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Hi, everyone.
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Welcome to another episode.
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AI is moving at a rapid pace, and most
organizations are using AI to move faster, to
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create more efficiencies in the organizations,
and create better workflows.
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My guest today, she helps companies to turn
reliable systems into...
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To turn their deep expertise into reliable
systems, what's made their company successful
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in the first place.
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My guest today, Laura Des Gant, she helps
founder led businesses adopt AI without losing
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judgment, culture, and the trust, which has
made them successful in the first place.
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As a fractional AI chief sustainability and
impact officer, she builds human centered AI
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systems that preserves institutional knowledge,
supports better decisions, and creates the
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continuity across teams.
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Her work isn't about chasing AI trends.
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Rather, it's about turning their deep expertise
into reliable systems that can help them grow
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and create more impact.
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Please give a warm welcome to Lourdes Gant.
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Hi, Lourdes.
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Thank you very much for having me.
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That was such a generous words for the
introduction.
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Thank you so much.
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Oh, you're very welcome.
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Well, let's start by what does it actually mean
to adopt AI without losing the soul of the
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business?
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Great question.
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I believe
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that from my almost twenty years of being in
sustainable seafood aquaculture, I have gained
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to realize that a lot of the knowledge and
judgment are buried inside the founder's head.
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And so one of the things that we've been
learning now with these new AI tools is to be
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able to preserve that judgment when no one is
able to do it because some...
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Most of the time, the founders become a
bottleneck.
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And to be able to do that, we need to go
through their searchable systems, playbooks,
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and, obviously, AI supported assistance so that
the teams can move when they are not available.
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Right.
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Absolutely.
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And, also, AI shouldn't erase the the human
aspect, which is what most people do have a
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fear that AI is going to erase humans.
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Right?
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So that...
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That's that's the one fear most people do have.
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I think there's, as you know, a lot of words
after the AI era that come about, and one of
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them is amplifying humans.
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And I belong into an EdTech group wherein we
always say artificial intelligence plus human
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equals superhuman.
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And so fascinating enough, you and I were just
in Egypt to have a speaking engagement there.
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And on my way back to Canada, was listening to
another podcast on how OpenAI came about as its
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history.
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And one of the founders actually was sharing
how when ChatGPT started, he decided to give
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all of the conversations, all of the chats that
he and his mom did, and then the mom died.
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And then at the time that chat...
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And then the chat GPT, after he actually put in
all those conversation, he started to talk to
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the bot like his mom was alive, and he was
cry...
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He was crying of what the message would be when
he asked the question of what would I do now
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now that you're not here anymore?
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And because of all the context that the AI was
trained on how to reply like his mom, he almost
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felt like his mom was there.
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So...
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And he said, you know, it's kinda weird and
bad, but also good at the same time.
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And I'm sure anybody can relate to this wherein
what
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do you think can happen if we put together all
of these brilliant minds and talk to and talk
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to them on how they can help us today.
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I think this is what the AI era has done for
us.
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It amplifies us.
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Absolutely.
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I do agree.
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And there were so many AI tools as we know.
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With this new tool that our mentor has come out
with with the JT five, this is only, I mean, as
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we were on the call, it is so exciting being in
this AI era.
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I'm I'm very grateful.
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I'm excited to know as to what is the future of
AI and especially with AI, you know, employees
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and the humans AI.
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This is what it's all about and how we don't
need to be fearful, but we need to embrace
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every aspect of what's happening with AI.
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It's a wonderful, wonderful invention.
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I came to believe that every time we have
something new, there will always be a group of
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people who are gonna be early adapters like you
and I, but there will also be people who are
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gonna be scared of it and rightfully so.
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I think of it like when fire was invented.
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The fire can either burn you or it can give you
warmth during the winter.
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So the same is true for me in terms of AI tools
and technology.
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This can become one of the greatest invention
in modern history, or it can be one that can
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doom humanity.
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You know?
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That that...
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Exactly.
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That is so true.
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In your view, in that case, Lourdes, what would
you say separates the the the trends as opposed
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to the AI adoption and AI implementation to to
give enterprise more control and authority in
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the organization?
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What would you say?
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It's a very good question and also hard to
answer because I believe that this technology
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has given small to medium businesses a level
playing field.
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So as you know, now you can have in your
fingertips a 6 figure CEO, maybe even, like, an
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8 figure executive team without having to pay
for the price.
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This is one of the things that democratized, I
guess, the salaries of people who have all that
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knowledge and now can be compacted into one AI
executive team.
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I remember, four years ago...
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Where are we now?
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2026.
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Yeah.
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Four four years ago, twenty twenty two one was
obviously in November was when ChatGPT was
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launched.
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But even before them, one of the other group
that I was in was already talking about this
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whole executive team that are made up of AI.
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I remember speaking in an aquaculture
conference in Melbourne, Australia in 2022, and
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one of the things that I presented there was
future trends.
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And I said Mhmm.
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There will come a time next year.
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This was 2022.
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Right?
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This was exactly July 2022.
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And I said next year, everybody will have an AI
CEO.
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And I I have, like, in the audience, and, like,
it's unbelievable.
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And now everybody has it.
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Right?
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And so it's just a matter of time.
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And so it's fascinating in terms of what the
trends that you're going to ride because you
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can't avoid it.
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You know?
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Imagine you're surfing.
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Are you going to be drowned?
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And in school, we were taught it's either you
sink or you swim, but they didn't they didn't
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teach us how to actually surf.
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And so the same can be said in the AI area.
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It's either you surf with the wave of this
technology to catapult you to what benefits it
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brings us or you sink or you swim.
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So to me Right.
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I've always been connected with people who are
futuristic.
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And as you mentioned, in our community with JT,
it has been, like, our nine figure brain
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originally that became, like, a core brain and
JT one wherein we have all these 16 brains that
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help us in our business.
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This is unheard of in Right.
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Business has always been like, you gain benefit
with your...
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Either with your own work or with the people
around you, but now we have to amplify this
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with technology.
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So I hope that answers your question.
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I kinda went roundabout way.
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No.
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Absolutely.
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Yes.
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It does.
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Yes.
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Exactly.
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And talking about you help founder led
businesses.
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So if a if a founder wants to adopt AI, but
they have a fear of losing control as most most
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founders do, but they have a fear of losing
control and the judgment or...
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What would you say?
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What would you say would be the first move that
they would have to make?
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I remember I I remember talking about this in
Aristen, and I have a formula for this on how
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we do this in three simple moves that are easy
to remember.
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If you remember what I said, it's find it,
repeat it, and ask it.
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So...
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But it's a very good question in terms of,
like, what if you didn't wanna lose control?
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I think even before I go through the three
simple moves of find it, repeat it, and ask it,
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I think the very first thing that founders need
to ask themselves is, are they actually really
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ready to go to go to the next level or or not?
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I don't know if you know the book, Small
Giants.
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There's a story there of several businesses who
have an opportunity to become bigger, but they
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chose to be small.
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Like I mentioned to you, our family firm is
kind of a...
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How do you say it?
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We're in a...
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We're very small in a very big pond, but we're
actually big in a small pond.
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And so the book on small giants talk about
this, that founders decided that they're just
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gonna become small giants because their culture
is gonna go away if they ended up being
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acquired or that their people are gonna change
the way that they do business if they ended up
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being with a new...
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Let's just say a venture capitalist.
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And so
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Mhmm.
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That's the very first question I asked them.
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Do you really wanted to go to the next level,
or you just wanna keep things as it is?
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Because they may not wanna employ technology to
be able Right.
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To scale up.
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They were happy with where where they are.
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But if they wanted to scale, if they wanted to
sell their business, if they wanted to exit,
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these are the three simple moves that I
mentioned.
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So find it.
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Right?
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So find what are these decisions that are hinge
on their founder.
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So I often said, it's not because the other
people in the team members doesn't know what to
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say.
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It's just that they have the history and the
experience of what it was like to decide on
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something because they have been in the
industry for so long.
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For case in my husband and my founder has been
in the aquaculture industry for thirty years.
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I joined them, as I mentioned, in the family
from twenty years ago.
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And so when I was first starting in that...
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Those first ten years, I asked him a lot of
questions.
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I didn't know what to answer just because I'm
new.
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So it's not because I I didn't know the answer.
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It's just there's no experience.
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Like, as you said, you know, experience is the
best teacher.
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So those are the things those are the things
that you need to find.
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So second is repeat it.
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Right?
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So the next step would be how can you create
playbooks so that these decisions, these
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relationships, whatever that experience can be
captured?
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And I'm just talking about playbooks.
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So in terms of standard operating procedures or
standard operating guidelines, can you capture
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all those so that you can actually repeat
without the founder being available?
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And then last and not the least would be ask
it. The
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The team should be able to use this technology
with AI.
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Know, they can ask the AI when the founder is
not there so that it will have the same
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decisions as if the founder is there.
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So there you have it.
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Exactly.
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No.
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That's amazing.
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And and there's gotta be a point where, you
know, the founders, have to be absent.
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They can be absent, and they have the team
running.
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So, Lord, is in in that case, are we building
AI systems that serve the business, or are we
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building AI systems to to redesign the
technology?
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That's a very good question in
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terms of what is it that they wanted to
accomplish.
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I think it hinges again on what are they
envisioning that these tools are gonna be able
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to help them with.
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So, for example...
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Right?
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So there's a lot of talk about workflows, but
what is that really?
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Right?
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Exactly.
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Explain to
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the audience.
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What is the workflows?
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So case in point, in our hatchery, as I
mentioned, we're in sustainable seafood
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aquaculture.
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In our hatchery, a workflow of production...
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And I'm gonna go a little bit technical, so
bear with Yes.
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No.
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Sure.
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Go ahead.
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Yes.
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Our shellfish, the workflow would
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be
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we get the parent animals, we call brood stock
from the ocean, and then that's step one.
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And then we bring them to the hatchery.
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We spawn them.
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And then after several months that they spawn,
we bring them to the primary nursery system
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just like a baby.
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And then they reach a certain size, then we
bring them to the secondary nursery system
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00:13:43,754 --> 00:13:46,715
before we bring them back into the farm.
241
00:13:46,950 --> 00:13:50,149
So that's a workflow in our production system.
242
00:13:50,389 --> 00:13:55,190
And so what is that for a certain company in a
certain industry?
243
00:13:55,190 --> 00:13:57,269
This was our shellfish production flow.
244
00:13:57,269 --> 00:13:57,669
Mhmm.
245
00:13:57,669 --> 00:14:04,664
So for you, for example, if that's product
based, if you are service based, workflow can
246
00:14:04,664 --> 00:14:05,945
be consist of...
247
00:14:06,504 --> 00:14:11,865
You have a pipeline that you're looking at,
meaning who are the people that you wanted to
248
00:14:11,865 --> 00:14:13,144
solve problems for.
249
00:14:14,105 --> 00:14:19,250
Let's just say, for example, in the context of
our conversation, you're solving the problem
250
00:14:19,250 --> 00:14:19,809
of...
251
00:14:19,809 --> 00:14:25,009
In your field, having visibility and
credibility for branding strategy.
252
00:14:25,250 --> 00:14:25,649
Mhmm.
253
00:14:25,649 --> 00:14:31,169
And so a workflow can become, you have a
pipeline, you build relationship with the
254
00:14:31,169 --> 00:14:36,044
pipeline, and then you build the foundation of
how you can work together to solve the problem
255
00:14:36,044 --> 00:14:42,845
so that the coach, the executive team, or a
founder and CEO can have better visibility
256
00:14:42,845 --> 00:14:44,204
slash credibility.
257
00:14:44,204 --> 00:14:45,644
That is a workflow for me.
258
00:14:46,070 --> 00:14:51,429
How you execute that depends on your, I call
it, signature system or unique method.
259
00:14:51,429 --> 00:14:51,990
Right?
260
00:14:52,070 --> 00:14:52,470
Right.
261
00:14:52,470 --> 00:14:55,830
So it can be, like, your signature system can
be...
262
00:14:56,070 --> 00:14:56,549
I don't know.
263
00:14:56,549 --> 00:14:59,029
You know better this field than I do.
264
00:14:59,029 --> 00:15:03,565
But I think people will know that is an example
of a workflow.
265
00:15:03,565 --> 00:15:03,804
Right?
266
00:15:03,804 --> 00:15:08,044
So I I just say one is product based and one
that's service based.
267
00:15:08,044 --> 00:15:09,004
Service based.
268
00:15:09,004 --> 00:15:09,725
Alright.
269
00:15:09,725 --> 00:15:11,485
So how AI comes into this?
270
00:15:11,485 --> 00:15:16,285
Like, so with technology, these workflows can
now be automated and mechanized.
271
00:15:16,360 --> 00:15:20,679
For example, one of the things that we're
looking into in our production would have been,
272
00:15:21,960 --> 00:15:25,399
what if we have actually a seeding machine?
273
00:15:25,639 --> 00:15:31,065
So right now, we're seeding all these little
baby gooey ducks slash shellfish with the
274
00:15:31,065 --> 00:15:31,785
diver.
275
00:15:31,865 --> 00:15:32,825
They go down there.
276
00:15:32,825 --> 00:15:33,625
Oh, wow.
277
00:15:33,625 --> 00:15:37,625
And then they scattered all the seed, and
there's very apple...
278
00:15:37,625 --> 00:15:40,345
Johnny apple seed, to be honest with you.
279
00:15:41,440 --> 00:15:43,600
But that's why we wanted to automate it.
280
00:15:43,600 --> 00:15:48,800
So we're looking into how can we actually
consistently have the same number of seed in a
281
00:15:48,800 --> 00:15:51,440
certain square meter out in the ocean.
282
00:15:51,440 --> 00:15:52,720
So we're thinking, okay.
283
00:15:52,800 --> 00:15:55,440
Technology can come into place with the seeding
machine.
284
00:15:55,440 --> 00:15:56,000
Or Mhmm.
285
00:15:56,000 --> 00:16:00,514
Once they they reach a certain market size, we
are looking into a harvesting machine.
286
00:16:00,514 --> 00:16:02,435
Because, again, right now, it's very manual.
287
00:16:02,514 --> 00:16:03,795
We pay our divers...
288
00:16:03,795 --> 00:16:09,075
The biggest actually expense in our profit and
loss statement is actually diver slash
289
00:16:09,075 --> 00:16:13,839
contractors because we pay them $2,000 a day
for a boat day.
290
00:16:14,000 --> 00:16:15,839
And so AI come into the place.
291
00:16:15,839 --> 00:16:18,399
What if we can actually have a harvesting
machine?
292
00:16:18,480 --> 00:16:20,959
So I think when people think about AI, when
think...
293
00:16:20,959 --> 00:16:27,665
People think about robot, they think about,
like, AI as this invisible technology.
294
00:16:27,665 --> 00:16:34,865
It it can be, but it can also be like a farmer
uses a certain machine that's run by robotics.
295
00:16:34,865 --> 00:16:37,105
Doesn't necessarily have to do with, like,
robot.
296
00:16:37,190 --> 00:16:39,509
So I think I think you get what I mean.
297
00:16:39,589 --> 00:16:39,909
No.
298
00:16:39,909 --> 00:16:40,470
I do.
299
00:16:40,470 --> 00:16:41,350
I understand.
300
00:16:41,429 --> 00:16:42,870
And, also, it's very...
301
00:16:43,429 --> 00:16:44,549
I I would say...
302
00:16:44,549 --> 00:16:51,665
And also the audience listening as opposed to,
you know, service based, you know, AI in
303
00:16:51,665 --> 00:16:52,865
service based, yes.
304
00:16:52,865 --> 00:16:54,945
So we know that how AI can play.
305
00:16:54,945 --> 00:17:03,879
But but in your industry with the the ocean
fish that, you know, with sustainability, it's
306
00:17:03,879 --> 00:17:04,599
not very...
307
00:17:04,599 --> 00:17:08,279
It's not heard of as to how AI can fully...
308
00:17:08,599 --> 00:17:12,759
How you can integrate and how it can fully just
amplify your business.
309
00:17:13,079 --> 00:17:15,400
So right now, you're doing it manually.
310
00:17:15,400 --> 00:17:15,559
Yes?
311
00:17:17,244 --> 00:17:18,765
There's there's a combination.
312
00:17:18,765 --> 00:17:19,804
We It's a combination.
313
00:17:19,804 --> 00:17:20,125
Okay.
314
00:17:20,125 --> 00:17:20,605
Yeah.
315
00:17:20,605 --> 00:17:26,845
So there's a combination of the same thing as
just any other industry we're in.
316
00:17:26,845 --> 00:17:27,244
You know?
317
00:17:27,244 --> 00:17:32,589
We obviously have to take care of press
releases, social media management.
318
00:17:33,150 --> 00:17:35,789
That's, like, the same as, like, any industry.
319
00:17:35,789 --> 00:17:36,029
Right?
320
00:17:36,029 --> 00:17:38,269
You have somebody who can create content for
you.
321
00:17:38,269 --> 00:17:41,869
You have the educational assets like the
podcast we're doing.
322
00:17:41,869 --> 00:17:42,670
So that's the same.
323
00:17:42,670 --> 00:17:48,755
We have AI slash maybe a content creator that's
an AI.
324
00:17:48,755 --> 00:17:49,154
Right?
325
00:17:49,154 --> 00:17:50,275
That's one example.
326
00:17:50,595 --> 00:17:51,474
So for...
327
00:17:51,875 --> 00:17:53,474
And same for marketing.
328
00:17:53,474 --> 00:17:55,315
Maybe you're using for marketing and sales.
329
00:17:56,259 --> 00:18:02,419
Claude, for example, can research your pipeline
wherein it can automatically actually send
330
00:18:02,419 --> 00:18:08,980
people emails in your local area if they're
interested in some AI workflow slash
331
00:18:08,980 --> 00:18:09,940
implementation.
332
00:18:09,940 --> 00:18:10,419
Right?
333
00:18:10,419 --> 00:18:10,980
Uh-huh.
334
00:18:10,980 --> 00:18:12,815
So that's what makes...
335
00:18:12,815 --> 00:18:15,215
Or maybe even in bookkeeping or finance and
admin.
336
00:18:15,215 --> 00:18:15,455
Right?
337
00:18:15,455 --> 00:18:20,255
So, like, my bookkeeper my bookkeeper actually
is from The Philippines wherein she...
338
00:18:20,255 --> 00:18:25,220
Before she used to do the bank reconciliation
manually wherein she has to look at the bank
339
00:18:25,220 --> 00:18:30,259
statement and look at all the invoices slash
deposit slips to be able to reconcile the bank
340
00:18:30,259 --> 00:18:30,580
account.
341
00:18:30,580 --> 00:18:33,619
Now she uses AI to be able to find all those.
342
00:18:33,619 --> 00:18:34,180
So it's less...
343
00:18:34,180 --> 00:18:35,220
That's convincing.
344
00:18:35,859 --> 00:18:39,924
So these are just example that is applicable to
all the Right?
345
00:18:39,924 --> 00:18:42,565
Marketing slash sales, finance and admin.
346
00:18:42,565 --> 00:18:42,965
Mhmm.
347
00:18:42,965 --> 00:18:43,445
Mhmm.
348
00:18:43,445 --> 00:18:46,404
Let's just say content creation.
349
00:18:46,644 --> 00:18:48,644
On the other side of things can be production.
350
00:18:48,644 --> 00:18:52,644
Like, what I mentioned, if you're product
based, you have some kind of production
351
00:18:52,644 --> 00:18:55,569
workflow, it can be...
352
00:18:55,569 --> 00:18:57,730
We're using sensors in our hatchery.
353
00:18:57,730 --> 00:18:59,409
And when I say that, it can be...
354
00:18:59,490 --> 00:19:01,409
As you know, we're based in Canada.
355
00:19:01,409 --> 00:19:06,609
And so we actually have a small building that
has all the equipment that actually tell the
356
00:19:06,609 --> 00:19:10,289
animals, like, it's summer when it's winter and
it's winter when it's summer.
357
00:19:10,654 --> 00:19:16,654
So these are just some different kind because
it's production based, and we also have, like,
358
00:19:16,974 --> 00:19:19,134
measuring the salinity of the water.
359
00:19:19,214 --> 00:19:23,855
So very important in terms of how salty can the
water be.
360
00:19:23,855 --> 00:19:26,255
Does that help the animal grow faster or not?
361
00:19:26,390 --> 00:19:29,269
So we have sensors to actually do measure this.
362
00:19:29,430 --> 00:19:35,110
Or if there's actually a blackout and power is
actually gone Mhmm.
363
00:19:35,190 --> 00:19:43,365
That that really affects of the animals die
overnight because they got cold because Right.
364
00:19:43,365 --> 00:19:44,804
There's no electricity.
365
00:19:44,884 --> 00:19:52,724
So we got sensors and automatic generator that
comes on if, again, powered by technology to be
366
00:19:52,724 --> 00:19:54,004
able to get that monitored.
367
00:19:54,700 --> 00:19:55,500
Exactly.
368
00:19:55,500 --> 00:20:00,619
Well well, with the ocean, you do have to make
sure that, you know, the fish and...
369
00:20:01,019 --> 00:20:04,779
You have to monitor that on a regular basis to
to make sure.
370
00:20:05,820 --> 00:20:09,820
In fact, in this case, how do we make sure,
Lordas, we...
371
00:20:10,755 --> 00:20:16,274
How do we make sure AI actually amplifies the
company's principles?
372
00:20:16,595 --> 00:20:19,394
You you help the founder and businesses.
373
00:20:19,394 --> 00:20:29,460
So how do you how do you make sure that the AI
is actually amplifying the company's principles
374
00:20:29,700 --> 00:20:32,420
rather than flatlining them?
375
00:20:33,220 --> 00:20:34,500
Hard question, Alka.
376
00:20:34,500 --> 00:20:39,025
But, let's see if I can put this in the
perspective that's easy to actually follow.
377
00:20:39,265 --> 00:20:42,625
So most of the things that we do in our
company...
378
00:20:43,105 --> 00:20:47,904
Mostly because my husband slash business
partner has been in this industry ten thousand
379
00:20:47,904 --> 00:20:51,904
hours under the water as a commercial
fisherman, have seen the ebbs and flow of this
380
00:20:51,904 --> 00:20:52,305
industry.
381
00:20:52,420 --> 00:20:52,900
Correct?
382
00:20:52,900 --> 00:20:53,220
Mhmm.
383
00:20:53,220 --> 00:20:53,619
Right.
384
00:20:53,619 --> 00:20:58,579
And so to be able to capture that, like, just
between the two of us, there's, like, half a
385
00:20:58,579 --> 00:21:01,619
century of knowledge base.
386
00:21:01,619 --> 00:21:01,940
Right?
387
00:21:01,940 --> 00:21:02,339
Right.
388
00:21:02,339 --> 00:21:02,579
Right.
389
00:21:02,579 --> 00:21:10,164
So to be able to talk about what's in his
brain, what's in his image, what is his voice,
390
00:21:10,164 --> 00:21:15,124
what can be put into video that captures all
that half a century of knowledge.
391
00:21:15,125 --> 00:21:21,169
And so at the beginning that we did this in our
company, I actually have a very thick book that
392
00:21:21,169 --> 00:21:26,529
they had from their original company that
contained all of the experiments that they did
393
00:21:26,609 --> 00:21:29,089
for research and development That's amazing.
394
00:21:29,169 --> 00:21:29,729
Wow.
395
00:21:29,569 --> 00:21:32,289
Introducing the shellfish that they actually
396
00:21:32,849 --> 00:21:35,715
started loving and started to aquaculture.
397
00:21:35,715 --> 00:21:42,434
And so I put in all those knowledge base,
actually, on our AI, and all of all of our
398
00:21:42,434 --> 00:21:48,500
scientific research and experimental
development put into it all of our SOPs, all of
399
00:21:48,500 --> 00:21:52,259
our, basically, protocols in all of the
departments.
400
00:21:52,339 --> 00:21:52,659
Right.
401
00:21:52,659 --> 00:21:55,940
So, Neil, all that r and d, all
402
00:21:55,940 --> 00:22:03,195
of that experimentation are in one file that
captures that if someone is going to present to
403
00:22:03,195 --> 00:22:06,474
me in one department that they're gonna do this
experiment.
404
00:22:06,475 --> 00:22:10,075
I have them go through the AI
405
00:22:10,475 --> 00:22:10,715
Right.
406
00:22:10,715 --> 00:22:12,795
And basically say, has not...
407
00:22:12,795 --> 00:22:14,234
Has this been done before?
408
00:22:14,394 --> 00:22:17,279
Or if it's done before, how can we make it
better?
409
00:22:17,359 --> 00:22:19,519
So it's really easy now to...
410
00:22:19,519 --> 00:22:24,160
One of the things that I have a project on
right now is capturing intellectual property on
411
00:22:24,160 --> 00:22:26,240
the joint venture partnerships that we have.
412
00:22:26,400 --> 00:22:32,265
And so so I just put it in on our AI that has
all of that knowledge base, and it just gives
413
00:22:32,265 --> 00:22:37,785
me, like, a wonderful opportunity to actually
look at what has been done, how can it be
414
00:22:37,785 --> 00:22:39,544
better, and how can we move forward.
415
00:22:39,544 --> 00:22:40,585
So that's just one example.
416
00:22:41,369 --> 00:22:41,769
No.
417
00:22:41,769 --> 00:22:43,450
I I I absolutely love that.
418
00:22:43,450 --> 00:22:45,929
I think that is so true as to, like, how we...
419
00:22:46,250 --> 00:22:53,289
And how we can use AI for multiple, you know,
reasons to, you know, research, as you said.
420
00:22:54,025 --> 00:22:55,785
But that is so fascinating.
421
00:22:55,785 --> 00:23:00,585
And and I'm always curious to know as to that
when it comes to the founder led businesses,
422
00:23:00,585 --> 00:23:01,784
how do we...
423
00:23:01,944 --> 00:23:11,180
How can founder led businesses scale without
the AI becoming generic or is losing the soul
424
00:23:11,180 --> 00:23:12,299
of the company.
425
00:23:12,779 --> 00:23:13,420
Yeah.
426
00:23:13,500 --> 00:23:14,860
And I was gonna say that next.
427
00:23:14,860 --> 00:23:19,740
Like, what about for those companies wherein
they don't have documentation of all this?
428
00:23:19,740 --> 00:23:20,860
So Mhmm.
429
00:23:21,019 --> 00:23:24,779
You can ask the AI to ask you some questions so
that it gets to know you better.
430
00:23:25,164 --> 00:23:29,884
It can be, like, what is your personality
profile?
431
00:23:29,884 --> 00:23:32,045
In the Briggs Myers, I'm ISTJ.
432
00:23:32,045 --> 00:23:32,845
We can put that in.
433
00:23:32,845 --> 00:23:33,164
Okay.
434
00:23:33,164 --> 00:23:35,644
For example, the founder is this personality.
435
00:23:35,964 --> 00:23:37,404
What is his Kolbe profile?
436
00:23:37,404 --> 00:23:40,365
What is his strengths in the StrengthFinder's
Gallup exercise?
437
00:23:40,669 --> 00:23:43,630
Even maybe Enneagram in the disc profile.
438
00:23:43,630 --> 00:23:49,470
Put all those in, and then it can actually
capture the personality of the founder.
439
00:23:49,630 --> 00:23:50,190
So Right.
440
00:23:50,349 --> 00:23:51,869
That's starting from scratch.
441
00:23:51,869 --> 00:23:52,190
Right?
442
00:23:52,190 --> 00:23:55,974
And you even probably hear a lot of people
talking about having a chief of staff.
443
00:23:55,974 --> 00:23:57,174
That's basically what it is.
444
00:23:57,174 --> 00:23:57,414
Right?
445
00:23:57,414 --> 00:24:03,335
So your chief of staff is probably, like, the
AI that thinks, talk, and speak and listen like
446
00:24:03,335 --> 00:24:03,654
you.
447
00:24:03,654 --> 00:24:04,214
Like you.
448
00:24:04,214 --> 00:24:04,694
Yes.
449
00:24:04,615 --> 00:24:07,734
You train it to behave the way that you would
behave.
450
00:24:08,329 --> 00:24:12,009
Just one example was this personality profiles
that you can put in.
451
00:24:12,009 --> 00:24:15,849
And then you give it parameters of what is
acceptable, what's not acceptable.
452
00:24:15,849 --> 00:24:19,289
For example, my AI chief of staff knows all my
brands.
453
00:24:19,289 --> 00:24:20,490
I have quite a bit of brand.
454
00:24:20,490 --> 00:24:24,884
So I have my product brand, which is the Go
Reduck, our shellfish, and I have my personal
455
00:24:24,884 --> 00:24:25,684
brand, obviously.
456
00:24:25,684 --> 00:24:30,484
And I also have a service brand, which is the
AI legacy for founders.
457
00:24:30,644 --> 00:24:31,204
So when
458
00:24:31,845 --> 00:24:37,765
I talk to my AI chief of staff, it's very, very
clear on which brand I'm talking about because
459
00:24:37,765 --> 00:24:41,089
I fed it all of the information that it knows
about me.
460
00:24:41,169 --> 00:24:42,529
And so when having a...
461
00:24:42,529 --> 00:24:44,369
It gives me my daily briefing.
462
00:24:44,609 --> 00:24:47,970
I also give it, like, certain topics that it...
463
00:24:47,970 --> 00:24:50,769
There's certain things that I needed to do on a
daily basis.
464
00:24:51,250 --> 00:24:55,515
Number one was a daily briefing of what my
priorities are for the day, my priorities for
465
00:24:55,515 --> 00:24:58,554
the week on Sunday night, what have I
accomplished on...
466
00:24:58,554 --> 00:24:59,835
At the end of Friday.
467
00:25:00,394 --> 00:25:02,875
And then I have, like, the quarterly focus.
468
00:25:02,875 --> 00:25:05,274
So, like, today today is September 30.
469
00:25:05,274 --> 00:25:09,649
So we're gonna have our last quarter of the
year starting tomorrow.
470
00:25:09,890 --> 00:25:11,009
It gave me, like...
471
00:25:11,009 --> 00:25:15,170
Based on what you've been working on for the
whole year, this should be your focus for the
472
00:25:15,170 --> 00:25:17,009
next last quarter of the year.
473
00:25:17,009 --> 00:25:18,450
So this is just one example.
474
00:25:18,450 --> 00:25:19,089
And then...
475
00:25:19,089 --> 00:25:20,690
You're mentioning about the soul.
476
00:25:20,849 --> 00:25:21,170
Mhmm.
477
00:25:21,170 --> 00:25:29,005
So giving it the personality that the way the
founder would have liked to do how things are,
478
00:25:29,484 --> 00:25:37,410
I think, is what makes it more personable, but
it doesn't really replace the founder itself.
479
00:25:37,410 --> 00:25:43,170
At the end of the day, the founder still needs
to talk to it more often so that it can get to
480
00:25:43,170 --> 00:25:45,090
know you better, but it doesn't replace you.
481
00:25:45,090 --> 00:25:45,410
Right?
482
00:25:45,410 --> 00:25:46,289
So Mhmm.
483
00:25:46,289 --> 00:25:46,450
Mhmm.
484
00:25:46,545 --> 00:25:49,585
I think our edge, and I mentioned this in...
485
00:25:49,585 --> 00:25:55,424
If you guys wanted to get my 2027 top 10 future
trends, please do so through Alka.
486
00:25:55,424 --> 00:25:58,865
But one of the things that I was talking about
there is the trust factor.
487
00:25:58,865 --> 00:26:04,680
I don't know if you know the Sam Edelman trust
barometer in 2023, I think, or 2022 talking
488
00:26:04,680 --> 00:26:10,519
about trust has been diminished because of
technology, rightfully so.
489
00:26:10,519 --> 00:26:11,720
People Yes.
490
00:26:11,720 --> 00:26:12,119
Exactly.
491
00:26:12,525 --> 00:26:12,845
Yeah.
492
00:26:12,845 --> 00:26:15,325
People has been booting things on the Internet.
493
00:26:15,325 --> 00:26:17,565
Like, it's true, but sometimes it's not.
494
00:26:17,565 --> 00:26:23,884
So so our main advantage is, like, telling the
truth when you're doing your post, for example,
495
00:26:24,125 --> 00:26:27,964
sharing still that humanity of we're not
perfect.
496
00:26:27,964 --> 00:26:28,285
Right?
497
00:26:28,950 --> 00:26:34,629
And so that is is still an edge for us humans
in the age of AI.
498
00:26:35,269 --> 00:26:35,750
Right.
499
00:26:35,750 --> 00:26:36,069
No.
500
00:26:36,069 --> 00:26:37,909
That is so true because I...
501
00:26:37,909 --> 00:26:47,744
You know, there are some fears when it comes to
AI and how AI will replace, you know, humans,
502
00:26:47,744 --> 00:26:48,704
like, in the workplace.
503
00:26:48,704 --> 00:26:50,144
So what I totally do understand.
504
00:26:50,144 --> 00:26:50,384
So...
505
00:26:50,384 --> 00:26:52,224
And this was that trust as well.
506
00:26:52,384 --> 00:27:02,700
What would you say, Lourdes, that founders fear
that AI will strip away the, strip away the
507
00:27:02,700 --> 00:27:08,619
instincts of the company, the principles, the
the trust that's, they've already had in the
508
00:27:08,619 --> 00:27:11,579
organization that's made them successful.
509
00:27:11,579 --> 00:27:15,825
What would you say has been the fear of most
founders?
510
00:27:16,545 --> 00:27:19,345
I think it's the stealing.
511
00:27:19,345 --> 00:27:21,985
Their intellectual property is first and
foremost.
512
00:27:21,985 --> 00:27:23,265
Obviously, if...
513
00:27:23,505 --> 00:27:29,450
As you know, if you're using a public learning
language model, your data is probably out
514
00:27:29,450 --> 00:27:34,329
there, which we always say that is the main
advantage that we have having our own AI
515
00:27:34,329 --> 00:27:39,209
company is because we know that our data that's
proprietary is safe.
516
00:27:39,529 --> 00:27:40,329
And so Yeah.
517
00:27:40,329 --> 00:27:43,544
Do in your best case possible to
518
00:27:44,184 --> 00:27:49,384
be able to be covered so that all the
information that you put out there is
519
00:27:49,384 --> 00:27:50,184
protected.
520
00:27:50,585 --> 00:27:54,984
Another example of what I was talking you about
a while ago, I was listening to another
521
00:27:54,984 --> 00:27:59,980
podcast, and one of the things that when
ChatGPT first launched, there was actually a
522
00:27:59,980 --> 00:28:01,179
mayor in Australia.
523
00:28:01,179 --> 00:28:05,659
I think it was Melbourne, and he was talking
about when he first is starting to type his
524
00:28:05,659 --> 00:28:14,195
name on ChatGPT, it spewed a lot of wrong that
he was in jail, that he did bad things.
525
00:28:14,195 --> 00:28:15,715
He never did any of those.
526
00:28:15,715 --> 00:28:20,835
So making the long story short, he went to his
lawyer, and in fact, the lawyer was sending a
527
00:28:20,835 --> 00:28:24,515
defamation case because all of these are not
true at all.
528
00:28:24,950 --> 00:28:30,309
And so they didn't get an answer, but the next
day, when he typed his name, the information
529
00:28:30,309 --> 00:28:33,670
that came out of GPT was no longer...
530
00:28:33,670 --> 00:28:34,150
He's...
531
00:28:34,150 --> 00:28:37,269
He doesn't have all these things that appeared
originally.
532
00:28:37,990 --> 00:28:45,015
But then another person who didn't name him,
but basically kind of use a generic of, like,
533
00:28:45,015 --> 00:28:48,214
what can you say about this person and doing
this doing this?
534
00:28:48,214 --> 00:28:50,534
It still spewed out the bad things.
535
00:28:50,535 --> 00:28:51,654
So Oh, wow.
536
00:28:51,654 --> 00:28:52,134
Yes.
537
00:28:52,134 --> 00:28:53,414
So we have to be careful.
538
00:28:53,414 --> 00:28:54,134
It's getting better.
539
00:28:54,679 --> 00:28:55,160
Mhmm.
540
00:28:55,160 --> 00:28:55,400
Mhmm.
541
00:28:55,400 --> 00:28:57,720
But at the same time, we have to protect
ourselves too.
542
00:28:57,720 --> 00:29:02,839
So do whatever means possible for you if you
can to avoid that intellectual property
543
00:29:02,839 --> 00:29:04,920
because, as you know, in the age of...
544
00:29:04,920 --> 00:29:09,794
I call it I call it the society five point o or
in the Internet of things. And
545
00:29:09,634 --> 00:29:16,594
And now with artificial intelligence era, our
main advantage as a human would be as creators.
546
00:29:16,835 --> 00:29:17,315
You're...
547
00:29:17,315 --> 00:29:19,234
It's the imagination society.
548
00:29:19,554 --> 00:29:22,429
And so right now, protect that intellectual
property.
549
00:29:22,670 --> 00:29:23,390
Yes.
550
00:29:23,390 --> 00:29:23,950
Absolutely.
551
00:29:23,950 --> 00:29:25,309
We absolutely have to.
552
00:29:25,390 --> 00:29:27,789
And talking about trends, your final question.
553
00:29:27,950 --> 00:29:33,630
Talking about trends, what would you say would
be the the trends in the next five to ten years
554
00:29:33,630 --> 00:29:40,054
will be the strongest company which implements
AI tools.
555
00:29:41,414 --> 00:29:43,575
Where would you say the trend is going?
556
00:29:44,134 --> 00:29:46,294
That is a very, very good question.
557
00:29:46,294 --> 00:29:52,630
If you guys can go to my LinkedIn, I have,
like, a video one one minute reel of each of
558
00:29:52,630 --> 00:29:54,149
these 10 future trends.
559
00:29:54,150 --> 00:29:59,190
But talking about AI, one of the things,
obviously, is no longer about the tools.
560
00:29:59,190 --> 00:30:02,230
It's obviously around, can it do the work for
us?
561
00:30:02,230 --> 00:30:06,150
As you know, recently, Meta just launched Muse.
562
00:30:06,150 --> 00:30:11,134
I'm starting to use it now because one of the
things that I really don't like about some of
563
00:30:11,134 --> 00:30:12,575
the other tools would be...
564
00:30:13,134 --> 00:30:17,295
I have a stack of tools, and then I have to go
from one tool to another because the other tool
565
00:30:17,295 --> 00:30:18,654
doesn't know the context.
566
00:30:18,654 --> 00:30:25,190
But with Muse, because a lot of us are already
connected on Facebook and Instagram, Meta,
567
00:30:25,190 --> 00:30:25,589
obviously.
568
00:30:25,589 --> 00:30:28,789
And on my phone, I got TikTok and I got
LinkedIn.
569
00:30:29,029 --> 00:30:30,230
It knows already.
570
00:30:30,230 --> 00:30:30,470
Right?
571
00:30:30,470 --> 00:30:31,830
So I'm experimenting on that.
572
00:30:31,830 --> 00:30:35,589
And they actually just launched Dots, which is
also a personal AI agent, which is a
573
00:30:35,589 --> 00:30:36,950
competition for Grokbot.
574
00:30:36,950 --> 00:30:37,910
And I'm sorry, Claude.
575
00:30:38,194 --> 00:30:39,634
Right now, Codex...
576
00:30:39,634 --> 00:30:43,634
I actually like Codex more than Claude other
than our own LLM.
577
00:30:43,634 --> 00:30:45,794
I love our own LLM for business.
578
00:30:45,795 --> 00:30:47,875
I don't depend on the generic one.
579
00:30:47,875 --> 00:30:51,315
I use our own LLM as, you know, CoreBrain and
JD five now.
580
00:30:51,554 --> 00:30:51,795
Right.
581
00:30:52,380 --> 00:30:55,900
But there are certain things that I still use
the other stuff.
582
00:30:55,900 --> 00:30:56,940
So I just...
583
00:30:56,940 --> 00:31:00,380
Like, if I'm just gonna do something for
front...
584
00:31:00,380 --> 00:31:02,140
For fun, I just use the free ones.
585
00:31:02,140 --> 00:31:11,634
So for fun, for example, would be I'd like an
image of a mascot that can represent my product
586
00:31:11,634 --> 00:31:12,354
brand.
587
00:31:12,355 --> 00:31:14,034
So I I don't actually...
588
00:31:14,034 --> 00:31:17,234
Before, I used image generator on a JD one,
actually.
589
00:31:17,315 --> 00:31:19,634
But now I'm actually using...
590
00:31:20,690 --> 00:31:22,690
Right now, Higgs field and Nano Banana.
591
00:31:22,690 --> 00:31:27,249
Higgs field, obviously, for, video and Nano
Banana for, image.
592
00:31:27,809 --> 00:31:28,210
Right.
593
00:31:28,210 --> 00:31:28,690
Exactly.
594
00:31:28,690 --> 00:31:29,809
And then also Gemini.
595
00:31:29,809 --> 00:31:33,569
I heard Gemini is also good too for image
creation.
596
00:31:34,315 --> 00:31:34,875
I haven't used...
597
00:31:34,875 --> 00:31:35,595
Have you tried?
598
00:31:35,595 --> 00:31:41,355
I haven't used Gemini for image creation, but I
I have a content creator assistant.
599
00:31:41,674 --> 00:31:49,069
And I actually put some context on Gemini gems,
and I created, like, an AI agent that she can
600
00:31:49,069 --> 00:31:51,309
ask if I'm not there because I fed...
601
00:31:51,309 --> 00:31:56,190
I trained the gem to able to think like me, and
we're using that same company email.
602
00:31:56,190 --> 00:32:02,325
So I told her that when I'm traveling from the
line away, ask the gem first, and then we
603
00:32:02,325 --> 00:32:02,964
practice it.
604
00:32:02,964 --> 00:32:07,444
Like, if I'm still here, I ask her to ask some
question if I will actually decide the same
605
00:32:07,444 --> 00:32:09,284
way, and so it's trained that way.
606
00:32:09,444 --> 00:32:10,085
It's trained.
607
00:32:10,085 --> 00:32:10,565
Well, that...
608
00:32:10,565 --> 00:32:11,364
That's so good.
609
00:32:11,365 --> 00:32:16,740
I mean, as I said, you know, there were so many
AI tools, and can be overwhelming for anyone as
610
00:32:16,740 --> 00:32:18,899
to what they need to use for what.
611
00:32:19,460 --> 00:32:23,220
But lord, this has been such a powerful
conversation.
612
00:32:23,460 --> 00:32:29,714
When it comes to AI, there is so many tools,
but AI can obviously make our lives so much
613
00:32:29,714 --> 00:32:33,474
easier and so much better in multitude of ways.
614
00:32:33,875 --> 00:32:37,075
Thank you to each and everyone for tuning in
today.
615
00:32:37,075 --> 00:32:41,714
Elodas, where can people find you, and how can
we connect and serve you better?
616
00:32:42,690 --> 00:32:44,769
Thank you so much for having me on the show.
617
00:32:44,769 --> 00:32:45,889
This has been a blast.
618
00:32:45,889 --> 00:32:48,609
And as always, time flies when we're having
fun.
619
00:32:48,609 --> 00:32:50,049
I'm active on social media.
620
00:32:50,049 --> 00:32:53,569
You can find me on Facebook, Instagram, TikTok,
and LinkedIn.
621
00:32:53,889 --> 00:32:59,545
And my website is sustainabilityteam.ai, and I
look forward to connecting with your audience.
622
00:32:59,545 --> 00:33:01,305
Thank you so much for having me, Alka.
623
00:33:01,465 --> 00:33:02,424
You're welcome.
624
00:33:02,424 --> 00:33:03,305
Thank you so much.
625
00:33:03,305 --> 00:33:03,865
And,
626
00:33:04,025 --> 00:33:08,904
Lourdes, thank you for also reminding us AI
isn't about speed or automation.
627
00:33:09,305 --> 00:33:13,619
It's about preserving the knowledge, protecting
protecting the the culture culture and and the
628
00:33:13,465 --> 00:33:20,100
the trust, but also building reliable systems
that can help the company grow without losing
629
00:33:20,100 --> 00:33:20,660
its soul.
630
00:33:20,660 --> 00:33:26,235
And thank you once again to each and everyone
for tuning in, and make sure you like and
631
00:33:26,235 --> 00:33:27,595
subscribe to the channel.
632
00:33:27,595 --> 00:33:33,275
In this way, we're gonna bring more amazing
guests like Nordisk Gant and more inspirational
633
00:33:33,275 --> 00:33:34,154
conversation.
634
00:33:34,154 --> 00:33:35,595
So until next time.
635
00:33:35,595 --> 00:33:36,634
Thank you for joining us.
636
00:33:36,634 --> 00:33:37,275
Bye for now.
637
00:33:38,662 --> 00:33:40,102
Thank you, Lordess.
638
00:33:40,102 --> 00:33:41,302
That's amazing.
639
00:33:41,622 --> 00:33:42,422
Thank you.
00:00:02,240 --> 00:00:03,279
Hi, everyone.
2
00:00:03,279 --> 00:00:05,919
Welcome to another episode.
3
00:00:06,559 --> 00:00:16,054
AI is moving at a rapid pace, and most
organizations are using AI to move faster, to
4
00:00:16,054 --> 00:00:21,654
create more efficiencies in the organizations,
and create better workflows.
5
00:00:22,214 --> 00:00:30,239
My guest today, she helps companies to turn
reliable systems into...
6
00:00:30,239 --> 00:00:36,960
To turn their deep expertise into reliable
systems, what's made their company successful
7
00:00:36,960 --> 00:00:38,159
in the first place.
8
00:00:38,559 --> 00:00:47,405
My guest today, Laura Des Gant, she helps
founder led businesses adopt AI without losing
9
00:00:47,405 --> 00:00:55,039
judgment, culture, and the trust, which has
made them successful in the first place.
10
00:00:55,439 --> 00:01:05,840
As a fractional AI chief sustainability and
impact officer, she builds human centered AI
11
00:01:05,840 --> 00:01:14,024
systems that preserves institutional knowledge,
supports better decisions, and creates the
12
00:01:14,024 --> 00:01:16,825
continuity across teams.
13
00:01:17,465 --> 00:01:20,905
Her work isn't about chasing AI trends.
14
00:01:21,439 --> 00:01:30,480
Rather, it's about turning their deep expertise
into reliable systems that can help them grow
15
00:01:30,640 --> 00:01:32,959
and create more impact.
16
00:01:33,120 --> 00:01:36,560
Please give a warm welcome to Lourdes Gant.
17
00:01:36,704 --> 00:01:37,825
Hi, Lourdes.
18
00:01:38,145 --> 00:01:39,905
Thank you very much for having me.
19
00:01:39,905 --> 00:01:42,704
That was such a generous words for the
introduction.
20
00:01:42,704 --> 00:01:43,745
Thank you so much.
21
00:01:44,064 --> 00:01:45,504
Oh, you're very welcome.
22
00:01:45,505 --> 00:01:55,869
Well, let's start by what does it actually mean
to adopt AI without losing the soul of the
23
00:01:55,869 --> 00:01:56,590
business?
24
00:01:57,869 --> 00:01:58,989
Great question.
25
00:01:58,989 --> 00:01:59,950
I believe
26
00:01:59,950 --> 00:02:06,825
that from my almost twenty years of being in
sustainable seafood aquaculture, I have gained
27
00:02:06,825 --> 00:02:14,264
to realize that a lot of the knowledge and
judgment are buried inside the founder's head.
28
00:02:14,264 --> 00:02:19,784
And so one of the things that we've been
learning now with these new AI tools is to be
29
00:02:19,784 --> 00:02:26,560
able to preserve that judgment when no one is
able to do it because some...
30
00:02:26,560 --> 00:02:29,200
Most of the time, the founders become a
bottleneck.
31
00:02:29,520 --> 00:02:34,319
And to be able to do that, we need to go
through their searchable systems, playbooks,
32
00:02:34,319 --> 00:02:39,685
and, obviously, AI supported assistance so that
the teams can move when they are not available.
33
00:02:40,165 --> 00:02:40,884
Right.
34
00:02:40,884 --> 00:02:41,685
Absolutely.
35
00:02:42,085 --> 00:02:50,250
And, also, AI shouldn't erase the the human
aspect, which is what most people do have a
36
00:02:50,250 --> 00:02:55,129
fear that AI is going to erase humans.
37
00:02:56,409 --> 00:02:56,810
Right?
38
00:02:56,810 --> 00:02:57,610
So that...
39
00:02:57,610 --> 00:03:01,129
That's that's the one fear most people do have.
40
00:03:01,449 --> 00:03:07,814
I think there's, as you know, a lot of words
after the AI era that come about, and one of
41
00:03:07,814 --> 00:03:09,495
them is amplifying humans.
42
00:03:09,495 --> 00:03:15,495
And I belong into an EdTech group wherein we
always say artificial intelligence plus human
43
00:03:15,495 --> 00:03:16,935
equals superhuman.
44
00:03:17,069 --> 00:03:22,830
And so fascinating enough, you and I were just
in Egypt to have a speaking engagement there.
45
00:03:22,830 --> 00:03:28,990
And on my way back to Canada, was listening to
another podcast on how OpenAI came about as its
46
00:03:28,990 --> 00:03:29,710
history.
47
00:03:29,710 --> 00:03:37,784
And one of the founders actually was sharing
how when ChatGPT started, he decided to give
48
00:03:37,784 --> 00:03:46,264
all of the conversations, all of the chats that
he and his mom did, and then the mom died.
49
00:03:46,439 --> 00:03:47,960
And then at the time that chat...
50
00:03:47,960 --> 00:03:55,560
And then the chat GPT, after he actually put in
all those conversation, he started to talk to
51
00:03:55,560 --> 00:03:59,639
the bot like his mom was alive, and he was
cry...
52
00:03:59,639 --> 00:04:05,534
He was crying of what the message would be when
he asked the question of what would I do now
53
00:04:05,534 --> 00:04:07,294
now that you're not here anymore?
54
00:04:07,294 --> 00:04:13,134
And because of all the context that the AI was
trained on how to reply like his mom, he almost
55
00:04:13,134 --> 00:04:15,055
felt like his mom was there.
56
00:04:15,294 --> 00:04:15,534
So...
57
00:04:16,639 --> 00:04:21,920
And he said, you know, it's kinda weird and
bad, but also good at the same time.
58
00:04:22,080 --> 00:04:26,000
And I'm sure anybody can relate to this wherein
what
59
00:04:26,240 --> 00:04:32,214
do you think can happen if we put together all
of these brilliant minds and talk to and talk
60
00:04:32,214 --> 00:04:33,974
to them on how they can help us today.
61
00:04:33,974 --> 00:04:36,535
I think this is what the AI era has done for
us.
62
00:04:36,535 --> 00:04:38,214
It amplifies us.
63
00:04:38,535 --> 00:04:39,334
Absolutely.
64
00:04:39,334 --> 00:04:40,294
I do agree.
65
00:04:40,294 --> 00:04:43,974
And there were so many AI tools as we know.
66
00:04:46,029 --> 00:04:54,189
With this new tool that our mentor has come out
with with the JT five, this is only, I mean, as
67
00:04:54,189 --> 00:04:59,654
we were on the call, it is so exciting being in
this AI era.
68
00:04:59,654 --> 00:05:01,014
I'm I'm very grateful.
69
00:05:01,014 --> 00:05:07,735
I'm excited to know as to what is the future of
AI and especially with AI, you know, employees
70
00:05:07,735 --> 00:05:10,214
and the humans AI.
71
00:05:11,175 --> 00:05:18,490
This is what it's all about and how we don't
need to be fearful, but we need to embrace
72
00:05:18,729 --> 00:05:22,649
every aspect of what's happening with AI.
73
00:05:23,449 --> 00:05:26,089
It's a wonderful, wonderful invention.
74
00:05:26,089 --> 00:05:31,194
I came to believe that every time we have
something new, there will always be a group of
75
00:05:31,194 --> 00:05:35,595
people who are gonna be early adapters like you
and I, but there will also be people who are
76
00:05:35,595 --> 00:05:38,074
gonna be scared of it and rightfully so.
77
00:05:38,235 --> 00:05:41,115
I think of it like when fire was invented.
78
00:05:41,599 --> 00:05:45,199
The fire can either burn you or it can give you
warmth during the winter.
79
00:05:45,199 --> 00:05:49,279
So the same is true for me in terms of AI tools
and technology.
80
00:05:49,680 --> 00:05:55,120
This can become one of the greatest invention
in modern history, or it can be one that can
81
00:05:55,120 --> 00:05:56,000
doom humanity.
82
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You know?
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That that...
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Exactly.
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That is so true.
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00:06:00,555 --> 00:06:09,210
In your view, in that case, Lourdes, what would
you say separates the the the trends as opposed
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to the AI adoption and AI implementation to to
give enterprise more control and authority in
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the organization?
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What would you say?
90
00:06:23,714 --> 00:06:29,394
It's a very good question and also hard to
answer because I believe that this technology
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has given small to medium businesses a level
playing field.
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So as you know, now you can have in your
fingertips a 6 figure CEO, maybe even, like, an
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8 figure executive team without having to pay
for the price.
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This is one of the things that democratized, I
guess, the salaries of people who have all that
95
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knowledge and now can be compacted into one AI
executive team.
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00:06:55,045 --> 00:06:57,045
I remember, four years ago...
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Where are we now?
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2026.
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00:06:58,564 --> 00:06:58,805
Yeah.
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Four four years ago, twenty twenty two one was
obviously in November was when ChatGPT was
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launched.
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But even before them, one of the other group
that I was in was already talking about this
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whole executive team that are made up of AI.
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I remember speaking in an aquaculture
conference in Melbourne, Australia in 2022, and
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one of the things that I presented there was
future trends.
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And I said Mhmm.
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There will come a time next year.
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This was 2022.
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Right?
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This was exactly July 2022.
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And I said next year, everybody will have an AI
CEO.
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And I I have, like, in the audience, and, like,
it's unbelievable.
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And now everybody has it.
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Right?
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And so it's just a matter of time.
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And so it's fascinating in terms of what the
trends that you're going to ride because you
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can't avoid it.
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You know?
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Imagine you're surfing.
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Are you going to be drowned?
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And in school, we were taught it's either you
sink or you swim, but they didn't they didn't
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teach us how to actually surf.
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And so the same can be said in the AI area.
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It's either you surf with the wave of this
technology to catapult you to what benefits it
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brings us or you sink or you swim.
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So to me Right.
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I've always been connected with people who are
futuristic.
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And as you mentioned, in our community with JT,
it has been, like, our nine figure brain
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originally that became, like, a core brain and
JT one wherein we have all these 16 brains that
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help us in our business.
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This is unheard of in Right.
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Business has always been like, you gain benefit
with your...
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Either with your own work or with the people
around you, but now we have to amplify this
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with technology.
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So I hope that answers your question.
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I kinda went roundabout way.
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No.
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Absolutely.
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Yes.
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It does.
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Yes.
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00:08:51,174 --> 00:08:51,894
Exactly.
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00:08:52,134 --> 00:08:55,335
And talking about you help founder led
businesses.
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So if a if a founder wants to adopt AI, but
they have a fear of losing control as most most
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founders do, but they have a fear of losing
control and the judgment or...
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00:09:11,700 --> 00:09:12,820
What would you say?
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What would you say would be the first move that
they would have to make?
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00:09:18,634 --> 00:09:23,674
I remember I I remember talking about this in
Aristen, and I have a formula for this on how
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we do this in three simple moves that are easy
to remember.
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00:09:26,475 --> 00:09:30,394
If you remember what I said, it's find it,
repeat it, and ask it.
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So...
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00:09:31,129 --> 00:09:35,769
But it's a very good question in terms of,
like, what if you didn't wanna lose control?
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I think even before I go through the three
simple moves of find it, repeat it, and ask it,
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I think the very first thing that founders need
to ask themselves is, are they actually really
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ready to go to go to the next level or or not?
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00:09:53,295 --> 00:09:56,095
I don't know if you know the book, Small
Giants.
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There's a story there of several businesses who
have an opportunity to become bigger, but they
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chose to be small.
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00:10:04,090 --> 00:10:07,210
Like I mentioned to you, our family firm is
kind of a...
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How do you say it?
161
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We're in a...
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We're very small in a very big pond, but we're
actually big in a small pond.
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And so the book on small giants talk about
this, that founders decided that they're just
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gonna become small giants because their culture
is gonna go away if they ended up being
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acquired or that their people are gonna change
the way that they do business if they ended up
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being with a new...
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00:10:32,629 --> 00:10:34,389
Let's just say a venture capitalist.
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And so
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Mhmm.
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That's the very first question I asked them.
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Do you really wanted to go to the next level,
or you just wanna keep things as it is?
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Because they may not wanna employ technology to
be able Right.
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To scale up.
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They were happy with where where they are.
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But if they wanted to scale, if they wanted to
sell their business, if they wanted to exit,
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these are the three simple moves that I
mentioned.
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So find it.
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Right?
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So find what are these decisions that are hinge
on their founder.
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So I often said, it's not because the other
people in the team members doesn't know what to
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say.
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It's just that they have the history and the
experience of what it was like to decide on
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something because they have been in the
industry for so long.
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For case in my husband and my founder has been
in the aquaculture industry for thirty years.
185
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I joined them, as I mentioned, in the family
from twenty years ago.
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And so when I was first starting in that...
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Those first ten years, I asked him a lot of
questions.
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I didn't know what to answer just because I'm
new.
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So it's not because I I didn't know the answer.
190
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It's just there's no experience.
191
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Like, as you said, you know, experience is the
best teacher.
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So those are the things those are the things
that you need to find.
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So second is repeat it.
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Right?
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So the next step would be how can you create
playbooks so that these decisions, these
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relationships, whatever that experience can be
captured?
197
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And I'm just talking about playbooks.
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So in terms of standard operating procedures or
standard operating guidelines, can you capture
199
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all those so that you can actually repeat
without the founder being available?
200
00:12:04,459 --> 00:12:08,195
And then last and not the least would be ask
it. The
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The team should be able to use this technology
with AI.
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Know, they can ask the AI when the founder is
not there so that it will have the same
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decisions as if the founder is there.
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So there you have it.
205
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Exactly.
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No.
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That's amazing.
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And and there's gotta be a point where, you
know, the founders, have to be absent.
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They can be absent, and they have the team
running.
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So, Lord, is in in that case, are we building
AI systems that serve the business, or are we
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building AI systems to to redesign the
technology?
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That's a very good question in
213
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terms of what is it that they wanted to
accomplish.
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I think it hinges again on what are they
envisioning that these tools are gonna be able
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to help them with.
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00:12:56,169 --> 00:12:57,529
So, for example...
217
00:12:57,610 --> 00:12:58,009
Right?
218
00:12:58,009 --> 00:13:01,835
So there's a lot of talk about workflows, but
what is that really?
219
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Right?
220
00:13:02,315 --> 00:13:03,035
Exactly.
221
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Explain to
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the audience.
223
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What is the workflows?
224
00:13:06,235 --> 00:13:11,355
So case in point, in our hatchery, as I
mentioned, we're in sustainable seafood
225
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aquaculture.
226
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In our hatchery, a workflow of production...
227
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And I'm gonna go a little bit technical, so
bear with Yes.
228
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No.
229
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Sure.
230
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Go ahead.
231
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Yes.
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Our shellfish, the workflow would
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be
234
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we get the parent animals, we call brood stock
from the ocean, and then that's step one.
235
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And then we bring them to the hatchery.
236
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We spawn them.
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And then after several months that they spawn,
we bring them to the primary nursery system
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just like a baby.
239
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And then they reach a certain size, then we
bring them to the secondary nursery system
240
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before we bring them back into the farm.
241
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So that's a workflow in our production system.
242
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And so what is that for a certain company in a
certain industry?
243
00:13:55,190 --> 00:13:57,269
This was our shellfish production flow.
244
00:13:57,269 --> 00:13:57,669
Mhmm.
245
00:13:57,669 --> 00:14:04,664
So for you, for example, if that's product
based, if you are service based, workflow can
246
00:14:04,664 --> 00:14:05,945
be consist of...
247
00:14:06,504 --> 00:14:11,865
You have a pipeline that you're looking at,
meaning who are the people that you wanted to
248
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solve problems for.
249
00:14:14,105 --> 00:14:19,250
Let's just say, for example, in the context of
our conversation, you're solving the problem
250
00:14:19,250 --> 00:14:19,809
of...
251
00:14:19,809 --> 00:14:25,009
In your field, having visibility and
credibility for branding strategy.
252
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Mhmm.
253
00:14:25,649 --> 00:14:31,169
And so a workflow can become, you have a
pipeline, you build relationship with the
254
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pipeline, and then you build the foundation of
how you can work together to solve the problem
255
00:14:36,044 --> 00:14:42,845
so that the coach, the executive team, or a
founder and CEO can have better visibility
256
00:14:42,845 --> 00:14:44,204
slash credibility.
257
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That is a workflow for me.
258
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How you execute that depends on your, I call
it, signature system or unique method.
259
00:14:51,429 --> 00:14:51,990
Right?
260
00:14:52,070 --> 00:14:52,470
Right.
261
00:14:52,470 --> 00:14:55,830
So it can be, like, your signature system can
be...
262
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I don't know.
263
00:14:56,549 --> 00:14:59,029
You know better this field than I do.
264
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But I think people will know that is an example
of a workflow.
265
00:15:03,565 --> 00:15:03,804
Right?
266
00:15:03,804 --> 00:15:08,044
So I I just say one is product based and one
that's service based.
267
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Service based.
268
00:15:09,004 --> 00:15:09,725
Alright.
269
00:15:09,725 --> 00:15:11,485
So how AI comes into this?
270
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Like, so with technology, these workflows can
now be automated and mechanized.
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For example, one of the things that we're
looking into in our production would have been,
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what if we have actually a seeding machine?
273
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So right now, we're seeding all these little
baby gooey ducks slash shellfish with the
274
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diver.
275
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They go down there.
276
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Oh, wow.
277
00:15:33,625 --> 00:15:37,625
And then they scattered all the seed, and
there's very apple...
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00:15:37,625 --> 00:15:40,345
Johnny apple seed, to be honest with you.
279
00:15:41,440 --> 00:15:43,600
But that's why we wanted to automate it.
280
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So we're looking into how can we actually
consistently have the same number of seed in a
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certain square meter out in the ocean.
282
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So we're thinking, okay.
283
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Technology can come into place with the seeding
machine.
284
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Or Mhmm.
285
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Once they they reach a certain market size, we
are looking into a harvesting machine.
286
00:16:00,514 --> 00:16:02,435
Because, again, right now, it's very manual.
287
00:16:02,514 --> 00:16:03,795
We pay our divers...
288
00:16:03,795 --> 00:16:09,075
The biggest actually expense in our profit and
loss statement is actually diver slash
289
00:16:09,075 --> 00:16:13,839
contractors because we pay them $2,000 a day
for a boat day.
290
00:16:14,000 --> 00:16:15,839
And so AI come into the place.
291
00:16:15,839 --> 00:16:18,399
What if we can actually have a harvesting
machine?
292
00:16:18,480 --> 00:16:20,959
So I think when people think about AI, when
think...
293
00:16:20,959 --> 00:16:27,665
People think about robot, they think about,
like, AI as this invisible technology.
294
00:16:27,665 --> 00:16:34,865
It it can be, but it can also be like a farmer
uses a certain machine that's run by robotics.
295
00:16:34,865 --> 00:16:37,105
Doesn't necessarily have to do with, like,
robot.
296
00:16:37,190 --> 00:16:39,509
So I think I think you get what I mean.
297
00:16:39,589 --> 00:16:39,909
No.
298
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I do.
299
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I understand.
300
00:16:41,429 --> 00:16:42,870
And, also, it's very...
301
00:16:43,429 --> 00:16:44,549
I I would say...
302
00:16:44,549 --> 00:16:51,665
And also the audience listening as opposed to,
you know, service based, you know, AI in
303
00:16:51,665 --> 00:16:52,865
service based, yes.
304
00:16:52,865 --> 00:16:54,945
So we know that how AI can play.
305
00:16:54,945 --> 00:17:03,879
But but in your industry with the the ocean
fish that, you know, with sustainability, it's
306
00:17:03,879 --> 00:17:04,599
not very...
307
00:17:04,599 --> 00:17:08,279
It's not heard of as to how AI can fully...
308
00:17:08,599 --> 00:17:12,759
How you can integrate and how it can fully just
amplify your business.
309
00:17:13,079 --> 00:17:15,400
So right now, you're doing it manually.
310
00:17:15,400 --> 00:17:15,559
Yes?
311
00:17:17,244 --> 00:17:18,765
There's there's a combination.
312
00:17:18,765 --> 00:17:19,804
We It's a combination.
313
00:17:19,804 --> 00:17:20,125
Okay.
314
00:17:20,125 --> 00:17:20,605
Yeah.
315
00:17:20,605 --> 00:17:26,845
So there's a combination of the same thing as
just any other industry we're in.
316
00:17:26,845 --> 00:17:27,244
You know?
317
00:17:27,244 --> 00:17:32,589
We obviously have to take care of press
releases, social media management.
318
00:17:33,150 --> 00:17:35,789
That's, like, the same as, like, any industry.
319
00:17:35,789 --> 00:17:36,029
Right?
320
00:17:36,029 --> 00:17:38,269
You have somebody who can create content for
you.
321
00:17:38,269 --> 00:17:41,869
You have the educational assets like the
podcast we're doing.
322
00:17:41,869 --> 00:17:42,670
So that's the same.
323
00:17:42,670 --> 00:17:48,755
We have AI slash maybe a content creator that's
an AI.
324
00:17:48,755 --> 00:17:49,154
Right?
325
00:17:49,154 --> 00:17:50,275
That's one example.
326
00:17:50,595 --> 00:17:51,474
So for...
327
00:17:51,875 --> 00:17:53,474
And same for marketing.
328
00:17:53,474 --> 00:17:55,315
Maybe you're using for marketing and sales.
329
00:17:56,259 --> 00:18:02,419
Claude, for example, can research your pipeline
wherein it can automatically actually send
330
00:18:02,419 --> 00:18:08,980
people emails in your local area if they're
interested in some AI workflow slash
331
00:18:08,980 --> 00:18:09,940
implementation.
332
00:18:09,940 --> 00:18:10,419
Right?
333
00:18:10,419 --> 00:18:10,980
Uh-huh.
334
00:18:10,980 --> 00:18:12,815
So that's what makes...
335
00:18:12,815 --> 00:18:15,215
Or maybe even in bookkeeping or finance and
admin.
336
00:18:15,215 --> 00:18:15,455
Right?
337
00:18:15,455 --> 00:18:20,255
So, like, my bookkeeper my bookkeeper actually
is from The Philippines wherein she...
338
00:18:20,255 --> 00:18:25,220
Before she used to do the bank reconciliation
manually wherein she has to look at the bank
339
00:18:25,220 --> 00:18:30,259
statement and look at all the invoices slash
deposit slips to be able to reconcile the bank
340
00:18:30,259 --> 00:18:30,580
account.
341
00:18:30,580 --> 00:18:33,619
Now she uses AI to be able to find all those.
342
00:18:33,619 --> 00:18:34,180
So it's less...
343
00:18:34,180 --> 00:18:35,220
That's convincing.
344
00:18:35,859 --> 00:18:39,924
So these are just example that is applicable to
all the Right?
345
00:18:39,924 --> 00:18:42,565
Marketing slash sales, finance and admin.
346
00:18:42,565 --> 00:18:42,965
Mhmm.
347
00:18:42,965 --> 00:18:43,445
Mhmm.
348
00:18:43,445 --> 00:18:46,404
Let's just say content creation.
349
00:18:46,644 --> 00:18:48,644
On the other side of things can be production.
350
00:18:48,644 --> 00:18:52,644
Like, what I mentioned, if you're product
based, you have some kind of production
351
00:18:52,644 --> 00:18:55,569
workflow, it can be...
352
00:18:55,569 --> 00:18:57,730
We're using sensors in our hatchery.
353
00:18:57,730 --> 00:18:59,409
And when I say that, it can be...
354
00:18:59,490 --> 00:19:01,409
As you know, we're based in Canada.
355
00:19:01,409 --> 00:19:06,609
And so we actually have a small building that
has all the equipment that actually tell the
356
00:19:06,609 --> 00:19:10,289
animals, like, it's summer when it's winter and
it's winter when it's summer.
357
00:19:10,654 --> 00:19:16,654
So these are just some different kind because
it's production based, and we also have, like,
358
00:19:16,974 --> 00:19:19,134
measuring the salinity of the water.
359
00:19:19,214 --> 00:19:23,855
So very important in terms of how salty can the
water be.
360
00:19:23,855 --> 00:19:26,255
Does that help the animal grow faster or not?
361
00:19:26,390 --> 00:19:29,269
So we have sensors to actually do measure this.
362
00:19:29,430 --> 00:19:35,110
Or if there's actually a blackout and power is
actually gone Mhmm.
363
00:19:35,190 --> 00:19:43,365
That that really affects of the animals die
overnight because they got cold because Right.
364
00:19:43,365 --> 00:19:44,804
There's no electricity.
365
00:19:44,884 --> 00:19:52,724
So we got sensors and automatic generator that
comes on if, again, powered by technology to be
366
00:19:52,724 --> 00:19:54,004
able to get that monitored.
367
00:19:54,700 --> 00:19:55,500
Exactly.
368
00:19:55,500 --> 00:20:00,619
Well well, with the ocean, you do have to make
sure that, you know, the fish and...
369
00:20:01,019 --> 00:20:04,779
You have to monitor that on a regular basis to
to make sure.
370
00:20:05,820 --> 00:20:09,820
In fact, in this case, how do we make sure,
Lordas, we...
371
00:20:10,755 --> 00:20:16,274
How do we make sure AI actually amplifies the
company's principles?
372
00:20:16,595 --> 00:20:19,394
You you help the founder and businesses.
373
00:20:19,394 --> 00:20:29,460
So how do you how do you make sure that the AI
is actually amplifying the company's principles
374
00:20:29,700 --> 00:20:32,420
rather than flatlining them?
375
00:20:33,220 --> 00:20:34,500
Hard question, Alka.
376
00:20:34,500 --> 00:20:39,025
But, let's see if I can put this in the
perspective that's easy to actually follow.
377
00:20:39,265 --> 00:20:42,625
So most of the things that we do in our
company...
378
00:20:43,105 --> 00:20:47,904
Mostly because my husband slash business
partner has been in this industry ten thousand
379
00:20:47,904 --> 00:20:51,904
hours under the water as a commercial
fisherman, have seen the ebbs and flow of this
380
00:20:51,904 --> 00:20:52,305
industry.
381
00:20:52,420 --> 00:20:52,900
Correct?
382
00:20:52,900 --> 00:20:53,220
Mhmm.
383
00:20:53,220 --> 00:20:53,619
Right.
384
00:20:53,619 --> 00:20:58,579
And so to be able to capture that, like, just
between the two of us, there's, like, half a
385
00:20:58,579 --> 00:21:01,619
century of knowledge base.
386
00:21:01,619 --> 00:21:01,940
Right?
387
00:21:01,940 --> 00:21:02,339
Right.
388
00:21:02,339 --> 00:21:02,579
Right.
389
00:21:02,579 --> 00:21:10,164
So to be able to talk about what's in his
brain, what's in his image, what is his voice,
390
00:21:10,164 --> 00:21:15,124
what can be put into video that captures all
that half a century of knowledge.
391
00:21:15,125 --> 00:21:21,169
And so at the beginning that we did this in our
company, I actually have a very thick book that
392
00:21:21,169 --> 00:21:26,529
they had from their original company that
contained all of the experiments that they did
393
00:21:26,609 --> 00:21:29,089
for research and development That's amazing.
394
00:21:29,169 --> 00:21:29,729
Wow.
395
00:21:29,569 --> 00:21:32,289
Introducing the shellfish that they actually
396
00:21:32,849 --> 00:21:35,715
started loving and started to aquaculture.
397
00:21:35,715 --> 00:21:42,434
And so I put in all those knowledge base,
actually, on our AI, and all of all of our
398
00:21:42,434 --> 00:21:48,500
scientific research and experimental
development put into it all of our SOPs, all of
399
00:21:48,500 --> 00:21:52,259
our, basically, protocols in all of the
departments.
400
00:21:52,339 --> 00:21:52,659
Right.
401
00:21:52,659 --> 00:21:55,940
So, Neil, all that r and d, all
402
00:21:55,940 --> 00:22:03,195
of that experimentation are in one file that
captures that if someone is going to present to
403
00:22:03,195 --> 00:22:06,474
me in one department that they're gonna do this
experiment.
404
00:22:06,475 --> 00:22:10,075
I have them go through the AI
405
00:22:10,475 --> 00:22:10,715
Right.
406
00:22:10,715 --> 00:22:12,795
And basically say, has not...
407
00:22:12,795 --> 00:22:14,234
Has this been done before?
408
00:22:14,394 --> 00:22:17,279
Or if it's done before, how can we make it
better?
409
00:22:17,359 --> 00:22:19,519
So it's really easy now to...
410
00:22:19,519 --> 00:22:24,160
One of the things that I have a project on
right now is capturing intellectual property on
411
00:22:24,160 --> 00:22:26,240
the joint venture partnerships that we have.
412
00:22:26,400 --> 00:22:32,265
And so so I just put it in on our AI that has
all of that knowledge base, and it just gives
413
00:22:32,265 --> 00:22:37,785
me, like, a wonderful opportunity to actually
look at what has been done, how can it be
414
00:22:37,785 --> 00:22:39,544
better, and how can we move forward.
415
00:22:39,544 --> 00:22:40,585
So that's just one example.
416
00:22:41,369 --> 00:22:41,769
No.
417
00:22:41,769 --> 00:22:43,450
I I I absolutely love that.
418
00:22:43,450 --> 00:22:45,929
I think that is so true as to, like, how we...
419
00:22:46,250 --> 00:22:53,289
And how we can use AI for multiple, you know,
reasons to, you know, research, as you said.
420
00:22:54,025 --> 00:22:55,785
But that is so fascinating.
421
00:22:55,785 --> 00:23:00,585
And and I'm always curious to know as to that
when it comes to the founder led businesses,
422
00:23:00,585 --> 00:23:01,784
how do we...
423
00:23:01,944 --> 00:23:11,180
How can founder led businesses scale without
the AI becoming generic or is losing the soul
424
00:23:11,180 --> 00:23:12,299
of the company.
425
00:23:12,779 --> 00:23:13,420
Yeah.
426
00:23:13,500 --> 00:23:14,860
And I was gonna say that next.
427
00:23:14,860 --> 00:23:19,740
Like, what about for those companies wherein
they don't have documentation of all this?
428
00:23:19,740 --> 00:23:20,860
So Mhmm.
429
00:23:21,019 --> 00:23:24,779
You can ask the AI to ask you some questions so
that it gets to know you better.
430
00:23:25,164 --> 00:23:29,884
It can be, like, what is your personality
profile?
431
00:23:29,884 --> 00:23:32,045
In the Briggs Myers, I'm ISTJ.
432
00:23:32,045 --> 00:23:32,845
We can put that in.
433
00:23:32,845 --> 00:23:33,164
Okay.
434
00:23:33,164 --> 00:23:35,644
For example, the founder is this personality.
435
00:23:35,964 --> 00:23:37,404
What is his Kolbe profile?
436
00:23:37,404 --> 00:23:40,365
What is his strengths in the StrengthFinder's
Gallup exercise?
437
00:23:40,669 --> 00:23:43,630
Even maybe Enneagram in the disc profile.
438
00:23:43,630 --> 00:23:49,470
Put all those in, and then it can actually
capture the personality of the founder.
439
00:23:49,630 --> 00:23:50,190
So Right.
440
00:23:50,349 --> 00:23:51,869
That's starting from scratch.
441
00:23:51,869 --> 00:23:52,190
Right?
442
00:23:52,190 --> 00:23:55,974
And you even probably hear a lot of people
talking about having a chief of staff.
443
00:23:55,974 --> 00:23:57,174
That's basically what it is.
444
00:23:57,174 --> 00:23:57,414
Right?
445
00:23:57,414 --> 00:24:03,335
So your chief of staff is probably, like, the
AI that thinks, talk, and speak and listen like
446
00:24:03,335 --> 00:24:03,654
you.
447
00:24:03,654 --> 00:24:04,214
Like you.
448
00:24:04,214 --> 00:24:04,694
Yes.
449
00:24:04,615 --> 00:24:07,734
You train it to behave the way that you would
behave.
450
00:24:08,329 --> 00:24:12,009
Just one example was this personality profiles
that you can put in.
451
00:24:12,009 --> 00:24:15,849
And then you give it parameters of what is
acceptable, what's not acceptable.
452
00:24:15,849 --> 00:24:19,289
For example, my AI chief of staff knows all my
brands.
453
00:24:19,289 --> 00:24:20,490
I have quite a bit of brand.
454
00:24:20,490 --> 00:24:24,884
So I have my product brand, which is the Go
Reduck, our shellfish, and I have my personal
455
00:24:24,884 --> 00:24:25,684
brand, obviously.
456
00:24:25,684 --> 00:24:30,484
And I also have a service brand, which is the
AI legacy for founders.
457
00:24:30,644 --> 00:24:31,204
So when
458
00:24:31,845 --> 00:24:37,765
I talk to my AI chief of staff, it's very, very
clear on which brand I'm talking about because
459
00:24:37,765 --> 00:24:41,089
I fed it all of the information that it knows
about me.
460
00:24:41,169 --> 00:24:42,529
And so when having a...
461
00:24:42,529 --> 00:24:44,369
It gives me my daily briefing.
462
00:24:44,609 --> 00:24:47,970
I also give it, like, certain topics that it...
463
00:24:47,970 --> 00:24:50,769
There's certain things that I needed to do on a
daily basis.
464
00:24:51,250 --> 00:24:55,515
Number one was a daily briefing of what my
priorities are for the day, my priorities for
465
00:24:55,515 --> 00:24:58,554
the week on Sunday night, what have I
accomplished on...
466
00:24:58,554 --> 00:24:59,835
At the end of Friday.
467
00:25:00,394 --> 00:25:02,875
And then I have, like, the quarterly focus.
468
00:25:02,875 --> 00:25:05,274
So, like, today today is September 30.
469
00:25:05,274 --> 00:25:09,649
So we're gonna have our last quarter of the
year starting tomorrow.
470
00:25:09,890 --> 00:25:11,009
It gave me, like...
471
00:25:11,009 --> 00:25:15,170
Based on what you've been working on for the
whole year, this should be your focus for the
472
00:25:15,170 --> 00:25:17,009
next last quarter of the year.
473
00:25:17,009 --> 00:25:18,450
So this is just one example.
474
00:25:18,450 --> 00:25:19,089
And then...
475
00:25:19,089 --> 00:25:20,690
You're mentioning about the soul.
476
00:25:20,849 --> 00:25:21,170
Mhmm.
477
00:25:21,170 --> 00:25:29,005
So giving it the personality that the way the
founder would have liked to do how things are,
478
00:25:29,484 --> 00:25:37,410
I think, is what makes it more personable, but
it doesn't really replace the founder itself.
479
00:25:37,410 --> 00:25:43,170
At the end of the day, the founder still needs
to talk to it more often so that it can get to
480
00:25:43,170 --> 00:25:45,090
know you better, but it doesn't replace you.
481
00:25:45,090 --> 00:25:45,410
Right?
482
00:25:45,410 --> 00:25:46,289
So Mhmm.
483
00:25:46,289 --> 00:25:46,450
Mhmm.
484
00:25:46,545 --> 00:25:49,585
I think our edge, and I mentioned this in...
485
00:25:49,585 --> 00:25:55,424
If you guys wanted to get my 2027 top 10 future
trends, please do so through Alka.
486
00:25:55,424 --> 00:25:58,865
But one of the things that I was talking about
there is the trust factor.
487
00:25:58,865 --> 00:26:04,680
I don't know if you know the Sam Edelman trust
barometer in 2023, I think, or 2022 talking
488
00:26:04,680 --> 00:26:10,519
about trust has been diminished because of
technology, rightfully so.
489
00:26:10,519 --> 00:26:11,720
People Yes.
490
00:26:11,720 --> 00:26:12,119
Exactly.
491
00:26:12,525 --> 00:26:12,845
Yeah.
492
00:26:12,845 --> 00:26:15,325
People has been booting things on the Internet.
493
00:26:15,325 --> 00:26:17,565
Like, it's true, but sometimes it's not.
494
00:26:17,565 --> 00:26:23,884
So so our main advantage is, like, telling the
truth when you're doing your post, for example,
495
00:26:24,125 --> 00:26:27,964
sharing still that humanity of we're not
perfect.
496
00:26:27,964 --> 00:26:28,285
Right?
497
00:26:28,950 --> 00:26:34,629
And so that is is still an edge for us humans
in the age of AI.
498
00:26:35,269 --> 00:26:35,750
Right.
499
00:26:35,750 --> 00:26:36,069
No.
500
00:26:36,069 --> 00:26:37,909
That is so true because I...
501
00:26:37,909 --> 00:26:47,744
You know, there are some fears when it comes to
AI and how AI will replace, you know, humans,
502
00:26:47,744 --> 00:26:48,704
like, in the workplace.
503
00:26:48,704 --> 00:26:50,144
So what I totally do understand.
504
00:26:50,144 --> 00:26:50,384
So...
505
00:26:50,384 --> 00:26:52,224
And this was that trust as well.
506
00:26:52,384 --> 00:27:02,700
What would you say, Lourdes, that founders fear
that AI will strip away the, strip away the
507
00:27:02,700 --> 00:27:08,619
instincts of the company, the principles, the
the trust that's, they've already had in the
508
00:27:08,619 --> 00:27:11,579
organization that's made them successful.
509
00:27:11,579 --> 00:27:15,825
What would you say has been the fear of most
founders?
510
00:27:16,545 --> 00:27:19,345
I think it's the stealing.
511
00:27:19,345 --> 00:27:21,985
Their intellectual property is first and
foremost.
512
00:27:21,985 --> 00:27:23,265
Obviously, if...
513
00:27:23,505 --> 00:27:29,450
As you know, if you're using a public learning
language model, your data is probably out
514
00:27:29,450 --> 00:27:34,329
there, which we always say that is the main
advantage that we have having our own AI
515
00:27:34,329 --> 00:27:39,209
company is because we know that our data that's
proprietary is safe.
516
00:27:39,529 --> 00:27:40,329
And so Yeah.
517
00:27:40,329 --> 00:27:43,544
Do in your best case possible to
518
00:27:44,184 --> 00:27:49,384
be able to be covered so that all the
information that you put out there is
519
00:27:49,384 --> 00:27:50,184
protected.
520
00:27:50,585 --> 00:27:54,984
Another example of what I was talking you about
a while ago, I was listening to another
521
00:27:54,984 --> 00:27:59,980
podcast, and one of the things that when
ChatGPT first launched, there was actually a
522
00:27:59,980 --> 00:28:01,179
mayor in Australia.
523
00:28:01,179 --> 00:28:05,659
I think it was Melbourne, and he was talking
about when he first is starting to type his
524
00:28:05,659 --> 00:28:14,195
name on ChatGPT, it spewed a lot of wrong that
he was in jail, that he did bad things.
525
00:28:14,195 --> 00:28:15,715
He never did any of those.
526
00:28:15,715 --> 00:28:20,835
So making the long story short, he went to his
lawyer, and in fact, the lawyer was sending a
527
00:28:20,835 --> 00:28:24,515
defamation case because all of these are not
true at all.
528
00:28:24,950 --> 00:28:30,309
And so they didn't get an answer, but the next
day, when he typed his name, the information
529
00:28:30,309 --> 00:28:33,670
that came out of GPT was no longer...
530
00:28:33,670 --> 00:28:34,150
He's...
531
00:28:34,150 --> 00:28:37,269
He doesn't have all these things that appeared
originally.
532
00:28:37,990 --> 00:28:45,015
But then another person who didn't name him,
but basically kind of use a generic of, like,
533
00:28:45,015 --> 00:28:48,214
what can you say about this person and doing
this doing this?
534
00:28:48,214 --> 00:28:50,534
It still spewed out the bad things.
535
00:28:50,535 --> 00:28:51,654
So Oh, wow.
536
00:28:51,654 --> 00:28:52,134
Yes.
537
00:28:52,134 --> 00:28:53,414
So we have to be careful.
538
00:28:53,414 --> 00:28:54,134
It's getting better.
539
00:28:54,679 --> 00:28:55,160
Mhmm.
540
00:28:55,160 --> 00:28:55,400
Mhmm.
541
00:28:55,400 --> 00:28:57,720
But at the same time, we have to protect
ourselves too.
542
00:28:57,720 --> 00:29:02,839
So do whatever means possible for you if you
can to avoid that intellectual property
543
00:29:02,839 --> 00:29:04,920
because, as you know, in the age of...
544
00:29:04,920 --> 00:29:09,794
I call it I call it the society five point o or
in the Internet of things. And
545
00:29:09,634 --> 00:29:16,594
And now with artificial intelligence era, our
main advantage as a human would be as creators.
546
00:29:16,835 --> 00:29:17,315
You're...
547
00:29:17,315 --> 00:29:19,234
It's the imagination society.
548
00:29:19,554 --> 00:29:22,429
And so right now, protect that intellectual
property.
549
00:29:22,670 --> 00:29:23,390
Yes.
550
00:29:23,390 --> 00:29:23,950
Absolutely.
551
00:29:23,950 --> 00:29:25,309
We absolutely have to.
552
00:29:25,390 --> 00:29:27,789
And talking about trends, your final question.
553
00:29:27,950 --> 00:29:33,630
Talking about trends, what would you say would
be the the trends in the next five to ten years
554
00:29:33,630 --> 00:29:40,054
will be the strongest company which implements
AI tools.
555
00:29:41,414 --> 00:29:43,575
Where would you say the trend is going?
556
00:29:44,134 --> 00:29:46,294
That is a very, very good question.
557
00:29:46,294 --> 00:29:52,630
If you guys can go to my LinkedIn, I have,
like, a video one one minute reel of each of
558
00:29:52,630 --> 00:29:54,149
these 10 future trends.
559
00:29:54,150 --> 00:29:59,190
But talking about AI, one of the things,
obviously, is no longer about the tools.
560
00:29:59,190 --> 00:30:02,230
It's obviously around, can it do the work for
us?
561
00:30:02,230 --> 00:30:06,150
As you know, recently, Meta just launched Muse.
562
00:30:06,150 --> 00:30:11,134
I'm starting to use it now because one of the
things that I really don't like about some of
563
00:30:11,134 --> 00:30:12,575
the other tools would be...
564
00:30:13,134 --> 00:30:17,295
I have a stack of tools, and then I have to go
from one tool to another because the other tool
565
00:30:17,295 --> 00:30:18,654
doesn't know the context.
566
00:30:18,654 --> 00:30:25,190
But with Muse, because a lot of us are already
connected on Facebook and Instagram, Meta,
567
00:30:25,190 --> 00:30:25,589
obviously.
568
00:30:25,589 --> 00:30:28,789
And on my phone, I got TikTok and I got
LinkedIn.
569
00:30:29,029 --> 00:30:30,230
It knows already.
570
00:30:30,230 --> 00:30:30,470
Right?
571
00:30:30,470 --> 00:30:31,830
So I'm experimenting on that.
572
00:30:31,830 --> 00:30:35,589
And they actually just launched Dots, which is
also a personal AI agent, which is a
573
00:30:35,589 --> 00:30:36,950
competition for Grokbot.
574
00:30:36,950 --> 00:30:37,910
And I'm sorry, Claude.
575
00:30:38,194 --> 00:30:39,634
Right now, Codex...
576
00:30:39,634 --> 00:30:43,634
I actually like Codex more than Claude other
than our own LLM.
577
00:30:43,634 --> 00:30:45,794
I love our own LLM for business.
578
00:30:45,795 --> 00:30:47,875
I don't depend on the generic one.
579
00:30:47,875 --> 00:30:51,315
I use our own LLM as, you know, CoreBrain and
JD five now.
580
00:30:51,554 --> 00:30:51,795
Right.
581
00:30:52,380 --> 00:30:55,900
But there are certain things that I still use
the other stuff.
582
00:30:55,900 --> 00:30:56,940
So I just...
583
00:30:56,940 --> 00:31:00,380
Like, if I'm just gonna do something for
front...
584
00:31:00,380 --> 00:31:02,140
For fun, I just use the free ones.
585
00:31:02,140 --> 00:31:11,634
So for fun, for example, would be I'd like an
image of a mascot that can represent my product
586
00:31:11,634 --> 00:31:12,354
brand.
587
00:31:12,355 --> 00:31:14,034
So I I don't actually...
588
00:31:14,034 --> 00:31:17,234
Before, I used image generator on a JD one,
actually.
589
00:31:17,315 --> 00:31:19,634
But now I'm actually using...
590
00:31:20,690 --> 00:31:22,690
Right now, Higgs field and Nano Banana.
591
00:31:22,690 --> 00:31:27,249
Higgs field, obviously, for, video and Nano
Banana for, image.
592
00:31:27,809 --> 00:31:28,210
Right.
593
00:31:28,210 --> 00:31:28,690
Exactly.
594
00:31:28,690 --> 00:31:29,809
And then also Gemini.
595
00:31:29,809 --> 00:31:33,569
I heard Gemini is also good too for image
creation.
596
00:31:34,315 --> 00:31:34,875
I haven't used...
597
00:31:34,875 --> 00:31:35,595
Have you tried?
598
00:31:35,595 --> 00:31:41,355
I haven't used Gemini for image creation, but I
I have a content creator assistant.
599
00:31:41,674 --> 00:31:49,069
And I actually put some context on Gemini gems,
and I created, like, an AI agent that she can
600
00:31:49,069 --> 00:31:51,309
ask if I'm not there because I fed...
601
00:31:51,309 --> 00:31:56,190
I trained the gem to able to think like me, and
we're using that same company email.
602
00:31:56,190 --> 00:32:02,325
So I told her that when I'm traveling from the
line away, ask the gem first, and then we
603
00:32:02,325 --> 00:32:02,964
practice it.
604
00:32:02,964 --> 00:32:07,444
Like, if I'm still here, I ask her to ask some
question if I will actually decide the same
605
00:32:07,444 --> 00:32:09,284
way, and so it's trained that way.
606
00:32:09,444 --> 00:32:10,085
It's trained.
607
00:32:10,085 --> 00:32:10,565
Well, that...
608
00:32:10,565 --> 00:32:11,364
That's so good.
609
00:32:11,365 --> 00:32:16,740
I mean, as I said, you know, there were so many
AI tools, and can be overwhelming for anyone as
610
00:32:16,740 --> 00:32:18,899
to what they need to use for what.
611
00:32:19,460 --> 00:32:23,220
But lord, this has been such a powerful
conversation.
612
00:32:23,460 --> 00:32:29,714
When it comes to AI, there is so many tools,
but AI can obviously make our lives so much
613
00:32:29,714 --> 00:32:33,474
easier and so much better in multitude of ways.
614
00:32:33,875 --> 00:32:37,075
Thank you to each and everyone for tuning in
today.
615
00:32:37,075 --> 00:32:41,714
Elodas, where can people find you, and how can
we connect and serve you better?
616
00:32:42,690 --> 00:32:44,769
Thank you so much for having me on the show.
617
00:32:44,769 --> 00:32:45,889
This has been a blast.
618
00:32:45,889 --> 00:32:48,609
And as always, time flies when we're having
fun.
619
00:32:48,609 --> 00:32:50,049
I'm active on social media.
620
00:32:50,049 --> 00:32:53,569
You can find me on Facebook, Instagram, TikTok,
and LinkedIn.
621
00:32:53,889 --> 00:32:59,545
And my website is sustainabilityteam.ai, and I
look forward to connecting with your audience.
622
00:32:59,545 --> 00:33:01,305
Thank you so much for having me, Alka.
623
00:33:01,465 --> 00:33:02,424
You're welcome.
624
00:33:02,424 --> 00:33:03,305
Thank you so much.
625
00:33:03,305 --> 00:33:03,865
And,
626
00:33:04,025 --> 00:33:08,904
Lourdes, thank you for also reminding us AI
isn't about speed or automation.
627
00:33:09,305 --> 00:33:13,619
It's about preserving the knowledge, protecting
protecting the the culture culture and and the
628
00:33:13,465 --> 00:33:20,100
the trust, but also building reliable systems
that can help the company grow without losing
629
00:33:20,100 --> 00:33:20,660
its soul.
630
00:33:20,660 --> 00:33:26,235
And thank you once again to each and everyone
for tuning in, and make sure you like and
631
00:33:26,235 --> 00:33:27,595
subscribe to the channel.
632
00:33:27,595 --> 00:33:33,275
In this way, we're gonna bring more amazing
guests like Nordisk Gant and more inspirational
633
00:33:33,275 --> 00:33:34,154
conversation.
634
00:33:34,154 --> 00:33:35,595
So until next time.
635
00:33:35,595 --> 00:33:36,634
Thank you for joining us.
636
00:33:36,634 --> 00:33:37,275
Bye for now.
637
00:33:38,662 --> 00:33:40,102
Thank you, Lordess.
638
00:33:40,102 --> 00:33:41,302
That's amazing.
639
00:33:41,622 --> 00:33:42,422
Thank you.
