How IBM Z Is Modernizing Mainframes with Skyla Loomis

And they absolutely need AI. Um, you And they absolutely need AI. Um, you know, if you're going to go and a lot of know, if you're going to go and a lot of know, if you're going to go and a lot of times they're very time sensitive. So, times they're very time sensitive. So, times they're very time sensitive. So, if you're going to go make a if you're going to go make a if you're going to go make a transaction, you want to catch that transaction, you want to catch that transaction, you want to catch that fraud at the moment that the transaction fraud at the moment that the transaction fraud at the moment that the transaction is happening, not 30 minutes or an hour is happening, not 30 minutes or an hour is happening, not 30 minutes or an hour later or even, you know, 30 seconds or later or even, you know, 30 seconds or later or even, you know, 30 seconds or 60 seconds later cuz by then you 60 seconds later cuz by then you 60 seconds later cuz by then you probably just had to let the transaction probably just had to let the transaction probably just had to let the transaction go because it took too long. And so, and go because it took too long. And so, and go because it took too long. And so, and once you let fraud go, it's basically a once you let fraud go, it's basically a once you let fraud go, it's basically a loss, right? Like it's just kind of a loss, right? Like it's just kind of a loss, right? Like it's just kind of a lot of banks look at it as the cost of lot of banks look at it as the cost of lot of banks look at it as the cost of doing business that you lose, you know, doing business that you lose, you know, doing business that you lose, you know, 8% of your revenue due to fraud in a 8% of your revenue due to fraud in a 8% of your revenue due to fraud in a year. year. year. Um, and that's a pretty high cost. And Um, and that's a pretty high cost. And Um, and that's a pretty high cost. And so, so, so, >> Hey friends, you probably knew that Text >> Hey friends, you probably knew that Text >> Hey friends, you probably knew that Text Control is a powerful library for Control is a powerful library for Control is a powerful library for document editing and PDF generation, but document editing and PDF generation, but document editing and PDF generation, but did you also know that they're a strong did you also know that they're a strong did you also know that they're a strong supporter of the developer community and supporter of the developer community and supporter of the developer community and it's part of their mission to build and it's part of their mission to build and it's part of their mission to build and support a strong community by being support a strong community by being support a strong community by being present, by listening to users, and by present, by listening to users, and by present, by listening to users, and by sharing knowledge at conferences across sharing knowledge at conferences across sharing knowledge at conferences across Europe and the United States. If you're Europe and the United States. If you're Europe and the United States. If you're heading to a conference soon, heading to a conference soon, heading to a conference soon, maybe check if Text Control will be maybe check if Text Control will be maybe check if Text Control will be there. Stop by and say hi. You'll find there. Stop by and say hi. You'll find there. Stop by and say hi. You'll find their full conference calendar at their full conference calendar at their full conference calendar at textcontrol.com.

textcontrol.com. textcontrol.com. That's t e x t control.com. Hi, I'm Scott Hanselman. This is another Hi, I'm Scott Hanselman. This is another episode of Hanselminutes. Today, I'm episode of Hanselminutes. Today, I'm episode of Hanselminutes. Today, I'm chatting with Skyla Loomis. She's a chatting with Skyla Loomis. She's a chatting with Skyla Loomis. She's a general manager of IBM Z software at general manager of IBM Z software at general manager of IBM Z software at IBM. How are you? IBM. How are you? IBM. How are you? >> I'm good. I'm good. Happy to be here. >> I'm good. I'm good. Happy to be here. >> I'm good. I'm good. Happy to be here. How are you? How are you? How are you? >> Yeah, thanks for hanging out. So, you've >> Yeah, thanks for hanging out. So, you've >> Yeah, thanks for hanging out. So, you've been at like IBM forever. This is really been at like IBM forever. This is really been at like IBM forever. This is really cool. I look at your LinkedIn. It is cool. I look at your LinkedIn. It is cool. I look at your LinkedIn. It is just filled with all kinds of just filled with all kinds of just filled with all kinds of experience. How do you get into like experience. How do you get into like experience. How do you get into like mainframe software? mainframe software? mainframe software? >> Yeah, you know, it's funny. You know, a >> Yeah, you know, it's funny. You know, a >> Yeah, you know, it's funny. You know, a lot of times you talk to someone who's lot of times you talk to someone who's lot of times you talk to someone who's been on the mainframe and they've been been on the mainframe and they've been been on the mainframe and they've been in the mainframe their entire career. in the mainframe their entire career. in the mainframe their entire career. Uh, that's not my story. Uh, that's not my story. Uh, that's not my story. Uh, you know, I I started out of college Uh, you know, I I started out of college Uh, you know, I I started out of college at IBM, bounced around at, you know, at IBM, bounced around at, you know, at IBM, bounced around at, you know, different parts of the tech stack, you different parts of the tech stack, you different parts of the tech stack, you know, mostly on distributed in the know, mostly on distributed in the know, mostly on distributed in the beginning, data, some mobile analytics, beginning, data, some mobile analytics, beginning, data, some mobile analytics, some cloud, early days of IBM cloud. And some cloud, early days of IBM cloud. And some cloud, early days of IBM cloud. And then, you know, I had this opportunity then, you know, I had this opportunity then, you know, I had this opportunity to uh, work on the mainframe and it's, to uh, work on the mainframe and it's, to uh, work on the mainframe and it's, you know, such a storied platform within you know, such a storied platform within you know, such a storied platform within IBM and so much meaning for our clients IBM and so much meaning for our clients IBM and so much meaning for our clients that it was really an exciting that it was really an exciting that it was really an exciting opportunity after you work on new stuff opportunity after you work on new stuff opportunity after you work on new stuff and you're always trying to get new and you're always trying to get new and you're always trying to get new clients, but it's also really refreshing clients, but it's also really refreshing clients, but it's also really refreshing to go to a platform where you have this to go to a platform where you have this to go to a platform where you have this rich history and these long-standing rich history and these long-standing rich history and these long-standing relationships with really important relationships with really important relationships with really important clients and you can make a difference, clients and you can make a difference, clients and you can make a difference, you know, for them in in in what they do you know, for them in in in what they do you know, for them in in in what they do and what they do for their clients. So, and what they do for their clients. So, and what they do for their clients. So, uh since then I've been about on the uh since then I've been about on the uh since then I've been about on the mainframe about 9 years or so and uh mainframe about 9 years or so and uh mainframe about 9 years or so and uh it's been been an exciting journey for it's been been an exciting journey for it's been been an exciting journey for me.

me. me. >> So, I'm I'm going to ask a couple of >> So, I'm I'm going to ask a couple of >> So, I'm I'm going to ask a couple of ignorant questions cuz it's been a while ignorant questions cuz it's been a while ignorant questions cuz it's been a while since I've done any mainframe work and since I've done any mainframe work and since I've done any mainframe work and when I did, it's it was invisible to me. when I did, it's it was invisible to me. when I did, it's it was invisible to me. I think one of the things that's I think one of the things that's I think one of the things that's interesting about the cloud and one of interesting about the cloud and one of interesting about the cloud and one of the things that's interesting about the the things that's interesting about the the things that's interesting about the mainframe is that people who work on mainframe is that people who work on mainframe is that people who work on them, whether they be a them, whether they be a them, whether they be a a young person just out of school who is a young person just out of school who is a young person just out of school who is working on the cloud or someone who's working on the cloud or someone who's working on the cloud or someone who's been around a minute who's working on been around a minute who's working on been around a minute who's working on the mainframe is in both instances, we the mainframe is in both instances, we the mainframe is in both instances, we may have never actually seen the may have never actually seen the may have never actually seen the machine. machine. machine. I was talking to a whole class of young I was talking to a whole class of young I was talking to a whole class of young people recently that just started at people recently that just started at people recently that just started at Microsoft and they were basically, you Microsoft and they were basically, you Microsoft and they were basically, you know, they don't know why the cloud know, they don't know why the cloud know, they don't know why the cloud existed. Like, what was the problem that existed. Like, what was the problem that existed. Like, what was the problem that was being solved was being solved was being solved for them has always existed. And in the for them has always existed. And in the for them has always existed. And in the old days, we used to visit the cloud. old days, we used to visit the cloud. old days, we used to visit the cloud. We'd take them out to a data center and We'd take them out to a data center and We'd take them out to a data center and it's like a Costco full of fridges. it's like a Costco full of fridges. it's like a Costco full of fridges. Like, this is a dumb question, but like, Like, this is a dumb question, but like, Like, this is a dumb question, but like, have you seen a mainframe? Do you see have you seen a mainframe? Do you see have you seen a mainframe? Do you see them anymore? Are they just in a cooler them anymore? Are they just in a cooler them anymore? Are they just in a cooler somewhere? somewhere? somewhere? >> Yeah, I know, absolutely. You know, we >> Yeah, I know, absolutely. You know, we >> Yeah, I know, absolutely. You know, we actually have some social media actually have some social media actually have some social media programs, hug your mainframe day and programs, hug your mainframe day and programs, hug your mainframe day and feel like at LinkedIn on those days, feel like at LinkedIn on those days, feel like at LinkedIn on those days, you'll see lots of people going around you'll see lots of people going around you'll see lots of people going around and and and hugging their mainframes in their data hugging their mainframes in their data hugging their mainframes in their data centers or where we have them. You know, centers or where we have them. You know, centers or where we have them. You know, certainly when we do launches, you know, certainly when we do launches, you know, certainly when we do launches, you know, the the box is certainly front and the the box is certainly front and the the box is certainly front and center and there's a lot of thought center and there's a lot of thought center and there's a lot of thought actually that goes into, if you believe actually that goes into, if you believe actually that goes into, if you believe it, the the design of the door it, the the design of the door it, the the design of the door and actually making it kind of a very, and actually making it kind of a very, and actually making it kind of a very, you know, very you know, very you know, very powerful, kind of impactful visual to I powerful, kind of impactful visual to I powerful, kind of impactful visual to I think represent what's behind what's think represent what's behind what's think represent what's behind what's behind that door.

behind that door. behind that door. >> Mhm. >> Mhm. >> Mhm. >> Now, do modern mainframes exist or are >> Now, do modern mainframes exist or are >> Now, do modern mainframes exist or are all all all are all mainframes legacy by definition are all mainframes legacy by definition are all mainframes legacy by definition or can I buy a new mainframe? or can I buy a new mainframe? or can I buy a new mainframe? >> Oh, well, you you can absolutely buy a >> Oh, well, you you can absolutely buy a >> Oh, well, you you can absolutely buy a new mainframe. new mainframe. new mainframe. Um, you know, I think it's funny. It is Um, you know, I think it's funny. It is Um, you know, I think it's funny. It is this perception that I mean there's and this perception that I mean there's and this perception that I mean there's and we often see these like super old we often see these like super old we often see these like super old pictures from, you know, the 1960s or pictures from, you know, the 1960s or pictures from, you know, the 1960s or 70s of these computers that filled an 70s of these computers that filled an 70s of these computers that filled an entire room and that's what people's entire room and that's what people's entire room and that's what people's perceptions of the mainframe are because perceptions of the mainframe are because perceptions of the mainframe are because as you said they don't necessarily go as you said they don't necessarily go as you said they don't necessarily go and see them. But, you know, the and see them. But, you know, the and see them. But, you know, the mainframe's kind of like a car. Sure, mainframe's kind of like a car. Sure, mainframe's kind of like a car. Sure, the car was created a long time ago, but the car was created a long time ago, but the car was created a long time ago, but you go buy a car today, it's nothing you go buy a car today, it's nothing you go buy a car today, it's nothing like the Ford Model T that you bought in like the Ford Model T that you bought in like the Ford Model T that you bought in the early 1900s. The same is true for a the early 1900s. The same is true for a the early 1900s. The same is true for a mainframe. It was invented, yes, in the mainframe. It was invented, yes, in the mainframe. It was invented, yes, in the 60s as like the first, you know, modern 60s as like the first, you know, modern 60s as like the first, you know, modern computing engine, but the mainframe of computing engine, but the mainframe of computing engine, but the mainframe of today is the most modern cutting-edge today is the most modern cutting-edge today is the most modern cutting-edge uh, compute stock that you can buy on uh, compute stock that you can buy on uh, compute stock that you can buy on the market. the market. the market. >> Yeah, I think that's an important thing >> Yeah, I think that's an important thing >> Yeah, I think that's an important thing to remember that, you know, I I think, to remember that, you know, I I think, to remember that, you know, I I think, you know, Ford Mustang and I think like you know, Ford Mustang and I think like you know, Ford Mustang and I think like a 60-year-old car and I'm sure they're a 60-year-old car and I'm sure they're a 60-year-old car and I'm sure they're beautiful, but I can buy a Ford Mustang beautiful, but I can buy a Ford Mustang beautiful, but I can buy a Ford Mustang today. And I think the thing that's most today. And I think the thing that's most today. And I think the thing that's most significant, even though IBM mainframes significant, even though IBM mainframes significant, even though IBM mainframes have been around since like '51, '52, is have been around since like '51, '52, is have been around since like '51, '52, is if I understand correctly, the Z in IBM if I understand correctly, the Z in IBM if I understand correctly, the Z in IBM Z stands for zero downtime. Is that Z stands for zero downtime. Is that Z stands for zero downtime. Is that true?

true? true? >> Well, the Z can, uh, you know, there's >> Well, the Z can, uh, you know, there's >> Well, the Z can, uh, you know, there's probably a lot of things the Z can stand probably a lot of things the Z can stand probably a lot of things the Z can stand for, but we do have, uh, one of our for, but we do have, uh, one of our for, but we do have, uh, one of our claim to fames is eight nines uh, you claim to fames is eight nines uh, you claim to fames is eight nines uh, you know, just inherently in the box and I know, just inherently in the box and I know, just inherently in the box and I don't think there's really much else don't think there's really much else don't think there's really much else that can compare to that. that can compare to that. that can compare to that. >> That That is, yeah, I would I can think >> That That is, yeah, I would I can think >> That That is, yeah, I would I can think about five nines being super about five nines being super about five nines being super challenging. challenging. challenging. Eight, I can't even conceive about. Eight, I can't even conceive about. Eight, I can't even conceive about. Like, what does that even mean? Like, a Like, what does that even mean? Like, a Like, what does that even mean? Like, a minute and a half every couple of years. minute and a half every couple of years. minute and a half every couple of years. >> Uh, yeah, I Yeah, I think even like I >> Uh, yeah, I Yeah, I think even like I >> Uh, yeah, I Yeah, I think even like I think it's like 300 milliseconds a year think it's like 300 milliseconds a year think it's like 300 milliseconds a year or something crazy like that, which, you or something crazy like that, which, you or something crazy like that, which, you know, turns out to know, turns out to know, turns out to ba- basically practically almost never. ba- basically practically almost never. ba- basically practically almost never. >> Uh-huh. >> Uh-huh. >> Uh-huh. And now by default they And now by default they And now by default they they run virtual virtualized, right? they run virtual virtualized, right? they run virtual virtualized, right? Everything is virtualization is required Everything is virtualization is required Everything is virtualization is required on on on on IBM. on IBM. on IBM. >> Yeah, I mean there's lots of ways that >> Yeah, I mean there's lots of ways that >> Yeah, I mean there's lots of ways that you can carve up the compute, right? And you can carve up the compute, right? And you can carve up the compute, right? And make it make it accessible. You know, make it make it accessible. You know, make it make it accessible. You know, you can run z/OS on on the platform, you you can run z/OS on on the platform, you you can run z/OS on on the platform, you can run Linux on the platform. Not can run Linux on the platform. Not can run Linux on the platform. Not everybody realizes that. So there's a everybody realizes that. So there's a everybody realizes that. So there's a lot of a lot of options for how you can lot of a lot of options for how you can lot of a lot of options for how you can leverage but you know, this highly leverage but you know, this highly leverage but you know, this highly resilient compute capacity that's you resilient compute capacity that's you resilient compute capacity that's you know, Yeah, it's really meant to be know, Yeah, it's really meant to be know, Yeah, it's really meant to be extremely optimized as like a full stack extremely optimized as like a full stack extremely optimized as like a full stack and run very dense and run very hot very and run very dense and run very hot very and run very dense and run very hot very reliably versus kind of the distributed reliably versus kind of the distributed reliably versus kind of the distributed scale-out model that you typically see scale-out model that you typically see scale-out model that you typically see in the cloud. This is really more of a in the cloud. This is really more of a in the cloud. This is really more of a scale-up kind of model.

scale-up kind of model. scale-up kind of model. >> That is a really interesting way to look >> That is a really interesting way to look >> That is a really interesting way to look at it. Like it is like a at it. Like it is like a at it. Like it is like a a cloud in and of itself, but to your a cloud in and of itself, but to your a cloud in and of itself, but to your point it's for big bursty batch heavy point it's for big bursty batch heavy point it's for big bursty batch heavy work and not little tiny HTTP get here work and not little tiny HTTP get here work and not little tiny HTTP get here and there kind of like work that like and there kind of like work that like and there kind of like work that like most modern cloud systems are doing as most modern cloud systems are doing as most modern cloud systems are doing as they're managing web servers. But do they're managing web servers. But do they're managing web servers. But do people run like a web server on do they people run like a web server on do they people run like a web server on do they treat a mainframe like a cloud or that's treat a mainframe like a cloud or that's treat a mainframe like a cloud or that's just simply not what they're for? just simply not what they're for? just simply not what they're for? >> Yeah, no absolutely. I mean >> Yeah, no absolutely. I mean >> Yeah, no absolutely. I mean yes, people of course run batch, but yes, people of course run batch, but yes, people of course run batch, but there's you know, a ton of online there's you know, a ton of online there's you know, a ton of online transaction processing. That's really a transaction processing. That's really a transaction processing. That's really a lot of the bread and butter lot of the bread and butter lot of the bread and butter of of what the systems are used for of of what the systems are used for of of what the systems are used for where speed where speed where speed you know, with asset properties, low you know, with asset properties, low you know, with asset properties, low latency is all super super critical and latency is all super super critical and latency is all super super critical and so so so you know, we absolutely can run web you know, we absolutely can run web you know, we absolutely can run web servers, we run databases, you know, all servers, we run databases, you know, all servers, we run databases, you know, all all the same things you run everywhere all the same things you run everywhere all the same things you run everywhere else you know, you can you can run on else you know, you can you can run on else you know, you can you can run on the on the Z platform also. the on the Z platform also. the on the Z platform also. >> So then when would I pick it though? I >> So then when would I pick it though? I >> So then when would I pick it though? I think the part that would be confusing think the part that would be confusing think the part that would be confusing for folks that are maybe listening is for folks that are maybe listening is for folks that are maybe listening is that everyone's so used to just throwing that everyone's so used to just throwing that everyone's so used to just throwing it in a cloud one of the many clouds and it in a cloud one of the many clouds and it in a cloud one of the many clouds and I don't know if I would if I were faced I don't know if I would if I were faced I don't know if I would if I were faced with a problem, how would I decide, you with a problem, how would I decide, you with a problem, how would I decide, you know, this is an IBM Z16 sized problem?

know, this is an IBM Z16 sized problem? know, this is an IBM Z16 sized problem? >> Yeah, so you know, we talk a lot about >> Yeah, so you know, we talk a lot about >> Yeah, so you know, we talk a lot about fit for purpose workload choices and you fit for purpose workload choices and you fit for purpose workload choices and you know, like IBM, you know, your your Z know, like IBM, you know, your your Z know, like IBM, you know, your your Z mainframe is is kind of like the race mainframe is is kind of like the race mainframe is is kind of like the race car. So you don't you don't need it for car. So you don't you don't need it for car. So you don't you don't need it for every application for sure. If you're every application for sure. If you're every application for sure. If you're going to have going to have going to have something that is you know, maybe something that is you know, maybe something that is you know, maybe smaller volumes, smaller volumes, smaller volumes, maybe perhaps more experimental, maybe perhaps more experimental, maybe perhaps more experimental, you know, you may not especially if you you know, you may not especially if you you know, you may not especially if you don't already have a platform, if you don't already have a platform, if you don't already have a platform, if you don't already have Z, you know, you may don't already have Z, you know, you may don't already have Z, you know, you may not choose to put it there. But you not choose to put it there. But you not choose to put it there. But you know, the thing about the Z platform know, the thing about the Z platform know, the thing about the Z platform actually is it gets it gets better and actually is it gets it gets better and actually is it gets it gets better and gets even more cost effective the more gets even more cost effective the more gets even more cost effective the more you put on it. All right, and because it you put on it. All right, and because it you put on it. All right, and because it can run so densely and so hot, a lot of can run so densely and so hot, a lot of can run so densely and so hot, a lot of our clients run their boxes extremely our clients run their boxes extremely our clients run their boxes extremely hot. And so you know, thinking about hot. And so you know, thinking about hot. And so you know, thinking about those like core transactional workloads those like core transactional workloads those like core transactional workloads where you really need the resiliency, where you really need the resiliency, where you really need the resiliency, you know, you effectively your brand you know, you effectively your brand you know, you effectively your brand trust is going to be at risk if this trust is going to be at risk if this trust is going to be at risk if this goes down, where you want to access to goes down, where you want to access to goes down, where you want to access to perhaps the data and the data gravity perhaps the data and the data gravity perhaps the data and the data gravity that you have in the platform already, that you have in the platform already, that you have in the platform already, you know, a lot of times, you know, why you know, a lot of times, you know, why you know, a lot of times, you know, why would you make a copy and introduce would you make a copy and introduce would you make a copy and introduce security risks, you know, costs of security risks, you know, costs of security risks, you know, costs of you know, storage costs, movement costs, you know, storage costs, movement costs, you know, storage costs, movement costs, you know, and all of those challenges, you know, and all of those challenges, you know, and all of those challenges, you know, the the compliance costs and you know, the the compliance costs and you know, the the compliance costs and then managing this data somewhere else then managing this data somewhere else then managing this data somewhere else when you've got it on the platform and when you've got it on the platform and when you've got it on the platform and just being able to really leverage it.

just being able to really leverage it. just being able to really leverage it. So there's really kind of a gravity that So there's really kind of a gravity that So there's really kind of a gravity that I think forms around these platforms I think forms around these platforms I think forms around these platforms where clients already have these where clients already have these where clients already have these existing workloads and so anything that existing workloads and so anything that existing workloads and so anything that needs to kind of take advantage of that needs to kind of take advantage of that needs to kind of take advantage of that transactionality or the data that you transactionality or the data that you transactionality or the data that you may already have there, that's where you may already have there, that's where you may already have there, that's where you really want to kind of keep extending really want to kind of keep extending really want to kind of keep extending and leveraging the platform versus and leveraging the platform versus and leveraging the platform versus trying to create some, you know, replica trying to create some, you know, replica trying to create some, you know, replica somewhere else. somewhere else. somewhere else. >> Do large systems mix and match? Like if >> Do large systems mix and match? Like if >> Do large systems mix and match? Like if I were building my I were building my I were building my I don't know, like an airline, I would I don't know, like an airline, I would I don't know, like an airline, I would have parts of the workload of managing have parts of the workload of managing have parts of the workload of managing the airline run on a mainframe and then the airline run on a mainframe and then the airline run on a mainframe and then parts run on a cloud and they would live parts run on a cloud and they would live parts run on a cloud and they would live together in the same data center or near together in the same data center or near together in the same data center or near each other? each other? each other? >> Yeah, absolutely. I mean, we really >> Yeah, absolutely. I mean, we really >> Yeah, absolutely. I mean, we really think of this as part of a hybrid cloud think of this as part of a hybrid cloud think of this as part of a hybrid cloud architecture and like you you said like architecture and like you you said like architecture and like you you said like you're probably not going to put your you're probably not going to put your you're probably not going to put your mobile, you know, mobile, you know, mobile, you know, part of your mobile app or your you part of your mobile app or your you part of your mobile app or your you know, your your web page necessarily know, your your web page necessarily know, your your web page necessarily hosted on the mainframe, but it's if hosted on the mainframe, but it's if hosted on the mainframe, but it's if you're going to go check your bank you're going to go check your bank you're going to go check your bank balance, that's going to call back to balance, that's going to call back to balance, that's going to call back to the mainframe. And so what we've really the mainframe. And so what we've really the mainframe. And so what we've really done a lot of work on is how do we done a lot of work on is how do we done a lot of work on is how do we enable the technologies that allow the enable the technologies that allow the enable the technologies that allow the platform to seamlessly integrate into platform to seamlessly integrate into platform to seamlessly integrate into that hybrid cloud world. You know, that hybrid cloud world. You know, that hybrid cloud world. You know, whether it's REST APIs, whether it's whether it's REST APIs, whether it's whether it's REST APIs, whether it's Kafka or you know, we just purchased Kafka or you know, we just purchased Kafka or you know, we just purchased Confluent. So, you know, we may have Confluent. So, you know, we may have Confluent. So, you know, we may have that prefer that flavor, right? Of of that prefer that flavor, right? Of of that prefer that flavor, right? Of of Kafka out there, but you know, all Kafka out there, but you know, all Kafka out there, but you know, all these, you know, common ways of these, you know, common ways of these, you know, common ways of interconnecting systems absolutely apply interconnecting systems absolutely apply interconnecting systems absolutely apply just as effectively to your IBM Z just as effectively to your IBM Z just as effectively to your IBM Z platform and can participate natively platform and can participate natively platform and can participate natively that way.

that way. that way. >> Yeah, I used to work before my day job >> Yeah, I used to work before my day job >> Yeah, I used to work before my day job at Microsoft, I used to work in banking at Microsoft, I used to work in banking at Microsoft, I used to work in banking and we would always we would have a big and we would always we would have a big and we would always we would have a big front-end that was running on X86 at the front-end that was running on X86 at the front-end that was running on X86 at the time that would handle the web pages for time that would handle the web pages for time that would handle the web pages for retail online banking and then we would retail online banking and then we would retail online banking and then we would interface with the mainframe via interface with the mainframe via interface with the mainframe via whatever technique that that bank's whatever technique that that bank's whatever technique that that bank's mainframe would use and it worked it mainframe would use and it worked it mainframe would use and it worked it worked very well and then bill pay was worked very well and then bill pay was worked very well and then bill pay was all handled at like the 2:00 a.m. all handled at like the 2:00 a.m. all handled at like the 2:00 a.m. nightly bill pay run. nightly bill pay run. nightly bill pay run. >> Mhm. >> Mhm. >> Mhm. >> And I would say that the machines that >> And I would say that the machines that >> And I would say that the machines that we were running for the web servers we were running for the web servers we were running for the web servers would would would I would be lucky if we had two or three I would be lucky if we had two or three I would be lucky if we had two or three nines at the time. This is a 25 years nines at the time. This is a 25 years nines at the time. This is a 25 years ago, but we never really thought about ago, but we never really thought about ago, but we never really thought about the mainframe going down. It was always the mainframe going down. It was always the mainframe going down. It was always there just humming along. Now, you say there just humming along. Now, you say there just humming along. Now, you say hot though, let's talk about that. Hot hot though, let's talk about that. Hot hot though, let's talk about that. Hot for for context for our listeners means for for context for our listeners means for for context for our listeners means that you're running those CPUs at 90% at that you're running those CPUs at 90% at that you're running those CPUs at 90% at 80%. You're you're not idle. If a 80%. You're you're not idle. If a 80%. You're you're not idle. If a mainframe is idle, that's a problem, mainframe is idle, that's a problem, mainframe is idle, that's a problem, right? right? right? >> Oh, well, it's certainly not a problem >> Oh, well, it's certainly not a problem >> Oh, well, it's certainly not a problem necessarily, but you're probably not necessarily, but you're probably not necessarily, but you're probably not getting the most you know, your maximum getting the most you know, your maximum getting the most you know, your maximum cost efficiency and value out of it. So, cost efficiency and value out of it. So, cost efficiency and value out of it. So, you know, and these boxes can be they you know, and these boxes can be they you know, and these boxes can be they basically come fully loaded with all of basically come fully loaded with all of basically come fully loaded with all of the capacity on it and you could just the capacity on it and you could just the capacity on it and you could just turn on the capacity that you need. So, turn on the capacity that you need. So, turn on the capacity that you need. So, you know, within the box you can, you you know, within the box you can, you you know, within the box you can, you know, set the capacity level and just know, set the capacity level and just know, set the capacity level and just pay for the capacity that is appropriate pay for the capacity that is appropriate pay for the capacity that is appropriate for your business, but if you need to for your business, but if you need to for your business, but if you need to spike or scale, right, there's that spike or scale, right, there's that spike or scale, right, there's that possibility of expanding up into kind of possibility of expanding up into kind of possibility of expanding up into kind of the dark capacity that basically is the dark capacity that basically is the dark capacity that basically is there, just not, you know, always there, just not, you know, always there, just not, you know, always enabled and that you're not always enabled and that you're not always enabled and that you're not always paying for within the platform.

paying for within the platform. paying for within the platform. >> Could you expand on that? What does that >> Could you expand on that? What does that >> Could you expand on that? What does that mean dark capacity? Cuz if I think about mean dark capacity? Cuz if I think about mean dark capacity? Cuz if I think about running something hot, I feel like running something hot, I feel like running something hot, I feel like there's not enough headroom for another there's not enough headroom for another there's not enough headroom for another burst. burst. burst. >> Well, so that's where it's there's >> Well, so that's where it's there's >> Well, so that's where it's there's there's the full box that's available there's the full box that's available there's the full box that's available that we ship that has basically that we ship that has basically that we ship that has basically everything, you know, most of what's everything, you know, most of what's everything, you know, most of what's possible in it. possible in it. possible in it. >> Mhm. >> Mhm. >> Mhm. >> And then you may choose to run it at, >> And then you may choose to run it at, >> And then you may choose to run it at, you know, just turn on or enable, say, I you know, just turn on or enable, say, I you know, just turn on or enable, say, I don't 60% of what's possible on the box. don't 60% of what's possible on the box. don't 60% of what's possible on the box. And so within that 60% that you've sort And so within that 60% that you've sort And so within that 60% that you've sort of entitled yourself to, you can run of entitled yourself to, you can run of entitled yourself to, you can run that at 80, 90, 95, 97%. that at 80, 90, 95, 97%. that at 80, 90, 95, 97%. >> But then if you need to turn on more, >> But then if you need to turn on more, >> But then if you need to turn on more, right, that's sort of that dark capacity right, that's sort of that dark capacity right, that's sort of that dark capacity that's still available in the box, but that's still available in the box, but that's still available in the box, but you're not actually paying for it cuz you're not actually paying for it cuz you're not actually paying for it cuz you haven't turned it on, you can then you haven't turned it on, you can then you haven't turned it on, you can then actually vertically scale up and turn on actually vertically scale up and turn on actually vertically scale up and turn on more capacity. more capacity. more capacity. >> Interesting. Okay. And that that kind of >> Interesting. Okay. And that that kind of >> Interesting. Okay. And that that kind of explains that the the mainframe is it explains that the the mainframe is it explains that the the mainframe is it has a cloud-like attribute, but it's on has a cloud-like attribute, but it's on has a cloud-like attribute, but it's on site, right? So, you've got site, right? So, you've got site, right? So, you've got self-provisioning of resources, you've self-provisioning of resources, you've self-provisioning of resources, you've got scalability within itself. You've got scalability within itself. You've got scalability within itself. You've got a extra fifth gear as it were that got a extra fifth gear as it were that got a extra fifth gear as it were that you can pop into if you need to.

you can pop into if you need to. you can pop into if you need to. >> Yeah, and we find we found some clients >> Yeah, and we find we found some clients >> Yeah, and we find we found some clients you know, there's obviously a lot of the you know, there's obviously a lot of the you know, there's obviously a lot of the core systems that run on z/OS. Then I core systems that run on z/OS. Then I core systems that run on z/OS. Then I mentioned Linux earlier and we've seen a mentioned Linux earlier and we've seen a mentioned Linux earlier and we've seen a lot of clients actually as their data lot of clients actually as their data lot of clients actually as their data centers are getting full, as their power centers are getting full, as their power centers are getting full, as their power consumption is maxing out, and they consumption is maxing out, and they consumption is maxing out, and they still have these needs for, you know, still have these needs for, you know, still have these needs for, you know, more database compute or more AI, more database compute or more AI, more database compute or more AI, actually turning to Linux on Z in their actually turning to Linux on Z in their actually turning to Linux on Z in their IBM Z mainframes and you can get a box IBM Z mainframes and you can get a box IBM Z mainframes and you can get a box that's like called Linux One that's just that's like called Linux One that's just that's like called Linux One that's just 100% Linux if you don't have z/OS, or 100% Linux if you don't have z/OS, or 100% Linux if you don't have z/OS, or you could just have an LPAR. It's one of you could just have an LPAR. It's one of you could just have an LPAR. It's one of those virtualized kind of slices of the those virtualized kind of slices of the those virtualized kind of slices of the compute and have that be a Linux um compute and have that be a Linux um compute and have that be a Linux um Linux-based LPAR. And then within that, Linux-based LPAR. And then within that, Linux-based LPAR. And then within that, we've seen a lot of clients really um do we've seen a lot of clients really um do we've seen a lot of clients really um do a lot of consolidation around databases. a lot of consolidation around databases. a lot of consolidation around databases. So, uh Citibank was a big example. They So, uh Citibank was a big example. They So, uh Citibank was a big example. They actually made a big splash at a MongoDB actually made a big splash at a MongoDB actually made a big splash at a MongoDB conference a few years back. They moved conference a few years back. They moved conference a few years back. They moved all of their MongoDB from x86 onto Linux all of their MongoDB from x86 onto Linux all of their MongoDB from x86 onto Linux on Z. And they had, you know, over 50% on Z. And they had, you know, over 50% on Z. And they had, you know, over 50% power savings. Um I think they had some power savings. Um I think they had some power savings. Um I think they had some license cost savings. And they were able license cost savings. And they were able license cost savings. And they were able to achieve some regulatory requirements to achieve some regulatory requirements to achieve some regulatory requirements uh around cyber resiliency and, you uh around cyber resiliency and, you uh around cyber resiliency and, you know, uh basically immutable copies, know, uh basically immutable copies, know, uh basically immutable copies, backups that could be totally separated backups that could be totally separated backups that could be totally separated that they weren't actually able to that they weren't actually able to that they weren't actually able to achieve on x86. So, they cost savings, achieve on x86. So, they cost savings, achieve on x86. So, they cost savings, you know, they got better performance, you know, they got better performance, you know, they got better performance, they had less power, and they were able they had less power, and they were able they had less power, and they were able to achieve things that they couldn't do to achieve things that they couldn't do to achieve things that they couldn't do otherwise.

otherwise. otherwise. >> Now, that term that you just said, LPAR, >> Now, that term that you just said, LPAR, >> Now, that term that you just said, LPAR, that's logical partition, that's like um that's logical partition, that's like um that's logical partition, that's like um virtual machine. It's a section that you virtual machine. It's a section that you virtual machine. It's a section that you are logically as as is the title, are logically as as is the title, are logically as as is the title, logically partitioning, you're setting logically partitioning, you're setting logically partitioning, you're setting aside a space. But then you mentioned aside a space. But then you mentioned aside a space. But then you mentioned regulatory things. Are mainframes regulatory things. Are mainframes regulatory things. Are mainframes somehow special or treated differently somehow special or treated differently somehow special or treated differently if I uh often we're we're told if I want if I uh often we're we're told if I want if I uh often we're we're told if I want to get past a certain regulation, I to get past a certain regulation, I to get past a certain regulation, I might need to move a workload from one might need to move a workload from one might need to move a workload from one part of the cloud to another to make part of the cloud to another to make part of the cloud to another to make sure it's on a physically different sure it's on a physically different sure it's on a physically different machine. Uh is a logical partition machine. Uh is a logical partition machine. Uh is a logical partition special in a mainframe that I can run, special in a mainframe that I can run, special in a mainframe that I can run, you know, workloads that are that need you know, workloads that are that need you know, workloads that are that need to be separate from each other, but they to be separate from each other, but they to be separate from each other, but they are separate are separate are separate both logically and physically? I guess both logically and physically? I guess both logically and physically? I guess I'm not understanding the question. I'm not understanding the question. I'm not understanding the question. >> Yeah, yeah. I mean, you can you can >> Yeah, yeah. I mean, you can you can >> Yeah, yeah. I mean, you can you can certainly um have separation certainly um have separation certainly um have separation uh you know, within the mainframe uh you know, within the mainframe uh you know, within the mainframe through some of those virtualized through some of those virtualized through some of those virtualized virtualization techniques. I think virtualization techniques. I think virtualization techniques. I think often, you know, the the mainframe is a often, you know, the the mainframe is a often, you know, the the mainframe is a good place for those regulated workloads good place for those regulated workloads good place for those regulated workloads in part because in part because in part because I mean, in most of these companies, it's I mean, in most of these companies, it's I mean, in most of these companies, it's already established. Uh you don't have already established. Uh you don't have already established. Uh you don't have to go establish something from scratch.

to go establish something from scratch. to go establish something from scratch. You know, the processes are there. The You know, the processes are there. The You know, the processes are there. The you know, the the the way that we do you know, the the the way that we do you know, the the the way that we do proof points, everything is is is proof points, everything is is is proof points, everything is is is basically there. And so, you kind of basically there. And so, you kind of basically there. And so, you kind of almost get it for free when you bring a almost get it for free when you bring a almost get it for free when you bring a workload because you're already taking workload because you're already taking workload because you're already taking advantage of that investment that's advantage of that investment that's advantage of that investment that's already been made um within the already been made um within the already been made um within the enterprise on that platform. And so, you enterprise on that platform. And so, you enterprise on that platform. And so, you kind of just inherit you know, that kind of just inherit you know, that kind of just inherit you know, that aspect of the qualities of service as aspect of the qualities of service as aspect of the qualities of service as long as well as you know, the others long as well as you know, the others long as well as you know, the others that are part of the platform. that are part of the platform. that are part of the platform. >> Mhm. >> Mhm. >> Mhm. Now, when I think about a mainframe, I Now, when I think about a mainframe, I Now, when I think about a mainframe, I certainly don't think about AI. Uh certainly don't think about AI. Uh certainly don't think about AI. Uh forgive me in my ignorance, but you forgive me in my ignorance, but you forgive me in my ignorance, but you know, I think about airlines and banks know, I think about airlines and banks know, I think about airlines and banks and big important stuff and power and big important stuff and power and big important stuff and power systems and things that needs to run uh systems and things that needs to run uh systems and things that needs to run uh forever. How has a mainframe uh been forever. How has a mainframe uh been forever. How has a mainframe uh been introduced to AI? Like are you literally introduced to AI? Like are you literally introduced to AI? Like are you literally running inference on things like an IBM running inference on things like an IBM running inference on things like an IBM Z16? Uh or are I mean, where does AI fit Z16? Uh or are I mean, where does AI fit Z16? Uh or are I mean, where does AI fit in and when did that shift start to in and when did that shift start to in and when did that shift start to happen? Cuz you've been there while this happen? Cuz you've been there while this happen? Cuz you've been there while this happened. Like you were at IBM during happened. Like you were at IBM during happened. Like you were at IBM during the rise of AI. the rise of AI. the rise of AI. Are they were Were were were IBM Z class Are they were Were were were IBM Z class Are they were Were were were IBM Z class mainframes just ready to run AI? Like do mainframes just ready to run AI? Like do mainframes just ready to run AI? Like do they have They don't have Nvidia cards?

they have They don't have Nvidia cards? they have They don't have Nvidia cards? How does that work? How does that work? How does that work? >> Yeah, so you know, I think we actually >> Yeah, so you know, I think we actually >> Yeah, so you know, I think we actually have been ahead of the curve on this. have been ahead of the curve on this. have been ahead of the curve on this. So, with IBM Z17, which we just So, with IBM Z17, which we just So, with IBM Z17, which we just announced last year, was actually our announced last year, was actually our announced last year, was actually our second generation of mainframe that has second generation of mainframe that has second generation of mainframe that has specialty AI chips built into the box. specialty AI chips built into the box. specialty AI chips built into the box. So, we first introduced this with Z16 So, we first introduced this with Z16 So, we first introduced this with Z16 I don't know, about 4 years I guess it I don't know, about 4 years I guess it I don't know, about 4 years I guess it before years ago. before years ago. before years ago. >> Mhm. >> Mhm. >> Mhm. >> Uh and and there we introduced something >> Uh and and there we introduced something >> Uh and and there we introduced something called the Telum chip. And that was called the Telum chip. And that was called the Telum chip. And that was really more of your traditional machine really more of your traditional machine really more of your traditional machine learning, I would say as opposed to you learning, I would say as opposed to you learning, I would say as opposed to you know, generative AI models. Uh but we know, generative AI models. Uh but we know, generative AI models. Uh but we really introduced this because we saw really introduced this because we saw really introduced this because we saw this need for AI to be much closer to this need for AI to be much closer to this need for AI to be much closer to these workloads. So, you know, we think these workloads. So, you know, we think these workloads. So, you know, we think about it in somewhat I suppose pragmatic about it in somewhat I suppose pragmatic about it in somewhat I suppose pragmatic terms, right? And really focus on how we terms, right? And really focus on how we terms, right? And really focus on how we can deliver value for our clients. So, can deliver value for our clients. So, can deliver value for our clients. So, they got these workloads that are they got these workloads that are they got these workloads that are running on in systems and they running on in systems and they running on in systems and they absolutely need AI. absolutely need AI. absolutely need AI. Um, you know, if you're going to go and Um, you know, if you're going to go and Um, you know, if you're going to go and a lot of times they're very time a lot of times they're very time a lot of times they're very time sensitive. So, if you're going to go sensitive. So, if you're going to go sensitive. So, if you're going to go make a transaction, you want to catch make a transaction, you want to catch make a transaction, you want to catch that fraud at the moment that the that fraud at the moment that the that fraud at the moment that the transaction is happening, not 30 minutes transaction is happening, not 30 minutes transaction is happening, not 30 minutes or an hour later, or even, you know, 30 or an hour later, or even, you know, 30 or an hour later, or even, you know, 30 seconds or 60 seconds later cuz by then seconds or 60 seconds later cuz by then seconds or 60 seconds later cuz by then you probably just had to let the you probably just had to let the you probably just had to let the transaction go because it took too long.

transaction go because it took too long. transaction go because it took too long. And so, and once you've let fraud go, And so, and once you've let fraud go, And so, and once you've let fraud go, it's basically a loss, right? Like it's it's basically a loss, right? Like it's it's basically a loss, right? Like it's just kind of a lot of banks look at it just kind of a lot of banks look at it just kind of a lot of banks look at it as the cost of doing business that you as the cost of doing business that you as the cost of doing business that you lose, you know, 8% of your revenue due lose, you know, 8% of your revenue due lose, you know, 8% of your revenue due to fraud in a year. to fraud in a year. to fraud in a year. Um, and that's a pretty high cost. And Um, and that's a pretty high cost. And Um, and that's a pretty high cost. And so, actually bringing AI to the platform so, actually bringing AI to the platform so, actually bringing AI to the platform is really critical because now you've is really critical because now you've is really critical because now you've completely cut out network latency. completely cut out network latency. completely cut out network latency. You're able to run it at the source of You're able to run it at the source of You're able to run it at the source of the transaction is happening and you can the transaction is happening and you can the transaction is happening and you can get, you know, less than a millisecond get, you know, less than a millisecond get, you know, less than a millisecond or single-digit millisecond kind of or single-digit millisecond kind of or single-digit millisecond kind of response times to those inferences and response times to those inferences and response times to those inferences and have been and be able to then score and have been and be able to then score and have been and be able to then score and do it in 100% of your transactions. So, do it in 100% of your transactions. So, do it in 100% of your transactions. So, then you can actually, you know, start then you can actually, you know, start then you can actually, you know, start to catch massively more amount of fraud to catch massively more amount of fraud to catch massively more amount of fraud and stop that, which becomes, you know, and stop that, which becomes, you know, and stop that, which becomes, you know, a huge business impact and again return a huge business impact and again return a huge business impact and again return on your investment um for the platform on your investment um for the platform on your investment um for the platform and for the investment. You know, and I and for the investment. You know, and I and for the investment. You know, and I think the same is true of the data. A think the same is true of the data. A think the same is true of the data. A lot of times people are copying data out lot of times people are copying data out lot of times people are copying data out and, you know, there's capabilities that and, you know, there's capabilities that and, you know, there's capabilities that we've built into DB2 on the mainframe to we've built into DB2 on the mainframe to we've built into DB2 on the mainframe to allow you to do like semantic analysis allow you to do like semantic analysis allow you to do like semantic analysis to be able to find similarities, to to be able to find similarities, to to be able to find similarities, to apply patterns and classifications and, apply patterns and classifications and, apply patterns and classifications and, you know, really be able to do that on you know, really be able to do that on you know, really be able to do that on platform um and and and again kind of at platform um and and and again kind of at platform um and and and again kind of at a lower cost, you know, for the use a lower cost, you know, for the use a lower cost, you know, for the use cases that matter for these enterprises.

cases that matter for these enterprises. cases that matter for these enterprises. And so, we introduced Telum in z16 and And so, we introduced Telum in z16 and And so, we introduced Telum in z16 and then in z17, you know, our latest then in z17, you know, our latest then in z17, you know, our latest generation of the mainframe, uh we generation of the mainframe, uh we generation of the mainframe, uh we introduced Telum 2, which is more introduced Telum 2, which is more introduced Telum 2, which is more powerful, can handle larger models. We powerful, can handle larger models. We powerful, can handle larger models. We also introduced Spire cards, also introduced Spire cards, also introduced Spire cards, uh which are um PCIe attached cards uh which are um PCIe attached cards uh which are um PCIe attached cards that, you know, you can run you know, that, you know, you can run you know, that, you know, you can run you know, small small to medium, not not your small small to medium, not not your small small to medium, not not your you're not going to run a frontier model you're not going to run a frontier model you're not going to run a frontier model on a mainframe, but uh you know, a small on a mainframe, but uh you know, a small on a mainframe, but uh you know, a small to medium model, kind of more special to medium model, kind of more special to medium model, kind of more special purpose uh for the use cases to be able purpose uh for the use cases to be able purpose uh for the use cases to be able to bring GenAI to the platform. to bring GenAI to the platform. to bring GenAI to the platform. >> Yeah, and the density of these, like >> Yeah, and the density of these, like >> Yeah, and the density of these, like it's I'm having trouble getting my head it's I'm having trouble getting my head it's I'm having trouble getting my head around it because again, you just see around it because again, you just see around it because again, you just see the giant black refrigerator with the the giant black refrigerator with the the giant black refrigerator with the cool front door. But the cool front door. But the cool front door. But the the Spire cards have like 128 gigs of of the Spire cards have like 128 gigs of of the Spire cards have like 128 gigs of of memory on them and 32 cores, and you can memory on them and 32 cores, and you can memory on them and 32 cores, and you can fit 48 of them. fit 48 of them. fit 48 of them. And And that's just such an insane And And that's just such an insane And And that's just such an insane amount of processor power. And you just amount of processor power. And you just amount of processor power. And you just plug the plug up 48 across all of the IO plug the plug up 48 across all of the IO plug the plug up 48 across all of the IO drawers. That just blows my mind. drawers. That just blows my mind. drawers. That just blows my mind. >> Yeah, yeah, I know, it's pretty cool. >> Yeah, yeah, I know, it's pretty cool. >> Yeah, yeah, I know, it's pretty cool. And uh you know, we're we're definitely And uh you know, we're we're definitely And uh you know, we're we're definitely seeing clients get excited about that.

seeing clients get excited about that. seeing clients get excited about that. We're seeing pretty big um takeoff in We're seeing pretty big um takeoff in We're seeing pretty big um takeoff in terms of folks buying cards, reserving terms of folks buying cards, reserving terms of folks buying cards, reserving space, and and kind of getting them space, and and kind of getting them space, and and kind of getting them installed as they're bringing in this installed as they're bringing in this installed as they're bringing in this next generation of the mainframe. You next generation of the mainframe. You next generation of the mainframe. You know, and I think we see a couple know, and I think we see a couple know, and I think we see a couple different ways that folks are thinking different ways that folks are thinking different ways that folks are thinking about using it. You know, one is about using it. You know, one is about using it. You know, one is we're really focused on how we continue we're really focused on how we continue we're really focused on how we continue to bring uh make it easier for folks to to bring uh make it easier for folks to to bring uh make it easier for folks to work with the platform. So, think about work with the platform. So, think about work with the platform. So, think about your operators, your DBAs, your security your operators, your DBAs, your security your operators, your DBAs, your security administrators, all those folks who administrators, all those folks who administrators, all those folks who maintain and operate the platform. And maintain and operate the platform. And maintain and operate the platform. And And we know that uh you know, the And we know that uh you know, the And we know that uh you know, the mainframe is highly uh mainframe is highly uh mainframe is highly uh differentiated in a proprietary way in differentiated in a proprietary way in differentiated in a proprietary way in terms of how it's been built, but some terms of how it's been built, but some terms of how it's been built, but some of its interfaces are also proprietary, of its interfaces are also proprietary, of its interfaces are also proprietary, and they're not quite so differentiated, and they're not quite so differentiated, and they're not quite so differentiated, right? Like, you know, some people don't right? Like, you know, some people don't right? Like, you know, some people don't will kick and scream if you took away will kick and scream if you took away will kick and scream if you took away their, you know, green screen or ISPF their, you know, green screen or ISPF their, you know, green screen or ISPF panels, but it's not And we don't want panels, but it's not And we don't want panels, but it's not And we don't want that to be the way that you have to work that to be the way that you have to work that to be the way that you have to work with the platform in the future. Um and with the platform in the future. Um and with the platform in the future. Um and and today, you know, there's a lot of and today, you know, there's a lot of and today, you know, there's a lot of ways that you can work with the platform ways that you can work with the platform ways that you can work with the platform without ever touching, you know, a a without ever touching, you know, a a without ever touching, you know, a a green screen, actually. And And part of green screen, actually. And And part of green screen, actually. And And part of that is how we're bringing agentic AI to that is how we're bringing agentic AI to that is how we're bringing agentic AI to the platform for those operators, the platform for those operators, the platform for those operators, um and for those folks that work with um and for those folks that work with um and for those folks that work with the platform. And you can run that the platform. And you can run that the platform. And you can run that leveraging your Spire cards. We also see leveraging your Spire cards. We also see leveraging your Spire cards. We also see clients, you know, have business use use clients, you know, have business use use clients, you know, have business use use applications, which which is kind of applications, which which is kind of applications, which which is kind of where I I with this and where we focused where I I with this and where we focused where I I with this and where we focused the beginning of our AI journey around the beginning of our AI journey around the beginning of our AI journey around is how do you actually bring more is how do you actually bring more is how do you actually bring more business operations agents again tied to business operations agents again tied to business operations agents again tied to that data gravity or that transactional that data gravity or that transactional that data gravity or that transactional gravity that you have on the platform gravity that you have on the platform gravity that you have on the platform and be able to leverage that.

and be able to leverage that. and be able to leverage that. >> I want to shift from running running AI >> I want to shift from running running AI >> I want to shift from running running AI models on the thing to understanding how models on the thing to understanding how models on the thing to understanding how AI is going to change how developers AI is going to change how developers AI is going to change how developers work because I was around at the banks work because I was around at the banks work because I was around at the banks when we were finding old people, pulling when we were finding old people, pulling when we were finding old people, pulling them out of retirement, and they were them out of retirement, and they were them out of retirement, and they were helping us with COBOL. And I was also in helping us with COBOL. And I was also in helping us with COBOL. And I was also in the banks during Y2K. the banks during Y2K. the banks during Y2K. And And And I you you know, you've been pretty vocal I you you know, you've been pretty vocal I you you know, you've been pretty vocal about the like Watson Code Assistant for about the like Watson Code Assistant for about the like Watson Code Assistant for Z being a developer assistant, and Z being a developer assistant, and Z being a developer assistant, and you've been very clear about it not you've been very clear about it not you've been very clear about it not being a replacement. Where do you see AI being a replacement. Where do you see AI being a replacement. Where do you see AI as it relates specifically to COBOL? as it relates specifically to COBOL? as it relates specifically to COBOL? And how does it going to help? And how does it going to help? And how does it going to help? I mean, there's young people now getting I mean, there's young people now getting I mean, there's young people now getting into COBOL. Like COBOL's a a growing into COBOL. Like COBOL's a a growing into COBOL. Like COBOL's a a growing shockingly a growing business. And like shockingly a growing business. And like shockingly a growing business. And like if you're you want to do some if you're you want to do some if you're you want to do some interesting work, go learn go learn interesting work, go learn go learn interesting work, go learn go learn COBOL. Where do you see AI fitting into COBOL. Where do you see AI fitting into COBOL. Where do you see AI fitting into that? that? that? >> Yeah, I think AI is a huge unlock for >> Yeah, I think AI is a huge unlock for >> Yeah, I think AI is a huge unlock for for development. You know, the I think for development. You know, the I think for development. You know, the I think the challenge with development on the the challenge with development on the the challenge with development on the mainframe historically it's not really mainframe historically it's not really mainframe historically it's not really been the language. It's been A, the been the language. It's been A, the been the language. It's been A, the complexity of the applications and the complexity of the applications and the complexity of the applications and the fact that you know, in many cases fact that you know, in many cases fact that you know, in many cases they've been around decades and are they've been around decades and are they've been around decades and are complex and don't have good complex and don't have good complex and don't have good documentation or tests. But B, it's been documentation or tests. But B, it's been documentation or tests. But B, it's been the tools that develop and that's really the tools that develop and that's really the tools that develop and that's really been the hardest friction point are the been the hardest friction point are the been the hardest friction point are the tools that developers have had to work tools that developers have had to work tools that developers have had to work with. And so, we've gone on a journey with. And so, we've gone on a journey with. And so, we've gone on a journey for quite some time now to completely for quite some time now to completely for quite some time now to completely modernize the developer experience so modernize the developer experience so modernize the developer experience so you can use VS Code, you can use you can use VS Code, you can use you can use VS Code, you can use Jenkins, right? You can have a fully Jenkins, right? You can have a fully Jenkins, right? You can have a fully modern CI/CD pipeline with automated modern CI/CD pipeline with automated modern CI/CD pipeline with automated tests, deploy code with Ansible, right?

tests, deploy code with Ansible, right? tests, deploy code with Ansible, right? Like every you know, use Artifactory, Like every you know, use Artifactory, Like every you know, use Artifactory, all the things that you would do on all the things that you would do on all the things that you would do on a you know, a distributed platform, you a you know, a distributed platform, you a you know, a distributed platform, you can have that exact same developer can have that exact same developer can have that exact same developer experience with your traditional z/OS experience with your traditional z/OS experience with your traditional z/OS applications. And clients that have applications. And clients that have applications. And clients that have invested in this cuz you know, it's a invested in this cuz you know, it's a invested in this cuz you know, it's a tool change, but it's also a cultural tool change, but it's also a cultural tool change, but it's also a cultural change, right? I know I think if change, right? I know I think if change, right? I know I think if anything that's probably the hardest anything that's probably the hardest anything that's probably the hardest part of it is the cultural change part of it is the cultural change part of it is the cultural change aspect. And but once you do that, we've aspect. And but once you do that, we've aspect. And but once you do that, we've got clients that are deploying code got clients that are deploying code got clients that are deploying code changes 20 times a day on a traditional changes 20 times a day on a traditional changes 20 times a day on a traditional ZOS kicks DB2 banking app, right? Like ZOS kicks DB2 banking app, right? Like ZOS kicks DB2 banking app, right? Like you can have the same agility and same you can have the same agility and same you can have the same agility and same modern tool toolkit, tool abilities. We modern tool toolkit, tool abilities. We modern tool toolkit, tool abilities. We also have other languages on the also have other languages on the also have other languages on the platform like Java and other things, platform like Java and other things, platform like Java and other things, right? And we've seen a lot of folks do right? And we've seen a lot of folks do right? And we've seen a lot of folks do as they operate incrementally as they operate incrementally as they operate incrementally as they modernize incrementally as they modernize incrementally as they modernize incrementally transform their applications to have a transform their applications to have a transform their applications to have a Java interoperate with COBOL. And we can Java interoperate with COBOL. And we can Java interoperate with COBOL. And we can do that in the same transaction scope. do that in the same transaction scope. do that in the same transaction scope. We've invested a lot in this We've invested a lot in this We've invested a lot in this interoperability capability. And so at interoperability capability. And so at interoperability capability. And so at what AI really does is it enables you what AI really does is it enables you what AI really does is it enables you know, you've got this modern base of know, you've got this modern base of know, you've got this modern base of your tool chain, and now you think about your tool chain, and now you think about your tool chain, and now you think about these applications and they're kind of these applications and they're kind of these applications and they're kind of like big tangled up balls of string.

like big tangled up balls of string. like big tangled up balls of string. And folks can't see through them, And folks can't see through them, And folks can't see through them, they're not sure what's connected to they're not sure what's connected to they're not sure what's connected to what. They're afraid to snip out a what. They're afraid to snip out a what. They're afraid to snip out a piece, they're afraid to kind of pull on piece, they're afraid to kind of pull on piece, they're afraid to kind of pull on a string. And what AI does is really a string. And what AI does is really a string. And what AI does is really kind of helps give you that x-ray kind of helps give you that x-ray kind of helps give you that x-ray vision, I think, into that application. vision, I think, into that application. vision, I think, into that application. And what we've done with AI is really a And what we've done with AI is really a And what we've done with AI is really a combination of, you know, combination of, you know, combination of, you know, analysis that is not necessarily AI analysis that is not necessarily AI analysis that is not necessarily AI based, right? It's more static analysis based, right? It's more static analysis based, right? It's more static analysis and some dynamic analysis we built in, and some dynamic analysis we built in, and some dynamic analysis we built in, but you know, declarative, I would say. but you know, declarative, I would say. but you know, declarative, I would say. And we use that actually as context to And we use that actually as context to And we use that actually as context to help inform the AI and the AI models to help inform the AI and the AI models to help inform the AI and the AI models to do their jobs better, which I think is do their jobs better, which I think is do their jobs better, which I think is what differentiates our stack versus what differentiates our stack versus what differentiates our stack versus just any other AI stack that you're just any other AI stack that you're just any other AI stack that you're going to get out there. It's because we going to get out there. It's because we going to get out there. It's because we have this base knowledge of how have this base knowledge of how have this base knowledge of how everything is interconnected, what everything is interconnected, what everything is interconnected, what transaction on kicks may hit a DB2 transaction on kicks may hit a DB2 transaction on kicks may hit a DB2 record over here, you know, impact record over here, you know, impact record over here, you know, impact something in IMS and come back around, something in IMS and come back around, something in IMS and come back around, right? That's the type of stuff that's right? That's the type of stuff that's right? That's the type of stuff that's hard to just know because a lot of times hard to just know because a lot of times hard to just know because a lot of times these code bases are tens or hundreds of these code bases are tens or hundreds of these code bases are tens or hundreds of millions of lines of code, and you can't millions of lines of code, and you can't millions of lines of code, and you can't like wrap all that in your head, and like wrap all that in your head, and like wrap all that in your head, and even the AI models can't quite consume even the AI models can't quite consume even the AI models can't quite consume that quantity either. And so, when you that quantity either. And so, when you that quantity either. And so, when you combine this like analysis and this combine this like analysis and this combine this like analysis and this declarative understanding of the declarative understanding of the declarative understanding of the applications, and use that in the applications, and use that in the applications, and use that in the context thing and in the prompting and context thing and in the prompting and context thing and in the prompting and how you how you how you um you know, do documentation around the um you know, do documentation around the um you know, do documentation around the application, and now totally empowers application, and now totally empowers application, and now totally empowers the developer to you know, not be afraid the developer to you know, not be afraid the developer to you know, not be afraid to find that dead code and cut it out.

to find that dead code and cut it out. to find that dead code and cut it out. Not be afraid to you know, re-architect Not be afraid to you know, re-architect Not be afraid to you know, re-architect this section of the application to make this section of the application to make this section of the application to make it I won't say microservices, but more it I won't say microservices, but more it I won't say microservices, but more service oriented, right? And and really service oriented, right? And and really service oriented, right? And and really helps you to have that confidence as you helps you to have that confidence as you helps you to have that confidence as you do those changes so that again, you can do those changes so that again, you can do those changes so that again, you can move with that same agility on the move with that same agility on the move with that same agility on the platform. platform. platform. >> Yeah, I feel like >> Yeah, I feel like >> Yeah, I feel like people who are getting their feet wet in people who are getting their feet wet in people who are getting their feet wet in AI think that we're we the AI people, AI think that we're we the AI people, AI think that we're we the AI people, you know, I'm an AI person at Microsoft you know, I'm an AI person at Microsoft you know, I'm an AI person at Microsoft and you're an AI person at IBM of a and you're an AI person at IBM of a and you're an AI person at IBM of a sort, are saying that like these LLMs sort, are saying that like these LLMs sort, are saying that like these LLMs are going to solve everything. But your are going to solve everything. But your are going to solve everything. But your point about static analysis is so point about static analysis is so point about static analysis is so important. The LLM may be an important. The LLM may be an important. The LLM may be an orchestrator or a coordinator, but that orchestrator or a coordinator, but that orchestrator or a coordinator, but that does not mean that the software does not mean that the software does not mean that the software development life cycle changes. It does development life cycle changes. It does development life cycle changes. It does not mean that static analysis changes. not mean that static analysis changes. not mean that static analysis changes. It's the tools around that and then the It's the tools around that and then the It's the tools around that and then the orchestration of those tools that that orchestration of those tools that that orchestration of those tools that that is the the real unlock. is the the real unlock. is the the real unlock. >> Yeah, absolutely. I mean, you know, >> Yeah, absolutely. I mean, you know, >> Yeah, absolutely. I mean, you know, certainly there's this view that you certainly there's this view that you certainly there's this view that you know, AI is going to change everything know, AI is going to change everything know, AI is going to change everything and in in some ways it will, but I also and in in some ways it will, but I also and in in some ways it will, but I also think that going back to some of the think that going back to some of the think that going back to some of the basics of like what makes good agile basics of like what makes good agile basics of like what makes good agile development practice, development practice, development practice, uh you know, what makes good engineering uh you know, what makes good engineering uh you know, what makes good engineering and good architecture become even more and good architecture become even more and good architecture become even more important, especially if you're going to important, especially if you're going to important, especially if you're going to be developing code at a significantly be developing code at a significantly be developing code at a significantly faster rate and pace. Uh you know, like faster rate and pace. Uh you know, like faster rate and pace. Uh you know, like we as humans aren't going to be able to we as humans aren't going to be able to we as humans aren't going to be able to necessarily consume or put everything necessarily consume or put everything necessarily consume or put everything together unless we have the right you together unless we have the right you together unless we have the right you know, kind of guardrails, we have the know, kind of guardrails, we have the know, kind of guardrails, we have the right architecture design that we're right architecture design that we're right architecture design that we're using really as input into this AI so using really as input into this AI so using really as input into this AI so that like we're driving the AI to do

that like we're driving the AI to do that like we're driving the AI to do what we want as opposed to the AI what we want as opposed to the AI what we want as opposed to the AI telling us what should be done. telling us what should be done. telling us what should be done. >> Yeah, yeah. I want to go back you >> Yeah, yeah. I want to go back you >> Yeah, yeah. I want to go back you mentioned Java. Like I feel like in mentioned Java. Like I feel like in mentioned Java. Like I feel like in 2026, like a lot of people don't realize 2026, like a lot of people don't realize 2026, like a lot of people don't realize that Java is on mainframes and like why that Java is on mainframes and like why that Java is on mainframes and like why is there an awareness gap in 2026? is there an awareness gap in 2026? is there an awareness gap in 2026? >> You know, that is that is a great >> You know, that is that is a great >> You know, that is that is a great question. I I would if I knew the question. I I would if I knew the question. I I would if I knew the answer, I would fix it. answer, I would fix it. answer, I would fix it. Uh you know, I I it's funny at the Z16 Uh you know, I I it's funny at the Z16 Uh you know, I I it's funny at the Z16 launch four or four or five years ago, launch four or four or five years ago, launch four or four or five years ago, you know, I went there and I was talking you know, I went there and I was talking you know, I went there and I was talking to a client and at I think at that time to a client and at I think at that time to a client and at I think at that time Java had already been on the platform 20 Java had already been on the platform 20 Java had already been on the platform 20 years and I was talking to someone and years and I was talking to someone and years and I was talking to someone and they didn't know. they didn't know. they didn't know. Um you know, even today there may be Um you know, even today there may be Um you know, even today there may be folks who've been over there Java has folks who've been over there Java has folks who've been over there Java has been there over 25 years and folks don't been there over 25 years and folks don't been there over 25 years and folks don't realize um you know, we've invested in realize um you know, we've invested in realize um you know, we've invested in Java on on Z for for a very long time Java on on Z for for a very long time Java on on Z for for a very long time now and this interoperability for a very now and this interoperability for a very now and this interoperability for a very long time. And we actually this is part long time. And we actually this is part long time. And we actually this is part of the beauty of the full stack of the of the beauty of the full stack of the of the beauty of the full stack of the platform is we actually optimize machine platform is we actually optimize machine platform is we actually optimize machine level instructions to make Java go level instructions to make Java go level instructions to make Java go faster. So things like sorting on Java faster. So things like sorting on Java faster. So things like sorting on Java or we actually reduce the amount of time or we actually reduce the amount of time or we actually reduce the amount of time that it takes to do garbage collection that it takes to do garbage collection that it takes to do garbage collection on the platform. Like Java runs better on the platform. Like Java runs better on the platform. Like Java runs better on the Z platform than any other on the Z platform than any other on the Z platform than any other platform platform platform full stop.

full stop. full stop. It's more performant, it's more It's more performant, it's more It's more performant, it's more efficient. So you know, people a lot of efficient. So you know, people a lot of efficient. So you know, people a lot of times think, oh, I'll move it to Java times think, oh, I'll move it to Java times think, oh, I'll move it to Java and I'll move it off. Well, you know, and I'll move it off. Well, you know, and I'll move it off. Well, you know, hey, you've got that option but you hey, you've got that option but you hey, you've got that option but you know, people think that modernization is know, people think that modernization is know, people think that modernization is a language thing. It's actually the a language thing. It's actually the a language thing. It's actually the value of the Z platform is is not really value of the Z platform is is not really value of the Z platform is is not really about the language. It's about this full about the language. It's about this full about the language. It's about this full stack optimization top to bottom that we stack optimization top to bottom that we stack optimization top to bottom that we do and you may be able to you know, move do and you may be able to you know, move do and you may be able to you know, move an application that's Java to another an application that's Java to another an application that's Java to another platform but is it going to perform the platform but is it going to perform the platform but is it going to perform the same? Is it going to have the same same? Is it going to have the same same? Is it going to have the same resiliency? Is it going to have the same resiliency? Is it going to have the same resiliency? Is it going to have the same latency when it's now disconnected from latency when it's now disconnected from latency when it's now disconnected from the data and everything that it's close the data and everything that it's close the data and everything that it's close to? And so it's really about these to? And so it's really about these to? And so it's really about these architectural decisions and again, what architectural decisions and again, what architectural decisions and again, what is the fit for purpose platform based on is the fit for purpose platform based on is the fit for purpose platform based on your use case that you really need to your use case that you really need to your use case that you really need to think about as opposed to just a think about as opposed to just a think about as opposed to just a language swap, which, you know, at the language swap, which, you know, at the language swap, which, you know, at the end of the day, COBOL is not that hard end of the day, COBOL is not that hard end of the day, COBOL is not that hard of a language. of a language. of a language. >> Yeah, it really isn't. >> Yeah, it really isn't. >> Yeah, it really isn't. >> Very readable, very understandable. >> Very readable, very understandable. >> Very readable, very understandable. >> Yeah, yeah. And not just Java, shout out >> Yeah, yeah. And not just Java, shout out >> Yeah, yeah. And not just Java, shout out to people who are running .NET on their to people who are running .NET on their to people who are running .NET on their their IBM mainframes as well, so. their IBM mainframes as well, so. their IBM mainframes as well, so. >> There you go. >> There you go. >> There you go. >> As a fan, I have to say I appreciate >> As a fan, I have to say I appreciate >> As a fan, I have to say I appreciate that.

that. that. I'm curious as someone who stayed I'm curious as someone who stayed I'm curious as someone who stayed somewhere I stayed at IBM for so long, somewhere I stayed at IBM for so long, somewhere I stayed at IBM for so long, like what kept you excited about staying like what kept you excited about staying like what kept you excited about staying there? Cuz a lot of people are doing the there? Cuz a lot of people are doing the there? Cuz a lot of people are doing the one you know, 18 months here and I'm one you know, 18 months here and I'm one you know, 18 months here and I'm proud to announce and their LinkedIns proud to announce and their LinkedIns proud to announce and their LinkedIns are filled with them moving from one are filled with them moving from one are filled with them moving from one place to another, but you stuck with it. place to another, but you stuck with it. place to another, but you stuck with it. >> Yeah, you know, it's a you know, it's >> Yeah, you know, it's a you know, it's >> Yeah, you know, it's a you know, it's not something I initially planned uh not something I initially planned uh not something I initially planned uh starting out, you know, I think well, starting out, you know, I think well, starting out, you know, I think well, it's sort of the story of a lot of folks it's sort of the story of a lot of folks it's sort of the story of a lot of folks at IBM. You think you're going to join, at IBM. You think you're going to join, at IBM. You think you're going to join, maybe stay for 5 years, go somewhere maybe stay for 5 years, go somewhere maybe stay for 5 years, go somewhere else and uh then you stay. And then, you else and uh then you stay. And then, you else and uh then you stay. And then, you know, you think later on, oh, maybe I know, you think later on, oh, maybe I know, you think later on, oh, maybe I should look around and go somewhere else should look around and go somewhere else should look around and go somewhere else or someone pings you about an or someone pings you about an or someone pings you about an opportunity and you look into it. And opportunity and you look into it. And opportunity and you look into it. And you do and then, you know, you look back you do and then, you know, you look back you do and then, you know, you look back at what you've gotten and you decide to at what you've gotten and you decide to at what you've gotten and you decide to stay. Um and so for me, I think it's stay. Um and so for me, I think it's stay. Um and so for me, I think it's been a continual series of conscious been a continual series of conscious been a continual series of conscious just choices to remain at IBM. And I just choices to remain at IBM. And I just choices to remain at IBM. And I think it's it's a few things. Partly, think it's it's a few things. Partly, think it's it's a few things. Partly, it's you know, people always say this it's you know, people always say this it's you know, people always say this about where they work, I guess, but it about where they work, I guess, but it about where they work, I guess, but it is the people you work with and the is the people you work with and the is the people you work with and the culture that you have. culture that you have. culture that you have. Um you know, IBM is a big place and Um you know, IBM is a big place and Um you know, IBM is a big place and there are a lot of amazing people that there are a lot of amazing people that there are a lot of amazing people that I've had the opportunity to to work with I've had the opportunity to to work with I've had the opportunity to to work with and learn from and we actually have a and learn from and we actually have a and learn from and we actually have a constant infusion of new talent and new constant infusion of new talent and new constant infusion of new talent and new perspectives coming into the company perspectives coming into the company perspectives coming into the company through the acquisitions and I've had through the acquisitions and I've had through the acquisitions and I've had the opportunity to work with a number of the opportunity to work with a number of the opportunity to work with a number of people through some of the acquisitions people through some of the acquisitions people through some of the acquisitions that we've done as well that have, you that we've done as well that have, you that we've done as well that have, you know, broadened my horizons and given me know, broadened my horizons and given me know, broadened my horizons and given me almost a startup experience uh in some almost a startup experience uh in some almost a startup experience uh in some cases. And I think it's also the the cases. And I think it's also the the cases. And I think it's also the the opportunity.

opportunity. opportunity. Uh you know, I've done a lot of things Uh you know, I've done a lot of things Uh you know, I've done a lot of things in my career at IBM from, you know, in my career at IBM from, you know, in my career at IBM from, you know, database engine optimization to you database engine optimization to you database engine optimization to you know, analytical queries and mobile know, analytical queries and mobile know, analytical queries and mobile applications and cloud and you know, now applications and cloud and you know, now applications and cloud and you know, now everything that I get to do on the everything that I get to do on the everything that I get to do on the mainframe is really kind of a a mainframe is really kind of a a mainframe is really kind of a a microcosm actually of the entire microcosm actually of the entire microcosm actually of the entire software industry because everything software industry because everything software industry because everything applies to the mainframe and I get to applies to the mainframe and I get to applies to the mainframe and I get to focus and choose what is most relevant focus and choose what is most relevant focus and choose what is most relevant and so for me it's been about that and so for me it's been about that and so for me it's been about that opportunity to continuing to work on opportunity to continuing to work on opportunity to continuing to work on great stuff on the people I get to work great stuff on the people I get to work great stuff on the people I get to work with and then the clients. with and then the clients. with and then the clients. Um we have really deep long-lasting Um we have really deep long-lasting Um we have really deep long-lasting relationships uh with many of our relationships uh with many of our relationships uh with many of our clients and so it's kind of this like clients and so it's kind of this like clients and so it's kind of this like multifaceted kind of community I guess multifaceted kind of community I guess multifaceted kind of community I guess that you get to be a part of and I've that you get to be a part of and I've that you get to be a part of and I've always felt like I've had the always felt like I've had the always felt like I've had the opportunity to keep learning and opportunity to keep learning and opportunity to keep learning and progressing. So uh it's been it's been progressing. So uh it's been it's been progressing. So uh it's been it's been an exciting ride. an exciting ride. an exciting ride. >> That's very cool. Well, thank you so >> That's very cool. Well, thank you so >> That's very cool. Well, thank you so much for hanging out with me today. much for hanging out with me today. much for hanging out with me today. >> Yeah, thank you. This was fun. >> Yeah, thank you. This was fun. >> Yeah, thank you. This was fun. >> We've been chatting with Skye Le Lumus, >> We've been chatting with Skye Le Lumus, >> We've been chatting with Skye Le Lumus, general manager of IBM Z software and general manager of IBM Z software and general manager of IBM Z software and this has been another episode of this has been another episode of this has been another episode of Hanselminutes and we'll see you again Hanselminutes and we'll see you again Hanselminutes and we'll see you again next week.