April 1, 2025 • 21 mins
In this episode of the "HR Mixtape," host Shari Simpson welcomes Luis Garcia, president and co-founder of PETE, to discuss the transformative impact of AI on workforce training and learning development. With over 25 years of experience in digital education and ed tech, Luis shares his journey and insights into how AI can enhance personalized learning experiences and improve evaluation methods in the workplace.
Key Takeaways:
- AI in Learning: Discover how AI can create adaptive learning models that personalize training experiences and evaluate learning outcomes effectively.
- Challenges in Hiring: Understand the complexities of modern hiring processes and how AI can complicate rather than simplify recruitment.
- Getting Started with AI: Learn practical tools and strategies for individuals and businesses to embrace AI technology in their professional lives.
Tune in to explore how AI is reshaping the future of work and education! Guest(s): Luis Garcia, President and CoFounder, PETE
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:02):
You're listening to the HR Mixtape. Your podcast with
the perfect mix of practical advice, thought provoking interviews, and
stories that just hit different so that work doesn't have to feel,
well, like work. Now, your host,
Joining me today is Luis Garcia, president and co-founder of
PETE. With over 25 years of experience in digital education
(00:24):
and ed tech, Luis is transforming workforce training through AI
powered learning. He's known for scaling startups, driving results,
and being a respected voice in AI innovation. Luis is
(00:46):
So I just got back from the Transform conference out
in California and AI is still like
one of the hottest topics in HR. And so I was
so glad that we were able to connect and we're going to talk about
AI. And I'd love if you could maybe set the stage by telling us
a little bit about your journey and your passion in the AI space.
(01:08):
Thank you so much and so I have
a long journey with AI as it turned out. Well, you know, AI has
been around for 50 years and so and folks that. He
sees that it is in the news every single day and it's become kind
of a household name. But it's been around for
a very long time. And so
(01:31):
my first encounter with AI was in college in
the early 90s. And as I took an artificial
intelligence a course back
in 1993 or something like that. And then
when I joined the workforce, it was as a software engineer,
which is just a tool that, you know, in the early years was
(01:54):
more about you creating your own AI
machines to solve particular problems, find patterns, or try
to do better predictions. And
then I evolved more into an executive and things like that, so
I've been watching more form of art than as an engineer. But
at some point in my career, I got into education almost accidentally and
(02:18):
was hired by a university to create an online university. And
so at the time, I wasn't really a learning executive. I
was just a technology exec. So I did what
software engineers do and do a pilot and try to collect
data and just try to understand what this learning thing was. the
(02:39):
a couple of years of pilots and then I designed a software, a
software, you know, learning management system early
2000s I'm speaking about now and because I didn't really
like the options back then. And so we we
we built it and then I end up spearheading
the effort for the university, which tripled the size of
(03:02):
the university. And we went in a couple of years, we
have 5000 degree seeking students. And then a couple of years later, we
had 12,000 degree seeking students. And I
had 1000 employees on their meeting. And it was a great, great
effort and example of hyper growth and hiring
people. But I became very familiar with the
(03:23):
challenges of creating digital learning.
And and even for workforce learning, because when
you grow very fast, then you have to have an effort to onboard people
and train them in that you are launching degree programs,
you know, five or six a year. So you can train people how
to think about that. So so that two problems
(03:47):
bubble to the top. And the first one was was
how do you create training materials for training
experiences in a sense? This is really hard to do.
But folks don't understand if you're in a classroom with an expert in front of you, and
that expert is a good communicator, then you feel very good, you
feel educated. But the moment you remove that expert, those
(04:10):
PowerPoints in the background that no one's paying attention to, those become the teacher.
And so creating materials for effective training is
a very big deal. And in workforce
learning, unless you're a company with a
lot of resources that can hire a learning department with instructional designers
(04:30):
and all that, you basically get boxed out of that. You
are down to using your experts as trainers, getting
them out of their jobs. So that's problem number one. Problem
number two, with existing all learning,
regardless of the workforce or traditional, is that
how do you do evaluation of learning in digital learning at
(04:52):
scale? And tests are a
terrible way to actually evaluate learning, but
it's the best that we have that it will be effective and scalable.
In the digital world, even better, because you just can think of things and it
can be automatically But
really, unless you ask the questions correctly, you
(05:14):
have really no way to personalize the evaluation, which
is the most effective way to do evaluation. So those
are the two problems that we want to solve. And
when Genentech AI came to be, and
my partner, who had been in another tech
startup and had very, very successful, it was a unicorn, exited
(05:37):
from that, he had gone through the same problem of high growth and having to
train people and seeing you
know, very closely how hard it was. And in
his own words, I thought it was going to be a couple hundred hours, and they end up being thousands
of hours. And at
(05:57):
the time I had left my job at the university, I was working with startups.
So we had launched and said, do you think we can use Genentech AI to solve this
problem? And I said, yes. Because when
it became available, it became very clear
that you can use the power of
creating content was there. But
(06:19):
I was most excited about how can we use a
vectorized knowledge base to create
an experience that will act as if the expert is asking
you questions and analyzing the answers
against learning outcomes. And we built
Well, it's so, it's so fascinating because it's
(06:42):
near and dear to my heart. I'm actually working on my doctorate and
the research that I want to get into has to do with adaptive
learning models in the digital space, which is right
up your alley and everything that you're talking about and everything that I'm seeing
and hearing in that learning and development space when we're thinking about AI.
You nailed it in that there's still this group that has to
(07:05):
do a lot of creation on their own. So having these tools
in place is amazing. They don't just have to go to YouTube and
find a video, right? They can create this training themselves.
So I love that. But then the level up to it
where you're thinking about these personalized journeys and these conversations
with AI that can really push you forward, that's
(07:27):
where it's going. How do you see that? kind of blowing up
You know, it's interesting because in learning, you
know, unless you're really, really into it, you
know, talking about evaluation of learning, or we call it assessment, and
(07:47):
it's a very hot conversation that has been happening for a very long time, but
not a lot of good solutions for it, because the solutions are never very scalable. But
unless you're in it, you never really think about that. And you
really, really think about how do I create the content so people can take it and
I can cross off my list. And so for
the customers that we that we target, which are, you know, between 50 to
(08:11):
500 employees, And without a learning department and
without people to think about that, it's so interesting when we tell
them, it's like, yeah, well, we can do the content. That's fine. And I actually
think that's going to be ubiquitous for learning management systems
in the future. And I said, but have you thought about the fact
that you don't know if they actually learn? And
(08:34):
more importantly, sometimes their solutions about shadowing and
things, you know, it can be effective for certain things, but when you're doing shadowing, you
know, you pick up the good practices and the bad practices too. So it's
a propagation of practices and good and bad. And so
how do you make sure that that is effective? And
then they get really excited about that. They say, oh, I could use that for, you
(08:55):
know, in customer service to train the
reps on how to deescalate a call. You know, and
we have a bank that use them to be trained and practice
on cases that are not very common and that come to your window.
Or a stadium uses it to train the people that work on
the event day to tackle certain situations. And
(09:19):
it's conversational. And always having a conversation with
you is evaluating your answers against the learning outcomes
of the experience. So I think it's a
very critical thing to have. And
there has been no other technology in the past that will allow you to do that.
Well, it's exciting to hear what you're working on. How do you see AI
(09:40):
changing other areas? So from the evaluation perspective, I
love that. You know, it does bring up the question in my head, though,
as you think about some of these conversations we're having around
knowledge, right? I'm glad that you mentioned kind of being in the 90s,
because I showed this before being in college in
the late 90s. And I remember when that transition from
(10:02):
you know, your card catalog in the library to using, you
know, Google to search something. And I remember professors being at the time being
like, well, you got to remember how to use the library card catalog,
like it's not going away. And like all this fear
of what Google was going to do is going to make us dumb, right? It wasn't going to
help us. I think we're kind of having that same sort
(10:24):
of debate if we think that AI is going to make
a stump. I don't think it is. What are you seeing in
Well, I mean, historically, technology wins. And
it doesn't matter how much people, I always give the examples like
I remember a time in which teachers were
(10:47):
not allowed a calculator in the classroom. So
this is a debate that has been
taking place for a very long time. And then it was the computer. And
then it was, as you say, searching on the Internet. And
technology always wins. And so my
(11:07):
message to teachers is and always is embrace it, take
it, take your curriculum to the next level because
of it, because it's not going away. Once it's adopted, the
learners will push you through it. And so you
have no choice but to use it. And so you may as well be part
of it. In terms
(11:28):
of how it's affecting areas, affecting all areas, I think that
when I talk to business owners, I encourage them to have
a serious conversation about where AI
can be applied to your business. Because if you're not doing your competition, And
it comes down to the individual also. How do you use it yourself? Because whatever
(11:48):
it is that you do, if you're not using it, somebody else that does what you do is
using it and will have an edge already. So
don't fight the calculator, you know? Now,
having said that, I do think that there are areas that are, you know,
specifically when we talk about human resources, that
(12:09):
is going to be very critical for it.
I actually believe that today hiring is broken and
that technology broke hiring altogether. And
I am conducting first interviews for people I hire through
AI, and AI is doing the first interview. Very
(12:30):
soon, people are going to be sending their own avatars to have
their first conversation with AI, and it's going to be
ruined all over again. So
that part I think that we're going through a troublesome time
and that instead of making hiring easier,
technology has made hiring more difficult for everyone, for the
(12:50):
applicant, for the employer. And if you wanted to
expect better matching, it's actually making it worse because people
can We have bots now that can rewrite your resume
to match the job description. So basically, everybody has the perfect
job description, the perfect resume. And none
of that is helping. And so we have to, this is an area that
(13:11):
I think it has to be rethought. And
my answer to people today is get out of your house and go meet people
like the way we used to do in the 90s. And because
it's also bad for the employer, I don't want to, I mean, I opened a
position the other day, I got 200 applicants in two hours. I can't, I
can't read that. And obviously,
(13:33):
when I brought a bot that will, you know, do the
work for me, but then there is like somebody turns
around, it's like, how about this guy? I'm like, oh, yeah, sure. Everybody else
out there doing that. I look at this one because at least I have some kind of endorsement. Yeah.
And so so there are areas in which AI
is not going to help. It's going to make things worse. And the content
(13:55):
on the Internet is, you know, multiplying scales
that we had never seen with a lot of, you know, random
thoughts with no essence. And so
we're going to have to get over that. But
it always gets to a control place
where we then can take it to the next level. I
(14:18):
do think that the net value will be way
higher. I actually think the generative AI becomes the
most transformative technology in my lifetime. And that's a
hard thing to say, because I've seen the transistor, I've seen the personal computer,
I've seen the internet, I've seen social media, the smartphone, and
all of these technologies are transformative. And I do think
(14:42):
Yeah, I actually couldn't agree more with that. I think it's going to be fascinating to
see what happens in the next, you know, 12 months, not
even five years, right? Everything's moving so quickly. What
do you say to the person who's listening, who's like, yeah, okay, I've heard
about AI. I love it. I want to get into it. I
don't even know where to start. Like, personally or
(15:03):
professionally, what are maybe some tools that you
have used or you've recommended to help people kind of get their feet wet with
Yeah, that's a great question. And I actually encourage everyone to do
it. And there, you know, if you asked me this question two
years ago, it would have been a little different. Today, there's a lot of
tools. But, you
(15:25):
know, the most famous is chatGPT by OpenAI. You can go
to chatGPT or openai.com, and they have several
options there. And then create an
account. And for free, you can do a lot. And
then just don't even apply it to your job. Be curious about
what else it can do. I usually do demonstrations, but I get
(15:46):
a piece of an article, put it in there, and I start telling
the agent to say, you know, this piece of news, let's write a
different headline. And let's make it very dramatic. Or let's
write it in half the words. Or now make this piece
of news as if it was the opening of a movie. And I
now do this like it was a telenovela, you know, and then having
(16:08):
fun with it is it's not threatening anybody's job unless you're a writer for
telenovelas. But but but
then then then you start getting familiar. Oh, if I could do this,
maybe I could do that for my job. And so so that's the
way I got started is just by playing with it. And
the next step, if I being so bold, is like get
(16:29):
a subscription and And the
engine is a lot better when you get a subscription for JGPT or
for Claude from Anthropic or Perplexity is
one that a lot of people like because it gives you citations
and things like that. But when
you pay the subscription, you kind of force yourself. You're paying now, so you
(16:50):
force yourself to use it. And so that's what I did to
myself. Like, I just kind of get the subscription to force myself to use it every day.
And I had never looked back. I think it's the first 20 bucks, the best 20 bucks
that I spent every month. And because the
amount of things that allows me to do, it just made
me. it multiplied me because I
(17:11):
can do work so much faster. And so that's what I would recommend for
everybody to do. You can go for JGPT, you can go
with Claude by Perplexity.
There are also, if you're not into text and you want to do images, then
there are a lot of options for image generation now that
are a ton of fun to work with. And I just think that the
(17:34):
text use case is a lot more interesting
I don't typically use tools like
ChatGPT to be a legal reference.
That being said, one of the things that I do find it very helpful is
if you want to learn a new concept or you want to learn about some
(17:54):
case law that exists in the HR space, it is a really
good place to kind of have that conversation and
not feel like you're going to get judged for asking questions because you're not
doing it to an employment lawyer or you know, to
your CEO, you're just having this conversation. It was
funny, my husband's a fireman and he had
(18:15):
a union question the other day. And I was like, hey, you know, I haven't looked at that
in a while. And kind of went down this whole rabbit hole for, I don't know,
20, 30 minutes, just going back and forth and saying, tell me how that applies to this. And, you
know, how would I, if this was the scenario, does do
both laws apply or does only one law apply? And it was really informative
and talk about You know, the amount of knowledge that I could get in
(18:37):
that 20 minute conversation that before would
have taken me a bunch of Google searches, a bunch of weird trying
to connect the dots. And it's doing all that work for me. So
It's huge. That's another great way to interact
with it. I have a friend that calls them jams. literally
(19:00):
schedule half hour of their time to
do a jam
with a LLM, and to
tackle a particular issue that you would like to have a conversation
with somebody with. It's like, how should I approach this?
If I were to create a report about
(19:21):
X, Y, and Z, how would I start? What would be
Yeah, it's like mind mapping and I don't know, I don't want
to make a bad reference, but it's definitely leveled
up for sure. As we wrap up our conversation, what
is kind of the one thing that you want to leave our audience with
(19:43):
from, you know, thinking about AI and its impact to
learning and development and HR as a whole? I think
Yeah, so I love coming to HR podcasts because we
talk to a lot of HR leaders. And I don't know why at some
point someone decided that the leader of HR somehow is a learning
(20:04):
expert, and then charged
them to do the training for the company. And
so we talked to a lot of HR leaders that, you know, they throw the ball
into the court and they don't know what to do. But if you're in
a smaller company, then please call us and
let us be your platform for learning that requires no
(20:25):
instructional designers to help your expert create courses and get
back to the job. And so if
this is something that resonates, then go to our website and
pete.com, that's a very easy domain, p-e-t-e.com, slash
Yeah, I love that. This has been a great conversation. Thank you so much
You're listening to the HR Mixtape. Your podcast with
the perfect mix of practical advice, thought provoking interviews, and
stories that just hit different so that work doesn't have to feel,
well, like work. Now, your host,
Joining me today is Luis Garcia, president and co-founder of
PETE. With over 25 years of experience in digital education
(00:24):
and ed tech, Luis is transforming workforce training through AI
powered learning. He's known for scaling startups, driving results,
and being a respected voice in AI innovation. Luis is
(00:46):
So I just got back from the Transform conference out
in California and AI is still like
one of the hottest topics in HR. And so I was
so glad that we were able to connect and we're going to talk about
AI. And I'd love if you could maybe set the stage by telling us
a little bit about your journey and your passion in the AI space.
(01:08):
Thank you so much and so I have
a long journey with AI as it turned out. Well, you know, AI has
been around for 50 years and so and folks that. He
sees that it is in the news every single day and it's become kind
of a household name. But it's been around for
a very long time. And so
(01:31):
my first encounter with AI was in college in
the early 90s. And as I took an artificial
intelligence a course back
in 1993 or something like that. And then
when I joined the workforce, it was as a software engineer,
which is just a tool that, you know, in the early years was
(01:54):
more about you creating your own AI
machines to solve particular problems, find patterns, or try
to do better predictions. And
then I evolved more into an executive and things like that, so
I've been watching more form of art than as an engineer. But
at some point in my career, I got into education almost accidentally and
(02:18):
was hired by a university to create an online university. And
so at the time, I wasn't really a learning executive. I
was just a technology exec. So I did what
software engineers do and do a pilot and try to collect
data and just try to understand what this learning thing was. the
(02:39):
a couple of years of pilots and then I designed a software, a
software, you know, learning management system early
2000s I'm speaking about now and because I didn't really
like the options back then. And so we we
we built it and then I end up spearheading
the effort for the university, which tripled the size of
(03:02):
the university. And we went in a couple of years, we
have 5000 degree seeking students. And then a couple of years later, we
had 12,000 degree seeking students. And I
had 1000 employees on their meeting. And it was a great, great
effort and example of hyper growth and hiring
people. But I became very familiar with the
(03:23):
challenges of creating digital learning.
And and even for workforce learning, because when
you grow very fast, then you have to have an effort to onboard people
and train them in that you are launching degree programs,
you know, five or six a year. So you can train people how
to think about that. So so that two problems
(03:47):
bubble to the top. And the first one was was
how do you create training materials for training
experiences in a sense? This is really hard to do.
But folks don't understand if you're in a classroom with an expert in front of you, and
that expert is a good communicator, then you feel very good, you
feel educated. But the moment you remove that expert, those
(04:10):
PowerPoints in the background that no one's paying attention to, those become the teacher.
And so creating materials for effective training is
a very big deal. And in workforce
learning, unless you're a company with a
lot of resources that can hire a learning department with instructional designers
(04:30):
and all that, you basically get boxed out of that. You
are down to using your experts as trainers, getting
them out of their jobs. So that's problem number one. Problem
number two, with existing all learning,
regardless of the workforce or traditional, is that
how do you do evaluation of learning in digital learning at
(04:52):
scale? And tests are a
terrible way to actually evaluate learning, but
it's the best that we have that it will be effective and scalable.
In the digital world, even better, because you just can think of things and it
can be automatically But
really, unless you ask the questions correctly, you
(05:14):
have really no way to personalize the evaluation, which
is the most effective way to do evaluation. So those
are the two problems that we want to solve. And
when Genentech AI came to be, and
my partner, who had been in another tech
startup and had very, very successful, it was a unicorn, exited
(05:37):
from that, he had gone through the same problem of high growth and having to
train people and seeing you
know, very closely how hard it was. And in
his own words, I thought it was going to be a couple hundred hours, and they end up being thousands
of hours. And at
(05:57):
the time I had left my job at the university, I was working with startups.
So we had launched and said, do you think we can use Genentech AI to solve this
problem? And I said, yes. Because when
it became available, it became very clear
that you can use the power of
creating content was there. But
(06:19):
I was most excited about how can we use a
vectorized knowledge base to create
an experience that will act as if the expert is asking
you questions and analyzing the answers
against learning outcomes. And we built
Well, it's so, it's so fascinating because it's
(06:42):
near and dear to my heart. I'm actually working on my doctorate and
the research that I want to get into has to do with adaptive
learning models in the digital space, which is right
up your alley and everything that you're talking about and everything that I'm seeing
and hearing in that learning and development space when we're thinking about AI.
You nailed it in that there's still this group that has to
(07:05):
do a lot of creation on their own. So having these tools
in place is amazing. They don't just have to go to YouTube and
find a video, right? They can create this training themselves.
So I love that. But then the level up to it
where you're thinking about these personalized journeys and these conversations
with AI that can really push you forward, that's
(07:27):
where it's going. How do you see that? kind of blowing up
You know, it's interesting because in learning, you
know, unless you're really, really into it, you
know, talking about evaluation of learning, or we call it assessment, and
(07:47):
it's a very hot conversation that has been happening for a very long time, but
not a lot of good solutions for it, because the solutions are never very scalable. But
unless you're in it, you never really think about that. And you
really, really think about how do I create the content so people can take it and
I can cross off my list. And so for
the customers that we that we target, which are, you know, between 50 to
(08:11):
500 employees, And without a learning department and
without people to think about that, it's so interesting when we tell
them, it's like, yeah, well, we can do the content. That's fine. And I actually
think that's going to be ubiquitous for learning management systems
in the future. And I said, but have you thought about the fact
that you don't know if they actually learn? And
(08:34):
more importantly, sometimes their solutions about shadowing and
things, you know, it can be effective for certain things, but when you're doing shadowing, you
know, you pick up the good practices and the bad practices too. So it's
a propagation of practices and good and bad. And so
how do you make sure that that is effective? And
then they get really excited about that. They say, oh, I could use that for, you
(08:55):
know, in customer service to train the
reps on how to deescalate a call. You know, and
we have a bank that use them to be trained and practice
on cases that are not very common and that come to your window.
Or a stadium uses it to train the people that work on
the event day to tackle certain situations. And
(09:19):
it's conversational. And always having a conversation with
you is evaluating your answers against the learning outcomes
of the experience. So I think it's a
very critical thing to have. And
there has been no other technology in the past that will allow you to do that.
Well, it's exciting to hear what you're working on. How do you see AI
(09:40):
changing other areas? So from the evaluation perspective, I
love that. You know, it does bring up the question in my head, though,
as you think about some of these conversations we're having around
knowledge, right? I'm glad that you mentioned kind of being in the 90s,
because I showed this before being in college in
the late 90s. And I remember when that transition from
(10:02):
you know, your card catalog in the library to using, you
know, Google to search something. And I remember professors being at the time being
like, well, you got to remember how to use the library card catalog,
like it's not going away. And like all this fear
of what Google was going to do is going to make us dumb, right? It wasn't going to
help us. I think we're kind of having that same sort
(10:24):
of debate if we think that AI is going to make
a stump. I don't think it is. What are you seeing in
Well, I mean, historically, technology wins. And
it doesn't matter how much people, I always give the examples like
I remember a time in which teachers were
(10:47):
not allowed a calculator in the classroom. So
this is a debate that has been
taking place for a very long time. And then it was the computer. And
then it was, as you say, searching on the Internet. And
technology always wins. And so my
(11:07):
message to teachers is and always is embrace it, take
it, take your curriculum to the next level because
of it, because it's not going away. Once it's adopted, the
learners will push you through it. And so you
have no choice but to use it. And so you may as well be part
of it. In terms
(11:28):
of how it's affecting areas, affecting all areas, I think that
when I talk to business owners, I encourage them to have
a serious conversation about where AI
can be applied to your business. Because if you're not doing your competition, And
it comes down to the individual also. How do you use it yourself? Because whatever
(11:48):
it is that you do, if you're not using it, somebody else that does what you do is
using it and will have an edge already. So
don't fight the calculator, you know? Now,
having said that, I do think that there are areas that are, you know,
specifically when we talk about human resources, that
(12:09):
is going to be very critical for it.
I actually believe that today hiring is broken and
that technology broke hiring altogether. And
I am conducting first interviews for people I hire through
AI, and AI is doing the first interview. Very
(12:30):
soon, people are going to be sending their own avatars to have
their first conversation with AI, and it's going to be
ruined all over again. So
that part I think that we're going through a troublesome time
and that instead of making hiring easier,
technology has made hiring more difficult for everyone, for the
(12:50):
applicant, for the employer. And if you wanted to
expect better matching, it's actually making it worse because people
can We have bots now that can rewrite your resume
to match the job description. So basically, everybody has the perfect
job description, the perfect resume. And none
of that is helping. And so we have to, this is an area that
(13:11):
I think it has to be rethought. And
my answer to people today is get out of your house and go meet people
like the way we used to do in the 90s. And because
it's also bad for the employer, I don't want to, I mean, I opened a
position the other day, I got 200 applicants in two hours. I can't, I
can't read that. And obviously,
(13:33):
when I brought a bot that will, you know, do the
work for me, but then there is like somebody turns
around, it's like, how about this guy? I'm like, oh, yeah, sure. Everybody else
out there doing that. I look at this one because at least I have some kind of endorsement. Yeah.
And so so there are areas in which AI
is not going to help. It's going to make things worse. And the content
(13:55):
on the Internet is, you know, multiplying scales
that we had never seen with a lot of, you know, random
thoughts with no essence. And so
we're going to have to get over that. But
it always gets to a control place
where we then can take it to the next level. I
(14:18):
do think that the net value will be way
higher. I actually think the generative AI becomes the
most transformative technology in my lifetime. And that's a
hard thing to say, because I've seen the transistor, I've seen the personal computer,
I've seen the internet, I've seen social media, the smartphone, and
all of these technologies are transformative. And I do think
(14:42):
Yeah, I actually couldn't agree more with that. I think it's going to be fascinating to
see what happens in the next, you know, 12 months, not
even five years, right? Everything's moving so quickly. What
do you say to the person who's listening, who's like, yeah, okay, I've heard
about AI. I love it. I want to get into it. I
don't even know where to start. Like, personally or
(15:03):
professionally, what are maybe some tools that you
have used or you've recommended to help people kind of get their feet wet with
Yeah, that's a great question. And I actually encourage everyone to do
it. And there, you know, if you asked me this question two
years ago, it would have been a little different. Today, there's a lot of
tools. But, you
(15:25):
know, the most famous is chatGPT by OpenAI. You can go
to chatGPT or openai.com, and they have several
options there. And then create an
account. And for free, you can do a lot. And
then just don't even apply it to your job. Be curious about
what else it can do. I usually do demonstrations, but I get
(15:46):
a piece of an article, put it in there, and I start telling
the agent to say, you know, this piece of news, let's write a
different headline. And let's make it very dramatic. Or let's
write it in half the words. Or now make this piece
of news as if it was the opening of a movie. And I
now do this like it was a telenovela, you know, and then having
(16:08):
fun with it is it's not threatening anybody's job unless you're a writer for
telenovelas. But but but
then then then you start getting familiar. Oh, if I could do this,
maybe I could do that for my job. And so so that's the
way I got started is just by playing with it. And
the next step, if I being so bold, is like get
(16:29):
a subscription and And the
engine is a lot better when you get a subscription for JGPT or
for Claude from Anthropic or Perplexity is
one that a lot of people like because it gives you citations
and things like that. But when
you pay the subscription, you kind of force yourself. You're paying now, so you
(16:50):
force yourself to use it. And so that's what I did to
myself. Like, I just kind of get the subscription to force myself to use it every day.
And I had never looked back. I think it's the first 20 bucks, the best 20 bucks
that I spent every month. And because the
amount of things that allows me to do, it just made
me. it multiplied me because I
(17:11):
can do work so much faster. And so that's what I would recommend for
everybody to do. You can go for JGPT, you can go
with Claude by Perplexity.
There are also, if you're not into text and you want to do images, then
there are a lot of options for image generation now that
are a ton of fun to work with. And I just think that the
(17:34):
text use case is a lot more interesting
I don't typically use tools like
ChatGPT to be a legal reference.
That being said, one of the things that I do find it very helpful is
if you want to learn a new concept or you want to learn about some
(17:54):
case law that exists in the HR space, it is a really
good place to kind of have that conversation and
not feel like you're going to get judged for asking questions because you're not
doing it to an employment lawyer or you know, to
your CEO, you're just having this conversation. It was
funny, my husband's a fireman and he had
(18:15):
a union question the other day. And I was like, hey, you know, I haven't looked at that
in a while. And kind of went down this whole rabbit hole for, I don't know,
20, 30 minutes, just going back and forth and saying, tell me how that applies to this. And, you
know, how would I, if this was the scenario, does do
both laws apply or does only one law apply? And it was really informative
and talk about You know, the amount of knowledge that I could get in
(18:37):
that 20 minute conversation that before would
have taken me a bunch of Google searches, a bunch of weird trying
to connect the dots. And it's doing all that work for me. So
It's huge. That's another great way to interact
with it. I have a friend that calls them jams. literally
(19:00):
schedule half hour of their time to
do a jam
with a LLM, and to
tackle a particular issue that you would like to have a conversation
with somebody with. It's like, how should I approach this?
If I were to create a report about
(19:21):
X, Y, and Z, how would I start? What would be
Yeah, it's like mind mapping and I don't know, I don't want
to make a bad reference, but it's definitely leveled
up for sure. As we wrap up our conversation, what
is kind of the one thing that you want to leave our audience with
(19:43):
from, you know, thinking about AI and its impact to
learning and development and HR as a whole? I think
Yeah, so I love coming to HR podcasts because we
talk to a lot of HR leaders. And I don't know why at some
point someone decided that the leader of HR somehow is a learning
(20:04):
expert, and then charged
them to do the training for the company. And
so we talked to a lot of HR leaders that, you know, they throw the ball
into the court and they don't know what to do. But if you're in
a smaller company, then please call us and
let us be your platform for learning that requires no
(20:25):
instructional designers to help your expert create courses and get
back to the job. And so if
this is something that resonates, then go to our website and
pete.com, that's a very easy domain, p-e-t-e.com, slash
Yeah, I love that. This has been a great conversation. Thank you so much
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