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Every product leader has to make them: the high-stakes decisions that define outcomes, shape careers, and don't come with easy answers.
The Hard Calls podcast, hosted by Trisha Price, features candid conversations with product and tech leaders about the pivotal decisions that drive great products and the pressure that comes with it. From conflicting priorities and unclear success metrics to aligning teams and navigating executive expectations, you will hear compelling stories and best practices that drive business outcomes and help you make the Hard Calls.
Real decisions. Real stakes. Real leadership.
Presented by Pendo
Learn more at pendo.io/
Follow Trisha Price on LinkedIn: https://www.linkedin.com/in/trisha-price-3063081/
If you build software or lead people
who do, then you're in the right place.
This is Hard Calls, real decisions,
real leaders, real outcomes.
Hi everyone.
Welcome back to Hard Calls, the
podcast where we bring the best product
leaders from all around the world
to talk about best practices, tips,
tricks, scaling lessons, and of course
the Hard Calls they've had to make.
Today we're mixing it up a little bit
and we are live from Pendo's headquarters
in Raleigh, North Carolina, and I am
with the co-founder and CEO Todd Olson.
Hi, Todd.
Hey, Trisha.
How you doing?
Good.
Good, good.
Well, as you know and the listeners know,
we always start Hard Calls with talking
about a hard call you've had to make.
But before we jump into that, I want
everyone to get to know you a little bit
and how we work together a little bit,
and then we'll get into the hard call.
Sounds good.
Sounds good.
So.
For all of you guys, I was hired
as the CPO here at Pendo about
four years ago when Todd hired me
in, and I often get the question.
How is it to be a CPO and work for Todd?
Most of you probably already know Todd is
one of the top product thought leaders,
has been a product leader for most of his
career before coming and founding Pendo.
He wrote the book on being product-led
and so obviously being a CPO and
working for someone like Todd can
probably feel intimidating to many
people and they often just ask me like,
How did you find your footing?
How was it to work with him?
So I'd love for you to just share like
what your thoughts are on bringing in
a CPO and how that, how that works.
Well, first off, I think very
few things intimidate you.
So I, I think, you need to find
someone who comes from, is cut from
that cloth that, I mean, obviously if
I'm speaking to someone and they're
intimidated by me, it's just gonna
be a bad relationship from the start.
I mean, I don't think any relationship
in life is positive where like
one person is intimidated or has
issues with the other person,
especially not a leadership position.
But look, I, I think you want, and I
think you did this well, is you wanna find
someone who wants to partner with you.
Yeah.
Who doesn't try to like box you out,
shuts you out, rather finds a way,
in a very healthy way to sort of
make room for you within the org.
I mean, reality is running an org
at scale - there's a lot of things
I probably don't wanna do, like
a lot of things I don't wanna do.
A lot of things I didn't do.
Career frameworks and ladders
But even like the details
of execution around a lot of
like, which team specifically?
Like no one wants me
in that sausage making.
Yeah.
And heck, I don't, I doubt you were
even in that sausage making, you
probably had one or two levels beneath
you doing it, and you're providing, of
course, accountability and oversight
and leadership to all those folks.
So like, look, I, I think what you
need is someone who finds space and,
and wants to collaborate and wants
to work and like we, we had a handful
of sessions that, I remember vividly
where you brought me in and we had
conversations like sometimes, folks, one
of our little hacks that we did that I
thought was a lot of fun, and we still
do to this day is like sort of evening
meetings, dinner meetings at the office.
Yeah.
We, we do some takeout, usually sushi.
Yeah.
We're in a conference room.
We got whiteboard markers going
and we're just like talking.
Yeah.
Brainstorming.
Yeah.
with, with, everyone's
idea is, is good and equal.
I think that worked.
I remember that one session
we had on our embedded guides,
our embedded content feature.
Yeah.
And I remember just sitting there and
like getting your feedback and getting
your opinion and putting it up there.
And it's not like you directed me,
you can't do this or you have to
do this, but I want your feedback.
You know the product, you're the founder,
you know the space better than anyone.
So for us to be able to collaborate on
it but not feel like it was directive,
I think was critical for both of us.
Well, I hope it was fun for me.
Me too.
And I hope it was fun for everyone,
I think it wasn't just you.
You had, you had, you, you had I think
a level beneath you and a level, but
Yeah.
So yeah, they were all in the room.
Yeah.
And I think, I think at the end of
the day, I'm a builder and I like to
build things and it brings me joy.
And, and I think, I like to think
I, I my happiest self in some
role where I can still build.
And I'm not just stuck in, everyone
assumes I'm just, the CEO I'm
stuck in a bunch of meetings with.
I don't know, bankers and finance
people or whatever, sometimes.
And, and I have to do those things,
that's part of my job as well.
But I, I think that the building
part, that's where the magic happens.
Yeah.
In companies and that like, so yeah,
I think you need a relationship
where people don't feel threatened.
They feel like each person understands
their space, their role, but, and
look, and then it's having direct
conversations like, Hey, this didn't
work for me, or, Hey, I'd like this more.
I think.
Having a good enough relationship
where you can be open and honest.
Yeah.
And direct with each other
Yeah for sure.
'Cause you're not gonna be,
It's not gonna be perfect every time.
No.
You're gonna like we
all move very quickly.
Yeah.
When you move quickly, sometimes
you forget to do something.
You unintentionally exclude someone.
May not even be me, maybe someone else.
And like, I think working through
that, that's really, really important.
Yeah.
Well, I appreciate it and um.
It's just something people ask me
all the time and it's hard to explain
how to make relationships work and
working relationships and trust, but
I think it's something we did really
well and hope that sharing that's
helpful for, for everybody else.
Well the key is sushi at the office.
Sushi at the office
after hours.
You know that, that.
It fixes most relationships.
Maybe, maybe a bottle of
wine with a sushi, maybe.
Yeah, a little wine won't,
won't hurt the creativity.
It doesn't.
It doesn't.
It doesn't.
So, Todd, this is Hard Calls, so I'd love
for you to share with us one of the Hard
Calls you've had to make in your career
that was, fairly career defining for you.
Yeah.
Look I think, there are so many.
I'm gonna go back to one pre-Pendo 'cause
I think it was one of the like, the sort
of like interesting hard calls I made.
I was, so this is at Rally Software
just prior to Pendo, this is maybe two
to three years before I started Pendo.
I was, I saw this opportunity to
build this add-on product and, I
was not the head of product there.
I had no power, no control,
no resources to do it.
I was in product marketing and but I
had this opportunity and I saw this
product and actually some customer
built some open source product using
our APIs and it was like, wow, all
of our customers could use this.
I mean, I'm talking
about product market fit.
When you have a customer build an add-on
to your product that uses your data,
you're like, okay, I know I want that.
So I convinced a bunch of people to hire
some consultants to take this open source
product and start productizing it with
customers, over the next three to six
months that, that, outsource team grew and
grew and grew into it was like honestly
kind of a full fledge engineering team,
to the point where finally the CFO kind
of woke up and was like, what's going on?
We have like, is this like some slush
fund that you're like directing funds to?
And, that ended up becoming, a
portfolio management add-on to our agile
project management solution, which,
the company ultimately sold to Computer
Associates, which was in that space.
But it was, I think it was that not
letting title, not letting role.
I eventually took over product
shortly thereafter, so then I
actually had probably helped ability
to move the whole, like move a bunch
of engineering resources onto it.
We, we pulled it in-house, but I think
just not letting things get in your way.
I think that's how you make hard calls and
like having conviction around something.
So, so yeah, I'd say that's it.
I love that.
I have often given product
managers the advice when they ask
me like, how do you get promoted?
I'm like, well, if you work at
a high growth company, you don't
have to wait till there's a job
opening or your boss leaves.
It's, I've always said, go
create a hill and go stand on it.
And that's exactly what you did.
You created a hill.
Yeah.
And so many people, they get hung up
on their title or their role or this
and that, and like, man, just go do it.
Build a business case.
Yeah.
And just go, go get after it.
Make it happen.
And, and I, I think, and look that
I wasn't the CEO of the company.
I, I think the, the reason I like
that story is that plenty of people
can say, well, now you can make hard
calls because, blah, blah, blah.
But I think anyone can make
a hard call in the company.
Yeah.
So you just have to have some conviction.
And what you did and pulled off is
hard, but I do think today with the
tools at our disposal, especially
with AI, doing what you did back then
should be even easier for people.
Yes.
Yeah.
Well, yeah.
Yeah.
Well, now I, I could've like,
had AI take this open source
project and work on it a bunch.
Right.
You wouldn't need all that.
Yeah.
No, I, I think, well now
it's a different world.
And yeah.
And then speaking of course of hard
calls, I, I think we are in a world
today, we're literally, every tech
company is being faced with hard call,
after hard call, after hard call.
And, it's completely
unique in dynamic times.
And, and while I used an older example,
pre Pendo, I could have very easily
chosen a number of of examples that
are like far more recent, like in the
last few weeks or the last few months.
Yeah, because I think now is a time where
I am, being not forced is the wrong word,
'cause it means that it feels
like something, something's
pushing me to do it.
I, but I feel conviction around
the need to make harder calls.
Yeah.
And is a lot of that just because of
market dynamics, is that because of AI in
your belief in how software's changing?
Well, yeah.
I, I think.
You wanna be capturing and jumping onto
some of the most interesting waves.
If you think about what sort of pulled
Pendo along, you could argue sort of
the SaaS wave when people were, yeah,
building up software as a service
and the whole cloud 100 community
and like, like we sold to pretty
much every one of those customers.
And that, and the growth of
those businesses fuel our growth.
And that's kind of why we're sitting
here in this nice office space.
We grabbed onto that wave, but
the next wave or current wave
you could even argue is AI.
And we need to find a way to
lasso that and jump on it 'cause
that is gonna fuel the next five
maybe even 10 years of our growth.
So, so the way I think of it is,
is you want to be on the waves.
It's gonna like the natural market
forces to drive the next level of growth.
But then it's also very, very clear
that these tools are redefining
the way you run businesses.
Mm-hmm.
And, and there's, it's, it, it's, it's
changing the way we develop software.
It's changing the way we market to people.
Yeah.
It's changing the way we're
gonna be selling to people.
And because it's all very, very
new, like there, the winners and
leaders are gonna be ones that
kind of figure out how to do it.
Because the truth is there is
no, like, people talk about,
There's no playbook right now for this.
Yeah.
People talk about the SaaS,
playbook's dead, you gotta do AI
stuff, but they don't say that.
There's no AI playbook!
Yeah.
And I, I speak with founders,
both founders of AI companies
who are younger than me.
You could say they're AI native.
Yep.
Their age actually doesn't really matter.
It it, what matters is they've been
creating AI companies from start.
And I, I talk with 'em to
learn like, what are you doing?
And I get some good nuggets
and there's some obvi.
We're all experimenting, but
the truth is they're just
experimenting like the rest of us.
Yeah.
And they have yet to figure it out.
And because the truth
is we just don't know.
We just don't know what, what,
how to do things the right way.
How to use these solutions.
And the tools are changing
Yeah.
Nearly every week.
Yeah.
And so that makes it very exciting.
A little bit scary, but as someone who's
a, honestly a lifelong entrepreneur.
Yeah.
I've been starting company since I was 20.
To me, I feel like the company
needs me to be more entrepreneurial.
Go back to sort of this day one
mindset that Amazon talks about.
I think that is what the company
needs for me now, because the reality
is that at nearly 900 employees,
we have a lot of folks here slash
leaders here who we hired because
they're good at scaling big things.
Mm-hmm.
Which is not the same thing as going
back to AI native and no rethinking how
you, it's very different skill sets.
Yeah.
And, and you're at this
interesting inflection.
You actually need both.
Correct.
You need scale, you have enterprise
customers, you have a pretty
big company at this point.
Yet at the same time, you've gotta kind
of start over with how you think about
your product, supporting customers, how
you do business, like, how do you do
both of those things at the same time?
Yeah.
We can't be like, you know,
cowboys running this company.
We're a decent sized business.
Yeah.
And, and like we need professional
HR practices and finance practices.
We're audited by a big
five accounting firm.
We need these things obviously.
Yet you kind of have to like be
comfortable throwing certain things away.
Yeah.
And experimenting.
And the question is, who at the
company has experience such interest
in going back to sort of day one.
And, and the truth is, it's like
I'm one of the few people who's
very comfortable in that world.
Yeah.
So the company needs that out of
me more and, and while I still do
plenty of scale things, I mean, I'm,
I've got like 12 hours of QBRs this
week, or no tiny company would do.
And maybe we won't do in five years,
years, maybe not, I don't know.
I honestly don't know.
But I'm gonna do 'em the next two weeks.
I don't, not because I think it's,
I think it's a good practice.
I like reflection, but yes,
but yeah, I think it's, yeah,
super interesting and dynamic.
It is really interesting and I love
what you're doing and challenging all
of the status quo and processes and
tools and the way we've done things.
I think in product, when I talk to
product managers, product leaders,
I mean, the first thing I tell them
is if you are not trying out all
of these AI tools, if you're not
prototyping, if you're not changing
up your product development lifecycle.
And I'm not even talking about
putting AI in your product yet.
I'm just talking about using it.
I tell people all the time as a product
manager, you are going to be completely
lost and not have a job in a very short
period of time because I think it is the
most interesting time to be in product.
But if you're not jumping on
this wave and trying these new
tools, you're just gonna be lost.
No, a thousand percent.
And, and I include myself in that
world and that that was one of the
things that it took me longer than
I would've liked, but for a while,
obviously as is happening, I go
to our leadership team, you at the
time, others, we need to do more.
We need to do more.
Let's do this, let's do that.
And we started doing things.
I think we did our first AI hackathon
like pretty early years ago.
Our AI launch was pretty early.
Years ago.
Yeah.
Yeah.
And that was sort of our, you, we
can call it 1.0, we can call it 0.5.
I don't know.
I don't like naming things, but that was
our first foray and just like touching,
experimenting, and you could see some
teams we had were just more natural early
adopters of it, playing around with it.
Right.
And, we did, we did well, we
got out there in the market.
We started experimenting with customers,
but I, I just felt very anxious the
whole time we weren't doing enough.
Now, I couldn't put my finger
on what we needed to do.
Right.
And I couldn't say, put three teams on
A, B, C 'cause I had no idea at a what,
a what A, B, C really was at the time.
But I knew in my heart, I just have,
I felt anxious for the last few years.
Yeah.
Which is a weird feeling to have.
And it's not constructive either,
just me walking around being anxious.
But I think what happened is about
nine-ish months ago, maybe longer, I
really started personally playing around,
like you just said, product managers
should be playing around and using this.
I started playing around
with it a lot more.
Yeah, I started experimenting, not
just with Chat GPT, which everyone sort
of experimented with, but I, I started
experimenting with those, some of the
prototyping tools, the prototyping
tools and the code generations for
zero and Lovable and things like that.
And, and as someone who is a programmer
professionally, and I don't get paid
for it now, but I used to get paid
for it, so, I was a bit skeptical
at first of all this, but once I
started using it, I was blown away.
It is
And yeah.
Is it right all the time?
No.
And does it like generate
code that has bugs?
Yes.
Yeah.
But if you tell it, go fix it,
it tries and does a decent job.
And if you give it more direction
and, and then the other thing is the
models are getting better and better.
So like maybe one week it
generates sort of the wrong thing
and then three weeks later it
generates sort of the right thing.
Yeah.
I mean, you can kind of see where
it's going and you're like, wow.
Wow.
And I still felt it was valuable for
me to have technical skills, but it was
also valuable that I have product skills.
And I have, I mean, I'm not a designer
that, that, that's the interesting thing
is a lot of us who are builders, we have
majors and minors and look I
cannot design things, period.
So I'm just gonna say period.
No one's ever put me in front of Figma.
I've never used Photoshop in my life.
I think I have a taste.
I have things I like.
You have an eye for it.
You have an eye for it.
I appreciate certain things
that are well designed.
And my wife doesn't think so about
furniture, but I think I have a decent
taste, but certainly on software design,
I think I have pretty good taste.
But then of course, product, I
would say is sort of a major of
mine I've been doing now for years.
I feel like I have a pretty
good skill set there.
And then of course, engineering
and coding, I have a good skill
set, but I probably am rusty, not
probably, let's just say I am rusty.
Me too.
AI sort of fills in those gaps.
It does.
And that, that's the power that I started
seeing is like, it takes someone like
me who is a major in something and
but I have some weaknesses in other
areas and it fills in those weaknesses.
Yeah.
And I get a lot done.
Yeah.
Now maybe it's not like production
quality for like a Pendo, but
it's a pretty darn good prototype
that I could hand off to someone.
And, and once, once I started playing
around with it more and touching it
more it really helped drive a lot more
clarity about what we needed to do.
And then others in the org started playing
around with it more and that's when you
realize just what's leadership about?
It's about setting an example.
Mm-hmm.
And if I'm not playing around
with it, which candidly
I can't expect everyone else to
Yeah.
That, that really hit home.
And look, I think the Shopify
memo, which was earlier this year.
Yeah.
And some people didn't like it.
Some people did like it.
I had a chance to hear, the president
of Shopify, Harley, speak at a
small event and they use this term
reflexive and it resonates with me.
'Cause I don't know, I don't know about
you, but like, I still reflexively
use Google for a lot of things.
Mm-hmm.
I have a question?
I Google it.
I've kind of switched over to ChatGPT.
My kids make fun of me all the time.
They're like, mom, that's something
you could actually just Google,
but I have kind of switched my
reflex now is to go to ChatGBT.
Well, I'm still working on it.
I mean, I would say I'm 50/50 now.
Yeah.
But, but I'm not 80/20.
And, and maybe there is a world
where like, depending on your, your,
your kids', point, like Google's
gonna be better at certain things.
Certain things.
That's what their point.
They're like, if you
don't need an opinion.
Just go to Google.
Yeah.
You know?
Well, and when you go to Google now,
it gives you an AI summary at the
top, which is pretty darn close.
It's pretty good.
It's, which is pretty good.
So like, like we're seeing these
sort of like different ways of
working evolve and we're all
experimenting their own personal hacks.
But if we don't do it ourselves,
like no one else, we can't
expect our org to do it.
So, you've talked about leading
the way for your AI revolution at
the company, by playing with tools.
You also went out and did a couple of
exciting acquisitions in the AI space.
Yeah.
And so how do you think about that?
Like how do you think about, obviously
when you're talking about internal and
ways to work, it's about tinkering and
experimenting and playing, but when
you're talking about changing your
product, for all of us product folks,
acquisition is a great way to do it.
Yeah.
Look, I, I think it was clear that
we needed to inject some different
experiences, different skill sets,
different DNA, Yeah, in the business.
When we, so the first acquisition we made
in the AI space was Zelta AI, and that
was the result of actually us being, I
would say, intentional in our MA strategy.
Yeah.
We went out looking for a product
that sort of solved that problem and
the problem was very, very specific
and everyone in product knows it.
We have lots of qualitative data.
It's sort of like scattered across our
org in these different systems, yes
a PM could go and read through every
Call log and support tickets,
Yeah.
Zendesk ticket and like, pull out the,
Enhancement requests
And no one does that.
But it's super valuable.
Yeah.
And there's like gold in those hills.
Yeah.
I like to say.
And if we can find a way to ingest it all
and, and, and really surface those things
that's incredibly valuable to customers.
And so we kind of set out to sort of,
be very intentional about acquiring
it as, as and, and then it was super
interesting 'cause as you meet companies
and there, some of our investors
guided us on this, that you actually
almost wanted younger companies.
Yeah.
Which may be counterintuitive because if
you started too long ago, you were pre
LLM and a lot of those companies were
rewriting their stacks to leverage LLMs.
Right.
We wanted specifically the skill
sets and the tech that was post.
Exactly.
LLMs
Because they're just building
things in different ways
And that's the skillset we needed.
Exactly.
We didn't need people
who were learning it.
The same way we were learning
and trying to pivot to it.
We needed people who natively thought
and built their products that way.
Exactly.
Yeah.
And, and so that's what we did.
And, and I think it's been successful
on a number of fronts: One the
product's great, we're excited about it.
It's in market.
I've gotten a lot of positive
feedback from customers around it.
Some CEO grabbed me the other week
at a conference, told me how I was
transforming their product practices.
So that felt really, really good.
But also like the DNA change, like,
whether it's like the engineering
team operates differently.
A little more agile, they've
been using AI tools from day one.
Yeah.
One of the things I, I was seeing an
engineering meeting with one of the
engineers from, from Zelta in a bigger
engineering room and it was all about
how to use AI in engineering and a
bunch of engineers were talking about.
Well, it couldn't handle this tail
recursion example that I had or whatever
they, I think a number of folks were
experimenting with things and like you
passed some sophisticated algorithm and
it got confused, et cetera, et cetera.
And the engineer from Zelta,
everyone's breaking it basically
and can't use it for this.
Can't use it for this,
can't use it for this.
And one thing that Mick said
that really struck with me, he is
like, look, I can spend two hours
typing or 30 minutes reviewing.
And it's just faster to spend
30 minutes reviewing code than
it is two hours a type code.
And it changed my mental model to
like, are a lot of us gonna start
really honing our editorial skills?
Yeah.
Where we may not be generating
large swaths of content,
but we may be curating it.
Yeah.
We may be editing it.
Yeah.
And like, if you think about the world
we're in now, like we love editors and
curators that like, those are the people
that are influencers across social media.
Like the people that we all follow are
essentially people pulling out the good
bits and surfacing it to us 'cause that's
what they think we should be looking at.
And I think, so we've already, as a
culture, started moving in this direction.
Yeah, I think we're gonna.
Yeah, large language
models and generative AI
It is gonna push us all to be a
set of curators, editors and that's
actually pretty exciting for me.
It is.
So, it is, it's really exciting.
And then you followed on from Zelta
and did another AI acquisition as well,
Correct!
Yeah.
Yeah.
And we've done two acquisitions
in 12, well, three actually,
technically we acquired a small
community called Product Collective.
But yes, this is the most
aggressive we've been in market,
since we started the company.
We've done, we averaged by one
every two years prior to this.
And now we're, we've done
several in, in one year.
And that was Forwrd.ai and
that was another intentional
purchase.
We know that our data is super valuable
for certain business outcomes, like
detecting churn or expansion signals,
which ultimately they on driving
revenue, like scoring leads or product
qualified leads, things like that.
But it's a hard problem.
Yeah, it's a hard problem.
It not only do you have our raw
data, which sort of needs to be
cleansed and sort of massaged and you
need to sort of, you know, join it
with CRM data and other data, like
it's a relatively hard challenge.
And look, some teams, some companies
have data science teams and they, four
or five people, maybe half dozen people
that can sort of do all that work.
I mean, we do, we do.
We have been doing that on.
But that's a rarer skillset.
Yeah.
And that when I talk to our customers,
even some of our larger enterprise
customers, they aren't doing that.
Yeah.
And this is an opportunity to, to take
our data and honestly drive revenue for
our customers because when I talk to our
customers, a lot of 'em kind of, they
wanna do this, they're trying to do this;
they have limited skill sets, limited,
like the skill you need is like taking
Pendo data and sort of making it relevant.
Right.
It's, and they just don't
understand it to the degree.
And the Pendo data is.
Is nuanced to it's nuanced, get the
right insights out, sophisticated.
It does need to be, it does
depend on like how you set up your
subscription in some instances.
Yep.
And we have all the
expertise in that on that.
But what we've seen is this, this,
our data is a really, really good
non-biased, early warning signal for
That's really cool.
For all these opportunities.
So yeah, that, that's been
really, really exciting.
And, um.
And it's just a great team.
Another thing comes down to, I,
I've talked to hopefully in both
instances, yes, the product, we were
intentional, the use case we liked,
but the team's adding something else.
Yeah.
And this entrepreneurial
mindset, AI talent, different
points of view of doing things.
Yeah.
I mean, Kobe, was a product leader in
our space so, obviously bringing his
background and experience to Pendo is,
is super helpful, super, super helpful.
Well, we already had a team in Israel,
so like that in some ways that made
it actually really, really easy.
Yeah.
Yeah.
In an office, like
literally it, it closed.
Next day everyone's in an office doing
a town hall, having lunch together.
That's great.
So, um.
Yeah,
Culture's important with these things.
So both of the acquisitions that you
talked about, were really using AI
to glean insights into your product.
Correct.
Into our product.
Mm-hmm.
But I know a lot of listeners, us too,
when we think about AI, we think about
insights, but we also think about
this whole agentic world and where
automation of workflows is going.
Conversational interfaces is going
and that's something I know that,
that you've been working on, not just
for Pendo and our product, but also
supporting everybody else, all the other
product people out there as well, and
building their agentic experiences.
So how, how are you, how are you
instilling those new skills and talents?
Because that's a different skill set
than gleaning the insights that you were
talking about from Zelta and Forwrd.
Correct, correct.
Well, the first thing before I move
on from insights, I will say like the
first thing we sort of prioritized
and built, which, I feel really good
about was it was clear as you're
starting to, Hey, what do we do?
At some level, we, we are measuring
user interfaces and experiences.
There's no question that the world's
moving where we're gonna have, we're
still gonna have clicks and scrolls and
page loads but some percentage of our
user interfaces are gonna be agentic,
chat-like in nature, whatever, whatever,
copilot-ish - and there's just so many
different terms - and I don't know if that
percentage is gonna be, like, some people
probably are theorizing, it's gonna be
a hundred percent of user experiences.
I'm probably not on that boat where
it's gonna be a hundred percent.
I think power users are gonna
want different experiences.
I know I, as a power user for
software, like I just wanna,
Somebody just wanna go do something.
I know I can do it.
I just wanna go in and
click a button or two.
Like Right.
I, yeah.
I don't need to like, type in a
sentence every time I wanna do anything.
Right.
So I personally don't think it'll be
a hundred percent, but I think a lot
of people are gonna try to do it and
they're gonna experiment with it.
So, but regardless of what it is.
I know that people are gonna measure
that part of their app, and if we see
all these other stuff and we don't
see this, then we're not providing a
hundred percent visibility into how
people are experiencing your product.
So, so the first thing we, we sort of
prioritize what we're calling agent
analytics, which leveraging the same Pendo
install, the same Pendo infrastructure.
You can basically direct us
to say, Hey, take this agent.
It starts pulling in the actual
conversation, and start giving
you insights into how people are
doing it when they're doing it.
How they're working in concert with
the other parts of your product,
start getting like honestly just 360
degree visibility of what's going on.
So that was kinda step one.
And that's powerful because as
step two for us is okay, now we
need to add sort of that user
interface element to our product.
Yeah.
And that different way of experiencing
the product and when we first started
going down this path, honestly, I, we
made an intentional decision to sort
of let teams run their own experiments
independently, we did not centralize it.
Yeah.
We didn't create one
piece of infrastructure.
There's just so many different types
of infrastructure and so many different
decisions, we decided that picking
one too early could lead us down
a path where, pick the wrong one.
Yeah.
So like, let teams experiment,
give people like creative license.
And we did that and, we ended up with,
three agents, four agents, whatever,
you, whatever, I don't know what
the exact number is, but a number of
different agentic experiences in Pendo.
Yeah.
Now you're gonna start
seeing us sort of like
Bring that together
Now that we we know enough to
know what's working and what's not
working, start creating some common
infrastructure, common UI elements.
We have an opinion now, almost a
point of view like, so to taste, so
to speak, and what we think the right
experience is long term and that's the
process we're sort of going through now.
So as product leaders, this is
a conversation I have with other
product leaders all the time.
Which is not the technical challenge of
doing what you're about to do, but the
emotional and change management of it.
Because you go and you let your various
teams and product teams build what
they wanna build, and they all think
theirs is the coolest and the best.
And there probably are pieces of each one
of them that are the coolest and the best.
But then you come up with sort of a, a
combined point of view of where you wanna
go with one experience, and then everyone
has to kill what they had built before.
And there's like this real sense
of loss 'cause the best product
managers love what they built.
They fall in love with it.
Yep.
And then you gotta tell
'em their baby's ugly.
Or even if their baby's not
ugly, it's not the prettiest.
And so how are you dealing with that?
In terms of, helping people still
feel connected to the strategy
and, and not feel that loss.
Yeah.
Look, I think we treat all of these
things as, this goes back to the, the
very classic book of Lean Startup, but
I, I see, I always say like, the value
in, in, in all of this work, whether you
throw it or not, is validated learnings.
Yeah.
We have valid, we have a validated
learning around, a, a certain path
or a certain technology set maybe
it doesn't scale the way we want.
Maybe it doesn't quite
hit our quality bar.
Maybe it's hard to maintain.
I, I think we're gonna have to take
some risks and be comfortable throwing
things away in this new environment.
Yeah.
Just like we did day one.
Yeah.
We're gonna make mistakes and, and
technology's we're gonna wake up one day
and we're like, oh wow, 05 just dropped
and it's like freaking amazing, you know?
And like, we need to move
everything to that, you know?
Yeah.
Sorry, GPT5.
Yeah I think it's just trying
to get, reprogram people's
mindset to be like, don't get too
attached or married to anything.
Yeah.
And, but you also need to
iterate very, very quickly.
Yeah.
Like if you threw away 18 months
of work, that's different than
throwing away six weeks of work.
Right.
So, so we're trying to move very, very
quickly and continually evaluate it.
Yeah.
I think it's important for all product
managers and product leaders always to
think this way: quick experimentation.
Don't get too tied up in
something or your idea, you know?
But right now with AI and how quickly
things are moving and changing, and
what technology is allowing us to
do today that it didn't two weeks
ago, not two years ago, two weeks
ago, more than ever, I think we all
have to be comfortable with that.
Yeah.
Well look, one of my classic
expressions in product is don't
get married to your roadmap.
Yep.
Another one of my classic
expressions is it's not your roadmap.
It's my roadmap,meaning
it's the company's roadmap.
Yeah, that's right.
Just like it's not your budget,
it's the company's budget.
That's right.
Like you are curating it, your
managing it on behalf of the company.
But if you think it's yours,
you are candidly wrong.
No, we, we owe outcomes to our investors.
Yeah.
And we owe value to our customers.
Yeah, that's it.
It's, that's what the roadmap is,
You knows, and if it's
wrong, we will change it.
Yeah.
And I am completely unafraid.
And, look, yeah.
You have to deal with the, the
constant, oh, everything's changing
and we can't even like, stay in one
thing long enough to like, you know.
Okay, great.
Yeah.
The world is changing right now.
The world's changing.
I'm not changing it, you know?
Yeah.
But we're gonna, like,
We didn't invent GPT five, but
we better take advantage of it.
Exactly.
Like, if, if you're not comfortable
sort of like adapting to the
environment, you will miss out on
things and I don't miss out on anything.
Yeah.
Like, like that's certainly
not how we're gonna roll here.
Yeah.
Agree.
So Todd, we've talked a lot today about AI
and the impact to Pendo, both using AI to
build our products and sell our products
and everything, and then also agentic
experiences and insights in the product.
But we also have a lot of sophisticated
enterprise customers who love AI and
are partnering with us on this AI
journey, but they're still what I
would call regular features and things
that they need and expect from us.
So how do you balance those things?
How do you make sure you're taking care
of your customers in the traditional
sense, not just in terms of leading the
charge with innovation and acquisitions?
Yeah.
I mean, look, I think.
The title of the podcast is Hard Calls.
This is a hard call.
Yeah.
Like what, what do you spend on, various
pieces, in various, parts of the roadmap.
I, I think this is, this is why we
all get paid the big bucks in product,
is to make those, those decisions.
And look, the, the truth is you're gonna
have to invest in a lot of things for
your enterprise customers, especially a
company like Pendo, which is still sort
of on its journey towards the enterprise.
Yeah.
Features like bulk operations.
And look, I, I know that, some
engineers or other, well, that's
not the exciting features.
It's exciting for large enterprises.
It's, yeah, if it's, if you just
save them like 20 hours of work
because you did something like in
one click versus like them spending
an hour or 20 hour, whatever it is.
Like, like those are the
features you need to do.
I mean, but, but we often forget is
that large enterprises, some of 'em
are heavily software so that we,
we protect them as they're sort of
like going through their journeys.
Now the cool thing is, is these two sort
of pillars are coming together where,
these large enterprises are, many of
'em are trying to experiment with AI.
They want to experiment with AI.
They may not be exactly ready for it this
moment, but they're gonna want a partner
like us who is already meeting their
needs in other areas of their business
to sort of help them along that journey.
Yeah, and I think that's where we think
the real opportunity is, is while we're
now experimenting with it with maybe our
more innovative customers are, are smaller
customers, startups even are starting to,
to, leverage some of our AI solutions.
We'll work out the kinks, we'll perfect
them, we'll get them, in a really, uh,
production quality sort of like position
and then we'll be able to bring a lot of
those to, to our enterprise customers.
And I think it's gonna be
a win-win for everyone.
But, but yeah, you have to
balance all these things.
And it's gonna be interesting
is that as enterprises adopt AI,
they're gonna want more controls.
Yeah.
They want,
Specific permissions.
We can use this, but we can't use this.
We can use certain types of AI but
we can't use other types of AI.
Exactly like they're gonna want
potentially to use their own large
language models that are possibly
tuned for their own environment,
Self hosted.
And yeah,
Yeah there's a lot of examples like
that that are things that we would do
for our large enterprise customers.
Yeah.
Like, there's really good reasons
for those companies to require
that, which still allow us to
deliver a great product experience.
So why?
Like, I don't necessarily,
I'm not super concerned.
Now, that's not ever like a version
1.0 feature you're gonna build,
but yeah, I think you have to pay
attention to both needs and you have
to invest heavily in both and yeah,
we, we have a lot of customers.
If I showed up at our Pendomonium.
which is our user conference and
said, we're only building AI features.
People get upset.
Yeah.
They get upset and rightly so.
Yeah.
I don't think it's the right decision.
Yeah.
But we're gonna invest a lot
in AI because I think it will,
the enterprises will want it.
Yeah.
We're already seeing, like some of
our large enterprise customers ask us
for things, I mean, agent analytics
is a great example where we have some
large enterprise customers that are
starting to experiment with it and
use it and because they have mandates
to play around with AI and they just
wanna know, are these things working?
Yeah.
What is it,
What are people doing with it?
What are they trying to solve?
How are they using it?
Who's using it?
Exactly.
And, and, and because when I talk to some
of large enterprises, they're not seeing
necessarily the the the benefits yet?
Yeah.
That they're reading about in the news,
so they're hoping by better understanding
it, understanding how people are
using it, they can tweak and tune and
ultimately get those, those outcomes.
So, so yeah, I think it's a constant
balancing act and we'll see.
We'll see how it goes.
Great.
Well, Todd, thank you for
being on Hard Calls today.
This is obviously a fun episode
for me to record, and just really
appreciate you sharing your experience
with us in terms of Pendo and really
fun to be here, live in Raleigh.
Well, it's fun for me too, so thank you.
Thank you.
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