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AI allows us to jump capability 
boundaries. 

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All of us have capability 
boundaries, right? 

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AI breaks those boundaries. 
AI allows us individually and 

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organization to jump boundaries.
Today's guest is Greg Shove, CEO

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of Section, and seven times 
startup founder with 30 years in

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tech. 
He's led companies through the 

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e-commerce, cloud, mobile, and 
AI waves. 

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And now specializes in 
transforming organizations for 

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the AI era. 
He was named one of Edelman's AI

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Creators to Know 2025. 
We all as humans have biases. 

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We all have blind spots. 
We all have a set of experience 

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that informs our decisions and 
our judgment. 

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I think it's irresponsible now 
for any executive who works for 

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me. 
If you're making a medium to 

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high stakes decision, I think 
it's irresponsible not to talk 

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to AI. 
What are some of your typical 

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advice or scenarios that leaders
can do now, in order to use AI 

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as a thought partner more? 
Write on the Post-it note "Ask 

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AI". 
Stick it on your monitor. 

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That's what I did for two years.
Move away from Google. 

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I don't care which AI you use, 
but just get out of the habit of

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using Google all the time for 
knowledge search. 

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Many people are kind of like 
afraid about their jobs when 

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thinking about AI. 
The people who are most scared 

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about AI are the people that use
it the least. 

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The people that use AI a lot can
see its value and can see its 

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shortcoming. 
And they don't think they're 

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very worried about losing their 
job. 

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Do not let your employer 
determine your AI future. 

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You own your future. 
You own your AI future. 

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If we keep using AI as much as 
we're using it now, probably 

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more. 
There's four different outcomes 

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and all them will happen. 
Here's what they are. 

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Hello, guys. 
Welcome back to another new 

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episode of the Tech Lead Journal
podcast. 

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Today, I have with me Greg 
Shove. 

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He's the CEO of Section, a 
company that is trying to train 

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people to get up to speed with 
AI and implement that in their 

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companies, enterprise or 
startups. 

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So Greg also is a multi-time 
founders, co-founders. 

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You know, he has successfully 
led seven companies as a CEO. 

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I think mostly or not all are in
AI, I'm not sure. 

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Like maybe later Greg can 
clarify that. 

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So welcome to the show, Greg. 
We're really looking forward to 

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talk to you today about, all 
about AI and how we can make AI 

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rollout successful. 
Thanks, Henry. 

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Yeah, those seven startups, now 
that was seven startups over 30 

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years, so there weren't all AI 
startups. 

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Otherwise, I would've been 
really busy the last two years. 

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Now, I'm currently CEO of one AI
company and chairman, founder 

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and chairman of another AI lab, 
a development lab. 

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And those other startups were 
all tech, uh, startups, uh, 

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starting 30 years ago in 
Toronto, uh, where my first 

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entrepreneurial venture in 
Canada. 

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Greg, I always love to invite my
guests to maybe share a little 

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bit more about you by telling us
any career highlights or turning

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points that you think we all can
learn from that. 

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Oh, yes. 
So many. 

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When you're as old as I am, you 
know, you've got a few pivotal 

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moments in a career. 
I'd say one was when I was in 

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Toronto and I was talking to a 
mentor and about how I wanted to

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be... 
I was in tech already. 

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I'd worked for a digital 
equipment corporation. 

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Doesn't exist anymore, and Sun 
Microsystems does not exist 

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anymore. 
And I was, uh, thinking about a 

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career as an entrepreneur. 
I didn't wanna work for anybody 

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else. 
And I was talking to this mentor

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and he said, listen, what are 
you doing in Toronto? 

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He said there's a grocery store 
in Palo Alto, California called 

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Molly Stones. 
And when you go to Molly Stones 

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on Saturday morning, do your 
grocery shopping, you're gonna 

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meet more people in tech than 
you'll meet all year in Toronto.

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And I thought, oh, that's 
actually pretty good advice. 

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So I got lucky. 
I got into Stanford Business 

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School in Palo Alto, obviously, 
and I stayed afterwards on a 

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student work visa and eventually
converted that, you know, into a

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H1B. 
And that, you know, that was a 

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pivotal moment, meaning I put 
myself as close to the action as

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I could. 
You know, other pivotal moments,

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really, the biggest ones where 
we learn our failures. 

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And so I think that, you know, 
I've had at least a couple 

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companies that I talk about, you
know, not make it and probably 

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more that I don't talk about. 
And so yeah, listen, I think 

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failure is a great teacher. 
And, uh, one of the things I 

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love about Silicon Valley is 
that we don't punish failure. 

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We know that, you know, 
innovation, entrepreneurship, 

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trying to build new products and
services is really hard and it 

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usually does not work. 
But we don't, you know, we don't

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blame people for that. 
We often want to back them 

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again, right? 
We wanna try to help them a 

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second time or fund them a 
second time and so on. 

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So, for me, I'd say just the 
resilience, the pivotal moments 

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are those failures and the 
resilience that you have to 

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develop to survive, you know, 
those failures and take them in 

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stride and not have them knock 
you too much off course. 

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I'd say the other is hiring 
great people. 

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It's, again, it sounds like a 
cliche, but it's hard to hire 

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people and it's particularly 
technologists. 

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But when I've hired great 
engineers, great developers, 

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great product people, my 
businesses have always benefited

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disproportionately by the one 
hire. 

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So really spending time and 
effort to make those one or two 

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critical hires, especially if 
you're building a new product, a

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technology product, you need 
amazing, you know, software 

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engineer and you need an amazing
product, kind of front-end guy, 

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you know, guy or gal to help 
bring that product to life. 

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And so when I really found that 
special person, I try to keep 

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working with them. 
You know, again and again 'cause

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I know how good they are and how
transformative they are. 

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So just being open to really 
having, uh, others are the 

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reason you're successful is how 
I think about it. 

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And, you know, your success is 
really a representation of how 

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well you hired and motivated and
worked with other people who are

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likely more talented than you 
are. 

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Before we continue, I want to 
tell you about our sponsor, 

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Unleash, who helps engineering 
teams ship code faster with less

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risk using feature flags. 
Let's hear what they have to 

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say. 
I am Egil, CEO of Unleash. 

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We believe that AI is having a 
tremendous impact of how 

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software is being delivered. 
It's going faster than ever 

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before. 
And if you look at the latest 

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DORA reports, we already see 
that more than 90% of developers

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are using AI in the day-to-day 
work. 

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AI is getting software to 
production faster, but we're 

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also seeing that the AI is 
impacting the stability of the 

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software in production. 
By the end of the day, what you 

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can say is that AI is getting 
more code to production faster. 

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But at the same time more bugs 
is coming with it. 

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Google is a cautionary tale. 
They talk about how more than 

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30% of their software is written
with AI. 

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At the same time, you'll 
remember this big outage that 

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happened back in June this year 
where a minor update in their 

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backend services took down 
Google Mail, BigQuery, and 

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basically half of internet, 
right? 

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So if you go and read their 
postmortem after this incident. 

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Really, what it says is that if 
this minor change would be 

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flag-protected, the incident 
wouldn't occur in the first 

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place. 
So feature flags are the fastest

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and safest way to roll back code
in production. 

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It always made sense for a human
written code. 

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And with the AI assisted 
development, it makes even more 

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sense. 
So this is what we call 

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FeatureOps. 
So where DevOps is all about 

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getting code into production, 
FeatureOps is all about how code

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operates in production at real 
time. 

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This is why teams that 
Prudential, Wayfair, Visa, and 

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many, many others are using 
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control plane to move fast, stay
safe, and be in control. 

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Learn more how to ship code 
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00:07:45,918 --> 00:07:49,005
getunleash.io. 
And now let's get back to our 

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episode. 
Yeah, I like that last sentence 

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you gave, right? 
Others, the reasons you are 

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successful, right? 
So I think, definitely there's a

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lot to learn about hiring great 
people. 

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And I think you mentioned about 
failures. 

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I wanna dig a little bit on this
area, because I'm always amazed 

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by someone, entrepreneurs who 
have done multiple, you know, 

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companies, right? 
Not all are successful. 

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Maybe some or not, like maybe 
all of, not all of them are 

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like, kind of like failures, 
right? 

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But like, one or two are big 
success. 

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But I think in the points when 
you had that failures, I think 

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that's where your resilience, 
your determination, maybe some 

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kind of your spirit as well, 
right? 

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Because I think here in Asia, we
are more risk averse, so we 

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don't like failures as much as 
possible. 

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But I think from your point of 
view, having done all these, how

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do you cultivate that 
resilience? 

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How do you actually motivate 
yourself to come back to it? 

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Yeah, I think one thing you have
to do, and I learned this the 

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hard way, like I learned this 
later in life, you have to do a 

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really good retro, right, 
retrospective on why you failed.

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Like really learn from your 
failures. 

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'Cause when you really examine 
failure and understand what went

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wrong in the business, let's 
say, or what went wrong in the 

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product, what you'll probably 
realize is it wasn't all your 

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fault. 
One of the reasons I think you 

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can be resilient is you can 
realize that some of this was 

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out of your control or some of 
this was circumstance. 

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Some of this was timing. 
Some of this was, yeah, maybe 

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you didn't make the right 
decisions every time. 

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You don't need to make the right
decisions every time. 

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I think failure is so hard on us
'cause we take it too 

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personally. 
And I think that we tend to 

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wanna move on from our failures 
very quickly. 

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We want to sort of put failures 
in the past as fast as we can. 

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That's human nature. 
And I think that's fine. 

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But I think you don't want to 
miss a step. 

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And the step is examine your 
failures. 

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Like spend a few hours talk to 
the team, really, you know, talk

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to your partner, your founder, 
you know, your wife or husband, 

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whatever, like really 
deconstruct and understand how 

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did you get there, what, you 
know, what went wrong, what, you

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know, what did not go according 
to plan. 

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And again, and when you do that,
I think you realize, oh, I, you 

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probably did a pretty good job, 
but it just wasn't, you know, it

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wasn't meant to be, right? 
The timing, again, the maybe the

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pricing of the product was off 
and that wasn't, you know, that 

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was it. 
Whatever it is, right? 

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And again, I think this idea of 
resilience really comes from 

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don't take failure too 
personally and know that you 

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probably did a pretty good job. 
So you'll probably do a pretty 

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good job the next time. 
You'll likely do a better job 

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the next time 'cause you'll have
that much more experience, 

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right? 
And maybe your timing will be 

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better. 
Listen, one of the reasons I 

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pivoted my business, Section, to
AI is that when I played with 

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ChatGPT Plus on February the 1st
2023, really for a couple hours,

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I really sort of played with, 
uh, with AI, a generative AI 

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chatbot, I just realized how 
amazing it was and how this was 

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going to be a wave. 
And I've never made any money, 

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Henry, unless one of my 
companies has been positioned in

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a wave. 
Like when you confine growth, 

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you don't have to execute 
flawlessly. 

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You have to execute well enough.
And then the growth, right, 

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that's outside of you. 
The growth that is happening, 

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regardless of what you do, you, 
if you're in that growth, you're

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probably gonna be okay and 
you're probably gonna find some 

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success. 
And so, you know, I've only ever

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made money, meaning I've only 
ever been able to sell my 

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companies when I've been able to
grow them. 

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And the growing is because I've 
been positioned in something 

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that is growing. 
So the first was e-commerce, the

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second was cloud, you know, and 
then mobile, and now AI. 

225
00:11:33,255 --> 00:11:37,555
So when I really understood AI, 
personally, I realized, okay, 

226
00:11:37,555 --> 00:11:40,333
this, you know, this is going to
be obviously big. 

227
00:11:40,723 --> 00:11:43,951
I'm not sure how big. 
I'm not sure you know, when, but

228
00:11:43,951 --> 00:11:46,003
it's gonna, it, this feels 
really big. 

229
00:11:46,483 --> 00:11:49,687
And that's why I, as I said, 
that's why I pivoted the 

230
00:11:49,687 --> 00:11:51,243
company. 
And that's worked out great for 

231
00:11:51,243 --> 00:11:53,353
us, right? 
We're growing now at a 100% a 

232
00:11:53,353 --> 00:11:55,743
year. 
You know, and that's just, 

233
00:11:55,743 --> 00:11:57,608
that's 'cause we're executing 
well enough. 

234
00:11:58,528 --> 00:12:01,312
But the growth is there. 
And the inverse of that, the 

235
00:12:01,312 --> 00:12:05,148
opposite of that is if you're in
a small market or you're in a 

236
00:12:05,148 --> 00:12:08,989
market that is declining or is 
maturing, you really have to 

237
00:12:08,989 --> 00:12:12,099
execute flawlessly. 
'Cause you're fighting over, you

238
00:12:12,099 --> 00:12:14,923
know, a slice of pie that is 
shrinking. 

239
00:12:15,013 --> 00:12:17,713
You're fighting over a market 
that is not growing. 

240
00:12:17,713 --> 00:12:20,203
And so it just makes it that 
much harder. 

241
00:12:20,263 --> 00:12:24,062
You really have to execute 
perfectly to get growth when 

242
00:12:24,062 --> 00:12:25,761
you're in a market that's not 
growing. 

243
00:12:25,761 --> 00:12:27,881
So I try to avoid those markets,
you know. 

244
00:12:29,071 --> 00:12:30,529
Right. 
The interesting point you 

245
00:12:30,529 --> 00:12:32,489
mentioned about the timing, 
right, and the waves. 

246
00:12:32,489 --> 00:12:35,459
So having gone through multiple 
waves, right? 

247
00:12:35,459 --> 00:12:38,223
Like what you mentioned, 
e-commerce and internet, and 

248
00:12:38,223 --> 00:12:41,534
then the mobile and then, um, 
now AI, right? 

249
00:12:42,484 --> 00:12:46,647
How, how do you think AI wave is
different than others or is it 

250
00:12:46,647 --> 00:12:48,844
similar? 
Or how much potential do you 

251
00:12:48,844 --> 00:12:53,165
think this wave is gonna be? 
Well, I think we'll know in a 

252
00:12:53,165 --> 00:12:56,009
couple years, first of all, 
meaning we will get, we'll get a

253
00:12:56,009 --> 00:13:00,224
clear answer in a couple years. 
It looks huge, obviously, it's 

254
00:13:00,224 --> 00:13:05,542
also obviously overhyped. 
It looks huge because this is 

255
00:13:05,542 --> 00:13:10,151
technology that I think is 
horizontal, meaning it crosses 

256
00:13:10,151 --> 00:13:14,645
the whole organization. 
It crosses almost any knowledge 

257
00:13:14,645 --> 00:13:18,255
worker job or role. 
That's one reason. 

258
00:13:19,170 --> 00:13:24,290
Second reason is it's highly 
democratizing in terms of AI 

259
00:13:24,290 --> 00:13:29,146
allows us all to be software 
engineers or to be writers or to

260
00:13:29,146 --> 00:13:31,440
be creators or to be data 
analysts, right? 

261
00:13:31,440 --> 00:13:36,699
It is a horizontal technology 
that moves up and moves down the

262
00:13:36,699 --> 00:13:40,045
org chart. 
It opens up access across the 

263
00:13:40,045 --> 00:13:43,896
organization, if you will, 
allows people that are siloed to

264
00:13:43,896 --> 00:13:47,335
get out of a silo, right? 
Think about a management 

265
00:13:47,335 --> 00:13:49,291
consultant. 
Management consultant relies on 

266
00:13:49,291 --> 00:13:52,141
a data analyst, typically. 
Well, now a data analyst can be 

267
00:13:52,141 --> 00:13:54,661
a management consultant with 
GPT-5 deep research, right? 

268
00:13:54,751 --> 00:13:57,241
And frankly, a management 
consultant can be more 

269
00:13:57,241 --> 00:14:00,374
self-sufficient and do their own
data analysis now using GPT-5. 

270
00:14:00,374 --> 00:14:03,578
So, you know, it's just this 
really powerful technology 

271
00:14:03,578 --> 00:14:08,554
'cause it allows us to flex in 
so many different directions as 

272
00:14:08,554 --> 00:14:12,394
individuals and as teams or and,
or companies. 

273
00:14:12,394 --> 00:14:14,044
I think about it, Henry, this 
way. 

274
00:14:14,344 --> 00:14:17,068
It's one of the few 
technologies, maybe the only 

275
00:14:17,068 --> 00:14:21,874
technology that allows us to 
jump capability boundaries. 

276
00:14:22,214 --> 00:14:24,884
All of us have capability 
boundaries, right? 

277
00:14:24,884 --> 00:14:28,536
We're bound, we're constrained 
by our capabilities. 

278
00:14:28,688 --> 00:14:31,190
And that makes sense. 
We, you know, we can't do 

279
00:14:31,190 --> 00:14:33,512
everything well, so we're a 
marketer, or we're a software 

280
00:14:33,512 --> 00:14:35,318
engineer, or we're a product 
leader, right? 

281
00:14:35,318 --> 00:14:38,048
We're typically not a marketer 
and a product leader, right? 

282
00:14:38,348 --> 00:14:41,168
And organizations, companies 
have the same boundaries. 

283
00:14:41,168 --> 00:14:44,244
And that's how we compete. 
We compete in our, within our 

284
00:14:44,244 --> 00:14:46,710
boundaries, right? 
As an organization, as an 

285
00:14:46,710 --> 00:14:50,108
enterprise. 
AI breaks those boundaries. 

286
00:14:50,438 --> 00:14:55,543
AI allows us individually and 
organization to jump boundaries.

287
00:14:55,933 --> 00:15:00,279
So it just, it seems to be 
where, whereas, you know, Slack,

288
00:15:00,279 --> 00:15:02,923
your communication software 
doesn't really do that, right? 

289
00:15:02,923 --> 00:15:05,943
Productivity software makes us 
more productive, but it doesn't 

290
00:15:05,943 --> 00:15:08,803
really allow us to jump 
capabilities and so on. 

291
00:15:08,803 --> 00:15:11,083
Other enterprise software is 
very valuable. 

292
00:15:11,318 --> 00:15:15,483
But this feels like a really 
transformative capability. 

293
00:15:15,583 --> 00:15:16,964
And by the way, I don't think 
it's software. 

294
00:15:17,144 --> 00:15:19,484
It's not really software in a 
traditional sense. 

295
00:15:19,484 --> 00:15:22,806
And I think that one of the 
reasons that large organizations

296
00:15:22,806 --> 00:15:27,740
are struggling with AI and why 
AI is such a superpower to small

297
00:15:27,740 --> 00:15:30,824
organizations and small teams is
because large organizations 

298
00:15:30,824 --> 00:15:33,176
struggle with it. 
And one of the reasons they 

299
00:15:33,176 --> 00:15:36,398
struggle with it, Henry, is they
think this is like another 

300
00:15:36,398 --> 00:15:38,854
software deployment. 
They buy AI. 

301
00:15:39,574 --> 00:15:43,027
You know, an enterprise LLM, 
ChatGPT for enterprise, 

302
00:15:43,027 --> 00:15:45,809
Microsoft Copilot Pro, you know,
Google Gemini. 

303
00:15:45,989 --> 00:15:49,433
They buy it like software and 
they deploy it like software, 

304
00:15:49,433 --> 00:15:52,319
which means they turn it on, 
everybody gets access. 

305
00:15:52,439 --> 00:15:56,536
Maybe they do a training or two.
You know, they do, you know, a 

306
00:15:56,536 --> 00:16:00,259
month of workshops or something.
And then they expect like other 

307
00:16:00,259 --> 00:16:04,636
software like an ERP or a CRM or
a, you know, project management 

308
00:16:04,636 --> 00:16:06,062
software. 
They expect everybody to use it.

309
00:16:06,613 --> 00:16:09,545
But this is not software. 
This is like co-intelligence. 

310
00:16:09,565 --> 00:16:11,635
This is like a cognitive 
service. 

311
00:16:12,565 --> 00:16:15,535
It doesn't behave like software 
'cause it's not reliable, as you

312
00:16:15,535 --> 00:16:17,640
know. 
It hallucinates, you know, which

313
00:16:17,640 --> 00:16:20,665
is Silicon Valley jargon for AI 
makes shit up, right? 

314
00:16:20,665 --> 00:16:23,335
So it, you know, it makes 
mistakes, it makes up stuff. 

315
00:16:23,335 --> 00:16:25,675
It's not reliable. 
It's really powerful. 

316
00:16:26,158 --> 00:16:28,635
But it's also kind of stupid at 
the same time. 

317
00:16:29,199 --> 00:16:32,019
And it scares employee, about 
their jobs. 

318
00:16:32,439 --> 00:16:35,707
You know, there's a lot of 
anxiety about AI when you think 

319
00:16:35,707 --> 00:16:37,839
about particularly larger 
organizations. 

320
00:16:38,199 --> 00:16:41,307
But you go talk to a startup 
CEO, you go talk to a software 

321
00:16:41,307 --> 00:16:45,333
engineer on a small engineer, a 
software team, they can't live 

322
00:16:45,333 --> 00:16:48,602
without it, right? 
They can't imagine, you know, 

323
00:16:48,602 --> 00:16:52,214
working and living without AI, 
especially here in Silicon 

324
00:16:52,214 --> 00:16:55,005
Valley or anywhere that's a 
small team, because small teams 

325
00:16:55,005 --> 00:16:57,860
don't have enough resources and 
small teams are always behind on

326
00:16:57,860 --> 00:17:00,324
the roadmap. 
Small teams have already always 

327
00:17:00,324 --> 00:17:03,354
have too many tickets, you know,
to clear, whatever it is. 

328
00:17:03,354 --> 00:17:07,001
And so they want the assist. 
You go to a big company, that's 

329
00:17:07,001 --> 00:17:09,140
not their world. 
Their world is about protecting 

330
00:17:09,140 --> 00:17:11,823
their job and kind of doing 
things the same way they've 

331
00:17:11,823 --> 00:17:14,688
always been done, which is why 
it's tough for bigger companies 

332
00:17:14,688 --> 00:17:17,982
to deploy AI. 
We really have to break down 

333
00:17:17,982 --> 00:17:21,550
this into small teams and get 
small teams to be AI-enabled 

334
00:17:21,550 --> 00:17:25,377
like a startup would. 
Like today you would not start a

335
00:17:25,377 --> 00:17:29,046
company and not think about, you
know, you're gonna turn on AWS, 

336
00:17:29,046 --> 00:17:32,328
you're gonna turn on email, turn
on, you know, document sharing, 

337
00:17:32,328 --> 00:17:34,626
and you're gonna turn on AI, and
you're gonna start your company.

338
00:17:35,445 --> 00:17:37,451
I think there are a lot of great
points that you mentioned just 

339
00:17:37,451 --> 00:17:39,235
now. 
I like in particular, you 

340
00:17:39,235 --> 00:17:42,020
mentioned about this capability 
boundaries that we can break 

341
00:17:42,020 --> 00:17:45,569
through simply by using AI. 
And I like also the nature of 

342
00:17:45,569 --> 00:17:47,675
AI, right? 
It's like using natural language

343
00:17:47,675 --> 00:17:49,915
for you to actually interface 
with it. 

344
00:17:50,409 --> 00:17:53,440
Unlike other software probably 
is more technical, slightly more

345
00:17:53,440 --> 00:17:56,399
clunky for some software, right?
So I think this feels a little 

346
00:17:56,399 --> 00:17:59,185
bit different. 
And your company as well, right?

347
00:17:59,185 --> 00:18:03,115
Section was not originally doing
stuff on AI, right? 

348
00:18:03,115 --> 00:18:05,715
If I'm not mistaken, you're 
doing more like, you know, 

349
00:18:05,715 --> 00:18:08,089
executive or education, you 
know, online kind of training, 

350
00:18:08,089 --> 00:18:11,059
those kind of stuff. 
And then you pivoted to doing 

351
00:18:11,059 --> 00:18:14,210
full AI. 
So tell us, you know, the pivot 

352
00:18:14,210 --> 00:18:17,973
experience that you did, right? 
First of all like what was the 

353
00:18:17,973 --> 00:18:20,667
rationale behind it? 
And secondly how do you make 

354
00:18:20,667 --> 00:18:23,980
that pivot actually successful? 
This comes to the learnings that

355
00:18:23,980 --> 00:18:27,572
maybe other organizations can 
also do in terms of, you know, 

356
00:18:27,572 --> 00:18:29,222
making them implementing AI 
successfully. 

357
00:18:29,759 --> 00:18:32,902
Sure. 
Well, as we talked about, the 

358
00:18:32,902 --> 00:18:36,732
pivot was inspired by my 
realization that this was the 

359
00:18:36,732 --> 00:18:38,761
next wave, right? 
This is something that would 

360
00:18:38,761 --> 00:18:40,921
provide growth. 
Also, you're right. 

361
00:18:40,921 --> 00:18:44,791
The original business of Section
was management education, online

362
00:18:44,791 --> 00:18:48,760
management training. 
'Cause we feel, we felt and we 

363
00:18:48,760 --> 00:18:51,470
still feel that management 
training, teaching people 

364
00:18:51,470 --> 00:18:55,631
strategy, teaching people better
management techniques and so on,

365
00:18:55,631 --> 00:18:58,511
they, those are accelerants. 
They help people's career. 

366
00:18:58,511 --> 00:19:01,051
They accelerate careers. 
Great, you know, business 

367
00:19:01,051 --> 00:19:03,501
schools, right? 
MBAs, executive education from 

368
00:19:03,501 --> 00:19:06,875
business schools. 
You know, those, partly it's the

369
00:19:06,875 --> 00:19:09,801
credential, but partly it's the 
actual knowledge, right? 

370
00:19:09,821 --> 00:19:12,551
The upskilling that you get, 
they are career accelerants. 

371
00:19:12,551 --> 00:19:16,625
When I used AI for the first 
time, my realization was this is

372
00:19:16,625 --> 00:19:20,141
the new accelerant. 
That in the short term, meaning 

373
00:19:20,141 --> 00:19:25,472
the next five years, knowing how
to use AI would be a personal 

374
00:19:25,472 --> 00:19:27,041
career or professional 
accelerant. 

375
00:19:27,491 --> 00:19:29,957
And I realized, okay, management
training is an accelerant, but 

376
00:19:29,957 --> 00:19:32,861
this is the new accelerant and 
no one knows how to do it. 

377
00:19:32,861 --> 00:19:37,653
So if I go early and fast, I can
be, you know, a school that 

378
00:19:37,653 --> 00:19:41,717
teaches AI basically and provide
that acceleration, you know, to 

379
00:19:41,717 --> 00:19:44,422
millions of others. 
Cause the world always, it 

380
00:19:44,422 --> 00:19:46,487
always takes a while to adopt 
these technologies. 

381
00:19:46,487 --> 00:19:49,117
It does not happen overnight. 
It's happening very quickly with

382
00:19:49,117 --> 00:19:53,213
AI, I would admit, you know, a 
billion users by the end of this

383
00:19:53,213 --> 00:19:55,787
year for ChatGPT is kind of an 
amazing number. 

384
00:19:56,117 --> 00:19:58,947
More than 10% of humanity. 
It is happening quickly, but 

385
00:19:58,947 --> 00:20:03,322
still a lot of people need to be
sort of supported, upskilled. 

386
00:20:03,660 --> 00:20:07,356
And frankly, the anxie- their 
anxiety has to be lowered, uh, 

387
00:20:07,356 --> 00:20:10,816
to use AI successfully. 
So that's really the inspiration

388
00:20:10,816 --> 00:20:12,975
for the pivot. 
The lesson about pivots, and 

389
00:20:12,975 --> 00:20:15,467
I've done a lot of pivots. 
'Cause when you do seven 

390
00:20:15,467 --> 00:20:18,207
startups, you know, you end up 
doing a lot of pivots. 

391
00:20:18,379 --> 00:20:22,759
Too many, maybe. 
But, um, the only way to pivot 

392
00:20:22,759 --> 00:20:27,973
is to be all in. 
The only way to pivot, in my 

393
00:20:27,973 --> 00:20:31,914
opinion, as a startup, you can 
test, you can experiment into 

394
00:20:31,914 --> 00:20:34,789
it. 
Meaning you need to develop the 

395
00:20:34,789 --> 00:20:38,669
confidence and the evidence that
your pivot is the right 

396
00:20:38,669 --> 00:20:41,350
decision, right? 
It's, it is the right direction 

397
00:20:41,350 --> 00:20:43,709
for the company. 
But once you've made that 

398
00:20:43,709 --> 00:20:47,313
decision, so you can be cautious
to a point to get to the 

399
00:20:47,313 --> 00:20:50,683
decision, once you get to the 
decision, you personally have to

400
00:20:50,683 --> 00:20:53,499
lead from the front and you 
can't go back. 

401
00:20:54,129 --> 00:20:57,064
You might keep, and we had to do
this at Section, and I've had to

402
00:20:57,064 --> 00:21:00,274
do it in my previous companies, 
in my previous pivots. 

403
00:21:00,544 --> 00:21:04,144
You might have to keep the old 
business 'cause you need the 

404
00:21:04,144 --> 00:21:06,614
revenue, right? 
And you might want those 

405
00:21:06,614 --> 00:21:10,834
customers as well for the pivot.
So you might keep what you have.

406
00:21:11,134 --> 00:21:15,166
So this is hard for teams to 
keep what they have and then to 

407
00:21:15,166 --> 00:21:17,458
pivot. 
But the pivot, my point about 

408
00:21:17,458 --> 00:21:20,464
the pivot is you're committed. 
You're not gonna go back. 

409
00:21:20,973 --> 00:21:24,823
You're gonna harvest or wind 
down the old business if you 

410
00:21:24,823 --> 00:21:27,373
have one, right? 
And we did at Section. 

411
00:21:27,373 --> 00:21:31,023
We had a very good management 
training business and we wound 

412
00:21:31,023 --> 00:21:35,054
it down over the last two years.
We let it atrophy, and then kind

413
00:21:35,054 --> 00:21:37,887
of closed it down. 
And then, but you've gotta be 

414
00:21:37,887 --> 00:21:40,516
committed. 
So once I was all in AI, there 

415
00:21:40,516 --> 00:21:43,688
was no choice. 
And the rest of the organization

416
00:21:43,688 --> 00:21:47,270
had to follow my lead, otherwise
they couldn't work at Section. 

417
00:21:47,630 --> 00:21:50,960
And I had skeptics for sure 
inside the organization. 

418
00:21:50,960 --> 00:21:53,630
You always do with a pivot. 
You always do. 

419
00:21:54,612 --> 00:21:58,442
And you know, that's your job as
a leader is to win them over or 

420
00:21:58,442 --> 00:22:02,967
ask them to leave. 
You can't afford to have one 

421
00:22:02,967 --> 00:22:07,549
person really, you know, on the 
team that after, you know, a 

422
00:22:07,549 --> 00:22:10,000
month or two or three months 
depends how big your company is,

423
00:22:10,000 --> 00:22:13,996
but you can't carry too many 
doubters or skeptics, you know, 

424
00:22:13,996 --> 00:22:16,540
along for the ride. 
It won't work. 

425
00:22:17,065 --> 00:22:18,482
Cause people are gonna be 
anxious. 

426
00:22:18,632 --> 00:22:20,458
People are gonna be anxious. 
They're gonna be scared about 

427
00:22:20,458 --> 00:22:21,872
the pivot. 
You know, will it work? 

428
00:22:22,458 --> 00:22:26,822
Is this a crazy idea for my CEO?
'Cause he woke up or she woke up

429
00:22:26,822 --> 00:22:29,840
one morning, you know, with this
crazy idea or is it real? 

430
00:22:29,900 --> 00:22:33,550
Like is this a pivot that you 
know that we're gonna do? 

431
00:22:33,590 --> 00:22:36,870
And so yeah, commitment is 
everything to me for pivots. 

432
00:22:37,781 --> 00:22:40,494
Yeah, personally, I've been 
through some pivots as well. 

433
00:22:40,524 --> 00:22:43,601
So always an uncertain time, 
especially for, you know, 

434
00:22:43,601 --> 00:22:46,213
employees, right, who were 
probably not consulted or 

435
00:22:46,213 --> 00:22:49,598
discussed, uh, in so many of 
those, uh, meetings where you 

436
00:22:49,598 --> 00:22:51,192
wanted to decide to pivot, 
right? 

437
00:22:51,192 --> 00:22:53,786
So thanks for sharing that. 
To be all in, right? 

438
00:22:53,786 --> 00:22:56,936
So once you decided you wanna 
commit to that, to be all in. 

439
00:22:57,432 --> 00:23:00,988
So you mentioned about skeptics.
I think even though many people 

440
00:23:00,988 --> 00:23:03,975
are raving about AI, you know, 
how great it could be. 

441
00:23:04,316 --> 00:23:06,836
But there are also some 
skeptics, right, uh, out there 

442
00:23:06,836 --> 00:23:10,290
that people who think that, oh, 
AI can still hallucinate, can 

443
00:23:10,290 --> 00:23:14,140
make wrong decision, you know, 
make catastrophic, uh, result as

444
00:23:14,140 --> 00:23:16,379
well. 
Uh, we've seen it sometimes in 

445
00:23:16,379 --> 00:23:18,220
the news or over Twitter, social
media. 

446
00:23:18,708 --> 00:23:21,644
And you, yourself personally 
have gone through this 

447
00:23:21,644 --> 00:23:24,940
realization that AI can be a 
thought partner for yourself. 

448
00:23:25,300 --> 00:23:27,910
And in, I think in one of your 
quote you mentioned, AI is like 

449
00:23:27,910 --> 00:23:31,230
your testosterone to the brain. 
I kind of like that term. 

450
00:23:31,830 --> 00:23:36,762
So maybe to remove some doubts 
that people have sub, from these

451
00:23:36,762 --> 00:23:39,952
skeptics, right? 
So tell us why you think AI is 

452
00:23:39,952 --> 00:23:42,830
such a good thing as a thought 
partner and something that 

453
00:23:42,830 --> 00:23:46,262
everyone should, you know, try 
to embed in their daily life. 

454
00:23:47,239 --> 00:23:48,421
Yeah. 
Well first of all, I wanna 

455
00:23:48,421 --> 00:23:50,182
answer the kind of the first 
part of your question. 

456
00:23:50,422 --> 00:23:52,627
I don't think we should 
necessarily be skeptical about 

457
00:23:52,627 --> 00:23:55,872
AI, but we should be sort of 
clear-eyed. 

458
00:23:55,872 --> 00:23:57,712
We should not drink all the 
Kool-Aid. 

459
00:23:57,802 --> 00:24:00,442
You know, there is a lot of hype
coming from Silicon Valley. 

460
00:24:00,922 --> 00:24:05,265
You know, this idea of we're 
gonna build AGI or SSI, super 

461
00:24:05,265 --> 00:24:08,145
intelligence, right? 
And really there, that's a story

462
00:24:08,145 --> 00:24:10,077
that they're using to raise 
capital. 

463
00:24:10,347 --> 00:24:13,653
Huge amounts of capital, right? 
OpenAI has just announced that 

464
00:24:13,653 --> 00:24:17,590
they will lose over a hundred 
billion dollars by 2030. 

465
00:24:17,590 --> 00:24:21,218
It's a just unheard of amounts 
of capital and losses for a 

466
00:24:21,218 --> 00:24:23,470
single company, single private 
company. 

467
00:24:23,470 --> 00:24:27,670
So, but listen, AI will have a 
lot of unintended consequences. 

468
00:24:28,165 --> 00:24:31,355
AI will, uh, continue to 
hallucinate for at least for 

469
00:24:31,355 --> 00:24:34,430
another year or two, as far as 
we know, maybe forever. 

470
00:24:35,124 --> 00:24:39,151
AI will not handle every 
personal interaction 

471
00:24:39,151 --> 00:24:42,898
successfully. 
So we will see more lawsuits 

472
00:24:42,898 --> 00:24:46,992
related to, you know, self-harm 
and suicide, uh, when people 

473
00:24:46,992 --> 00:24:50,282
using AI as a therapist and so 
on and so on and so on. 

474
00:24:50,282 --> 00:24:54,113
We'll see lawsuits probably from
parents about how dumb their 

475
00:24:54,113 --> 00:24:57,472
kids are because, you know, they
went to, they didn't go to 

476
00:24:57,472 --> 00:25:00,563
school, they just used AI. 
We'll see all kinds of crazy, 

477
00:25:00,563 --> 00:25:03,479
crazy sort of, uh, lawsuits and 
consequences of AI. 

478
00:25:03,509 --> 00:25:06,992
So I think we need to be, as 
leaders, you know, smart about 

479
00:25:06,992 --> 00:25:09,053
it. 
We should be optimistic, but we 

480
00:25:09,053 --> 00:25:11,957
should also be pragmatic. 
And we shouldn't just think it's

481
00:25:11,957 --> 00:25:15,035
all gonna be great. 
Listen, energy prices are going 

482
00:25:15,035 --> 00:25:18,648
up in certain parts of the 
United States, because of the 

483
00:25:18,648 --> 00:25:22,489
demand that data centers are 
pulling from the energy grid. 

484
00:25:22,489 --> 00:25:27,000
So there's a real consequences 
here to our adoption of AI. 

485
00:25:27,000 --> 00:25:29,856
So I think we should be 
pragmatic and we should be 

486
00:25:29,856 --> 00:25:35,593
balanced in our view of AI. 
What I do think is AI has 

487
00:25:35,593 --> 00:25:38,820
superpowers. 
And when properly used, when we 

488
00:25:38,820 --> 00:25:43,920
drive AI, when we steer AI, it 
can be really valuable. 

489
00:25:44,302 --> 00:25:47,115
And you're right. 
One of my favorite use cases is 

490
00:25:47,115 --> 00:25:50,720
AI as a thought partner. 
I think it's irresponsible now 

491
00:25:50,720 --> 00:25:55,821
for any executive who works for 
me, any executive, if you're 

492
00:25:55,821 --> 00:26:01,056
making a medium to high stakes 
decision, you know, about, uh, 

493
00:26:01,056 --> 00:26:06,105
hiring someone or a product 
roadmap or a pivot or a board 

494
00:26:06,105 --> 00:26:08,535
meeting, anything, any medium to
high stakes decision. 

495
00:26:08,535 --> 00:26:12,465
And at home, parenting question 
or a health question. 

496
00:26:12,735 --> 00:26:16,205
I think it's irresponsible not 
to talk to AI. 

497
00:26:16,925 --> 00:26:20,215
I'm not saying do what AI says. 
I'm not saying that. 

498
00:26:20,765 --> 00:26:23,850
I'm saying that we all as humans
have biases. 

499
00:26:25,110 --> 00:26:29,863
We all have blind spots. 
We all have a set of experience 

500
00:26:29,863 --> 00:26:32,040
that informs our decisions and 
our judgment. 

501
00:26:32,040 --> 00:26:34,560
But the, those set of 
experiences are quite narrow 

502
00:26:34,560 --> 00:26:37,200
when you think about all of 
human experience. 

503
00:26:37,686 --> 00:26:41,815
We have decision frameworks that
we rely on just because they're 

504
00:26:41,815 --> 00:26:44,070
the ones that work for us in the
past. 

505
00:26:44,100 --> 00:26:46,719
But we don't use all the 
decision frameworks available to

506
00:26:46,719 --> 00:26:48,836
us. 
We use the ones that we know how

507
00:26:48,836 --> 00:26:51,790
to use, right? 
So AI has none of that, meaning 

508
00:26:51,790 --> 00:26:56,275
AI does not have blind spots. 
AI if properly steered or 

509
00:26:56,275 --> 00:26:59,405
managed, AI can use any decision
framework. 

510
00:26:59,851 --> 00:27:03,533
AI can cross boundaries, as I 
already talked about, capability

511
00:27:03,533 --> 00:27:05,581
boundaries. 
AI crosses countries. 

512
00:27:05,611 --> 00:27:07,621
AI crosses languages and 
cultures. 

513
00:27:07,892 --> 00:27:11,071
AI crosses industries. 
AI crosses functions. 

514
00:27:11,951 --> 00:27:15,140
AI can be a personal coach and a
business coach at the same time,

515
00:27:15,140 --> 00:27:18,589
and so on. 
So I think that for any decision

516
00:27:18,589 --> 00:27:22,821
that has high stakes and that 
could be, again, as I said, what

517
00:27:22,821 --> 00:27:26,288
to do with your kid who has 
these symptoms, you know, and a 

518
00:27:26,288 --> 00:27:30,261
temperature of 102 degrees, uh, 
as a parent or you know, how to 

519
00:27:30,261 --> 00:27:33,036
prepare for a board meeting as 
an entrepreneur. 

520
00:27:33,096 --> 00:27:37,160
I think you should be spending 
10, 5, 10, 15, 20, 30 minutes 

521
00:27:37,160 --> 00:27:40,640
talking to AI about it and 
uploading the business plan to 

522
00:27:40,640 --> 00:27:44,806
AI or the board deck or the 
photo of the, of your kid in 

523
00:27:44,806 --> 00:27:47,686
terms of, you know, the symptoms
or whatever it is, right? 

524
00:27:47,814 --> 00:27:51,758
The photo of the, of the house 
you, I don't know, you might 

525
00:27:51,758 --> 00:27:55,159
wanna buy. 
Whatever it is, talk to AI 

526
00:27:55,159 --> 00:27:57,584
about. 
AI is a very effective thought 

527
00:27:57,584 --> 00:27:59,768
partner. 
Again, you're not gonna do what 

528
00:27:59,768 --> 00:28:04,124
AI tells you, but my guess is 
you'll be able to improve or 

529
00:28:04,124 --> 00:28:08,327
optimize many decisions. 
And at the very least, you'll be

530
00:28:08,327 --> 00:28:10,989
better prepared to have a 
conversation with someone else 

531
00:28:10,989 --> 00:28:13,887
about that decision. 
So that might be with a doctor, 

532
00:28:13,887 --> 00:28:16,783
that might be with a board 
member, that might be with a 

533
00:28:16,783 --> 00:28:19,703
partner or a co-founder if 
you're having a disagreement or 

534
00:28:19,703 --> 00:28:23,721
a difficult decision about the 
product roadmap or about, you 

535
00:28:23,721 --> 00:28:26,330
know, a customer. 
You know, whatever it is. 

536
00:28:26,620 --> 00:28:28,620
So yeah, I think it's the 
universal use case. 

537
00:28:28,620 --> 00:28:30,060
And by the way, the data shows 
this. 

538
00:28:30,352 --> 00:28:35,331
This, you know, this idea of AI 
as a therapist, AI as a coach or

539
00:28:35,331 --> 00:28:38,209
companion. 
Those are emerging as the, some 

540
00:28:38,209 --> 00:28:42,213
of the top use cases for AI. 
I think it's AI superpower, 

541
00:28:42,213 --> 00:28:44,797
actually, Henry. 
I think it's the surprise sort 

542
00:28:44,797 --> 00:28:49,237
of hit, if you will, for AI. 
This use as a personal coach or 

543
00:28:49,237 --> 00:28:51,007
a therapist or a thought 
partner. 

544
00:28:51,445 --> 00:28:54,979
Uh, it's someone to talk to 
who's pretty smart and will 

545
00:28:54,979 --> 00:28:57,592
listen to us. 
'Cause AIs are trained right to 

546
00:28:57,592 --> 00:29:00,540
listen to us. 
AIs are trained probably to be 

547
00:29:00,540 --> 00:29:02,685
too flattering. 
And that's why they hallucinate,

548
00:29:02,685 --> 00:29:05,643
'cause they're trained to give 
us an answer, kind of no matter 

549
00:29:05,643 --> 00:29:07,431
what. 
So we have to learn to use AI 

550
00:29:07,431 --> 00:29:10,347
the right way. 
And we have to know that AI is 

551
00:29:10,347 --> 00:29:13,592
really sort of playing us. 
AI wants to be liked by us. 

552
00:29:14,002 --> 00:29:17,876
So we have to be aware of that. 
You know, I'm tired of how many 

553
00:29:17,876 --> 00:29:20,243
times AI has told me how smart I
am. 

554
00:29:20,273 --> 00:29:23,055
You know, I'm not that smart, 
but AI just keeps telling me I 

555
00:29:23,055 --> 00:29:25,037
am, right? 
So, you know, again, that's why 

556
00:29:25,037 --> 00:29:28,297
we have to be smart about this. 
And we have to have a balanced 

557
00:29:28,297 --> 00:29:31,331
perspective on it when, you 
know, we know that AI behaves a 

558
00:29:31,331 --> 00:29:34,488
certain way based on how it is 
built, how it's designed. 

559
00:29:34,885 --> 00:29:38,084
But again, very useful. 
It's a use case that I'm not 

560
00:29:38,084 --> 00:29:39,652
sure people want to pay that 
much for. 

561
00:29:39,772 --> 00:29:43,342
I don't think companies want to 
pay for AI for us to use it as a

562
00:29:43,342 --> 00:29:45,340
thought partner, right? 
I think companies want to pay 

563
00:29:45,340 --> 00:29:48,108
for AI to make us more 
productive, so we write more 

564
00:29:48,108 --> 00:29:51,196
lines of code, you know. 
Or we, uh, create more marketing

565
00:29:51,196 --> 00:29:55,093
briefs or whatever it is, right?
But yeah, I think it's a great 

566
00:29:55,093 --> 00:29:57,773
use case and I think everyone 
should be using AI, as I said, 

567
00:29:57,773 --> 00:29:59,707
as a thought party. 
You should be talking to AI. 

568
00:29:59,947 --> 00:30:02,405
That's a great way to interact 
with AI. 

569
00:30:02,435 --> 00:30:04,355
When you think about AI as a 
thought partner. 

570
00:30:04,595 --> 00:30:07,168
You know, do it while you're 
commuting or you're in your car 

571
00:30:07,168 --> 00:30:09,062
or when you've got some 
downtime, right? 

572
00:30:09,062 --> 00:30:13,693
Just get your phone out and use,
um, you know, one of the AI apps

573
00:30:13,693 --> 00:30:17,024
on your phone. 
Advanced Voice Mode in GPT, it's

574
00:30:17,024 --> 00:30:20,237
just fantastic. 
Yeah, so I think the key word 

575
00:30:20,237 --> 00:30:21,620
here is a thought partner, 
right? 

576
00:30:21,620 --> 00:30:25,186
So you're kind of like not 
outsourcing fully, you know, the

577
00:30:25,186 --> 00:30:28,146
answer, the decision and in the 
end, you kind of like have to be

578
00:30:28,146 --> 00:30:29,990
the one accountable making the 
decision. 

579
00:30:30,260 --> 00:30:34,579
And I personally also have, you 
know, used AI in so numerous 

580
00:30:34,579 --> 00:30:37,697
scenarios, uh, for learning, 
explore ideas and all that. 

581
00:30:37,697 --> 00:30:40,757
I think it's great to kind of 
like open up your perspectives. 

582
00:30:40,967 --> 00:30:43,827
And sometimes it could be just 
curiosity on a certain topics, 

583
00:30:43,827 --> 00:30:46,175
right? 
And from there maybe you can 

584
00:30:46,175 --> 00:30:49,143
learn something new and, you 
know, improve the ideas that you

585
00:30:49,143 --> 00:30:51,171
have. 
And you mentioned in your 

586
00:30:51,171 --> 00:30:53,658
companies, um, you said that it 
will be irresponsible for 

587
00:30:53,658 --> 00:30:55,608
leaders or the executives not to
use AI. 

588
00:30:55,972 --> 00:30:58,590
I'm pretty sure in most of the 
companies, apart from using 

589
00:30:58,590 --> 00:31:02,369
maybe just a simple ChatGPT and 
all that, maybe many leaders are

590
00:31:02,369 --> 00:31:06,105
still not, how should I say, 
natural in using AI in their 

591
00:31:06,105 --> 00:31:08,860
day-to-day work. 
Maybe what are some of your 

592
00:31:08,860 --> 00:31:12,850
typical advice or scenarios that
leaders can do now in order to 

593
00:31:12,850 --> 00:31:16,246
use AI as a thought partner more
and improve their decision 

594
00:31:16,246 --> 00:31:19,300
making or improve their, you 
know, performance as a leader? 

595
00:31:19,917 --> 00:31:21,287
Yeah, that's a... 
Sure. 

596
00:31:21,287 --> 00:31:23,371
I think it's easy to get 
started. 

597
00:31:23,371 --> 00:31:27,816
First of all, get the app. 
Like I'm surprised how many 

598
00:31:27,816 --> 00:31:30,915
executives don't have a premium 
account, first of all. 

599
00:31:31,980 --> 00:31:34,980
So they're using, you know, free
AI is pretty good, right? 

600
00:31:34,980 --> 00:31:39,285
GPT-5 freemium is or Claude 
or... they're all pretty good. 

601
00:31:39,285 --> 00:31:41,655
They're free products, but pay 
the extra 20 bucks. 

602
00:31:41,655 --> 00:31:45,094
It's only 20 bucks a month. 
Get the additional features, you

603
00:31:45,094 --> 00:31:47,155
know. 
Get the mobile app, get it on 

604
00:31:47,155 --> 00:31:49,229
your phone. 
In fact, what I did recently 

605
00:31:49,229 --> 00:31:54,023
actually, Henry, is I put the 
GPT-5 widget on my iPhone. 

606
00:31:54,023 --> 00:31:58,625
So now it's occupying a good 
amount of my home screen, of my 

607
00:31:58,625 --> 00:32:02,303
iPhone is the GPT widget, which 
is just more prominent, you 

608
00:32:02,303 --> 00:32:05,483
know, on my home screen. 
I just use GPT more. 

609
00:32:05,723 --> 00:32:09,285
So that's the first thing. 
Second thing is move away from 

610
00:32:09,285 --> 00:32:11,333
Google. 
I don't care which AI you use. 

611
00:32:11,333 --> 00:32:13,313
You can use Claude, you can use 
Gemini. 

612
00:32:13,553 --> 00:32:16,993
But just get out of the habit of
using Google all the time for 

613
00:32:16,993 --> 00:32:19,383
certain searches. 
What I call functional search, 

614
00:32:19,383 --> 00:32:22,331
of course, use Google. 
You know, when is this 

615
00:32:22,331 --> 00:32:24,628
restaurant open? 
Or, you know, the, those kinds 

616
00:32:24,628 --> 00:32:26,153
of searches, very functional 
searches. 

617
00:32:26,153 --> 00:32:30,095
Google's probably still the 
fastest and best source of 

618
00:32:30,095 --> 00:32:32,993
truth. 
But for a knowledge search, stop

619
00:32:32,993 --> 00:32:35,579
using Google and begin to use 
AI. 

620
00:32:35,609 --> 00:32:37,529
And you'll notice the 
differences, good and bad. 

621
00:32:37,529 --> 00:32:39,659
It's not always good. 
I'm not saying it's gonna be 

622
00:32:39,659 --> 00:32:42,149
better all the time, but again, 
change some habits, right? 

623
00:32:42,569 --> 00:32:45,534
Third thing, very lo-fi, very 
cheap. 

624
00:32:45,749 --> 00:32:48,519
And this only costs like, you 
know, a few cents. 

625
00:32:48,739 --> 00:32:53,789
Get a post-it note, write on the
post-it note, "Ask AI". 

626
00:32:54,689 --> 00:32:59,489
Stick it on your monitor. 
Stick it on your monitor. 

627
00:33:01,036 --> 00:33:05,073
That's what I did for two years.
For two years, I had, you know, 

628
00:33:05,073 --> 00:33:08,458
none of us likely in this 
audience, your audience are AI 

629
00:33:08,458 --> 00:33:10,438
native. 
AI native kids are in school 

630
00:33:10,438 --> 00:33:12,376
right now, right? 
They're in middle school. 

631
00:33:12,707 --> 00:33:15,356
Maybe they're in high school. 
Some the kids graduating from 

632
00:33:15,356 --> 00:33:16,876
college right now aren't AI 
native. 

633
00:33:16,876 --> 00:33:19,346
They learned AI at school so 
they could cheat and get their 

634
00:33:19,346 --> 00:33:21,541
homework done faster and submit 
more assignments. 

635
00:33:21,917 --> 00:33:24,386
But, you know, it's really the 
kids in middle school today that

636
00:33:24,386 --> 00:33:26,746
are, will be the first AI native
generation. 

637
00:33:26,746 --> 00:33:30,306
The rest of us grew up in a 
world dominated by browsers and 

638
00:33:30,306 --> 00:33:31,879
dominated by Google and search, 
right? 

639
00:33:31,879 --> 00:33:33,859
And this idea of a search 
results page. 

640
00:33:34,419 --> 00:33:37,599
And so, uh, we have to really 
remind ourselves to use AI. 

641
00:33:37,599 --> 00:33:39,169
So I used a post-it note for two
years. 

642
00:33:40,079 --> 00:33:43,794
In January, Henry, I bought a 
monitor and I call it my AI 

643
00:33:43,794 --> 00:33:45,948
monitor. 
So it's on my desk in my 

644
00:33:45,948 --> 00:33:47,810
workspace. 
It's right next to my main 

645
00:33:47,810 --> 00:33:50,208
monitor. 
It's on the vertical horizon, so

646
00:33:50,208 --> 00:33:53,700
it's vertically oriented. 
And I have one browser open with

647
00:33:53,700 --> 00:33:56,286
three tabs. 
And every morning I turn that 

648
00:33:56,286 --> 00:33:59,670
monitor on and I've got Claude, 
uh, Anthropic Claude, Perplexity

649
00:33:59,670 --> 00:34:02,844
and ChatGPT. 
That's all I have in that, on 

650
00:34:02,844 --> 00:34:04,634
that monitor. 
And so I can see it all the 

651
00:34:04,634 --> 00:34:06,389
time. 
I, you know, it's right, just to

652
00:34:06,389 --> 00:34:09,007
the right of my main monitor, 
it's in my line of sight. 

653
00:34:09,284 --> 00:34:12,097
And every morning I can see 
Claude and Claude says, good 

654
00:34:12,097 --> 00:34:14,433
morning captain. 
'Cause Captain is what I told AI

655
00:34:14,433 --> 00:34:17,246
to call me, right? 
Because I'm the captain, they're

656
00:34:17,246 --> 00:34:19,975
the co-pilot, right? 
But it's, it only costs a 

657
00:34:19,975 --> 00:34:21,199
hundred dollars for that 
monitor. 

658
00:34:21,641 --> 00:34:23,351
And it's just a, it's kind of a 
hack. 

659
00:34:23,641 --> 00:34:25,781
It's a cognitive hack, but it 
works. 

660
00:34:25,831 --> 00:34:30,333
It reminds me to use AI. 
And when I have good work with 

661
00:34:30,333 --> 00:34:35,270
AI, I cut and paste it from AI 
into my main workspace, which is

662
00:34:35,270 --> 00:34:39,328
my documents, my decks, you 
know, my whatever it is, right, 

663
00:34:39,328 --> 00:34:41,618
uh, that I'm working on. 
So I like that. 

664
00:34:41,777 --> 00:34:44,328
Eventually, we, I won't, we 
won't need to do this. 

665
00:34:44,328 --> 00:34:47,987
Eventually AIs will be watching 
our, you know, we'll be sharing 

666
00:34:47,987 --> 00:34:50,358
our screens real time with AI 
soon. 

667
00:34:50,678 --> 00:34:54,431
And AIs will just be watching as
we work and offering to help us.

668
00:34:54,791 --> 00:34:56,431
That is soon in the next year or
two. 

669
00:34:57,001 --> 00:34:59,321
But uh, for now, this is, I 
think, a good hack. 

670
00:34:59,321 --> 00:35:03,495
And you can see where AI is 
going 'cause as you know, AI now

671
00:35:03,495 --> 00:35:07,249
has better memory, particularly 
OpenAI, now Anthropic enabled 

672
00:35:07,249 --> 00:35:10,918
memory, uh, recently for the 
Claude, you know, chat bot. 

673
00:35:11,198 --> 00:35:14,472
And memory, I don't see a lot of
value yet, but we're gonna see a

674
00:35:14,472 --> 00:35:17,158
lot of value from capabilities 
like AI memory. 

675
00:35:17,158 --> 00:35:20,808
'Cause they'll really be able 
to, you know, hold conversations

676
00:35:20,808 --> 00:35:24,290
for longer and remember things 
that they've, that we've talked 

677
00:35:24,290 --> 00:35:27,718
to AI about and so you can see 
where we're going here. 

678
00:35:27,718 --> 00:35:33,406
Really, really powerful, sort of
always on agent or, you know, 

679
00:35:33,406 --> 00:35:36,395
co-intelligence. 
But to get started, yeah, just 

680
00:35:36,395 --> 00:35:41,387
get started and begin to move 
your behavior away from Google 

681
00:35:41,387 --> 00:35:44,032
to AI. 
And that could be the Gemini, 

682
00:35:44,032 --> 00:35:46,642
which is obviously Google's AI. 
It doesn't matter, I don't 

683
00:35:46,642 --> 00:35:48,717
think. 
All these AIs are, I think, 

684
00:35:48,717 --> 00:35:50,567
quite similar in capability at 
this point. 

685
00:35:50,927 --> 00:35:53,473
If you're a software engineer, 
obviously, and for your 

686
00:35:53,473 --> 00:35:57,141
audience, at least some of them,
I'm sure they're already using 

687
00:35:57,141 --> 00:35:58,951
coding co-pilots and maybe 
multiple. 

688
00:35:59,002 --> 00:36:02,484
Eventually I expect there'll be 
one or two winners, you know, 

689
00:36:02,484 --> 00:36:05,092
uh, in terms of coding and 
software engineering. 

690
00:36:05,842 --> 00:36:09,270
I find it interesting that the 
AI companies, and for good 

691
00:36:09,270 --> 00:36:12,596
reason 'cause they see how many 
conversations are related to 

692
00:36:12,596 --> 00:36:15,545
software, you know, software 
coding and writing code. 

693
00:36:15,855 --> 00:36:18,285
So they keep improving that part
of the product. 

694
00:36:19,035 --> 00:36:21,708
But software engineers are a 
small part of the knowledge 

695
00:36:21,708 --> 00:36:23,493
economy. 
When you look at the knowledge 

696
00:36:23,493 --> 00:36:26,198
economy, it's, you know, huge 
and a lot of other roles. 

697
00:36:26,198 --> 00:36:29,190
You know, marketers and 
salespeople and finance and HR. 

698
00:36:29,190 --> 00:36:32,198
AI is not as good yet for those 
functions, right? 

699
00:36:32,198 --> 00:36:34,957
It's still 'cause it 
hallucinates and it's not as 

700
00:36:34,957 --> 00:36:37,656
easy to work with. 
But, you know, these are AI 

701
00:36:37,656 --> 00:36:38,939
companies. 
They're full of software 

702
00:36:38,939 --> 00:36:41,503
engineers and so they keep 
releasing better features for 

703
00:36:41,503 --> 00:36:44,786
software engineers, right? 
OpenAI just released, uh, GPT-5 

704
00:36:44,786 --> 00:36:50,241
codex this week, right? 
Or retire and go play golf. 

705
00:36:51,452 --> 00:36:54,524
If you wanna keep your head in 
the sand about this AI thing, 

706
00:36:54,524 --> 00:36:57,382
you could try. 
If you're 45, I don't think it's

707
00:36:57,382 --> 00:37:00,372
gonna work. 
If you're 60, you know. 

708
00:37:00,972 --> 00:37:02,012
What's the, I don't want the 
retirement. 

709
00:37:02,012 --> 00:37:03,522
What's the.... you're in 
Singapore? 

710
00:37:04,202 --> 00:37:06,138
Yes. 
What's the typical retirement 

711
00:37:06,138 --> 00:37:10,032
age in Singapore? 
60, 62. 62. 

712
00:37:10,032 --> 00:37:12,218
Yeah. 
So yeah, maybe if you're 60, 

713
00:37:12,218 --> 00:37:15,798
maybe if you're 57 or something,
keep your head in the sand, you 

714
00:37:15,798 --> 00:37:18,812
know, just stay outta trouble 
and you can get to retirement 

715
00:37:18,812 --> 00:37:20,582
and then you can focus on the 
golf game. 

716
00:37:20,882 --> 00:37:23,582
I'm 63, but I wanted to keep 
working. 

717
00:37:24,032 --> 00:37:26,672
I intend to work for at least 
five more years and I live and 

718
00:37:26,672 --> 00:37:29,192
work in Silicon Valley. 
It's a very ageist place. 

719
00:37:29,552 --> 00:37:32,412
You know, if you're not 28 years
old and wearing a hoodie, you're

720
00:37:32,412 --> 00:37:35,544
an idiot. 
So, you know, when I used a GPT 

721
00:37:35,544 --> 00:37:39,024
for the first time, I very 
selfishly thought for me this 

722
00:37:39,024 --> 00:37:42,149
was gonna be great. 
I thought it would be great for 

723
00:37:42,149 --> 00:37:43,762
the company and that's why we 
pivoted. 

724
00:37:44,032 --> 00:37:47,958
But my first reaction was, hey, 
this is great for me 'cause I 

725
00:37:47,958 --> 00:37:52,462
can maintain my cognitive edge, 
I can really keep working and at

726
00:37:52,462 --> 00:37:56,245
a high level. 
Because, you know, as we age, 

727
00:37:56,245 --> 00:37:59,077
you know, our cognitive 
abilities do decline and that 

728
00:37:59,077 --> 00:38:01,387
decline accelerates after the 
age of 50. 

729
00:38:01,827 --> 00:38:04,017
Cause I asked GPT and that's 
what it told me. 

730
00:38:04,317 --> 00:38:07,767
So, uh, you know, I thought 
about it as this is a way I'm 

731
00:38:07,767 --> 00:38:10,832
gonna stay cognitively sharp. 
Now you already kind of 

732
00:38:10,832 --> 00:38:15,117
referenced this, there's a real 
risk that the opposite happens. 

733
00:38:15,237 --> 00:38:20,522
If we over rely on AI, if we 
cognitively offload too much to 

734
00:38:20,522 --> 00:38:23,667
AI, we won't stay sharp. 
We'll actually get stupid. 

735
00:38:24,657 --> 00:38:29,700
And that is happening already. 
People are losing their minds to

736
00:38:29,700 --> 00:38:32,325
AI. 
And I would argue that this 

737
00:38:32,325 --> 00:38:36,761
greatest risk when we're younger
- kids in school, in college or 

738
00:38:36,761 --> 00:38:40,825
early career - where they are 
literally working with AI 

739
00:38:40,825 --> 00:38:44,787
cutting and pasting the answer, 
sticking it into the document, 

740
00:38:44,787 --> 00:38:48,260
the deck, the report, whatever 
it is, and submitting it as 

741
00:38:48,260 --> 00:38:50,934
their work. 
And, you know, that's not gonna 

742
00:38:50,934 --> 00:38:54,246
end well for anyone. 
Uh, it won't end well for the 

743
00:38:54,246 --> 00:38:57,009
employee and not for the 
organization because you'll have

744
00:38:57,009 --> 00:39:00,240
a lot of mediocre work being 
done by AI. 

745
00:39:00,660 --> 00:39:03,260
And again, I worry a lot about 
this. 

746
00:39:03,285 --> 00:39:07,615
I think that we are at risk of a
whole generation of young people

747
00:39:07,615 --> 00:39:12,226
who over rely on AI. 
And really, like we have with, 

748
00:39:12,226 --> 00:39:14,898
you know, the obvious example is
GPS, right? 

749
00:39:15,103 --> 00:39:17,991
No one can really, no one can 
use a map anymore and can, no 

750
00:39:17,991 --> 00:39:21,060
one knows how to find their way 
in a city. 

751
00:39:21,060 --> 00:39:25,399
They just use GPS on a phone. 
And that part of our brain has 

752
00:39:25,399 --> 00:39:28,135
literally atrophied. 
That's kind of spatial 

753
00:39:28,135 --> 00:39:31,950
processing part of our brain uh,
has atrophied in humans. 

754
00:39:32,470 --> 00:39:36,800
So yeah, I think that we need AI
in some ways. 

755
00:39:36,980 --> 00:39:42,163
We are overwhelmed with data, 
content, feeds, information, 

756
00:39:42,163 --> 00:39:44,147
right? 
You know, our human brains have 

757
00:39:44,147 --> 00:39:46,762
not changed much as you know, 
Henry, in 70,000 years. 

758
00:39:47,171 --> 00:39:48,682
It really haven't evolved that 
much. 

759
00:39:48,682 --> 00:39:53,146
It's the same three pounds of 
cognitive capability and we're 

760
00:39:53,146 --> 00:39:57,046
overwhelmed with inputs. 
And so in some ways, as humans, 

761
00:39:57,046 --> 00:40:01,576
we need AI to help us manage the
cognitive load that the average 

762
00:40:01,576 --> 00:40:05,912
knowledge worker kind of faces. 
But at the same time, as I said,

763
00:40:05,912 --> 00:40:09,536
the real risk is we offload too 
much and we stop thinking. 

764
00:40:09,536 --> 00:40:12,394
And I have a, you know, we're 
very clear about that at 

765
00:40:12,394 --> 00:40:15,555
Section, at my companies. 
You can say it once, you can't 

766
00:40:15,555 --> 00:40:17,664
say it twice. 
You say it twice, you probably 

767
00:40:17,664 --> 00:40:19,326
won't be working at my company 
anymore. 

768
00:40:19,326 --> 00:40:23,676
If you say, well, AI said we 
should do it, you know, it's the

769
00:40:23,676 --> 00:40:27,483
worst thing to say. 
You know, I will lose my shit if

770
00:40:27,483 --> 00:40:30,741
someone says that in a meeting 
or in a email or Slack message. 

771
00:40:30,771 --> 00:40:33,787
I will not tolerate it. 
Again, you can say it once, you 

772
00:40:33,787 --> 00:40:36,199
can't say it twice. 
Wow. 

773
00:40:36,267 --> 00:40:38,925
Um, so many tips I think are 
really great. 

774
00:40:39,135 --> 00:40:41,808
Uh, in the beginning you 
mentioned some simple hacks, in 

775
00:40:41,808 --> 00:40:43,803
fact. 
It's not something, you know 

776
00:40:43,803 --> 00:40:46,815
that is grandiose, right? 
It could be as simple as remind 

777
00:40:46,815 --> 00:40:49,245
yourself to always ask AI. 
Because it's a new habit, right?

778
00:40:49,455 --> 00:40:53,175
I think most of the time, many 
people are very natural, you 

779
00:40:53,175 --> 00:40:56,217
know, asking Google search. 
Um, so I think changing the 

780
00:40:56,217 --> 00:40:58,365
habit into asking AI is one 
thing. 

781
00:40:58,755 --> 00:41:01,802
And I think you also play around
with different types of AI, 

782
00:41:01,802 --> 00:41:03,479
right? 
So I think that could be another

783
00:41:03,479 --> 00:41:05,586
thing, right? 
Because some AI might be good on

784
00:41:05,586 --> 00:41:08,696
some particular tasks. 
And I think one other aspects 

785
00:41:08,696 --> 00:41:10,908
about using AI is like 
experiment, right? 

786
00:41:10,968 --> 00:41:14,624
Because I mean, as a start, you 
will be just asking questions, 

787
00:41:14,624 --> 00:41:16,458
right? 
A lot of questions and answers. 

788
00:41:16,857 --> 00:41:20,037
But then there are many other 
features that AI can also 

789
00:41:20,037 --> 00:41:22,156
support. 
Like, I don't know, like deep 

790
00:41:22,156 --> 00:41:24,286
research, coding or whatever 
that is, right? 

791
00:41:24,586 --> 00:41:27,144
I think just play around and 
experiment and get the feeling, 

792
00:41:27,144 --> 00:41:28,988
right? 
So I think that's a very 

793
00:41:28,988 --> 00:41:31,473
important. 
I wanna understand a little bit 

794
00:41:31,473 --> 00:41:34,181
more about when you roll out 
this into companies, right? 

795
00:41:34,391 --> 00:41:37,410
Because many companies now, 
maybe not many, like a few 

796
00:41:37,410 --> 00:41:41,614
companies now are trying to roll
out AI fully to their employees.

797
00:41:41,942 --> 00:41:44,012
Companies like Shopify or 
Salesforce, right? 

798
00:41:44,216 --> 00:41:48,402
They even advocate use AI first 
instead of hiring more people, 

799
00:41:48,402 --> 00:41:50,634
right? 
And I'm sure in, similarly it 

800
00:41:50,634 --> 00:41:54,067
happens in your company as well,
but many people are kind of like

801
00:41:54,067 --> 00:41:56,282
afraid about their jobs when 
thinking about AI. 

802
00:41:56,282 --> 00:42:00,352
They think, oh, if I use AI 
more, maybe my job, it won't be 

803
00:42:00,352 --> 00:42:03,472
safe anymore. 
Um, so how do you actually 

804
00:42:03,472 --> 00:42:07,797
create this culture to everyone 
that use AI, uh, how to make 

805
00:42:07,797 --> 00:42:12,056
sure that they are still 
upskilled, they are like safe in

806
00:42:12,056 --> 00:42:15,621
terms of, you know, career. 
Um, maybe a little bit of tips 

807
00:42:15,621 --> 00:42:17,221
here. 
How do you actually roll it out 

808
00:42:17,221 --> 00:42:19,748
fully to the company, yeah? 
Yeah, great question, Henry. 

809
00:42:19,778 --> 00:42:22,052
And listen, I'd say in the 
United States right now, almost 

810
00:42:22,052 --> 00:42:26,758
every organization that I talk 
to is rolling out AI in some way

811
00:42:26,758 --> 00:42:30,058
to either a large part or the 
whole workforce. 

812
00:42:30,208 --> 00:42:32,878
And certainly to the soft- to 
the engineering and product 

813
00:42:32,878 --> 00:42:37,084
development teams, absolutely. 
And to marketing, to sales, and 

814
00:42:37,084 --> 00:42:39,522
maybe the whole organization. 
And it's a struggle. 

815
00:42:39,522 --> 00:42:43,593
I would also say that very few 
companies that I talk to are 

816
00:42:43,593 --> 00:42:47,458
doing it well. 
Most are failing or stalling, 

817
00:42:47,458 --> 00:42:50,754
really struggling. 
And it is for some of the 

818
00:42:50,754 --> 00:42:54,625
reasons you said. 
First of all the training is one

819
00:42:54,625 --> 00:42:58,430
time and that's not enough. 
You must be continuously 

820
00:42:58,430 --> 00:43:02,520
upskilling with AI because the 
AI capabilities are changing all

821
00:43:02,520 --> 00:43:05,010
the time, always improving. 
This will be good. 

822
00:43:05,040 --> 00:43:07,260
This will keep going on for the 
next several years, right? 

823
00:43:07,260 --> 00:43:08,910
AI is getting better and better 
and better. 

824
00:43:09,211 --> 00:43:11,829
This idea of take, you know, 
taking one class and giving 

825
00:43:11,829 --> 00:43:14,104
employees one, you know, one 
class, it's not enough. 

826
00:43:14,104 --> 00:43:16,918
That's the first thing. 
Second thing is, I think if you 

827
00:43:16,918 --> 00:43:20,904
go back to the beginning of 
this, like why are we doing AI 

828
00:43:20,904 --> 00:43:24,580
as an organization? 
I think CEOs, and you referenced

829
00:43:24,580 --> 00:43:28,518
Shopify, Tobi Lütke, CEO of 
Shopify, who published his memo 

830
00:43:28,518 --> 00:43:31,196
to all employees why you have to
be using AI. 

831
00:43:31,504 --> 00:43:34,786
And you know, he also said in 
that, why are we doing this. 

832
00:43:34,856 --> 00:43:36,826
And you need to have a why of 
AI. 

833
00:43:37,426 --> 00:43:40,316
Because if you don't say to the 
organization, why are we doing 

834
00:43:40,316 --> 00:43:42,878
this? 
Then all they're gonna think is 

835
00:43:42,878 --> 00:43:46,116
what you said. 
They're gonna think, oh, 

836
00:43:46,116 --> 00:43:50,176
efficiency, which is code for 
layoffs, right? 

837
00:43:50,176 --> 00:43:53,546
Like if you don't tell people 
why AI, then they're just gonna 

838
00:43:53,546 --> 00:43:55,938
assume, well, you want the 
robots, you want the AI to do 

839
00:43:55,938 --> 00:43:57,856
the work. 
And by the way, the media, 

840
00:43:57,856 --> 00:44:00,643
that's been the narrative that 
the media has been feeding us 

841
00:44:00,643 --> 00:44:03,958
for three years, right? 
The image we have of AI is AI is

842
00:44:03,958 --> 00:44:06,759
coming for our jobs, and we're 
gonna need, we're gonna be 

843
00:44:06,759 --> 00:44:09,539
unemployed, or we're gonna be 
sitting on a beach, you know, 

844
00:44:09,539 --> 00:44:11,741
picking up a universal basic 
income check. 

845
00:44:12,071 --> 00:44:13,421
I don't think that's gonna 
happen. 

846
00:44:15,584 --> 00:44:17,054
So... 
But this is what the media's 

847
00:44:17,054 --> 00:44:19,209
been telling us. 
So of course, employees are 

848
00:44:19,209 --> 00:44:20,684
anxious. 
Here's how I think about it. 

849
00:44:20,684 --> 00:44:23,624
So establish your why of AI. 
What is the mission of your 

850
00:44:23,624 --> 00:44:26,302
business? 
How does AI make that mission 

851
00:44:26,302 --> 00:44:29,434
more possible? 
Whatever your mission is, if 

852
00:44:29,434 --> 00:44:33,386
you're a hospital or a financial
advisor or, you know, a retail 

853
00:44:33,386 --> 00:44:36,283
company, it doesn't matter. 
What is the company's mission 

854
00:44:36,283 --> 00:44:39,594
and then link that company 
mission to the AI, and that 

855
00:44:39,594 --> 00:44:43,396
becomes your why of AI. 
It's what I call the AI 

856
00:44:43,396 --> 00:44:45,194
manifesto. 
Everybody has AI rules and 

857
00:44:45,194 --> 00:44:47,274
regulations, what not to do with
AI. 

858
00:44:47,304 --> 00:44:50,154
Don't do this, don't do that. 
You'll get fired if you do this.

859
00:44:50,424 --> 00:44:53,004
Okay, all that's gonna do is 
discourage usage. 

860
00:44:53,064 --> 00:44:58,252
It is so stupid for CEOs to be 
talking about AI rules. 

861
00:44:58,282 --> 00:45:00,182
I know you need them. 
You need them. 

862
00:45:00,502 --> 00:45:03,957
And your chief legal counsel and
your security officer, you know,

863
00:45:03,957 --> 00:45:06,142
you need to have rules. 
So you need to publish them. 

864
00:45:06,532 --> 00:45:09,412
But you also need a manifesto. 
Why are we doing AI? 

865
00:45:09,502 --> 00:45:13,205
How do we think about AI? 
Do we reward people for using 

866
00:45:13,205 --> 00:45:15,016
AI? 
Do we celebrate people who use 

867
00:45:15,016 --> 00:45:18,832
AI or do we accuse them of 
cutting corners or cheating? 

868
00:45:19,012 --> 00:45:23,115
You know, you need to be very 
positive and affirmative in the 

869
00:45:23,115 --> 00:45:25,376
use of AI if you want people to 
use it. 

870
00:45:25,586 --> 00:45:28,378
You also need to be honest. 
So my point of view in this, 

871
00:45:28,378 --> 00:45:29,816
Henry, is there will be job 
loss. 

872
00:45:30,613 --> 00:45:34,453
And not talking about it I think
is naive and inauthentic. 

873
00:45:34,453 --> 00:45:36,733
And I don't think your employees
are that stupid. 

874
00:45:36,913 --> 00:45:41,448
And by the way, your employees 
are probably using AI maybe at 

875
00:45:41,448 --> 00:45:43,852
work even at, you know, 
unsanctioned or they're 

876
00:45:43,852 --> 00:45:47,325
certainly using it at home and 
they're realizing it's pretty 

877
00:45:47,325 --> 00:45:49,042
powerful. 
It's not that good. 

878
00:45:49,252 --> 00:45:52,160
Frankly, the people who are most
scared about AI are the people 

879
00:45:52,160 --> 00:45:54,922
that use it the least is my 
experience. 

880
00:45:55,102 --> 00:46:00,024
The people who use AI a lot can 
see its value and can see its 

881
00:46:00,024 --> 00:46:02,341
shortcomings, and they don't 
think they're very worried about

882
00:46:02,341 --> 00:46:05,114
losing their job. 
So it's kind of this ironic, 

883
00:46:05,114 --> 00:46:06,560
right? 
The people that don't use AI 

884
00:46:06,560 --> 00:46:08,032
seem to be the most scared about
it. 

885
00:46:08,422 --> 00:46:10,414
But I think you've gotta be 
honest with employees. 

886
00:46:10,414 --> 00:46:14,074
Here's what I tell my team, and 
this is what I coach other CEOs.

887
00:46:14,579 --> 00:46:17,903
Go all in on AI. 
Pay for AI for everybody. 

888
00:46:18,233 --> 00:46:20,443
Don't have people paying for it 
for themselves. 

889
00:46:20,983 --> 00:46:22,613
That's dumb, right? 
It's not fair. 

890
00:46:22,613 --> 00:46:25,138
You're gonna get the 
productivity benefit as the 

891
00:46:25,138 --> 00:46:27,882
employer. 
As the CEO, you're gonna get the

892
00:46:27,882 --> 00:46:29,468
gain. 
Pay for the AI. 

893
00:46:29,678 --> 00:46:32,588
That's the first thing. 
Do the upskilling and do the 

894
00:46:32,588 --> 00:46:34,898
change management. 
Encourage the adoption of AI. 

895
00:46:35,108 --> 00:46:38,528
Encourage best practices, right?
Watch out for hallucinations. 

896
00:46:38,738 --> 00:46:42,188
Don't cut and paste the AI 
answer into the document. 

897
00:46:42,188 --> 00:46:45,362
Think about it, you know. 
How AI is, what advice you're 

898
00:46:45,362 --> 00:46:47,828
getting from AI, and then add 
your own judgment. 

899
00:46:47,828 --> 00:46:51,303
And the final thing is tell your
team, tell your company, your 

900
00:46:51,303 --> 00:46:52,863
organization, what's gonna 
happen. 

901
00:46:53,073 --> 00:46:58,193
And here's what I say. 
In a year, if we keep using AI 

902
00:46:58,193 --> 00:47:02,809
as much as we're using it now, 
probably more, I want more AI in

903
00:47:02,809 --> 00:47:05,685
the company. 
I want all of us really 

904
00:47:05,685 --> 00:47:10,545
optimizing ourselves with AI. 
If we do that, I think there's 

905
00:47:10,545 --> 00:47:13,593
four different outcomes and all 
of them will happen. 

906
00:47:13,743 --> 00:47:17,271
Here's what they are. 
Some teams will be the same 

907
00:47:17,271 --> 00:47:19,203
size, they'll be doing more 
work. 

908
00:47:20,103 --> 00:47:23,427
Okay, that's one. 
Some teams will be smaller and 

909
00:47:23,427 --> 00:47:27,375
doing the same amount of work, 
meaning AI made people more 

910
00:47:27,375 --> 00:47:30,287
productive. 
We did not need more of that 

911
00:47:30,287 --> 00:47:33,303
work, so we actually reduced the
size of the team. 

912
00:47:33,333 --> 00:47:35,103
That's gonna happen in some 
teams. 

913
00:47:35,343 --> 00:47:37,623
Some teams will actually be 
bigger with AI. 

914
00:47:38,293 --> 00:47:43,057
As an example, my point of view 
is because the business I'm in, 

915
00:47:43,057 --> 00:47:45,709
software engineers and 
salespeople, 'cause I'm building

916
00:47:45,709 --> 00:47:48,828
and selling a SaaS platform. 
Software engineers and 

917
00:47:48,828 --> 00:47:52,135
salespeople are the two of the 
most valuable people in the 

918
00:47:52,135 --> 00:47:53,817
organization. 
If AI makes them more 

919
00:47:53,817 --> 00:47:55,757
productive, I actually want more
of them. 

920
00:47:55,997 --> 00:47:57,547
I don't want less software 
engineers. 

921
00:47:58,037 --> 00:48:01,914
Talk to any CEO and what will 
they tell you about their 

922
00:48:01,914 --> 00:48:04,067
roadmap? 
They're always a year or two 

923
00:48:04,067 --> 00:48:06,827
behind on their roadmap. 
I've never found a CEO, right, 

924
00:48:06,827 --> 00:48:10,217
in Silicon Valley who says, my 
roadmap, I got everything I 

925
00:48:10,217 --> 00:48:13,597
wanted today in my roadmap. 
I never heard that. 

926
00:48:13,887 --> 00:48:17,279
Never going to. 
All you ever hear from a CEO is 

927
00:48:17,279 --> 00:48:20,507
or a product, Head of Product is
my roadmap is behind. 

928
00:48:20,507 --> 00:48:23,267
I have more features, I have 
more roadmap I want built. 

929
00:48:23,569 --> 00:48:26,743
If coding co-pilots or coding 
agents makes software engineers 

930
00:48:26,743 --> 00:48:30,879
twice as productive or even 15% 
more productive, I'm gonna want 

931
00:48:30,879 --> 00:48:33,679
probably more engineers, right? 
Salespeople, the same. 

932
00:48:33,709 --> 00:48:36,679
If AI makes salespeople more 
productive and more salespeople 

933
00:48:36,679 --> 00:48:40,099
can hit their targets, do I want
less salespeople? 

934
00:48:40,099 --> 00:48:43,997
No, I want more, right? 
So some teams will be the same 

935
00:48:43,997 --> 00:48:46,189
size, some will be smaller, some
will be bigger. 

936
00:48:46,189 --> 00:48:49,723
And the last thing is we're 
gonna add some jobs that don't 

937
00:48:49,723 --> 00:48:52,384
exist this year, right? 
And that's happened to every 

938
00:48:52,384 --> 00:48:53,869
year the last two years at 
Section. 

939
00:48:53,869 --> 00:48:56,911
We've added new jobs that did 
not exist the year before 

940
00:48:56,911 --> 00:49:00,567
because of AI. 
So those are the four, in my 

941
00:49:00,567 --> 00:49:03,689
opinion, organizational outcomes
that will likely happen because 

942
00:49:03,689 --> 00:49:05,809
of AI. 
And I think the best thing is 

943
00:49:05,809 --> 00:49:07,489
just tell the team we don't know
yet. 

944
00:49:07,609 --> 00:49:10,459
Like this isn't, this is a new 
thing. 

945
00:49:10,609 --> 00:49:13,225
So I can't tell you the 
marketing team will be smaller 

946
00:49:13,225 --> 00:49:15,675
or bigger. 
You know, it might be the same 

947
00:49:15,675 --> 00:49:17,419
size, might be smaller, it might
be bigger. 

948
00:49:17,569 --> 00:49:19,969
We just need to go in this 
together, quite frankly. 

949
00:49:19,969 --> 00:49:25,514
It'll require some trust. 
And I'm gonna upskill you, so no

950
00:49:25,514 --> 00:49:30,028
matter what happens, and again 
the company has to pay for this 

951
00:49:30,028 --> 00:49:32,229
my opinion, I'm gonna upskill 
you. 

952
00:49:32,419 --> 00:49:36,054
And so if I do have to lay you 
off, if I do have to shrink the 

953
00:49:36,054 --> 00:49:39,795
size of a team, at least when 
you go into the job market, 

954
00:49:39,795 --> 00:49:41,799
you're gonna be an AI-enabled 
employee. 

955
00:49:41,799 --> 00:49:44,985
They'll be the most valuable 
employees, the most valuable 

956
00:49:44,985 --> 00:49:47,949
candidates for a job. 
So that's how I think about it. 

957
00:49:48,607 --> 00:49:52,800
And what I would say is if your 
employer is not doing that, then

958
00:49:52,800 --> 00:49:55,411
it's your responsibility. 
If your employer doesn't pay for

959
00:49:55,411 --> 00:49:58,297
your AI, pay for your own AI. 
And if your employer's not 

960
00:49:58,297 --> 00:50:01,177
paying for your upskilling and 
your training, do it yourself. 

961
00:50:01,237 --> 00:50:05,142
There's no excuse at this point.
Do not let your employer 

962
00:50:05,142 --> 00:50:09,905
determine your AI future. 
If they are clueless or they're 

963
00:50:09,905 --> 00:50:13,699
hesitant or they're scared, 
that's not a reason for you to 

964
00:50:13,699 --> 00:50:16,095
be. 
You own your future. 

965
00:50:16,125 --> 00:50:20,647
You own your AI future. 
Yeah, so in the end, I think our

966
00:50:20,647 --> 00:50:23,402
growth, our personal growth, you
know, our upskilling, it comes 

967
00:50:23,402 --> 00:50:26,382
back to us, right? 
I think we are the only driver. 

968
00:50:26,592 --> 00:50:28,212
Obviously company can support, 
right? 

969
00:50:28,452 --> 00:50:31,302
Great companies with great 
culture, I think will uh, be 

970
00:50:31,302 --> 00:50:33,906
able to support our growth. 
But I think, yeah, we should not

971
00:50:33,906 --> 00:50:35,442
kind of like rely on just the 
company. 

972
00:50:35,702 --> 00:50:39,464
I think many companies still 
think AI as like an efficiency 

973
00:50:39,464 --> 00:50:41,328
play, right? 
So you mentioned about layoffs. 

974
00:50:41,328 --> 00:50:43,838
I think it was in the news a lot
of times. 

975
00:50:43,838 --> 00:50:47,556
You know, a lot of companies, 
including big tech themselves, 

976
00:50:47,556 --> 00:50:49,795
AI providers, right, actually 
lay off people. 

977
00:50:50,220 --> 00:50:53,064
And many people actually 
associate that, okay, AI means 

978
00:50:53,064 --> 00:50:56,347
more layoffs, I'm gonna lose my 
job, less employees and all 

979
00:50:56,347 --> 00:50:58,285
that. 
And thanks for mentioning those 

980
00:50:58,285 --> 00:51:01,250
four possible outcomes that 
could happen when you roll out 

981
00:51:01,250 --> 00:51:03,698
AI. 
So I think for those executives 

982
00:51:03,698 --> 00:51:06,674
now who are thinking of 
implementing AI in the company, 

983
00:51:06,674 --> 00:51:09,554
I think most of them probably 
the ROI thinking is like, okay, 

984
00:51:09,554 --> 00:51:13,234
if I deploy this AI solutions, 
I'll be able to cut, you know, 

985
00:51:13,234 --> 00:51:16,194
some costs or maybe more 
efficient in some areas, which 

986
00:51:16,194 --> 00:51:18,912
is probably like the naive way 
of calculating that. 

987
00:51:19,242 --> 00:51:22,372
But what do you think, um, you 
know, having worked on this 

988
00:51:22,372 --> 00:51:25,806
area, how do you actually advise
leaders, executives to actually 

989
00:51:25,806 --> 00:51:28,572
see the ROI of implementing AI 
in their company? 

990
00:51:29,699 --> 00:51:33,594
Yeah, I think that's exactly 
right for phase one. 

991
00:51:33,594 --> 00:51:37,669
So what I mean by that is 
McKinsey would use a language 

992
00:51:37,669 --> 00:51:41,372
like efficiency and growth. 
My language is more crude. 

993
00:51:41,582 --> 00:51:45,152
I say cut and create. 
Just 'cause it's more memorable,

994
00:51:45,152 --> 00:51:47,813
right? 
How I think about that is there 

995
00:51:47,813 --> 00:51:50,969
are two modes. 
There are two strategy modes for

996
00:51:50,969 --> 00:51:53,135
AI. 
One is efficiency, one is 

997
00:51:53,135 --> 00:51:56,120
cutting, and this doesn't mean 
necessarily cutting people. 

998
00:51:56,150 --> 00:52:00,009
It means cutting tasks, cutting 
workflows, cutting 

999
00:52:00,009 --> 00:52:01,940
organizational inefficiency, and
so on, right? 

1000
00:52:02,090 --> 00:52:06,152
Use AI to become more efficient.
That is, I think, is the first 

1001
00:52:06,152 --> 00:52:09,020
phase of AI. 
And you're right, that's how 

1002
00:52:09,020 --> 00:52:11,570
most CFOs will justify it, 
right? 

1003
00:52:11,570 --> 00:52:13,730
CEOs are less interested in 
cutting. 

1004
00:52:13,730 --> 00:52:16,490
CEOs. 
CEOs want creation. 

1005
00:52:16,580 --> 00:52:19,619
CEOs want growth. 
So that is the... 

1006
00:52:19,619 --> 00:52:22,564
That is what happens next. 
By the way, you can do them at 

1007
00:52:22,564 --> 00:52:24,789
the same time. 
You can become more efficient 

1008
00:52:24,789 --> 00:52:28,451
and you can find growth at the 
same time, or you can stage 

1009
00:52:28,451 --> 00:52:30,979
them. 
Efficiency first and growth 

1010
00:52:30,979 --> 00:52:32,209
second. 
Create. 

1011
00:52:32,239 --> 00:52:36,169
Create new products, create new 
services, create new revenue 

1012
00:52:36,169 --> 00:52:40,354
streams, create new jobs. 
Create new markets. 

1013
00:52:40,414 --> 00:52:45,792
AI will enable that as well. 
As a leader, my opinion is, you 

1014
00:52:45,792 --> 00:52:49,271
are responsible for both and 
you're, particularly, you're 

1015
00:52:49,271 --> 00:52:53,265
responsible for moving through 
the first phase, that efficiency

1016
00:52:53,265 --> 00:52:57,701
phase or that cut phase. 
You are responsible for moving 

1017
00:52:57,701 --> 00:52:59,795
through that as fast as 
possible. 

1018
00:53:00,575 --> 00:53:04,587
The sooner you move through 
that, the lower the anxiety in 

1019
00:53:04,587 --> 00:53:08,063
the workforce, in your 
workforce, frankly the sooner 

1020
00:53:08,063 --> 00:53:12,595
you'll get the efficiency gains.
And then most importantly, the 

1021
00:53:12,595 --> 00:53:17,038
faster you'll get to the next 
phase, which is creation, which 

1022
00:53:17,038 --> 00:53:20,915
is growth, and that's what your 
CEO cares about. 

1023
00:53:21,698 --> 00:53:23,678
So I want an efficient 
organization. 

1024
00:53:23,948 --> 00:53:27,558
Of course, I do. 
And we are using AI every day at

1025
00:53:27,558 --> 00:53:29,478
Section to make ourselves more 
efficient. 

1026
00:53:29,918 --> 00:53:33,188
I'm most excited about growth. 
I'm most excited about adding 

1027
00:53:33,188 --> 00:53:34,748
new products and services 
faster. 

1028
00:53:34,748 --> 00:53:38,504
I'm most excited about 
accelerating our roadmap, so our

1029
00:53:38,504 --> 00:53:41,858
software platform has more 
capability so I can charge more 

1030
00:53:41,858 --> 00:53:45,434
for it and drive more revenue. 
And so, you know, we're trying 

1031
00:53:45,434 --> 00:53:48,862
to do both at once, but we did 
focus for the first year on 

1032
00:53:48,862 --> 00:53:51,708
let's make ourselves more 
efficient and let's eliminate, 

1033
00:53:52,038 --> 00:53:54,038
you know, work, annoying 
workflows. 

1034
00:53:54,038 --> 00:53:58,568
Let's eliminate tedious 
workflows with AI and so on. 

1035
00:53:58,843 --> 00:54:01,243
That impacted a couple people in
terms of jobs. 

1036
00:54:01,243 --> 00:54:04,443
Not that many, but it did. 
We did had to sort of the team 

1037
00:54:04,443 --> 00:54:07,907
changed because of that. 
Now we're focused on growth, 

1038
00:54:07,907 --> 00:54:10,689
we're adding headcount. 
We're adding probably less 

1039
00:54:10,689 --> 00:54:14,556
headcount than I thought we 
would 'cause based on our rate 

1040
00:54:14,556 --> 00:54:18,427
of growth, we are more headcount
efficient than we used to be. 

1041
00:54:18,497 --> 00:54:20,457
That's great. 
But we're still hiring people 

1042
00:54:20,457 --> 00:54:23,927
obviously, and we're hiring in 
some cases, I said new roles 

1043
00:54:23,927 --> 00:54:26,838
'cause we're beginning to create
new jobs, right? 

1044
00:54:26,879 --> 00:54:28,709
Based on creating new products 
and services. 

1045
00:54:28,709 --> 00:54:30,959
So I think about this as two 
phases. 

1046
00:54:31,039 --> 00:54:35,895
As leaders, we wanna get through
that efficiency phase as fast as

1047
00:54:35,895 --> 00:54:38,024
possible. 
'Cause everybody I think will 

1048
00:54:38,024 --> 00:54:41,559
relax and calm down to some 
extent and realize, okay, it's 

1049
00:54:41,559 --> 00:54:44,790
not coming for my job. 
In fact, I can use this. 

1050
00:54:45,570 --> 00:54:47,640
I can use this to start to 
create. 

1051
00:54:48,153 --> 00:54:52,227
You know, bring more value. 
I talked to, today, Henry, some 

1052
00:54:52,227 --> 00:54:57,409
people who are responsible for 
AI for hospitals in the US and 

1053
00:54:57,409 --> 00:55:01,972
we talked a lot about doctor AI 
note takers for doctors and 

1054
00:55:01,972 --> 00:55:03,774
nurses. 
So, you know, when they're in 

1055
00:55:03,774 --> 00:55:06,192
sitting with patients. 
Pretty much every hospital now 

1056
00:55:06,192 --> 00:55:09,702
is almost everywhere in the US 
is using these AI note takers. 

1057
00:55:10,121 --> 00:55:13,604
And the idea being that if we do
that, the doctor's not sitting 

1058
00:55:13,604 --> 00:55:15,971
at the keyboard, obviously 
typing notes. 

1059
00:55:16,757 --> 00:55:19,847
And so it's just like elevating,
the doctors didn't go to medical

1060
00:55:19,847 --> 00:55:22,597
school to type notes, right? 
The doctors went to medical 

1061
00:55:22,597 --> 00:55:25,547
school to learn how to, you 
know, diagnose and deliver care 

1062
00:55:25,547 --> 00:55:27,887
to patients. 
And so that's what we're trying 

1063
00:55:27,887 --> 00:55:31,847
to move everyone up to the top 
of their capability. 

1064
00:55:32,120 --> 00:55:35,792
This is the potential. 
And I think it is happening in a

1065
00:55:35,792 --> 00:55:40,910
lot of jobs, a lot of roles 
where we can see how AI can 

1066
00:55:40,910 --> 00:55:44,289
elevate us. 
And that's what doctors are 

1067
00:55:44,289 --> 00:55:47,034
seeing, absolutely. 
And all these, I had four, I was

1068
00:55:47,034 --> 00:55:49,480
talking to four healthcare 
leaders, AI leaders in 

1069
00:55:49,480 --> 00:55:52,649
healthcare companies, and they 
all said that universally 

1070
00:55:52,669 --> 00:55:57,104
doctors love these note takers. 
It's drudge work to sit there 

1071
00:55:57,104 --> 00:56:00,996
and, and, you know, type up 
patient notes and it's not 

1072
00:56:00,996 --> 00:56:02,397
great. 
And you've probably experienced 

1073
00:56:02,397 --> 00:56:05,009
this, I certainly have, where 
you're sitting waiting for your 

1074
00:56:05,009 --> 00:56:08,496
doctor and your doctor comes 
into the room and the first 

1075
00:56:08,496 --> 00:56:11,616
thing he or she does is sits 
down at a computer and starts 

1076
00:56:11,616 --> 00:56:13,836
typing the keyboard. 
'Cause they have to start making

1077
00:56:13,836 --> 00:56:16,904
the notes, right? 
And what a better experience, 

1078
00:56:16,904 --> 00:56:21,028
what a more human experience if 
AI note takers are running and 

1079
00:56:21,028 --> 00:56:25,396
the doctor can come in, sit down
and look at you and not look at 

1080
00:56:25,396 --> 00:56:28,256
your patient record that's on 
the computer and start typing. 

1081
00:56:28,592 --> 00:56:32,308
This has the opportunity to make
doctors more efficient. 

1082
00:56:32,338 --> 00:56:36,300
It has an opportunity to make 
them more humanistic in their 

1083
00:56:36,300 --> 00:56:38,926
healthcare, right, which in the,
uh, which is I think good for 

1084
00:56:38,926 --> 00:56:43,027
doctors and good for us. 
Yeah, I like your maybe slogan, 

1085
00:56:43,027 --> 00:56:44,715
right? 
Cut and create, right? 

1086
00:56:44,955 --> 00:56:47,397
So I think what you mentioned 
also, like cut doesn't mean 

1087
00:56:47,397 --> 00:56:49,836
always cut the number of 
employees, the number of roles, 

1088
00:56:49,836 --> 00:56:51,919
right? 
It could be efficiency like 

1089
00:56:51,919 --> 00:56:55,784
workflows, tasks, mundane thing 
that you used to do maybe by 

1090
00:56:55,784 --> 00:56:59,345
hand or something like that. 
But now you can actually kind of

1091
00:56:59,345 --> 00:57:01,603
like use AI to augment the 
capability, right? 

1092
00:57:01,663 --> 00:57:04,215
And I think I love the example 
you mentioned about doctors, 

1093
00:57:04,215 --> 00:57:06,545
right? 
Like simply because they need to

1094
00:57:06,545 --> 00:57:09,592
type in the past, right? 
That kind of like burdens the 

1095
00:57:09,592 --> 00:57:10,812
responsibility of a doctor, 
right? 

1096
00:57:11,142 --> 00:57:14,279
And kind of like consume some, 
you know, cognitive load 

1097
00:57:14,279 --> 00:57:16,142
whenever they diagnose a 
patient, right? 

1098
00:57:16,142 --> 00:57:19,211
So I think that is a good 
possibility where AI can 

1099
00:57:19,211 --> 00:57:20,719
actually improve our cognitive 
ability. 

1100
00:57:21,409 --> 00:57:23,764
And I think creation is also 
another thing that I find. 

1101
00:57:24,479 --> 00:57:28,509
Once people realize the power of
them being able to create a lot 

1102
00:57:28,509 --> 00:57:31,745
more new things just by, you 
know, partnering with AI and all

1103
00:57:31,745 --> 00:57:34,777
that, I think that will re, that
will somehow feel the 

1104
00:57:34,777 --> 00:57:36,479
excitement, I feel, rather than 
fear. 

1105
00:57:36,719 --> 00:57:37,839
Just like what you mentioned, 
right? 

1106
00:57:37,879 --> 00:57:41,399
The people who play the least 
with AI is the one who fear the 

1107
00:57:41,399 --> 00:57:45,179
most about their job security. 
So I think by playing around and

1108
00:57:45,179 --> 00:57:48,205
create more, I think you will 
get this excitement, which I 

1109
00:57:48,205 --> 00:57:52,185
find some people may need to try
more in order to feel the 

1110
00:57:52,185 --> 00:57:54,169
benefit. 
The last section of this 

1111
00:57:54,169 --> 00:57:57,201
conversation, I wanna touch on a
little bit about your mission to

1112
00:57:57,201 --> 00:58:01,615
actually train leaders to be 
more like AI, you know, native 

1113
00:58:01,615 --> 00:58:04,189
leaders, right? 
And you have even the 

1114
00:58:04,189 --> 00:58:06,525
certification called pro-FAI 
from Section, right? 

1115
00:58:06,735 --> 00:58:08,525
Uh, ProfAI. 
Prof-AI. 

1116
00:58:08,595 --> 00:58:11,100
Prof AI. 
Yeah, to actually, um, train 

1117
00:58:11,100 --> 00:58:13,381
people. 
So tell us about this, I don't 

1118
00:58:13,381 --> 00:58:16,304
know, like certification or what
kind of education that you 

1119
00:58:16,304 --> 00:58:21,085
think, uh, leaders need to take 
on in order for them to be ready

1120
00:58:21,085 --> 00:58:22,944
to be AI native leaders? 
Yeah. 

1121
00:58:23,154 --> 00:58:27,713
Uh, so ProfAI is a good example,
I think, of AI powered education

1122
00:58:27,713 --> 00:58:32,084
and how amazing it is. 
So we built a course catalog, we

1123
00:58:32,084 --> 00:58:34,836
built a whole bunch of AI 
classes, and they're good 

1124
00:58:34,836 --> 00:58:36,870
classes. 
You know, we were early, you 

1125
00:58:36,870 --> 00:58:40,388
know, before LinkedIn and before
Coursera and before, you know, 

1126
00:58:40,388 --> 00:58:43,125
Udemy, Udacity. 
We were fast to build out an AI 

1127
00:58:43,125 --> 00:58:43,950
curriculum. 
And that was great. 

1128
00:58:43,950 --> 00:58:45,840
It was good for us for the first
couple years. 

1129
00:58:46,589 --> 00:58:49,945
But the reality is education, 
almost all education today is 

1130
00:58:49,945 --> 00:58:53,520
one size fits all whether it be 
at high school or college or, 

1131
00:58:53,520 --> 00:58:55,590
you know, upskilling corporate 
training. 

1132
00:58:55,590 --> 00:58:58,548
It's like you make a course, you
make a training experience, and 

1133
00:58:58,548 --> 00:59:01,825
then everybody experiences the 
same experience, which really is

1134
00:59:01,825 --> 00:59:05,753
not very good, you know? 
It's, it is okay, but it's not 

1135
00:59:05,753 --> 00:59:09,331
great. 
AI powered education is mind 

1136
00:59:09,331 --> 00:59:12,819
blowing. 
It takes your breath away the 

1137
00:59:12,819 --> 00:59:17,025
first time you experience an AI 
powered learning experience. 

1138
00:59:17,614 --> 00:59:21,563
It's amazing! 
Because if it's a well built 

1139
00:59:21,563 --> 00:59:25,657
learning experience using AI, it
immediately customizes the 

1140
00:59:25,657 --> 00:59:28,239
learning experience for the 
student. 

1141
00:59:28,909 --> 00:59:33,559
So a year ago, a year and a half
ago, I realized I needed to use 

1142
00:59:33,559 --> 00:59:36,069
AI to build an AI learning 
experience. 

1143
00:59:36,399 --> 00:59:38,649
And so we started building 
ProfAI. 

1144
00:59:38,649 --> 00:59:44,193
ProfAI is an AI application. 
It's built on top of ChatGPT and

1145
00:59:44,193 --> 00:59:46,722
Anthropic Claude. 
We use their APIs. 

1146
00:59:46,992 --> 00:59:51,949
So the experience is powered by 
AI and it teaches you how to 

1147
00:59:51,949 --> 00:59:55,041
become AI proficient. 
It teaches you how to find your 

1148
00:59:55,041 --> 00:59:58,315
own use cases. 
It coaches you on what workflows

1149
00:59:58,315 --> 01:00:01,227
that you know you can use AI 
for. 

1150
01:00:01,527 --> 01:00:04,137
And it does all that 'cause you 
tell it where you work. 

1151
01:00:04,227 --> 01:00:07,911
You tell it the job you're in, 
the company you're in, the 

1152
01:00:07,911 --> 01:00:10,092
location. 
You're in Singapore, you're in 

1153
01:00:10,092 --> 01:00:12,673
Hong Kong, you're in London, 
doesn't matter. 

1154
01:00:12,703 --> 01:00:16,099
By the way, ProfAI is already in
eight languages, and we will 

1155
01:00:16,099 --> 01:00:19,583
soon have many more. 
Like we're using that power of 

1156
01:00:19,583 --> 01:00:22,753
AI to teach people AI. 
It's always available. 

1157
01:00:22,753 --> 01:00:27,073
It's basically an AI coach for 
people who need coaching. 

1158
01:00:27,073 --> 01:00:28,573
And I think we all do need 
coaching. 

1159
01:00:28,603 --> 01:00:30,823
There's only 1% of us who are AI
experts. 

1160
01:00:31,243 --> 01:00:32,623
Uh, the rest of us need the 
coaching. 

1161
01:00:32,683 --> 01:00:36,167
So I'll never make another video
class again. 

1162
01:00:37,187 --> 01:00:40,634
Why would I? 
Anybody who's making, anybody, 

1163
01:00:40,634 --> 01:00:44,633
anybody who thinks we're gonna 
be learning the way we learn 

1164
01:00:44,633 --> 01:00:48,533
today in five years, really has 
no idea what's going on right 

1165
01:00:48,533 --> 01:00:51,093
now. 
And they have no real 

1166
01:00:51,093 --> 01:00:54,251
appreciation for the power of 
learning experiences that are 

1167
01:00:54,251 --> 01:00:58,102
powered by AI. 
So, uh, yeah, we love ProfAI, 

1168
01:00:58,102 --> 01:01:00,596
obviously. 
Uh, it's free for consumers. 

1169
01:01:00,656 --> 01:01:05,162
So if you go to prof.ai, you can
get ProfAI for free, as a 

1170
01:01:05,162 --> 01:01:07,581
consumer, as an individual. 
We are charging, obviously teams

1171
01:01:07,581 --> 01:01:10,866
and companies have to pay for 
it, for their, you know, for 

1172
01:01:10,866 --> 01:01:14,729
their organizations. 
Again, I think, if you play with

1173
01:01:14,729 --> 01:01:18,615
ProfAI, you'll realize all of 
learning will move in this 

1174
01:01:18,615 --> 01:01:22,315
direction, meaning we'll teach 
everything using AI assistants 

1175
01:01:22,315 --> 01:01:25,551
or agents. 
And the value of that is they 

1176
01:01:25,551 --> 01:01:28,969
will know who you are and 
they'll be able to test you, 

1177
01:01:28,969 --> 01:01:33,289
assess your competency, and then
only teach you what you need to 

1178
01:01:33,289 --> 01:01:35,875
know. 
And you won't have to sit 

1179
01:01:35,875 --> 01:01:39,183
through a 30 minute video to 
watch five minutes that you care

1180
01:01:39,183 --> 01:01:41,910
about, you know. 
You're not gonna have to spend 

1181
01:01:41,910 --> 01:01:45,223
an hour on YouTube finding the, 
you know, the two best videos to

1182
01:01:45,223 --> 01:01:46,961
watch. 
It's such a waste of time. 

1183
01:01:47,351 --> 01:01:49,391
We'll never do that again in the
future. 

1184
01:01:50,241 --> 01:01:52,599
Right. 
So I hope you're successful in 

1185
01:01:52,599 --> 01:01:55,935
your mission to train more 
people to be more AI kind of 

1186
01:01:55,935 --> 01:01:58,722
like savvy. 
So Greg, it's been a great 

1187
01:01:58,722 --> 01:02:00,192
conversation. 
I only have one last question 

1188
01:02:00,192 --> 01:02:03,092
that I would like to ask you. 
This is kind of like a tradition

1189
01:02:03,092 --> 01:02:05,826
in my podcast, which I call the 
question the three technical 

1190
01:02:05,826 --> 01:02:08,064
leadership wisdom. 
Doesn't have to be tech, but 

1191
01:02:08,064 --> 01:02:11,563
it's more like leadership thing.
Um, so if you can give this 

1192
01:02:11,563 --> 01:02:14,619
advice to us listeners, uh, what
will be the version of your 

1193
01:02:14,619 --> 01:02:15,865
three technical leadership 
wisdom? 

1194
01:02:17,681 --> 01:02:20,707
I don't know if I have three. 
Uh, I have one to start. 

1195
01:02:21,884 --> 01:02:26,367
It's all about doing what you 
ask others to do. 

1196
01:02:27,717 --> 01:02:30,187
And that doesn't mean you have 
to be able to do their job. 

1197
01:02:31,327 --> 01:02:35,305
But if you want your employees 
to be empathetic, if you want 

1198
01:02:35,305 --> 01:02:38,793
your employees to be committed, 
if you want your employees to 

1199
01:02:38,793 --> 01:02:42,641
have care for quality, uh, have 
care for customers, if you have 

1200
01:02:42,641 --> 01:02:46,035
standards that you want your 
organization to meet, you must 

1201
01:02:46,035 --> 01:02:48,087
meet them. 
You must do all of that. 

1202
01:02:48,087 --> 01:02:49,317
You must treat them with 
empathy. 

1203
01:02:49,317 --> 01:02:53,264
If you want your organization to
be AI enabled, you must be AI 

1204
01:02:53,264 --> 01:02:56,753
enabled. 
I see so much inauthentic 

1205
01:02:56,753 --> 01:03:00,793
leadership and frankly, our 
employees see that. 

1206
01:03:02,253 --> 01:03:07,279
And so, and that's when the 
trust breaks and that's when 

1207
01:03:07,279 --> 01:03:09,955
the, you know, the alignment 
breaks. 

1208
01:03:09,955 --> 01:03:14,789
We, as leaders, we have to live 
our truth as leaders and lead 

1209
01:03:14,789 --> 01:03:17,301
the way we want our organization
to behave. 

1210
01:03:18,441 --> 01:03:21,940
So, um, you know, walk the walk.
Okay. 

1211
01:03:22,220 --> 01:03:23,910
Anything else or that's uh, 
that's it? 

1212
01:03:24,147 --> 01:03:25,647
That's it. 
That's hard. 

1213
01:03:26,107 --> 01:03:28,227
Henry, one's enough. 
Do that. 

1214
01:03:28,407 --> 01:03:32,456
'Cause here's the thing. 
You don't do it five days a 

1215
01:03:32,456 --> 01:03:35,655
year. 
The reason this is so hard is 

1216
01:03:35,655 --> 01:03:40,525
you have to do it every day. 
Leadership is not a, the- you 

1217
01:03:40,525 --> 01:03:42,825
know. 
We have this archetype or myth 

1218
01:03:42,825 --> 01:03:44,549
of leadership. 
Steve Jobs, right? 

1219
01:03:44,759 --> 01:03:49,607
These moments of high drama, 
these moments of high impact 

1220
01:03:49,607 --> 01:03:52,764
leadership, the product 
announcement or, you know, the 

1221
01:03:52,764 --> 01:03:55,829
that's what sort of, that's the 
myth of leadership. 

1222
01:03:56,619 --> 01:03:58,719
Same for military leadership, 
right? 

1223
01:03:58,719 --> 01:04:01,839
The single moment. 
That's not leadership. 

1224
01:04:03,126 --> 01:04:07,701
Leadership is everything that 
happens every day that no one 

1225
01:04:07,701 --> 01:04:09,567
sees. 
Wow! 

1226
01:04:09,567 --> 01:04:14,449
So I only offer one piece of 
advice because it's a very hard 

1227
01:04:14,779 --> 01:04:18,773
piece of advice to actually do. 
Very nicely put. 

1228
01:04:18,893 --> 01:04:21,713
I think it's a great reminder 
for all leaders out there, you 

1229
01:04:21,713 --> 01:04:24,957
need to walk your talk, right? 
So it's not like, okay, please 

1230
01:04:24,957 --> 01:04:28,044
do this, but you don't embody 
the behavior, you don't embody 

1231
01:04:28,044 --> 01:04:31,881
the thing that you're preaching.
We all can see if leaders are 

1232
01:04:31,881 --> 01:04:33,901
inauthentic, right? 
And that's where probably the 

1233
01:04:33,901 --> 01:04:37,625
trust breaks and you kind of 
like don't actually follow fully

1234
01:04:37,625 --> 01:04:41,132
from the leaders. 
So I think, yeah, please be, try

1235
01:04:41,132 --> 01:04:44,736
our best to be more authentic. 
Uh, walk the talk and embody the

1236
01:04:44,736 --> 01:04:46,563
kind of spirit that you actually
preaching. 

1237
01:04:47,043 --> 01:04:49,413
So Greg, I think it's a great 
conversation. 

1238
01:04:49,413 --> 01:04:54,011
I learned a lot about how to use
AI more, uh, and people here I'm

1239
01:04:54,011 --> 01:04:57,051
sure they're kind of like 
inspired as well to try some of 

1240
01:04:57,051 --> 01:04:58,503
the things that you mentioned 
today. 

1241
01:04:58,653 --> 01:05:01,747
If people want to follow you or 
ask you more questions, is there

1242
01:05:01,747 --> 01:05:03,453
a place where they can reach out
online? 

1243
01:05:04,735 --> 01:05:06,260
Uh, yeah, sure. 
Just on LinkedIn. 

1244
01:05:06,260 --> 01:05:09,150
They can find my LinkedIn, Greg 
Shove, on LinkedIn. 

1245
01:05:09,150 --> 01:05:12,819
Or go to prof.ai to get their 
access to an AI coach. 

1246
01:05:13,403 --> 01:05:16,073
Or go to sectionai.com and you 
can find me. 

1247
01:05:16,133 --> 01:05:20,662
Uh, yeah, I'll do whatever I can
to help anyone prepare 

1248
01:05:20,662 --> 01:05:23,623
themselves to thrive in the age 
of AI. 

1249
01:05:24,277 --> 01:05:26,250
Yeah. 
And I wanna mention as well, 

1250
01:05:26,250 --> 01:05:30,244
Greg here is, uh, picked as like
one of the top AI creators in 

1251
01:05:30,244 --> 01:05:33,172
2025 by Edelman. 
So definitely you can follow 

1252
01:05:33,172 --> 01:05:36,577
Greg on social media or wherever
you create, uh, including your 

1253
01:05:36,577 --> 01:05:38,534
newsletter, Personal Math. 
Yep. 

1254
01:05:38,677 --> 01:05:40,564
Right? 
So I find some great pieces that

1255
01:05:40,564 --> 01:05:43,408
you wrote before. 
So I think, uh, definitely check

1256
01:05:43,408 --> 01:05:45,745
out Greg's resources. 
So thank you so much, uh, for 

1257
01:05:45,745 --> 01:05:47,527
the time, Greg. 
Uh, it's been a pleasant 

1258
01:05:47,527 --> 01:05:49,304
conversation. 
Yeah, likewise Henry. 

1259
01:05:49,304 --> 01:05:50,054
Thanks for inviting me.