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The WorkOps Podcast is your weekly conversation with HR leaders and People Ops practitioners doing the real work.
In every episode we dig into one story. A process that went sideways, a system that just didn't work, and what someone actually did about it. Packed with practical lessons you'll want to bring back to your team. Whether you're supporting 500 employees or 5,000, this is how the best People leaders are building for what comes next.
Jean & Jeet | May 13
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Speaker 2: ~um,~ [00:00:00] if you're not seeing it, I think it's more of a culture problem than a tool problem. Mm-hmm. Because those tools, they're good, and they're changing all the time, and if you can't get your team to experiment and try them and kind of over that learning hump that they're gonna go through, it's-- that's more about the culture than it is about what tool you're gonna choose.
Welcome to the Work Ops podcast. In every episode, we dig into one story, a process that went sideways, a system that just didn't work, and what someone actually did about it. It's packed with practical lessons that you'll want to bring straight back to your team. This podcast is brought to you by Kinfolk, the AI service desk built for HR.
I'm your host, Ajit Mukherjee, and with that, let's dive in.
Speaker: Hey, everybody. Today, I am joined by Jean Parchewsky, who's the VP of People Operations at Vendasta. Jean, thank you so much for joining us today. Before we jump into things, can you tell us a little bit about yourself and how did you choose [00:01:00] HR?
Speaker 2: Yes, for sure. Thanks for having me. Great to be here. I don't know if HR was that much of an intentional choice for me, ~you know,~ in my career.
~Um,~ it just seemed to continue to grow and change when I-- now that I've found myself here. But I hear that from a lot of leaders today, that the spot and career that we're in now looks way different than we originally imagined when we were 18 or, or 20 years old. Mm-hmm. I went to university for psychology, ~actually, and, um,~ I did a short practicum at the hospital, and that's when I realized this isn't kind of where I want to be.
I was pretty creative. I love entrepreneurialism, ~um,~ I'm competitive. I really like business, and I liked a great challenge. So I ended up joining a startup, ~uh,~ that was just starting to expand in Canada. And I moved provinces and, ~uh,~ I spent many years just working with different brands as they were coming to Canada.
And, ~um,~ that involved management mostly, but a lot of HR. And I, and my last one was with Target Canada, and they, ~you know,~ opened up, I think, 270 stores in Canada and then closed them just as fast. And, ~uh-~ Wow ... when I applied [00:02:00] there, I had applied to, ~um,~ in management, but I ended up, they asked, "Hey, would you do HR for us?"
So I kind of didn't look back after that.
Speaker: Wow. What are the, what are the elements that really drew you into HR?
Speaker 2: ~Um,~ I like to remove unnecessary friction from... so people can just come in and do their jobs. ~You know,~ I think that we-- In the past, HR has been fairly policy and, ~um,~ compliance driven, and I thought, ~you know,~ what if we can build a company without policy and just make it on, ~um-~ Nice
~you know,~ good business practices and you don't have to, ~you know,~ it sounds kind of fluffy and, and, ~um,~ Pollyanna of me, but we were able to do it for a long time till we grew to a certain size. Like, obviously, you need some policy, but I, I like that part of HR. ~You know,~ make it easy for people to do the work that they're hired to do without extra, ~um,~ red tape.
Speaker: You're speaking my language. ~Um,~ I like that a lot. And, ~uh,~ in this podcast, as ~you know,~ we do talk about one of those, ~um,~ points of friction- Perfect ... ~uh,~ a system or process that w-didn't quite work out or was, was dysfunctional. ~Um,~ so Jean, would love to dive into that. What is the story that you wanted to share with us today?
Speaker 2: A [00:03:00] big point of friction for me at, at another company I worked for, um, it was a pretty established company, and it was, it was a while ago. It was when they used to have, um, all the learning material was in, like, big binders on the shelf. Like, I remember looking through these binders, this big- Wow ... ~you know,~ training manual.
And there was so much on how you had to, like, I think probably like two chapters just on how you would, ~um,~ do performance management where, where you had to remove somebody from the organization or, ~you know,~ let them go or terminate them. There was very little on how to hire the right talent or how to develop the right talent.
~You know,~ maybe a- Hmm ... just short paragraph, and then here you have an extra whole binder on how to re- ~you know, um,~ do the termination. So I feel like they, they really optimized for, ~um,~ legal and, and liability, ~um,~ to, to make sure that their, their, ~um,~ risk mitigation versus optimizing for what's good for the person or good for the team and, and the company.
Speaker: Okay. And, ~um,~ w- I wonder what kind of impact did that have on the team or the company, given that they were optimizing for risk mitigation as opposed [00:04:00] to the human experience?
Speaker 2: Yeah. Anyone that, ~you know,~ that you wanted to, ~uh,~ do performance management with, you'd have to write it all up, ~uh,~ make sure that you had the-- somebody that was at head office sign off on it.
You had to wait for them to sign off on it. You'd have to, ~um,~ review the meeting. So it was really, really lengthy. So here you have somebody that's underperforming, probably not happy in their job, ~um,~ not being successful. I think obviously, ~uh,~ foundationally, everybody wants to do a good job and, and at least try, ~uh-~ Right
to be successful. So y- it was just like drawn out. And I would see, ~you know,~ once I even saw somebody good leave because they were tired of waiting for the manager to, ~um,~ to handle this person that was underperforming and not coming to work. So they were like picking up their slack for so long that, ~you know,~ you have good people leave because you have this lengthy process that really, if you were just honest and transparent from the beginning with the person, you could, you could alleviate it.
I believe in, ~um,~ the saying, ~uh,~ "Hire slow, fire fast." And so- Yeah ... ~uh,~ you can put your efforts into hiring the right people and spending a long time on that and a [00:05:00] short time on- Hmm ... removing them when you know it's not working. It's just better all around, I think.
Speaker: Yeah. And, and that sounds like a, a, a huge impact.
I mean, not only is there friction in the process itself, which is what we were talking about earlier that you wanna fully avoid, but the impact that a good person ended up leaving. Uh-huh. That sounds like possibly beyond the legal and liability piece from a, from a, um, organizational benefit perspective, that is, sounds like the worst outcome that could have been possible out of that experience.
Hmm. Yes. ~Um,~ that is, that is not related to them at all. ~Um,~ is that kind of what triggered, triggered you to, to wanna look at this process and, and make you wanna fix it, ~um,~ while you were there?
Speaker 2: Yes. Yeah. I wanna-- I reached out to our director at the time and said, I don't know, just- Discussed how much time was spent on that, and we ended up, ~um,~ decreasing it a bit.
They, ~you know,~ they still were a little, ~uh,~ nervous and, ~um,~ kind of afraid to reduce some of the paperwork on it. But at least at this company now that I'm with, we, we're very much into the spend a long time on [00:06:00] hiring, ~um,~ and- Yeah ... and make sure that when something's not working just, just tell them right away.
We, we spend, ~um...~ We have something that we call, ~um,~ it, it's, it's from, it's an Amazon principle to have a bar raiser in every interview. So I tell the managers- Nice ... like my slogan is how, how you don't go to the grocery store hungry. You also shouldn't- ... ~um,~ 'cause you're gonna end up buying stuff that you don't need.
You also should always have somebody in your interview process who doesn't have skin in the game, someone that doesn't care that it's gonna take an extra two weeks. What they care about- Mm-hmm ... is that you find the right person. ~Uh,~ 'cause when you really need to hire, ~uh,~ you can overlook certain maybe flaws or certain traits that the person might have that are not gonna help build your team and build your culture.
Speaker: That is an amazing analogy. ~Um,~ I have definitely, ~uh,~ gone to the grocery store when hungry and- ... ~um,~ come back with way too much stuff. And you're right, having my partner with me there to say, "Uh-uh, no"- Yes ... "don't, don't bring that home," absolutely helps. And, ~um,~ I've also been, ~uh...~ I've, I've also not hired as, [00:07:00] as slowly as we'd wanted to, and we've seen the impacts in previous roles, so I, I totally get that.
That's such a neat little addition, ~um,~ to have someone else there. And, ~um,~ you mentioned that you were looking to decrease the time a little bit. ~Um,~ did that end up having enough of an impact, or, ~uh,~ did you still see kind of the same things play out and still a primary focus on legal and liability versus an improvement on the leaver experience or the underperformer experience?
Speaker 2: I think it's here. ~You know,~ I've, ~uh,~ I've been here 12 years, so obviously there's been times- Mm ... where we've had to let people go. But I'll see them out... ~You know,~ I saw somebody even just last night, and they'll come up, and they say hi, and they visit with me. And I feel that when you're honest with somebody, and you say, ~um, you know,~ "Why work for s- why try for s- 12 weeks?"
Especially if you don't know, ~uh,~ if it, if... Like, especially if you know already that it's not gonna work out. ~Um,~ I'd rather even pay them the time and, and not have them- Mm-hmm ... them have to suffer through the stress of it all. And yeah, they're appreciative. They, they're, ~um...~ It's, it's been really good for us.[00:08:00]
Speaker: Yeah. They, they prefer that, I imagine- Okay ... ~um,~ to be honest and upfront and be told what's gonna happen. ~Um, and, uh,~ in wh- where you are at the moment- Mm-hmm ... ~um,~ what are some of the, ~um,~ frameworks that you're using to, ~uh,~ decide, hey, this person maybe isn't quite the right fit for us, or maybe we're not right, right for, for them?
Speaker 2: Mm-hmm. I think there's always- Kind of the, the competency reasons or the conduct reasons. So conduct's pretty easy. ~You know,~ if somebody isn't showing up to work over and over and over, ~you know,~ or they're, ~um,~ not able... ~You know,~ we have a software product that can be complex, so if they're not able to handle learning the software or, ~um,~ not making certain goals if they're in sales, ~um,~ we have metrics like that.
We have weekly one-on-ones, and we document at the very beginning, ~um, you know,~ these are the outcomes that we need, really clear, and so that we, when we meet with them weekly or on 30, 60, 90 days we also meet, ~uh,~ we do an evaluation each, each of those meetings, and that helps- Mm-hmm ... call that out really quickly.
But most people pass their probation. I think that I [00:09:00] would go to the root cause again, that if you spend a... If you hire the right people, ~um,~ to begin with, it kind of alleviates a lot of that, ~um,~ that problem. So I treat it the same way I think that marketing treats, ~um,~ their ideal customer profile or sales will have these- Hmm
customer profiles. So I like to think of it that way, too. Like, who is our ideal employee profile? And a while ago, probably eight years ago, we sat down as an ec- executive team and we thought about what type of culture do we want here? ~Um,~ what are the competencies and the behaviors that we want our employees to be doing day in and day out, which really is what builds your culture.
So we came up with, ~um,~ how we want them to behave, and, ~you know,~ do you want someone that is going to prioritize perfection over speed? Do you want someone that would be about having consensus as a team, or do you want them to, ~um,~ there's a principle, ~uh,~ have a backbone, disagree and commit. Like, do you wanna argue things out?
Hmm. And we came up with these, ~um,~ main ones, [00:10:00] and then we built this ideal employee profile that isn't about technical skill at all. It's just about what, what are they like as a person? And, ~um,~ I think that's really helped in our, in our hiring, ~uh,~ practices to make sure that we're- Hmm ... getting that, that right, ~uh,~ fit from the beginning.
Speaker: That's awesome. And h- how have you seen those hold true? ~Um,~ you mentioned you've been there for a few years. Mm-hmm. ~Um,~ given that they're not kind of competency or technical, ~um,~ based, ~um,~ frameworks, ~um-~ Yeah ... they're behaviors, right? ~Uh,~ so I assume those behaviors have carried through and they're kind of constant regardless of what- whatever's happening in the market or even in the business.
Speaker 2: Yeah. Yeah. It- it's kind of like tall enough to ride the ride. Like, if they don't have those, they don't go through the technical stage. ~Um,~ I think it's really helped us with AI as well because when you have a team that is open to failing, ~uh, you know,~ we have movers and shakers announced at our all hands every Friday.
So they, they like moving around, they like trying new things, they're very agile. ~Um,~ that helped us because they were okay with trying AI, and they're okay with changing their roles, ~uh,~ and, and weren't as afraid to kinda jump in [00:11:00] and, and learn something new.
Speaker: And, ~um,~ since we're kind of talking about the, the capability or the competency piece, are you also seeing AI fluency become one of those, ~um,~ one of those, those measures, ~uh,~ to understand if someone is a good fit for, ~uh,~ the organization?
Speaker 2: We check if they are interested in AI and if they've been experimenting with it. ~Um,~ if they're open to learning, we can... ~you know,~ they can learn that tool. Mm-hmm. I found that, ~um,~ AI enablement in a company, if you're not seeing it, I think it's more of a culture problem than a tool problem. Mm-hmm. Because those tools, they're good, and they're changing all the time, and if you can't get your team to experiment and try them and kind of over that learning hump that they're gonna go through, it's-- that's more about the culture than it is about what tool you're gonna choose.
Speaker: Yeah. Are, are you facing some of those scenarios now where there's a bit of a hump that you're, you're encouraging employees to go through? Or are you seeing kind of full, fuller adoption and uptake?
Speaker 2: ~Um,~ we [00:12:00] are-- We're seeing the hump, a-and it, it comes and goes too. It's this, ~um,~ who... It's, ~uh,~ trying to think of the person that...
It's a Trough of Disillusionment, I think is the title they say- Yes ... in the, in the book. But, ~uh...~ And then when something new launches, you get that again. So we're coaching them through that. We have something called, ~um,~ a citizen developer program. So we found the early adopters. We found the people that were really excited about, about, ~uh,~ AI at the beginning, and we put them together, and we went through and trained them.
And they had to be non-developers because we have a development org here too, department. ~Uh,~ and we train them on how to use Claude, and at the time it was, ~um,~ Cursor, and now it's, keeps changing. But how to use Claude to build things themselves. And then they went out, and they spread that to their departments and teams to help- Yes
support them. ~Uh,~ we built a AI builds board, so you can see it, ~you know,~ how many builds have we made, ~uh,~ how many, ~um,~ AI agents have we built or, ~uh,~ workflows have we improved, hours saved. And so that's helped us to kind of like duplicate this and kind of super spreaders through our organization. But [00:13:00] we have to share every Friday, and we also have a meeting every Monday where people demo what they've built, and they have to be okay with failing, and they have to be okay with sharing how they failed so that other people think, "Oh, okay, so it's not just me.
It's, it's me and, ~uh,~ every one of my peers going through this at the same time."
Speaker: Yeah. That's, that's awesome. How, ~um,~ was your team kind of involved in this? W-were they one of the folks that were building the process, or were you more kind of coordinating the process and, and enabling people to use AI within the business?
Speaker 2: Mm-hmm. At first, we let everybody, IT was kind of driving it, and we let everybody experiment with it, and we got- Mm ... a lot of usage, but we didn't get a lot of improved workflows. ~Um,~ we got a lot of better emails. So we- ... ~uh,~ we decided to have it live in people operations 'cause we're close to the people and the workflows, and it's not just a policy, ~um,~ in a book that's gonna sit there, and it's not just, ~um,~ a new tool or, or...
We had the guardrails made, but people ops- Mm-hmm ... took it to then start working with the teams and start [00:14:00] seeing, "Hey, let's break down your workflows. Let's see what you're doing and see how you can, ~um,~ make some of this automated with AI." And then, ~um,~ we-- Also, there's a concept called T-shaped worker and M-shaped worker.
So in the past, we had a box that, ~uh,~ an employee would go into, and it's a job description with skills and competencies. And w- maybe you have one, like a blog writer and a content writer and reputation reviewer and a website writer. And so you had all these different roles, and when one of them left, you posted for the blog writer, and you hired.
Mm-hmm. And the T-shaped worker was, ~uh,~ from EOS, I think, or EONS, and it was, ~uh,~ breadth across the top and then one strong skill for the T. Right. And now the M-shaped worker is that the person will be able to grow multiple prongs of, of skills, and they'll be able to learn from their peers 'cause you can do so much more with AI.
So now our blog writer, if they're to leave, ~um,~ because we've made that whole team into M-shaped workers, they, ~uh,~ [00:15:00] all know each other's workflow, and they can, ~um,~ pick up where the other one left off, and you don't necessarily have to just backfill that one role. So that's helped us a lot too, and because we're close to them, people ops, we're able to work with the teams to do that.
Speaker: That's amazing. ~Um,~ are you also seeing that there are more and more folks who are M-shaped, given they can now use AI to be able to go deeper into things?
Speaker 2: Yes, yes. They're getting M-shaped. We're changing their titles too, and, ~you know,~ it's kind of funny. You hire somebody, and sometimes within the first week, they're like, "What's then my next job title?"
Or, "What can I do next?" I feel like they're really interested in growing their LinkedIn. ~Uh,~ so as a t- as a company, along with compensation and along with all the benefits, I think that's something we can offer them. ~Uh, you know,~ people aren't staying at careers for, ~you know,~ even 10 years seems like a long time today, especially- Yeah
~um,~ when they're just starting out their career. So if we have them for three years, and they can do an amazing job here, and we can help them to learn a bunch of new skills and be M-shaped and get that on their, their LinkedIn, how they grew here, I think that's something that [00:16:00] is a win for, for both of us.
Speaker: Yeah, and I really like the approach that you took, ~um,~ where rather than necessarily starting with AI, you started with the workflows, and you said that you worked with the teams to be able to break down the workflows and look at actually what is the unit of work, and then can we automate that, and what is the best way to automate that?
~Um,~ how did you go about that process? Do you set up meetings with, with managers first, or did you do presentations? How did you get people excited to even open up how their work is being done so that you can partner with them to help them improve it?
Speaker 2: Mm-hmm. We changed our director of learning to director of AI business enablement.
So we changed her title. Nice. Okay. And changed her job description. ~Um,~ I do say some... AI, AI might take some jobs, but I think more than anything, it's changing job descriptions, and if you're willing to- Yeah ... ~you know,~ move with that, you're, you can be safe. So we had to remove the fear. We talked... We did all of the above that you said.
We talked very openly about it. We said that we have jobs for everyone that is open [00:17:00] to learning the new skills, ~um,~ and we did presentations, and then we, we dove in. So we took those citizen developers and made sure that we could, ~um,~ have them go back to their teams, and it wasn't just, ~um,~ redesigning the...
or, like, automating their current work-workflows. Really reimagining, do you need to even be doing this anymore? And it's a, a fresh start on, "Hey, do we even need this process or this spreadsheet? Could there be something different we do?" And we had to really give a lot of examples. So when on Friday, when people stand up and show what they've built, even though they might be in R&D or they might be in marketing, ~uh,~ we can really relate to, "Hey, they, they did that with their emails and they automated this, ~um,~ script, or they made this agent.
I can do that and use it for this process." So it's relatable, and that really helps people just grow from each other.
Speaker: Yeah. Nice. And it sounds like those citizen developers are there who wanna take on that responsibility. [00:18:00] They're making time, ~um,~ within the workday, perhaps even over weekends, to be able to take this forward.
I also imagine, though, that there is a core of folks who are perhaps a little bit apprehensive. ~Um,~ we've heard phrases that, "Hey," ~actually, you know,~ some employees, they are scared of looking stupid because they may not be so au fait with the lingo of skills and projects and .md files and that type of stuff.
Mm-hmm. And therefore, they shy away from that. ~Um,~ have you experienced that, and is that something that you had to navigate, ~uh,~ within, within the transformation itself?
Speaker 2: Yes, for sure. I feel like that too. I I'm like, "What's Markdown and what is this and..." All the new terminology. Mostly I feel that What helped with this is the CEO, he is a huge advocate, and some of our smartest engineers getting up in front of everyone and saying, "I don't know what this means," or, "I had to learn this to..."
Or, ~you know,~ "I, I just asked, ~uh,~ ChatGPT," or, "I asked Gemini what this [00:19:00] meant." So if you know that the CEO's even asking those questions, it really allevia- alleviates your, ~um,~ imposter syndrome or your feelings of inadequacy- Yeah ... because you don't know what that is. Just sharing. You gotta... Y- we just, we can't stop talking about it enough.
Speaker: Yeah. And, and it sounds like you've also created a really great space where people are okay to, to fail, they're okay to burn tokens if they need to, and they're okay to create stuff which may be AI slop. And that's- Yeah ... okay because that's the only way that you're gonna, you're gonna learn. Is that something- Yeah
that's kind of on your mind of like, "Hey, at some point we wanna reduce the, let's call it slop, and we wanna move to things where they are going to actually be directly impactful to the business"? ~Um,~ or are you more in an experimentation phase where it's like, "You know what, guys? It's okay. Just, just go for it and experiment."
Where on the journey are you?
Speaker 2: We are definitely wanting to make it impactful for the business. And- Mm ... we had that conversation though ex- ~you know,~ exactly what you said, the, the slop, and [00:20:00] people were building things for, like, their hockey teams and, ~um- ... uh,~ different stuff. So we, we said it, it has to impact the business in, in some way, and we also had...
One of our developers built Vendasta Vibe, which is a way to vibe on our own platform. So Vibe Code. So we're, we're moving it there too so everything's on the platform and everyone can see it. We... You get sprawl too because people are building the same types of agents and the same things. Mm. So on our build board you can see what everyone's built, ~uh,~ you can search it, and you can read about what that agent does so that you don't have to rebuild it.
You can just, ~uh,~ copy their, the workbook and playbook, I mean, and, and paste it in.
Speaker: That's awesome. And i- is this something that you've built, ~uh,~ in Claude and it's pulling all the different, ~um,~ workflows from Claude? ~Uh,~ or how is that managed?
Speaker 2: Yeah. It was built, ~uh,~ in Claude and with our IT as well. We had to...
Because there was some personal information in there that we had to link, and then it's pulling from Jira and things like that as well.
Speaker: That's awesome. And you're seeing, ~uh,~ not just the technical folks but also non-technical folks, ~um,~ start with these kind of [00:21:00] pieces and then also get, get added to the build board?
Speaker 2: Yes. It's mostly non-technical. ~Um,~ the developers, they, they don't add to it as much. It's, it's really the, ~you know,~ our, our executive assistant, our HR team. It's just everybody who, who- ... ~you know,~ they said they didn't, they didn't, ~uh,~ know that they could develop and, and they're able to join
Speaker: Isn't that so great?
What a time to be alive where anybody can start to experiment, at least get to your proof of concept or some kind of- Mm-hmm ... minimum viable product. And you just mentioned there that it also included the HR team. ~Um,~ what are some of the, the most impactful or the most fun things that, that you and your team have built, ~uh,~ during that process?
Speaker 2: I'd say the most impactful is really early on, we built, ~uh, a, uh, um,~ an employee. Now we-we're kind of moving from calling them agents to now employees. So an employee. Mm-hmm. Her name or his name is Pepper, and we linked it... There's one on the back end, so it's private. You can't see the chats, and then like well, HR can see them to, to help, ~um,~ improve our data that's in there.
But then [00:22:00] there's also one just on our Gchat, kind of like our Slack channel, and you can ask any questions you want in there, and we've trained it to, ~um,~ be able to answer or to send forms, send links, send, ~uh,~ send them to the right person. So they'll ask, ~you know,~ somebody put in there, ~uh,~ about their benefits.
It'll say, "What country are you from?" Because we have employees in 12 countries. Yeah. And then it'll give them the specific information and, ~uh,~ any time of the day. And we, in HR, we were getting tons of questions. ~You know,~ "I want a, ~you know,~ I want a mortgage, and I need a letter of employment." Just things like that.
And so this allows us to, ~uh,~ do that without letting the AI do it, and we just manage the, the employee itself, the AI employee. The, the lady that was answering most of these questions before, her job changed because now she manages the AI employees.
Speaker: That's so great. And, ~uh, I mean,~ I imagine the, the lady that was doing those things, she probably didn't become someone in HR to spend her time generating verification letters or answering [00:23:00] those basic questions.
Yeah. So it's even a, it's even a great level up for her, I imagine. And, ~um,~ is this something that you, that you and your team fully built, or what was the level of, ~uh,~ partnership with, let's say, engineering or IT in order to get this off the ground?
Speaker 2: We did. We worked with a product manager, ~uh-~ Awesome ... to, to do it.
We didn't do it alone. It was, it was the first one that our company built, so it was probably a couple of years ago even now. I'd say maybe 18 months ago. Oh, wow. Yeah. So it was before we were even on Claude at that time. ~Um,~ so we really needed, we needed some help with it there.
Speaker: You were ahead of the curve.
Yeah. That's so great to hear. And, ~um,~ I'm curious to hear your thoughts on what made you want to give it a persona and call it an employee, ~um, and, uh,~ give it a name, ~uh,~ versus treat it as a tool. Was there anything around this is gonna drive further adoption or help people think differently about how they interact with it?
Speaker 2: They, we have names for all of them. ~Um,~ I think that it, it helps really. Yeah, personifying it just makes it that more friendly. Like, it has a personality. It can be really sassy back to people, and it's, I don't know. It's kind of funny. It, [00:24:00] it'll, ~uh,~ make jokes with people. And yeah, it just helps them in- to feel that it's not just a bot on a, on a website.
It's... And because- Yeah ... we're able to, ~um,~ jump into the chats as well. So if it has something that it can't answer, it will just add us and, and we can see that something's come up that we have to, to reach out to somebody. We have one for learning as well called CID- Uh-huh ... for the Citizen Developer Program.
We have Mira. ~Um,~ so we have a lot of, a lot of different
Speaker: ones. Are you thinking of keep creating, ~uh,~ let's call them digital twins of yourselves? 'Cause that seems like the next, next piece of the puzzle of like, "Hey, what would Jean say to this?" Yeah.~ Uh,~ like, "CID is telling me this stuff, but what would Jean say?"
Is that the next phase of development, or are you kind of looking at other areas, ~um,~ to, to build out?
Speaker 2: We are, we do have digital twins, ~uh,~ from one of our... We actually are doing a, a thing on it tomorrow night for our Ideas on Tap event. Mm. And we're talking about digital twins, so you can... ~You know,~ when I, if my...
Our CEO has one, so if I call his phone, the [00:25:00] digital twin will reply to me. And, ~uh,~ you can ask it anything. It's really good for, for authors and things like that because they can, people can ask anything about your book, and it can just respond. ~Um,~ so we do do that. Right. But I think the next phase for us is getting everybody on their own, having their own AI operating system.
So- Mm-hmm ... it's something that, ~uh,~ the, they'll interact with every day, and it'll help them. As it builds over time, it'll help them with all their workflows. And the AI OS will talk to a larger information intelligence layer that the company has. Have you heard about this idea of the graph- Yeah ... the brain- Yeah
of the company? ~Uh,~ so I, we're, we're looking into that, of how we- Consolidate all of our data into one place. That's the biggest thing, ~you know.~ AI's only as good as the information it can get access to. And when it's living- Yeah ... in people's heads and we, ~you know-~ ... in our thoughts, doesn't help.
Speaker: Yeah. We're seeing, we're seeing interesting things, ~um,~ across the different teams that we speak with where they have a new challenge where [00:26:00] people are creating their own agents.
And let's say they're using Claude, ~um,~ which is a one-to-one personal agent. ~Um,~ but then they might be creating skills, ~um,~ or they might be using files that are really useful. And now the new challenge is how do we make those accessible, and how do we make those available to the rest of the team, so we can then multiply their impact and make sure- Sure
that you share those learnings as, as they come through. And it sounds like- Yeah ... you guys have cracked it, ~uh,~ in terms of having the billboard, in terms of having a, a shareable system which is built internally that isn't dependent on Claude. Do I have that right?
Speaker 2: Yes, yes.
Speaker: Yeah. We- And what did it take to build that?
Speaker 2: Yeah, they can go... It took a, a couple weeks to build it, and she wasn't able to do it just with Claude. She had to use the help of a developer, ~uh,~ for some of it- Mm-hmm ... in IT. And, ~uh,~ it's really helped for that sprawl and to make sure that we can see what skills somebody's employee has or AI employee has and- Mm-hmm
~um,~ and build those, copy them.
Speaker: Yeah. Mm-hmm. So it, it sounds like actually as a [00:27:00] team, ~um,~ since you built a chatbot two years ago, and as a company, you're, you're quite far ahead in the AI journey compared to, ~uh,~ a lot of other folks. ~Um, I know before we started, um, recording, I think you also mentioned that sometimes you might also feel behind, but, but from what you're saying, uh, it sounds like you're, you're really pushing the, the boundaries here, which is awesome to hear.~
There are a lot of folks who are not quite there yet, and for folks that are listening, is there anything that you would wanna share with them as one piece of advice if they're thinking about, ~uh,~ experimenting with AI, particularly improving processes, about what they need to think about or where should they start?
Speaker 2: I think that you have to... It's, it's a tool that you really have to experiment with to, to learn. So I think you just have to jump in-
Speaker 3: Yeah ...
Speaker 2: and share. You know how I said we, we talk about it relentlessly. Yeah. Our CEO, we laugh about how many times he says AI in every single meeting. But you really just need to jump in.
You just, you need to start playing with the tools. You can, you can even say to it, "I don't know how to use this-" Yeah ... "and I don't know what I'm doing, and treat me like I'm, ~you know,~ 10 years old." ~Uh,~ sometimes if it, if Claude answers too [00:28:00] much, I can say, "Can you just an- ask me one thing at a time?" And it'll, it'll really...
It's amazing what it can do. So I think if you're feeling behind, we all are, so just know that. Yeah. And, ~um,~ there's... You have to just jump in and start learning.
Speaker: All right. Jean, thank you so much for joining us on the WorkOps podcast. ~Uh,~ I have a feeling that people are gonna listen to this, and then they're gonna wanna reach out and learn your secrets in terms of how you're driving AI enablement across the business.
~Um,~ is LinkedIn the right place to, to connect with you?
Speaker 2: Yes, for sure. Amazing. Reach out to me on LinkedIn. I'd love to show them our billboard and, and, ~uh,~ bring the person- Amazing ... who actually built it to talk more about how it was done. ~Um,~ yeah, anytime. LinkedIn works great. That's awesome.
Speaker: Thank you, Jean.
And to everyone listening, we'll catch you on the next one.
Speaker 2: Yeah, thanks for having me. This was great.