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[AI Series] Driving Business Success Through Digital Transformation With Eric Bourget

Eric Bourget

Eric Bourget is the Founder and CEO of HalfSerious, a renowned product innovation studio known for its exceptional creativity and unrivaled technological expertise. The company specializes in designing and creating bespoke software solutions that enable businesses to achieve their growth. 

With a strong background in the video game industry, Eric brings a unique blend of creativity and technical insights to his work at HalfSerious. He is a highly sought-after speaker who addresses topics such as the role of design in business, nurturing passion in the workplace,, and the impact of AI on business operations.

Here’s a glimpse of what you’ll learn:

  • Eric Bourget explains how HalfSerious helps people 

  • How HalfSerious keeps its employees focused and engaged 

  • Getting businesses to adopt new technology

  • Insights on the use of AI in businesses 

  • Eric’s leadership style 

In this episode…

The business space is rapidly evolving in the digital age and companies that fail to keep up risk falling behind their competitors. Digital transformation has crucial for long-term success, helping companies achieve greater growth and streamline their operations. By embracing transformation, businesses can potentially improve their agility, efficiency, and customer experience.

While technology can be complex, tech expert Eric Bourget suggests that the user experience should be intuitive and user-friendly.. As a tech developer company, involving clients in the development process is crucial. You can gain valuable insights that help you create customized solutions to address their unique challenges and opportunities. By tailoring the technology to each business’ specific requirements, you can ensure that it delivers the maximum value for all involved.

In this episode of The Customer Wins, Richard Walker sits down with Eric Bourget, Founder and CEO of HalfSerious, to discuss digital transformation for businesses. Eric explains how HalfSerious helps people, how to get companies to adopt new tech, and shares his insights on using AI in businesses.

Resources mentioned in this episode:

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Episode Transcript:

Intro 0:02 

Welcome to The Customer Wins podcast where business leaders discuss their secrets and techniques for helping their customers succeed and in turn grow their business.

Richard Walker 0:16 

Hi, I'm Rich Walker, the host of The Customer Wins, where I talk to business leaders about how they help their customers win, and how their focus on customer experience leads to growth. I want to dedicate this episode to Ashtan Moore a previous guest of mine. He is always kind, generous and creates exceptional opportunities to meet new people. We've had some past guests on our show, including Mike Jalonen of Habit Driven and Parham Nasseri of InvestorCOM, and today is a special episode of my series on AI and today's guest is Eric Bourget, founder and CEO of HalfSerious. Today's episode is brought to you by Quik! the leader in enterprise forums processing. When your business relies upon processing forms, don't waste your team's valuable time reviewing the forms, instead get Quik! using our Form Xtract API. simply submit your completed forms and get back clean, context-rich data that is 99.9% accurate. Visit to get started. All right, I'm excited to introduce Eric Bourget, he's the founder and CEO of HalfSerious a technical and creative agency that specializes in digital transformations for midsize companies. His firm focuses on helping businesses with 200 to 2000 employees navigate the complex landscape of digital evolution. With a background in the video game industry, Eric brings a unique blend of creativity and technical insight to his work at HalfSerious. At HalfSerious, Eric leads a team that excels and merging technical know-how with creative strategies to engage and inspire their clients and their teams. He often speaks on topics such as the role of design and business, fostering passion in the workplace leading transformative change and the impact of AI, as well as the power of creativity and problem solving. Eric, welcome to The Customer Wins.

Eric Bourget 2:00 

Hey, Rich, nice to be here. Thank you so much.

Richard Walker 2:03 

Well, I'm excited to talk to you. And for those who haven't heard this podcast before, I love to talk to business leaders about what they're doing to help their customers win, how they build and deliver great customer experience. And the challenge is to grow their own company. So Eric, let's understand your business a little better. What does your company help people do?

Eric Bourget 2:19 

All right, so really simply HalfSerious. And I usually have to explain the name a little bit. So HalfSerious comes from my background in video games, I wanted to have something that was going to be focused on technology, but with a really strong desire to get people to adopt it and to enjoy using technology. So it's always been part of the DNA today what HalfSerious does is we help like you said midsize companies move to a more digital way of serving their customers or operating. And I think the most interesting way of describing the company is to say that we're a hybrid between a technology firm, and a communications agency. Because as we develop their skills and went through Project and Project, we figured out that developing the right technology, we're great at that we've never dropped the ball on that. The problem a lot of times is just getting people to adopt it, whether that's customers, any stakeholders or really employees? Like how do you evolve the digital landscape with a client in a way that just makes all the employees feel like they've been involved in this and proactively turned potential detractors into promoters of this change.

Richard Walker 3:30 

So I'm gonna go back to your name HalfSerious, because I do actually love this company name. And it's always made me think of improv comedy. And before we started this conversation, you were telling me that you are giving out weekly messages to your team, and you're working hard to make them fun and engaging? How do you do it?

Eric Bourget 3:46 

So first of all, create a space like this room here is made for that. And so one of the first things that I did is removes all the friction for myself, right? We used to be in a situation where, when I wanted to do this, I needed to set up my stand, and then lights and stuff like that. And now that there's a dedicated room, and I could just show up, and I have someone that handles shooting it, and then packaging it, and then sending it by removing all friction. I just made sure that I'm going to do it every single time. And then, at first I was thinking, these are going to be two minute clips, I'm going to get right down to the information that I'm trying to or the message I'm trying to send employees. And by trying different things, I figured out that this was really like a mini podcast, we have about, say 60, 65 employees with a hybrid model. A lot of people never come into the office. So how do you create this sort of sense of a shared experience in this company when people don't necessarily meet each other in the hall. So I'm going to talk about things happening in different projects and where we're going about it, but I make it very down to earth. And I try to make it funny with jokes. We do dead jokes sometimes. It's like, I was uneasy about that at first because I'm like I'm taking 20 minutes out of your day. Shouldn't I be more focused on the information, but really the data and the feedback just says, it's a mini podcast that comes out every Friday at nine o'clock. It's on Loom, we push it on Slack, everyone watches it, and then comments below it. And it's like, it's an internal podcast, basically.

Richard Walker 3:46 

No, that's awesome. I don't know, a lot of technologists who are thinking this way, which is why I wanted to bring it up. Because if your company is, oh, we build tech. And there's lots of companies that build tech. But your focus is on how to make the tech make sense to somebody, and how do you get adoption? And how do you communicate that and I think this example of what you're doing with your own team is a good way to look at it. So what are you thinking about doing with your customers to help them get the adoption with their products that you're working with them on?

Eric Bourget 5:44 

Right, so one of the things that we really invested in was a strong UX research team. So the first things we're going to do is we're gonna go out in the field, we have a mining company, and when we put the team on planes, and we went to the mining site, and stuff like that, and you get to talk to a lot of people and what most companies are going to do when you're designing custom software is you're going to use this sort of empathy driven methodology called design thinking, I don't want to get caught up in terms, but it's like an empathy driven way of figuring out where the opportunities and the challenges and the pains are. In a classic way, what you would do is you would take this information, and you would leverage it to design the best solution possible. But there's really two ways to use this empathy base data is one of them, obviously, to develop the best platform possible, the best solution possible. The other is to develop the best communications plan possible. So think of this, you're working, you're working as a truck driver in a mine, you get this guy from the big city that comes in, and he asks you a bunch of questions about what you're working on, and blah, blah, blah, and then he disappears. And a year and a half later, there's a new platform that comes out. And you're being told that that's what you're going to, like, how much are you going to watch? Or how much are you going to feel that you've been part of this? Not very much. So our approach to this is to say, as soon as we have a single conversation with someone, they're part of our audience that we're catering to. And so we're gonna make sure that month after month, they're getting updates on what's going on, so that they feel like this conversation was actually them coming into this tribe, that's the digital transformation tribe. And now they're part of this movement. And so our hope is that if we do it, well, most of the people that we've touched, that we've created a relationship with, when we roll things out, they're going to be our allies. And if we don't do anything, they're not going to be passive, they're most likely going to be actively resisting the change, right? Unless you turn them into promoters, they will probably be detractors. And I think that that's the most interesting part of the approach is to say, look, digital transformation is about business transformation. And business transformation is about people and getting everyone aligned on what we're trying to do, and getting them, making them feel like they haven't been left at the station, when the train took off. Everyone's on that train. We're all part of this together. And it's easy to say, but how do you operationalize this thing so that people actually, we're managing how people are feeling about what's going on.

Richard Walker 8:21 

We had a customer, a very, very long standing customer of ours, spent 18 months implementing our product in a brand new way. And they said, we're really excited, we're going into user acceptance testing, and they got into that testing. And within two weeks, they shut down the project, months of work down the drain, because, like, we can't use this, it completely violates our policies, our compliance rules, etc. And so that need to involve people and engage them throughout the process of building the tech, man, you're onto it. That is so important.

Eric Bourget 8:53 

And it came from failures, as with most learnings, and I think one of the cases that I could actually talk about was we created a platform for recruiters in the retail space. And the problem that they had is that you're receiving a bunch of resumes of 16 year olds, that addicts just went into word and put in, they don't have any experience. And so you're creating all this pipeline, this talent pipeline that was made for something else, and you're trying to force fit it into this thing called retail and restoration. So we created this new platform, where these people with an app that could put in what we called powers and passion, it was a little gamified. But you create a profile. And then we have a profile for the job opportunities. And we have a software that matches these things. And then we give to the recruiter, a sorted list of candidates. And so we're like, this is obviously a better solution compared to receiving a bunch of crappy PDFs, that VP of HR, super excited signs of check. We roll it out, and in the end it completely fail because we never involve the recruiter and to the recruiter, they actually don't talk to most of those people. They're not managing candidates, they're managing PDFs resumes in PDF form. And so if you remove the PDF, they're completely lost, we've completely changed our day to day never involve them. So technology works perfectly, really cool algorithm, plans on improving that with AI a bunch of stuff, the candidates love, but the BP loves it. But we didn't create allies of the people that were actually going to be using the software and therefore we just fell on our face.

Richard Walker 10:30 

Oh, man, yeah, that is so important to keep people involved in formed, and giving him checkpoints along the way, as well, to hear their feedback periodically. Let's talk more in depth about AI. I mean, companies come to you for technology projects, how many are coming to you now to say I need something that is AI built AI driven whatever?

Eric Bourget 10:53 

Most people will come to us with a question, which is, considering my industry, is AI going to disrupt me? Or do I have an opportunity to disrupt my market using AI. And it's funny because AI just made technology interesting to a lot of players that were not traditionally interested in using technology for what they were doing, for instance, a communications company. So communication company comes to us. And they say, we want to be able to use chatGPT. But our clients for business forbids us from doing that. Because they're afraid that it's going to be used as learning data for open AI, which it absolutely will. And so they can't use it. But it's very easy for us to create a platform that leverages open AI, but that protects the data that's basic, and usually the question is going to be well, are you just trying to build a tool so that you can use open AI? That's not really interesting? What is it that you would love to change in your industry that AI could completely change? So it's an interesting merger of people that know technology, but are not an expert in your industry, and you're an expert in your industry, but your knowledge or what you understand about AI is very naive. And it's very shallow. And it's based on a bunch of stuff that you've heard. And so that initial merge of these two things is very interesting. I was gonna give you an example. I don't know if that makes sense. But so one of our clients, has a situation where they need to respond to about 400 RFPs, every single month. And so they have an army of people that are doing it, no one loves to fill out an RFP. So it tends to go to the lowest people in your company, like the interns, whatever. Well, the interns, they don't really know anything about your company. So you're giving him a bunch of paperwork to understand. So it's this mess of clerical work drudging painful. And so they're like, how could we use AI to do this. And so what we've ended up doing just to make the story short, we created an application that utilizes I don't want to get too technical, but it's the basic principle is called rag. So it's a retrieval augmented generation. So you're grabbing information somewhere else, you are using that as inference data, and you're telling the AI stack, hey, you need to become a master of all this information. So regulatory information, and all that stuff so that I could take a question from an RFP, put it in here. And that says, what is our policy in case of someone quits, and we want to prevent them to have access to our data, that information is in one of the 400 documents that sits in there? Well, the AI tool is going to find that in a fraction of a second, compose a really cool message, that response that the user can just paste it back. And so we've taken a process that takes about six weeks, and we reduced it to about six hours. That's just what AI does really well. Then the other thing that's interesting is that always leads to the next level. So an example is, one of the questions is, hey, what is your policy for inclusion from the LGBTQ community? They don't have a policy for that. And so instead of replying, I don't know. It's very easy for you to say, well, would you like us to generate one? Because there's a central bank of other stuff. And so you can then work with that stack to create the missing policy, you get it approved. You put it back in your stack, and now you can answer and so by, look, there's a saying that says the only way to win in business is to be in business. Well, the only way to win an AI is to be in AI, you need to put things together. You need to vibe with it. Figure out what's going on and then you'll get a bunch of new ideas, but you just need to get started do something.

Richard Walker 15:03 

Now that's the most important point, I think, just dive in. I mean, yes, be careful about what kind of mistakes you can make, like anything, right? You don't want to delete your C drive on your computer when you're learning computers for the first time. I think this is really interesting, you just give me this idea. Because, I mean, I really don't like RFPs. And the customers that do it, they often don't give you enough context to understand what it is they're trying to solve. It's almost like they're just saying, give us everything about your company, and we'll figure it out. So I feel like I want to take the RFPs we've answered really, really diligently throw it into a GPT model, and make it answer more RFPs for us in the future. We don't do 400. I mean, I would never have been 400 in my life.

Eric Bourget 15:46 

But what you could do is you could also tell open AI, before you answer any of those questions, go browse all the information from the company, and try to optimize the answers so that they fit with the language that this company is using. Right? The companies love to hear their own words back. So it's like, make sure you use their words.

Richard Walker 16:07 

That's even smarter man. One of the things I'm noticing and what you talk about here is you're not talking about AI for AI sake, you're not talking about it as enamored with tech, you're talking about it from the business standpoint. When you're thinking about it, you're thinking about how to solve a business problem. So you mentioned large language model GPT approaches, is that the number one thing people are asking about? Or is that the number one way to solve problems for people that they're bringing business problems to you with?

Eric Bourget 16:36 

Yeah, HalfSerious is in the business of productization of technology. Right. So that's the number one thing. Open AI is the 800 pound gorilla, and it's a general LLM does a lot of stuff. But we do use other models. So I'm trying not to get too technical. But, whenever you're saying, hey, I'm going to query, I need to ask you a question. And the answer resides in this database. And then I want you to answer, it's almost like, think about it, like talking to your hard drive, you're talking to this big database, the database contains all the information that I need to respond to the RFP? Well, when I'm asking the question, using natural language, what is our policy for whatever? It doesn't go directly to open AI, it first goes to an LLM. That's a separate technology. That's a model that's optimized to convert natural language to an SQL query. Right. And so that one, it's a much smaller model, it just creates an SQL query, it asks the database, the database answers back in the way the databases do, you feed that to open AI, so that it can package it into the socket generate natural language that then you can use? So you're combining different models together in order to create this product? So a lot of people to your point, will think that we're basically just wrapping open AI. It's a lot more sophisticated than that.

Richard Walker 18:10 

Yeah. And there are other texts, like you said, I mean, the Google has theirs, but AWS has it too, right? So which one of these, of all these open GPT models or large language models? Which one do you think is the easiest to secure for client?

Eric Bourget 18:26 

Oh, I mean, open AI is obviously the best choice right now. And they're sort of on this path of, you remember, a couple of years ago, you would have a Google Drive account. And then you would get an email that says, hey, your previous account was 25 gigs, for five bucks a month, your plan has been updated. It's now 100 gigs, and it's good cost you two bucks a month. And that seems to be like when they did their latest upgrade, they cut the price by four. So they're still they cannot ignore it. But you get to everything around open AI as well, there's going to be a bunch of different things. Some of our clients are saying, hey, if I'm trying to get this form filled or understood by someone who is vision impaired, we're not going to use open AI to do that. There's other models that are going to give me text to speech, or even puts a personality on the screen or like a live person that talks to you. There's a bunch of like, packaging, all these, I'm going to call them agents, packaging all these agents together, in order to productize it, I think is the most interesting thing. If you want to browse all these things I suggest you go to there's a site called hugging face. Hugging face is a big repository of different models, where you could do a bunch of stuff with it. So I think that for the foreseeable future, open AI is probably going to be the backbone of everything that we build, but we don't access it directly. We're AWS partners, and AWS has this platform that's called bed Iraq that you can use to access these things. So that later on, if we decide, you know what, it's not open AI, we're going to inject it and plug something else, then we can do it. So I think if you're building AI right now or productizing AI, right, now, there's probably two things that you want to keep in mind, you build an architecture that allows you to be flexible, because it's a very, very dynamic field, you want to be able to swap things around without breaking anything. And in order to be able to take advantage of it's like, it's a technical debt as a constant. And so you need to be really, really smart about the way that you're packaging these things. So there's really good abstraction levels, that layers so that you can unplug and plug things I'm simplifying, but you understand what I'm saying. And then the other thing is, build a bigger team from the start, you need to build, you need to have at least five people on your team, you're going to have at least two people, they're just going to be monitoring technologies, testing it, and then you're gonna have a frontline team that's going to productize it. And the reason it needs to be somewhat bigger, is you're gonna lose 50% of these people every year, because the competition for that talent is just insane. So if you have one person who's a full stack, who plugs things into open AI, you'll get somewhere, you'll probably lose that person in the next years. So, what are you going to do?

Richard Walker 21:20 

Yeah, I think that's one of the challenges with these evolving new innovative technologies. There's a lack of people who have the skills when they develop the skill, it's in demand, they get paid more. That's definitely one of the challenges. But I want to go back to something else. Because we've been talking about AI, as technologists for five, 10, 15 years, I know some people way, way, way longer, I met somebody who was working on AI in 1992. But those different models were a machine learning that was like text to speech and speech to tax all those things. And I think that open AI is kind of like the Henry Ford of our day. They made it so obvious. They made it so easy to consume and work with that everybody who's getting into AI now is thinking that's what it is. But it's not. It's a whole bunch of different models, like you talked about, some of which approach large language, some of them approach vision imagery, there's so many different pieces to the puzzle. It also makes it daunting, which is why people I think, come talk to you. How do we figure this out?

Eric Bourget 22:20 

Yeah, exactly. I think yeah. It's weird, because open AI, what they also did is like, you remember, QR codes came out a long time ago. They were very unpopular, they disappeared for a while. And then we had a resurgence. And now they're somewhat popular, right? Pandemic, I don't want to say that word again. I don't want to jinx anything. But somehow they're popular. And what open AI did is they've created things in people's minds. And they created desire for this, because like you said, they made it very accessible. One of the issues is, no one really understands what it is. And everyone's understanding of it is extremely naive. And they'll in the same conversation, they'll tell you something, and my answer is going to be well, that sounds like one guy, two weeks, get it done. Oh, I have also that have this other idea. And I'm like, two PhDs five years. So they don't really understand where the limits are.

Richard Walker 23:19 

Yeah, it's one of my favorite things was the technology when people who don't build technology come to you with an idea? Oh, Rich, I got this great idea. It's just a simple little app. I'm like, that's minimum six figures, probably 12 months of work. They're like, No, but it's really simple. Just do that. Yeah, no, no.

Eric Bourget 23:35 

A friend of mine was using this analogy saying like, hey, I need an app. Okay, well, what does that app do? It takes a picture of a bird, and it uploads it to the cloud. So, easy, three weeks of work one guy? Oh, and also I needed to classify its exact genome, and describe, okay, two PhDs, that's gonna be that type of thing. So sometimes it just sounds like this little extra thing. But you're asking for something that's completely different.

Richard Walker 24:04 

So Eric, I've asked a lot of people on this podcast, who are more business leaders and less technologists, if they think AI is going to change people's jobs, if it's going to replace people's jobs, is there a threat, that kind of thing? You're working with tech all the time, and working across lots of industries and customer types? So you're seeing a totally different perspective. So what do you think AI is actually doing to impact people's work lives? Is it going to replace jobs? Is it going to replace old technologies out there?

Eric Bourget 24:33 

I think that it will replace jobs, and I think it already has, it is probably a good thing in this environment, because we don't have enough people for the jobs that we have. And right now, at least the jobs that it's replacing, it's usually jobs that people just don't really want to do that is very sort of dredging. If I had to like hit crystal ball or I had to make a prediction. I think that at some point, we are going to have departments of people and departments of AI. And let me explain that. There's a platform that you might want to play with called AutoGen. I don't know if you've ever heard of that? AutoGen is basically you could create an agent. And you could get that agents to work with another one.

Richard Walker 25:18 

Oh, I've seen this. Yes.

Eric Bourget 25:20 

Yeah. So I have a friend of mine in Toronto, he's actually built a website that updates itself. And the way that he's done it is he has created a couple of different agents. The first agent is an agent that browses the internet. And I think that agent is interested in Tesla, and the Toronto real estate, right. And so it just grabs what's going on, and it lists them out. And then it provides it to another agent, that's a writer, and the writer will look at these topics and write articles. And then they'll hand it over to an editor. And the editor will make comments because it's been optimized to understand the tone of the article that it's looking for, there will actually give feedback to the writer. And you can observe these AI's talk to each other, because they talk to each other in like a chat format, in a chat room that you can observe. So you can see them talking to each other. And so back and forth, back and forth. And then there's probably an SEO agent that says, hey, make sure use these words, because they track better. And then at the end of the pipeline, there's an agent whose optimization is to put it on the website. So in the end, what do you have, you have a website that updates itself based on a department, if you will of AI agents that are just collaborating with each other? I am fascinated with this concept. In fact, if my company got sold today, and I wanted to start something else, I would start a company that helps other companies build AI departments, I would call it the department's.

Richard Walker 26:50 

Wow, what a fascinating view of this, you're right, I have been so focused on AI augmenting skill sets. And so like a lot of our customers, they're looking at our new product Form Xtract to eliminate having to look at forms and type the data that came in on a completed form. What I'm finding across the board is that these are high value high paid people, it's not their full time job to do data entry, it's part of the job, and it's the worst part of their job. So we're getting them out of that task. And we're not replacing the person we're giving them the better work to do.

Eric Bourget 27:20 

I think what you're describing is we are short sighted sometimes in the way that we think of AI as an assistant. And we might be better served by thinking of AI as labor. So I don't know that much about your business. But you might say, you know, this form is incomplete. Figure it out, and if that AI needs to send an email to someone, because it's missing information, then it does it. Like it gets all the information, it fills the form. And maybe it sends the form to another AI, who's an auditor, and that other AI is like, hey, this thing doesn't make sense or whatever. And so you're getting the AI to actually do the work instead of just assisting the person that does the work.

Richard Walker 28:04 

Yeah, I mean, applying AI to the workflow in business is going to be so powerful over time. It's going to be amazing. Man. Eric, I want to keep talking about we want to wrap up. Before I ask you my last question, what is the best way for people to find and connect with you.

Eric Bourget 28:19 

Probably send me an email, I would say is the best way. I don't want to send people to my website, because it's outdated. But we'll figure that out. For sure I need to. It's always the thing because the thing that I struggle with sometimes is I does things well, but never great. And some things need to be done great. And greatness comes from human ingenuity. And I do not think that will ever replace that not in my lifetime. And I believe that AI's role is to free us from the burden of drudgery so that we can apply our creativity and human ingenuity to things that deserve it.

Richard Walker 29:03 

You're here man, cheers to that. That's exactly what I want to see. All right, so here comes my last question. Who has had the biggest impact on your leadership style, or how you approach your role today?

Eric Bourget 29:13

I think I'm gonna go to another topic, probably. But my biggest, I want to say, issue challenge really is running the business as someone who's called, like, I want to be more thoughtful. I want to be more prepared. When I show up for a conversation. I want to be more present in the conversations that I have. And so I'm simplifying the organization. I'm trying to master myself. I'm looking at a lot of books and content that 10 years ago me would have just rolled his eyes and warrior sage and all that stuff to just it like I want. Now that I have a lot more means and a bigger company and a tighter mission, I wanted to be able to do this for a long time and have, but to do it in a way where my mind is at ease as opposed to just being on the gun all the time, right. And so I want to give a shout out to Maddie Josie, who's in my forum, I'm part of EO as you know. And so she's in my forum. And she's always struck me as someone that's been doing this for a long time. And she always looks like she's on top of everything that she's doing. But she always also has time for you and his call. And I've always been very impressed with the ability to do great things. But to feel like it just makes it look easy. And I'm sure it's not easy. But she just seems like she's very Zen about everything that she's doing.

Richard Walker 30:47 

I love this topic. So can I share a technique that I use with you, please? I have a very simple belief I've applied throughout my life. And that is if somebody else is stressed out about something worried about it, it's their job to worry about it. I won't be. So I can't tell you how many times in my company, we couldn't pay payroll. And that's not a problem today, but so many times and my COO had to manage that problem. Since he was stressed out about it. I wasn't, oh, yeah, he just kept me so much more calm about the things that were going on. Because my product is stressed. My engineer has stressed my customer service team is stressed. I don't have to be stressed about those things that they're worried they're worried about.

Eric Bourget 31:25 

Yeah. Interesting. You have a couple of I'm trying to work on like, what are my principles or playbook or recipe and one of the things I'm really interested in these days is, well, I just I'm reading right now Untethered Souls, which is really interesting, but you have to sort of be ready for it. And one of the things that I keep on thinking about is, in the end, what I'm trying to manage, is I'm trying to focus my attention, and I trying to have clarity on my intention. And so every moment where I feel like this is too much, I'm always like, okay, what is my intention in this moment? And how do I manage my attention? And so if my intention is to, I don't know, increase my network, and my attention is being distracted by payroll, or whatever? I'm like, oh, how do I solve that to get back to this balance? I'm not saying that I figured it out. But that's like, that's my latest version.

Richard Walker 32:19 

Oh, that's awesome. All right, we got to wrap this up. So I want to give a huge thank you to Eric Bourget CEO of HalfSerious for being on this episode of The Customer Wins. Go check out Eric's website at Go check it out. Because he's gonna make it better, And don't forget to check out Quik! at where we make processing forms easy. I hope you enjoyed this discussion, will click the like button, share this with someone and subscribe to our channels for future episodes of The Customer Wins. Thank you so much for joining me today, Eric.

Eric Bourget 32:54 

All right. Been a pleasure. Thank you.

Outro 32:57 

Thanks for listening to The Customer Wins podcast. We'll see you again next time. And be sure to click subscribe to get future episodes.


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