Charlotte Ward: 0:12
Hello and welcome to episode three hundred and thirteen of the Customer Support Leaders Podcast. I'm Charlotte Ward. Today, welcome Italo Belandria, talking about building with AI and bringing the team with you. I'd like to welcome to the podcast today, Italo Belandria. Italo, it's lovely to have you on the podcast for the first time. Thank you so much for joining me.
Italo Belandria: 0:41
Thank you, Charlo. Thank you. It's a pleasure for me to join.
Charlotte Ward: 0:45
Yeah, and and I know we had a chat a couple of weeks ago now, and uh I think we found a lot of common ground on uh the topic that we're talking about tonight. But before we dig into that, see tonight it's because it's it's evening for me and daytime for you, which will give hopefully the audience some some indication of where we are in the world, but but you can you can be a bit more specific for them. Would you please just introduce yourself?
Italo Belandria: 1:08
Yes, as you mentioned, my name is Italo Bellandria. I'm originally from Venezuela. Um, and just just sometimes I don't know why, but with my accent, I say Venezuela, and people here in the US hear Minnesota. Oh, really? Yeah, but I said no, Venezuela is warm, it's hot, it's sunny. It's not cold like Venezuela. So yeah, from Venezuela. Uh grew up there, went to college there, then I moved to Costa Rica uh to work in a project there with a friend, and then another friend invited me to work uh in the United States. So I had the chance to to past through Costa Rica for a few years. It was beautiful. I miss it. Uh it's an incredible place to live. Uh, but yes, now I'm here in Atlanta um working at Ringover as the head of customers. So I oversees the customer success, customer support uh for all the Americas. Um I have the privilege to be in Ringover for the past three years, almost four. And I have seen the growth, you know, from just a few people in the office for now having almost uh 40 people here in the in the US side.
Charlotte Ward: 2:13
Wow, wow, yeah, yeah, yeah. Changing times indeed. Um, yeah. Um gosh, what some lovely places that you mentioned there. I'm very jealous of the geographical kind of uh progression you've been on. Um yeah, uh I I've never been to Venezuela or Costa Rica, but they're definitely both on the list.
Italo Belandria: 2:32
Um, definitely like one of the things I love there is like an eternal summer, so you can go to the beach any time of the year. Yeah. So now live in the forest stations of of course I enjoy it, but you know, at the end of summer, I'm like, it's too hot. I want I want this to go. It's winter. At the end of winter, I'm like, this is too cold, and this I need this to go.
Charlotte Ward: 2:52
Yeah, place with seasons will do that to you. Come on. Have you ever been to the UK Italo?
Italo Belandria: 2:58
I have not. Uh I think the closest one has been. I mean, I have been in Portugal, South uh Spain and France. So I've been around the UK, but I have a cousin living uh not in the well in the United Kingdom in in Dublin. But she was like, you have to go to London one day.
Charlotte Ward: 3:16
Oh, okay. Well, you've been you've been close enough to get an appreciation of the difference in weather we're talking about here. So when you so when you're talking about the eternal summer and things like that, like I can fully buy into that dream. Um, I definitely don't experience it here. That's all I can say. Um, so so what are we talking about today?
Italo Belandria: 3:36
Yeah, so I am uh I'm not a technical person, I'm not a developer. I'm uh uh my dad used to be a developer, he always was like, Hey, you should learn how to develop, and I was like, No, I hate that. And now with this AI uh world that we're living, I'm now I'm like, man, I should have listened to to my dad to learn how to develop. Um, but one thing I have experiencing a lot is with these new tools that are available literally for everybody, is that you can refine how your operation runs with with AI. And and this is kind of like it's gonna be probably trial for I mean, so it's like okay, I have heard about AI all the time, you know, it's very it's a hot hot word going out, uh going around. But something that has helped me redefine our operations is just being able to communicate, not only communicate, because I can communicate, but to prototype and to show, hey, this is what I actually need. This is what I actually uh need from the technical team, from the dev team, um without just saying words, but actually putting in action, actually giving like this is how it should look like. Um and I think that's something that a lot of operational people uh in our in a world of support is like we're missing is like, hey, we have the idea, we have the strategy, I don't know how to communicate this to our technical team to develop it. And of course, it's not something that is gonna go to Google and say, hey, do this and that's it. Like you have to put the effort on this. I've been, I mean, using AI tools for almost a year and a half, uh, as I always tell my team to try to push my technical team into learning more. I'm like, hey, January 2025, uh, 5th, so last year, I what I didn't know, I didn't know anything about endpoints, webhooks, any of anything of the technical stuff. But I put myself out there, I started experimenting, I created many tools that don't work because again, I don't have the background for that. But I exposed myself to the tools, I exposed myself to learn how they work, and now I can put stuff to work that when I show one of the technical teams, hey, I developed this for my team, this workflow. Can you guys make it actually enterprise? Can you guys actually make it like scalable? Yeah, and they're like, Oh, this is pretty good. Like, how long it took you? I'm like, well, like four hours, and they're like, Okay, this is not normal. So that's the part I'm very passionate right now, is helping the team members that the leaders that are taking the operations on the day-to-day say, Hey, you can use AI not only to help you write a better email, or not to just help you like let me review a ticket because I don't want to read, you know, back and forth 10 10 emails. It's just outside that there is so much that AI can help you with.
Charlotte Ward: 6:27
Yeah, yeah, yeah, yeah. Yeah. I couldn't agree more actually. And I think there's some interesting things about the changing dynamics of different how different functions in a business relate to each other here that we should dig into. But you know, what immediately springs to mind is like from the operational front, I I I fully agree, like the speed at which you can try something out and then throw it away, both whether you're just thinking about a workflow or or something like quite self-contained in the team, um, to being able to explain that thing more visually because a lot of humans are much more visual kind of learners or or um connect better to visuals rather than words. Like I think that's that's very real and very um uh like it's a it's a it's kind of a superpower, isn't it? It enables you to move much faster through the early stages of kind of definition and like like let's just get this out there and give you something like concrete to talk over. Um I think that is definitely true of ops as well as product and other things. The interesting thing to me, first of all, is that you immediately kind of said, I can prototype this thing, I can get it in front of the devs or in front of product, and they go, Oh, this is great, like let's let's take it further. The thing that historically, particularly engineers in my experience, and well, and no, that's unfair, product people too, really historically have not liked is when we try and find the solution for them. Uh, you know, and so when you say, like, customers are hitting this problem, I think we should do XYZ. I in my experience across many organizations, um, the response is often something in the ballpark of, well, like outright rejection, please don't tell me my job, or or or more circumspectly, you know, uh more considerate considered um kind of responses like, um, well, I'm not sure that's the right way to solve this, you know, those kind of conversations. So it's interesting that you're I I'm I'm assuming it's some of the time, not all of the time, but like they're they're quite happy to engage with this prototyping flow where you show more, show more than tell.
Italo Belandria: 8:42
Yeah, and I and I think that's the key word is the prototype. Yeah, it's not the end product, it's not the end idea. Because as I mentioned, like I created many tools that it worked, but as soon as I put a user, as soon as I put something extra, boom, it broke. It was like, okay, it's bro, it's broken now, I cannot use it. I have to like reverse so many stuff because there are still so many technical things that I still don't know that when I go to the technical team, and this is the part that at least for me growing up with my dad being a developer, my mom being a lawyer, very social person, very outspoken person. My dad was more an introvert. I kind of have like I will say the best of both worlds because I kind of understand how the developer mind works, I understand how the social brain works because that I'm more social than than than than introvert. So I try to go into like, hey, I don't know what I don't know, but this is the idea I have. How can you make it work? Yeah, and I put that into them, and this is kind of like in our in our side of customer is that touch that we have with the client that hey, we cannot just be aggressive on like hey, this is our terms, XYZ, or hey, you did this wrong, XYC. We have to like be very polite, yeah, very kind. I try to keep that mind that I have with the customer, with our internal teams, right?
Charlotte Ward: 10:09
Right.
Italo Belandria: 10:09
Very polite. Hey, I'm having this idea, I prototype this during the weekend. What do you think? And that takes kind of like another view on their side, of course, relationship. If you don't have a relationship with them, as you mentioned, and you go, Hey, I think you should be doing your job in a different way, it's like you don't know how to do my job, don't tell me how to do it.
Charlotte Ward: 10:31
Yeah, yeah, yeah.
Italo Belandria: 10:32
It's a mix of those things.
Charlotte Ward: 10:34
I think it's it's really interesting that you described yourself as kind of you know, uh a bit of both introvert and extrovert. I think that's quite typical for support people. Like, I think you can't be in support and not know how to relate to people. Um, but uh also, you know, be like we have to think on our toes a lot. So be willing to experiment, be willing to try things out, be willing for them to be rejected or at least not to work. Like that's just that's just a the life cycle of a ticket often in support, isn't it? Never mind, like this whole idea that you might be building towards operationally or or to carry an idea to product or anything else. So that kind of split personality, I think, is quite quite uh typical in support, much more so than in say engineering, where they do deep dive, they do see you know see a problem through like beginning to end, um, in in the long form.
Italo Belandria: 11:32
Yeah, and and for example, one of the things as well is, and and this is a part of the operations, kind of like bringing AI into actions on your operation, is that when I sit down to do tests, because I still love getting into tickets, I still love connecting with clients, even though that we have a team doing that. Uh, whenever we have an update, whenever we ship something new, I like to sit down and test everything. And as I mentioned, I'm an outspoken person, I'm an extra extrovert, so I gotta talk to make my brain going. And I literally I just bring our AI agent, the empower tool that we have, it's called Empower within Ringover. I bring it to my video call, I put it to record, and I start doing my tests, and I'm just talking everything that I'm doing. I'm doing this, I'm testing this, I'm doing this, I'm testing that. So by the end of the uh at the end of the time uh of the that kind of session that I have with myself, I go back to the agent and say, Hey, this is what is what I was doing. I need you to give me the results of my test because as I would I'm testing these settings, I'm testing this setting, this is the results, I'm testing this, I'm testing this, this is the result. And then I go back to that, I send it back to the technical team, say, Hey, these are my results. Now we can build the documentation that we need to provide our team so to be able to support. Before you will have to like, you know, sit down, write notes, get an Excel sheet, and doing all that stuff, take you 45 minutes, two hours to do that. Literally, my last test lasted eight minutes.
Charlotte Ward: 13:02
Yes, yeah.
Italo Belandria: 13:04
Because all that note taking, all that process operation was just done by AI on the on the back end, and you say, Hey, just I need you to provide me this information, of course. As always, I review the data, I review what it gives me.
Charlotte Ward: 13:18
We validate, we validate, yeah, yeah, yeah.
Italo Belandria: 13:21
Validate that data, but for me, it was like in 15 minutes between the eight minutes that was talking, two minutes of the AI processing, my notion page, and then three to five minutes me reading the documentation in 15 minutes, 20 minutes, I was already giving a feedback back to the team. So, hey, this is what I found. I think these are the tweaks we need to do. I think this is how the client is going to use this tool. This is the lingo, the language we need to put in the in the in the UI for the agent to do that. Yeah, again, something that will take me two, three hours of my day to be 20 minutes, and now I have you know a bunch of time ready to use on something else.
Charlotte Ward: 13:59
Yeah, yeah, yeah, yeah. Yeah, it's a game changer, isn't it? It's a game changer. So you're talking primarily here about product then, but I think we sort of touched on in early on about how this is sort of this a lot of the same principles apply to operations, and and I suppose particularly for us, that means customer operations, it means um like customer um touch points, right? And and how we can influence those, what we can do leading up to and and and feeding back from those those interactions. Um, do you do you take the same approach of like this kind of prototyping, try something out? Because it feels, I always think like when you when you're doing something in in an area where it might impact the customer experience, first of all, take an extra beat on it. Um it's all right having those internal conversations and and like prototyping really quickly and experimenting, but if you're doing something that's likely to have like touch a customer surface somewhere, take an extra minute on it more, you know, and then and then like how what does iteration look like? What does prototyping and iteration look like there?
Italo Belandria: 15:12
No, that's great. Yeah, we as a company, we definitely like my tools are not shaped to the clients. I have I have done prototyping that the team has taken, and it's like, oh, this is good. Let's make it client approved, if we call it like that. Yeah, because like we don't trust this guy that don't know what type of code is behind this. Um, so that's very, yeah, what you mentioned is very important. It's like what are the things that we are doing internally, what are the things we're doing externally? Or even things that we are doing locally, like only works on that computer. And what are the things that work on the cloud?
Italo Belandria: 15:45
Um, so there are many, like because we are very, I mean, on we are on the telecom side, it's very delicate, the data, the calls, the outdoor, all that. So all that stuff that we do prototype, we do it in-house. We even have our own LLM, so we can do it locally cheaper. But the things, for example, with I have uh uh experience with a client, great partner has been with us for like uh almost two years, a little bit over two years. And he emailed me, he was like, Hey Italo, I have a concern. I don't know why the data that the ticketing system, a third-party ticketing system that you we use, is telling me that the average ticket uh resolution is 28 days. And he even tell me, like, I know you guys work faster than that, but this is the data I have. So I'm a little concerned because we are, you know, every year we go through a list of things that we need to change or we need to keep. And this is the data where he's coming out of Ringover. Can you can you help me out? And it was around like 200 something tickets, which the majority were super simple tickets like configuration, stuff like that. So I was like, well, I don't have the time to sit down and do 200 something tickets if I want to do it in the next you know couple days. Um I put I connected my account with Claude. We the we created on our own NCP with this technical uh with this ticketing system. And the system went in and looked at every single event of the ticket whenever an agent replied, change of status, internal notes, everything. And the conclusion was that the we have an automation that after 20 days of the ticket being sold, it will close. Then there's no modification else to the ticket, anything else, but the third party company on the client side, it shows creation date and last update. Right. So in so at that point, of course, the client's saying, Well, the my you know, my creation was January 1st, but the last update is January 28th. It took 28 days to close. But the reality is the ticket took three hours in the back and forward and it got solved that same day, but the automation updated the ticket 28 days later. So for me, that operation to just plug in, give the problem, hey, this I first went to one ticket and I said, Hey, I think this is the specific issue we are seeing. Investigate this on this other 200-300 tickets. And within like 25 minutes, it took a while. It wasn't like you know, Chat GPT or o'clock just giving you an answer, it was a long analysis. It came back to like, hey, no, actually, your response, you your closing race between it, your media and it's like it was like six hours, you average it's like eight hours, but here is all the data, and then I pass it to the to the guy. Of course, I review everything. I mean, I reviewed like a sample of like 20 tickets. I pass it to to our partner, and he was like, Oh, yeah, this makes so much sense because this is the experience that we have been feeling, but the data that we had was telling us something different. But your your point is now it's great. So for me, it was like, hey, this is an operation, this is something I have to do. Client facing, of course, the tool was not used by the client, but I I was able to create it, use it, and been able to reply back to the client with the real data. And I was like, okay, this was this was great. Like a bad prototype saved me, saved me the day, and thus now, whenever we need to analyze a specific account or something, we can use that tool internally.
Charlotte Ward: 19:18
Yeah, yeah, yeah. That that's awesome. I I um like I have so many little stories like that as well. Sometimes it's just this like a simple thing, like a bit of validating some numbers or pulling numbers in a different way, or um, you know, even just creating collateral or something that you just know is is faster, more correct, like easier to produce or or has validated some perception or something, like whichever way you take it, something that actually has an impact on a customer is just where it begins to really show value, I think. Um, and that includes, to your point earlier, the product feedback as well, you know, the things that you can do for customers by going via product. Um how do you um how do the rest of your team sit in all of this? Because because you're there, you're you you're um, it sounds like you're you're constantly tinkering with AI and like generating like stuff, stuff for product. Where how do the how do the team kind of fit into this? Are they experimenting in the same way? Are you are you leading the charge or or how's that how's that working?
Italo Belandria: 20:29
Yeah, that's a great, that's a great question. I think that's the hardest part as a leader is like how you can move your team to start using this outside their time. Because, you know, if you have been in the business for a while and it's like the downtime that we have sometimes is like minimum. Uh, I even like most of the time I just eat my
Italo Belandria: 20:50
lunch here at desk, well, you know, meetings and stuff.
Charlotte Ward: 20:53
Yeah.
Italo Belandria: 20:53
So one of the things I tell the team almost every week is I want to know what are you doing with AI outside work. If you're doing a personal project, if you're doing something for yourself, even if you're doing a side gig and you're trying to you know to sell some sort of service using AI where you live. Like I want to know what are you doing. Yeah, and for example, we had this specific week, we have one of our um agents say, Hey, I want to show you a tool that I developed it. I have a local LLM, very technical, like I'm way more technical than me. We have a local LLM, I have a local host in my computer, so everything still is local. We whenever we have a specific issue, I just send this command to the to the system I created, and it captures the data, but not only capture the data, it explains the data to me. So instead of the the human going and see all these numbers for the routing of the calls and all the interactions that we have, the system goes, analyzes that and provides the the the the result, not the resolution, but the explanation to the end. I was like, this is great. I show it to one of the co-founders, I show it to the chief customer officer, and they both were like, we need to have this internally for everybody on the team. And that's what I'm trying to motivate the team. It's like, what are those things that are like, oh man, I wish we had this. I wish I had something that will help me on this. It's not like it's not gonna change maybe the world, but if we fix this issue that I'm encountering every day, 20 minutes a day, yeah, it's gonna make a compound difference.
Charlotte Ward: 22:33
Yeah.
Italo Belandria: 22:34
You and your team. So that's how I'm trying is like not only telling them and showing them what I'm doing. Hey, I build this for you guys. Hey, I build this tracking system that connects to Slack, that does this, that sends this automation. I ask them for feedback for the stuff I built. Hey, what we should do, and I put a little box, like you can they can click on it, they can send feedback, I receive the feedback, I I develop on that. Um, and I think no, as I mentioned, not only saying it, but doing it, I think it speaks volumes. And now after months, I'm seeing that kind of return. It's like, oh man, this this guy is now doing something, this other one is doing something. Uh, but again, it's hey, what are you doing outside work that you're passionate about that you're doing? This is what I'm doing, and let me know how I can help.
Charlotte Ward: 23:22
Yeah, yeah, yeah. I think it, I think it to your point about it being months, I think it can be a slow burn to get people to feel confident sharing at the same level, even that you're sharing, right? I I think that as a leader, you kind of get you step uh I and I'm I do the same, like you sort of you have a bit of a vision that you want to build against anyway. And so what has when you think about what AI has done for you as a leader, like it's enabled you to just accelerate a bunch of stuff that you kind of have agency over a lot of the time, you know, your own operations and things. And so um the the idea that uh you can that you're basically empowered to do a lot of stuff that you might otherwise have had to slow roll or rely on vendor tooling or whatever to to do is kind of is kind of uh you know, if you're if you're a one of those leaders that's adopted AI to that level, then then you're gonna run at it even more. Like it's just you're gonna run at it more and more every day and just like keep outputting. Like I and I think the slight danger is like as the leader of the team, it can seem like you're building for the system, and the team then can kind of like get a bit stuck of like, well, Italo is doing all of the, like, he's just like creating all of the tooling, he's doing all of the things, and I get I sometimes feel the same about me, like Charles just creating this whole ecosystem. First of all, I don't know if I should touch it, if I can touch it, if I can add to it, if I can give her feedback on it, your feedback point's a really important one. Um, but like, where's the space for me? Like you become you you like the the kind of output levels are so accelerated, it I think it can almost like shut the team down if you're not careful.
Italo Belandria: 25:20
And I and I think you hit a really good point because with this specific team that I'm that that I'm working with right now, that I love the team that we have built, they come from a place that their voice is not hurt. Like and I have been working for this for months showing that hey, this is the culture that I want our team to have here at Ringover. Doesn't matter where you're located, you could be in the US, Spain, UK, Colombia, India, uh, France, your voice matters. And that's that's one of the first things I have I started noticing with this uh team that we started hiding and growing is that they come from
Italo Belandria: 26:05
a place that they were working for these big companies, but they were just put in a place like, hey, this is your job, that's your box, stay there. And when I started bringing them here, I said, Hey, what do you think about this? They were like, as you mentioned, they they were kind of scared of like giving even feedback, providing like, what can I say? Should I say that this is not working correctly, that we should do something? And it took me a little bit to to realize because thankfully I come from organizations with feedback when open communication with with leadership is always open. There is no like you gotta you gotta stop, you gotta do this. Um has at least for me, has made me feel like every single company is like this. So when I started hiring these people, I was like, hey Eduardo, about this, they're like, Oh, oh, well, I think about this. I'm like, no, no, no, give me your real feedback. And I started kind of learning more, uh, specifically Eduardo was like, well, the thing is when in previous companies, this is how we were told, is like you do the job and that's it. You even if you provide feedback, that feedback goes straight to the trash. So it's kind of new for for me to exp what I'm experiencing here that and and it may not be the the the I don't know on you know big corporations, but like even our CEO. If somebody has an answer, uh question and he has the answer, he will just jump in and send a message, hey, this is the answer, or hey, go ask this person, hey, whoever jump in on this. So that type of communication for them was not normal. So I think that was, and this is again outside AI, this is just full human relationship. Yeah, this is the part that when we jump with AI, we oh AI can do everything. It's like, yes, it can do a lot, but there is a lot of human part interaction in our in our work that we still have to be very uh pay attention a lot. And that was the part I kind of came into a realization. It's like, hey, I have to empower them, I have to give in the the the the the I have to lay down the rules, say hey, you can actually speak here. You voice matters, your voice actually is needed in this company. And when I started seeing that first, it's kind of like they get more trust, confidence within the organization to say, Oh, can I do this? Hey, I thought about this. Um, but I think that's the root of everything is first giving that trust.
Charlotte Ward: 28:34
Yeah, yeah.
Italo Belandria: 28:36
Hey, because you provide feedback about something in the product that it may not be a hundred percent. That doesn't mean that it's something on you, it means something on the product, and we need to fix that, and we actually need that point of view from you.
Charlotte Ward: 28:48
Yeah, yeah, yeah.
Italo Belandria: 28:49
That's a part that we can easily kind of forget because we get into this AI world, but at the end of the day, we're still working with humans, we still have to work with them, and and I and I hope for a world that we are all still in the loop, um, because it's part of something like hey, we are growing together when we're working together.
Charlotte Ward: 29:07
Yeah, and uh, you know, and and you're absolutely right. This isn't about AI, it's about humans, it's about creating that trust and safe space. I think I think the thing that you know building at this speed does is just magnify that. And um what I've seen is teams go through cycles of like wanting to share a lot, and then suddenly it all gets a bit overwhelming. And I think all of the builders on the team just kind of retreat to their own space for a little while. And I think I think the trick is, and I haven't quite haven't quite figured out the solution to this, but but the I think the right thing to do is is to ask the question, how do you maintain the high points so that people constantly feel that it's safe to share, and that there is, to your point, like space for their voice as well among all the stuff. You're building among all the stuff, like the other big adopters in your team are building. And because otherwise, people will retreat, they'll retreat to their local machine, they'll retreat to their local projects and skill skills they've built and private pages and things like that. And before you know it, you've got people building in parallel, and even worse, people building it like divergently, like going off in different directions, trying to solve the same problem, and then that's just a different sort of inefficiency, isn't
Charlotte Ward: 30:32
it?
Italo Belandria: 30:32
And and and that, and that that specific point that you make is so easy to get in in that bad route, because then everybody's building on their own, everybody's building their own stack, their own idea without that internal communication. And that's the part, I think, on the trust, on like, hey, what are you doing? How can we work together? And and with this tool that I created internally to like do like all the spreadsheets we were having, kind of keeping them together. Hey, we have one system, and that's the part I'm like always asking them, hey, what else can we have? What else can we do? Uh, not for me to build, but like to one, give them the idea like, hey, what what can you what are you thinking that it could be possible? Even when it's something like super technical of what what this guy did, I tell, hey, build the prototype, let's see how it works, and from there we take it from there.
Charlotte Ward: 31:30
Yeah, yeah.
Italo Belandria: 31:31
I want to give them the the space to to kind of wonder a little bit, to wonder where they can go, wonder what they can they can do. And then once we see something, it's like, okay, now that you have built something that is is productive, it's good, let's now build it the the way integrated with our with our ecosystem. Yeah, I think you hit on a great point is when you're building independently, you can you need to always kind of do like a check-in of like, okay, I build this, it works, how can I bring it into my ecosystem where my team is building, and right now there is a a big movement on companies uh doing hiring that most of hirings are external, like okay, go and deploy for the client, go on and doing this. But it's an internal hiring of doing this job, of going into the positions and say, Okay, support. What are the processes that you know it takes you time during the day that we can automate? And then you get a problem that person is in charge of developing that tool that integrates to the ecosystem of the company, and then that you have somebody for sales, somebody for customer success, you have somebody for even the developers in order for the other teams to connect with the developers. And because for I will say a year and a half, almost two, people have been building on their own, and we're getting to that road of okay, great, we have great tools, but they don't talk to each other. Yes, yeah, interconnect to each other. Now we need our own ecosystem of these mini tools that help the entire team, but we need to bring them together.
Charlotte Ward: 33:02
Yeah, and and that can only happen if people are continually open about the problems they're solving and what and how they're solving them as well as why why they you know why why they need to be part of that ecosystem, why they need to connect. And uh yeah, you're right, it's it's a role that's uh it's then it's the new frontier, isn't it? It's not just building, it's connecting and making sure that all of these processes share the right data, the right arch artifacts, the right surfaces and the right handovers um efficiently as much as anything else.
Italo Belandria: 33:39
And that's and that's the that's the key.
Charlotte Ward: 33:42
Yeah, yeah, yeah. Um, Ito, thank you so much for joining me today. It's um it's been I mean, this started out as prototyping, and I think we ended up somewhere in the kind of human change management kind of ballpark, but um I I knew we would like all of these conversations around AI tend to like have to sweep the humans into there somewhere, like otherwise, what are we doing? Right. Um, thank you so much for joining me. Would you come back for another conversation another time?
Italo Belandria: 34:08
Oh yeah, definitely.
Charlotte Ward: 34:09
Perfect. Let's set that up. Thanks so much.
Italo Belandria: 34:12
Thank you, Charlotte.
Charlotte Ward: 34:14
That's it for today. Go to customersupportleaders.com forward slash three one three for the show notes, and I'll see you next time.
