Hello, hello. I am here with Sean, very excited to chat with Sean today on the 99 Dev Problem
Show. Sean, I'd love for you to introduce yourself.
Hey, everyone. It's great to see you again. My name is Sean Faulkner, and I am currently
the AI entrepreneur in residence at a company called Confluent, which is famous for essentially
the Kafka open source project. Jay Krapse, the founder and the rest of the founders, created
that project and then spun that off into Confluent, which is now a publicly traded company for
the last three years and has about 3,500 employees. So, good size company. And I recently joined
a couple of just a couple of months ago.
Ooh. Well, I love your title. Say your title again.
AI entrepreneur in residence.
I love that. You said it very quickly, which is fine, but I think it's a really interesting
title. And so I'd love to unpack that a little bit. Like, what do you do over Confluent?
Yeah, this is a big question, right? I get that pretty much every day, even for people
inside at Confluent. They're like, what are you doing here? Everybody's excited about
being here, but what is it that you do? So, I mean, really, it's... So if you think about...
If you're familiar with the concept of an entrepreneur in residence, usually you see
those roles within venture capital firms, where they bring in somebody that has certain background
expertise. Maybe they've been a founder in the past and they're there for a while to
sort of spend some time. They get some resources in this sort of incubating and trying to figure
out what is their next business that they want to watch in a particular space. And at
the same time, they're also serving as a subject matter expert and offering some mentoring to
existing private portfolio. And in a similar spirit within larger companies, sometimes
larger companies will also have these EIR roles. But there, it's less about necessarily
spinning off like a new business that I'm going to be the CEO of and it's going to be
separate entity from Confluent. But how do you essentially create sort of like an innovation
arm within a company where they can drive to trying to create like either a new type
of product or a new business unit centered around like whatever your area expertise is.
And then for me, in particular with this role of AI entrepreneur residence, I did a master's
in PhD and postdoc years ago in computer science, my background there was in machine learning
and also applied machine learning across a bunch of different domains. And so it's kind
of dipping into my background expertise there. I've worked in industry doing, applying machine
learning as well. I was an entrepreneur at some point. So it's combining a lot of these
different skill sets. We're primarily focused on from a technology strategy point, the point
of view, like how do we drive Confluent as a AI thought leader? How do we align our product
offering with other parts of the business unit to start to essentially generate revenue
and solve problems for customers?
Yeah, I love that. That's really cool. I definitely want to unpack a little bit more
of that because there's some really awesome stuff I'm sure you're doing over there. You
alluded to it, but one of the first questions I like to ask is what's your developer education?
So you did share some of it, but if you want to kind of share all of that, we'd love to
hear what your formal education is.
Yeah, sure. So I spent a lot of time in school. But I started sort of engineering, maybe when
I was like 14 or 15 in high school, when I really fell in love with computers. And I
was fortunate to go to high school at the time where sort of the home PC era and the
internet was first sort of being introduced in mass to people. So that really, like, I
just became obsessed, essentially, like I grew up in a really small rural community
in Canada. So suddenly to be able to like learn anything that I wanted or talk to people
all over the world really just was super fascinating to me. And I would get up at like 435 a.m.
in the morning before school to because back then you had dial up internet and we had free
you had free internet from like 12 to 8 a.m. So we get up at like 435 a.m. before school
to get like three hours, three hours of free internet before before school started and
like work on websites. And I started looking at websites and then that kind of gets you
into, you know, basics HTML. And then it's like, well, I want to make this website do
something and then it's like, you know, that's kind of like gateway to like JavaScript or
something. And then, you know, older back end technologies like Pearl to write scripts.
And I started learning like, you know, basic and Java and all this sort of stuff. So that
was sort of the entry point. Then I went on to study computer science for my undergrad,
focused on theory and computation with a minor mass of very math, math heavy. And then I
did a master's degree again, like focused in sort of pattern recognition machine learning.
And then a PhD after that, working on sort of applied machine learning using machine
learning in combination with human and the loop expertise to solve sort of hard data
problems. And then move from Canada to the US after that to do a postdoc in bioinformatics.
And then while I was doing that postdoc, I also started a company, which is what where
I ended up leaving the world of academics into industry. But the entire time I was in
school, I also worked on the side as an engineer, software engineer for a variety of companies.
And part of that was because it was a way for me to pay for my education. But also, I
was always worried that at some point I might want to go back into industry. And I saw a
lot of people who focused on more research and academics kind of de skill their ability
to write code. And I was always worried about that might maybe happening. Like I knew a
lot of professors, brilliant people that couldn't write, you know, like a basic Hello World
program, because they just been too far away from it for a long time. So I was always nervous,
but so I always wanted to keep up my programming skills. So I would have just in case I needed
it. So I spent probably combined through all my education, like I ended up accumulating
my probably, you know, six, seven years of actual like engineering work during that time
as well. Beyond just what I was doing academically. And then I started a company where I was the
CTO founder of that company ran it for seven years. And then after that, I joined Google
in engineering. And then when I left Google, I was sort of I was leaving a team and engineering
and product. And then I joined a company called Skyflow, which is on a sort of data privacy
space. And that was probably my biggest like departure from sort of day to day engineering
work. I ended up doing reading the marketing team there. I can go into details of like
how that happened. I was like, you know, like I kind of accidentally became the CMO company
that spent three years there. And then now more recently joined Confluent to kind of
go back onto the technology side of the business.
Oh my gosh, I love that. Okay, I think we need to hear the story of how you accidentally
became a CMO. I think I can very much relate to probably how this story goes.
Well, so I originally joined Skyflow's head of developer relations, do some more stuff
that I did at Google more focused on like developer experience and, you know, improving
like our, you know, APIs, SDKs, engineering documentation, so on. And then about partly,
you know, halfway through my first year, the original CMO, the company didn't work out.
And there were a lot of challenges with the marketing team that he had built. So the CEO
came to me and said like, Hey, I want you to like step in and take over marketing on
an intram basis and figure out, you know, what's going on here and come up with a plan
to try to fix it. And the reason he had done that is because he had been an investor in
the company I'd started, you know, years ago, and I did a lot of go to market stuff there
because as a founder, you just end up being thrust into things that maybe you had absolutely
no business being thrust into, but there's nobody else to do that. I had tons of engineering
training and skills. I didn't know anything about like the business side of the business.
I just had to learn that stuff. So I got sort of like my MBA the hard way. And also like,
you know, whatever sort of marketing chops I had, I got the hard way as well through
a lot of experimentation and making mistakes. And so I ended up jumping in on the marketing
team and, you know, taking the lead there. And, you know, through the first six months,
I rebuilt most of the team. And we fixed a lot of sort of fundamental problems. And
a lot of it comes down to, I think, just like having a first principles mindset of like,
in asking questions, not being afraid of asking like, you know, quote unquote dumb questions,
right? And I think some advantage of being sort of a non traditional marketer there is
that I, I have a fresh set of eyes. I'm not coming in with a playbook that I've done 10
times. I'm just like, does this make sense or not make sense? And we sold to CTOs. So
I had been a CTO previously. So I could, you know, sort of figure out whether things made
sense to me, you know, does it pass the smell test? Does this feel authentic? Is the messaging
like to marketing, all these types of things. So there were some advantages there. And,
you know, so after six months, you know, look at reflecting on where we come, we'd like
to buy that star pipeline, we cut costs by 50%. And we were operating, you know, significantly
more efficiently. And I became, I guess, like someone a victim of my, you know, our own
success with that, where something that originally was more of an interim role became more of
a permanent role. But I was always clear to the company that my, I had no desire to be
like a career CMO. I like solving problems, but I felt like, you know, we had kind of
solved one of the fundamental problems. I continued to, you know, operate that capacity
for another year or so before I made the transition to going back into more of a technology leadership
role.
Oh my gosh, I love everything that you just shared because it's like everything that I
do in my day to day business today is like talking with technical founders and they're
like, I'm doing things I should not be doing. And it's usually marketing, right? And, and
I think something that you shed light on there too is like reducing costs, right? I think
that a lot of the marketing, traditional marketing playbooks have a huge investment in sort of
ad spend and these other types of big convoluted expensive things that don't necessarily drive
the results that, you know, companies actually need. So that I think it's really cool and
lucky for them that you fell into that role because it sounds like you really, you know,
created something absolutely beautiful over there in the marketing department.
Well, I've been, because when I had to do marketing at my company, like we were never
very well resourced and by the time I was really driving into a market, we were like
really under resourced. So we were like, you know, crawling on our bellies to the dirt
for years, trying to do everything on like a shoestring budget. So we had to really figure
out and be scrappy on, you know, what our investments were and always be asking ourselves,
like, does, is this the best way we can spend this money? You know, if it's $10,000, what
are the other ways we could spend $10,000? Do we think that that might deliver a higher
ROI or not? You have to be always sort of asking yourself these things. And the good
thing about sort of being starved for resources is it does create sort of this discipline
around, you know, does a dollar out equal, you know, a dollar in or more, right? And
you have to really be evaluating things like that. And I think one of the challenges that
companies sometimes go through is when learning these high growth phases where the market's
really good, getting money is really easy or relatively easy, then sort of the growth
at all costs and you lose sight of, hey, like, of that discipline of, does this make sense?
Is this just a, you know, is this smart growth or is this, you know, like inefficient growth,
essentially, and you get basically build up habits as a business of spending money rather
than, you know, essentially like making money?
Yes, yes, I agree. We just had a good little, I'm just reading, we had a question come in,
but I agree with that, honestly. And I think a lot of, a lot of founders are feeling that,
especially right now, because the VC space is very different right now. If you're going
after AI, here you go, here's your check. But if that's not a $100 billion C-dram,
exactly. If you're not in that space, though, it's like, where's your revenue, right? They
want to see revenue these days. And it's really difficult to do that, especially in that earlier
stage. I'm really curious if you're open to it, what business did you have? Like, if
you're willing to share, what did, what did you build?
So we were always interested in buildings for technology for like an underserved part
of the job market. Originally, like if you think about people who are like college-educated,
work and technology, we have a ton of tools built for us, whether you're on the hiring
side or you're on the side of a candidate, you know, you've linked in, you know, tons
of applicant tracking systems, there's a multi-billion dollar industry built around this. But your
work is like a tradesperson, where you work in restaurants, you know, whatever it is,
there's a lot less technology built for you, both on the hiring side and also on the, you
know, jobseeker side. But really back when we were doing it, like on the jobseeker side,
your best option was Craigslist. Or if you worked in Blue Collar, there's staffing agencies
that you could work with that would, you know, temporarily place you different places. So
originally we were focused on Blue Collar, temple labor, and that's what we originally
raised while I was still doing my postdoc. We raised close to $2 million to start that
business. And that's why I left academics to do that full time. And then we kind of
activated a number of times. There's kind of a long story of all the things that we
screwed up along the way. And, but eventually we settled on sort of this two sided marketplace
focused primarily on high turnover positions, like restaurants, hospitality and so forth.
And we were really early investors in mobile. And the original versions of the product was
all like text messaging. We were probably one of the first like customers of Tulio. And
we built these sort of fairly simple, you could call them maybe AI, but like bots that
would allow you to, you know, place somebody at a job, you could broadcast out a job to
a bunch of different people that had skill matches and so forth. And you could coordinate
everything over cell phones. Because back then, like, people didn't a lot of especially
in Blue Collar, they didn't have the latest iPhone because they were too expensive, but
they all had future phones, you could do stuff over text. Eventually as you know, Android
and iPhone became more common than and we went into more of the restaurant industry,
like all those people in their early 20s in places like San Francisco and New York,
they're all like getting jobs on their phones. They're just doing it in super convoluted
ways. So we were really the first, we were the first company to ever build a full end
to end hiring experience, both from a candidate and hiring standpoint on a mobile device.
And then we got featured by Apple and Google at the time and grew a lot in terms of our
mobile application. Yeah. Wow. That's really cool. I'm really, I'm actually pretty sad
that that didn't come to fruition further. And I think that, you know, and maybe it
did, but it's sort of things evolved, right? Yeah. I mean, we didn't, I mean, I think
we created a lot of innovative technology at that time. And I think that was like where
our strength was in retrospect, you know, looking at things in hindsight, we should have
probably leaned more into our, our strength of like being a technology innovator in the
sort of job space and became maybe more of a tools company of like selling that software
as like a SaaS offering or even like a, you know, on-prem installation or something like
that to existing staffing and hiring companies, because we kind of sucked at that business,
to be honest. Like we were very good at like taking this problem space and applying technology
to it in a way that no one had ever done it before. But we were the business, some of
the business side of just like staffing. We just didn't have the domain expertise and
we didn't have the resources to always hire those people. So that was really like a gap
in the company.
That's interesting. I actually came from hospitality management before I got into tech and was
actually in restaurant management. So I know very, very, very closely the exact audience
and type of roles and sort of humans playing those roles that you're talking about. And
you know, who knows exactly, I don't know where the timing aligns, but may have been
one of those potential users. If that aligns, I don't think it did. But either way, I think
that's really interesting because it is sort of a difficult space and it was and it was
funny because you said Craigslist and I remember like when I first taught myself how to code
and I got out of hospitality management, that's where I found all my freelance clients was
on Craigslist because like it was great. Craigslist is not what it used to be today.
Yeah. I mean, it's still like has huge, I mean, it's been a while since I've been, you
know, on Craigslist. There was a time where I probably knew more about Craigslist than
any human alive besides maybe Craig, Craig, but like we, once you get the thing about
like marketplaces is once you have network effects is really, really difficult to just
place something as network effects. So the entire valley is like littered with the bodies
of companies that have attempted to take on Craigslist, especially in their core places
where they make money like rentals and as well as jobs because jobs is really where
they make the majority of their money. And a lot of people don't even know that they
charge for jobs, but they do. And back when we were doing it, the most expensive place
in US was the Bay Area where it was like $75 supposed job. But if you compare that to almost
any other sort of equivalent job board, that was a fraction of the cost. You know, it's
like, you know, this kind of disaster experience for people. It's like, I know I can put my
money in and I'm going to get like a hundred applications for, you know, my host's disposition
or my host's position. And for people who are working where they have roles that are
over 100% turnover rate, and you're paying, you know, minimum wage, you just can't afford
to pay $500 to place that person or pay a like a, you know, recruiter to go and source
this person. It's just not a reasonable thing to do. So it's very, very, it's all about
like cost efficiencies, essentially. And most of these people are non professional
hires. So they're kind of okay using something like email to manage that process.
Yep. Yep. I agree. All right. So Jay has a question that he asked in the chat. And I
think sort of as we get into the interview, which we've already, you know, been able to
chat about a number of things, but addressing Jay's question, with your broad experience
in technology, do you believe that IT services are ending as some warned that AI is taking
over? We chatted about this pre pre show. So I'm excited.
This of course is like a huge topic or conversation of like, is AI taking your jobs? And actually
I remember about a year and a half ago, I had traveled to visit my parents in rural Canada,
my dad picked me up in like Maine, where I was flying into and the first thing he asked
me is like, is AI going to take people's jobs? And I was like, wow, if this is on sort of
the topic of conversation amongst the retirement community of people in their mid 70s in rural
Canada, this is really like a hot topic of conversation right now.
But I mean, so a couple of things. One thing is that I think if you look at the history
of technology, even going back to things like printing press, like every big shift that's
happened in technology, people got scared of the idea of losing jobs. Yeah, you look
at the trends, every new technology shift has actually led to many, many more jobs than
previously. And there's it's hard to point to a situation where a device or some sort
of technology innovation actually led to less jobs, or even the full elimination of a tier
of job. But that doesn't mean that there isn't some sort of collateral damage that can happen
during those swings where there can be jobs that become sort of less relevant or they
require less people than previously. And there's suddenly like a new branch of jobs that you
have to skill up for. So there can be certainly shifts that happen where people unfortunately
get do lose their jobs or what they do today. And they might have to figure out how to like
reskill before you get sort of the next generation of job seekers that maybe are no longer training
as a, I don't know, a blacksmith and a cobbler, but are you know, going and training is something
else. So I do think that can happen. Now, in terms of like, today is AI taking on it.
I don't believe that for the most part, any most AI technologies in the place where it
could really replace somebody today, you know, especially on sort of engineering, IT side,
there's things where I think you can do a lot more with a single individual than maybe
you could previously. If you look at things like coding assistant tools, like there's
plenty of statistics to show that people are significantly more productive, productive using
some of those tools, they're closing out more bugs, they're generating more PRs, all those
types of things. And you can take somebody who's maybe a little bit more junior and upskill
them a little bit faster using some of those. But there is a ceiling to it. Essentially,
at some point, you need to like have those skills. But even if you are able to do more,
like let's say one person becomes suddenly five X that person, I think all you end up
doing is you end up creating five X more companies, because that suddenly you can run a lot more
efficiently. And the cost of essentially starting a business is lower, because I know I can
do it for less cost, then I'm going to you're going to end up with more people essentially
innovating and having it and becoming entrepreneurs. So you see the same thing that has happened
like the with public cloud, that led to a huge birth of new companies, because suddenly
I don't need to spend two years investment in like real infrastructure, racking and stacking
servers. I can just literally click a button and have an EC2 instance running on AWS and
can get up and running. And now there's even with iPass and stuff like that, like really
like low, basically just commit something to GitHub and suddenly I have an amazing, you
know, scalable web at front end. So for the most part, my perspective on this is that
I think the idea that AI is taking over and then replace people's jobs is sort of premature
thinking. Like I don't think we're at that stage. And I think that for the most part,
it's going to actually generate a lot more jobs than that in reality in the long run.
Yeah, I there are so many things that you said that I think just kind of pull on a little
bit. And I think you're definitely right about like more businesses being able to be created
and sort of more efficiency for anyone who's might be listening. If you are curious and
for Jay who's in the chat, there's actually a recording on YouTube that we did on Monday.
We didn't get to dig into as much of like how exactly folks are utilizing AI, but we had
a really good conversation about is AI going to take jobs and a lot of bits and pieces
that came out of that was really like it's just it's making all of us better. And in
my business, like there's a lot of things that I've been able to do and start to optimize
and start to streamline that I never could have done before with some of the tools that
now exist like Claude, right? I've got certain prompts or chat GPT has gotten better lately
that all prompt against it. And it's things that I would have needed an assistant for
or things that I would have needed to bring someone in. And so I do agree that I think
it's a beautiful supplement. I think one of the biggest comments that came out of that
panel is someone said that he's like, I don't have to do this stuff. I don't want to do
anymore. And I think that's the beautiful part of sort of the IT software engineering,
some of that it's like we can use these great skills that we have that we've learned throughout
the years, right? To actually start to improve our day to day and offload the things we don't
want to do and actually use sort of that human that problem solving brain that that we all
have to actually do the things that humans need to be doing.
Yeah. And I want to address a follow up to from the person that asked that question and
where they said, you know, even basic apps can be developed by AI. So if you think about
like some of the, like, I don't know, like business or consumer facing applications that
exists that are some of the most high value apps in the world, like, I think, like you
could go, let's say you even without AI, you had a team of engineers and you went and clone
that application. I think the idea that simply creating a copy of that application suddenly
gives you the same value as existing application is sort of a misinterpretation of where the
value of that is. So like things like Atlassian, Salesforce, Twitter, like you could essentially
say that all those companies are the front end of a database. They have a database and
they're just re-skinning it in the front end of an out of database. So would it be that
hard to like create a similar experience? Like I can, you know, go and create a version of
Twitter, like especially the first version of Twitter was very, very simple. It's like
you text something and it shows up online. Like that's not that hard an application.
Anybody could build that, you know. And but the value of those businesses has very little
in some ways to do with the actual front end consumer application experience. It's something
like Twitter, the value of any social network is the essentially the fact that there's people
there. That's like the hard part of themselves. They solve that problem. So I can go and clone
Twitter, but there doesn't make me Twitter. And I could go clone Salesforce as well. And
a ton of people have tried to take on Salesforce as new, better versions of a CRM that will
prettier and all this sort of stuff. But there's very, there's no company that has the sort
of market cap and the penetration of the market of Salesforce. So it has sort of less to do
with being on the copy it versus some of these other things that exist. Like you have to
figure out what is the driving value of that business? And is that something that I can
take on versus the sort of software experience?
Yes, I love that you added that because we spent a good section of the time talking about
that. Because like you said, right, you can go and create that thing, but can you bring
the people to it? Can you build a business around it? Can you drive revenue? Can you,
you know, do the things that are required of an actual business? This like almost gets
into sort of the controversial conversation of like, do we need to start to partner our
engineering degrees with business degrees? Right? Is that the shift that we will maybe
see? And, and I think it's, I think it's going to be interesting.
Yeah, I mean, I think some of the shifts that will happen from an engineering perspective
is that the levels of abstraction will start earlier. So like, if you think about like
going from junior engineer to maybe senior to staff to like architect or, you know, even
CTO, you're sort of each level along the way, you're doing bigger problems. And there's
a jump in sort of the level of the abstraction. And you know, you might spend your first couple
years engineering doing fairly like very specific tasks like go and like add a button
to this form, you know, solve the specific bugs and stuff like that. And I think that
if you start to be able to take some of that work away from using AI or make it, you know,
much, much faster to do as an individual, then you have more time to sort of spend on
these like larger, more complex problems. And that trend has been existing for a very
long time. Like even when we shifted coding from like punch cards to assembly to see there
was people at each generation, like shaking their fists at the next generation about how
you're losing something by having this level of abstraction and that and also that it's
going to degrade the quality of the output. And all it did was essentially create more
opportunity, more jobs and more companies. Right. Yep. Yep. I agree. Okay, so we're getting
towards the end of time. We got to really tap on most of the interview questions I like
to ask just naturally through conversation. Jay, thanks for the great questions. What
do you do and your day to day, maybe you're programming a little bit less, check me on
that might be interesting to hear about that. But when you're stuck or when you're you're
trying to find that sort of next solution, you just feel like you just can't quite grasp
exactly what that looks like. What are usually your next steps? What do you go to? So you're
talking about from like maybe from a programming standpoint, I'm stuck, not sure what to do.
Or even just think like in your role, right? Maybe you're not writing as much code. So
you can kind of check me on that. And maybe you are right. But like, generally, strategically,
how do you get on stock, even in code, how do you get at stock? Just sort of the listeners
are usually developers here and the precedents precedent is like, where can they go to start
to get these resources that they might need? Yeah. So I mean, I deal still code, even when
I was in my position of like sort of, you know, interim CMO, I was also, I would find
any excuse to do a little bit of, you know, psychoting projects from time to time. I think
it's just built into ingrained into me. I've been doing it since I was a kid. And I think
they'll always be doing that in some fashion, even if it's just for fun. But I think from
there's a couple of things that I do when I'm like stuck on a problem. And it kind of depends
on the type of problem maybe I'm stuck on. But you know, sometimes I think, you know,
there's like the whole like rubber duck, you know, I think sometimes just like talking
to somebody about it, like even, you know, my wife is not in technology at all. But even
going kind of like explaining maybe what I'm working on and to her a lot of times that
active explanation will lead to like an insight where you're like, Oh, yeah, of course, like
I made this mistake. And I used to be when I was in college, I did a lot of competitive
programming. That's cool.
Problem solving competitions. And they are like, sometimes if I was stuck on like a really
hard problem, I would go for a walk or, you know, sometimes if I was about to fall asleep
in your sort of in that like partial cycle between actually asleep and awake, I would
sometimes get that aha moment as well, where you're sitting in the lab, working on the
problem. And I found that as well, just like in my career, these kind of larger scale problems.
A lot of times when I allow myself to just kind of think freely, like not under the pressure
of like, you need to come up with a solution right now, but just kind of walk and be thinking
about stuff passively that a lot of times can lead to those aha moments as well.
Yeah, you know, it's really interesting because that ends up being the answer from pretty
much everyone that I speak to really, they've got some other resources they may be throw
out, but it really is like that rubber ducky that re explaining it and just getting away
from the problem and coming back to it. And it's interesting to me, you know, how frequently
this is actually helpful and that someone hasn't actually created some sort of like
developer community at which you just, this is where you go after you can't solve a problem.
You just rubber ducky. But yeah, I think I think it's a it's interesting when you explain
that to somebody, I do the same with my spouse, I will explain something and he doesn't have
any clue what I'm talking about. But all of a sudden I'll be like, yes, never mind, I
get it. He's like, okay, great, I'm glad I can help.
Yeah, I also think sometimes that sort of trying to figure out like a new way to attack
the problem can help as well, because maybe you're just like the thing that you're trying
to do, maybe you you you think it's the best way to do it. And you're sort of like, you
know, hitting a wall with it. It's taking a step back and thinking about from sort of
first principles, like, is there another way I can approach this problem can help a lot
as well. And in that might even lead to that aha moment for the thing that you're working
on, because you're able to make these connections that you weren't able to before. It was very
hard when you're sort of like, so deep in it. And you're just like, oh, why can't I do
this? And it's like, you know, hitting the wall over and over and over again, you need
to kind of figure out like, how do I move around the wall and take a different approach?
I agree, you kind of lose sight of the problem sometimes too, when you're that deep into it
because you're you're frustrated, you're trying to solve it. And it's hard to actually see
the light of what's what's all going on as well. So yeah, I love it. Okay, well, where
can people find you there? Obviously, they're, you know, Jay has already sent you a LinkedIn
request, but where can anyone else who is listening find you?
LinkedIn is probably the best, you know, I'm on, I'm recently joined, you know, Blue Sky
and some of these things, but I'm most active on LinkedIn.
All right, I love that. Well, thank you so much for chatting with us today. Lots of amazing
insights that I learned and the listeners learned. And it was just absolutely lovely
having your time. So I hope you have a fabulous rest of your week.
Great. Well, thanks for having me.
Of course.