From Wall Street to Wisdom: Experience as the Blueprint for AI Innovation

Episode Transcript
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Tonya J. Long (00:00):
I'm Tonya Long and I am here live in Los Gatos
with my friend, Joyce Li.
I am so excited about havingeveryone today join us to hear
about more adventures in AI.
You guys know this is not atech podcast.
That is not my intention at allbut a lot of my friends are in
tech or related to tech and theyhave remarkable stories, and so

(00:24):
this podcast is about stories.
Stories, in particular, aboutthe resets that we are all
moving through as we'retransitioning in this remarkable
period in time, with so muchchanging in technology and work
and longevity, and then, ofcourse, in purpose, and purpose

(00:44):
is a big part of this, and myfriend Joyce Li has a ton to
share with us about evolvingtoward purpose.
I can't wait for you to meetJoyce.
She brings a fascinatingperspective.
She's been a software engineer.
She's been managing investmentsworth billions in her mutual
funds and hedge funds that shewas responsible for, and now

(01:05):
she's been to me one of theleading AI writers on the
real-time space, as she hasdeveloped quite a following and
has one of the most useful, ifnot the most useful, newsletter
that I subscribe to.
So I'm just excited for youguys to all meet and to be
inspired by what Joyce offers,because that's what Joyce offers

(01:28):
to me.
So, Joyce Li, welcome to RESET.

Joyce Li (01:31):
Thank you so much for having me and right back at you.
I'm inspired by you every dayand couldn't wait to share what
my journey has been.

You have had a lot of turns similar to me.
We'll talk more about that intime, but let's start with today
.
What are you working on nowthat is exciting to you in your
current work and life?
What's big for you right now?

Joyce Li (01:54):
Right At work.
Right now I work in theintersection of AI and finance
and governance finance andgovernance and I talked to a lot
of board directors, financeleaders on how they can use AI
to accelerate their strategy but, at the same time, ensure the
right governance in place.
I'm very excited about thatbecause it's almost like every

(02:18):
day.
I get to be a learner, but alsoa teacher and also a
collaborator, so that bridgingaspect is where I enjoy the most
, and I also hope that's mysuperpower.

I love that you understand and recognize your
superpower.
You have been in differentplaces.
You know you've had a 20-yearcareer plus, like I have, and we
have gotten to have theseexperiences that all add up.
To me.
It's the gestalt.
The whole is so much greaterthan the sum of its parts.
So at one point you were asoftware engineer, at one point

(02:53):
responsible for hedge funds,phil.
How have the values remainedconstant across those lines to
point you, as your North Star,to where you're headed?

Joyce Li (03:06):
lines to point you, as your North Star, to where
you're headed.
I feel more and more in lifeI'm sort of carving out what's
important to me, that clarity ofideally working in the
intersection of what I'm good atand what I love to do, and the
most important part is it'sgoing to be useful for the world

(03:27):
.
So that is the North Star, andthat North Star or that
usefulness could change overtime.
Maybe when I was young and justentering the workforce, writing
codes is the most meaningfulcontribution, but now I feel
like in this, I would say,generational defining moment of

(03:49):
AI transformation in governanceand finance, my bridging ability
is where I can add the mostvalue to the world I love it
when I think about how I see youshow up, which is, frankly,
mostly, mostly work.

We're friends, but we see each other in our
work environment.
I see you as a problem solverwith a broad worldview.
Where do you think you got thatfrom?
Do you think you pulled thatfrom your professional
experience?

Joyce Li (04:22):
I actually think this is a question I didn't prepare
for, but this is the answer Ialways have.
I almost feel like I grew upwhen I was a child thinking I
would be an engineer.

Okay so that was your path.

Joyce Li (04:35):
Yes, my dad was an engineer and obviously he he
also come to look at every newthings in history as a problem
to solve with the tools he hasin hand.
So in his 40s he self-taughtcomputer programming and I saw

(04:57):
my dad do that, and then Ialmost have this mindset of
everything in life there is aproblem waiting to be solved
with your current tools, andthat tools can change.
Of course, 20, 30 years agothere was no AI, but now there's
AI.
So I always approach thatworldview and this may be what

(05:17):
you think about as problemsolver.
I'm really glad my dad will beglad to hear that I'm viewed as
a problem solver.
I'm going to tell him.

He's so strong for me, that reaction of seeing
you as a problem solver, thatcan't be a surprise to you.

Joyce Li (05:35):
That's really interesting, and one of the
nature of problem solving todayis that the solution may not be
clear.
It's a very iterative process.
So, for example, some of oursolutions initially maybe in

(05:57):
2022 with AI is not that good,and now we just keep at it
solving the same problems andthen eventually we get better
and better at the solution, andthat's also one of the key
points I keep telling theleaders that now more than ever,
make sure you fall in love withthe problem, not the solution.

Yeah, yeah, I would even add because I know I
just intuitively, I know thatyou experience this as well.
So many times when I go in andwork with clients, they don't
know what the problem is they'retrying to solve.
They, you know, they want to X,they want to save money, they

(06:44):
want to position something, butthey're not really clear on
their why.
And so for me, that's where Ithink people like you and I,
with rich history not just onethreaded, but multiple things
that we've done what we're ableto do is to help them sort
through the possibilities wewouldn't have tried to do 10

(07:07):
years ago because it would justhave been impractical with the
capacity and the compute powerand all those things.
But now companies can use datato get insights and do things
that they've never done before,but they don't know where to
start.
Do you have the same reflectionon companies' understanding?

Joyce Li (07:23):
Yeah, I completely agree.
And then you are such a greatperson to ask intelligent
questions and just probing,probing, probing, and until you
come to the bottom of it andunderstand the key motivations
and also drivers of something,and I do the same.

(07:46):
So one of the things I amgrateful of my investment career
was that it cultivate thisquestion asking ability and also
sort of tallying the signalfrom the noise, ability to
really focus on what trulymatters.
So one of the things that I helpmy conversations or my friends

(08:11):
to do is to always think aboutwhat is that key driver or key
element that makes your businesstick, and just keep asking and
whether that mode we always saycompetitive advantage of a
business continue to be in placein today's world.

(08:34):
It may not be, but if that'sthe case, what really make your
business and your workforceshine in this new time?
And you just keep asking,asking until that alignment
builds, the alignment betweenyou know your business goals,

(08:54):
visions and you're going back toa problem what problem to solve
?
And that problem, that keyproblem you need to solve in
order to for your businesspurpose to shine, and then put
that key problem you need tosolve in order to for your
business purpose to shine andthen put on constraints that you
have and that's your problemthat you need to focus on.
So I think, like you, justasking questions is a very

(09:16):
important talent and that buildsover time.

And I'm not splitting hairs when I say this,
but it's more than talent, it'sunderstanding nuance, reading
the room, um, because I can askquestions in some rooms that are
very unwelcome in other roomsbecause of the company's culture
.
The um, the um, how rigid theyare in terms of how willing, how

(09:45):
far are they willing to bendcertainty.
You know, how do they managerisk.
So I think it's not just goodquestions, it's also making
people comfortable to explorewhat's new.
Do you?

Joyce Li (10:01):
agree Absolutely.
I think, ultimately it's not atechnology problem, it's a
culture of people problems.
I love it.
It is yes.
So that's why, you know, havingthose conversations at the sea
level, at the board level, aresuper important, because this is
not just something that you cancompletely execute from

(10:25):
bottom-up, grassroot effort.
It has to be coming from thetop.
In fact, the top-levelleadership have to fully buy
into the vision and otherwise itwouldn't be solved by any
technology Right.

I think I have a lot of empathy for what the
people that we serve.
I have a lot of empathy becausethey are experts in their
domain.
They've been luminaries in theseindustries for as long as we've
been working Right with AI.

(11:06):
It's very hard.
It's very hard for the ego,it's very hard for the people
who need to know what's going tohappen.
You know, traditional product,I'm going to make a better blue
pen, you like to, and if I makethe blue pen, I can put numbers
around how much I'll sell.
You know it's finite.
So products, because I've beenin tech for so long but my
products were always finite withestimations of how we'd be able
to break into the market andserve better, do more and make

(11:28):
more money for our shareholders.
But there's a lot of uncertaintywith that.
With AI, the commitments aremuch.
They're much less prescriptivein how we arrive at giving
people comfort, and especiallyboard members in C-suites need
comfort.
I know you've experienced this,like with the hedge funds that

(11:51):
you operated.
You were responsible forbillions of dollars, so you
learned to deal with uncertaintyright.
So how have you translated thatexperience into helping these
boards with this big, massivething with two little letters
A-I, to help them get over itwith this comfort?

Joyce Li (12:12):
I completely agree with the point that a lot of the
board leaders and alsoexecutive leaders, for the first
time in their professionalcareer perhaps feel less
confident about what questionsto ask, whether the answers
given are good enough answersbecause they haven't got the

(12:33):
time to build up that.
You know knowledge base andtechnology, and it's just so
fast, it's just too fast.
I know both you and I arelooking at this every day, but
we still from time to time feeloverwhelmed and behind.
For example, this week there'sjust so much happening in the AI
world.

(12:53):
Even today we don't know whatOpenAI is going to say.
But I think the key is to reallylook through the surface of
what's the symptom and then lookdown into frameworks.

(13:14):
I do think that frameworks thatpeople develop over time in
managing their businessnavigating uncertainty are still
solidly in place.
Navigating uncertainty arestill solidly in place.
I will give you an example.
One of the interesting thing orphenomenon that really feels
very new to board directors isthe pace of solutions that can

(13:40):
change over, like between boardmeetings.
Typical board meetings for theaudience who are less familiar
is quarterly yes, and they comein and approve 90 days is
forever Correct.

Current AI cycle of development.

Joyce Li (13:56):
Correct, correct.
So when they come in and approvesome sort of AI roadmap and
then next time they come in, allof a sudden they realize the
last time the solution nowbecomes there's maybe a better
way to do it or maybe there's apartnership instead of buying a
solution.
They're not used to this quickchange of solution or the

(14:20):
roadmap cadence, but if you takea step back and really think
about what questions we need tofocus on are basically the same
One is it still aligned with thebusiness objective over the
long run to create value forthis company's shareholders
stakeholders?
Second, are we having the righttalent in place and are the

(14:45):
culture and operationalstructure in place to support
that?
And third, do we have riskmanagement metrics in place to
make sure that things are goingin the way they are supposed to
go?
They may not go exactly the waythey plan to, but in terms of

(15:05):
direction, in terms of theoutcome, the sort of roadmarks
are staying on track.
Those are the same questions,ai or not.
So once the leaders get enoughfluency, feel confident enough
to ask the same frameworkquestions, they will be able to

(15:29):
navigate this time much, muchmore comfortably.

I'm just letting that sink in because you're 100%
right and it's so hard tobalance the hype cycle with I
said with very intentionally thehype cycle managing that with
long-term thinking, which iswhat boards are supposed to be
based on yeah, and I think youcan have your cake and eat it

(15:57):
too.
Absolutely.
I think we can't ignore what'shappening now, because there's
so much learning with the thingsthat are happening Learning
sometimes in the failures.
Now, all times, you learn fromthe failures, but I think you
can keep a long-term visionabout what your company's trying

(16:18):
to do.
Ai is just the how.
It's just the tools and themodeling that helps you get to
the long-term vision, and youdon't have to sacrifice one for
the other.
In fact, I think you have tohave both to be successful.

Joyce Li (16:33):
Absolutely, and make sure that people's incentives
are aligned to the strategicgoals, not just some sort of
flashy demo goals.

Mm-hmm.
Speaking of flashy andincentives aligned, I have to do
a quick.
I want to do a quick stationbreak for the Signal Society.
The KPCR Signal Society wantsto thank Spinga Los Gatos for
sponsoring the Signal Society.
Spinga is a local LosGatos-based fitness center and

(17:05):
they're one of our sponsors, andmembers of the Signal Society
receive $100 off an unlimitedfitness membership.
So you can sign up for theSignal Society at kpcrorg slash,
join or go see our friends atSpinga here in Los Gatos and get
your groove on and be flashythat's the word you had just
used, Joyce, so flashy AI.

(17:30):
We've talked all about AI thefirst 15 minutes and that's fine
.
When I think about you, you'reone of the first people that I
remember.
That was like me.
So many people on this AI trainare deep technologists.
You and I are deep businesspeople broad and deep business

(17:51):
people.
So we both had 20-year careersin our respective different
verticals, if you will, then weboth started this AI thought
leadership that we do, andalmost the same time we found
each other.
We started collaborating.
We saw each other at all thesame events.

(18:12):
Sometimes I was on the panel,sometimes you were on the panel.
That's how we got to know eachother.
What was happening in yourworld?
I can tell you about mine, butwhat was happening in your world
that brought you into the AIheight curve at the time?
And we've not gone off thatcurve since we started, but what
brought you from the investmentworld into leaning hard on what

(18:38):
you could do and help otherswith?

Joyce Li (18:41):
regarding AI, Well, I guess the timing turned out to
be really interesting because,in 22, I spent a long time of
that year doing soul searching,going back to our North Star.
How do we find thatintersection of what we love and

(19:05):
then the meaning of life, butalso what we are good at?
And I have to thank my coach,tisa richards, and she really
helped me to build this clarityof what's important, what's
non-negotiable for me.
So, interestingly, among allthe lists, on all of, about all
the items on that non-negotiablelist, there's nothing saying I

(19:28):
have to do investment,continuing to do investment over
the next, you know, 20 years.

The way you had evolved Correct.
You were no longer really inalignment.
You didn't need the investmentpiece to be part of your work
life.

Joyce Li (19:44):
Correct.
I love it.
So then it completely opens upmy mind and then I just went
into events see what's going onand the timing of it.
That's where it getsinteresting.
I went into this social eventand really met this wonderful
woman who introduced herself asworking for a little startup

(20:06):
called OpenAI.
Oh, that little thing I know Atthat time really it was little,
but I got interested and I justwant to support all these women
I met and just to try to usethe product they were doing.
And I was thrown awaycompletely and the timing was
great.
I'm looking for something new.

(20:26):
I do see immediately thepotential of rethinking
everything in how we do finance.
So one of the things that I'vebeen thinking about is how,
ultimately, ai can lower thatpersonalization or finance

(20:50):
advice to almost zero over time.
So I just want to go into thatrabbit hole and then reunite
with one of my college friendsin the computer science area and
just have this startup.
And that's how everything gotstarted.
And of course, startup didn'twork out.

(21:11):
We can talk about that, butit's very typical of Silicon
Valley story.
But it opens doors forinteresting communities, like
Athena Alliance, where I writeabout.
You know what this means forboard governance, because those

(21:31):
are two areas I feel passionateabout.
Not many people were payingattention and one thing led to
another.
We have a group of reallyinteresting women executives in
that space.
Come together and write thisgovernance playbook that help us
to develop this holisticframework to think about

(21:52):
governance in the age of AI.
But that's an example ofcuriosity plus positive energy,
plus finding a tribe, plushaving that clarity really
helped me on this journey andthat led me into getting to know
you.

The work that you did with Athena on the
governance playbook wasincredible.
The thing I reflect as anauthor and as someone who works
inside of a lot of teams I liketo work alone.
I'm the only decision maker andI love people, yeah, but but I

(22:31):
remember looking at the tribe ofwomen powerhouses that created
that governance playbook and Ithought, oh my God, because
you've got 15 type a strong,opinionated yes and the fact
that you could produce anythingI I recognized what, what, what

(22:52):
labor you had to go through tocollaborate right on style, tone
, prioritization of content allthose things and you produced a
beautiful product.
For me, the most remarkablething about the product was
looking at who put it togetherand how they all had to learn to
give and take in order for afinal product to be produced.

Joyce Li (23:14):
It's interesting.
When we started to think aboutthis project, it was completely
sort of almost like this iswe're creating something to give
to the world, so there's reallyno string attached and there's
really also no PR plans oranything put in place.

(23:35):
We just thought we all have thisurge to let people know.
This is something you have topay attention to.
But we also got a little bittriggered by at that time you
probably remember a lot ofarticles and newspaper headlines
talking about all the thoughtleaders or all the AI frameworks

(23:58):
are fully developed by men.
We thought we just have thisadditional layer of incentive to
spotlight some of the amazingtalents from product, from
technology, from law, from, youknow, regulatory considerations

(24:22):
All sorts of interesting walksof life, and that's also a
learning process for us.
To your point, like, how do wefit that into our busy schedules
and work together almost forsomething bigger than ourselves?
And fortunately, I do think wehad the right people in place,

(24:42):
and Athena is a great sort offiltering machine to get these
people in place, have thisamazing product coming out of it
.

I love it.
I love it.
You know a lot of people worryabout AI and humanity and the
impacts on humanity, but Ihonestly believe and I started
out feeling this way and I metevery iteration it's stronger
and stronger that AI is aplatform to save us, to save

(25:12):
humanity, to connect us, to giveus opportunities and vehicles
for collaboration that we didn'thave before we were, I think we
were driving ourselves into theoblivion of mundane tasks, and
now I think we can all.

(25:33):
I don't care if you, I don'tcare if you, you know work in a
daycare or an ice cream shop orif you're at the top of the top
AI companies.
I think everyone is going tohave an opportunity to reinvent
themselves with the new thingsthat we will be able to do,
understand and the content wewill be able to work with as a

(25:55):
society so that we can, you know, do things like you and the 20
women that collaborated on thatplaybook, absolutely, yeah.
Speaking of reinvention, wewere talking before the show
started and I said, oh, justgive me a gift.
And I was using improv termsand I said, oh, have you ever

(26:22):
looked at improv?
And you've done more than lookat it.
You're a fan of improv and forthose that are not following
this track, a gift is when yougive someone a statement,
knowing that it's a hook thatthey can attach to in
conversation, because the wholepoint of improv is to help keep

(26:45):
the dialogue going, to help eachother, not to find funny,
snarky things that shut down theother person, but to find funny
, uplifting things that theother person can say, and me too
.
So I think that the improv.

(27:11):
We have a studio announcementabout Wi-Fi.
I apologize for my presentation, so so we're good, um, but um,
I was thrilled that you had hadan improv journey, because that
gives us something else that wehave a connection with, but I
also think it's part of who weare.
Once you've studied improv, itbecomes part of how you interact

(27:38):
with people, because you wantto give people something to
continue the conversation.
Tell me what your experiencehas been with using that journey
to improve what you do.

Joyce Li (27:53):
I love improv.
Improv is.
I love that you started.
Yes, improv is something so yes,so hard, and growing up in a
traditional Chinese family,that's the last thing.
But you sort of come into everyconversation, you sort of learn
the ropes beforehand, getprepared to 100% Perfection,

(28:16):
exactly.
And improv is like theprofession is not to be prepared
ahead of time.
And of course you know a littlebit like frameworks, know a
little bit about you knowteamwork.
But it's more about trustingyour collaborators.
It's about be present, fullypresent, and just deal with what

(28:37):
you're dealt with right.
So one of the when I was aninvestor, I went to visit
companies all the time.
I go to conferences all thetime.
If it happens to be in a city,mid-size or large city on a
Thursday night or Friday night,I would look crazy for an improv

(28:58):
show and then just go and thensit in the audience and just
enjoy it.
And over time I realized why Ilove it so much, because I just
I feel like it satisfies twothings.
One is be very, very curiousand be very, very open-minded
during that curiosity surge.

(29:19):
But second thing is really havethat trust that things will work
out.
You'll find a solution.
But how do we get there?
You'll find a solution, but howdo we get there?

(29:41):
You have to be collaboratingwith your teammates or with your
whoever is on that.
Most of us are on this AIjourney or about to embark on
this AI journey.
Trust that you will get it.
It will fulfill your life andalso be trusting your own
ability to find a solutionthat's the most suitable for you

(30:06):
, for your domain knowledge toshine.
I love it.

I'm going to come back to it after this quick
bottom-of-the-hour announcementNot an announcement a station
identifier.
You're listening to Pirate CatRadio and Pirate Cat Radio keeps
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For those who follow us, listento this.
We are at KPCRLP 92.9 FM herein beautiful Los Gatos it's

(30:33):
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We are also translator K215GA90.9 FM in Los Gatos, 9 FM in
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(30:55):
And yes, ladies and gentlemen,that Portland the one way, far
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So we have just launched onlinein Portland and, of course, a
lot of you are already listeninghere at kpcrorg online.
So we're thrilled to have you.
Going back to Joyce's earliercomment about improv and I wrote

(31:18):
down the words curiosity, trustand collaboration.
I would say that's how you'vebecome so successful with your
AI board advisory practice.
Thank you.
Curiosity, trust andcollaboration and I shouldn't
put boundaries around it to bejust your board practice.

(31:40):
You do a lot of differentthings, but all kind of in this
forward motion of AI strategy,all kind of in this forward
motion of AI strategy andbuilding trust, working
collaboratively and beingcurious about the possibilities
is what we do.
Tell me how that love of improvand those things has helped you

(32:01):
be more successful in workingwith groups that are uncertain
and uncomfortable about movinginto this new era.

Joyce Li (32:15):
I I love the opportunity that a lot of these
leaders give me maybe based onmy past career building up that
credibility in the investmentworld or in the board governance
world to open the door for meto be in the room having the

(32:37):
conversation.
But what really helped me, andand also inspired me too, is the
ability to ask questions andthen just let the conversation
flow.
Yeah, so, going back to improv,yes, you give a gift, right,
exactly, and then let people um,tell what their challenges are,

(33:03):
opportunities are, andsometimes I feel like providing
a little bit like peer, whatyour peers are doing or what the
industry is moving towards,especially the emerging startup
world, where maybe in the pastit was not very obvious to these
board leaders that that'srelevant.
Now, these days, any startupscan potentially disrupt a

(33:26):
business with the technology,ai-first mindset.
I really appreciate that improvmindset of just listen, just
build on, just ask questions toyour earlier point and then I
know you are an expert on thatand then find a way to

(33:47):
collaborate and maybe evenco-design the way forward.
I do think that, more thananything today, providing a
solution is not the way to go,right, right, it's almost like
can you be a co-designer of that?

journey.
Yeah, co-designer, 100% right.
The problem is it's a newmindset shift and the people
that we go in to see call us inbecause we're the experts, yeah,
and they want us to walk in andgo here.
It is, yeah, and you and I knowthat it's a process to

(34:29):
co-create, to co-design.
For me, I think that we have to, often in the groups we go into
, create an environment ofcuriosity, trust and
collaboration.
I have this little trick I do,and since you don't expect any
of my clients are listening,I'll say and create FOMO.
Fomo is how I entertain myself.
That's the fear of missing out,and it's so easy because the

(34:52):
boards that call us they've notdone the work.
They're calling us becausethey're ready to do the work.
And if I go in and talk aboutthe other people in their
industry who are already doingreally interesting things, that
creates first FOMO.
They're like what?
No, how are they doing that?

(35:13):
Right, and it's easy for us toget this information, but then
that creates curiosity and doubtabout what could they do?
Right, right, what are some ofyour tricks that you've used to
create, to build out anextension of you in that team
around either curiosity orcollaboration, or trust?

Joyce Li (35:39):
I do think trust needs time.
It's very hard for you to comein the first meeting and then
really get people to trust whatyou say, especially for me.
A lot of times people would saythey were expecting a
technologist who has a PhD in AI.
You know, come in and have thatsolution right on the table and

(36:02):
then also tell them how muchmoney profit they can make after
implementing that solution.
Unfortunately, that doesn'texist.
So that trust of we can figureit out ourselves.
But very specifically to yourbusiness needs and constraints
are very, very important, andthen you just have to sometimes

(36:23):
you just have to hold yourtongue and be very patient and
understand who's at the tablethe stakeholders also, the
hidden influencers not at thetable oh, good point.
It's very, very important.
Ultimately, I think youwouldn't be surprised if you
operate in that world.

(36:43):
You know it's never abouttechnology, it's all about the
people and unfortunately, orfortunately that's the lever
that you have to build trust onand that's the leverage point
that you have to restack yoursolutions on to make it happen.

(37:04):
Unfortunately, also becauseeveryone is trying to move fast
in this AI impacted businessworld.
The competitors what arecompetitors doing, as you said
have an outsized impact thesedays.
And not only that what are someof the up-and-coming companies

(37:27):
AI-first mindset doing are very,very important.
And last point I would just sayis also very interesting is
that people are more open tolook at other industries with
similar characteristics.
So, for example, I work withyou know investment leaders,

(37:47):
investment team leaders.
They obviously are very heavilyregulated and they are now very
open to look at not just theirown peers but also their
counterparts in, let's say,legal or healthcare industries,
where regulation, obviouslycompliance, is a very important

(38:11):
element in that consideration.
So I do think that bridging,going back to what I love to do
plays a really important role inthat mindset change.

You mentioned regulatory things and to me I've
just taken on a new role.

Joyce Li (38:33):
You and I keep swapping places because I've
just taken on a role with aninvestment fund.

And it's largely currently.
The makeup is largely lifesciences Yep Life sciences
heavily regulated Yep.
You've been infinancial-oriented verticals,
heavily regulated, and the speedand the pace in the very
beginning.
You also mentioned pace beingone of the challenges of this AI
cycle.
Regulatory frameworks are notbuilt for speed.

(39:03):
They're built for security andprotection protection of
people's money, people's health.
But there's a mindset that I'mexperiencing now, being in a, if
you will, a vertical where Ihave more exposure to people who
have spent a lifetime in aregulated industry, and I think

(39:24):
innovation is more challengingGetting people aligned to these
components of trust,collaboration, curiosity is not
always the normal thinkingbecause the constraints have
been unnegotiable.
The constraints have beenfederal law around medical

(39:45):
devices or around payment.
So what are you seeing that isbeing effective at helping
manage both pace and these longcycles?
Frankly, for me, I'm looking atways around the long cycles.

(40:06):
I'm looking at ways that becauseI think our regulatory, the
requirements that we've put oncertain things, like in the
medical side, especially for mewere because we could not
appropriately test things, andnow that we have AI we can.
So it shouldn't take sevenyears to get a medical product,
device or pharmaceutical intothe market.

(40:27):
So our regulations need tochange.
But in the meantime, when we'rein this fuzzy period where we
have the constraints ofregulations and the hype and the
speed of the current era, whatdo you offer to people to help
them manage both without gettingdisappointed?

Joyce Li (40:50):
I think the most important thing for me is to
meet your clients or prospectiveclients, where they are and
understanding why they are sokeen on having the safe,
responsible systems in placebefore they fully embrace the

(41:12):
innovation.
Ultimately, I definitely feellike they are doing it because
they want to protect theirclients, they want to deliver
responsible AI outputs towhoever they're serving, and I
don't think it's an either orproblem anymore, because this is

(41:33):
one of the things that peopleall the enterprise clients are
very clear that this isnon-negotiable.
They have to be compliant, theyhave to be safe, they have to
to the extent they know, theyneed to have the right data
governance practice, and that'swhy the governance framework is
very important.

(41:53):
It's almost like once you setup the guardrails, it's actually
easier or more free to playwithin the guardrails.
When you don't have theguardrails, it's almost like you
always feel like you can jumpinto a hole right there.
So I think the right guardrails,right frameworks for the

(42:14):
governance and risk control haveto put in place as soon as
possible in order for you toinnovate more freely.
If we accept that, then we alsosee a lot of ecosystem players,
such as infrastructure playersand also some startups have

(42:35):
these collaborations across theboard Like?
How do you, for example,collaboration across the board
Like?
How do you, for example, how doyou audit AI activities real
time across different platformsin your enterprise environment
so that you don't haveunintended data leak?
For you know, unauthorized AIuse, which is sometimes a big

(42:56):
problem in some of the companies.
That helps that you have thepeace of mind to really
introduce innovative workflow,design, collaboration with
partners and rethink even someof the functions.
So one example I seeacceleration in adoption is in

(43:18):
the CFO suite, which means theCFO usually have a lot of
functions underneath talkingabout.
We're talking about accounting,forecast and budgeting and
planning and all those.
In the past you would thinkthey are the most conservative

(43:40):
because they need to get thingsright and, interestingly,
because of that, labor shortage,talent shortage in that space
and also a lot of tediousprocess over the last few
decades never got changed.
The incentive of using AIsolution is actually quite
appealing, of using AI solutionis actually quite appealing.

(44:02):
So in that space, people figureout how to, you know, break
down the workflow so that theycan test and verify the results
more easily.
How do they make sure the datagovernance who has access to
what data is in place beforethey introduce solutions?
The end result of that is we'reseeing a very fast adoption
curve in that space and for someof the startups, very, very

(44:25):
young startups, barely two yearsold, got adopted by very large
companies because they can,let's say, shorten the days
required to close for more than10 days to less than three.
So that's a huge improvement.
But that's also an example ofwhen you have that alignment,

(44:47):
you put the wrist guardrail inplace, you put the audible
process in place.
You can move fast.
You absolutely can move fastwith that guardrail.

Yeah, yeah, and I love your example of a close.
Anyone who's been close tofinancial you know.
I remember at one of my verylarge $5 billion enterprise
companies it was an 11-day closeand it was almost like a
certain set of us were paralyzeduntil the quarter was done.
The quarter's not done untilyou have numbers to reflect how

(45:21):
well it went.
And the closed process wascritical to a lot of the company
for what we would do for thenext quarter or two in terms of
what we would have for fundingfor building out staff, those
kinds of things, Absolutely.
So it is a game changer whenyou move it from an 11-day close
to a three-day close.
Right, Even less, Even less, Imean absolutely even less, so

(45:44):
fast that I think it would scaresome people.
Three days feels good, threehours so much.
But I think things are going tochange dramatically in the
finance world.
I talked a minute ago aboutsome of the things that we'll be
seeing with medical devices,pharmacological treatment, and I

(46:05):
think those things are going tospeed up, but I think the
finance vertical you areinvolved in is going to have
some things happen.
I'm not, as I don't spend asmuch time on the fintech side.
What do you think are the bignot strategy shifts, but the big
how we work shifts that arecoming in the finance sectors?
What do you see on the horizon?

Joyce Li (46:31):
There are a lot of changes already happening, so
you know I'm a big fan of Claudeperplexity.
They all launch various types offinancial analysis or research
tools right yes, yes, and I dothink in the traditional world
of investing, for example,research, we see a lot of high

(46:57):
value work being done withcollecting information,
filtering out the noises andthen making decisions better
based on that.
Now that whole sort of threesteps can be shrank into one
with AI's help.
So how we work now having, Iwould say, a lot of people doing

(47:20):
research or analysis work rightnow are going through their
mid-life career reflection.

Oh, can we tack another hour on to this
conversation?

Joyce Li (47:33):
Yeah, but more like now what are we going to do in
terms of day-to-day?
What are we going to do interms of day-to-day and where is
the most value-add componentsof your work to your ultimate
clients?
And going back to whatdifferentiate your business
value as an investment firm oras a wealth advisory firm?

(47:54):
So I actually think this is themost exciting time, because I
talked to quite a few leadersinvestment team leaders and
wealth advisory leaders over mytrip to New York and then also
last few weeks and I'm hearingmore and more interestingly and
also inspiringly, that they areasking question are we thinking

(48:17):
big enough?
What will our industry or theway we work become in 10 years?
And let's walk back from there.
And how do we think about whereto invest, how we structure our
team, how do we train our talent?
And to go into your I think,the theme of your episode how do

(48:38):
you accelerate that build uptowards wisdom faster?
Yes, and these leaders areabsolutely brilliant, for sure,
but now they are taking almostthis as an industry defining
moment.
Yes, it is.
It's really inspiring Multipleverticals.

It has an industry defining moment.
I latched on a few months, amonth ago, to the term habit
highest and best use, and a lotof people have been going
through transpersonal journeysof you know what's my personal
purpose, yep.
But I think now organizationsare starting to think that way.

(49:14):
That's what you're saying isthat organizations are thinking
in terms of what's the highestand best use of our time and
effort on behalf of theconstituents we serve?
Exactly, constituents is payingcustomers, but it's also
employees, it's also investorsin that company, exactly so
there's an ecosystem of impactthat goes beyond just selling

(49:35):
that blue pen, absolutely.

Joyce Li (49:37):
To as many people as possible.

Right, right, I love that you've mentioned this.
By the way, you were in NewYork and you had lunch with one
of my like LinkedIn, like youknow those people that you just
have so much admiration for, andyou got to have lunch with her
and I was like I was like fanned.
I didn't even know that youguys had a connection other than

(50:01):
.
I bet you worked on theplaybook together.

Joyce Li (50:03):
Absolutely, and Jaya is a fantastic leader.

She's just absolutely remarkable.
I envy in the best way herplace in life where she thinks
for a living.
She thinks broadly, deeply,consistently with people, and I
love what I see her put out intothe world.

Joyce Li (50:25):
And that's one thing I really enjoy this moment in our
journey shared journey is thatyou keep your door open and
anyone online, and then that'sanother thing that I think both
of us do is to share while youlearn.
You don't have to be 100%expert yet, you only have to be.

(50:49):
You know you're learning, youhave some thoughts to share and
then just share openly, and thatopens doors for these type of
friendship collaboration tohappen, and anyone is just
message away and it could leadto the most interesting
friendship ever.

Yeah, absolutely, absolutely Something about what
you said.
There's a point that I shouldhave made earlier about the
variety of things that we do andthe variety of people that we
connect ourselves to and how weserve, how we show up in the

(51:27):
workplace, um, and you youreflected this just a few
minutes ago about uh, peopleexpected someone with more of a
deep tech background, and Ithink that we are honestly so
good at what we do because wedon't have a deep tech

(51:48):
background.
We have been in tech, we havespoken on behalf of tech.
I mean, we're clearlycomfortable with tech knowledge,
but because our background isbroader, we are able to create
more touch points.
That is ultimately how AI willenable and connect the world in
new and different ways we've noteven considered.
So I think I look at you andwhat you're doing and I think,

(52:14):
if you had been because there'ssomething that triggered the
thought in your last statementsabout you're not locked in,
you're not rigid about how asolution evolves, you're not
thinking about elegant code.
I used to have a crop ofengineers all about their
elegant code.

Joyce Li (52:32):
I didn't give a flip about their elegant code.

I wanted to do it at a higher quality level At a
higher quality level, but Ithink that that variety in who
we are is what enables us toserve.
So the next part of our lastfew minutes, I want to move us
to what I call the lightninground, because these are just

(52:58):
quick questions, quick answers,and for the last five or six
weeks I've been doing this havebeen the best part of this
episode, of these episodes,because people get to like, say
things that they haven'tconsidered before and they get
to show people in the audiencelike who they are.
Okay, and this is not going tobe like the interview question
about if you're any item in afridge, what would it be?

(53:18):
Well, we painted that one Shutup.
So if you weren't in finance orAI, what career would you have
chosen, Joyce?
Teaching, love it, love it.
I can see why.
What's the one AI tool youcan't live without in your daily
work, claude?
Oh, good, okay, what's the bestpiece of advice you've ever

(53:41):
received?

Joyce Li (53:49):
That's an interesting one Because that changed a lot.
My answer definitely wasdifferent in the past, but now I
truly believe focus on you know, pursuing excellence during the
process.
Yeah, do not be too caught upon the outcome.
Outcome is there's definitely acomponent of out of your

(54:10):
control.

So that's a mindset of inner excellence from
the book by Jim Murphy my nextbook keeps getting pushed out in
terms of other priorities,keeping me from writing it.
But the title of the next bookis the journey is the job, so
you'll see me hashtag that a lotbecause I believe all this that

(54:31):
we're doing, this is the workcorrect, not the solution, not
the end result, but the work,and especially for us, because
it's so collaborative, itinvolves others, it teaches
there's by design and this isthe journey you know, the
journey is the job.
There's another quote thejourney is the destination um

(54:52):
the.
Or prioritize the journey overthe destination and um yeah, so
all right, the most overratedtrend in ai right now.
All right, the first overratedtrend in AI right now.

Joyce Li (55:06):
Oh, that's a tough one , because I was wrong so many
times.

Oh, but I know I love that.
My last guess Jesse Anglin outof Coeur d'Alene, Idaho.
Yeah, he has a lot of pride inhow wrong he has been about AI.
Yes, and it's all on time.

Joyce Li (55:24):
What he?

saw is his vision and he's got a pretty
aggressive vision, but he waswrong on timing for a single
time, because things havehappened so much faster than we
could have forecasted Right, sohe's always been wrong.
We started out with a Bitcoinstory.
So Bitcoin from like 2010Bitcoin, so do you have anything
in mind about?

Joyce Li (55:46):
About what's overhyped .
About what's overhyped, I dothink that video generation
tools right now like so muchmoney going into it.
I like the virtual worldbecause that has a lot of things
to do with robotics and stufflike that, but completely like
imaginary video creation.

(56:08):
I guess I just haven't got thehang of it why it's so important
, ethan.

Mollick can make Veo work.
But, I can't get the beautifulimages out of any of the imagery
apps that I want and that Iwould say is consistently the
most frustrating consumerexperience that I have, yeah.
Is I'm like I want a picture ofa teddy bear sitting on a

(56:36):
picnic table next to me.
That's pretty simple, that'sright, and it gives me a dragon
flying over the Grand Canyon.

Joyce Li (56:42):
Yeah, it's yeah, I'm pretty sure there are experts on
that.
So now that we say it, we'regoing to be wrong.
Yeah.

You talked about learning in the very beginning.
What's something that you'relearning right now?
What's a skill you're workingon?

Joyce Li (57:03):
I'm actually picking up coding again.
Oh are you?

vibe coding.

Joyce Li (57:09):
I actually think vibe coding is a misnomer, which it's
another our long story, butit's definitely, I would say,
creating with these type oftools like Cloud, for example,
cloud code.
I created all these products.
In fact, I actually recreatedthe things that I built when I

(57:31):
was having that startup.
We spent months on it and now Ican build it within a couple of
days.
So it's really interesting howI can just have an idea and then
have a chat with my AI internor coder and have that done.
Of course, the learning processis the most important thing,

(57:54):
because it's easy to getsomething.
You can get very confidentimmediately, but then you go
into the debugging and then itwill kill you.
And then you went through thatand then now I better understand
how to work with AI.
I do feel like that.
Just keep learning by doing.

(58:15):
It's a very fun thing.

But I experienced that too.
The debugging process.
But for me that's like when Iused to have high homes, when I
was in fencing, like big housesnot the condo that I have here.
When I first started buyinghomes, I bought old homes and I
would have to redo everything.
It's part of the joy whenyou're in your 20s, and I think

(58:42):
that's when I would developintimacy with a home, when I had
painted all the corners, when Ihad stripped the wallpaper in
the bathroom.
Because you know all the curvesand all the nooks and crannies
of that space.
When you've crawled underneath,you know the sink to put in
something new, yeah.

(59:02):
So I think the same thing aboutdebugging you develop true
intimacy with the product you'vecreated as you figure out how
to make your vision work.

Joyce Li (59:14):
I completely agree.
Anything that you know, youhear people talk about, even if
you end up not liking it, suchas image creation.
Um, you can still develop thatlevel of taste and that taste
will come in handy when youdetermine what's more of a hype,
what's more of a tangiblebenefit for what you do, what

(59:36):
you help other to do, withoutyou know, trying it, you know,
just get other people's view onit, it's not going to cut it?

Yeah, not at all.
All right, as we wrap up allthis experience, all these
amazing experiences that you'vebeen having for the last 20 plus
years, they are all leading yousomewhere.
What do you hope they arepreparing you to do next?

Joyce Li (01:00:06):
I want to just play into this bridging concept.
Oh, yes, I now imagine all thethings in life and work and
friendships are like in allthese amazing islands and I just
jump, hopping across andbridging between them,
connecting through them, and Ifeel like that's the best

(01:00:30):
learning journey and hopefully,during the same process, I share
what I learned and help othersto build their own bridge.
That's what I hope to do.

Tonya J. Long (01:00:41):
I love it.
Now you've got some of thosebridges already in place for
other people to enjoy.
So, as we end the session,because there are so many things
I wanted to talk to you aboutand just did not get to Tell
people how they can follow you,how they can learn with you,
what avenues are out there forthem to connect to your work-

(01:01:03):
Absolutely.

Joyce Li (01:01:04):
I would love for your audience to come and say hi and
then you know, this is how wegot to know each other and maybe
we can collaborate more.
Linkedin is where I'm veryactive.
Yes, and then I also have anewsletter called AI Simplified
for Leaders or Substack.
You can also get a link fromthe linking profile.
Excellent, Excellent, Thank you, Thank you, and from time to

(01:01:29):
time, I will be coming on anoutstanding show like this and
just yeah, just to share alittle bit of what I'm going
through in terms of my learningjourney.

There's so much there for all, for all of us to,
because it is about all of ustogether.
There's less competition nowand more collaboration.

Joyce Li (01:01:51):
Abundance mindset.

Abundance mindset oh, help me out here.
Awesome we're.
We're giving love to thosepeople that that have taken
their time with us today, and soeveryone from RESET with Tonya,
with Joyce Li talking aboutliving in this technology, but
living being the priority.
I think that's what today'stheme was, because we see it as

(01:02:15):
a pathway for us to do thethings, to be with people to
serve humanity, and it has beena fun conversation.
I appreciate you being here.
Thank you so much, Talia.
Excellent, All right.
So signing off from Pirate CatRadio, Are you ready for it?
Kpcr LP 92.9 FM in Los Gatos.
Translator K215GA 90.9, also inLos Gatos.

(01:02:39):
Kmrt LP 101.9 FM in Santa CruzI need to automate this and
KVBELP 91.1, our little baby inproduction less than a couple of
weeks up in Portland.
Also, for those of you online,I love you, I thank you, and
Joyce and I have tremendouslyenjoyed being part of your last

(01:03:01):
hour.
Thank you so much everyone.
Thank you so much everyone.

Joyce Li (01:03:03):
Thank you so much.

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Episode Transcript

Host

Tonya J. Long

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