Hello, this is Eva and you're listening to the In Between Tech
and Trust podcast. And this week's episode is quite
special because I talked to Chief Transformation Officer
Grisha Pavlotsky from Miro. And Miro is the collaboration
board that probably everyone of you has already used.
And the interesting part is that when Grisha and I met, we dove
into a rabbit hole and it's not what you think.
It's not transformation, collaboration teams and how you
pick the right skills for incorporating AI in
collaboration, even though that was part of our conversation as
well. We talked about how to raise
children in the age of synthesized knowledge and what
it means to provide them with background information, skills,
mindset, and also raising them in a way that they are prepared
for what's to come. So this week's episode covers
quite a lot of perspective use, but also dives deep into the way
that technology shapes trust not only in a professional but also
in the private areas of our lives.
Hi, Grisha, and welcome to the In Between Tech and Trust
podcast. Hi Eva, thank you so much.
This is my first podcast in my life in that girl.
I want to start our conversation about technology systems, but
also from a personal view of what trust means to you on like
a personal level, but then again, also at the intersection
of technology and transformation.
My background is I spent half of my life in various leadership
roles. So the, the concept of trust was
always important for me because I've built teams, I LED teams, I
was a member of the team myself, LED large organizations.
Building trust, building empowered teams, high performing
teams was a big, big part of my life.
So my current formula for trust, if you will, this is again, this
is not a final truth, but my current formula is consist of
two things. Trust consists of intent and
understanding the decision making framework, right?
So I'll, I'll unpack that intent means for me to say that I have
trust in you and I am working with you and I'm we can build
the parallel between human trust between humans and trust between
technology. But I do believe it's, it's
valuable to talk about human trust and how that translates
into technology world. For me to have a, a degree of
trust, I need to understand that we're standing on the same place
as far as our intent and what are we solving for?
Do we are we both aligned on what our final goal and what
good looks like? Right.
We can have a really good alignment about what the final
goal is, but very different definitions of what good looks
like. So that's the intent part.
Are we aligned on the intent? And the second part is around,
am I clear how your brain works? Like what, what's under the
hood? What's the mental model, your
decision making frameworks? How do you challenge yourself?
What's, what methods do you use to get to, to get to the
outcome? So understanding what's under
the hood is the second part. So that's like intent plus
decision making framework. Those two components will decide
whether I personally have a trust with someone.
And the interesting direction that you directly took is that
it's bidirectional and some sort.
But now you and myself, we're collaborating in teams and also
we've collaborated in global systems.
So your formula gets even more complex the more people are
integrated into those, right? Or how would you say it?
I think you're spot on actually, because we were talking about
binary between two humans, right?
And then when you build a team of 5-7 people, I don't know what
the arithmetical formula is, but there is a exponential number of
combinations of, of how you build the choice between teams.
And then even in the technology world now, because each one of
us have access to AI tools, we're proficient.
We go in, we come to team discussions feeling much more
prepared. And a lot of times we even go
outside of our domain area. So we have a point of view or
opinion on things that we're not experts in.
But because we've researched and with the deep thinking and
whatever we wipe coded, we we bring a much more informed and
broader point of view to the meeting.
So it's now the complexity is not just arithmetical.
It's not only like multiplied by five people, but it's also five
people that are to various degree equipped by high level of
confidence. And I say that carefully, like
high level of confidence, that they also bring a high degree of
expertise to the rooms. So that if you unpack that, then
my formula needs to be applied not only to the human to human
iteration, but also if you ever bring some artifact to a team
meeting, I need to know which models did you use?
What prompt did you use? What context did you use?
Do I trust you to work with your AI in the same in a consistently
same high quality way as I am so that we can connect the
artifacts and then continue the discussion at the human level?
100% you're a spot on. And I mean from the current
technological conversations, all of us are supposed to have and
maybe even already have coded their own AI agents and like we
build up AI genetic systems that we collaborate with and so on.
So that is also something that then requires joint design.
So I think the over empathy that we need to look into how we
design such AI and humans systems in order for us to trust
each other when we get into like those conversations gets even
more important. How would you say we can ensure
that that there is like the sort of transparency or at least a
common understanding that what we bring into the conversation
creates this underlying layer of trust?
So if we're talking about designing, let let me play this
back to you and let's see if I'm, I'm hitting your question
right. And they told me if, if I don't.
But when you say the designing the system, it goes back to,
again, shared understanding of what we as a team collectively
are solving for, but also the understanding of guardrails,
right? Because we all need to
understand what's below the line, what's under the line such
that when the agentic system starts working, it executes
within the boundaries of what we as a team deem acceptable.
Otherwise, I mean, the teamwork will still happen, but it will
just significantly slow us down down the road.
So I think when I, when I say as a team, when we need to align on
what we're solving for, we should also align on what's off
limits, what's the guardrails, because we're going to be
dealing with a non deterministic systems and, and the outcomes
are probabilistic. They will be within the sphere
of acceptable, but we will have some outliers and, and we as a
team, we need to understand upfront how we're going to deal
with those. Well, first of all, how to how
to identify those outliers that how do how do we know that this
particular probabilistic outcome falls outside of the spectrum of
what we agreed acceptable, how to identify it and how to deal
with it so. What are you currently solving
for on a professional but also on a personal level?
I'm so on the personal level, I'm raising for kids, trying to
figure out what to prepare them for in the future.
I have a older girl, she's a freshman in college.
We just took her to to university and then two
teenagers and one small ones also have 4 kids.
Questions come up what to study, what to prepare themselves.
So I'm I'm constantly evolving and like think evolving in my
thinking about what's going to be important in the future.
That's occupies big part of my life at the personal level.
Interestingly enough, same questions we're asking
internally as a company. As we're going through another
wave of transformation internally, a big question on
the table is what does the skill set of the future look like?
What kind of people should we hire?
What good looks like when it comes to performance?
Do the teams look the same as a composition of teams and
responsibilities? So apart from bringing a cool
technology to the market, we're also rethinking what the new
ways of working look like. And, and, and a strong talent.
We just hosted a large gathering of 50 CX OS at our office
yesterday and I facilitated 4 round tables and that was what
the new talent model looks like. For the futures consistent
theme, it's top three together with security adoption and the
talent model like those 3 themes come through consistently as top
of mind for CX OS. Let's linger with the aspect of
you being a parent of Ford also in quite like interesting times
of development from their personality level.
And I could see that you also like working at the intersection
of like transformation Tekken teams.
You have an opinion about it also like quite, you know, basis
on how you enter the conversation with your children.
Can you let us know a bit of how you approach it and also what
the current ways of interactions are that you choose to provide
them with? So I like mental models.
It's just, it's, it's easier. I'm a big fan of different
frameworks. It's just structures you're
thinking and at least tells you how you got to the, to the
opinion that you have. So when I think about like what
to prepare my kids for, I'm asking myself, I'm not, I'm by
far not the first parent on this planet and probably not the not,
not the last. So a lot of generations of
parents ask this question. So what is different about me
asking this question today? So that's the first thing, like
what makes it different today from what it was 10 years ago,
50 years ago, etcetera. And it's obvious that what makes
it different that our kids will have infinite access to
knowledge, but not only the knowledge, but also they will
have infinite access to synthesis and synthesis I'm
using with a, with a small word of S because the way the AI
models are coming up with, with the answer, a lot of times if
you're not careful about the question you ask, it comes out
with a definitive answer, the absolute claim for truth.
And an educated or unprepared user can take that as a not just
a data point, but actually as a synthesized conviction of
synthesized point of view, which makes it super dangerous because
then an unprepared user can say if somebody already synthesized
the data and information for me. So now what I'm getting is
basically a ready food. I can consume it, I can eat it.
I don't have to work for it, right?
Like, So what we've been taught to synthesize, convert facts
into point of view. If our kids are going to get be
getting, you know, this processed food, it's like the
synthesized point of view, will it encourage them to stop
thinking and generating these ideas themselves?
So one one thing that I'm preparing my kids for is I'm
saying, I know this going to happen like this.
I know that the puck is skating that way.
I want to teach my kids to recognize when what they've been
fed is actually not the fact that it was actually pre
synthesized point of view. And I'm teaching them to
challenge things and ask provocative questions.
And people call it critical thinking, but but the concept of
saying what I'm looking at, is it the fact or is it point of
view? And if it's a point of view,
whose point of view is it? And that's a big question when
it comes to AI models, we really don't know.
We have no visibility on data set that they were trained.
And I think that's going to change in the future.
I think in the future the model providers will have to will have
to come up with more transparency about what data set
was used to train the model and what group of experts post
trained the model, right. Because model itself is just a
math, then you have a data set and then you have a group of
experts that do reinforced learning, etcetera, etcetera.
In the future, I would want the tech providers to be transparent
about what data set went in and who are these experts, quote UN
quote that trained it such that then I can transparently choose
which model I want to work with or not.
But until then, users and my kids will have to learn to
unpack facts. I was quite impressed.
But so my kids go to International School here in
Amsterdam. A couple of years ago, my
daughter was taking a history class and and I said, can I see
a history book? I really want to see what
they're teaching you, right? Because the history, you know,
it's, it depends who wrote the book.
And she said, we don't have history book.
I'm like, what do you mean? Like, how do you study history
if you don't have a textbook? And she says the way they teach
history in this International School in Netherlands is they on
one day, they tell kids, look, there was 1812, the year 1812,
there's this person Napoleon Bonaparte, and he attacked this
country by name Russia. Go and find out everything you
can about it. And they just, and they just
asked them to go and do the research.
And then they spend a week kids doing their own research.
Nobody tells them how to do the research.
Week later, kids come back to the classroom and one by one
they stand up and they start telling the story that they've
researched. And very quickly, like 15
minutes into it, kids started like looking at each other like
why am I story different from your story and your story?
You know why our the outcomes of research came out quite
different And very quickly this class turns into not learning
the facts or not learning the definition of truth of what
happened, but learning how do we live in a society when we have 5
people and five people have a different versions of what
happened. So the teaching history becomes
less about fact and it's more about how do I live in this very
complex society and and navigate the complexity and different
convictions. That was a big aha moment, big
unlock for me. It's like I need to teach my
kids in the world where access to knowledge and quote UN quote,
post synthesized point of view is easily accessible.
You will have to like society is already highly fragmented.
It's going to be even more fragmented.
I think in the future, it's going to be critical human skill
to live in a society and, and and connect the dots and and try
to reconcile while why different people have different point of
views. So AI can take us up to a
certain point. It's it's a tool, but this this
human skill of navigating the complexity, connecting the dots
and helping people align on on the intent.
It's going to be highly, highly human.
So that's what I'm investing in. And if you turn this into games,
obviously it's, it's much less boring like than what I'm
telling you now. But when we play with kids, but
asking critical questions, double checking, even like even
prompting, you know, you prompt something that it gives you an
outcome and then next prompt is like, now give me quite the
opposite point of view in debate with yourself, like as an as a
user, it's a quite interesting mental exercise where you force
yourself to read to opposing point of views and then work
through the synthesis. And that way AI becomes the
assistant for your thinking rather than a driver.
And you've now shared with us of how you approach it from your
perspective. How do your children perceive
it? Like what do they reflect with
you upon? How do they circle back their
experiences using AI, not only probably in their learning and
like also personality development journey, but for
themselves particularly? I love it.
I mean, the fact that they well, first of all, no, hold on, they
love it. I'm sure they're going to be
listening to this podcast. So they come to Jesus moment
more often than not, the response is, oh, no, again,
we're going into this lessons learned, blah, blah, blah type
stuff from dad so that that that's there and I'm trying to
navigate how do I not become a boring dad that like tries to
get the piece of wisdom out of every conversation.
But the fact that they do have cell phones and I know there's
like the parents split on these opinions and whether you should
or should not give device to your kids.
All of my 4 kids other than 8 year old, so 8 year old doesn't,
but all other kids cut the devices at the age of 10 or so.
And the idea is like I want them to have, I want them to be able
to Fact Check and to confirm and go in and have their own develop
their own patterns of finding answers and not always rely on
what dad says or what mom says, etcetera.
And it's very interesting. So my 13 year old son, three
years ago, when he was 10, he said that I want to to code.
I'm like, yes, awesome, great. I'm going to hire you a great
teacher. You're going to be a great
coder. He's like, no, no, no, I don't
need a teacher. And I'm like, what do you mean?
He's like dad, there's YouTube, right?
Like so in like in two days, he learned to he learned to how to
write games in Python from YouTube, which was pretty cool.
And then he goes from like one game to another.
He starts iterating. And then I said, you're really
good at this, let me hire somebody who can make you even
better. He's like, look, and this is
this was another aha moment for me.
And I think, I don't know if it's my kids.
So it's a generational thing. But my son said, if you hire me
somebody, I will learn to think how that person thinks.
If I go to YouTube, I listen to 15 bloggers, I read 15 different
things. I pick and choose what I like
and I compose my own learning path.
So I get to the outcome in my own way, in my own mental modes
rather than learning how other people think.
So for me, I mean, that's giving kids, giving kids curiosity.
This, it's a fundamental thing that's they're, they're curious
and then given them access to, to the tools.
It's super cool. It's just it's a super cool to
see how they come up with their own ways of learning, Which then
brings us to a separate topic, whether our educational system
is equipped to support that, that level of open endedness.
That is actually the connect that I wanted to draw to our
jobs or like the professional environment.
Because for me, there's the statement, we don't hire juniors
anymore because like we also need some more senior ones that
can now delegate or orchestrate or whatever.
And I have the hypothesis and maybe it's, it's going to prove
me wrong, but I do think it's not the right approach because
what you just described with your children having curiosity,
being able to solve things differently is a real addition
to, to teams. And it's also adding to like
heterogeneous collaboration. So I'm actually also looking
into the way of how these additional skill sets can be
built up into collaboration. However, our juniors coming
directly from universities, they are are sometimes differently
approached and trained of how they're thinking.
Also their ways of performance has been elaborated.
So bridging that from the university, like ending
university and entering the kind of like new ways of working is
something that requires also some sort of different kind of
leadership. So that is quite now the broad
aspects to it. But I did want to look into it
with you from a university like systems perspective, what would
be required different then also enabling like juniors in order
to be more curious and challenge existing processes And then from
a leadership perspective of what is required from leaders to have
this oversight into teams to bring those capabilities
together? Yeah, that's, that's a billion
dollar question. So let's let's take it in 1-2
steps. So #1 if you go back to the
technology again, the role of technology of AI and I, I live
in the world where I, I want human to always be in the loop,
like I always, I want the human to be responsible for the
decisions. I, I see AI an agent as
assistants, as an accelerators of the how, but it's always the
human that decides what we do and why we do.
And at the end of the day, there's got to be a human who
takes responsibility or accountability for the decision,
right? If, if AI helps a medical
profession to write a, a, a diagnosis, that's fine, but
there's got to be a human who takes responsibility for the
final yes or no. If the agentic system reviews
the mortgage application, there's got to be still a human
who says yes, yes or no. So there's got to be a human
person that not only takes responsibility, but also designs
the system so the system achieves the desired outcome.
That's so that's number one. Now, if I if I need a human who
designs the system, we'll go back to my definition of trust.
The first one is intent is like, what am I solving for?
What good looks like? What is the biggest?
What is the final outcome I'm building the system for?
And that is the skill that universities need to teach.
Historically, universities that I've I've been to and to the
best of my knowledge, the domain expertise that as we prepare our
kids are too narrow like we've we're building or educational
system teaches kids to be subject matter experts in small
boxes. So they can fit a job in a team,
in a function in a large organization.
And that says the whole model was designed in 20th century,
right? In the future world, knowledge
workers will be orchestrators of of the system.
So the knowledge worker will need to say, I have all these
tools, models, agentic platforms and orchestration layers.
I can orchestrate the work, but I need to know what I'm building
for in that way. The level of expertise needs to
be much broader. So I expect the universities to
respond to this and say we're not like the faculties or
schools or or departments or how do they call them colleges and
universities. They will have to broaden up the
breadth of knowledge and skills that they're teaching.
So it doesn't make sense such that people will be able to in a
much smaller teams to design the holistic end to end systems,
rather than you would have to like put 15 different very
narrow, very deep subject matter experts to say, now you're
collectively designing a system which is super complex to do.
We just started this conversation from from the
beginning. So, so education system I
believe need to change very rapidly and expand the the T
shape like the vertical T of of the of students that they're
graduating and producing. It's trading on that.
I want to share a hypothesis with you and I would love your
perspective on it in terms of collaboration models of the
future or let's call them operating models.
But I do think that future teams are are smaller than the ones
that we have currently and they will be cross functional.
So in a lot of organizations we have full sets shaped or
allocated towards projects outcomes.
And I do think that we need some sort of speedboat teams that are
able to drive into the direction of the larger perspectives and
also like the overarching value chain of an operating model such
as as an organization, how do using that?
Legacy companies, large companies in my point of view,
will struggle with us a lot and we will see companies.
Let me make a statement and then I'll rationalize.
I'll explain why I believe so. Legacy companies will be super
slow to respond to that trend, and there will be younger, more
nimble companies that don't have legacy org structures, legacy
egos, legacy processes, and ways of working that they have to
comply with. Sorry, but in general you would
agree with the 100? Percent agree that's the
decision. But you, you said something
interesting in your, in your statement, you said cross
functional. I, I believe that the definition
of functions will change in the future.
I would even like, I wouldn't call it cross functional.
I would call it outcome based, right, because the way the
functions are built like so I build the product, marketing,
distributed sell, sell sales, sales at finance collects the
cash. This is how we designed the
assembly process in 20th century and that's how we designed
function. And now marketing is like 15
different marketing and sales, different stages of sales in the
future. You're not going to say how do I
put cross functional team? What you're going to say, how do
I get to this outcome with the least amount of people involved
in the least amount of handovers And I don't even care what
function they sit in. I just need to work backwards
from the outcome. But today the outcome is defined
by my job description. My job description is this.
This is my outcome. This is what I do.
I'm the best designer. I do the best pixel perfect
designs. Then I hand it over to somebody
else. I am the best UX researcher.
I produce the best UX research, etcetera, etcetera.
That's how we define outcomes. In the future, what you're
saying, the speedboats will, will crush the walls between
this job descriptions and I'll say, who cares about this
intermediate outcomes. What we care about is the
product is in the market, the users love it and we're
collecting cash. So let's work from that outcome
and work backwards into what it will take to to achieve this in
the future. So 100% agree that this is where
the puck is skating. And large organizations should
be asking the question. If they're not already asking
the question, they're already too late.
And then the punchline is why this going to be so difficult is
because people have egos. People have, if I am an expert,
I went to school, I paid $300,000 for my college.
I have a diploma in this space. I worked there for 15 years.
I told my family that I'm the best at XYZ.
My kids know me as the best at XYZ.
I write blogs about this. I'm on the stage, I'm speaking,
I'm the best person in XYZ and now you're my boss and you're
telling me saying gusha, you know what, this XYZ not relevant
anymore. Actually you need to shift to
the right. This is a a huge alter ego
traces for individuals like a lot of people like
subconsciously respond to that very defensively say no, no, no,
there's like myself worth myself value is attached to being the
best artist in this XYZ thing, and now you're telling me that
XYZ is not the thing. Now you have to shift to the
right. So and now you multiply that by
you know, 10,000 people in the average fortune, whatever 500
company. It's super.
It's the change transformation is human and humans.
And I understand that by the way, like I'm not very, I'm not
judge mental about this at all. Like I, I think this will be a
big self identity crisis for a lot of knowledge workers, like
redefining what are they attaching their self value to?
And but the good ones will step out, the good ones will embrace
the good ones will see it as a huge growth opportunity and will
move fast. So I hope large organizations
recognize this and, and, and start thinking about first of
all, inflow of new talent. Like my advice would be one, one
thing is within your control, control the inflow of unit tone.
So the new, the hiring policies, they need to be rethought
considerably. And then internally there are a
bunch of techniques how you can, you know, create like sandbox
environment and like, you know, put people behind the Chinese,
Chinese walls, allow them to move fast, break things.
But we, I think we, it's going to, it's going to take a while.
It's going to take a while for, for organizations to change.
And by a while, I mean like years, it's 5-7 years.
We'll see. And coming back to the very
beginning of our conversation and your formula for trust now
knowing that we have, let's call them cross talent on teams and
that there is also some sort of ego identity attached to the way
of how they will be shaped in future, the trust aspect becomes
probably more more relevant, or at least that's what I'm
exploring also. But I'm hosting the podcast.
But at the same time, we face this tax celebration and
shifting identities in times of speed, velocity and so on, and
also needing to constantly upskill our capabilities.
Isn't that overwhelming? And if so, how would we handle
that as persons but also then as an organization?
100% it is overwhelming. There will be a little bit a lot
of anxiety on the market. That's why I'm saying it's going
to take years because you can't hit the button reset on a 10,000
people organization, 100,000 it will take.
I don't have a golden recipe how to do this and gradually.
But what is clear that organizations need to think
about it and they need to have a strategy how to deal with this.
There's probably not the right answer, but they need to
recognize the depth of the problem and the complexity of
the problem and have a very gradual, you know, step by step,
face by face strategy, how we get from point A to point B.
What may throw a curveball into all of this is a competitive
environment, right? Because if I am incumbent and I
have my strategy and it implies that I'm moving gradually from
point A to point B / 5 years. And then there is a fast moving
speedboat comes from the left to the small AI native startup.
That disruption can 'cause leaders to rethink how fast they
need, they need to change. But it's also, it's also top
down on border bop like from, from leaders.
We can talk about it. We can say we have a strategy,
we have a plan. But it also a lot of owners also
sits with employees like the knowledge workers.
They're saying, like it's me, like if I want to stay
competitive for next 25 years, I have to do this.
I can't just take a passenger seat and, and rely on leaders to
come up with a plan. And I, I think your, your life
is in your hands and this is, you know, wealth of your kids,
they're on it. So I think a lot of knowledge
workers will have to realize how serious you said upscaling,
probably rescaling. That notion will be so big
opportunity for educational system to step in plenty of
resources. Now I'm thinking about whether
it's resources or it's mindset. That's an interesting question.
Maybe it's for a next podcast. It's like if I'm 37, I'm not 37,
but let's say I'm 37 and I'm offered this program for
rescaling, but I don't have a mindset for it.
Is mindset something that can be acquired in the middle of your
life? If I don't have a mindset for
that, I'm have a different path. There are so much routes that we
could now take because I would also be curious to hear who's
responsible for, you know, providing the opportunity to
rethink mindset as AD individual or the organization.
But I do want to briefly pick up on the curveballs because you
said like you threw in the incumbent ones.
Do you see any other curveballs that could be thrown into like
the way of as individuals but then also to organizations with
or without heritage? I mean the most imminent one I
think that's coming is I don't know if it's a curveball or not,
but I think everybody's talking about AI bubble overhyped
expectations, what it can, what it can do, whereas technology's
over mystified what's not. I think the next next several
years as knowledge workers and their leaders will drive their
own and team level adoption with AI that the level of proficiency
and familiarity with technology will increase and
correspondingly the level of mystification will will
decrease. So I think, I think what we will
see is a lot more like consistent understanding of what
AI cannot, cannot do for your business.
Like direction of travel is clear, like with with the models
and they're going to get better and bigger.
We're going to get more multi modality.
We're going to get the physical world, the general population,
knowledge workers will learn general principles.
Because right now I still don't believe people understand how a
A works the basic level. I mean, people know how to use
JDBT, but they don't know what's under the hood and how it works.
And therefore people sort of like tend to overestimate the
capability that is like I think was Bill Gates, right?
So like in short term, we overestimate and long term, we
underestimate the implications of technology.
So I would encourage everybody to invest their time to really
get, you know, hands dirty, sign up to tools, build your own
agentic flows, automations, help yourself increase your own
productivity. Like if you're using Chen GBT
right now, that's table stakes. That's not AI familiarity.
You need to start when I hire people, by the way, in my team,
I don't ask them whether you're familiar with AII asked them to
show me the latest genetic flow that they've built.
Like literally just on the call screen share, show me what
you've built. And it doesn't have to be work
related. It can be personally related.
And if if a person can't show, then that's the end of interview
because that's, that shows the mindset like where people are
theoretically curious, but not like really.
What's the last thing that you built?
I'm building a smart agentic system that it helps me to
manage the key professional relationships that I have.
So I don't want to call it CRM because CRM sounds like a
database. This is the proactive agentic
system that understands my business objectives, what I'm
trying to do. It understands where I am in
different relationships and it's it helps me to actively,
proactively manage the content, manage the touch points, manage
the relationships, etcetera. That's that's quite fun.
Also something that can be iterative and without ending
right, So it's probably. Exactly, Yeah.
And the first, first version will be super simple.
It's like Air Table plus Zapier plus your Gmail.
I mean, that's all you need. And then and then you start
building like connections to your sales force and gun calls
and your, you know, your calendar and things like that.
You can always at some point in time, you're probably will end
up buying a professional platform that is the same thing.
But just the fact that you can build these things in a no cold
way as a as a non-technical person is pretty cool.
And once knowledge workers who are not technical, once they
start putting their hands on these technologies, once they
start building, what the interesting thing will will
happen, They'll start being their curiosity will lead them
to ask questions. Why am I doing the way I'm doing
this? Is there a better way?
And you will start rethinking the way your work happens.
So you're not just going to be automating the steps as is, but
you'll be collapsing steps, you'll be skipping steps, you'll
be rethinking and and you'll become the orchestrator of your
own work. That is a really, really cool
sort of a byproduct of actually building something with your own
hands. On an organizational level,
who's the master responsible orchestrator and to orchestrate
or have the other persons collaborate on also like a
technological or knowledge sharing perspective if that is
something that's also, you know, continuously evolving.
The orchestrators might be different, but I, but I am, I am
convinced the tone from the top comes from the CEO.
Like the CEO has to come in and say, this is not optional, this
is mandatory. We're going there.
It's not like we're going to, I mean, OK, two months, we're
going to play around, we're going to give you tools, you
guys experiment, increase your own productivity.
But the tone from the top should be very, very mandated, I
believe and say, look, this is my organization, I'm responsible
for all of you and for the business model, I'm responsible
the shareholders to the board, etcetera.
I'm declaring this is not this is not optional.
This is mentor. We're moving with that speed and
everybody needs to hear that message from the top that it's
there's a sense of urgency and there's a sense of direction and
we're moving there. Now how it's been orchestrated
at the at the functional level. So there's different ways it's
top down, bottom up. Like we at Bureau, we do it
combination, we do a bottom up, we give a bunch of tools, people
experiment at the individual level, at the team level.
But we we did identify a series of use cases that are overflows
that are critical to the business end to end and those
are owned by senior leaders in the organization.
Again, they might come from the function, but as a owner of the
workflow end to end, they own the whole end to end.
So that that model can can differ company by company.
But I do believe that without clearly declared a mandate that
we're moving and we're moving with that urgency and beyond
that point is going to be non acceptable if you cannot work in
that way, like you cannot work for my company if you don't
behave like this after that day. Since we now come to the end of
our current episode, I do want to share some moments with you,
the so-called in between moments.
I have them with all my guests, so I also want to have them
together with you. And I want to start with one
question. What does trust feel to you
like? But trust feels.
I'll quote Satya Nadella on this one.
I really admire him as a leader. For him, trust is consistency
over time. And what does AI need more of?
AI needs more new ones and more contacts.
What is parenting in the age of AI to you?
Teaching kids to connect the dots and and synthesize opposing
point of views. And finally, what will the next
generation redefine? The next generation will
redefine how the work is done. Thank you for stepping into
those moments with me. And now thank you so much for
joining us, joining me on In Between Tech and Trust podcast
and also for sharing all your insights.
I loved it, but it was great. Thank you so much.
Appreciate it.