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A podcast that explores how AI is transforming careers, businesses, and industries. Hosts Greg Boone and Erica Rooney deliver real-world use cases and actionable AI strategies to help professionals stay ahead of the curve.
Learn more about your hosts:
Erica Rooney, author of The AI Gap: Women, AI, and the Next Great Leap Forward
Greg Boone, author of AI at the Speed of Trust (available for pre-order)
Angela Liu: Everybody needs
to make a living, right?
And none of us have all the answers,
not even the people at the top, right?
Like, let's remember to
be humble as leaders.
Make spaces for people to experiment,
to explore, to share what didn't
work, and share what worked, right?
Because Thomas Edison came up with
how many ideas before he finally
made the light bulb work, right?
What doesn't work is just as important
as figuring out what works, right?
It's that journey that gets there.
Greg Boone: AI isn't the future, it's now.
And whether you're in hr, sales,
operations, or leadership, the
choices you make today will determine
whether you thrive or get left Behind
today on ai, voice of victim will bringing
together two sharp minds who are shaping
what it really means to move AI forward.
Angela Liu.
Is the founder and CEO of Ikaru
Consulting, where she helps
businesses scale with strategy,
clarity, and compassion.
We also have Tom Simon from Walk
West, our growth architect here.
I work with him every day.
He's focused on AI automation
and helping organizations create
efficiencies that drive real impact.
Uh, together we're gonna explore how
leaders are navigating AI adoption
from protecting human dignity to
reshaping how we work, learn, and lead.
So I wanna welcome you both
to ai, voice of Victim.
Thank you for being here today.
Thanks.
Thanks for having me.
So, uh, before we get started, you know,
I gave my view of Angelou and what you do.
Can you tell our audience what
you do and what you're all about?
Angela Liu: Yeah, so, um, I'm
basically a fractional COO.
So I love working with small
businesses, startups, early stage
organizations and nonprofits, and
helping them grow and scale, be
ready for whatever their shifts are.
Um, make sure that they have the people,
processes and tools in place to make
sure that they can deliver on the
impact and the missions that they have.
Greg Boone: Okay.
So, um, just a little
background for our audience.
You and I used to work together.
I don't know, uh, how
long ago do you remember?
Maybe
Angela Liu: 10 to 15 years
Greg Boone: ago now.
Yes.
So yeah.
Over a decade ago we, we
used to work together at a, a
different consulting mm-hmm.
Company in a completely
different industry.
Yeah.
Right.
So a lot of change has
happened over the years.
You and I both have kind of, uh,
centered on ai and we're gonna talk a
little bit more about that in a second.
But I wanna give Tom a little space
here to tell us a little bit more about.
What the hell is a growth architect Tom?
Tom Simon: So a growth architect
is designed to help your company
grow in terms of ROI and in terms
of efficiency in your marketing.
So my goal and job is to work with
clients to help them through automation
processes and also help them streamline
how they're working, how they're reaching
out to clients, how they're nurturing
leads, so that we can help through this
whole process of lead crisis and also
attach it to our overall loop strategy.
Okay.
You
Greg Boone: said a lot there.
We're gonna, we're gonna break that
down a little bit as we go through this.
You know, I recently was with
both of you in, in Charlotte at
the AI Forward Conference, right?
Which is all about this, uh, AI shift,
if you will, this transformation
that people and organizations
are going through, uh, today.
So, first and foremost, can you guys
give me just a recap of what you learned?
I'll start with you, Angela.
What did you see?
What did you like, what did you
dislike about the conference?
Make sure I don't forget the dislike part.
Oh, I don't forget
Angela Liu: that part.
You gotta have a hot take.
So it was two days, right?
The first day Mark Hinkle just
kind of did this whole overview.
Right?
And um, I'll just say it was really great
because it was not overly technical for
people who aren't technical with like,
say, a development background, right?
Um, but I felt like it really
touched on what people needed to.
Genuinely understand in order to lead from
the top, like as a Cee o, um, as you're
moving through this AI transformation.
So with my background as a former
software consultant and doing digital
implementation through the organizations
I've led right understanding.
What the technology is from an
architectural standpoint and which
defines what its limitations and cap
capabilities are, is really important
because then that actually helps you
imagine, what can it do for this team?
How can we actually implement it?
And so he did a really great
job, I think, of helping.
Um.
Bring that level of perspective across
a variety of dimensions, um, around ai.
So like for anybody who had been new
to the, the space and hadn't really
followed it much, I think they would've
gotten a huge amount out of it.
For me, it was very validating,
um, because it kind of, he
shared a lot of perspectives
that I was like, yep, I agree.
Um.
And then the, the next day, you
know, a lot of panels and stuff.
Um, honestly, I really wish
that we could have, I could have
sat on on more of 'em, right?
Just the fact that there were two
panels going on at the same time.
I was like, man, I'm missing out on
something else that's also really awesome.
Um, but one thing that I don't
feel like was really there
enough, right, was talking about.
The responsible use of ai, right?
So there's a, there's ethics, right?
But there's also say the
environmental piece, right?
And so there are people out
there who are really, really
concerned about this, right?
And even if some people feel like it's
not as big of a deal, they're dismissing
it, whatever the case might be, right?
You know, there are still people out
there who genuinely care and want to make
sure that as we're building and scaling
this technology right, we're doing it
in a way that makes sense for the future
of our society and our planet also.
Right.
Um, there was also, we'll say
like some people out there who
were like, where are the women?
Right.
Um, not to say that we didn't
have women's speakers, we did have
some women's speakers, of course.
Right.
I think it's, you know, there is.
There's definitely also a demographic of
people right in the space who are like,
we want to see more, uh, space being made
for the women and the tech leaders who
are also pushing this forward, right?
Because, you know, there are differences
in how men and women lead, right?
We're capable of the same things, but
where we focus in the values that we have.
Sometimes differ.
Right?
And it's not that any is less
important than the other.
They're both important, right?
And we need to be inclusive of that
so that we're, what we're creating
as a future together is stronger.
Greg Boone: Yeah.
I mean, there was a lot there.
So I, I appreciate that you and I had a
very similar conversation at a conference.
Uh, I guess.
It's been a month ago at this point.
Um, I actually had a very, uh, spirited
debate with Mark Kinkle yesterday
for, uh, the end of the day yesterday.
'cause we're talking about the next
conference and thing that we're
gonna be doing on December 3rd.
But we talked about, um, the other
one was the AI State of the Union.
Mm-hmm.
Uh, conference.
And I said on stage that same
comment, which is there needs to
be a, a much more diverse audience.
Right.
Women are gonna have to be
represented and also lean in.
Right, because there was a point,
and there continues to be a point
at which women are adopting it at
significantly less the rate of men.
Right now there's already a
lot of inherent bias in AI
because of history, right?
And so for people to be see better
representation, we do need, uh,
more folks want to create a stage.
So credit to Mark, there was, I
would say a significant number of,
of women on stage that were talking,
but it was also very notable.
The, there was less
representation in the audience.
Um, one of the things I did think was a,
a, a kind of a good, uh, view was that
there was a good number of leaders, right?
I've gone to a lot of these conferences
and a lot of tinkerers and a lot of
people that are trying to build stuff,
and I keep calling out the leadership
community and say, you have to better
understand what's happening right now.
And then, um, we'll get back to the
responsible use here in a second.
But, Tom, what are some of your takeaways?
So we were only there the second day.
Tom Simon: Um, I kinda share
the same thing about the panels.
Um, there was, so there was overlapping
times where I was like, gosh, I wanna
be in both spots, um, to pick through.
But for an all things open type
of event, I did find it was really
encouraging to see that things were
covered at a much higher level.
If you've been to ai.
All things open.
The AI conference in March, it'll
be in Durham again this year.
Um, it's very, very technical and so
our, most of those events are uh, I
sat in one that talked about CPS and
it was a really well discussed kind
of topic in terms of what they do.
They showed the flow of how it worked.
However, there was one point, and you and
I discussed this as well in that, where
he said, this is where the poison is.
And I kind of cringed at
that moment 'cause I went.
That's now telling people there's
something dangerous and that's not what
you intended to do, but your graphic
made it look like as if something
very dangerous or scary can happen,
and it's not that kind of complex.
So I was a little thrown there.
I think the other panels though, to your
point, there were great leaders involved.
Um, they had one panel, uh, with,
that was focused on startups.
Which really kind of gave me the first
feeling in a while, these conferences that
somebody was talking about how startups
can engage with ai, not these kind of,
you know, not bigger companies or this is
how Disney uses it, or stuff like that.
Really grounding it down to a
very basic level where people can
engage and use the products and
everything that comes out of AI today.
Um, so again, I think for the, in general.
Really well done, um, really well covered,
uh, in terms of some of the topics.
Um, just like anything else, you just
wanna see more or have more time.
That's about it.
Erica Rooney: Yeah.
Greg Boone: Yeah.
I mean, I see this quite a bit, right?
I've been to a lot of
conferences this year.
Tom and I have both been to some
conferences this year and there's just so
much excitement and so much energy, but
there's also so much overlap and you're
like, I want to be in the same, like in
two different places at the same time.
And I think that's a challenge,
but it's also a testament
that people wanna learn more.
And they want to understand that
people are trying to pack as much
as humanly possible on the MCP.
Now, was that, was that
Don Shin's who's Yes.
Yeah, yeah, yeah.
Alright, so I was chatting
with Don over LinkedIn over the
weekend, so I'm gonna give Don a,
a chance to come on to the, uh.
To the podcast and defend
himself and explain what's there.
Uh, you know, we had a, a former
coworker that said, uh, that commented
'cause Don commented on some post
I made and he said, he's like, man,
see you and Dom know each other.
He said, that's like my first time
seeing the Avengers come together.
I said, as long as I'm Black
Panther and not Hawkeye.
'cause I was like, 'cause he
is barely a real superhero.
Um,
I wanna go back just for a second.
On the responsible use.
Kinda give some, um.
A little bit more air, uh, to that.
'cause I've heard that a lot.
Right.
I don't think people understand
the amount of power and energy that
is needed that is required for ai.
It is significant.
Right.
You're talking about, I think at one
point they were saying that I think it
was in 2024, that, uh, OpenAI use as
much energy as the nation of Barbados.
Mm-hmm.
Right.
I always explain to folks, I'm
like, that's at like 5% adoption.
And I say this all the time, it's like,
what happens when we get to 20% adoption?
Mm-hmm.
Right?
You're literally gonna
melt the grid, right?
Or you're gonna get into a
situation where it's gonna be.
My view is that we're already
kind of racing towards this.
There's gonna be this
have and have nots, right?
You're gonna have the bigger
companies that are buying up all
the data centers, all the racks.
They're the ones that can build their
own, uh, you know, substations and
hubs for all these things, right?
So my concern is partly yes, the,
the responsible use and, and kind
of the energy and all the things,
um, you know, affecting the planet.
But the other part is also.
What happens to the much
smaller organizations?
How do you compete and survive?
So do you have a take
on that at all, Angela?
Angela Liu: You know, I think,
I always look at the future as a
spectrum of po po possibilities, right?
Yeah.
And I think there's a lot of different
ways things can go, and I think the
reality is it's gonna probably be a mix.
Right where we're going to have
some of the giant conglomerates
and we're still also going to have
options for the small businesses.
Right.
I think, you know, as we talk about,
say, some of the disparities, right,
the technological access disparities
that we're, we're worrying about, right?
It's going to be a propagation of
basically what has been happening
over the last few decades as it
pertains to computers, internet,
things like that, right?
When you think about the world and the
amount of data that's been digitized and
that the AI is being trained on, right?
It's predominantly centered
around certain languages.
Certain cultures, certain parts of the
world, there are areas of the world that
haven't gotten their data digitized.
They are not represented in that data.
So that's what causes, in my
opinion, the inherent bias of ai.
It's less of an intentional, we don't
want their data and more just a, it hasn't
gotten digitized, so it's not available
to give to the, the models and such.
Right.
Um, so I think if we want to see better
representation across the globe and
across different cultures and races
and things like that, we'll have to
make a much more intentional move to
go to these places in the world and
say, we want to make sure that your
culture, your, your ways, the knowledge
that you have and the information
you can share is included, right?
Maybe there's a business model in there.
I don't know what that is.
Right?
But there's something there, right?
Where if we really want to
make these models more powerful
and less biased, right?
Something's gonna have to happen to
make sure that information's brought in.
From an environmental standpoint, my
understanding was that it's mostly
the training that's training so much
of the resources, but like the prompt
in and of itself is pretty much, I
think at this point, the equivalent
of you put in a Google search, right?
Um, so I guess the big
question is how much do we keep
training and retraining and.
Doing that big load on these
models to make them bigger.
And I hear some voices in the, the
community, right, who are talking
about small models are actually
gonna probably be the future, right?
If that's the case, maybe it won't
be so energy intensive, right?
But I don't know, there's,
there's still a lot to be worked
out in the space, I think.
I
Tom Simon: think just to tap onto
that too, you've got Oracle announced.
Billion dollar deals with
Brett Chappie, uh, jet, GBD.
Mm-hmm.
Think it was anthropology yesterday.
Talked about doing a massive deal
with AWS one of our clients, check Hub
works with Oracle and some of these
things working in terms of how these
processes are working, how their teams
are managing it, and there's a big
talk about dependency on water as well.
Yep.
So take, you know, electricity
is the one part, the water is
a significant other part to it.
And I think to your point.
You know, maybe as we get past some
of these large, you know, language
learning kind of opponents and we
do all this kind of stuff, we'll
be able to move away from them.
But there again, does the future of
AI become so consumable that all we
do is adjust from one pile to another
pile, still consume those resources,
but now for a different focus?
And I don't know that we know
that necessarily yet, but it
certainly was a, I had no idea.
That they took that much
kind of resource to do.
So it's an interesting take, um,
that I think stays to the side.
You know, the, uh, the ethical part
floats a little higher, but there's
an environmental impact that we're
gonna have to consider as we continue
to develop and grow these things.
Greg Boone: Yeah, I think
they, you know, they, the thing
people don't understand, right?
So, to your point, the, the, the
training runs are the most, uh, power
intensive, uh, part of this, right.
Then the water that you're
describing is all about cooling.
Mm-hmm.
Right.
So the, now the challenge in the US
is our infrastructure isn't built in a
way where the data centers and things
are close to where the actual power is.
That's the fundamental problem we did.
We haven't invested in infrastructure
in like 70 years, and now that is
creating its own set of challenges.
So if you think about now, a lot
of people are building in Virginia
and in rural places in Georgia.
In Tennessee.
That's great.
There's no access to water
and energy right now.
Earlier this year, I remember talking
to the team here at Walk West, 'cause
someone brought this up near the
beginning of this year and they were
asking me the same thing and I said,
well, here's the promising thing.
So deep seek coming out of China.
What they proved out was they were
able to train on significantly less.
'cause they, they kind of flip the script.
They change effectively,
I'm paraphrasing here.
They trained on the top 15% of experts
instead of the entire internet.
So instead of them having to scrape and
leverage all that, now also in China,
they've also invested significantly.
Right, right, wrong, or indifferent in how
they built infrastructure over the years.
Right?
And so you're hearing a resurgence
also of what, uh, people would
describe as clean nuclear, right?
In different ways for,
uh, getting this energy.
It's also what's behind the
drive for the US to try to buy
Greenland, whatever that means.
It's all about energy.
People are trying to figure
out how do you create.
These massive data centers closer
to where there's wind, solar,
other forms of energy, right?
That's what's kind of, uh, backing that.
And then I agree with you on the small
language model side of things, right?
You don't need a large language model
for, to solve every single problem.
So I do, I was talking to some
other folks earlier this year.
I do predict that in 2026, you're
gonna see a big uptick in small
language models, open source models
that folks are gonna start to
leverage as they better understand.
But it goes back to an
earlier comment, which is.
We need more leaders to lean in.
If the leaders don't fundamentally
understand that, Hey, I don't, 'cause
all they're hearing is buzzwords.
And I talk to people all the
time, it's like, well, I think we
need a, a large language model.
It's like, I not to solve that.
You don't.
Right.
And so I think that's
part of the challenge.
I wanna get back to kind of the, uh,
something that you talk about, Angela, you
know, both off camera, you know, and I've
seen you at conferences and other places.
Right.
But you talk about
protecting the human dignity.
Right.
Can you unpack that for us a little bit
more and how are you describing that?
Angela Liu: So a lot, there's,
there's a lot of excitement and a
lot of energy around AI right now.
Of course.
Right.
And I think the thing that people
sometimes forget is, this is
still digital change management.
Fundamentally change
management at the heart of it.
Right.
And the, the most challenging part
of change management is the people.
Right.
It's about getting people to learn
and adopt new ways of doing, right?
Learning new tools, new ways
of interacting and working
together, things like that.
Right?
And there's always some
level of resistance that we
have to work through, right?
Um.
Then on the flip side, right, of business,
right, we talk about how turnover, right?
Cost.
There's real cost to turnover
in a business, right?
Um, whether it's because people left
your company or just attrition, you know,
people who cycle through whatever, right?
But.
You gotta think about this, I think
from a bigger perspective than just we
need AI and we're gonna implement it.
Um, I think there are unfortunately
some leaders who are thinking about
things in from the framework of,
you know, okay, we're gonna go ai,
so let's just lay off these people.
Let's implement a bunch of ai.
Let's bring in people who know ai.
Right?
Well, that pool, that talent pool is still
small because AI is still relatively new.
Just like what, A few decades ago
computer knowledge was low, right?
It's like, yeah, everybody wants a
computer expert, but you're gonna
just have to homegrown that, right?
AI, in my opinion, is really la
That's where we're at right now.
People should be thinking more about
home growing their AI expertise
rather than just, let's just get rid
of these people who are resistant
and bring in somebody else, right?
Because you're losing, um, the
knowledge, the historical knowledge of
what's going on in your business, the
people who understand your business,
what it's about, your customers.
How, you know there are internal
secrets and, and special secret
sauce for your business, right?
There's value to that, that
you can't really put a real
concrete dollar amount on per se.
But when you say goodbye, right, rather
than upskilling your people, you're
losing that and you're actually slowing
down your business's momentum, right?
Because let's face it, you bring in
somebody new, give them a year before
they're actually really adding.
Like something unique
to the business, right?
So when I start, talk
about human dignity, right?
I'm saying remember that one, all of
us are humans, first and foremost,
before anything, any title, any
role, our first breath, right?
And treat people with respect, right?
With dignity, right?
Everybody needs to make a living, right?
And none of us have all the answers,
not even the people at the top, right?
Like, let's remember to be
humble as leaders, right?
And remember we're figuring it out.
Our people are figuring it out too, right?
So give people that space to
experiment, to explore together.
One of the things I thought was really
great, um, another takeaway from the
conference at AI Forward was, um, this
theme of how community learning in
community is actually really powerful,
especially for this transition, right?
Make spaces for people to experiment, to
explore, to share what didn't work, and
share what worked right, because that.
Learning.
That's where we're gonna get
really great learning, right?
Because Thomas Edison came up with
how many ideas before he finally
made the light bulb work, right?
What doesn't work is just as important
as figuring out what works, right?
It's that journey that gets there.
Human dignity is about making sure you are
treating your people with respect, right?
And so that's partly okay, how do
we create these intentional spaces
so that they can learn, right?
Rather than putting all this pressure
on, they gotta figure it out, right?
That they gotta do it fast, right?
Um, but also.
Remember, you gotta
bring your people along.
You know, as a leader, it's our
responsibility to make sure we're
thinking about how do we take care
of not just this business, but this
business includes the team, right?
So it's not just the money,
it's also the people.
Because the people are what helps us have
the scale and impact that we have, and be
able to pull in the revenue that we have.
So bring in your people.
Let them learn, right?
Treat them respect.
And yes, there's gonna be some turnover.
I'm very pragmatic, right?
So if you're gonna do that.
Treat them with dignity
on the way out, right?
If for whatever reason you really
can't find a way to reskill
them, upskill them, right?
Treat them with dignity, right?
Like the way people have been
getting laid off in more recent
years, in my opinion, it's a crime.
Like, come on, man.
Like at the end of the
day, we're all people.
Would you wanna be treated like that?
Like, come on now.
It's not, that's, yeah.
Greg Boone: I, uh, that's
Angela Liu: not a good business.
Greg Boone: You know, my whole
presentation at AI four conference
was around AI with the soul, and the
whole point was around the human edge.
Right.
And to your point, like you have to
treat some folks with dignity for sure.
Right?
Like, I've seen a couple of big CEOs,
uh, one in a, one of the big consulting
firms, let go of 11,000 people.
And basically said publicly that, because
these folks couldn't learn, GAI, it
was a, I'm paraphrasing here, but how
is that helpful for that individual
trying to find their next job, even if
that was the rationale right behind it.
I think the other part is like, uh,
I, I lead off all of my speaking
engagements now with this Upton
Sinclair, uh, quote from 1934.
It's, it is difficult, you know,
it's difficult to, uh, get a man to
understand something when their salary
depends on them not understanding it.
Right.
It is very challenging.
Right?
And this is where I put kind
of the, you know, I put some, a
lot of the onus on the leaders.
I'm constantly calling these folks out.
I'm like, you have to lean in.
We always say here at Walk West, you
gotta make it personal, fun, and safe.
Right?
And those folks would then
start to row, you know, with you
instead of rowing against you.
But I do think that we're gonna reach
a point though, where it's gonna
be very challenging because I tell
people all the time also, is that as
business leaders, I say, you don't
have to worry about AI replacing you.
If your company goes outta business,
all y'all gonna be replaced.
So there is a fine line where these
folks are gonna have to figure out this
balance and you're gonna see, you know,
slowly but surely going into 2026, people
are gonna move from carrot to stick.
Right.
At some point, and I agree with what
you're saying, but at some point the
business is gonna take care of the
business because I gotta take care
of the 80, 90% of the people, right?
I can't resort to just the 10%
that are gonna keep pushing back.
You wish them well and to your point,
if they need to exit, exit with dignity.
Right.
Um, but it's also very challenging
because the market isn't great.
Right.
So you have some people that are just
staying sabotaging the efforts mm-hmm.
Because they can't find a place to go.
Yeah.
So it's, it's a very
challenging time, you know?
Tom, what's your thoughts?
So, I think two things.
Tom Simon: One, the
community aspect of it.
That's such a big part of how.
Those guys put their
events together, right?
They're different people with different
specialties that teach in a panel.
Then also then provide an outlet to say,
I put this up on GitHub for you to use,
or I put this on that where if you go to
a major corporate conference, it's gonna
be clients or customers that have used it
and use it as a pitch and an opportunity
to use their platform and do that other
stuff from the ethical side of it.
I also think there's a combination.
It's leadership, it's comms teams as well.
Right?
So if you look at the Amazon,
uh, recent layoff, one of the big
headlines, it was in LinkedIn News.
It was right along the side, was them
saying, you know, we're doing this
'cause AI is gonna replace these things.
No ai.
I.
Should be a, something that, you
know, individual contributors can help
drive and help businesses grow with.
Not be replacement tool,
not be led as such.
Because quite frankly, there's
not enough data or analysis
to say that that's the case.
So there are a couple residual rules
maybe, but I'm not even willing
to have that conversation yet.
To your point, I think it's not ethical
and I think there is a human element
to this that we have to be very.
Like very, very important and
very keeping focus about right.
We need to keep that there because
the moment we stop doing that.
The moment becomes about machines.
The moment this entire AI conversation
could go completely to the left
and then it becomes the enemy, and
that's not what we want it to become.
It's, you know, we talk a lot about
here at Walk Retrospect being a very
human-centric experience, right?
These.
These things will grow and mature
and companies processes will get
better because the people using
those tools will help enable that.
But if you don't empower them, if you
don't give them that opportunity and
you just say, well, let's just cut bay
and plug something in and let it run.
I don't see a world where that's gonna
help you necessarily today in that aspect.
And two, to your point, you're gonna lose
not only just that, but the human, the
cultural element of it, the engagement
process, that kind of one-to-one
thing that is still so important.
I don't, you know, web bubbles didn't
change that, you know, everything
else, like that's still an important
element to this, to your point.
The market's hard right now, so that makes
it a challenging conversation to have.
But I think the core reality of it is, is
that while we can continue to grow this
and develop it, we have to keep humans.
This conversation and not
make it about a machine.
And that's, that's the responsibility
of leaders, that's the responsibility
of comms teams and major companies.
'cause they're the ones making the
biggest noise when they're making
these big challenges and decisions.
I, you look, turn on TikTok now and
there's entire channels devoted to
people recording themselves getting
laid off and half the time they're
talking about these things and that it.
It's really terrible and hard to watch.
So I think we have to keep that in focus.
I think it's great that people like you
are out there having that conversations.
I don't think there are enough and we need
to keep that in focus as we move forward.
Greg Boone: Yeah.
Tom Simon: Yeah.
There's a lot
Greg Boone: of, uh.
There's a lot of scapegoating also for ai.
Like there's a lot of people
that overhired during the
pandemic for whatever reason.
Yeah.
Amazon's one of them, right?
They just be cr Yeah.
They may say ai, AI
Angela Liu: companies were a lot of them.
Right.
Greg Boone: But there's a lot of people
that overhired during the pandemic
thinking that people were never gonna
go back and talk to humans again or be
in rooms as small as this one right here.
Right.
And I think they're using
AI in the narrative.
To be able to be the scapegoat
for bad decisions that were
made 2, 3, 4 years ago.
So that is also a challenge that
is happening, Ray, and this is
probably the first time in my.
Career that I've seen so many knowledge
workers, not that we're any better than
any other worker, but it's the first time
that I've seen people at the director
and higher level knowledge workers.
So just to be clear, the Amazon,
uh, layoffs were primarily affecting
corporate knowledge workers.
There weren't people in the
factories or the drivers.
Right.
And that's the part where people
are like, oh, now it's a problem.
You are okay when you know.
My family members were getting removed
from the factories or these other places.
Right.
And so that is a challenge, but let's
bring it back a little bit here, right?
Let's talk a little bit about culture.
Like, you know, how are you helping
workplace culture think about ai?
Is that a part of your consulting
or how are you thinking about that?
Angela Liu: It's a portion.
Um, mainly because I, I think about
the business as a whole, right?
So all dimensions of a business,
um, in terms of culture, right?
I think one.
Having a strong culture
of learning, right?
And experimentation is really valuable.
And so what I'm usually trying to
encourage, you know, leaders to think
about and encourage in their own teams,
right, is get your people to just
start experimenting with it, right?
Um, and be intentional, right?
Think about the ideas of
where could you be using this?
Right?
And I think it's really important
to give people a certain level of
exposure to what it can do before
they can start ideating on their own.
Right?
Like you can't, you can't just
give somebody a tool and say, yeah,
see what you can do with this.
Right.
Um.
They're probably not gonna
be sure where to start.
Right?
And they still have metrics and
deliverables they need to meet, so,
you know, how much time are they gonna
actually spend tinkering with it?
Right?
And this was something else that I
felt like that was a theme, uh, at
AI Forward, which is, you know, be
intentional about your experimentation,
your exploration, and your playing
around with these tools, right?
Because that will actually
help you go further.
And that was just not just on
an individual level, but also
on a business level, right?
So there does need to
be a certain amount of.
Training that I think people need to
be given to help them learn about what
is AI as a technology and what are
the possibilities that it can offer.
Right?
Then there's the next level of training,
which is okay, for my role specifically
in the responsibilities I have in
this organization, how could I use it?
Right?
So you, it's, it's not so simple as,
okay, everybody just, just start playing
around with it, and it's not so simple
as, all right, just general AI training.
Same thing for everybody.
No, what a developer needs to know.
In terms of how they can work
with AI is gonna be very different
from, say, working with, um,
somebody who's in marketing, right?
Because they're gonna be working
with these models in very
different, uh, frameworks, right?
The UI is gonna be different, what
they're asking of it, how they, how
they frame their prompts is gonna be
different, all that kind of stuff, right?
So that experimentation
piece, that cultural, that,
that community piece, right.
Share.
Um, I've heard a lot of success
coming out of organizations, right?
That are creating these
sharing communities, right?
Where it's like, okay.
Every single week.
Um, somebody's going to share what they've
been playing around with in ai, right?
What's worked, what didn't
work, things like that.
Right?
And some of them we're learning
from each other and seeing
what AI is capable of, right?
And that accelerates it, but also
helps make positive momentum.
Um, and I think it's also really
important for people to, to
learn and understand what the
limitations of the technology are.
Um, I think a lot of people who
don't understand that, think
that, oh, sky's the limit.
It can do everything.
And it's just like.
Mm. Not really.
Actually.
There are certain things it's good at and
certain things it's really not good at.
You shouldn't think that
it's good at that, you know?
Yeah,
Greg Boone: a hundred percent.
So it's very, uh, polarizing though.
Yeah, right.
You have some camps that believe it can
do any and everything, and then you have
some folks that say, say the same thing.
They always say, oh, it doesn't
know how many Rs and strawberry,
and I'm like, man, if I have that
conversation one more time with someone.
But it's that polarizing
right on that spectrum.
And then also you have a lot of
organizations that historically aren't.
Cultures of innovation.
Mm-hmm.
Right?
AI affects every single person
on the planet, which means it
affects every single company.
There's a lot of companies
out there that innovation is
not how you would define them.
Right.
Which is gonna make it
very, uh, challenging.
Then there's also the, the aspect of,
like everybody talked about, uh, the
MIT uh, uh, report a few months ago,
about 95% of these pilots fail and they
were taking the wrong pieces from that.
They should fail because you should
be experimenting and trying this.
Mm-hmm.
Right.
You know, Tom, you were instrumental
in Walk West's journey on, um,
getting trained and certified.
Right.
What was that journey like and what kind
of, what was the, what do you, what do
you view as like to unlock as to why
Tom Simon: that worked or did not work?
So that journey, you know, as we first
started it, we had to think through how
are we going to roll this out to the
team and, and what makes the most sense?
And as we rolled it out and brought
more people into the fold and gamified
it and did all this other stuff.
It started unlocking a little
more interest and opportunity.
And what we also did in
between is we shared ideas.
We did a couple, like
kind of lunch and learns.
We just sat in a room and talked about
what we learned in AI today, uh, and
kind of, oh, hey, I use this to try this.
You should try that out.
We had team members internally, uh,
some of our content studios saying,
for example, we did this with AI
now and check out how cool this is.
And I think initially we weren't
sure how that was gonna be accepted
or how that was gonna work.
And as it grew.
The conversations in the hallways
and then the conversations in the
room, everything else started turning
more into, Hey, well, I played with
AI to try this, or Did you try that?
Or, Hey, I used AI for this and
it didn't work, but here's why.
Because I think that was another
important element of that conversation.
It wasn't always about how it worked.
It was also about some of
the challenges that created.
One of our, you know, copywriters talked
about how it was great in helping certain
aspects, but that he was constantly
running into m dashes, you know, and
how does that, how do we get past that?
Or there was some hallucinations and,
you know, in a graphic that was created
and, and so we knew that there's
limitations that are still there, but
people using the tools and growing with
those, learn both sides of the coin.
And then in return.
Became more engaging as a process.
And that really point, I mean, I
don't remember how many, you said
how many certifications we got total?
I don't remember at this point.
It's in the hundreds.
It's in the hundreds.
Yeah, it's in the hundreds now, but.
It wasn't just about that anymore.
It was about the practical nature
that people had learned from using
AI and how they could apply it.
And that happened in a
relatively short window of time.
'cause we did it collectively, we made
it safe, we made it very approachable.
We encouraged whatever you
wanted to do, just have fun with
it, you know, figure it out.
And that made it so much better than just
saying, Hey, here's a tool, sit down,
come back to me in a week and tell me
how this is gonna make your job better.
That's, that's, I
Greg Boone: mean, it was, uh.
Again, taking it back to the, the
conference last week, there was a
moment, I remember being on stage and
showing the slide, talking about it.
And they probably got the most
people pulling out their phones
and taking pictures of, of all
the slides I showed, right?
Like they wanted to take a picture
of, because I think people understand.
I was calling the audience
out and I said the same thing
over and over and over again.
Stop telling people to
just be curious with it.
Like if you wanna have an
alert, you wanna see me have
allergic reaction to something?
When I see a leader say, oh, just be
curious and play, I'm like, come on man.
Like at some point you
gotta invest in your team.
Mm-hmm.
Yeah.
Right.
Or this is going to go nowhere.
Mm-hmm.
And I had to invest in myself.
I have over 30 gen I certifications.
But the beauty of the, the competition
and what we did, I don't think I was
involved in any of it truthfully,
other than just being a player.
And it, I wasn't at the, um, the, the
lunch and learns any of the sessions
by design, because what I also realized
as the Cee o of the company, like
if I'm in there, people are gonna.
Act and think differently.
And I wanted to give people that space.
You gotta make it personal, fun, and safe.
People don't feel safe when the CEO
is looking over their shoulder like,
Hmm, that's not how you prompt.
Like, don't do that.
Like, you don't get the
wrong answer with that.
Mm-hmm.
And so you have to figure out,
you know, what is your own path?
But I'm gonna take it back again.
It affects every single
human on the planet.
And so I've seen, I've talked to
companies that are in construction.
I've talked to folks that are in proser.
Everybody's trying to figure this out,
and there is no one size fits all right?
What you may need it for and what
someone else needs it for are may
be, uh, radically different here.
Um, so we've only got a
little bit more time here.
You talk a lot about ethics and dignity.
You know, how are you using ai?
I don't think we've ever talked about
how you yourself are actually using it.
Angela Liu: So I use Claude usually.
Um, part, partly reason.
Okay.
So the reason why I
chose Claude is because.
My, at least my assessment,
you know, in reading about the
various LLM models, right, is that
philanthropic has a stronger commitment
to data security and privacy.
It also has a stronger commitment to
basically making an LLM that doesn't do
harm to people, and I appreciate that.
Right?
They may not necessarily have all the
shiniest bells and whistles that say
chat JPT has come out with, right?
Um, but their models still performs
and competes from a quality of output.
Capability and reasoning perspective.
Right.
Just as good as chat GPT and
then sometimes it's even better
than chat GT's model, right?
I mean Sure.
Chat GT five just came out.
Right.
But I'm sure Anthropics model next
release gonna outperform it again.
Right.
So it's like it's, I'm not, I don't
feel like I'm losing out on the,
uh, the quality of output there.
Right.
It's more just, it's gonna take them
maybe a little catch up to add on
the extra bells and whistles that
chat GPTs thought of already, but.
Greg Boone: I would argue that they
actually are not very far behind and
it points, yeah, they just dropped
clawed skills a week or two ago.
Mm-hmm.
Yep.
So they're actually
ahead in certain areas.
A lot of people say that, uh, they
like clawed 'cause it gets them right.
Like it has a more friendly
interface by design.
Right.
It was.
Always try to break down for folks chat.
GBT is a consumer model, right?
They're big play.
They have 800 million, um, weekly,
uh, active weekly users, right?
Google or Microsoft are
leaning to enterprise plays.
Claude's play was the
ethical choice, right?
So in 23 they said, Hey, we're not gonna
be connected to the internet, right?
Because we want to be safe.
That sounded great until in 24
people got tired of the, oh, my
training run ends in October of 2023.
I can't answer that right, because
the end of the day, people are looking
for answers, right, and not links.
Now, what I would also say is.
That's great marketing and positioning
because their Cee O is the main one
that goes on to TV shows all the
time, saying 50% of all workers are
gonna be replaced in three years.
Yeah.
Like they're all playing this game.
Yep.
Right.
I'm not saying it's now an anthropic.
Again, they did come out to try
to position as the ethical choice,
but they're all within 5% of
the same level of capabilities.
Claw can create some amazing artifacts
if you're trying to vibe code anything.
Most of the, uh.
Vibe coding platforms,
um, sit on Claude, right?
They're using Claude code predominantly.
Now, some of 'em are starting to use chat.
CCP t uh, because of GPT five.
Right.
But even Gemini is an amazing model.
So they all have their kind of
different slivers of kind of view.
Do they have the video generation?
No.
Right.
Or the image generation, like a,
a Chad GT or with their, um, SOA
organized SOA two is amazing.
Or VO three with Google or
no.
Right.
But I always find it interesting
'cause they all, the nano banana
for the image generation for Google.
Which is amazing product.
But all of these, you know, I will
say that Claude has continually
tried to position themselves that
way, but it's a very interesting
dynamic because I continue to watch
the CMO go on stage in places.
Right?
If you want more people to buy
your ai, just say it's gonna
replace 50% of all workers.
Angela Liu: Well, I think, I
think he's also trying to raise
some flags about, you know.
Risks, right?
There are going to be
changes to the workforce.
Just like computers changed things, right?
Like what accountant out there actually
manually goes in and does like the
manual recordings these days, right?
Everybody uses a computer to do
these things these days, right?
Nobody's doing that math by hand
anymore with a calculator, you
know, unless they need a audit.
Something maybe, but you know, like.
With, with Claude, right?
The, one of the things I,
I do with Claude, right?
Um, so one of the re I'll, I'll
just share another fun story.
First time I ever played with an LLM was
actually chat GPT, and I said, tell me
the top 10 models or top five models.
AI models, right?
And it lists out dah, dah, dah, whatever.
It doesn't mention Claude.
And I was just like,
okay, tell me the top 10.
Still no mention of Claude.
In fact, it lists one of its
older models, maybe once or twice.
And I was just like, what the heck?
I was like, so I added into the prompt.
Be objective, right?
Now Claude showed up and I
was like, all right, yeah, I'm
not gonna trust this model.
It's clearly got a bias against Claude.
It's really weird, you know?
And this is, like I said, it was
my first time interacting with
it, so there shouldn't have been
any sort of user history, memory
or whatever stored up, right?
So I was just like, eh, that's fine.
I'll, I'll just work with Claude.
'cause I have a friend who's
an AI researcher and he was
like, you should check this out.
It's really good stuff, right?
So I've been working with Claude.
Um, some of the things that I do with
Claude are like, you know, I, I basically.
I gave it all my, I gave it a lot
of history and context about my
professional experiences because
I actually use it a little bit as
a thought partner on some various
professional kind of activities, right?
So sometimes I'll like maybe draft a
post or something, you know, so I'm
actually coming up with my own thoughts
and stuff, but then I'll be like.
You know, help me cut that down.
Right.
But it at least has context about
sort of what I'm about right.
Sometimes I've had it help me, um,
sort of brainstorm around how could I
position around something or, um, if
I'm gonna do a talk or something, right?
Like, here's some things that
I'm thinking about, right.
And it's like in my, pull some things
from my background or whatever.
Also, um, one of the things I actually
did recently was I was on my way
back from Asheville and I was like.
Getting an email from somebody about
like finding a time and I was like, my
calendar is packed right now and I don't
honestly wanna sit on my phone in the
car and look through my calendar and find
these, what few pockets are left, right?
I was like, man.
This keeps, if this is,
this kinda keeps happening.
So it'd be great if I could
just have Claude just tell me
what are my windows, right?
And I was like, well, we got
the MCP for the calendar.
So I was like, all right.
So I literally spent like
the four hour drive back.
'cause I was a passenger.
I spent this four hour drive.
Important caveat there.
Yeah, there.
And I'm sitting here, I'm like talking
with Claude and I'm like, all right,
I want you to look at my calendar.
I want you to tell me these.
These windows of availability, dah,
dah, dah, dah, whatever stuff, right?
And going back and forth, whatever, right.
And trying to refine its behavior
and its output and stuff like that.
Trying to make sure it has the context
it needs to understand how, I want it to
evaluate what it does see on my calendar.
Because there are things where some
of 'em are out of office, some of them
are buffer times, some of them are
actual work things, you know, some
of them are events, whatever, right?
It's just, there's a lot of things there
and Got it to a point where I, I kind
of describe it as I got it to like 95%.
Right.
There's like this one thing where every
now and then it just, it's like 15
minutes off on something and I'm just
like, all right, that's close enough.
You know?
Like I could probably play around
with it more and get it to a hundred
percent, but it's like, you know,
it's perta rule at this point.
It's not, probably not worth the time.
Right.
Greg Boone: 80 20, yeah.
Toyota 80
Angela Liu: 20 rule.
Yeah.
So it's just like, so yeah.
So, um, my next, one of my, one of
my ideas that I haven't had the time
yet was when Claude Skills came out.
I was just like, oh, I wanna take that.
And I wanna see if it'll do better
with quad skills or if maybe it'll
just perform the same anyway.
Right.
Let's see how quickly it translates.
Greg Boone: The irony is that, uh, we
continually hold technology to a much
higher bar than we hold humans, right?
So Claude is wrong 5% of the time.
It's like, what the f man, like
a serious, it's like hollow.
My own admin who I love and I've
worked with forever, maybe wrong,
10 to 15% of the time, right?
It's like, Hey man, I'm double booked.
Right?
In a very bad way.
Right?
But that's, uh.
I mean, it's the, the nature kind
of where we are, but I do think
we're crossing that chasm, right,
where people are starting to.
Also like take his advice a little bit
more than probably we should or not.
Uh, you know, but the other
irony, we didn't talk about this
earlier, about when we're talking
about responsible use and power.
And I tell people all the time, AI may
be the only thing that we have that
helps us solve the energy crisis, right?
I've heard that
it may be the only thing we have to solve
and create the cure for cancer, right?
So as much as people say, well, I
don't like this and this, I'm like.
Well, do you like this thing worse?
Right?
Because at point, everything in society
becomes a trade off at some point, right?
And you have to think in that way.
Well, you just teed us up for
our favorite part of the show,
which is we call Last chat.
So you're gonna have to
bring out your phone.
Oh gosh.
Like I'm very scared to see what Tom Yeah.
Is gonna have in his last chat and
what he's gonna show says something
Tom Simon: about Greg.
Lemme see.
I
Greg Boone: mean, they probably
was like, Hey, I was, you know,
how can I dress like this dude?
And you probably took a
picture of me, put it in there.
It was a killer costume.
It was really, it was.
He had a, he had a killer,
uh, Halloween costume.
So we're gonna play a little.
Secondly we call last chat.
So Angela, we can, we can start
with you or we wanna start with Tom.
Start with Tom.
Um, and it can be Claude if
we just call it last chat.
Yeah,
Tom Simon: yeah, yeah, yeah.
I, well, I did, so I, I agree
with you by the way, on Claude.
Um, but I did pull chat GBT for this one.
Um, I. Yesterday.
Uh, user journey Personas.
Personas was what I was using it for.
Uh, we have a client that we're
developing a new site for, um, and
we're working through the menu process.
And so I use the, I asked chat GBT
to analyze the current site, it's
mega menus and how it works and
what that user journey might look
like so that we can do two things.
One, identify where there's too much
friction and help us then model.
Or architect how the new menu and
mega menus will work so that there's
a cleaner point path to what the
person is actually looking for.
Right?
People show up now 60% more educated
about you than they did five
years ago, used to be like 30%.
So you wanna give them a clear path.
So this user journey mapping allowed
me to start understanding better so
that we can apply it to the future
state of what their site would be.
Angela Liu: Nice,
Tom Simon: Angela.
Angela Liu: Well.
I'll be honest, my last
chat was, uh, was about me.
I was actually talking with Chloe.
Greg Boone: Whatever
you're comfortable about.
No, it's sharing to the three
viewers that we have for me
Angela Liu: too funny.
Greg Boone: So
Angela Liu: I, uh, no, it was
actually, I was actually brainstorming
with it, um, this weekend on
clarifying a talk overview.
So I was just like, okay, here's what I
wanna talk about, but I need this to fit
in three sec, three, three sentences.
And I'm not, I'm not
exactly the most succinct.
Speaker, you know, I'm actually very
verbose naturally, so, um, and this
is usually how I partner with Jet,
with, with, with Claude actually
is like, help me cut this down.
And without losing like, the
essence of what I'm trying to
say and without losing my voice.
So yeah, it was basically like, all
right, here's what I wanna talk about.
Help me with a, help me get a
good title, gimme some ideas.
Um, all right, cool.
And.
Gimme some, some suggestions on how I
can frame this overview and went through
this iterative process and stuff.
Like, for me, it's always
an iterative process.
I'm like, all right, well, I like some
of these things and I like some of
those things, you know, and this is
like, all right, smash that together.
And then I look at that and I'm like,
Hmm, I don't really like this part.
Let's, what are some options here?
Whatever, like that, right?
So I mean, I just use it as a thought
partner for, for wording because,
um, I can be very particular about
my wording and it'll take me a
while to come up with it on my own.
But I do find that if
I'm working with Claude.
And it's spitting out
some different things.
Sometimes I'm like, all
right, I like that wording.
You know, I, I feel like I can get
there a little bit faster and sometimes
it gives like some alternatives that
I probably wouldn't have come up with.
But one thing that I don't
think any of these AI models
will ever do is make up words.
'cause I definitely make up words.
Greg Boone: See, you're like me, right?
I use it as a thought party.
'cause I need something that
hallucinates less than me, right?
Well, I don't know about that one.
For fingers.
It's like,
all right, this person, at least, at least
this thing stays on track more than I do.
I was having a, um, a moment where I
kept seeing all these I was having, I
was, I was having a very jealous moment
where I kept looking at all these people
with these beautiful keynotes and all
these presentations, and I was trying to
figure out how the hell to make Canva.
You know?
I was like, how do I use Canva
to make my keynote right?
Look like this thing, right?
Versus how I, I, I typically present.
Um, I'm not gonna go through the back
and forth 'cause there's a lot of
back and forth that we were having.
I was starting to get very frustrated
and then at some point I was just
simply like, I was like, how do I just
give camel my colors and fonts to use?
Right?
Like, I didn't understand what was
happening and then it finally figured out.
Later it through our whole dialogue
that, oh, you need to, you want
to use Canva's AI features.
I was trying to use the old kind
of version to do all these things,
and I could not figure it out.
I was like, I'm certain I could
just give this, this thing.
And then I finally scrolled down
on the left hand side of it.
It was like, click on this thing here.
And it was like, Canva, ai.
I was like, oh.
I'm, I'm the dumb ass.
My, my bad.
Classic
Angela Liu: example.
My bad.
I knowing how to use technology, right?
We cool.
Greg Boone: This is
that product I'm doing.
Yeah.
No, but, uh, I appreciate
time with both of you guys.
I enjoyed when we were
in Charlotte, right.
And talking about, and every time I run
into Angela, um, you know, a month ago I
ran into Angela at the conference and I
saw her in the back and I called her out.
Like she made me stop.
I was like, oh, Angela's here.
She's in the back.
Right?
She's, she's seen me.
Rent on stage enough.
And, uh, we used to work here,
uh, work together quite a bit.
And, uh, now I get to work with Tom.
You, he, he didn't replace you, Angela.
Right?
It's just a, it's just
a different, he's cool.
I like him.
Angela Liu: I'd work with him too.
You
Greg Boone: so she implied
that I wasn't cool.
I don't No,
Angela Liu: no, you're cool too, man.
Greg Boone: No, no.
It's all right.
So that's a wrap.
So I appreciate the time today.
Erica Rooney: Thanks for joining
us on AI, voice or victim.
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