the right time.
And so we believe thatthe gap really in how
organizations work today.
So like you, good, you know,sales reps, for example,
they drown in playbooks, inframeworks and they're required
(08:52):
to go through all the training.
It's amazing content.
But when they're aboutto walk into a meeting.
What are the two thingsthey need to know to say
in that meeting to win thedeal or move it forward?
Right?
They don't need 200 pagesbefore that meeting, right?
And so there is a place formore in-depth, more in-depth
coaching, et cetera, but there'sa gap in like solutions and
learning out there that isn'tsolving for like what the most
(09:14):
important things to know are.
And we've truly seen thattraining in organizations
and just in general isn'tbroken because the content
is bad by any means.
It's because it's notdesigned around people's
mo like the moment of need.
Right.
And actually one of our clientsis redesigning, like moving away
from skills and capabilitiesto like more of a product
mindset, which is like what arethe jobs to be done on like an
(09:35):
average weekly basis when theyinteract with tools and that's
helping them like integrateAI more, which is interesting.
Just to give another example.
One of our clients is likeone of the oldest insurance
companies in the world, andthey were struggling with
training service reps toincrease like CSAT scores.
Basically, they adopted Aristto try to solve the problem,
and a lot of their learningdesigners were like, no way.
We cannot reduceinformation by this much.
(09:57):
We can't make it 1200characters, which is like
the forcing function weput into our product.
And they honestlyfought against it a lot.
We said, okay, justtry our AI tool, like
try to write it short.
And they actually came backsaying like, that was a really
good exercise because I realizedhow 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 actuallynot like super critical.
(10:18):
And so they push it out andthey increased like CSAT scores
by, I think it was like 20%or something from like a three
lesson course because theyjust were able to like actually
narrow down parts information.
And like still like six monthslater I met again with them.
They said, I still like anytool I use, I put way less
information because of Arist.
So yeah, I think the forcingfunction of like, what do
people actually need to know?
And it applies in marketing andlearning, like in a lot of it's
(10:39):
just like human psychology, likepeople can only consume so much.
Hannah Clark (10:43):
What comes to mind for me is user onboarding.
Like how many times have youhad an onboarding experience
where it's just like, ohmy gosh, I feel like I'm
reading a tome just toget 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'relistening to this podcast,
please take to heart.
Users can only take so manypieces of information at once.
So, yeah, I think this isa really good principle to
(11:04):
embody and this is somethingI think that is useful in
all forms of communication aswell, because I think we have
a tendency to think, not justin product, but in general,
that by over-explaining orproviding all the information
up front that we are givingeverybody what they need.
Often I think thattends to backfire.
So I think this is a,such a, like it is a cool
exercise to just review anyform of communication or
(11:27):
learning and pare it down tolike the absolute minimum.
Okay.
Let's talk a little bit aboutjust the idea of, now that
we've talked about consumingcontent, getting people to
actually put it into practice,like now that you've delivered
the information, how doyou kind of ensure that the
actual skill that you'retrying to deliver is in place?
Maxine Anderson (11:47):
A couple things we look at, so we've done our
own research on what drives.
So like most learning toolstrack things that I call
our, like leading metrics ofpotential behavior change,
which are like, okay, youcompleted a course, or like
you got a certificationfor a skill, right?
It's like, okay, they're morelikely to perform better.
Right?
We look at a couple thingslike one, we look at confidence
(12:08):
lift, so our AI evaluatesif someone's like confidence
and like ability to liketalk about the subject has
changed throughout the course.
And then we basicallyshow confidence lift.
And we pull data from othersystems that basically measure
if a change has happened.
So an example for like asales rep could be like gong
basically their confidencein like following this
(12:29):
messaging framework increased.
And in gong we pull like theyhave like insights and they
have like pillars of like whatreps are like saying in meetings
and so we can like pull that.
Basically provide it backto admin and say, okay, you
like, after this course,within 10 days, these
pillars on like successrate, like shifted basically.
So we're always trying to, like,we're trying to change behavior
like just in organizations ofhow admins and like I should
(12:53):
say, like enablement leadersand leadership delivers
training internally that theythink first of like, what
is the actual like businessproblem or business outcome
that we're trying to solve.
Versus like taking in anlike incoming like training
request and then likesaying someone has a skill.
And so like with our tool also,we're trying to change the
behavior of how like needs arefulfilled in our organization so
(13:13):
that leaders have a pulse on allthe data in their organization
and can rapidly close gapsthat exist versus having a
long lead up time on theseanalysis, taking in a bunch of
requests, prioritizing them,and then missing, you know,
like 75% of closing those gaps.
And you know, something we'vealso learned is like, and any
(13:34):
of our clients will tell youthis is like most other teams
that go to central like learningand development teams or HR
to like solve the problem.
They basically are like.
A lot of times the prom's nottraining, like they actually
don't need more enablement.
It's that like the messagingframework doesn't make sense
or like people need moretime with their manager.
Right?
Like sometimes the problem andthe solution's not learning
actually sometimes, even thoughorganizations default to it.
(13:56):
So it's like your salesteam'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, wellit's not actually like.
Probably gonnasolve the problem.
So that's what we see inorganizations is like, just
back to your original question,is that the way that we track
performance is like, we do workreally closely with leaders and
we're trying to like make thatmore automated and with like
agent AI and pulling informationfrom different systems to like
(14:19):
really prove that enablementand like targeted actions or
like that are, you know, sentas nudges to people through
Arist are actually like drivinga change in how they behave or
how they perform in their jobs.
So we're always trying towork towards that wholly
grail of measuring successbecause most learning tools
just like candidly, theyjust like can't get there.
And so like what's used asa default instead is like
(14:41):
certifications or otherthings that like point to like
potential change of behavior.
Hannah Clark (14:46):
Another thing that I think is really interesting
about the delivery methodof Arist is this element of.
Personalization and being ableto kind of emulate to some
extent the experience of beingtaught directly by a teacher.
And I think that the socialaspect and the relationship
aspect of learning issomething that I think also
is kind of missed by a lotof the traditional corporate
(15:06):
training methodology.
You know, the online coursesand that kind of thing that are
very content focused but arekind of void of having that more
of like a relational aspect.
So was that kind of a partof how you guys conceived
of it or have you kind ofnoticed anything that's kind
of interesting or a byproductof having this approach that
does kind of emulate moreof a personal connection?
Maxine Anderson (15:28):
Yeah I dunno if I can speak to the
personal connection as much.
There was like a phase of toolslike three years ago that was
like social learning and likeevery, like you, it seems
like you're learning from yourmanager and I think that like,
it's valid, but we actuallytry to abstract a way like.
That component and gamificationfor like the same reason, which
is that if we believe that yougive someone like only what
(15:48):
they need and then they liketrust 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, andis what like goes with what
you're saying is that peopleshare a lot more over text,
like open-ended and thelearning experience can be
personalized and more whenit's a one-to-one relationship.
I think what we mastered withArist is that it's an at scale
(16:10):
learning solution, but you'recreating one-to-one experiences.
Most learning tools are likemade in it for enterprise or
like at scale solutions, butit's like everyone's is very
much the same and it is throughlike a platform, which in itself
makes it feel less personable.
It's different than like, we'renot like personifying like
another person in a companynecessarily, but I do see
what you're saying and likeit makes a big difference.
(16:32):
And that's what I meantby like the context, like
also psychological safety.
And like just sharing anything,like people go through courses
and it's like, okay, if likean exec is asking you as a new
manager what you're strugglingwith, like you probably have a
lot of reasons you don't wannashare, but like over a text, if
the course is gonna help you andit's like made for you, that's
gonna change the way you respondand like probably help you more
(16:52):
'cause you're more vulnerable.
Hannah Clark (16:54):
Yeah, absolutely.
And there's that conversationelement that I think just
kind of facilitates morejust open-ended learning.
I haven't personally usedthe platform, so, you know,
maybe I wanna, I don't wannastep too far in a turn, but
I just think it's a reallyamazing delivery method.
Okay.
So tell me a little bit abouthow AI has sort of figured in,
you know, where are you guysseeing AI in terms of like the
(17:16):
story of your product right now,and kind of where do you see
that sort of fitting in generalat this kind of, I would maybe
even call this kind of a nextgeneration method of education.
Maxine Anderson (17:28):
So I'll say like what we're not solving, but
I think is valid, like there area lot of like AI role playing
and coaching and adaptivelearning tools out there.
I think we've realizedthat basically a lot of the
reason that learning endsup not being like learner
focused, or I should sayemployee focused or like the
employees not at the center,is because of honestly, like
(17:50):
how messy the administrativeoverload and burden is.
Across teams and organizationto coordinate to get effective
enablement out there.
And so what we've decided totackle is like essentially
changing the way that anorganization approaches
doing learning from like atop down approach, right?
So the first thing I'll saythere is that like one of our
(18:12):
early observations was like,okay, most people do wanna learn
in an organization, but theydon't pull learning, right?
Why is that?
Because it's not builtfor the way they need
and whatever, right?
But there's also not many toolsout there that are built other
than compliance learning, thatare built for like pushing,
learning based on likeorganizational intelligence.
So the first layer is like,you assume humans have that.
(18:32):
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, youshould be able to push learning
to people when they need it.
So we are like an AI enablementtool and what we say is like.
Or like the solution tolike instant enablement
in your organization?
I don't mean justlike sales enablement.
I mean we use enablementbroadly for like learning
(18:53):
anything that helps peopleperform better basically.
So our AI does everythingfrom understanding needs
an organization to creatingit and then analyzing if
there's performance gaps.
What we've found is thatentire process is shifting.
So historically in organizationslike large enterprise, you
know, you have business unitfunctions like a CRO, Chief
Revenue Officer, and theyhave to go to, like, they have
all these new sales reps, thenew sales onboarding program,
(19:15):
they either have like anenablement team on their team,
which a lot of sales teams do.
But let's say you're likean ops team, you have
to go to like centrallearning and development.
It goes into their queue.
Then they basically do like anexpanded needs analysis on it.
So then they interview likehundreds of ops people, or I
dunno, ops leaders get insightsand then they say, okay, great.
Now we have all these insights.
(19:35):
Now as humans, which we knowtakes a while to process,
we're gonna process thisinformation, decide what to do.
Now we're going tocreate training.
Now it has to go through allthe approval processes, which
is a lot of back and forth.
And now after it's gone throughall the approval processes,
we're gonna come back.
Now we have to like translateit and version it for different
groups in the organization.
And then we're gonna launchit and then we're gonna like
try to get people to adopt it.
(19:56):
Right?
So that whole process takes like40 weeks, like minimum, right?
Woo.
What's changed completely andlike where Arist fits in is
that businesses are changingfaster than ever before because
it's so much, especially techcompanies, but other companies
as well, because it's so fastto build product now that
like the rest of the companyliterally can't keep up.
(20:16):
And so basically thesecompanies have like all this
revenue potential and they'rejust like bleeding money.
Like one of a really well knownlike tech companies, one of
our clients, they just iPodand they like keep shipping
features, like AI features,keep shipping features.
They literallyjust can't keep up.
And so like their supportreps aren't enabled.
Their sales reps aresaying the wrong things.
They aren't driving likesuccess of those AI tools.
And so like, it's a huge gap.
(20:36):
And so what we're realizingand fitting in is that like.
Arist like end-to-endsolution is basically like
an orchestration engine onunderstanding like, okay, this
is what we're working towards.
Right?
And like what we're helpingour clients with is like, this
release is coming up, it's likein, you know, writing launch.
Now we're gonna pull notes fromall the relevant tools like,
you know, the commit the gi,you know, from GitHub or like
(20:57):
linear notes or whatever it is.
Jira, you know,anything from there.
And then basically like spinup content and like basically
create versions based on thedifferent teams, get quick
approval and send it out.
So like AI also needs to knowlike when to get human approval.
But you can imagine that thenthat makes like people in
that organization, in a techcompany or whatever, rather
than being maybe like a learningdesigner specialist, they're
(21:19):
basically like being the humanapprover or like pointing it
in the right direction basedon like business challenges.
So they become more oflike an orchestrator.
Rather than like maybe aspecialist in their job
is kind of the way thatwe're seeing it change.
And so like workflows justhave to change completely,
and that's like very painfulin a large enterprise.
So there's just tons ofproblems right now with that.
But like you can tack on amillion AI features to like, you
(21:42):
know, other learning tools thatexist that are like traditional
corporate learning tools, butit just doesn't change the
way that people work enoughto like actually meet the
needs of organizations today.
And so that's why we tooklike a ground up approach
to building like a tool thatis optimized around like
business outcomes versus likehow humans do the work today.
Hannah Clark (21:59):
Yeah, and I really resonate also
with this idea of peoplebecoming more orchestrators.
I think that we've discussedthat before on the show.
We've kind of thrown aroundthis idea of ai kind of,
actually, kind of in a waybuilding people's management
skillset, because you'resort of acting more in the
mindset of a people managerwhen you're directing agents,
for example, or when you'rekind of reviewing and kind of
(22:21):
guiding information, ratherthan just sort of building from
scratch and kind of, you know,throwing spaghetti at the wall.
So I think that's kind ofinteresting how like we're
seeing this kind of in multipledifferent verticals how
this kind of effect of Yeah,orchestration and guiding
things and kinda refiningrather than having to kinda
build, interpret, do allof these things manually.
I think that's might bethe biggest thing in, in
(22:43):
all AI advancements lately.
So now that we're kind of atthis point in the company,
what would you say has beenthe most significant lesson
like this is, it sounds likequite a journey for you.
You know, this all startedfrom your experiences in
rural Oregon and now you knowyou're working with enterprise
clients and this has been likea relatively short period of
time, if I'm not mistaken.
(23:04):
In the last several yearsthat you've been working in
your capacity, what have youlearned that you think is
like the most impactful thatyou would want other people,
other founders, other peoplein the education space to know?
Maxine Anderson (23:15):
Yeah, I think whether it's called education,
learning, enablement, whateverit is, like I always view
it, the goal is that you'rehelping someone realize
their potential to accomplishwhat they want in life.
Basically, like that'sthe 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 theworld 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
(23:37):
that is not accomplished throughthe best content in the world.
It's accomplished throughproviding the right context to
the learning and by basicallylike bumping into problems.
Right?
And that sounds weird, butlike even technology should
get people to do that.
Like don't sit and likeconsume three hours of
(23:57):
video training, right?
Like people need to, andthis is done, but like.
Anyone building technologyor implementing whatever it
is like should really focuson like how do you get people
to like bump into problems alittle bit more like practice?
And that's when it likereally sticks in their head.
And how do you create thatexperience in context when
it's like needed the most?
Right?
I always talk aboutlike podcasts are the
(24:18):
party example for me.
I love listening to podcasts.
I listen to all the time.
Like 10% of them like driveme to like change anything.
And it's because I likehappen to listen to it.
Like the day before I facedthat problem or like that
night, I like listened tothe podcast and I faced a
problem earlier in the day.
And so like I think contextis like super important and
creating that context forpeople is really important.
I also.
(24:39):
I think it's interesting andlike curious people and like
you can learn knowledge, butlike, you know, our goal with
our technology at least is notlike for people to just learn.
It's for people to likeactually change their behavior,
perform better, like feelthe impact of that learning.
So I think it's like, youknow, great content is totally
necessary, but I think it'sjust like what we've learned
is just not what drivespeople to like actually.
(24:59):
Gain a new skill or somethingis like, it's just not, it's
just not through content.
I know people who likeconsume the most content ever
on like product managementand like still struggle
with like the day-to-day oflike how to get something
like actually out there.
Right?
So I think it's just like humanbehavior, like needs practice
and it needs like, you need tolike provide that context so
that people can like actually,you know, understand and like
utilize the content basically.
Hannah Clark (25:21):
I completely agree.
We actually, we were for along time hosting panel events
and kinda like live events.
And over, over time we werekind of figuring out like,
how do we make these better?
How do we makethese more useful?
And one of the thingsthat we kind of thought
we would experiment withwas doing something that
was a lot more hands-on.
So we ran a vibe codingworkshop and it was a similar
format where we would havea facilitator still leading
(25:43):
it, we would still havehosts and that kind of thing.
But what we did was we toldpeople to come prepared with a
few of these different supplies,have some accounts built, kinda
already have a platform inmind, or a concept that they
wanted to try to prototype.
And just by making theformat more following along,
rather than just listeningand taking in all this
(26:03):
information that withoutcontext can be very abstract.
We got way betterparticipation levels.
We got way better people.
I guess as far as thepercentage of people that
stayed throughout the entirething, people who gave us great
feedback about how many skillsthat they actually retained.
It was just night and day.
So I yeah, like firsthand, Ican say that context piece is
(26:24):
super, super, super critical.
Maxine Anderson (26:26):
Yeah.
And one response islike, there's just
nothing more frustrating.
Like, have you ever heardsomeone say something
like, so intelligent?
You're like, okay,stick it in my mind.
I'm gonna use thatin my next meeting.
And like, you just forget it.
You're like, oh, like I wasgonna like come to this meeting.
So smart.
Like I, I heard the best tidbitfrom someone, like there's
value to that, but like,there's an opportunity with
ai, like just being able togenerate content on the fly to
(26:47):
like give people information.
Like if you add goodautomation, integrated data.
When they need it.
And that's like so powerful.
Like that's like an, itcan be a serious engine
for an organization.
So yeah, I'm excited to seehow it changes learning.
Hannah Clark (27:00):
Same to here, and I'm a little bit
disheartened to hear thatthis actually means that
homework is actually valuable.
Oh, no.
Anyway, thank you so muchfor joining us today, Maxine.
This was a really fun chat.
Where can listeners followyour work online and find
out more about Arist as well?
Maxine Anderson (27:12):
Yeah, so we're at www.arist.co.
I post a lot on LinkedIn aboutwhat learning and reinventing
learning organizations forthe future of work looks like.
So I'm at MaxineAnderson on LinkedIn.
Hannah Clark (27:23):
Cool.
Well thank you somuch for being here.
Maxine Anderso (27:25):
Yeah, thank you.
Hannah Clark (27:28):
Next on The Product Manager podcast.
Now that you know how peoplelearn, our next episode is
all about how people buy.
We'll be digging into buyerpsychology and the small
tweaks you can make to yourcustomer touch points that
boost conversion, driveadoption, and fill the cracks
in your growth strategy.
You don't wanna miss this one.
So subscribe now to jumpin with us next time.
Popular Podcasts
My Favorite Murder with Karen Kilgariff and Georgia Hardstark
My Favorite Murder is a true crime comedy podcast hosted by Karen Kilgariff and Georgia Hardstark. Each week, Karen and Georgia share compelling true crimes and hometown stories from friends and listeners. Since MFM launched in January of 2016, Karen and Georgia have shared their lifelong interest in true crime and have covered stories of infamous serial killers like the Night Stalker, mysterious cold cases, captivating cults, incredible survivor stories and important events from history like the Tulsa race massacre of 1921. My Favorite Murder is part of the Exactly Right podcast network that provides a platform for bold, creative voices to bring to life provocative, entertaining and relatable stories for audiences everywhere. The Exactly Right roster of podcasts covers a variety of topics including historic true crime, comedic interviews and news, science, pop culture and more. Podcasts on the network include Buried Bones with Kate Winkler Dawson and Paul Holes, That's Messed Up: An SVU Podcast, This Podcast Will Kill You, Bananas and more.
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com