3044: AI in Boardroom Conversations and IT Strategies For 2025

[00:00:03] Welcome back to The Tech Talks Daily Podcast where today I'm going to be joined by Dave Donnatale,

[00:00:09] a distinguished leader in the tech sector from a company called Riverbed. Because as businesses navigate

[00:00:16] the complexities of the modern tech environment, we're going to explore some of the key issues at the forefront of executive conversations.

[00:00:24] And I'm talking everything from the increasing importance of AI in strategic decision-making,

[00:00:31] to the top prior is for CIOs. And Dave brings with him a wealth of experience and insight.

[00:00:38] So we're also examining the critical role of unified observer ability and what role that plays in overcoming IT challenges

[00:00:46] to ensure those exceptional digital experiences that we all expect are standard now.

[00:00:53] And Dave's also going to share a few exciting updates on the Riverbed platform, a groundbreaking solution

[00:00:58] that is leveraging AI and full fidelity data to eliminate visibility blind spots and hence user experiences across every touch point.

[00:01:08] And at the end of today's episode, I am going to be asking you to answer how can your organisation harness the innovations that we're talking about today

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[00:03:08] Let's get started today.

[00:03:10] So buckle up and hold on tight as I beam your ears all the way to the US where Dave is waiting a join us today.

[00:03:18] So a massive welcome to the show Dave, can you today for listening a little about who you are and what you do?

[00:03:25] Dave, don't tell me I'm CEO of Riverbed Technologies. I've been the CEO for a little bit over a year prior to that. I've worked in the industry for many decades. I was president of EMC.

[00:03:37] I was ran with his now called Heal of Back and Enterprise and I ran the cloud business group at Oracle.

[00:03:42] Well, it's a pleasure to have you on the podcast and you've probably seen so many different changes throughout your career.

[00:03:47] Well, the pace of technological change continues to ramp up right now. Everyone's obsessed with AI, etc.

[00:03:54] But of course we've come across so many different changes from the arrival of the EMC and at mobile and so much more.

[00:04:02] So I've got to ask right here right now how are you at Riverbed Innovating within the realm of AI and automation to address some of those visibility challenges in digital user experiences,

[00:04:13] particularly in new environments such as riverworking and public clouds. There's so many big changes happening right now, isn't that?

[00:04:21] There really is and I think that's what makes our industry so much fun to work in over the years.

[00:04:26] You know, I'm one of the people who actually started my career pre-commercial internet.

[00:04:31] So you know, the internet had obviously been around but really commercial internet didn't start to the mid 1990s

[00:04:35] and clearly there was a before internet and an after internet and as we know the internet changed everything, right?

[00:04:42] Really changed the way the whole world works. And now where yet as you mentioned, another one is inflection points AI.

[00:04:49] And you know I think AI is still in very early stages at Holt's great promise.

[00:04:54] One of the great things about Riverbed is that we've been working on AI for some time.

[00:04:57] You know Riverbed's been in business for the 20 years. We've been big innovators and that innovation has carried us forward to where AI is today.

[00:05:06] And what I like to say about you know what we're doing in AI is we're into our second generation of products.

[00:05:11] So we actually have for our space products that have you know work, they're installed in large customers, they do active things,

[00:05:18] which I think is so important for a new technology is showing that you can actually change the way customers work and help their environment.

[00:05:25] You know, giving an example we're working with a very large manufacturer in a particular case, you know they thought they are getting 2000 alerts a day of problems.

[00:05:36] And the issue with that is most of those alerts were false positives. So eventually they just had problem problem problem.

[00:05:42] They what really mattered would didn't matter. It wasn't really helpful.

[00:05:46] And by applying one of our AI technologies, they were able to reduce that amount by 86%.

[00:05:50] And then get to the 14% of real problems that really mattered. The other thing was ironic about that is they thought they were getting 2000 problems a day once they were able to clear away all the debris, they were getting 2000 per hour.

[00:06:03] And they were just so innovative that they couldn't see them.

[00:06:07] So as a case where you know technology ultimately helps in this case AI machine learning help them that the technologies we have.

[00:06:14] And it's really all about delivering a better what we call in user experience.

[00:06:18] You know whether it's your customer or whether it's people who work at your organization, you know people want to be able to show up and log in get their job done and they want to in a very efficient manner.

[00:06:29] And that gets more challenging to do every day.

[00:06:32] You know if you think about it, we were talking about the changes. You know five years ago not that many people work from home.

[00:06:39] Now people work from everywhere. You know the coffee shop, their house, their accessing corporate applications, their accessing the cloud.

[00:06:47] And if you're an IT person who has to deliver that experience as someone that gets more challenging.

[00:06:53] You know it was a lot easier when I first started we you know I showed up my to desktop. It was wired.

[00:06:58] I could go down and look at this thing in the fish bowl and essence the data center where I was hooked up to.

[00:07:03] If anything happened was really a problem between my desk in that data center, which was a floor below me.

[00:07:09] And now you know you have again people all over the world trying to connect it at any given time to a whole host of on-prem or cloud applications and making sure that experience is good across all.

[00:07:19] Is really the challenge the most customer space today.

[00:07:22] Hundreds of percent and you mentioned a great point. There are five years ago today working from home was almost just for the privilege view not that many.

[00:07:31] And now that's exactly what's spread now hybrid working we're at now and if we go back further with the arrival of mobile and the internet.

[00:07:37] And I read a great start before you came on the podcast today that I think since the year 2000 52% of the fortune 500 companies have disappeared.

[00:07:47] So we know that adapting to technological change is so important and the role of the C-suite is equally crucial for driving technological advancements.

[00:07:57] Can you tell me a bit more about that importance of securing top tier talent for these roles and how it river bad do you approach this challenge because it's a very real challenge and the cost of not accepting that challenge incredibly high on it.

[00:08:11] Yeah, it's really a two part answer for you. First is what's happening with big organizations out there and as you rightly said 52% of the fortune 500 is gone pretty much since the start of the commercial internet that we were talking about earlier.

[00:08:27] And you know all the C-suite and board people saw that that you know they watched that movie.

[00:08:33] And you know if you're the CEO, the first thing you hear from your board is hey don't let that happen to us this time, you know what are you doing? What is your strategy around AI?

[00:08:41] How are you not going to be disrupted like what happened with the internet? How can you become a leader out of that?

[00:08:46] And that's really what happened the last time around you know the 52% are gone as you know.

[00:08:52] But then we had companies who took advantage of the new technology who were bigger and better and more successful than ever.

[00:08:57] You know if you think of companies like Walmart or UPS, they pivoted and leverage the internet and they're doing better than ever before.

[00:09:04] And then you had a whole bunch of new companies who grew up from nothing, right? You take Google and others who you know cave that technology enable them to exist.

[00:09:12] And I think AI will play out in a very similar fashion right we're going to have the smart companies pivot and become better more successful than ever.

[00:09:20] The ones who just can't do well at technology are going to be in trouble because someone will come along and do a better job using the new technology with them.

[00:09:28] And I don't think we're at this phase yet with AI but eventually we'll get a couple new large companies they'll come you know who are just born to do it.

[00:09:35] So I think that's what's happening on the business side from our side and you say well how do you attract talent and we're very fortunate we have a lot of great technical talent in the company.

[00:09:44] And I think it's all about with engineers and I manage engineers for many decades now having them work on you know interesting work that you know the words of fuel and packer that makes a contribution.

[00:09:58] And what I mean by make a contribution is you know moving or industry forward helping customer solve problems they couldn't otherwise solve on their own.

[00:10:07] Providing new solutions that allow new things to happen and you know personally that's one of the things I'm very proud of my career is that literally every day you touched something I made.

[00:10:18] You might not know it because you know it's infrastructures in the background you won't see it you won't know that but you know a little part of the world works everyday because of something.

[00:10:27] You know that that my me and my teams I work with enabled and and that attracts people you know it's it's very exciting to bring new things out to life and help you know see the excitement of customers when you enable them to do something they couldn't otherwise do or help them solve really critical problems.

[00:10:45] And it will be a bad we really do both those things.

[00:10:48] You know a customer told me the other day he said you know you really take a lot of my pain away.

[00:10:53] And by doing that you also saved me money in the process so then I can go and invest in other things as well.

[00:10:59] And the pain meant dealing with issues you know that we were talking about before work you know the colleagues can't access their their applications colleagues can't work done people are upset.

[00:11:11] We solve those problems for people and makes it look better.

[00:11:14] So I'm proud to do that.

[00:11:16] And another topic that we're hearing more about is AI frequently being on the board room agenda there's a lot of talk and debates around the need for a chief AI office or the moment but.

[00:11:27] I'm curious from everything that you're seeing and hearing what are the most common concerns or topics of conversation that your encountering with your customers and clients and how are you at riverbed addressing some of these discussions too because I imagine you you've got the air of a lot of big businesses right now.

[00:11:43] It what happens is you know AI ultimately comes back to data right good data equals good at.

[00:11:53] AI bad data bad AI and if you know seeing what's happened in the marketplace there's been examples of both of those and on the bad data front you hear about AI hallucinations.

[00:12:03] And essence that is bad data leads to like a laughable result from artificial intelligence and people like oh I how can I trust this is so bad.

[00:12:10] So being able to accumulate enough data to run good you know algorithms against being able to secure that data making sure that you know many customers obviously don't mix their data or make their data publicly available so how to have that data private.

[00:12:27] How to have the scale required.

[00:12:29] These are all the fundamentals that need to be in place before you can really get to good AI.

[00:12:34] And you know if you look at what we've been doing and and you remember my background I was at Oracle also he'll a packer does that you see it was all about scaling enterprise data and what riverbed's done very uniquely is built a data store.

[00:12:48] That scales very well and what I like to say about our approach they are is safe secure and accurate.

[00:12:56] And what I mean by that is from a safe perspective our data store uses information that's only the customers proprietary data so in essence the customers data stays private.

[00:13:08] The only thing that goes in there is what they want to go in there so they have full control over their data.

[00:13:13] That's what also makes it secure and because which you'll see these big sites.

[00:13:18] Is they don't want to have their data turn to open source they don't want to intermingle their very proprietary corporate data with somebody else.

[00:13:25] So they want to make sure it's safe they can only you know use the data they want to use they want to make sure it's secure no one else is going to get their hands on their data.

[00:13:32] And then the accuracy part comes down to as I mentioned good data good AI bad data bad AI is that we have the ability to collect data across your enterprise on how things are performing so whether it's your mobile phones or an iPad or an endpoint you see a lot of people having an endpoint device is now when you go out to dinner or something.

[00:13:52] Your network itself your applications your cloud we could put all that into one place and then from there we run our machine learning on it and that gives us extremely accurate results on what's happening in your environment.

[00:14:07] So through that we can prevent problems or when we find problems we could automate the resolution to them.

[00:14:13] And the automation again back to safety is as much as the customer would like us to do sometimes they just want us to show them what's wrong you know through the system.

[00:14:21] Sometimes they want us to go all the way through to fix it and.

[00:14:24] So the customer in the UK is an example they're doing 20,000 automated fixes a month using these types of systems so there's 20,000 problems that before someone would have to intervene with that now automatically it's fixed.

[00:14:37] And then we just report to it we open up a service call me close the service calls so they can see we've done how we did it and what transpired.

[00:14:45] So all that's really about making AI that works that sells practical problems for people and really provides a good business value to them.

[00:14:53] And something else that's difficult for me to believe in at least it were only four months away from life in 2025 which is something I never thought I'd hear myself say I'm so looking forward what do you see as the top prior is for CIOs and again how we live a bit positioning yourself to support some of these objectives because I would imagine there's a lot of trending conversations.

[00:15:16] There certainly is I mean we've we talked a lot about AI in this conversation but there's there's an equal if not more amount in our space all going around digital experience that I spoke about before.

[00:15:26] Yeah, it's that the the incest need to provide a better experience for everybody who works in an organization no matter where they are and and that's a big priority.

[00:15:35] How they want to get there is through simplification.

[00:15:39] So I'll speak in one customer again another UK based customers telling me for them to provide their digital experience they had 56 different tools.

[00:15:49] Now as you can imagine with a 56 different tools that is.

[00:15:53] Too much the managed very difficult you as a customer enough trying to sew together all these disparate pieces in order to get a solution so they found it very frustrating.

[00:16:00] So what they really are looking to do is have fewer tools cover more of this broader environment as we mentioned the environment gets broader every day so give me fewer tools to cover more my my space.

[00:16:13] So it's easier speaking the voice of the customer it's easier for them to manage and provide the experience I want to their end users.

[00:16:20] So that's exactly what we're doing.

[00:16:22] We announced back in May are in and shipped so it's real it's here today the Riverbed platform.

[00:16:29] And that platform is an open platform so it uses our data and if the customer so desires other people's data.

[00:16:36] And it manages across network in point cloud and applications and user experience and then applies the automation we talked about in order to again prevent or remediating fix problems and report on them ultimately.

[00:16:53] So what I see for 2025 is that's going to become a bigger you know desire for customers again they want simplification the other thing they really want is they want to see an ROI.

[00:17:04] You know as the economies of the world you know they're doing okay but there's a little bit slower than they were a year ago if you watch you know what's happening to all the various stock markets and all these reports.

[00:17:14] And when that happens customers get very conscious about ROI you know how can I make sure I'm only investing things that provide true value.

[00:17:20] How could I make sure my investment is getting the return I want so we spend a lot of time work with our customers on our eye and I think that's going to become more prevalent next year.

[00:17:28] And then as I really say I you know in general with AI you always hear people talk about you know the trough of disillusionment you know so you go through the hype cycle.

[00:17:39] Then people get kind of getting this disillusionment phase of what's really happening here and then they come out of it as new solutions start to matter.

[00:17:47] And you know as you heard what I'm proud of the word doing is we have AI that really works.

[00:17:53] And people have been solid and they're running in and they're doing real things with it and you'll see more that deployment as the years go on next year is you know customers really want to do it as we talked about earlier in this.

[00:18:04] Truly is a more discussion to see your discussion see your patient people they want to see progress.

[00:18:08] And you'll see more that in 2020 fact.

[00:18:11] And one of the reasons I was excited to get you on the podcast today is the fact that unified observe mobility is gaining incredible traction as a vital component in IT strategies right now and I know this is a topic close to your heart so can you tell me a little bit more about how riverbed platform is enhancing that approach and also some of the specific IT challenges it over.

[00:18:33] It helps to overcome because we hear a lot about the shiny technologies and the the hype and the push words etc but each those challenges that it helps to overcome that's where the magic happens right.

[00:18:43] Yeah I think the I think the biggest nightmare for most CIOs is something breaks and again you know we're not living in a world of perfect so something breaks all the time.

[00:18:53] Is so something breaks and the question they always get is what's wrong and how do I fix it.

[00:19:00] And you'd hear it's really interesting I love spending time with customers I talked about all the time and different departments within IT always talk about meantime between to before innocence.

[00:19:11] Meantime to innocence so they want to say hey I'm the network person it's not the network I proven it's not maybe it's somebody else and they kind of play hot potato to figure out where the problem is.

[00:19:21] And the the the challenge that is that can take you know.

[00:19:26] Many many hours sometimes you know over a day to figure out what's really going on so what they're really looking for if you look about this unit for observability is precision.

[00:19:36] In my whole big complex world that we've been speaking about on-prem off-prem cloud applications everything else if something breaks what is it.

[00:19:44] You might think that simple it's not a simple as you think and so tell me what's wrong because once I know what's actually wrong then I can go fix it.

[00:19:54] And again it's a gray area it's not as black and white as people think and that's really what our technologies do in the whole idea behind the platform is enabling people to do that so I'll give you a couple elements of it you might find interesting.

[00:20:06] First of all you know in it the highest sense we do three things we collect a lot of data on what's happening.

[00:20:16] We then analyze that data through machine learning and then act on as we talked about we can automate fixes and things like that and the third thing we do is we report on it so we tell you what we did.

[00:20:26] And you know on the collection phase because everybody's environment gets bigger and bigger and bigger we're able to collect real data not synthetic data on all these different data points so we can do it in your network we can do it on your laptops we can do it on your phones collect data in our data is just data understanding how things are working is a working is it not work it is it fast as it slow what are your problems.

[00:20:51] So you know by collecting that data and then having a repository that we talked about before world that data resides we can very quickly understand what's broken what action needs to be taken in our own.

[00:21:02] So it's very very valuable to our customers but to do that increasingly you need agents and the simple thing to talk about agents and in every just virtually every big software product out there uses agents.

[00:21:14] customers don't like agents because that's a one-worth thing to manage so on an average laptop you can have 20 agents.

[00:21:21] That they have to manage and they don't really like that so we went to a common agent technology so in essence one agent can then manage all these things versus having an individual agent for your network your application everything else customers like that.

[00:21:33] Once we got past the agents then we started developing new agent modules as we call them.

[00:21:38] So you might you know you might have some guests on who are talking about you know security and one of the big security trends out there is zero trust environments.

[00:21:47] So zero trust environments solve a problem around security but they create a problem around observability and figuring out what's wrong with something breaks because the old ways of looking at networks don't work in a zero trust environment.

[00:21:59] So we're able to take our single agent technology put a product module and they'll be called MPM plus which now looks at networks in a way very different from the past we can look at it from the endpoint in versus from the network out.

[00:22:14] And by doing that customers regain the visibility they lost at a zero trust environment.

[00:22:19] So that's since we give people the best of both worlds they can adopt zero trust for security reasons.

[00:22:23] At the same time they can still keep a zerobility on their network and create something goes wrong they want to understand how to fix it.

[00:22:28] So that's an element to it.

[00:22:31] You know and then from there as I mentioned we'll have more of these types of modules that come out.

[00:22:37] Once you look at your CPU ones that look at unified communications all the big problems you know unified communication is a new problem people face a lot if you're talking about 2025.

[00:22:48] Just like you know world video right now unified communication to me is typically the CEO's on a video call the video goes down who does he call first.

[00:22:56] CIO well and wrong I don't know.

[00:23:00] Those modules address that and fix those problems so the idea is a very comprehensive platform.

[00:23:08] People can start really small or they can start really big whatever they want to do add mix and match whatever works for them.

[00:23:14] But a simplified way to solve what are becoming very increasingly complex problems for people.

[00:23:19] And each so important and our revenue signal listening to your story and I think meaning part of IT or a tech team often feels like that spider map mean with the apps guys are saying it's not it's not the application it's the network and then the network and the network is the third party.

[00:23:36] Everyone's kind of putting each other for that first triple shooting period because that's the way you should be wasn't but he did he's getting better thanks for the tools like this that we're talking about.

[00:23:44] I didn't tell you it hasn't really changed much does I've been on those calls for years and again these technologies are meant to help solve that problem for people.

[00:23:55] And even you know the one that you find surprising is, you know the amount of PCs is still blue screen it's a shocking about people who can access things.

[00:24:06] And again our technology helps fix those and you know one of our UK customers is a national health service and you know they're talking about just missed doctor appointments.

[00:24:15] Because you know if their PCs out now all of a sudden someone's worried about the PC electronic medical records which are very important but if you can't access it it does you know good.

[00:24:24] So literally by using our technology to help eliminate those problems, you know all of a sudden now your doctors are more efficient they can see more people they can help with health outcomes.

[00:24:32] These are very real numbers we're able to measure with them showing that you know just by giving that better solution around observability and deni to identify the problem faster.

[00:24:43] More patients can be seen and you know that's important everybody.

[00:24:48] So that just gives an example of how important this stuff really is.

[00:24:52] And before you came on the podcast I was doing a little research something else I was reading about is the riverbed acceleration portfolio and how that promises agile secure acceleration of applications over any network which feels like a big game change or two.

[00:25:08] So just to bring that to life, can you share add an arcaste study or use case or an example where this is significantly impacted a client's operations.

[00:25:17] You don't have to name any names but is any stores that's been to my.

[00:25:21] Yeah so you know it's very interesting is as we talked about everything always comes back to data.

[00:25:29] Right and the big thing about acceleration is.

[00:25:33] Many times customer cannot move the amount of data they want to move at the speed they want to move it in order to either feed applications even a i for instance you know a i requires a total data as we talk about before.

[00:25:44] And you need to move it very quickly and so that's what our acceleration products do and we've seen that.

[00:25:52] You know with companies like key site technologies an example they they had a big challenge moving data fast enough there will increase their speeds by over 25% just by adding this technology in.

[00:26:04] We see this at a number of both new technologies meaning you know newer written software as well as even legacy software that even some legacy software you can put a fat network pipe or out of without acceleration added to it you won't see the speed that you're looking to see.

[00:26:20] So the market place itself is we're seeing a very strong resurgence in it and I and again I think just driven by the amount of data people are now moving either again new types of applications or some of the more legacy type applications.

[00:26:33] And it for as big as networks get there never big enough and that's what we see with acceleration and it's a business that we've been in for many many years.

[00:26:42] We've been the gardener leader you know for over a decade and coupling the acceleration piece with what we've talked about observability.

[00:26:51] Give us the ability to not only understand what's broken as we've been talking about how do you break it, how do you remediate it.

[00:26:58] But we can also speed things up in the process so we can use that knowledge to figure out how do we apply more speed and make your environment run better.

[00:27:06] And as you said sometimes things have never big enough and I think implementing AI networks an ultimately scales is a significant challenge for many organizations too.

[00:27:17] So, any of you can share around the kind of strategies that you employ to ensure that scalability and effectiveness of your AI driven solutions because I suspect about something that people are asking for your help with a lot to.

[00:27:29] Yeah, you know it's really important you know think about endpoints for a second the it's not uncommon for many organizations to have half a million or more.

[00:27:39] You know if you think about how many desktop's your an organization, how many laptops, how many PCs so are in a single instance our technology scales up to over 800,000 employees per instance.

[00:27:51] So that's large enough to handle the largest organizations in the world and you know we're very proud that we have many, many large organizations out there running our products at scale which I think is critical.

[00:28:02] In the on the AI front.

[00:28:06] We have built a very unique you know patent pending data stores I mentioned and the data store uniquely.

[00:28:14] Can scale with very large amounts of data from all these different points in a very efficient manner I don't want to give too much away but I'll just say it's extremely efficient.

[00:28:24] We designed it to be that way and I think that that solves one of the major barriers people see about AI.

[00:28:33] You might have had some of their folks on the podcast you know back at the day talking about things like Hadoop clusters and you know data warehouses and all these things.

[00:28:45] And what you found is Hadoop although in how a lot of problems you don't see a lot of people actually really running it in production anywhere you know at scale.

[00:28:52] And the reason why it's because it's really hard it's hard to build these large data stores.

[00:28:58] You have to have the right data sources the data has to be you know usable and multi different formats there's all kinds of things that go into yet I can bore you to death though the details I mean it gets kind of boring but it's technically extremely important to really make this stuff real.

[00:29:14] And I and I still believe that's going to be a big barrier for AI adoption and enterprise is just getting the data right so we solve that problem for our customers it's already solved or in our second generation.

[00:29:28] They can use that and again, it works with their data at the same time we can if they want third party data injected to it their choice we can do that as well so it's an open.

[00:29:38] scaleable data store which I think is really critical going forward and I'm curious if I look at riverbed solutions and strategies what do you foresee is the next big challenge or the next big opportunity when you're looking across that.

[00:29:53] That landscape and how you preparing to me is anything that's cool you're interested excitement or keeps you up at night.

[00:30:01] Well, I'm very excited about what we're doing I mean I think that's that's why I was so excited to join riverbed is again a lot of very smart engineers who thought you know who thought it through.

[00:30:10] I've spent my career in products again, you know, I very high market share products either number one server share products that are one.

[00:30:18] Storage share products number two and networking were all ones I developed so I'm very much a product person and when I saw what they're doing around the data store when I saw what they're doing around the platform I was like this is really good.

[00:30:31] And you know and to their credit before I arrived and I wanted to be a part of it and since I've been there we've invested more heavily in R&D.

[00:30:40] And it's all about bringing these technology out to market faster in which we've done we've shipped a record amount of products this year we have a whole bunch more coming next year.

[00:30:49] So we're excited every day because we see how important this challenge is for our customers and we think you know we in our segment of the market so we get into large tech market out there but in our segment of the market which is you know around the end user experience.

[00:31:06] We think we build a very unique solution that solves problems that no one else has.

[00:31:11] But conscious today we've talked about so much about AI where we're going the future but as we reach the end of our conversation I'd love to almost ask you to look back at your career because there is.

[00:31:23] I think it's very difficult for any of us to achieve any degree of success without a little help along the way and sometimes it can be someone that sees something in us in vessel it will time and is anybody like that that's impacted you throughout your career that we could maybe give it a little recognition and a shout out to.

[00:31:41] Yeah lots I named to in particular I started EMC right at a college.

[00:31:48] And the founder of EMC the E if he will is a gentleman by a name of Dick Egan Dick on fortunately his past away but I think Dick never got the credit he deserved he was a true industry legend who had really the foresight of what storage could mean and again storage might not be something that people touch every day.

[00:32:07] But storage what enabled the internet it's what enabled a cloud it's you know again getting all this data in one place you know you had to overcome a lot of technical barriers and that's what EMC specialized in so I joined there is employee one twenty nine.

[00:32:22] And I learned so much from Dick he just knew so much about technology and business and how to scale a business and I think for the people listening out there he was the most customer centric person ever met.

[00:32:35] He gave everybody his home phone number.

[00:32:39] Extension one thousand of the company was his home anybody could pick it up.

[00:32:44] In column and if a customer had a problem he wanted to know and he wanted to fix it and I learned so much from from that and he's want to give him my start.

[00:32:53] And he was also a very interesting entrepreneur in that he as he likes to say he kicked himself upstairs to become a board member and hired CEO to replace him named Mike Rutgers and must.

[00:33:05] Folks want to do that but he did it on his own and Mike Mike really gave me the experience of a general manager he enabled me running software engineering hard engineering supply chain manufacturing customer service quality and emergency acquisitions.

[00:33:19] So he put me in all these jobs over the years so I could learn all aspects of how the business ran and you know that was really an education that.

[00:33:27] You have so grateful for because I use it every day every day every day I remember bed everything I learned through that and both those gentlemen impact me when I was in my 20s.

[00:33:35] And I started at age 22. Mike was my boss by age 25 and you know so between Dick and Mike they really helped launch.

[00:33:45] My own personal career and you know I try and return the favor to the younger folks who work for me over the years.

[00:33:52] Oh, a beautiful story. I think it's so important to recognize this and I suspect that Dick and Mike we thought were to go back into and they wouldn't automatically understand the impact they had on you and your career and also the impact of how you're now spreading it on and sharing everything that you've learned so he goes on and on and on and it's.

[00:34:11] So important to share that and looking forward to be a lot of people listening maybe inspired by our conversation maybe we've a welcome our curiosity.

[00:34:20] They want to find out more information so where's the best place for them to find you or your team online or for I'm more about anything we talked about today.

[00:34:28] Well two places we're Rebecca calm and on there you'll see whole explanations of all these products we spoke about in some customer stories so they can get to know those better if they like.

[00:34:38] And then also on LinkedIn your famous South Carolina I think those are the two best places to find us.

[00:34:43] And I'm testing well love Jay with you today we covered a lot there from the importance of attracting top talent in the sea sweet common board room conversations about AI the CIO priorities and also unified observability is role in addressing IT challenges to deliver that.

[00:34:59] Excellent digital experience that people almost take for granted than expected as standard now but more than anything just thank you for sharing that with me to know.

[00:35:07] It's been a pleasure as Dave highlighted today the future of business technology hinges on embracing AI university our observability and delivering a seamless digital experience.

[00:35:20] And these elements are no longer optional or nice to have their essential for maintaining a competitive edge.

[00:35:27] And I think the insights they've shared about the new Riverbed platform with that cutting edge approach to solving visibility gaps and enhancing user interactions.

[00:35:38] I think they all offer a glimpse into this next wave of technological advancements.

[00:35:44] But if you're interested in exploring these solutions further or connecting with Dave and his team I encourage you to visit Riverbed's online resources but.

[00:35:53] Over to you how are you going to integrate these strategies to propel your organization forward and optimize every aspect of your digital operation.

[00:36:04] That's what we're talking about here you've heard from myself you've heard from today's guest.

[00:36:09] Over to you email me now takeblog right to outlook.com twitter linked in instagram just out now see yous but that's it for today's episode so just a big thank you for listening as always and until next time.

[00:36:22] Don't be a stranger.