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Hello, hello. I am here with Sean, very excited to chat with Sean today on the 99 Dev Problem

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Show. Sean, I'd love for you to introduce yourself.

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Hey, everyone. It's great to see you again. My name is Sean Faulkner, and I am currently

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the AI entrepreneur in residence at a company called Confluent, which is famous for essentially

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the Kafka open source project. Jay Krapse, the founder and the rest of the founders, created

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that project and then spun that off into Confluent, which is now a publicly traded company for

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the last three years and has about 3,500 employees. So, good size company. And I recently joined

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a couple of just a couple of months ago.

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Ooh. Well, I love your title. Say your title again.

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AI entrepreneur in residence.

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I love that. You said it very quickly, which is fine, but I think it's a really interesting

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title. And so I'd love to unpack that a little bit. Like, what do you do over Confluent?

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Yeah, this is a big question, right? I get that pretty much every day, even for people

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inside at Confluent. They're like, what are you doing here? Everybody's excited about

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being here, but what is it that you do? So, I mean, really, it's... So if you think about...

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If you're familiar with the concept of an entrepreneur in residence, usually you see

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those roles within venture capital firms, where they bring in somebody that has certain background

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expertise. Maybe they've been a founder in the past and they're there for a while to

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sort of spend some time. They get some resources in this sort of incubating and trying to figure

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out what is their next business that they want to watch in a particular space. And at

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the same time, they're also serving as a subject matter expert and offering some mentoring to

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existing private portfolio. And in a similar spirit within larger companies, sometimes

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larger companies will also have these EIR roles. But there, it's less about necessarily

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spinning off like a new business that I'm going to be the CEO of and it's going to be

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separate entity from Confluent. But how do you essentially create sort of like an innovation

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arm within a company where they can drive to trying to create like either a new type

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of product or a new business unit centered around like whatever your area expertise is.

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And then for me, in particular with this role of AI entrepreneur residence, I did a master's

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in PhD and postdoc years ago in computer science, my background there was in machine learning

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and also applied machine learning across a bunch of different domains. And so it's kind

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of dipping into my background expertise there. I've worked in industry doing, applying machine

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learning as well. I was an entrepreneur at some point. So it's combining a lot of these

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different skill sets. We're primarily focused on from a technology strategy point, the point

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of view, like how do we drive Confluent as a AI thought leader? How do we align our product

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offering with other parts of the business unit to start to essentially generate revenue

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and solve problems for customers?

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Yeah, I love that. That's really cool. I definitely want to unpack a little bit more

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of that because there's some really awesome stuff I'm sure you're doing over there. You

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alluded to it, but one of the first questions I like to ask is what's your developer education?

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So you did share some of it, but if you want to kind of share all of that, we'd love to

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hear what your formal education is.

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Yeah, sure. So I spent a lot of time in school. But I started sort of engineering, maybe when

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I was like 14 or 15 in high school, when I really fell in love with computers. And I

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was fortunate to go to high school at the time where sort of the home PC era and the

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internet was first sort of being introduced in mass to people. So that really, like, I

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just became obsessed, essentially, like I grew up in a really small rural community

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in Canada. So suddenly to be able to like learn anything that I wanted or talk to people

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all over the world really just was super fascinating to me. And I would get up at like 435 a.m.

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in the morning before school to because back then you had dial up internet and we had free

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you had free internet from like 12 to 8 a.m. So we get up at like 435 a.m. before school

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to get like three hours, three hours of free internet before before school started and

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like work on websites. And I started looking at websites and then that kind of gets you

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into, you know, basics HTML. And then it's like, well, I want to make this website do

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something and then it's like, you know, that's kind of like gateway to like JavaScript or

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something. And then, you know, older back end technologies like Pearl to write scripts.

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And I started learning like, you know, basic and Java and all this sort of stuff. So that

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was sort of the entry point. Then I went on to study computer science for my undergrad,

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focused on theory and computation with a minor mass of very math, math heavy. And then I

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did a master's degree again, like focused in sort of pattern recognition machine learning.

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And then a PhD after that, working on sort of applied machine learning using machine

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learning in combination with human and the loop expertise to solve sort of hard data

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problems. And then move from Canada to the US after that to do a postdoc in bioinformatics.

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And then while I was doing that postdoc, I also started a company, which is what where

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I ended up leaving the world of academics into industry. But the entire time I was in

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school, I also worked on the side as an engineer, software engineer for a variety of companies.

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And part of that was because it was a way for me to pay for my education. But also, I

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was always worried that at some point I might want to go back into industry. And I saw a

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lot of people who focused on more research and academics kind of de skill their ability

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to write code. And I was always worried about that might maybe happening. Like I knew a

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lot of professors, brilliant people that couldn't write, you know, like a basic Hello World

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program, because they just been too far away from it for a long time. So I was always nervous,

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but so I always wanted to keep up my programming skills. So I would have just in case I needed

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it. So I spent probably combined through all my education, like I ended up accumulating

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my probably, you know, six, seven years of actual like engineering work during that time

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as well. Beyond just what I was doing academically. And then I started a company where I was the

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CTO founder of that company ran it for seven years. And then after that, I joined Google

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in engineering. And then when I left Google, I was sort of I was leaving a team and engineering

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and product. And then I joined a company called Skyflow, which is on a sort of data privacy

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space. And that was probably my biggest like departure from sort of day to day engineering

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work. I ended up doing reading the marketing team there. I can go into details of like

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how that happened. I was like, you know, like I kind of accidentally became the CMO company

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that spent three years there. And then now more recently joined Confluent to kind of

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go back onto the technology side of the business.

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Oh my gosh, I love that. Okay, I think we need to hear the story of how you accidentally

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became a CMO. I think I can very much relate to probably how this story goes.

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Well, so I originally joined Skyflow's head of developer relations, do some more stuff

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that I did at Google more focused on like developer experience and, you know, improving

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like our, you know, APIs, SDKs, engineering documentation, so on. And then about partly,

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you know, halfway through my first year, the original CMO, the company didn't work out.

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And there were a lot of challenges with the marketing team that he had built. So the CEO

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came to me and said like, Hey, I want you to like step in and take over marketing on

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an intram basis and figure out, you know, what's going on here and come up with a plan

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to try to fix it. And the reason he had done that is because he had been an investor in

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the company I'd started, you know, years ago, and I did a lot of go to market stuff there

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because as a founder, you just end up being thrust into things that maybe you had absolutely

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no business being thrust into, but there's nobody else to do that. I had tons of engineering

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training and skills. I didn't know anything about like the business side of the business.

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I just had to learn that stuff. So I got sort of like my MBA the hard way. And also like,

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you know, whatever sort of marketing chops I had, I got the hard way as well through

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a lot of experimentation and making mistakes. And so I ended up jumping in on the marketing

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team and, you know, taking the lead there. And, you know, through the first six months,

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I rebuilt most of the team. And we fixed a lot of sort of fundamental problems. And

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a lot of it comes down to, I think, just like having a first principles mindset of like,

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in asking questions, not being afraid of asking like, you know, quote unquote dumb questions,

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right? And I think some advantage of being sort of a non traditional marketer there is

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that I, I have a fresh set of eyes. I'm not coming in with a playbook that I've done 10

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times. I'm just like, does this make sense or not make sense? And we sold to CTOs. So

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I had been a CTO previously. So I could, you know, sort of figure out whether things made

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sense to me, you know, does it pass the smell test? Does this feel authentic? Is the messaging

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like to marketing, all these types of things. So there were some advantages there. And,

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you know, so after six months, you know, look at reflecting on where we come, we'd like

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to buy that star pipeline, we cut costs by 50%. And we were operating, you know, significantly

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more efficiently. And I became, I guess, like someone a victim of my, you know, our own

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success with that, where something that originally was more of an interim role became more of

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a permanent role. But I was always clear to the company that my, I had no desire to be

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like a career CMO. I like solving problems, but I felt like, you know, we had kind of

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solved one of the fundamental problems. I continued to, you know, operate that capacity

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for another year or so before I made the transition to going back into more of a technology leadership

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role.

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Oh my gosh, I love everything that you just shared because it's like everything that I

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do in my day to day business today is like talking with technical founders and they're

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like, I'm doing things I should not be doing. And it's usually marketing, right? And, and

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I think something that you shed light on there too is like reducing costs, right? I think

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that a lot of the marketing, traditional marketing playbooks have a huge investment in sort of

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ad spend and these other types of big convoluted expensive things that don't necessarily drive

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the results that, you know, companies actually need. So that I think it's really cool and

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lucky for them that you fell into that role because it sounds like you really, you know,

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created something absolutely beautiful over there in the marketing department.

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Well, I've been, because when I had to do marketing at my company, like we were never

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very well resourced and by the time I was really driving into a market, we were like

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really under resourced. So we were like, you know, crawling on our bellies to the dirt

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for years, trying to do everything on like a shoestring budget. So we had to really figure

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out and be scrappy on, you know, what our investments were and always be asking ourselves,

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like, does, is this the best way we can spend this money? You know, if it's $10,000, what

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are the other ways we could spend $10,000? Do we think that that might deliver a higher

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ROI or not? You have to be always sort of asking yourself these things. And the good

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thing about sort of being starved for resources is it does create sort of this discipline

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around, you know, does a dollar out equal, you know, a dollar in or more, right? And

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you have to really be evaluating things like that. And I think one of the challenges that

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companies sometimes go through is when learning these high growth phases where the market's

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really good, getting money is really easy or relatively easy, then sort of the growth

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at all costs and you lose sight of, hey, like, of that discipline of, does this make sense?

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Is this just a, you know, is this smart growth or is this, you know, like inefficient growth,

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essentially, and you get basically build up habits as a business of spending money rather

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than, you know, essentially like making money?

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Yes, yes, I agree. We just had a good little, I'm just reading, we had a question come in,

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but I agree with that, honestly. And I think a lot of, a lot of founders are feeling that,

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especially right now, because the VC space is very different right now. If you're going

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after AI, here you go, here's your check. But if that's not a $100 billion C-dram,

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exactly. If you're not in that space, though, it's like, where's your revenue, right? They

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want to see revenue these days. And it's really difficult to do that, especially in that earlier

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stage. I'm really curious if you're open to it, what business did you have? Like, if

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you're willing to share, what did, what did you build?

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So we were always interested in buildings for technology for like an underserved part

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of the job market. Originally, like if you think about people who are like college-educated,

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work and technology, we have a ton of tools built for us, whether you're on the hiring

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side or you're on the side of a candidate, you know, you've linked in, you know, tons

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of applicant tracking systems, there's a multi-billion dollar industry built around this. But your

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work is like a tradesperson, where you work in restaurants, you know, whatever it is,

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there's a lot less technology built for you, both on the hiring side and also on the, you

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know, jobseeker side. But really back when we were doing it, like on the jobseeker side,

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your best option was Craigslist. Or if you worked in Blue Collar, there's staffing agencies

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that you could work with that would, you know, temporarily place you different places. So

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originally we were focused on Blue Collar, temple labor, and that's what we originally

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raised while I was still doing my postdoc. We raised close to $2 million to start that

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business. And that's why I left academics to do that full time. And then we kind of

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activated a number of times. There's kind of a long story of all the things that we

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screwed up along the way. And, but eventually we settled on sort of this two sided marketplace

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focused primarily on high turnover positions, like restaurants, hospitality and so forth.

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And we were really early investors in mobile. And the original versions of the product was

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all like text messaging. We were probably one of the first like customers of Tulio. And

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we built these sort of fairly simple, you could call them maybe AI, but like bots that

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would allow you to, you know, place somebody at a job, you could broadcast out a job to

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a bunch of different people that had skill matches and so forth. And you could coordinate

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everything over cell phones. Because back then, like, people didn't a lot of especially

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in Blue Collar, they didn't have the latest iPhone because they were too expensive, but

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they all had future phones, you could do stuff over text. Eventually as you know, Android

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and iPhone became more common than and we went into more of the restaurant industry,

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like all those people in their early 20s in places like San Francisco and New York,

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they're all like getting jobs on their phones. They're just doing it in super convoluted

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ways. So we were really the first, we were the first company to ever build a full end

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to end hiring experience, both from a candidate and hiring standpoint on a mobile device.

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And then we got featured by Apple and Google at the time and grew a lot in terms of our

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mobile application. Yeah. Wow. That's really cool. I'm really, I'm actually pretty sad

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that that didn't come to fruition further. And I think that, you know, and maybe it

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did, but it's sort of things evolved, right? Yeah. I mean, we didn't, I mean, I think

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we created a lot of innovative technology at that time. And I think that was like where

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our strength was in retrospect, you know, looking at things in hindsight, we should have

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probably leaned more into our, our strength of like being a technology innovator in the

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sort of job space and became maybe more of a tools company of like selling that software

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as like a SaaS offering or even like a, you know, on-prem installation or something like

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that to existing staffing and hiring companies, because we kind of sucked at that business,

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to be honest. Like we were very good at like taking this problem space and applying technology

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to it in a way that no one had ever done it before. But we were the business, some of

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the business side of just like staffing. We just didn't have the domain expertise and

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we didn't have the resources to always hire those people. So that was really like a gap

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in the company.

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That's interesting. I actually came from hospitality management before I got into tech and was

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actually in restaurant management. So I know very, very, very closely the exact audience

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and type of roles and sort of humans playing those roles that you're talking about. And

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you know, who knows exactly, I don't know where the timing aligns, but may have been

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one of those potential users. If that aligns, I don't think it did. But either way, I think

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that's really interesting because it is sort of a difficult space and it was and it was

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funny because you said Craigslist and I remember like when I first taught myself how to code

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and I got out of hospitality management, that's where I found all my freelance clients was

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on Craigslist because like it was great. Craigslist is not what it used to be today.

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Yeah. I mean, it's still like has huge, I mean, it's been a while since I've been, you

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know, on Craigslist. There was a time where I probably knew more about Craigslist than

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any human alive besides maybe Craig, Craig, but like we, once you get the thing about

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like marketplaces is once you have network effects is really, really difficult to just

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place something as network effects. So the entire valley is like littered with the bodies

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of companies that have attempted to take on Craigslist, especially in their core places

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where they make money like rentals and as well as jobs because jobs is really where

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they make the majority of their money. And a lot of people don't even know that they

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charge for jobs, but they do. And back when we were doing it, the most expensive place

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in US was the Bay Area where it was like $75 supposed job. But if you compare that to almost

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any other sort of equivalent job board, that was a fraction of the cost. You know, it's

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like, you know, this kind of disaster experience for people. It's like, I know I can put my

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money in and I'm going to get like a hundred applications for, you know, my host's disposition

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or my host's position. And for people who are working where they have roles that are

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over 100% turnover rate, and you're paying, you know, minimum wage, you just can't afford

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to pay $500 to place that person or pay a like a, you know, recruiter to go and source

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this person. It's just not a reasonable thing to do. So it's very, very, it's all about

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like cost efficiencies, essentially. And most of these people are non professional

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hires. So they're kind of okay using something like email to manage that process.

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Yep. Yep. I agree. All right. So Jay has a question that he asked in the chat. And I

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think sort of as we get into the interview, which we've already, you know, been able to

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chat about a number of things, but addressing Jay's question, with your broad experience

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in technology, do you believe that IT services are ending as some warned that AI is taking

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over? We chatted about this pre pre show. So I'm excited.

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This of course is like a huge topic or conversation of like, is AI taking your jobs? And actually

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I remember about a year and a half ago, I had traveled to visit my parents in rural Canada,

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my dad picked me up in like Maine, where I was flying into and the first thing he asked

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me is like, is AI going to take people's jobs? And I was like, wow, if this is on sort of

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the topic of conversation amongst the retirement community of people in their mid 70s in rural

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Canada, this is really like a hot topic of conversation right now.

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But I mean, so a couple of things. One thing is that I think if you look at the history

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of technology, even going back to things like printing press, like every big shift that's

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happened in technology, people got scared of the idea of losing jobs. Yeah, you look

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at the trends, every new technology shift has actually led to many, many more jobs than

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previously. And there's it's hard to point to a situation where a device or some sort

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of technology innovation actually led to less jobs, or even the full elimination of a tier

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of job. But that doesn't mean that there isn't some sort of collateral damage that can happen

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during those swings where there can be jobs that become sort of less relevant or they

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require less people than previously. And there's suddenly like a new branch of jobs that you

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have to skill up for. So there can be certainly shifts that happen where people unfortunately

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get do lose their jobs or what they do today. And they might have to figure out how to like

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reskill before you get sort of the next generation of job seekers that maybe are no longer training

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as a, I don't know, a blacksmith and a cobbler, but are you know, going and training is something

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else. So I do think that can happen. Now, in terms of like, today is AI taking on it.

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I don't believe that for the most part, any most AI technologies in the place where it

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could really replace somebody today, you know, especially on sort of engineering, IT side,

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there's things where I think you can do a lot more with a single individual than maybe

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you could previously. If you look at things like coding assistant tools, like there's

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plenty of statistics to show that people are significantly more productive, productive using

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some of those tools, they're closing out more bugs, they're generating more PRs, all those

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types of things. And you can take somebody who's maybe a little bit more junior and upskill

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them a little bit faster using some of those. But there is a ceiling to it. Essentially,

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at some point, you need to like have those skills. But even if you are able to do more,

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like let's say one person becomes suddenly five X that person, I think all you end up

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doing is you end up creating five X more companies, because that suddenly you can run a lot more

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efficiently. And the cost of essentially starting a business is lower, because I know I can

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do it for less cost, then I'm going to you're going to end up with more people essentially

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innovating and having it and becoming entrepreneurs. So you see the same thing that has happened

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like the with public cloud, that led to a huge birth of new companies, because suddenly

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I don't need to spend two years investment in like real infrastructure, racking and stacking

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servers. I can just literally click a button and have an EC2 instance running on AWS and

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can get up and running. And now there's even with iPass and stuff like that, like really

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like low, basically just commit something to GitHub and suddenly I have an amazing, you

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know, scalable web at front end. So for the most part, my perspective on this is that

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I think the idea that AI is taking over and then replace people's jobs is sort of premature

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thinking. Like I don't think we're at that stage. And I think that for the most part,

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it's going to actually generate a lot more jobs than that in reality in the long run.

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Yeah, I there are so many things that you said that I think just kind of pull on a little

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bit. And I think you're definitely right about like more businesses being able to be created

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and sort of more efficiency for anyone who's might be listening. If you are curious and

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for Jay who's in the chat, there's actually a recording on YouTube that we did on Monday.

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We didn't get to dig into as much of like how exactly folks are utilizing AI, but we had

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a really good conversation about is AI going to take jobs and a lot of bits and pieces

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that came out of that was really like it's just it's making all of us better. And in

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my business, like there's a lot of things that I've been able to do and start to optimize

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and start to streamline that I never could have done before with some of the tools that

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now exist like Claude, right? I've got certain prompts or chat GPT has gotten better lately

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that all prompt against it. And it's things that I would have needed an assistant for

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or things that I would have needed to bring someone in. And so I do agree that I think

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it's a beautiful supplement. I think one of the biggest comments that came out of that

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panel is someone said that he's like, I don't have to do this stuff. I don't want to do

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anymore. And I think that's the beautiful part of sort of the IT software engineering,

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some of that it's like we can use these great skills that we have that we've learned throughout

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the years, right? To actually start to improve our day to day and offload the things we don't

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want to do and actually use sort of that human that problem solving brain that that we all

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have to actually do the things that humans need to be doing.

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Yeah. And I want to address a follow up to from the person that asked that question and

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where they said, you know, even basic apps can be developed by AI. So if you think about

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like some of the, like, I don't know, like business or consumer facing applications that

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exists that are some of the most high value apps in the world, like, I think, like you

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could go, let's say you even without AI, you had a team of engineers and you went and clone

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that application. I think the idea that simply creating a copy of that application suddenly

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gives you the same value as existing application is sort of a misinterpretation of where the

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value of that is. So like things like Atlassian, Salesforce, Twitter, like you could essentially

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say that all those companies are the front end of a database. They have a database and

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they're just re-skinning it in the front end of an out of database. So would it be that

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hard to like create a similar experience? Like I can, you know, go and create a version of

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Twitter, like especially the first version of Twitter was very, very simple. It's like

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you text something and it shows up online. Like that's not that hard an application.

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Anybody could build that, you know. And but the value of those businesses has very little

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in some ways to do with the actual front end consumer application experience. It's something

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like Twitter, the value of any social network is the essentially the fact that there's people

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there. That's like the hard part of themselves. They solve that problem. So I can go and clone

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Twitter, but there doesn't make me Twitter. And I could go clone Salesforce as well. And

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a ton of people have tried to take on Salesforce as new, better versions of a CRM that will

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prettier and all this sort of stuff. But there's very, there's no company that has the sort

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of market cap and the penetration of the market of Salesforce. So it has sort of less to do

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with being on the copy it versus some of these other things that exist. Like you have to

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figure out what is the driving value of that business? And is that something that I can

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take on versus the sort of software experience?

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Yes, I love that you added that because we spent a good section of the time talking about

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that. Because like you said, right, you can go and create that thing, but can you bring

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the people to it? Can you build a business around it? Can you drive revenue? Can you,

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you know, do the things that are required of an actual business? This like almost gets

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into sort of the controversial conversation of like, do we need to start to partner our

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engineering degrees with business degrees? Right? Is that the shift that we will maybe

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see? And, and I think it's, I think it's going to be interesting.

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Yeah, I mean, I think some of the shifts that will happen from an engineering perspective

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is that the levels of abstraction will start earlier. So like, if you think about like

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going from junior engineer to maybe senior to staff to like architect or, you know, even

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CTO, you're sort of each level along the way, you're doing bigger problems. And there's

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a jump in sort of the level of the abstraction. And you know, you might spend your first couple

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years engineering doing fairly like very specific tasks like go and like add a button

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to this form, you know, solve the specific bugs and stuff like that. And I think that

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if you start to be able to take some of that work away from using AI or make it, you know,

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much, much faster to do as an individual, then you have more time to sort of spend on

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these like larger, more complex problems. And that trend has been existing for a very

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long time. Like even when we shifted coding from like punch cards to assembly to see there

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was people at each generation, like shaking their fists at the next generation about how

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you're losing something by having this level of abstraction and that and also that it's

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going to degrade the quality of the output. And all it did was essentially create more

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opportunity, more jobs and more companies. Right. Yep. Yep. I agree. Okay, so we're getting

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towards the end of time. We got to really tap on most of the interview questions I like

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to ask just naturally through conversation. Jay, thanks for the great questions. What

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do you do and your day to day, maybe you're programming a little bit less, check me on

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that might be interesting to hear about that. But when you're stuck or when you're you're

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trying to find that sort of next solution, you just feel like you just can't quite grasp

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exactly what that looks like. What are usually your next steps? What do you go to? So you're

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talking about from like maybe from a programming standpoint, I'm stuck, not sure what to do.

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Or even just think like in your role, right? Maybe you're not writing as much code. So

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you can kind of check me on that. And maybe you are right. But like, generally, strategically,

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how do you get on stock, even in code, how do you get at stock? Just sort of the listeners

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are usually developers here and the precedents precedent is like, where can they go to start

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to get these resources that they might need? Yeah. So I mean, I deal still code, even when

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I was in my position of like sort of, you know, interim CMO, I was also, I would find

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any excuse to do a little bit of, you know, psychoting projects from time to time. I think

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it's just built into ingrained into me. I've been doing it since I was a kid. And I think

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they'll always be doing that in some fashion, even if it's just for fun. But I think from

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there's a couple of things that I do when I'm like stuck on a problem. And it kind of depends

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on the type of problem maybe I'm stuck on. But you know, sometimes I think, you know,

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there's like the whole like rubber duck, you know, I think sometimes just like talking

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to somebody about it, like even, you know, my wife is not in technology at all. But even

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going kind of like explaining maybe what I'm working on and to her a lot of times that

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active explanation will lead to like an insight where you're like, Oh, yeah, of course, like

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I made this mistake. And I used to be when I was in college, I did a lot of competitive

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programming. That's cool.

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Problem solving competitions. And they are like, sometimes if I was stuck on like a really

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hard problem, I would go for a walk or, you know, sometimes if I was about to fall asleep

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in your sort of in that like partial cycle between actually asleep and awake, I would

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sometimes get that aha moment as well, where you're sitting in the lab, working on the

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problem. And I found that as well, just like in my career, these kind of larger scale problems.

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A lot of times when I allow myself to just kind of think freely, like not under the pressure

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of like, you need to come up with a solution right now, but just kind of walk and be thinking

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about stuff passively that a lot of times can lead to those aha moments as well.

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Yeah, you know, it's really interesting because that ends up being the answer from pretty

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much everyone that I speak to really, they've got some other resources they may be throw

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out, but it really is like that rubber ducky that re explaining it and just getting away

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from the problem and coming back to it. And it's interesting to me, you know, how frequently

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this is actually helpful and that someone hasn't actually created some sort of like

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developer community at which you just, this is where you go after you can't solve a problem.

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You just rubber ducky. But yeah, I think I think it's a it's interesting when you explain

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that to somebody, I do the same with my spouse, I will explain something and he doesn't have

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any clue what I'm talking about. But all of a sudden I'll be like, yes, never mind, I

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get it. He's like, okay, great, I'm glad I can help.

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Yeah, I also think sometimes that sort of trying to figure out like a new way to attack

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the problem can help as well, because maybe you're just like the thing that you're trying

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to do, maybe you you you think it's the best way to do it. And you're sort of like, you

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know, hitting a wall with it. It's taking a step back and thinking about from sort of

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first principles, like, is there another way I can approach this problem can help a lot

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as well. And in that might even lead to that aha moment for the thing that you're working

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on, because you're able to make these connections that you weren't able to before. It was very

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hard when you're sort of like, so deep in it. And you're just like, oh, why can't I do

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this? And it's like, you know, hitting the wall over and over and over again, you need

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to kind of figure out like, how do I move around the wall and take a different approach?

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I agree, you kind of lose sight of the problem sometimes too, when you're that deep into it

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because you're you're frustrated, you're trying to solve it. And it's hard to actually see

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the light of what's what's all going on as well. So yeah, I love it. Okay, well, where

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can people find you there? Obviously, they're, you know, Jay has already sent you a LinkedIn

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request, but where can anyone else who is listening find you?

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00:32:20,280 --> 00:32:25,000
LinkedIn is probably the best, you know, I'm on, I'm recently joined, you know, Blue Sky

397
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and some of these things, but I'm most active on LinkedIn.

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All right, I love that. Well, thank you so much for chatting with us today. Lots of amazing

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insights that I learned and the listeners learned. And it was just absolutely lovely

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having your time. So I hope you have a fabulous rest of your week.

401
00:32:40,120 --> 00:32:42,080
Great. Well, thanks for having me.

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Of course.