Latest / The DEX Show: A Show for IT Change Makers / From Cloud Hype to AI Reality: A MASTERCLASS w/ David Linthicum

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From Cloud Hype to AI Reality: A MASTERCLASS w/ David Linthicum · The DEX Show: A Show for IT Change Makers

0:02
Speaker 1: Hey it change makers, and welcome to the Deck Show
0:05
Speaker 1: with Tom mc grath. Let's get into it. Hello, change makers.
0:13
Speaker 1: So we've now spent as an industry over a decade
0:17
Speaker 1: moving everything to the cloud that we can. At the
0:22
Speaker 1: same time, we've seen digital employee experience become a real
0:26
Speaker 1: priority for organizations, and now layered on top of this
0:29
Speaker 1: complicated picture, we've got a huge wave of AI investment
0:33
Speaker 1: and AI expectations. But across the first and third in particular,
0:39
Speaker 1: there is a similar question that haunts all of this transformation,
0:43
Speaker 1: which is this is everybody getting the value they expected?
0:50
Speaker 1: It's a big question, It's an almost ubiquitous question. You
0:53
Speaker 1: encounter it a lot of the moment. And we're very
0:56
Speaker 1: very happy today to have a guest who's becen of
0:58
Speaker 1: the center of the cloud conversation were generally for decades,
1:02
Speaker 1: and I think can give us some really interesting answers.
1:05
Speaker 1: David Limpick, and welcome to the show. For those I'm
1:09
Speaker 1: familiar with your work, please introduce yourself for us.
1:11
Speaker 2: Yeah, Dave Linthigham, I'm an AI architect and cloud architect
1:15
Speaker 2: by trade. My latest gig, I was a chief Cloud
1:18
Speaker 2: strategy officer Deloitte for about eight or nine years, and
1:21
Speaker 2: prior to that, I was CTO of several consulting firms
1:24
Speaker 2: and technology firms, and you know, just kind of had
1:27
Speaker 2: a long career. Right now, I'm an independent analyst, a
1:30
Speaker 2: slash influencer, got some YouTube stuff going on, podcast stuff
1:34
Speaker 2: going on, and I wrote seventeen books, including my latest two,
1:38
Speaker 2: Unlocking the Power Cloud and An Insider's Guide to Cloud Computing,
1:41
Speaker 2: just published a couple of years ago.
1:42
Speaker 1: Quite the bibliography there, David, Congratulations. And you know, as
1:47
Speaker 1: you just framed it yourself, you've had really a front
1:49
Speaker 1: row seat to the cloud for a long time now,
1:52
Speaker 1: and I was curious to begin with maybe an unorthodox question,
1:54
Speaker 1: which is how your own relationship to that technology has
1:58
Speaker 1: evolved during that period. Has that been perhaps a feeling
2:02
Speaker 1: of disenchantment or where you indeed like always have a
2:06
Speaker 1: very pragmatic, realistic outlook to the cloud and what could
2:09
Speaker 1: be done rather than a sort of idealistic one per se.
2:13
Speaker 2: Yeah, I jumped into it in the nineties, actually wrote
2:15
Speaker 2: a business plan for a company called Project Archangel, which
2:18
Speaker 2: was providing infrastructure, storage, compute, and integration stuff as a service.
2:22
Speaker 2: Couldn't get anybody interested in it, and then I was
2:26
Speaker 2: working for a company as software ag at the time,
2:29
Speaker 2: then worked for a company called macatur and then left
2:32
Speaker 2: after the cat was sold IBM to go work for
2:35
Speaker 2: Grand Central, which was probably one of the first cloud
2:37
Speaker 2: companies out there early days no longer around, and you know,
2:41
Speaker 2: really tried to innovate in the fact that I think
2:43
Speaker 2: that we have something here. If we're able to share infrastructure,
2:46
Speaker 2: we should be able to use it in cheaper, more
2:49
Speaker 2: reliable ways. And now that we have the Internet, we
2:51
Speaker 2: have the ability to do that, and so that was
2:53
Speaker 2: always the focus. So software is a service. Infrastructures the
2:56
Speaker 2: service platforms a service, and you know, grew up that
2:59
Speaker 2: whole And when cloud finally took off in two thousand
3:02
Speaker 2: and nine, when I wrote my first cloud book, I
3:07
Speaker 2: saw a lot of promise in our ability to make
3:10
Speaker 2: this stuff scale. There were thirty cloud companies out there
3:12
Speaker 2: at the time. Believe it or not, every telecon company
3:14
Speaker 2: had a cloud company. Rack Space was not a managed
3:16
Speaker 2: service provider, they were a cloud company. And I thought
3:18
Speaker 2: it was a true shift in terms of how we're
3:22
Speaker 2: going to leverage compute systems moving forward. As I worked
3:25
Speaker 2: through that, I understood there were some realities that people
3:29
Speaker 2: needed needed to understand. Number one, not every work leader
3:32
Speaker 2: data set should be moved to the cloud. We're going
3:34
Speaker 2: to have to look at the data set where they're
3:36
Speaker 2: going to be optimized and best use and moving forward.
3:40
Speaker 2: It was, you know, basically looking at the realities behind
3:45
Speaker 2: cloud computing in terms of the value that it's going
3:47
Speaker 2: to bring back to the enterprise. Current the time, the thinking,
3:50
Speaker 2: the hype was driving everything. Everybody was moving to the cloud.
3:53
Speaker 2: Gartner had said that eighty percent of the people are
3:55
Speaker 2: going to be in the cloud in one year, and
3:56
Speaker 2: everybody's making these bold predictions. And I didn't see it happening.
4:00
Speaker 2: It's too expensive, enterprises can't move that fast and moving forward,
4:06
Speaker 2: I just thought there were some limitations that people should
4:08
Speaker 2: be aware of. And so what I started to do
4:10
Speaker 2: is started to take some realistic takes on it. I
4:13
Speaker 2: was writing and still do the cloud blog on info
4:15
Speaker 2: World and started writing about the value viability and the
4:19
Speaker 2: business viability of the technology. So it has to earn
4:22
Speaker 2: its own keep. And I realized at the time people
4:24
Speaker 2: were lifting and shifting thousands of applications and thousands of
4:28
Speaker 2: data sets in the cloud, and in many cases they're
4:30
Speaker 2: running on those things was two to three times the
4:32
Speaker 2: cost of running it on prem. I said, well, that
4:34
Speaker 2: wasn't supposed to happen. We were supposed to get a
4:36
Speaker 2: significant discount and had reliability and you know, Compex versus
4:39
Speaker 2: Zopek stuff. But that was the case. And as we
4:42
Speaker 2: normalize the industry, he got down to basically three cloud providers, Amazon,
4:46
Speaker 2: Microsoft and Google. I didn't see the prices going down.
4:49
Speaker 2: I didn't see additional stabilization. In fact, if anything, I
4:51
Speaker 2: saw the prices going up. So we had, you know,
4:54
Speaker 2: kind of the joining of companies making I think, bad
4:59
Speaker 2: architectural decision without having understanding the value of cloud in
5:02
Speaker 2: other words, moving workloads and data sets to the cloud,
5:04
Speaker 2: it really didn't belong there. And then the cloud provider
5:07
Speaker 2: is not necessarily getting to good value in terms of
5:10
Speaker 2: the services are able to provide. And that was a
5:12
Speaker 2: recipe for disaster. And so suddenly here we are in
5:15
Speaker 2: twenty twenty six. We have maybe forty to fifty percent
5:18
Speaker 2: of workloads that have migrated to the cloud are migrated
5:20
Speaker 2: to software as the service systems. Many of them are
5:23
Speaker 2: not returning value back to the business. In fact, they're
5:25
Speaker 2: removing value from the business and that's why we're seeing
5:28
Speaker 2: the repatriations that are going now, and also the acceptance
5:31
Speaker 2: is that necessary public cloud is going to be the
5:33
Speaker 2: ultimate destination like it was ten years ago. It's an
5:35
Speaker 2: architectural option we can still use on prem systems which
5:39
Speaker 2: are enormously cheap. Even though hardware is going up in price,
5:41
Speaker 2: they're still a cheaper alternative. Managed service providers, co location providers,
5:45
Speaker 2: other alternatives behind the public beside the public cloud and
5:49
Speaker 2: allow you to an essence, get to a better place
5:53
Speaker 2: with the technology that you're looking to leverage. And now
5:55
Speaker 2: we're into the AI era, everybody's looking to in flag
5:58
Speaker 2: you can consume GPUs Cloud's definitely on the table and
6:01
Speaker 2: kind of it's the easy button for AI, but still
6:04
Speaker 2: two three times more expensive than on prem alternatives, and
6:07
Speaker 2: companies are really kind of making these core decisions now.
6:10
Speaker 2: So I'm focused on that. I'm focused on educating people
6:13
Speaker 2: as to what the value is, where the value is not,
6:16
Speaker 2: and looking at this technology with a bit of a
6:18
Speaker 2: skeptical bent, not necessarily anti cloud, but understanding where it's
6:23
Speaker 2: going to work in areas of the business where it
6:25
Speaker 2: shouldn't be. And I think that's you know, something is
6:27
Speaker 2: typically not said. And you know, it's very much still
6:29
Speaker 2: a cloud computing world. There's a narrative out there that
6:32
Speaker 2: cloud is a way to go, always move to the cloud,
6:34
Speaker 2: cloud only, cloud first, all that kind of stuff, and
6:36
Speaker 2: I've been pushing back against it, but really kind of
6:39
Speaker 2: from a pragmatic architectural bent, not from just kind of
6:42
Speaker 2: a contrarian bent. In other words, I'm pushing back on
6:45
Speaker 2: it if I have data to back it up. And
6:47
Speaker 2: here's why we're doing this.
6:50
Speaker 1: So I'm going to pick up one of the one
6:51
Speaker 1: of the issues you kind of mentioned in passing, which
6:56
Speaker 1: is and ask you why our companies still struggling so
6:59
Speaker 1: much to answer the basic question of what value they're
7:02
Speaker 1: actually getting from clouds and sas aps.
7:07
Speaker 2: I think it's a couple of things. Number One, it's
7:09
Speaker 2: really not known how to do that. And now we
7:12
Speaker 2: haven't had a growth of a discipline called finops in
7:14
Speaker 2: other words, cloud finops financial operations, the ability to determine
7:18
Speaker 2: what this stuff is actually costing us. But very few
7:22
Speaker 2: enterprises out there active in the finops organization. So they're
7:25
Speaker 2: getting their information from two places. Number one, the public
7:28
Speaker 2: cloud providers, which have you know, twenty billion dollars in
7:31
Speaker 2: marketing that they're spending out in the space that are
7:33
Speaker 2: obviously spinning everybody to using the public cloud providers, and
7:37
Speaker 2: also from the consulting firms. Of course I come from
7:39
Speaker 2: that world as well, who are incentivized to move them
7:42
Speaker 2: into the cloud because they obviously make money from change.
7:44
Speaker 2: They also get fees from the public cloud providers, which
7:46
Speaker 2: by the way, they're partnered with, and so listening it
7:49
Speaker 2: from both sidnes, you have some very smart people with
7:51
Speaker 2: very strong personalities that are showing up in the executive
7:54
Speaker 2: conference rooms that are leading them down that path without
7:59
Speaker 2: looking at the realities of it, and so in other words,
8:01
Speaker 2: very much is like an oversimplification of everything you're telling
8:05
Speaker 2: them to move to the cloud, and understanding of what
8:07
Speaker 2: they're moving, what the business objectives are, and not necessarily
8:11
Speaker 2: doing their architectural work to make it happen. Some aren't,
8:13
Speaker 2: most or not, and so it's very easy to go
8:16
Speaker 2: along to get along. In other words, at the end
8:18
Speaker 2: state all your stuff is going to work, Your applications
8:20
Speaker 2: running on the cloud are going to work perfectly fine,
8:22
Speaker 2: You're just going to pay three times as much for them.
8:25
Speaker 2: So there's not this immediate pushback of things failing and
8:28
Speaker 2: the business not working, and so they're making decisions that
8:32
Speaker 2: are financially irresponsible, i think, without looking at the details
8:37
Speaker 2: and not doing the hard work that it takes to
8:39
Speaker 2: make it happen. I'm talking about both sides. The public
8:41
Speaker 2: cloud providers are doing that because obviously they're selling something.
8:44
Speaker 2: Their interest is in to get your workloads and get
8:47
Speaker 2: your data sets into the cloud. And then the consulting firms,
8:51
Speaker 2: which are obviously promoting change, and you know, they're complicit
8:54
Speaker 2: in this as well. So we're not getting the objective
8:57
Speaker 2: third parties out there that are talking about this in
8:59
Speaker 2: ways that I I've been talking about this, and so
9:01
Speaker 2: it's a very unique time that we live in. And
9:06
Speaker 2: now we're looking at AI. AI applications are ten to
9:08
Speaker 2: twenty times as it more expensive than the traditional applications
9:11
Speaker 2: that they would mimic, and in doing so, we have
9:14
Speaker 2: a big decision to make. Are we going to run
9:16
Speaker 2: that stuff in the cloud and pay you know, three
9:18
Speaker 2: times as much? Are we going to run it on
9:20
Speaker 2: prem you know, and pay a discount? Are going to
9:22
Speaker 2: run it in somewhere in between? And I think it's
9:25
Speaker 2: a tough question and quite quite frankly, when you're in
9:28
Speaker 2: the room, you become the designated buzzkill. You raise your
9:31
Speaker 2: hand and go, he you know, shouldn't we really kind
9:32
Speaker 2: of figure out the business case and the value, whether
9:34
Speaker 2: you know this platform should be right or not. I
9:36
Speaker 2: got the public cloud providers on one side and the
9:38
Speaker 2: consultants on the other. I do this for a living now,
9:41
Speaker 2: and they really don't want to hear it because it
9:43
Speaker 2: puts kind of noise against many of their decisions or
9:46
Speaker 2: where they're looking to go. The public cloud providers obviously
9:49
Speaker 2: want the business, so they don't want to talk about
9:51
Speaker 2: other alternatives. And the consulting firms get a fee, you know,
9:54
Speaker 2: from the public cloud provider, so they don't want to
9:56
Speaker 2: do it either. So you're kind of shouted down ultimately
10:00
Speaker 2: based on the number of folks that are out there,
10:02
Speaker 2: and mean, one hundred and fifty thousand people go to
10:04
Speaker 2: reinvent that Google Next is happening this week, There'll be
10:07
Speaker 2: many tens of thousands of people there. They're all cheerleading
10:10
Speaker 2: parties for the cloud, and it's very tough to get
10:12
Speaker 2: above those noise.
10:14
Speaker 1: So I mentioned it if it gives us a deeper
10:17
Speaker 1: visibility into how employees are actually interacting with their technology.
10:21
Speaker 1: Does that present the opportunity to tie cloud and SaaS
10:25
Speaker 1: investments more closely to productivity and I guess experience as well.
10:30
Speaker 2: Yeah, it should, you know, getting to the architectural realities
10:34
Speaker 2: and how much value is going to come back from
10:36
Speaker 2: these things in terms of how employees and other functional
10:41
Speaker 2: entities machines in the company are going to work you know,
10:44
Speaker 2: with these with these technologies. So everything is tied back
10:47
Speaker 2: to the value that comes back to the business now,
10:50
Speaker 2: and it's very weird. It's multi dimensional. I can write
10:52
Speaker 2: a system or basically move to a platform that's going
10:55
Speaker 2: to save me money. However it may become less value
11:00
Speaker 2: if it doesn't provide the agility, if it doesn't provide
11:03
Speaker 2: the scalability, then I need So we always have to
11:05
Speaker 2: look at the you know, how it's going to come
11:07
Speaker 2: back to running the core business processes, dealing with the humans,
11:10
Speaker 2: dealing with the customers. And I always look at that
11:12
Speaker 2: as really kind of the architecture of it. I start,
11:15
Speaker 2: when I build a system, I start with the architecture
11:18
Speaker 2: and then move to the solution. I don't take the
11:20
Speaker 2: solution and move back, you know, move back to the sorry,
11:24
Speaker 2: I started with the business and moved to the architecture.
11:26
Speaker 2: I don't start with the architecture, moved with the business.
11:29
Speaker 2: And it's getting those sorts of things where you're considering
11:31
Speaker 2: how this affects everybody in the organization, including the executives,
11:35
Speaker 2: the employees, and the consultants and the and the and
11:38
Speaker 2: the and the customers. And that's something I think that
11:41
Speaker 2: people are missing right now.
11:42
Speaker 1: And this is another sort of hot topic at the moment, David.
11:45
Speaker 1: Should vendors start to be held more accountable for outcomes
11:48
Speaker 1: rather than consumption? What's your view on VIA I guess
11:52
Speaker 1: sas apocolypse? Is it sometimes going out?
11:55
Speaker 2: Yes, vendors should be held accountable, but they're typically not andally,
12:00
Speaker 2: if you read the agreements that you're signing, they're not
12:03
Speaker 2: responsible for any kind of misuse or misvalue using their technology.
12:07
Speaker 2: But it's concerning to me that we see some of
12:11
Speaker 2: the value being removed from the business by using this
12:14
Speaker 2: particular cloud provider's Cloud vendors SaaS providers infrastructure to the
12:17
Speaker 2: service providers, and there doesn't seem to be accountability. In
12:20
Speaker 2: other words, if I, you know, look at somebody and
12:22
Speaker 2: say what it looks like you've lost ten million dollars
12:24
Speaker 2: by using this technology over the last three years. Why
12:28
Speaker 2: are we not considering alternative technologies moving forward if we
12:31
Speaker 2: known that to be an issue? And and sometimes it's
12:36
Speaker 2: they do listen to reason. For the majority of times
12:38
Speaker 2: they're looking at the devil. They know they're going to
12:40
Speaker 2: work with the technologies. The money doesn't necessarily need seem
12:43
Speaker 2: to be you know, it's an issue. If you find it,
12:45
Speaker 2: they're like, hey, there you go, Dave, you figured it out.
12:48
Speaker 2: But you're not having any kind of recourse or course
12:50
Speaker 2: correcting very little, very few and so. And the cloud
12:54
Speaker 2: providers quite frankly, aren't held accountable because they're part of
12:58
Speaker 2: the narrative out there. You know, they're supposed to be
13:00
Speaker 2: the solution, and so people often don't question what their
13:03
Speaker 2: role is. And I think that's really dangerous because they're
13:06
Speaker 2: allowed to work in perpetuity, charge whatever they want, and
13:09
Speaker 2: not necessarily provide reliable infrastructure to take some of these
13:12
Speaker 2: businesses forward. So it's ask again. It's asking the tough
13:16
Speaker 2: questions that I think people don't want to ask and
13:18
Speaker 2: getting to some of the answers that need to be there.
13:21
Speaker 2: Good news is more people are listening to reason now
13:23
Speaker 2: they're hiring me to audit their projects. They're you know,
13:26
Speaker 2: talking about you know, putting in you know, finnops, cloud
13:29
Speaker 2: finops kind of arrangements to figure out where the value
13:31
Speaker 2: is going to be, and they're doing some of the
13:33
Speaker 2: deep architectural choices to make it happen, but those are
13:35
Speaker 2: still few and far between versus everybody else is making
13:37
Speaker 2: a knee jerk reaction to move to the cloud and
13:40
Speaker 2: kind of hoping for the best.
13:42
Speaker 1: And you've articulated it brilliantly how AI presents a new
13:46
Speaker 1: potential for effectively massive waste, but also does the technology
13:52
Speaker 1: provide somewhat paradoxically with great and means for us to
13:56
Speaker 1: scrutinize value, whether it's a AI app or cloud usage, Like,
14:03
Speaker 1: does the technology allow allow us to identify, for instance,
14:07
Speaker 1: outcomes over consumption better?
14:12
Speaker 2: Yeah? Absolutely, And some of the AI augmented phinops tools
14:16
Speaker 2: out there are brilliant. They just work extremely well and
14:20
Speaker 2: it's able to get to the core patterns and what's
14:23
Speaker 2: leading up to the value. You've got to remember again,
14:25
Speaker 2: value is a multi dimensional thing. It's not just saving money,
14:27
Speaker 2: it's the ability to operate the business in a more
14:30
Speaker 2: optimized way. And the ability to you know, impress the
14:33
Speaker 2: customers so they we grow the customer base, the ability
14:36
Speaker 2: to provide better systems for the employees so we're able
14:39
Speaker 2: to maintain the employees are going to be there. And
14:41
Speaker 2: it's looking at all aspects of this. And so if
14:43
Speaker 2: you have a model that's trained in not only the
14:46
Speaker 2: information of the consumption of the cloud resources, say over
14:49
Speaker 2: the past ten years, where the business is going, what
14:51
Speaker 2: the objectives are, you're more likely to get to a
14:54
Speaker 2: series of corrective actions. Are going to get to where
14:57
Speaker 2: you need to be. It's never going to be you know,
14:59
Speaker 2: the answer is fin you know, it's always going to
15:01
Speaker 2: be a plan and how you're going to implement it,
15:03
Speaker 2: how to make these incremental improvements. And AI is a
15:06
Speaker 2: great weapon to make that happen. Don't ever use it
15:09
Speaker 2: and don't put it into everything. Use human beings still
15:11
Speaker 2: have to make the decision. But if some of these lms,
15:15
Speaker 2: I use them all the time, and you know in
15:16
Speaker 2: my architecture stuff, they're able to lead us into better ways,
15:19
Speaker 2: but they're able to consider massive amounts of data that
15:22
Speaker 2: I can't consider as a human and therefore, use it
15:25
Speaker 2: as a tool, use it to augment your decisions, don't
15:27
Speaker 2: allow it to make your decisions. And it's absolutely brilliant.
15:30
Speaker 1: Amazing, And let's focus in on AI itself and as
15:33
Speaker 1: a potential source of waste or value. You've already painted
15:39
Speaker 1: this picture of organizations and the massive pressure a lot
15:42
Speaker 1: of it kind of financially motivated to transform. But can
15:47
Speaker 1: these organizations or should they be able to better articulate
15:51
Speaker 1: what the ROI is specifically for AI investments, and what
15:55
Speaker 1: should they do to be better able to If they can't.
16:00
Speaker 2: I think it's going to be down to a margin
16:03
Speaker 2: of ERA plus or minus five percent, which is something
16:05
Speaker 2: we haven't hit before. Because if we're going to spend
16:07
Speaker 2: this amount of money, in many cases, there's going to
16:09
Speaker 2: be billions and billions of dollars for some of the
16:11
Speaker 2: global two thousand companies out there. And if I'm sitting
16:14
Speaker 2: on a board, you know, I'm damn well going to
16:16
Speaker 2: want to know how that money is going to come
16:18
Speaker 2: back to me in terms of OROI and when it's
16:20
Speaker 2: going to come back to me in terms of our OI.
16:22
Speaker 2: And you know this, just going for the technology for
16:25
Speaker 2: the technology's sake is something they're not going to accept
16:27
Speaker 2: when you're looking at twenty times the cost. So the
16:30
Speaker 2: cost of these AI systems is so cost prohibitive that
16:33
Speaker 2: we have to pick the right battles to win the
16:35
Speaker 2: war and the ability to look at the incremental improvements
16:38
Speaker 2: we're going to make the systems are going to put in,
16:40
Speaker 2: and how we're going to back that into value that's
16:44
Speaker 2: going to back it into additional profits, additional customer loyalty,
16:48
Speaker 2: you know, something that we can turn into revenue. Now,
16:50
Speaker 2: AI can be a great force multiplier for many businesses
16:53
Speaker 2: out there. I think we're going to have some breakout
16:55
Speaker 2: companies in the next five years where AI really was
16:58
Speaker 2: their catalysts to take them to the next level, you
17:00
Speaker 2: know Allah, you know, Netflix and Uber things like that.
17:05
Speaker 2: But in doing so, we can't invest in everything. They
17:08
Speaker 2: have to biing a out where the investments are going
17:09
Speaker 2: to be made in priority order, and the only way
17:11
Speaker 2: to do that is to figure out the value. So
17:14
Speaker 2: my guidance to everybody is to have a financial viability
17:18
Speaker 2: model done. When you're looking at the stuff, figuring out
17:21
Speaker 2: and estimating where the value is going to come in,
17:22
Speaker 2: look at the risk of not having the value and
17:25
Speaker 2: that has an incremental cost onto itself and then getting
17:28
Speaker 2: to a number you're able to commit to. Now one
17:30
Speaker 2: of the things I do. You know, it's pretty scary,
17:32
Speaker 2: you know, walk into a boardroom and say, well, listen, look,
17:34
Speaker 2: we can generate twenty million dollars in value over the
17:37
Speaker 2: next few years if we move to this particular system
17:40
Speaker 2: and here's how I found out show my work. You know,
17:42
Speaker 2: this would be you know, customer attention that leads into
17:44
Speaker 2: additional sales based on the demographics, the ability to have
17:47
Speaker 2: logistics systems are able to you know, optimize, the ability
17:51
Speaker 2: to get the raw material goods to the manufacturing facility, YadA, YadA, YadA,
17:55
Speaker 2: whatever it is that your business is able to do.
17:57
Speaker 2: But I can put it back to a number that
17:58
Speaker 2: they're likely to see. I don't think we're doing that now.
18:01
Speaker 2: People will just say that's where the value is going
18:03
Speaker 2: to be agile, theyse paint things in very simplistic terms.
18:07
Speaker 2: I think it's the details that matter. And certainly when
18:09
Speaker 2: you're dealing with AI, when you're dealing with ten to
18:12
Speaker 2: twenty times the cost, you're going to put yourself out
18:14
Speaker 2: of business fairly quickly. If you don't pick the right
18:16
Speaker 2: battles to you.
18:18
Speaker 1: There's a sense, David, in which what you're describing, which
18:22
Speaker 1: is all going to transformation, not delivering the dividends organizations
18:27
Speaker 1: expect from it, nonetheless becomes just part of the movement
18:32
Speaker 1: of our technological economy.
18:34
Speaker 2: Do you know what I mean?
18:35
Speaker 1: Like, just because individual companies are rewarded by that, it
18:39
Speaker 1: still becomes an inevitable necessity for the more. I was
18:41
Speaker 1: just wondering what your reflection is on that tension between
18:45
Speaker 1: individual organizational expectations and just the general direction of travel
18:50
Speaker 1: in terms of our infrastructures and such like, and whether
18:52
Speaker 1: it's possible to hang back in any meaningful way if
18:56
Speaker 1: everybody else is searching forward towards what might be unrealizable goals.
19:03
Speaker 2: Yeah, that's the pressure, right, I mean, go to Google
19:06
Speaker 2: next this week and just get which is now an
19:08
Speaker 2: adentic AAI show and just you know, have cheerleaders for
19:11
Speaker 2: three days or four days on agenta GAI and the
19:14
Speaker 2: use of the Google infrastructure and reinvent and Microsoft Ignite.
19:19
Speaker 2: And it's very difficult to say something that's contrary to
19:23
Speaker 2: those sorts of things and saying, right, my business is special.
19:26
Speaker 2: I need to hang back and moving forward too quickly.
19:28
Speaker 2: I think it's going to cause issues because we don't
19:30
Speaker 2: have the right funding to get us to the right
19:33
Speaker 2: point of value, and therefore I'm concerned about moving ahead. Now.
19:36
Speaker 2: Those are decisions, however, that adults make, and you've got
19:39
Speaker 2: to be if you're an executive at a company. I've
19:43
Speaker 2: been an executive many times, you have a responsibility to
19:46
Speaker 2: maximize the return of investment back to the shareholders and
19:49
Speaker 2: obviously the shareholders of the employees and you and you
19:52
Speaker 2: know lots of folks out there, So making those decisions
19:55
Speaker 2: that are financially responsible becomes an imperative, even the ones
19:58
Speaker 2: that don't feel right. It's you're going to make some
20:01
Speaker 2: unpopular decisions that kind of goes against the narrative, goes
20:04
Speaker 2: against the grain, and I think that's what courageous, you know,
20:08
Speaker 2: executives need to do. The ones out there who know
20:11
Speaker 2: how to make these decisions, typically they're the ones that
20:13
Speaker 2: are going to be you know, the most have the
20:16
Speaker 2: most success. But having the fortitude and having the ability
20:21
Speaker 2: to take a detailed look at this stuff and get
20:24
Speaker 2: to the right answers where the risk is going to
20:26
Speaker 2: be lowered as much as possible as you're making mistake
20:29
Speaker 2: is going to be a much better path to do it.
20:30
Speaker 2: I understand you're going to get, you know, criticism from it.
20:34
Speaker 2: I remember my days as a CTO. I would get
20:37
Speaker 2: pressure to move to something like XML back in the days,
20:40
Speaker 2: and I would make a decision not to do it
20:42
Speaker 2: because there's no value there for the technology. I was
20:45
Speaker 2: going to have to spend ten million dollars to put
20:46
Speaker 2: a feature in something. It would actually make the technology worse,
20:50
Speaker 2: but the pressure was to make it happen. I push
20:53
Speaker 2: back on that. You know, I took a lot of
20:54
Speaker 2: grief and arrows for that, but ultimately it was the
20:56
Speaker 2: right decision. And I think people need to get some
20:58
Speaker 2: courage and you know, make some of these things with technology,
21:01
Speaker 2: because right now the bets are getting to a point
21:03
Speaker 2: where you're going to kill the business.
21:05
Speaker 1: Wow. Interesting. How do you think conversely, organizations are approaching
21:11
Speaker 1: the question of AI ROI you've already said it's very
21:14
Speaker 1: it's vague, would be my paraphrase of what you so
21:16
Speaker 1: sketched out. But I mean, what use cases, expectations, or
21:21
Speaker 1: measurements do they have stipulated for what they would consider
21:24
Speaker 1: success presently?
21:26
Speaker 2: I don't think they do I think that I'm just
21:29
Speaker 2: seeing a bunch of confusion out there. I was with
21:31
Speaker 2: a bunch of CIOs last week, you know, at a conference,
21:34
Speaker 2: and they don't know how to articulate or understand what
21:38
Speaker 2: the use cases that they need to pick for the ROI.
21:40
Speaker 2: They know that AI is important, and they're letting it grow.
21:43
Speaker 2: And then the organization now typically around edge edge use cases.
21:47
Speaker 2: In other words, they're giving it to their employees to
21:48
Speaker 2: automate their calendars and automate email responses and you know,
21:52
Speaker 2: do some CRM based stuff tied to salesforce things like that.
21:55
Speaker 2: But as far as what's core to the business, what's
21:57
Speaker 2: going to actually change the business inventory manager, logistics management,
22:01
Speaker 2: sales order entry, things like that that are fundamental to
22:03
Speaker 2: the way the business operates, they don't know how to
22:06
Speaker 2: attack that yet. And that's a fundamental confusion. And by
22:09
Speaker 2: the way, that's why we're seeing people picking the wrong
22:11
Speaker 2: use cases. I mean the MIT study from six months ago,
22:14
Speaker 2: and we've seen other studies that are aligning up with that.
22:16
Speaker 2: Ninety five percent of you know, AI projects out their tank,
22:19
Speaker 2: they don't return OURI. People picking the wrong use cases.
22:23
Speaker 2: People don't understand how much money and time has to
22:25
Speaker 2: be spent on it. They're not necessarily aligning the correct technologies.
22:28
Speaker 2: They're over using AI in many cases, in other words,
22:31
Speaker 2: it shouldn't be used they are. It's costing twenty times
22:33
Speaker 2: as much and they're still failing. So all of that
22:36
Speaker 2: confusion is out there very much more than it was
22:38
Speaker 2: in the cloud. And the cloud we're basically moving to
22:41
Speaker 2: the same infrastructure, but it was replicated as a service
22:44
Speaker 2: with a cloud provider. With the AI system, there's you know,
22:48
Speaker 2: five factorial of decisions you need to make in terms
22:51
Speaker 2: of what use cases, what business cases need to be addressed,
22:54
Speaker 2: how deeply you need to use AI, what AI models
22:58
Speaker 2: where it's agentic or prompt based. All these sorts of
23:00
Speaker 2: things are in line. And be honest with I think
23:02
Speaker 2: most enterprises haven't you know, started that journey yet. In fact,
23:05
Speaker 2: the complaints I hear from the technology providers out there
23:08
Speaker 2: is that they haven't. You know, what do we do
23:09
Speaker 2: to make them move forward? What do we do to
23:11
Speaker 2: you know, get them beyond simple use of LLM, you know, chat,
23:14
Speaker 2: GPT to write letters to their grandma or things like that.
23:17
Speaker 2: And the reality is you've got to get some smart
23:19
Speaker 2: people in there who have some good architectural knowledge to
23:23
Speaker 2: figure out what your business realities are, what you can
23:26
Speaker 2: conceivably do with the technology we have today, and put
23:28
Speaker 2: together a plan to move forward. Those plans typically don't exist.
23:32
Speaker 2: I meet a lot of chief AI officers, and of
23:35
Speaker 2: course they were you know, chief cloud officers two years ago.
23:38
Speaker 2: They just you know, made the change. Everybody's AI watching
23:40
Speaker 2: the resume these resumes these days, and they don't seem
23:43
Speaker 2: to have a clue as to how to do this,
23:46
Speaker 2: and there doesn't seem to be as many people who
23:48
Speaker 2: are seeking advice on how to make it happen. Now.
23:50
Speaker 2: I have the most watched agentic AI Architecture course you know,
23:54
Speaker 2: in the world right now. You know, cool for me,
23:56
Speaker 2: but I would like to see that turn into you know,
23:58
Speaker 2: basically the lessons I teach, and that course turn into
24:01
Speaker 2: actions where the companies are moving in the correct directions holistically.
24:05
Speaker 2: That's not happening. I'm sure in some micro instances they're
24:09
Speaker 2: going to show me where there is some project progress
24:11
Speaker 2: may and they are making many of the good decisions.
24:13
Speaker 2: Those are few and far between, and so we're at
24:15
Speaker 2: a point right now we know AI is important, we
24:18
Speaker 2: don't know what it's supposed to be used for for
24:20
Speaker 2: our particular purposes. We don't understand the use cases, and
24:23
Speaker 2: we don't understand the ROI. But go AI. That's where
24:26
Speaker 2: we are. And you see that cartoon. You know, what
24:28
Speaker 2: do we want AI? When do you want it? Now?
24:30
Speaker 2: What are you going to use it for? We don't know?
24:31
Speaker 2: And that's exactly the world today.
24:34
Speaker 1: And is that a direct parallel with where cloud was,
24:38
Speaker 1: say ten years ago? Is that where you drove a
24:41
Speaker 1: parallel specifically in terms of the stage of transformation and
24:45
Speaker 1: the perspective that could save you money in the future.
24:49
Speaker 2: Yeah, it probably more like thirteen years ago. We're at
24:53
Speaker 2: the same sort of inflection point and there's more on
24:56
Speaker 2: the line with this. So, you know, making a mistake
24:59
Speaker 2: in the cloud, it's going to cost you some additional money,
25:01
Speaker 2: but it's not going to kill you. You know, you're
25:03
Speaker 2: going to have your CFO mad at you because you're
25:05
Speaker 2: spending too much money on the cloud when you told
25:07
Speaker 2: them they were going to reduce money, not increase money.
25:09
Speaker 2: Money spent. The AI stuff is very much making the
25:13
Speaker 2: same types of decisions where we're looking at the advantages
25:17
Speaker 2: of some technologies in front of us that we feel
25:20
Speaker 2: compelled to use or compelled to look at, and not
25:23
Speaker 2: necessarily coming to grips with the realities of what that
25:26
Speaker 2: what that technology can do for us, and the value
25:29
Speaker 2: can be that it's able to bring back. And I
25:31
Speaker 2: saw many people, you know, probably seventy percent of the
25:33
Speaker 2: organizations you know, made lift and shift decisions, taking massive
25:38
Speaker 2: amounts of applications and data and moving into the cloud
25:41
Speaker 2: without an understanding is the rhyme and reason of doing so,
25:43
Speaker 2: and never having any kind of concern about the ROI
25:46
Speaker 2: that's coming back. They just felt it was the right
25:48
Speaker 2: thing to do, and people congratulated them from making the move,
25:51
Speaker 2: and they got to speak at reinvent and they got
25:53
Speaker 2: to you know, to speak to the board of directors,
25:56
Speaker 2: and how amazing that this cloud migration went. I was
25:58
Speaker 2: working on a lot of them at the time. However,
26:01
Speaker 2: what you don't see is three years later when they're
26:03
Speaker 2: looking at the value and the values not there. I
26:05
Speaker 2: think we're going to go through the same thing with AI.
26:07
Speaker 2: I think ultimately people are going to make some tactical
26:09
Speaker 2: decisions how to using this technology, probably what the wrong frameworks,
26:14
Speaker 2: the wrong understanding and getting the wrong advice and they're
26:16
Speaker 2: going to find that many of the mistakes in two
26:18
Speaker 2: to four years are going to come back as value
26:21
Speaker 2: and being removed from the business. And if that's the case,
26:23
Speaker 2: they're going to have to either take corrective action or
26:25
Speaker 2: do what most people did with the cloud. They just
26:28
Speaker 2: didn't talk about it, and it went on for ten
26:30
Speaker 2: years until finally the CFO put his foot down and say, hey, listen, look,
26:33
Speaker 2: move to something else beside data aws, because this is
26:35
Speaker 2: killing us. And I think the same sort of mistakes
26:40
Speaker 2: are happening in slow motion right now.
26:42
Speaker 1: Let's unpack in a little bit more detail than what
26:45
Speaker 1: good ai I might look like in practice. And David,
26:51
Speaker 1: what concretely should you just be measuring And how much
26:55
Speaker 1: of a challenge is visibility when trying to answer us
26:59
Speaker 1: kind of questions and find those kinds of measurements.
27:02
Speaker 2: Yeah, it sho come back as business value, but you know,
27:04
Speaker 2: let me explain what that is. And so, in other words,
27:07
Speaker 2: what's important to us that's going to bring more value
27:12
Speaker 2: back to the business, whether it's revenue increase, valuation, whatever,
27:16
Speaker 2: And typically it's related to how we serve a customer.
27:19
Speaker 2: And so if I'm selling cars, my ability to serve
27:22
Speaker 2: the customer ways that are far advanced as to what
27:24
Speaker 2: my competitors are doing, or from running a pharmaceuticals company
27:27
Speaker 2: or selling carpets, your ability to automate that process in
27:31
Speaker 2: such a way where it's absolutely going to delight the
27:34
Speaker 2: market and provide some key advantages that your competitors don't have.
27:38
Speaker 2: And it's really getting at that with AI. So, in
27:41
Speaker 2: other words, with the addition of AI, how can I
27:43
Speaker 2: delight my customers, How can I optimize my supply chain?
27:47
Speaker 2: You know, all the little friction points they have within
27:49
Speaker 2: a business. How I'm able to do this extremely much
27:52
Speaker 2: better than I could without AI, And what are the
27:55
Speaker 2: fundamental things that need to change and make it happen.
27:57
Speaker 2: Businesses need to look at that. Hearing about things in
28:01
Speaker 2: terms of the edge use cases and analytical stuff and
28:04
Speaker 2: things like that, but it's what your business does. If
28:06
Speaker 2: you're manufacturing something, how you can use AI to optimize
28:10
Speaker 2: that process, supply chain integration, raw material goods sourcing, things
28:14
Speaker 2: in manufacturing optimization, how can you deal with logistics, and
28:17
Speaker 2: how you can deal with the customer customer interface and
28:20
Speaker 2: ways are going to improve your business? And so I
28:22
Speaker 2: would look at it that way. Now if we figure
28:24
Speaker 2: out those ways to improve the business, then I can
28:26
Speaker 2: figure out the metrics and figure how much value is
28:28
Speaker 2: going to come back to the business and say look
28:30
Speaker 2: to a five to ten year horizon. But it's those
28:33
Speaker 2: sorts of things where the questions need to be asked
28:36
Speaker 2: answered before we start moving to the technology where the
28:39
Speaker 2: enterprises are quite confused as to what it is. When
28:42
Speaker 2: I used to talk about agility in terms of a
28:45
Speaker 2: value of cloud computing, which is definitely there, and scalability
28:48
Speaker 2: is really kind of an aspect of agility, no one
28:50
Speaker 2: knew what the hell that meant. They know it's important.
28:53
Speaker 2: But if you're talking to a company that over the
28:55
Speaker 2: next ten years they plan on acquiring five more companies
28:58
Speaker 2: to add to their portfolio, than the cloud is going
29:00
Speaker 2: to have some value because you're able to shift those
29:03
Speaker 2: systems fairly quickly. Because cloud is something you're outsourcing your infrastructure,
29:07
Speaker 2: something somebody else is running and you can do so
29:10
Speaker 2: through configuration, and therefore that's where the value is going
29:12
Speaker 2: to be delivered. We're making those assumptions as to the
29:15
Speaker 2: cloud having value, the values delivered and you're going to
29:17
Speaker 2: make that happen. Same thing with AI, but there's more,
29:20
Speaker 2: much more at risk. So in other words, we're trying
29:22
Speaker 2: to move in a direction that's going to you know,
29:26
Speaker 2: provide us, you know, a business advantage and then figuring
29:30
Speaker 2: out what the advantage is and then figuring out how
29:32
Speaker 2: much money we can make and how much valuable we
29:34
Speaker 2: can make, and how better of a company we can be,
29:36
Speaker 2: even with some of the ethical stuff around it as well.
29:38
Speaker 2: And those are way tougher questions to answer. That's where
29:41
Speaker 2: you get into architecture. That's we can get into business
29:44
Speaker 2: analytics and some of these things that we really should
29:46
Speaker 2: be thinking about. Now. You've got to remember architects stand
29:49
Speaker 2: between the business and the technology, and they're the ones
29:51
Speaker 2: who are on the hook to make the right decisions.
29:54
Speaker 2: Whether those are architects that's run work for a consulting
29:57
Speaker 2: company or work within the organizations, leave the hype back,
30:01
Speaker 2: figure out what you need to do with this, figure
30:03
Speaker 2: out the core advantage is going to have with them
30:04
Speaker 2: in priority, or figure out how much money you can
30:06
Speaker 2: spend realistically over time. Enterprises typically can't move that pass
30:10
Speaker 2: because of the money limitations, and then move forward with that.
30:13
Speaker 2: And that's something that we don't seem to be as
30:17
Speaker 2: interested in now, but I think it's something we should
30:19
Speaker 2: be interested.
30:19
Speaker 1: Now, there's be such a privileged talking to you. And
30:22
Speaker 1: one thing I've always noticed in your work is you're
30:24
Speaker 1: a kind of crusader against hype. You know. That's how I've.
30:28
Speaker 2: Always thought of you, that they needed buzzkills what they
30:30
Speaker 2: normally call.
30:31
Speaker 1: Me designate buzz amazing. So I'm going to ask you
30:34
Speaker 1: a couple of questions just to finish off, about the
30:36
Speaker 1: nature of hype and which point do you see hype
30:42
Speaker 1: in our economy, in our evolution, technological evolution as useful.
30:48
Speaker 1: It clearly drives his adoption right, but it also leads
30:51
Speaker 1: to a lot of bad decisions what's for right balance
30:54
Speaker 1: and does play an important role in things in general.
30:58
Speaker 1: Should we give hypes some credit it?
31:00
Speaker 2: Yeah, I think we should because it gets people interested
31:03
Speaker 2: in change. In other words, if they see something in
31:05
Speaker 2: front of them, they view it as value. Obviously, the
31:07
Speaker 2: hype is generated from the marketing stuff that comes from
31:09
Speaker 2: the technology providers now doesn't come for the press anymore,
31:12
Speaker 2: the tech press. It comes from the technology providers, which
31:15
Speaker 2: basically drive much of the messaging in the tech press.
31:18
Speaker 2: So in doing so, they're open to change because of
31:22
Speaker 2: the hype. They know there's something out there they should
31:24
Speaker 2: be looking at, they don't know exactly what it is.
31:27
Speaker 2: AI is of course the best instance of that now
31:29
Speaker 2: and it gets people to reconsider altering their technology solution
31:34
Speaker 2: to get to a better, more optimized state, and that's
31:36
Speaker 2: what hype is good at. Hype can also be confusing
31:39
Speaker 2: and lead them in the wrong direction, but it gets
31:40
Speaker 2: people you know, out of the office to the conferences,
31:44
Speaker 2: you know, that have these discussions to learn more about
31:46
Speaker 2: what some of the opportunities are now. They also have
31:49
Speaker 2: opportunities to make mistakes. But I think there's something to
31:51
Speaker 2: be said about, you know, pushing action and hype pushes action.
31:56
Speaker 2: People feel like there's a party going on and we're
31:58
Speaker 2: left out if we're not, you know, a part of
31:59
Speaker 2: the hype. And people have a tendency not to want
32:02
Speaker 2: to go against the narratives and are not going to
32:03
Speaker 2: stand up in meetings now and push back on AI.
32:07
Speaker 2: That's obviously it could be a career killer in some organizations.
32:10
Speaker 2: They're going to go along to get along because they're
32:13
Speaker 2: following the hype because they view that's where the zeitgeist
32:15
Speaker 2: is and that's where their success is. Going to be
32:17
Speaker 2: and I understand it by the way I tell my
32:19
Speaker 2: students all the time. You can disagree one time, don't
32:22
Speaker 2: make a habit of it, don't be a designated commission
32:25
Speaker 2: because at the end of the day, people are going
32:28
Speaker 2: to expect you to have a positive look in terms
32:32
Speaker 2: of where this technology is going and not necessarily push
32:34
Speaker 2: back on each piece of it. So you have to
32:36
Speaker 2: kind of play the game. If you're in the enterprise.
32:38
Speaker 2: I don't anymore because I'm retired. You know, I've kind
32:41
Speaker 2: of gotten out of the shooting range of most of
32:44
Speaker 2: the people I work for in the past. But you
32:47
Speaker 2: have to keep a positive view in terms of where
32:51
Speaker 2: the technology is going, where the hype is going, and
32:53
Speaker 2: be able to explain it, but also be able to
32:55
Speaker 2: make the adult decisions as to whether or not you
32:57
Speaker 2: should use it or not. And so I always tell
33:00
Speaker 2: people have a positive look on any technology, cloud AI,
33:03
Speaker 2: things like that. Don't push back on any of it
33:05
Speaker 2: until you understand how it's going to be used, because
33:07
Speaker 2: you don't know it's whether or not it's a solution.
33:09
Speaker 1: For you or not.
33:09
Speaker 2: You just know it's there, and then make sure that
33:13
Speaker 2: you make an adult decision as to whether or not
33:15
Speaker 2: be should be used. And if you're pushing back on
33:17
Speaker 2: some of the stuff, make sure you have the data
33:19
Speaker 2: that instructs people in terms of why you're doing it.
33:21
Speaker 2: I don't show up and say, listen, look, you shouldn't
33:23
Speaker 2: put this in the cloud's you shouldn't put in this
33:25
Speaker 2: the cloud because of this in this reason, So that's
33:27
Speaker 2: going to be ten more thousand dollars a week you're
33:28
Speaker 2: going to have to spend if you make this cloud decision.
33:31
Speaker 2: And so I would recommend that you put it on
33:33
Speaker 2: a colocation provider. But by the way, it would work
33:35
Speaker 2: just as well on a colocation provider as it would
33:37
Speaker 2: in the cloud. Just one's going to cost you ten
33:39
Speaker 2: thousand dollars more a week. What do you want to do?
33:41
Speaker 2: That's the decision. Well, I know what I want to do.
33:43
Speaker 2: I want to leave it, you know, put it on
33:44
Speaker 2: the co location provider and spend less money. But you
33:47
Speaker 2: have to kind of look at it with those sorts
33:49
Speaker 2: of ways. But I never show up pushing back on
33:51
Speaker 2: cloud in general, because that's dumb, because I don't know
33:53
Speaker 2: if clouds are fit for them or not. It's a technology,
33:56
Speaker 2: and technologies don't know what the business problem is they're
33:59
Speaker 2: looking to solve oh if good people have to make
34:01
Speaker 2: that happen, and I think that's where we're losing it now.
34:03
Speaker 2: The technology onto itself is not a strategy.
34:06
Speaker 1: Last question for you, David, do you think anything out
34:09
Speaker 1: Is there anything out there at a moment which is
34:11
Speaker 1: under hyped?
34:13
Speaker 2: Boy, that's a great question. By the way, I think
34:16
Speaker 2: edge computing kind of went through a hype shift and
34:19
Speaker 2: it's under hyped now. Otherwiss I think if many of
34:23
Speaker 2: these AI systems are going to function at the edge
34:25
Speaker 2: and not necessarily in these huge data centers you know
34:28
Speaker 2: that are saturated with GPUs that we're building everywhere around here,
34:31
Speaker 2: and I think looking at that as an architectural option
34:33
Speaker 2: is something people are missing. It's normally something I have
34:36
Speaker 2: to recommend. They go, oh, yeah, the edge computing stuff
34:38
Speaker 2: that was a big deal here a couple of years ago,
34:40
Speaker 2: wasn't it yet? And we kind of missed it after
34:43
Speaker 2: a while because AI took over and everybody's been focused
34:47
Speaker 2: on that and we're going to do AI. People are saying, well,
34:49
Speaker 2: it's going to have to be on big intensive GPU
34:50
Speaker 2: based systems that lives in a data center, not necessarily
34:53
Speaker 2: the case.
34:55
Speaker 1: David, where would you most like people to come find
34:58
Speaker 1: you and follow your work? Yeah?
35:00
Speaker 2: I have two YouTube channels, the Cloud Computing Insider a
35:03
Speaker 2: bit about three hundred thousand subscribers there also, Dave Length
35:08
Speaker 2: is not AI Skeptic and expert and that could be
35:12
Speaker 2: found out as well. Or just find me on LinkedIn
35:14
Speaker 2: just type in my name. There's not too many Dave
35:16
Speaker 2: Length comes around. I'll come up first.
35:18
Speaker 1: Great pleasure having you on a deck show. Thanks so
35:20
Speaker 1: much for coming on.
35:21
Speaker 2: Did thank you.
35:26
Speaker 1: That's it for this week's deck Show. We'll be back
35:28
Speaker 1: next week, and if you don't already, be sure to
35:31
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35:34
Speaker 1: next time.