The Tin Man’s silk heart in The Wizard of Oz is a perfect metaphor for AI right now—it can convincingly mimic empathy, but it’s not the real thing. In this episode, Hannah Clark sits down with Megan O’Rourke, Executive Director of Product at Metalab, to explore the delicate balance between AI-powered productivity and human-driven resonance. They dive into why empathy and storytelling are irreplaceable in both product development and leadership, and the risks we run if we trade them away for efficiency.
Megan shares stories from the field, frameworks for deciding when AI belongs in the workflow, and practical ways leaders can embed human connection into their teams’ processes. From reading the silence in a meeting to designing for emotional moments, this conversation is all about building products—and cultures—that people can truly connect with.
Resources from this episode:
- Subscribe to The Product Manager newsletter
- Connect with Megan on LinkedIn
- Check out Metalab
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Hannah Clark (00:01):
Whether or not you personally participate in
the Wicked movie hype train,I'm reasonably sure you're
familiar with The Wizard of Oz.
In the story, the character ofthe Tin Man is portrayed as a
humanoid robot who wants nothingmore than to have a heart.
But when he finally receivesone, what he gets is actually an
imitation of a heart, a silk bagof sawdust that convinces the
Tin Man that he has the empathyand emotional depth of a human.
(00:25):
If you haven't figured outwhere I'm going with this,
the Tin Man makes for apretty intriguing allegory
for where we're at with AI.
LLMs have reached a levelof advancement in which they
can pretty convincingly mimicthings like empathy and deep
human understanding, andthat presents dual effects.
On one hand,astonishing opportunity.
But on the other, hiddentraps that can slowly
(00:45):
melt away your impact.
My guest today is MeganO'Rourke, Executive
Director of Product atMetalab, an end-to-end
product design agency.
Megan's role sits at theintersection of design,
development, research and peoplemanagement, and so she's keenly
aware of the connection betweenstorytelling and user value.
And perhaps more importantly,what's really at stake if
we override empathy forefficiency, both in product
(01:07):
development and in leadership.
We discussed the balancing actbetween AI powered productivity
and human-driven resonance,why storytelling is as critical
as data, and the questionthat every product leader
should be asking constantly—ifthey have the courage.
Let's jump in.
Oh, by the way, wehold conversations
like this every week.
So, if this sounds interestingto you, why not subscribe?
(01:30):
Okay, now let's jump in.
Welcome back to theProduct Manager podcast.
I'm here today withMegan O'Rourke.
She's the Executive Directorof Product at Metalab.
Megan, how are you doing today?
Megan O'Rour (01:41):
I'm doing so well.
Excited to be here.
Hannah Clark (01:43):
Me too.
So can you tell us a littlebit about your background
and how you got to whereyou are today at Metalab?
Megan O'Rourke (01:48):
Absolutely.
I got my start in advertising.
Crispin Porter + Bogusky, thisbig agency in the States known
for creating very bold verydestructive work, very culture
shaping, sort of advertising.
So I was part of a teamthat managed the creative
process, reviews andproduction, and through that
it really instilled in meand appreciation for detail.
(02:11):
For high craft and alsojust the exposure to working
with world class creatives.
Even though I'm, I didn'tconsider myself a creative,
just loved being partof the creative process.
So loved advertising, butI found that over time I
was yearning for somethingjust a little bit different.
Not these sort of one anddone campaigns, but rather
something that felt a littlebit more living and breathing
(02:34):
so you could build andevolve and ultimately respond
to a need and a desire.
That shift ultimately ledme to Metalab, which is
where I've been since 2016.
So coming up on 10 years now.
It's a long time in agency land.
Hannah Clark (02:49):
In any job now.
Yeah.
Megan O'Rourke (02:51):
In any job.
In any job.
But I mean, yeah, it reallyspeaks volumes to the type
of work that we do and thepeople that we work with that's
keeping work really interesting.
And I'm happy to be there.
Yeah.
Metalab is a, an end-to-endproduct, very design led agency.
So we partner with companies.
Ranging from early stagestartups to Fortune 500.
Some clients come to us to gofull Z to one, which is always
(03:13):
fun and challenging, whereasothers come to us to maybe a
partial or a full redesign oroverhaul of an existing product.
So we're very design led.
At our core, we're veryfocused on craft and outcomes.
We're not about vaporware.
We don't have bigstrategy decks.
We are focused on just buildingreally great products and
making products that matter.
(03:34):
So my role today.
I'm the executive directorof product management at
Delam, so that means I,I lead our PM function.
I am involved in some of ourhigher profile projects as
well, and these days I amthinking a lot about how we
build happy teams and teamsthat build great products.
Hannah Clark (03:54):
Yeah.
Well, I'm so excited totalk to you because all of
these experiences reallyfunnel well into our core
topic today, which is.
All about how product teamscan leverage storytelling
and empathy in this ageof AI, such a chaotic,
full of gray area time.
So in the spirit ofstorytelling, I'd love if you
could share an anecdote thatsort of puts in perspective,
(04:15):
you know, what do we have togain and maybe also what's at
stake if we don't prioritizethese very human elements
of storytelling in ourorganizations and our products.
Megan O'Rourke (04:23):
I'll share an example that is more
on the personal side, likeit's not a flashy product.
It's not a big strategicdecision, it's just this
very like human moment andit's about someone on my team
who is this really smart,really engaged individual.
They're always supervocal in meetings.
They bring ideas to thetable, and over the course
of a couple weeks, I juststarted to notice like they
(04:45):
were going a little bit quiet.
They weren'tspeaking up as much.
They seemed a little withdrawnand there was nothing dramatic.
There was no like performanceconcerns, but there was
just this shift thatI could kind of feel.
And I thought in this momentI was like, if I was running
completely on automation, if Iwas using AI to attend meetings
for me and just tracking alongon things that needed to be done
(05:05):
or dashboards of work completed,I probably would've missed it.
But I was there, I was payingattention, I was reading the
nuances, and I was able tosee a bit of a difference
and just reach out to themand say Hey, how you doing?
Like nothing formal, but just ahuman connection or reach out.
And through conversation Irealized that, you know, there
was something deeper going on.
(05:27):
They were feelingreally overwhelmed.
They were not really sureof kind of their place
in this complex and fastmoving product and they
just kind of felt invisible.
And it just, it was this likeaha moment for me because
I thought AI is so greatat so many things and it's
not great at picking up atthe absence of information
or the quiet moments.
Like it didn't catch thathesitation of that person just.
(05:51):
Muting or unmuting andthen choosing to mute
again, like it doesn'tsay to us something's off.
And I feel like that'swhat we notice as human.
So small example there.
But I think what it representsfor me is in leading with
the human approach andwith empathy, what we have
to gain here is trust.
And I look at that is that'sreally the foundation for
how we collaborate, howwe support each other.
(06:13):
In this example, howwe give feedback.
Those are so coreto how we work.
And.
To answer your questionof what's at stake here?
If we overly on AI in thesemoments and we let it, you
know, stand in for us beingpresent and attentive and
having intuition, then we'relosing out on those signals and.
(06:34):
When individuals on theteam feel like people aren't
paying attention or peoplearen't caring, that's a really
quick way to get to lack ofengagement or feeling withdrawn.
And it would be awful to losegreat people, not because their
work doesn't matter, but becausethey don't really feel seen.
Hannah Clark (06:49):
Yeah.
Okay.
Multiple reactions I haveto that because I feel
like this really hits.
One thing that kind of comesto mind, first of all is I
feel like what you're touchingon is kind of a reckoning
that a lot of us are sort offacing about, you know, what
is the role of work and whatis the role of a company in
our culture, in our society.
(07:10):
If we are trying to automatea way the things that make
these things meaningful to usI think it's a really important
reminder that there are thingsthat, you know, we could choose
to automate, but we stillhave to be selective about.
What do we stand to lose byremoving ourselves sometimes
from those like reallyessential human interactions
(07:30):
that create culture and thatnurture and foster culture
in an organization and makepeople wanna stay for nine
years or 10 years or more.
The other thing that I thinkwas really poignant that you
said was about this idea ofwhat is not being said, the
idea of storytelling being alot about what is not revealed.
(07:51):
I had a very acutemoment of that recently.
There's a fringe festivalthat just completed in my area
and in my non-career time.
I am a performer and a lotof the storytelling that's
happening there, you know,I've been kind of observing
it more with the idea of maybedoing my own show you know,
a non-professional show, butsomething that has really kind
(08:11):
of come to the surface when Isee really good storytellers.
And I think this applies to,you know, even in a product
or professional context.
The really good storytellersare able to show a moments
and a narrative by beingselective about what they
include and what they omit.
And so like in some cases you'llsee a story that kind of takes
you on a whole journey overseveral years, or can be, you
(08:33):
know, through the course of asales funnel or whatever, but
the moments that you chooseto include and also mean being
selective about what moments.
You don't include and whatmoments you have to pay
attention are absent fromlike a certain narrative.
So I think it's kind ofinteresting that you're
bringing this up now becausethis is something that's
really been on my mind is likestorytelling is as much about
(08:54):
what we choose not to say.
You're right.
Like this is something thatas people, we have such a
unique ability to derivemeaning from certain things
that aren't explicit andalso derive meanings from
silences that are very subtle.
Anyway, it's a bit of atangent, but I'm liking
where this is going.
Megan O'Rourke (09:11):
I love that and I think that's, we'll
probably get into this later,but like I think that's
the important element ofbringing the human purpose.
There's so much information, butit's the discretion and it's the
intuition and it's experienceof understanding what makes the
cut and what's going to createthat compelling story when all
of the data can be presentedto you, but what are you using?
(09:32):
What are you excluding andhow are you packaging it up?
That's the nuance that I reallysee as the benefit coming
from the human side of things.
I don't want.
AI could make that call for me.
Hannah Clark (09:43):
I agree.
I think it, I don't want AInecessarily make that call.
And I think that there's areally important stage of this.
I mean, we, when we think abouta sales funnel for example,
you know, we think of theawareness stage and that's
like a lot of, that maybe issuitable for being generated.
You know, there's alot of awareness stage.
Kinda stuff that we can do thatmakes sense to kind of automate.
(10:04):
But that nurture part of thesales funnel I think is that
is an area where we have sucha huge opportunity to be able
to really infuse very deeplypersonal experiences, foster
an emotional connection,leverage community.
Like I feel like there issuch a, an opportunity there.
And I think that the hungerfor really compelling, human
(10:27):
elements is going to onlyincrease now that there is such
a volume of generated content.
Megan O'Rourke (10:31):
Oh, I agree.
Hannah.
I think we're verymuch aligned there.
That will become increasinglythe differentiator.
Hannah Clark (10:38):
Yeah.
And, okay.
When we talk aboutdifferentiators in product
design, like what do youlook for in practice?
Like when you're, you know,developing a narrative
or like working witha client at Metalab?
What are some of the morespecific strategies or exercises
that you might use with yourteam to create conditions
for like empathetic design?
Megan O'Rourke (10:56):
Okay, so I'll start by saying like
humanity and empathy.
I think that shows up notjust in the what we build,
but the how we build this.
My team's, I have to hearyou say this all the time.
I'm like, it's not just whatwe build, it's how we do.
It's the experienceof working together.
It's the experience ofhow we listen, how we
challenge, how we're creatingspace for the honest and
(11:17):
the real conversation.
I'll share one specificexercise that we love to use
just to help build empathyfor our end customers.
And then also just onemore philosophical or kind
of overarching strategicapproach for how we
create those conditions.
So the first is the exercise.
So you're probably familiarwith this as there are many
PMs, but it's going back to thebasics of experience mapping.
(11:38):
So this is somethingthat we do with.
Most of our new clients on anew project, and it's a simple
exercise, but it's so powerfulbecause you, it puts you in
the shoes of the customeror the target audience, and
you have to step through thejourney with them in mind.
And you pause moment by moment,and we ask at each stage,
what is the user thinking?
(11:58):
What are they doing,what are they feeling?
And we're identifyingwhat are those friction
points and what are theemotional highs and lows.
This is important that wedo this with our clients,
even those who know, youknow, the entire product
lifecycle inside and out.
It's an empathy buildingexercise because it grounds
us in ultimately a humanproblem before we just
jump into solutions, whichis easy and fun to do.
(12:21):
So we find that's a reallyhelpful grounding exercise,
not only for our team whomight be ramping into a new
product or a new industry,but also just to help align
stakeholders and ground them in.
The things that matter, andthat's people and the problems
that we're trying to solve.
So that's the first one.
And then the second is moreof just like an overarching
approach for how we crit work.
So embracing critique and howwe make decisions as a team.
(12:44):
And like many organizations, I'msure you know, running regular
design and engineering crits,but approaching it with a very
like empathetic and human lens.
So rather than opening up arubric and checking boxes and
saying, does this look good?
Does this meet the requirements?
Is this to spec?
The first questions that weask have to be grounded in
(13:04):
the user and their needs.
So we ask ourselves like,is this meaningfully
solving the user's problem?
Is this intuitive?
Is this clear?
Can it be understood withoutexplanation, without the
designer voicing over the work?
How does this make me guys feel?
And yes, does this movethe business forward?
Ultimately, is it creatingvalue for the user?
(13:26):
And so even just makingsure that the first lines
of questioning when we'recritiquing work, start with
the user is a really importantpart of how we approach
critiquing collaboration.
And ultimately that comes downto a very empathetic mindset
and it's very intentionalwith how we work and also
with how we hire at Metalab.
Empathy is just a baseline.
(13:47):
Like we require thatcross-functionally.
So our designers, of course,engineers, yes, PMs, but
like everyone needs tohave an empathetic mindset.
And the last thing I'll addto that is, you know, when
you're creating the conditionsfor folks to feel like they're
advocating for the user, it'snot bringing like personal
perspectives to the table.
They're a bit more objective.
(14:07):
And sometimes that meansbringing ideas that are outta
left field or out of scope.
Oh, no.
It's really important in thosemoments to not shut things
down, but instead just tostay curious and to stay open.
That's just really a core partof our culture in terms of
like how we're challenging eachother in service of solving
(14:29):
the right problem or theright person in the right way.
Hannah Clark (14:33):
Okay.
I like what you brought up hereabout the way of working and
obviously, you know, keepinghuman elements central, I think
is a through line that we'llhave through this whole chat.
I wanna talk a little bitabout expanding on what we
sort of talked about withregards to where human.
Interference and connection iscritical and where AI really
is, you know, the solution tostep in, like kind of where,
(14:54):
when do we kind of make someof those decisions on what is
for AI and what is for people.
When you think about your teamand how things are done and
led at Metalab, how do youkind of make the call between
what is a task to outsourceto a robot and what do you
keep in the human realm?
Megan O'Rourke (15:11):
Not to totally reframe the question, but.
I think it's rarelyone or the other.
I think it's often about knowingwhen we leverage AI and when
we lean on that insight to kindof go deeper there, I can share
an example within the contextof a project that we've worked
on and when we chose to indexone direction versus the other,
(15:35):
so we were working with a big,global athletic manufacturer,
we were helping to improvetheir internal tool ecosystem.
So think about things likeproduction workflow throughout
production lifecycle, likephysical production lifecycle.
And the company had done aton of research, but what they
were really missing was a bitof clarity and a through line,
(15:57):
and really like an emotionalhook that could really convince
people to go in, all in onexecuting on this initiative.
We started by leveraging AI'cause we needed to make sense
of mountains of research andneeded to cluster feedback.
But what it didn't do waslike really hone in on
the feeling for the endusers of these products.
(16:21):
And ultimately that's whatmattered to our stakeholders.
Like they already had thebusiness case, but they needed
to understand why all thesebroken tools were causing as
much frustration as they were.
We parked a lot of that AIdriven work and we got in the
field, so we spent weeks onsite with dozens of user groups
to like really understand whatwas working, what was not.
(16:43):
And if you've ever had thepleasure of sitting next to
someone who is struggling todo their work, kind of like
the work is the workaround,as we say in these scenarios,
but it just builds such adeep empathy and understanding
and it allowed us to get way,way more meaningful content.
We were ultimately able touse for storytelling purposes.
(17:04):
For example, one, we gotlike really great sound bites
and you can just hear thefrustration in people's voices
just lamenting the challengesthat they were facing.
Capturing videos, youcould see people working
through the workaroundsfor their day-to-day work.
And yeah, just those moments oflike insight and empathy that
come from sitting down next tosomeone who's working through.
(17:29):
A problem thatthey've normalized.
And when you're just sittingwith that, like you just can't
untangle yourself from it.
And ultimately those becamelike core pillars for how we
were telling the story backto our stakeholder group.
So considering high emotionalweight of that problem,
these are people stay today tasks and work this how
they feel about their job.
(17:51):
And then considering thosekind of storytelling needs of
the stakeholders and bringingthem along in a way that could.
Make them feel like theyreally understood the impact
of the challenges that theirteams were facing through
those lived experiences.
So it's a long way of sayingit's rarely either or for
us, it's often about kind offinding those right moments
(18:11):
where it can be leveraged, andthen also staying open to those
limitations of being open andcritical to pivoting back to
those more human led approaches.
Hannah Clark (18:23):
That's a beautiful answer.
There's so much in there.
I appreciate the flexibleapproach because I can resonate
with this idea of the beautyof being able to be in a field
research position and be able toreally connect personally with
people who your product impacts.
There's really no substitutefor being able to get really up
(18:43):
close to, you know, well, how isthis person experiencing this?
Because to just parse throughdata and just get insights, you
know, that are broad strokes,they're very disconnected
from the actual impact thatyou know, that you would
see if you're on the user.
Side of the screen.
So yeah, I think that's a reallylovely way to look at it and
kind of what I'm getting fromthat to sort of summarize that
back to you is being flexibleenough to kind of lean on AI
(19:08):
to sort of parse and organizeand make things digestible.
But to lean more on humans, tomake more of an interpretive
role and kind of play more ofa run interference a little bit
for what is the real impact?
What am I missing by notunderstanding the user's pain
point intimately that canmaybe force me or cause me
(19:28):
to overlook some of the data,the way that it's presented in
kind of like a parsed format.
Megan O'Rourke (19:34):
Totally.
Well, and I think yeah, if youwere to just look at these like
large swaths of data, you'remissing out on the nuances
that come from those like ofsoundbites we even found in
leveraging AI for some of thatinfield research summaries oh,
quotes were misattributed andthe emotions were like really
flattened and it just didn'thave that same resonance.
(19:55):
So I, I feel like it's embracingthat moment to say, okay, no,
like we need to go we were ableto use AI to get us here, but
what's that differentiation?
What's that compellingstory point?
Like we were saying earlier,that nuance of understanding
like, okay, how am I gonna getthis across the finish line
in a compelling and human wayand build upon the things that
(20:15):
AI is able to accelerate forus, is going to continue to
be the differentiator there.
Hannah Clark (20:20):
My experience with that that calls to mind,
I used to work, I was alsoin a marketing background,
and we used to have a,an agricultural client.
I promise.
This connects todigital product as well.
We used to really rely withour marketing strategy on
just straight up results.
Like we would just talkabout, you know, what's
the results you can expect?
What is the averageresult that the average
customer gets in your area?
(20:42):
And just really kind oflean on a very data first,
very flattened as you'd say,approach to how we're going
to kind of sell the, you know,the results or what you could
expect from this product.
I had an amazing opportunityto actually go to farms where
the product was being usedand interview families and
(21:02):
communities that were actuallyhands-on, like using the
products and, okay, this mightbe like a little bit way more
human than the average useryou know, depending on the
solution that you're behind.
But I had an opportunityto spend some time with
a Hutterite colony.
I don't know if you'refamiliar with Hu Writes.
There's like parallels to bedrawn with Amish communities in
the United States, but basicallythey're very live off the land.
(21:24):
They're very handmade.
Everything is made from scratch,this very low technology
usage community, and it wasamazing to be able to see the
real impact that a productwould have those results.
Little decimal points thatwe would think of in a
data-driven, like a purelydata-driven campaign.
Seeing those, what those actualdecimal points mean in a real
(21:49):
life context completely changeshow you think about what that
means as a marketer, as aproduct person, as whoever is.
Behind that solution and you,it really reframes how you
empathize and therefore developand, you know, strategize
around the needs of thosepeople because they're no
longer just, you know, likecustomers that are buying
(22:10):
and getting these results.
They're people who arereally impacted day to day
by what you're offering them.
So I, yeah, I mean, I don'tthink everybody is so fortunate
to be able to get that kindof a hands-on experience.
I do think that there's a lotof value in finding ways to
get closer and spend time.
With users to be able to kindof see that journey from their
(22:31):
point of view and like youjust described, like to really
be able to see that journeyand like where those friction
points really impact likeso many people around them.
Anyway, there's a littlestory time for me.
Megan O'Rourke (22:43):
No I love that and I, here's what's
so great about that is whenyou are reflecting upon that
experience, I can hear thecare in your voice and I
can hear the impact that hascontinued to have on you.
That is something AI can't do.
AI is not going to care.
It's not going to care deeply.
It does not have a heart.
And sure there's, you know, thememory that you can look back
(23:06):
in time and say, what is that?
But it's not going to havethat same care and conviction
that you've just shared.
I would argue that I thinkit's actually more important
than ever, especiallyin a remote culture.
Many of us work indistributed teams.
We aren't on the ground dayto day with our end customers.
We prioritize those in-personmoments and connection
(23:27):
because we're havingless and less than that.
So sure, it might cost moremoney and take more time.
You have to make a businesscase to go spend a week on site
with farmers who are using theseproducts every day, but that is
such an incredibly valuable useof time because you're carrying
that experience then in yourheart and you are caring deeply.
(23:48):
I think it's money well spent,money and time well spent.
Hannah Clark (23:51):
I agree.
I think that this is an erathat's really highlighting
the difference betweenraw productivity and being
really customer centricand results focused.
And I think being resultsfocused in this context
really means, you know,is what I'm doing.
You know, I can put out thingsreally quickly, I can accelerate
cycles, I can, you know, doall these things, but if it
doesn't truly connect with whoI'm trying to reach, and if it
(24:13):
doesn't really solve people'sproblems at the root cause.
That productivityis, it's cheap.
Megan O'Rou (24:21):
But is it valuable?
Hannah Clark (24:22):
Exactly.
Exactly.
Yeah.
Okay, so let'sget tactical then.
So if you are working withclients who are really eager to
integrate AI into everything,what would be your framework
for determining, you know,like when do you recommend
leveraging AI tools in,say, like a client's product
versus a human led process?
Megan O'Rourke (24:43):
We tend to ask ourselves three questions,
but before I reveal what thoseare, I'll just harken back to
the fact Metalab's been aroundfor about 20 years and we've
seen a lot of technology waves.
So there's always hype.
There's things that takeover, you know, it's Web3,
oh, it's mobile first design.
Now everything's AI andthere's conversations that
we have regularly where weare reminding ourselves the
(25:04):
technology itself isn't.
What matters most?
Like where are we drivingtoward positive outcomes?
And I'll attribute this quoteto our chief design officer,
Sarah Vienna, total badass.
She has this great question,this provocation that
super direct, and it's veryconstructive, and she asks, does
this product even need to exist,or this feature or this element?
(25:27):
And really the question thereis are you building something
because it solves a realproblem for real people with
a real need or because it'strending and it's something
that can just be leveraged.
The second is AI reallythe right tool or the job?
So is it making the experience?
Faster, great, smarter,let's hope, impactful.
(25:48):
It needs to be or arewe just asking it to do
something that it's not goodat, which might be being
empathetic or building trust.
And then the third is, what isthat risk if it gets it wrong?
So low stakes output, likecontent tagging, you're like,
yeah, sure, like low risk.
But if it's somethingthat ultimately affects.
(26:08):
Accuracy or someone's senseof being understood or even
just like being dismissed.
If they're not happy withthe AI output, then I
think that deserves justa line of questioning and
validation of does thisreally need to be leveraged?
So I think that's ultimatelywhy the grounding question of
does this need to exist and why?
Reminds us that AI shouldnever just be the reason
(26:30):
something gets built.
It should be used to empowerand enable work to work better.
Hannah Clark (26:36):
I really like that, and I think
that is a very crucial.
Approach and line ofquestioning that can easily
kind of get lost in the fold.
I had a conversation agesago, this is you know, one of
those addendums of you know,additional resources, but a long
time ago we had a conversationwith Samantha Gonzalez who is
she was also working, I'm notsure if she's still there,
but she was working at a firmthat was very specialized
(26:57):
in ethical product design.
And that was a big layer as wellin their process was the way
that they kind of framed it was.
Like, she tends to use alot of improv exercises in
her process with clients.
And her thing was, what isyour product's evil twin?
And it was kind of like a wayto kind of look at some of
the ethical, weak spots orareas that kind of oversight
(27:18):
or Yeah, like kind of lookat does this need to exist?
Is this a good thing?
You know, like just kind ofa different way of framing.
So this is kind of reminiscentof the process that she used,
and I think that it's likethat conversation happened
well before AI was even a chat.
Now we're talking aboutthis in you know, there's so
much excitement about thistechnology that I feel like
sometimes we get a littlebit into the hype and don't
(27:40):
really think about some of theramifications that some of these
things have that are easy tooverlook in the excitement and
drive towards the solution.
So I think that I, this is aprocess I hope everybody starts
to adopt as a matter of course.
Megan O'Rourke (27:56):
You've probably experienced this in using
other products, and you cantake or leave this example,
and I won't call them outby name, but I think about
a product I have used forthe better part of a decade.
I love this product.
I'm a diehard user.
And it rolled out an AIfeature that I think really
missed the mark and it'sa fitness tracking app.
So I like uploaded ahike from this weekend.
I got this nice little AIsummary that was clearly
(28:17):
meant to be a pat on the back.
Oh, great.
New hike you've never donebefore great elevation.
Like all this stuff would'vebeen great if it was true.
None of that was accurate andI felt this sounds dramatic.
So like disappointed in thisproduct and the rollout of that,
because I'm like a diehard userof this app and I just, I saw
(28:40):
content that wasn't accurate,so it felt really generic.
It felt off base.
I'm like, do I trustthis app anymore?
Or it's just gonna makethese broad strokes.
And so I think that's just asmall, like personal example,
but one risk of what's at stake.
When you have diehard users whoaren't resonating with like your
AI feature, credibility erodes.
(29:04):
Now, I'm still gonna use theapp, but I just wanna dismiss
that little AI summary now.
Like I don't need it.
It doesn't actually provideany value and it does not
pass muster of does thisactually need to exist?
Does this solve a need or isthis providing user benefit?
No, actually quite the contrary.
Hannah Clark (29:19):
Yeah, I have had a similar reaction, I'm sure to
products that I've used and, butothers that I've kind of seen
emerge where it's kind of like adifferent area of skepticism in
which I feel like the potentialfor abuse of the technology
that is being developed islike so clear to those who
aren't working for the product.
(29:41):
Okay.
So I'm not gonna name namesalso, and you know, the solution
basically that I saw was.
Being able to use a sampleof someone's voice, a very
brief sample of someone'svoice to create and generate
audio content similar towhat we're doing right now.
And I can see the desire to helpcreators scale and to be able to
(30:03):
produce more content and put outmore value faster and with less.
Time spent having conversationsas if that's a waste of time.
I think this is the best partof my job but anyway, I can see
the value proposition and yetI kind of feel like, I mean, is
it just me or does the potentialfor abuse of something like this
(30:24):
maybe overshadow the value interms of productivity and is
that a good thing, that we'renot having real conversations
and trying to outsource them?
These are kind of the questionsthat I'm asking, and this is
kind of what I mean about thehype kind of overshadowing or
causing people to kind of losethat layer of, I wanna say
common sense because, you know,I, I don't know if, I think
(30:48):
it's a good thing that we areable to take a small sample of
someone's voice and replicatethat however we see fit.
Megan O'Rourke (30:56):
Does it need to exist?
Hannah Clark (30:58):
Does it need to exist?
Yeah.
Megan O'Rourke (31:00):
And importantly, it's does it deserve to exist?
Yeah.
Is there a fundamental why andwhat is the trade off there?
Is that robbing us fromthe full conversation
that you and I both love?
Hannah Clark (31:10):
Yeah.
Well, the full conversation.
Megan O'Rourke (31:12):
It does not deserve.
Hannah Clark (31:13):
Exactly.
Well, and we're I feel likeright now we're in a time
and space where, I mean, notto be dramatic, but like the
products that we build noware truly intangibly shaping
the world that we live in.
And it's like the productdecisions that we make now
aren't just about what kindof value we are and aren't
creating for stakeholders.
It's also about what is thevalue and what is the kind
of culture that we're kindof laying the groundwork
(31:35):
for generations to comeand ourselves, even in the
kind of the near future.
You know, we have like muchbigger questions to ask
ourselves now that we'vebeen bestowed with this, like
pretty significant power.
Anyway, this is getting tophilosophical territory but
yeah, I think that this is likethis layer of questioning of
does this deserve to exist?
Is AI and the answer here, orare we maybe taking a route
(31:59):
that is better left in the bin?
Yeah.
Let's talk about storytellingin product design.
So the introduction of AI.
You know, we have obviouslychanged a way that we approach
narrative and storytelling.
I'm curious about how do youkind of use human storytelling
in the process of developinga new, like you, you
(32:20):
mentioned you guys do some zto one kind of development.
What does that looklike in process?
Like, how do you kind ofdistill human storytelling
into that early developmentprocess of a product?
Megan O'Rourke (32:30):
And I think this hearkens back to the earlier
part of this conversation.
So look at usconnecting that thread.
So I think at our core, likestorytelling has always been a
part of our design process wherewe've always been of the mindset
of no decks, you know, a hundredpage decks, like show prototype,
brain experience to life.
And so I think AI hascertainly accelerated
certain parts of our work.
Like it allows us tosynthesize things faster or
(32:52):
spot patterns quicker, right?
Series quicker.
But that element and thatnuance and that discretion.
Like what and how andwhen I think is rooted
in that human empathy.
So at Metalab we havebroad range of clients.
So how we work with thattwo person founder team
looks very different toour partnership with our
(33:14):
enterprise organization.
So for example, with ourtwo person founder team.
Do you think they wannasit through a big deck?
No.
No.
They want us to open up Figmaand just walk through the
prototype and just kind oflightweight narrative and
discuss as we go and unpack.
And sometimes we're riffinglive because that's what
works well for them.
And it's an understandingthrough stakeholder
(33:35):
interviews and just the wayin which their organization.
Run.
You know, it doesn'trequire all that perfectly
curated storytelling.
Whereas other partners ofours, product teams who might
sit within large enterpriseorganizations who might
be bringing along widerstakeholder teams, there's a
lot of care and crafting thatgoes into those presentations
(33:56):
and that storytelling andcreating super defensible
positions and rationalefor every decision made.
And it's that understandingthrough yeah, experience,
but also just intuition andempathy and at that, because
in an agency we have thepleasure of working with so
many different clients inso many different stages.
It's really that tailoringof the process and the
(34:17):
approach that I think isreally sort of human led.
So we'll have a baselineprocess, but we rely on the
project team caring deeplyand asking the critical
thinking questions what isgoing to be best suited for.
This audience for thisstakeholder need and the needs
of what we're hoping to achieve.
So I feel like it's humanempathy is what's driving
(34:39):
the tailoring to like thehow, what and the when.
Hannah Clark (34:42):
Cool.
So to kind of dig deeper onthat, do you have a specific
example that you could shareof this kind of empathetic
approach and how it's kind ofuncovered, like an insight or
a solution like just throughthat kind of workshopping.
Megan O'Rourke (34:55):
For sure.
We've got this one very coolclient called Tally Health.
They're a longevity focusedcompany and they focus
on at home testing, likebiological age testing and
health recommendations.
So got a lot of people whoare super passionate about
health, which is very cool.
And anyway, they had come to uswith, again, a lot of existing
(35:16):
research and they had a prettystrong conviction in knowing
what problems they were solvingand who they were solving for.
So they were like, okay,let's get straight to design.
And our team kept feelinglike there's kind of
this like missing layer.
And so objectively, like we hadall the data, but we were kind
of missing this like behavioral,why I would've context there.
So we got to work withsome early research and
(35:38):
prototyping and startedsimulating what the delivery
of results would look like.
So imagine that you'resending your test, you
get your results back.
This can be like a prettyemotional experience
and sometimes like afairly confronting one
to your biological age.
And yeah, what we learned wasthat people who got younger
than their biological age,they felt really affirmed.
(36:00):
You know, they were like,I've made the right life
choices and health choices.
And then the folks whowere older than their
biological age were likerange of emotions, like fear,
shame, sometimes denial.
And what this differencewas here was like the
mindset, not just the number.
And so like even people whohad received quote unquote,
(36:20):
negative or difficult resultswere motivated to change.
And so anyway, all ofthis to say the data was
there, but the behaviorneeded to be understood.
And it turned out to be like areally impactful insight that
drove a major feature withinthe product, which was creating
these personalized health plan.
So interestingly, that wasn'ton the original roadmap.
(36:43):
Once we saw what was inthe research, it became
a real cornerstone ofexperience and it's actually
like a main retentiondriver within the product.
That was just an exampleof had we just followed the
data, we would've missed thatnuance and it was empathy.
It was that human approach thatreally revealed that insight,
and then our design teamcould bring it into something
(37:03):
really like meaningful andimpactful within the product.
Hannah Clark (37:06):
That's amazing and a very succinct like example.
And I like, I feel like that'ssuch a huge thing to discover
too, because that opens likewhole avenues for a product
portfolio around like next stepsand how the product can mature.
So yeah, what a huge thingto kind of discover through
that like very empatheticempathy led process.
(37:28):
I think that's anamazing example.
I know we've kind of takenup a lot of your time here,
soapboxing and kind of getgoing all over the map.
Megan O'Rourke (37:34):
No we're passionate.
We're passionateabout this subject.
Hannah Clark (37:37):
Yes, exactly.
Yes.
That's great.
I'm glad that's clear.
I do want to kind of come backto the product leadership aspect
because you know, we've gota lot of product leaders who
listen and I know that all ofus are kind of grappling with
this idea of how to maintainthis human touch and kind
of strike this balance ofAI powered productivity and
making sure that we're stillvery much focused on the human
(37:59):
components of our organizations.
So what are three actionablesteps in your view, that you
would recommend implementingin teams starting next week
to product leaders listening?
Megan O'Rourke (38:10):
Yeah.
These are simple ones, theseare things you can try, doesn't
require a lot of buy-in,you can just get on with it.
The first is sharing astory, not just statistics.
You know, we've talked a littlebit about like the importance
of bringing that human voice in,bringing a soundbite, bringing a
quote, bringing a raw clip intoyour next print or team review,
(38:30):
and let that speak for itself.
And it's really important tolet your broader team sit and
feel that problem rather thanjust see cliff swaths of data.
So sharing a story, two,this is again a kind of a
personal one for me, butcreating one moment each week.
To check in or give feedback.
So I practice a little somethingcalled feedback Fridays.
(38:51):
You do it with the cadencethat works for you, but it
doesn't have to be formal,but just like a quick check
in with a team member or asmall note of appreciation for
team members goes a long way.
So AI can help track standupsand whatnot, but it's that
recognition and that outreachlike that comes from you.
So definitelythat's an easy one.
And it feels good.
(39:12):
It feels good, especiallyon a Friday to wrap
up a week like that.
And then third is that empathy.
I'm gonna call itempathy rubric.
So for those critiques,creating, you know, what
are your go-to list ofquestions that you wanna
bring to your product reviews.
Your crits, maybe informingroadmap decisions that
are rooted in thoseuser-focused questions.
So does this meaningfullysolve the user's problem?
(39:33):
Does this deserve to exist?
And how might someonefeel in this moment?
And really driving that lineof questioning that shifts.
Ultimately the conversationfrom, did we build it or
did we build it right to,are we building on the right
thing for the right reason?
So it's really not about notusing AI, it's about using it
with intention and using AIto help create capacity for
(39:56):
the things that I think mattermost, which are really creating
moments of human connection.
Hannah Clark (40:01):
So elegantly said.
Oh, Megan, thank you somuch for joining me today.
This has been such a great chat.
It's been all over the map.
It's cathartic, it's beenempathetic, it's been beautiful.
Where can folks keepthe conversation
going with you online?
Megan O'Rourke (40:14):
Yeah, so definitely encourage folks
to follow metalab.com.
It's our full portfolio, butyou can also follow us on
LinkedIn or Instagram justto keep up to date on new
work and portfolio updates.
And then for me, youcan find me on LinkedIn.
Happy to connect with folks.
Hannah Clark (40:29):
Wonderful.
Well, it's been wonderfulconnecting with you, and thank
you so much for making the time.
Thanks for listening in.
For more great insights,how-to guides and tool reviews,
subscribe to our newsletter attheproductmanager.com/subscribe.
You can hear more conversationslike this by subscribing to
the Product Manager whereveryou get your podcasts.
Whether or not you personally participate in
the Wicked movie hype train,I'm reasonably sure you're
familiar with The Wizard of Oz.
In the story, the character ofthe Tin Man is portrayed as a
humanoid robot who wants nothingmore than to have a heart.
But when he finally receivesone, what he gets is actually an
imitation of a heart, a silk bagof sawdust that convinces the
Tin Man that he has the empathyand emotional depth of a human.
(00:25):
If you haven't figured outwhere I'm going with this,
the Tin Man makes for apretty intriguing allegory
for where we're at with AI.
LLMs have reached a levelof advancement in which they
can pretty convincingly mimicthings like empathy and deep
human understanding, andthat presents dual effects.
On one hand,astonishing opportunity.
But on the other, hiddentraps that can slowly
(00:45):
melt away your impact.
My guest today is MeganO'Rourke, Executive
Director of Product atMetalab, an end-to-end
product design agency.
Megan's role sits at theintersection of design,
development, research and peoplemanagement, and so she's keenly
aware of the connection betweenstorytelling and user value.
And perhaps more importantly,what's really at stake if
we override empathy forefficiency, both in product
(01:07):
development and in leadership.
We discussed the balancing actbetween AI powered productivity
and human-driven resonance,why storytelling is as critical
as data, and the questionthat every product leader
should be asking constantly—ifthey have the courage.
Let's jump in.
Oh, by the way, wehold conversations
like this every week.
So, if this sounds interestingto you, why not subscribe?
(01:30):
Okay, now let's jump in.
Welcome back to theProduct Manager podcast.
I'm here today withMegan O'Rourke.
She's the Executive Directorof Product at Metalab.
Megan, how are you doing today?
Megan O'Rour (01:41):
I'm doing so well.
Excited to be here.
Hannah Clark (01:43):
Me too.
So can you tell us a littlebit about your background
and how you got to whereyou are today at Metalab?
Megan O'Rourke (01:48):
Absolutely.
I got my start in advertising.
Crispin Porter + Bogusky, thisbig agency in the States known
for creating very bold verydestructive work, very culture
shaping, sort of advertising.
So I was part of a teamthat managed the creative
process, reviews andproduction, and through that
it really instilled in meand appreciation for detail.
(02:11):
For high craft and alsojust the exposure to working
with world class creatives.
Even though I'm, I didn'tconsider myself a creative,
just loved being partof the creative process.
So loved advertising, butI found that over time I
was yearning for somethingjust a little bit different.
Not these sort of one anddone campaigns, but rather
something that felt a littlebit more living and breathing
(02:34):
so you could build andevolve and ultimately respond
to a need and a desire.
That shift ultimately ledme to Metalab, which is
where I've been since 2016.
So coming up on 10 years now.
It's a long time in agency land.
Hannah Clark (02:49):
In any job now.
Yeah.
Megan O'Rourke (02:51):
In any job.
In any job.
But I mean, yeah, it reallyspeaks volumes to the type
of work that we do and thepeople that we work with that's
keeping work really interesting.
And I'm happy to be there.
Yeah.
Metalab is a, an end-to-endproduct, very design led agency.
So we partner with companies.
Ranging from early stagestartups to Fortune 500.
Some clients come to us to gofull Z to one, which is always
(03:13):
fun and challenging, whereasothers come to us to maybe a
partial or a full redesign oroverhaul of an existing product.
So we're very design led.
At our core, we're veryfocused on craft and outcomes.
We're not about vaporware.
We don't have bigstrategy decks.
We are focused on just buildingreally great products and
making products that matter.
(03:34):
So my role today.
I'm the executive directorof product management at
Delam, so that means I,I lead our PM function.
I am involved in some of ourhigher profile projects as
well, and these days I amthinking a lot about how we
build happy teams and teamsthat build great products.
Hannah Clark (03:54):
Yeah.
Well, I'm so excited totalk to you because all of
these experiences reallyfunnel well into our core
topic today, which is.
All about how product teamscan leverage storytelling
and empathy in this ageof AI, such a chaotic,
full of gray area time.
So in the spirit ofstorytelling, I'd love if you
could share an anecdote thatsort of puts in perspective,
(04:15):
you know, what do we have togain and maybe also what's at
stake if we don't prioritizethese very human elements
of storytelling in ourorganizations and our products.
Megan O'Rourke (04:23):
I'll share an example that is more
on the personal side, likeit's not a flashy product.
It's not a big strategicdecision, it's just this
very like human moment andit's about someone on my team
who is this really smart,really engaged individual.
They're always supervocal in meetings.
They bring ideas to thetable, and over the course
of a couple weeks, I juststarted to notice like they
(04:45):
were going a little bit quiet.
They weren'tspeaking up as much.
They seemed a little withdrawnand there was nothing dramatic.
There was no like performanceconcerns, but there was
just this shift thatI could kind of feel.
And I thought in this momentI was like, if I was running
completely on automation, if Iwas using AI to attend meetings
for me and just tracking alongon things that needed to be done
(05:05):
or dashboards of work completed,I probably would've missed it.
But I was there, I was payingattention, I was reading the
nuances, and I was able tosee a bit of a difference
and just reach out to themand say Hey, how you doing?
Like nothing formal, but just ahuman connection or reach out.
And through conversation Irealized that, you know, there
was something deeper going on.
(05:27):
They were feelingreally overwhelmed.
They were not really sureof kind of their place
in this complex and fastmoving product and they
just kind of felt invisible.
And it just, it was this likeaha moment for me because
I thought AI is so greatat so many things and it's
not great at picking up atthe absence of information
or the quiet moments.
Like it didn't catch thathesitation of that person just.
(05:51):
Muting or unmuting andthen choosing to mute
again, like it doesn'tsay to us something's off.
And I feel like that'swhat we notice as human.
So small example there.
But I think what it representsfor me is in leading with
the human approach andwith empathy, what we have
to gain here is trust.
And I look at that is that'sreally the foundation for
how we collaborate, howwe support each other.
(06:13):
In this example, howwe give feedback.
Those are so coreto how we work.
And.
To answer your questionof what's at stake here?
If we overly on AI in thesemoments and we let it, you
know, stand in for us beingpresent and attentive and
having intuition, then we'relosing out on those signals and.
(06:34):
When individuals on theteam feel like people aren't
paying attention or peoplearen't caring, that's a really
quick way to get to lack ofengagement or feeling withdrawn.
And it would be awful to losegreat people, not because their
work doesn't matter, but becausethey don't really feel seen.
Hannah Clark (06:49):
Yeah.
Okay.
Multiple reactions I haveto that because I feel
like this really hits.
One thing that kind of comesto mind, first of all is I
feel like what you're touchingon is kind of a reckoning
that a lot of us are sort offacing about, you know, what
is the role of work and whatis the role of a company in
our culture, in our society.
(07:10):
If we are trying to automatea way the things that make
these things meaningful to usI think it's a really important
reminder that there are thingsthat, you know, we could choose
to automate, but we stillhave to be selective about.
What do we stand to lose byremoving ourselves sometimes
from those like reallyessential human interactions
(07:30):
that create culture and thatnurture and foster culture
in an organization and makepeople wanna stay for nine
years or 10 years or more.
The other thing that I thinkwas really poignant that you
said was about this idea ofwhat is not being said, the
idea of storytelling being alot about what is not revealed.
(07:51):
I had a very acutemoment of that recently.
There's a fringe festivalthat just completed in my area
and in my non-career time.
I am a performer and a lotof the storytelling that's
happening there, you know,I've been kind of observing
it more with the idea of maybedoing my own show you know,
a non-professional show, butsomething that has really kind
(08:11):
of come to the surface when Isee really good storytellers.
And I think this applies to,you know, even in a product
or professional context.
The really good storytellersare able to show a moments
and a narrative by beingselective about what they
include and what they omit.
And so like in some cases you'llsee a story that kind of takes
you on a whole journey overseveral years, or can be, you
(08:33):
know, through the course of asales funnel or whatever, but
the moments that you chooseto include and also mean being
selective about what moments.
You don't include and whatmoments you have to pay
attention are absent fromlike a certain narrative.
So I think it's kind ofinteresting that you're
bringing this up now becausethis is something that's
really been on my mind is likestorytelling is as much about
(08:54):
what we choose not to say.
You're right.
Like this is something thatas people, we have such a
unique ability to derivemeaning from certain things
that aren't explicit andalso derive meanings from
silences that are very subtle.
Anyway, it's a bit of atangent, but I'm liking
where this is going.
Megan O'Rourke (09:11):
I love that and I think that's, we'll
probably get into this later,but like I think that's
the important element ofbringing the human purpose.
There's so much information, butit's the discretion and it's the
intuition and it's experienceof understanding what makes the
cut and what's going to createthat compelling story when all
of the data can be presentedto you, but what are you using?
(09:32):
What are you excluding andhow are you packaging it up?
That's the nuance that I reallysee as the benefit coming
from the human side of things.
I don't want.
AI could make that call for me.
Hannah Clark (09:43):
I agree.
I think it, I don't want AInecessarily make that call.
And I think that there's areally important stage of this.
I mean, we, when we think abouta sales funnel for example,
you know, we think of theawareness stage and that's
like a lot of, that maybe issuitable for being generated.
You know, there's alot of awareness stage.
Kinda stuff that we can do thatmakes sense to kind of automate.
(10:04):
But that nurture part of thesales funnel I think is that
is an area where we have sucha huge opportunity to be able
to really infuse very deeplypersonal experiences, foster
an emotional connection,leverage community.
Like I feel like there issuch a, an opportunity there.
And I think that the hungerfor really compelling, human
(10:27):
elements is going to onlyincrease now that there is such
a volume of generated content.
Megan O'Rourke (10:31):
Oh, I agree.
Hannah.
I think we're verymuch aligned there.
That will become increasinglythe differentiator.
Hannah Clark (10:38):
Yeah.
And, okay.
When we talk aboutdifferentiators in product
design, like what do youlook for in practice?
Like when you're, you know,developing a narrative
or like working witha client at Metalab?
What are some of the morespecific strategies or exercises
that you might use with yourteam to create conditions
for like empathetic design?
Megan O'Rourke (10:56):
Okay, so I'll start by saying like
humanity and empathy.
I think that shows up notjust in the what we build,
but the how we build this.
My team's, I have to hearyou say this all the time.
I'm like, it's not just whatwe build, it's how we do.
It's the experienceof working together.
It's the experience ofhow we listen, how we
challenge, how we're creatingspace for the honest and
(11:17):
the real conversation.
I'll share one specificexercise that we love to use
just to help build empathyfor our end customers.
And then also just onemore philosophical or kind
of overarching strategicapproach for how we
create those conditions.
So the first is the exercise.
So you're probably familiarwith this as there are many
PMs, but it's going back to thebasics of experience mapping.
(11:38):
So this is somethingthat we do with.
Most of our new clients on anew project, and it's a simple
exercise, but it's so powerfulbecause you, it puts you in
the shoes of the customeror the target audience, and
you have to step through thejourney with them in mind.
And you pause moment by moment,and we ask at each stage,
what is the user thinking?
(11:58):
What are they doing,what are they feeling?
And we're identifyingwhat are those friction
points and what are theemotional highs and lows.
This is important that wedo this with our clients,
even those who know, youknow, the entire product
lifecycle inside and out.
It's an empathy buildingexercise because it grounds
us in ultimately a humanproblem before we just
jump into solutions, whichis easy and fun to do.
(12:21):
So we find that's a reallyhelpful grounding exercise,
not only for our team whomight be ramping into a new
product or a new industry,but also just to help align
stakeholders and ground them in.
The things that matter, andthat's people and the problems
that we're trying to solve.
So that's the first one.
And then the second is moreof just like an overarching
approach for how we crit work.
So embracing critique and howwe make decisions as a team.
(12:44):
And like many organizations, I'msure you know, running regular
design and engineering crits,but approaching it with a very
like empathetic and human lens.
So rather than opening up arubric and checking boxes and
saying, does this look good?
Does this meet the requirements?
Is this to spec?
The first questions that weask have to be grounded in
(13:04):
the user and their needs.
So we ask ourselves like,is this meaningfully
solving the user's problem?
Is this intuitive?
Is this clear?
Can it be understood withoutexplanation, without the
designer voicing over the work?
How does this make me guys feel?
And yes, does this movethe business forward?
Ultimately, is it creatingvalue for the user?
(13:26):
And so even just makingsure that the first lines
of questioning when we'recritiquing work, start with
the user is a really importantpart of how we approach
critiquing collaboration.
And ultimately that comes downto a very empathetic mindset
and it's very intentionalwith how we work and also
with how we hire at Metalab.
Empathy is just a baseline.
(13:47):
Like we require thatcross-functionally.
So our designers, of course,engineers, yes, PMs, but
like everyone needs tohave an empathetic mindset.
And the last thing I'll addto that is, you know, when
you're creating the conditionsfor folks to feel like they're
advocating for the user, it'snot bringing like personal
perspectives to the table.
They're a bit more objective.
(14:07):
And sometimes that meansbringing ideas that are outta
left field or out of scope.
Oh, no.
It's really important in thosemoments to not shut things
down, but instead just tostay curious and to stay open.
That's just really a core partof our culture in terms of
like how we're challenging eachother in service of solving
(14:29):
the right problem or theright person in the right way.
Hannah Clark (14:33):
Okay.
I like what you brought up hereabout the way of working and
obviously, you know, keepinghuman elements central, I think
is a through line that we'llhave through this whole chat.
I wanna talk a little bitabout expanding on what we
sort of talked about withregards to where human.
Interference and connection iscritical and where AI really
is, you know, the solution tostep in, like kind of where,
(14:54):
when do we kind of make someof those decisions on what is
for AI and what is for people.
When you think about your teamand how things are done and
led at Metalab, how do youkind of make the call between
what is a task to outsourceto a robot and what do you
keep in the human realm?
Megan O'Rourke (15:11):
Not to totally reframe the question, but.
I think it's rarelyone or the other.
I think it's often about knowingwhen we leverage AI and when
we lean on that insight to kindof go deeper there, I can share
an example within the contextof a project that we've worked
on and when we chose to indexone direction versus the other,
(15:35):
so we were working with a big,global athletic manufacturer,
we were helping to improvetheir internal tool ecosystem.
So think about things likeproduction workflow throughout
production lifecycle, likephysical production lifecycle.
And the company had done aton of research, but what they
were really missing was a bitof clarity and a through line,
(15:57):
and really like an emotionalhook that could really convince
people to go in, all in onexecuting on this initiative.
We started by leveraging AI'cause we needed to make sense
of mountains of research andneeded to cluster feedback.
But what it didn't do waslike really hone in on
the feeling for the endusers of these products.
(16:21):
And ultimately that's whatmattered to our stakeholders.
Like they already had thebusiness case, but they needed
to understand why all thesebroken tools were causing as
much frustration as they were.
We parked a lot of that AIdriven work and we got in the
field, so we spent weeks onsite with dozens of user groups
to like really understand whatwas working, what was not.
(16:43):
And if you've ever had thepleasure of sitting next to
someone who is struggling todo their work, kind of like
the work is the workaround,as we say in these scenarios,
but it just builds such adeep empathy and understanding
and it allowed us to get way,way more meaningful content.
We were ultimately able touse for storytelling purposes.
(17:04):
For example, one, we gotlike really great sound bites
and you can just hear thefrustration in people's voices
just lamenting the challengesthat they were facing.
Capturing videos, youcould see people working
through the workaroundsfor their day-to-day work.
And yeah, just those moments oflike insight and empathy that
come from sitting down next tosomeone who's working through.
(17:29):
A problem thatthey've normalized.
And when you're just sittingwith that, like you just can't
untangle yourself from it.
And ultimately those becamelike core pillars for how we
were telling the story backto our stakeholder group.
So considering high emotionalweight of that problem,
these are people stay today tasks and work this how
they feel about their job.
(17:51):
And then considering thosekind of storytelling needs of
the stakeholders and bringingthem along in a way that could.
Make them feel like theyreally understood the impact
of the challenges that theirteams were facing through
those lived experiences.
So it's a long way of sayingit's rarely either or for
us, it's often about kind offinding those right moments
(18:11):
where it can be leveraged, andthen also staying open to those
limitations of being open andcritical to pivoting back to
those more human led approaches.
Hannah Clark (18:23):
That's a beautiful answer.
There's so much in there.
I appreciate the flexibleapproach because I can resonate
with this idea of the beautyof being able to be in a field
research position and be able toreally connect personally with
people who your product impacts.
There's really no substitutefor being able to get really up
(18:43):
close to, you know, well, how isthis person experiencing this?
Because to just parse throughdata and just get insights, you
know, that are broad strokes,they're very disconnected
from the actual impact thatyou know, that you would
see if you're on the user.
Side of the screen.
So yeah, I think that's a reallylovely way to look at it and
kind of what I'm getting fromthat to sort of summarize that
back to you is being flexibleenough to kind of lean on AI
(19:08):
to sort of parse and organizeand make things digestible.
But to lean more on humans, tomake more of an interpretive
role and kind of play more ofa run interference a little bit
for what is the real impact?
What am I missing by notunderstanding the user's pain
point intimately that canmaybe force me or cause me
(19:28):
to overlook some of the data,the way that it's presented in
kind of like a parsed format.
Megan O'Rourke (19:34):
Totally.
Well, and I think yeah, if youwere to just look at these like
large swaths of data, you'remissing out on the nuances
that come from those like ofsoundbites we even found in
leveraging AI for some of thatinfield research summaries oh,
quotes were misattributed andthe emotions were like really
flattened and it just didn'thave that same resonance.
(19:55):
So I, I feel like it's embracingthat moment to say, okay, no,
like we need to go we were ableto use AI to get us here, but
what's that differentiation?
What's that compellingstory point?
Like we were saying earlier,that nuance of understanding
like, okay, how am I gonna getthis across the finish line
in a compelling and human wayand build upon the things that
(20:15):
AI is able to accelerate forus, is going to continue to
be the differentiator there.
Hannah Clark (20:20):
My experience with that that calls to mind,
I used to work, I was alsoin a marketing background,
and we used to have a,an agricultural client.
I promise.
This connects todigital product as well.
We used to really rely withour marketing strategy on
just straight up results.
Like we would just talkabout, you know, what's
the results you can expect?
What is the averageresult that the average
customer gets in your area?
(20:42):
And just really kind oflean on a very data first,
very flattened as you'd say,approach to how we're going
to kind of sell the, you know,the results or what you could
expect from this product.
I had an amazing opportunityto actually go to farms where
the product was being usedand interview families and
(21:02):
communities that were actuallyhands-on, like using the
products and, okay, this mightbe like a little bit way more
human than the average useryou know, depending on the
solution that you're behind.
But I had an opportunityto spend some time with
a Hutterite colony.
I don't know if you'refamiliar with Hu Writes.
There's like parallels to bedrawn with Amish communities in
the United States, but basicallythey're very live off the land.
(21:24):
They're very handmade.
Everything is made from scratch,this very low technology
usage community, and it wasamazing to be able to see the
real impact that a productwould have those results.
Little decimal points thatwe would think of in a
data-driven, like a purelydata-driven campaign.
Seeing those, what those actualdecimal points mean in a real
(21:49):
life context completely changeshow you think about what that
means as a marketer, as aproduct person, as whoever is.
Behind that solution and you,it really reframes how you
empathize and therefore developand, you know, strategize
around the needs of thosepeople because they're no
longer just, you know, likecustomers that are buying
(22:10):
and getting these results.
They're people who arereally impacted day to day
by what you're offering them.
So I, yeah, I mean, I don'tthink everybody is so fortunate
to be able to get that kindof a hands-on experience.
I do think that there's a lotof value in finding ways to
get closer and spend time.
With users to be able to kindof see that journey from their
(22:31):
point of view and like youjust described, like to really
be able to see that journeyand like where those friction
points really impact likeso many people around them.
Anyway, there's a littlestory time for me.
Megan O'Rourke (22:43):
No I love that and I, here's what's
so great about that is whenyou are reflecting upon that
experience, I can hear thecare in your voice and I
can hear the impact that hascontinued to have on you.
That is something AI can't do.
AI is not going to care.
It's not going to care deeply.
It does not have a heart.
And sure there's, you know, thememory that you can look back
(23:06):
in time and say, what is that?
But it's not going to havethat same care and conviction
that you've just shared.
I would argue that I thinkit's actually more important
than ever, especiallyin a remote culture.
Many of us work indistributed teams.
We aren't on the ground dayto day with our end customers.
We prioritize those in-personmoments and connection
(23:27):
because we're havingless and less than that.
So sure, it might cost moremoney and take more time.
You have to make a businesscase to go spend a week on site
with farmers who are using theseproducts every day, but that is
such an incredibly valuable useof time because you're carrying
that experience then in yourheart and you are caring deeply.
(23:48):
I think it's money well spent,money and time well spent.
Hannah Clark (23:51):
I agree.
I think that this is an erathat's really highlighting
the difference betweenraw productivity and being
really customer centricand results focused.
And I think being resultsfocused in this context
really means, you know,is what I'm doing.
You know, I can put out thingsreally quickly, I can accelerate
cycles, I can, you know, doall these things, but if it
doesn't truly connect with whoI'm trying to reach, and if it
(24:13):
doesn't really solve people'sproblems at the root cause.
That productivityis, it's cheap.
Megan O'Rou (24:21):
But is it valuable?
Hannah Clark (24:22):
Exactly.
Exactly.
Yeah.
Okay, so let'sget tactical then.
So if you are working withclients who are really eager to
integrate AI into everything,what would be your framework
for determining, you know,like when do you recommend
leveraging AI tools in,say, like a client's product
versus a human led process?
Megan O'Rourke (24:43):
We tend to ask ourselves three questions,
but before I reveal what thoseare, I'll just harken back to
the fact Metalab's been aroundfor about 20 years and we've
seen a lot of technology waves.
So there's always hype.
There's things that takeover, you know, it's Web3,
oh, it's mobile first design.
Now everything's AI andthere's conversations that
we have regularly where weare reminding ourselves the
(25:04):
technology itself isn't.
What matters most?
Like where are we drivingtoward positive outcomes?
And I'll attribute this quoteto our chief design officer,
Sarah Vienna, total badass.
She has this great question,this provocation that
super direct, and it's veryconstructive, and she asks, does
this product even need to exist,or this feature or this element?
(25:27):
And really the question thereis are you building something
because it solves a realproblem for real people with
a real need or because it'strending and it's something
that can just be leveraged.
The second is AI reallythe right tool or the job?
So is it making the experience?
Faster, great, smarter,let's hope, impactful.
(25:48):
It needs to be or arewe just asking it to do
something that it's not goodat, which might be being
empathetic or building trust.
And then the third is, what isthat risk if it gets it wrong?
So low stakes output, likecontent tagging, you're like,
yeah, sure, like low risk.
But if it's somethingthat ultimately affects.
(26:08):
Accuracy or someone's senseof being understood or even
just like being dismissed.
If they're not happy withthe AI output, then I
think that deserves justa line of questioning and
validation of does thisreally need to be leveraged?
So I think that's ultimatelywhy the grounding question of
does this need to exist and why?
Reminds us that AI shouldnever just be the reason
(26:30):
something gets built.
It should be used to empowerand enable work to work better.
Hannah Clark (26:36):
I really like that, and I think
that is a very crucial.
Approach and line ofquestioning that can easily
kind of get lost in the fold.
I had a conversation agesago, this is you know, one of
those addendums of you know,additional resources, but a long
time ago we had a conversationwith Samantha Gonzalez who is
she was also working, I'm notsure if she's still there,
but she was working at a firmthat was very specialized
(26:57):
in ethical product design.
And that was a big layer as wellin their process was the way
that they kind of framed it was.
Like, she tends to use alot of improv exercises in
her process with clients.
And her thing was, what isyour product's evil twin?
And it was kind of like a wayto kind of look at some of
the ethical, weak spots orareas that kind of oversight
(27:18):
or Yeah, like kind of lookat does this need to exist?
Is this a good thing?
You know, like just kind ofa different way of framing.
So this is kind of reminiscentof the process that she used,
and I think that it's likethat conversation happened
well before AI was even a chat.
Now we're talking aboutthis in you know, there's so
much excitement about thistechnology that I feel like
sometimes we get a littlebit into the hype and don't
(27:40):
really think about some of theramifications that some of these
things have that are easy tooverlook in the excitement and
drive towards the solution.
So I think that I, this is aprocess I hope everybody starts
to adopt as a matter of course.
Megan O'Rourke (27:56):
You've probably experienced this in using
other products, and you cantake or leave this example,
and I won't call them outby name, but I think about
a product I have used forthe better part of a decade.
I love this product.
I'm a diehard user.
And it rolled out an AIfeature that I think really
missed the mark and it'sa fitness tracking app.
So I like uploaded ahike from this weekend.
I got this nice little AIsummary that was clearly
(28:17):
meant to be a pat on the back.
Oh, great.
New hike you've never donebefore great elevation.
Like all this stuff would'vebeen great if it was true.
None of that was accurate andI felt this sounds dramatic.
So like disappointed in thisproduct and the rollout of that,
because I'm like a diehard userof this app and I just, I saw
(28:40):
content that wasn't accurate,so it felt really generic.
It felt off base.
I'm like, do I trustthis app anymore?
Or it's just gonna makethese broad strokes.
And so I think that's just asmall, like personal example,
but one risk of what's at stake.
When you have diehard users whoaren't resonating with like your
AI feature, credibility erodes.
(29:04):
Now, I'm still gonna use theapp, but I just wanna dismiss
that little AI summary now.
Like I don't need it.
It doesn't actually provideany value and it does not
pass muster of does thisactually need to exist?
Does this solve a need or isthis providing user benefit?
No, actually quite the contrary.
Hannah Clark (29:19):
Yeah, I have had a similar reaction, I'm sure to
products that I've used and, butothers that I've kind of seen
emerge where it's kind of like adifferent area of skepticism in
which I feel like the potentialfor abuse of the technology
that is being developed islike so clear to those who
aren't working for the product.
(29:41):
Okay.
So I'm not gonna name namesalso, and you know, the solution
basically that I saw was.
Being able to use a sampleof someone's voice, a very
brief sample of someone'svoice to create and generate
audio content similar towhat we're doing right now.
And I can see the desire to helpcreators scale and to be able to
(30:03):
produce more content and put outmore value faster and with less.
Time spent having conversationsas if that's a waste of time.
I think this is the best partof my job but anyway, I can see
the value proposition and yetI kind of feel like, I mean, is
it just me or does the potentialfor abuse of something like this
(30:24):
maybe overshadow the value interms of productivity and is
that a good thing, that we'renot having real conversations
and trying to outsource them?
These are kind of the questionsthat I'm asking, and this is
kind of what I mean about thehype kind of overshadowing or
causing people to kind of losethat layer of, I wanna say
common sense because, you know,I, I don't know if, I think
(30:48):
it's a good thing that we areable to take a small sample of
someone's voice and replicatethat however we see fit.
Megan O'Rourke (30:56):
Does it need to exist?
Hannah Clark (30:58):
Does it need to exist?
Yeah.
Megan O'Rourke (31:00):
And importantly, it's does it deserve to exist?
Yeah.
Is there a fundamental why andwhat is the trade off there?
Is that robbing us fromthe full conversation
that you and I both love?
Hannah Clark (31:10):
Yeah.
Well, the full conversation.
Megan O'Rourke (31:12):
It does not deserve.
Hannah Clark (31:13):
Exactly.
Well, and we're I feel likeright now we're in a time
and space where, I mean, notto be dramatic, but like the
products that we build noware truly intangibly shaping
the world that we live in.
And it's like the productdecisions that we make now
aren't just about what kindof value we are and aren't
creating for stakeholders.
It's also about what is thevalue and what is the kind
of culture that we're kindof laying the groundwork
(31:35):
for generations to comeand ourselves, even in the
kind of the near future.
You know, we have like muchbigger questions to ask
ourselves now that we'vebeen bestowed with this, like
pretty significant power.
Anyway, this is getting tophilosophical territory but
yeah, I think that this is likethis layer of questioning of
does this deserve to exist?
Is AI and the answer here, orare we maybe taking a route
(31:59):
that is better left in the bin?
Yeah.
Let's talk about storytellingin product design.
So the introduction of AI.
You know, we have obviouslychanged a way that we approach
narrative and storytelling.
I'm curious about how do youkind of use human storytelling
in the process of developinga new, like you, you
(32:20):
mentioned you guys do some zto one kind of development.
What does that looklike in process?
Like, how do you kind ofdistill human storytelling
into that early developmentprocess of a product?
Megan O'Rourke (32:30):
And I think this hearkens back to the earlier
part of this conversation.
So look at usconnecting that thread.
So I think at our core, likestorytelling has always been a
part of our design process wherewe've always been of the mindset
of no decks, you know, a hundredpage decks, like show prototype,
brain experience to life.
And so I think AI hascertainly accelerated
certain parts of our work.
Like it allows us tosynthesize things faster or
(32:52):
spot patterns quicker, right?
Series quicker.
But that element and thatnuance and that discretion.
Like what and how andwhen I think is rooted
in that human empathy.
So at Metalab we havebroad range of clients.
So how we work with thattwo person founder team
looks very different toour partnership with our
(33:14):
enterprise organization.
So for example, with ourtwo person founder team.
Do you think they wannasit through a big deck?
No.
No.
They want us to open up Figmaand just walk through the
prototype and just kind oflightweight narrative and
discuss as we go and unpack.
And sometimes we're riffinglive because that's what
works well for them.
And it's an understandingthrough stakeholder
(33:35):
interviews and just the wayin which their organization.
Run.
You know, it doesn'trequire all that perfectly
curated storytelling.
Whereas other partners ofours, product teams who might
sit within large enterpriseorganizations who might
be bringing along widerstakeholder teams, there's a
lot of care and crafting thatgoes into those presentations
(33:56):
and that storytelling andcreating super defensible
positions and rationalefor every decision made.
And it's that understandingthrough yeah, experience,
but also just intuition andempathy and at that, because
in an agency we have thepleasure of working with so
many different clients inso many different stages.
It's really that tailoringof the process and the
(34:17):
approach that I think isreally sort of human led.
So we'll have a baselineprocess, but we rely on the
project team caring deeplyand asking the critical
thinking questions what isgoing to be best suited for.
This audience for thisstakeholder need and the needs
of what we're hoping to achieve.
So I feel like it's humanempathy is what's driving
(34:39):
the tailoring to like thehow, what and the when.
Hannah Clark (34:42):
Cool.
So to kind of dig deeper onthat, do you have a specific
example that you could shareof this kind of empathetic
approach and how it's kind ofuncovered, like an insight or
a solution like just throughthat kind of workshopping.
Megan O'Rourke (34:55):
For sure.
We've got this one very coolclient called Tally Health.
They're a longevity focusedcompany and they focus
on at home testing, likebiological age testing and
health recommendations.
So got a lot of people whoare super passionate about
health, which is very cool.
And anyway, they had come to uswith, again, a lot of existing
(35:16):
research and they had a prettystrong conviction in knowing
what problems they were solvingand who they were solving for.
So they were like, okay,let's get straight to design.
And our team kept feelinglike there's kind of
this like missing layer.
And so objectively, like we hadall the data, but we were kind
of missing this like behavioral,why I would've context there.
So we got to work withsome early research and
(35:38):
prototyping and startedsimulating what the delivery
of results would look like.
So imagine that you'resending your test, you
get your results back.
This can be like a prettyemotional experience
and sometimes like afairly confronting one
to your biological age.
And yeah, what we learned wasthat people who got younger
than their biological age,they felt really affirmed.
(36:00):
You know, they were like,I've made the right life
choices and health choices.
And then the folks whowere older than their
biological age were likerange of emotions, like fear,
shame, sometimes denial.
And what this differencewas here was like the
mindset, not just the number.
And so like even people whohad received quote unquote,
(36:20):
negative or difficult resultswere motivated to change.
And so anyway, all ofthis to say the data was
there, but the behaviorneeded to be understood.
And it turned out to be like areally impactful insight that
drove a major feature withinthe product, which was creating
these personalized health plan.
So interestingly, that wasn'ton the original roadmap.
(36:43):
Once we saw what was inthe research, it became
a real cornerstone ofexperience and it's actually
like a main retentiondriver within the product.
That was just an exampleof had we just followed the
data, we would've missed thatnuance and it was empathy.
It was that human approach thatreally revealed that insight,
and then our design teamcould bring it into something
(37:03):
really like meaningful andimpactful within the product.
Hannah Clark (37:06):
That's amazing and a very succinct like example.
And I like, I feel like that'ssuch a huge thing to discover
too, because that opens likewhole avenues for a product
portfolio around like next stepsand how the product can mature.
So yeah, what a huge thingto kind of discover through
that like very empatheticempathy led process.
(37:28):
I think that's anamazing example.
I know we've kind of takenup a lot of your time here,
soapboxing and kind of getgoing all over the map.
Megan O'Rourke (37:34):
No we're passionate.
We're passionateabout this subject.
Hannah Clark (37:37):
Yes, exactly.
Yes.
That's great.
I'm glad that's clear.
I do want to kind of come backto the product leadership aspect
because you know, we've gota lot of product leaders who
listen and I know that all ofus are kind of grappling with
this idea of how to maintainthis human touch and kind
of strike this balance ofAI powered productivity and
making sure that we're stillvery much focused on the human
(37:59):
components of our organizations.
So what are three actionablesteps in your view, that you
would recommend implementingin teams starting next week
to product leaders listening?
Megan O'Rourke (38:10):
Yeah.
These are simple ones, theseare things you can try, doesn't
require a lot of buy-in,you can just get on with it.
The first is sharing astory, not just statistics.
You know, we've talked a littlebit about like the importance
of bringing that human voice in,bringing a soundbite, bringing a
quote, bringing a raw clip intoyour next print or team review,
(38:30):
and let that speak for itself.
And it's really important tolet your broader team sit and
feel that problem rather thanjust see cliff swaths of data.
So sharing a story, two,this is again a kind of a
personal one for me, butcreating one moment each week.
To check in or give feedback.
So I practice a little somethingcalled feedback Fridays.
(38:51):
You do it with the cadencethat works for you, but it
doesn't have to be formal,but just like a quick check
in with a team member or asmall note of appreciation for
team members goes a long way.
So AI can help track standupsand whatnot, but it's that
recognition and that outreachlike that comes from you.
So definitelythat's an easy one.
And it feels good.
(39:12):
It feels good, especiallyon a Friday to wrap
up a week like that.
And then third is that empathy.
I'm gonna call itempathy rubric.
So for those critiques,creating, you know, what
are your go-to list ofquestions that you wanna
bring to your product reviews.
Your crits, maybe informingroadmap decisions that
are rooted in thoseuser-focused questions.
So does this meaningfullysolve the user's problem?
(39:33):
Does this deserve to exist?
And how might someonefeel in this moment?
And really driving that lineof questioning that shifts.
Ultimately the conversationfrom, did we build it or
did we build it right to,are we building on the right
thing for the right reason?
So it's really not about notusing AI, it's about using it
with intention and using AIto help create capacity for
(39:56):
the things that I think mattermost, which are really creating
moments of human connection.
Hannah Clark (40:01):
So elegantly said.
Oh, Megan, thank you somuch for joining me today.
This has been such a great chat.
It's been all over the map.
It's cathartic, it's beenempathetic, it's been beautiful.
Where can folks keepthe conversation
going with you online?
Megan O'Rourke (40:14):
Yeah, so definitely encourage folks
to follow metalab.com.
It's our full portfolio, butyou can also follow us on
LinkedIn or Instagram justto keep up to date on new
work and portfolio updates.
And then for me, youcan find me on LinkedIn.
Happy to connect with folks.
Hannah Clark (40:29):
Wonderful.
Well, it's been wonderfulconnecting with you, and thank
you so much for making the time.
Thanks for listening in.
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