Latest / The DEX Show: A Show for IT Change Makers / OFFICIAL DEX SHOW END OF YEAR SPECIAL 2024 W/ GEOFF WRIGHT

Transcript

OFFICIAL DEX SHOW END OF YEAR SPECIAL 2024 W/ GEOFF WRIGHT · The DEX Show: A Show for IT Change Makers

0:01
Speaker 1: Welcome it, change makers to the Deck Show with Tim
0:05
Speaker 1: Flower and Tom McGraw. Let's get into.
0:07
Speaker 2: It and change makers. It is the end of twenty
0:13
Speaker 2: twenty four. We hope on the Deck Show that you've
0:15
Speaker 2: had a good year, and we're very grateful for everybody
0:19
Speaker 2: tuning in over the course of this year. And there
0:22
Speaker 2: is only one way that Tim and I like to
0:25
Speaker 2: end a year of Deck Show broadcasting, and that is
0:28
Speaker 2: by welcoming perhaps our favorite. If that's not to you know,
0:33
Speaker 2: you can't really say that, but he's certainly up there.
0:36
Speaker 2: Perhaps he is, and he is well, he has been.
0:40
Speaker 2: He has been on the show more than anybody else.
0:43
Speaker 2: Just let's just cop to that. I think this might
0:46
Speaker 2: be his fifth or sick for appearance, and I think
0:47
Speaker 2: it might be his third end of year show with
0:51
Speaker 2: us in a row.
0:52
Speaker 3: At that time somebody cancels, right? Is that how it works?
0:54
Speaker 3: Every time somebody cancels, you're like, oh God, can we
0:56
Speaker 3: get Jeff on, can we get check on this?
0:57
Speaker 2: I'd love to I'd love to cut you down a
1:00
Speaker 2: bit and say that's true. But sadly, Jeff, sadly, Jeff,
1:03
Speaker 2: this is a this is an illustrious spot.
1:05
Speaker 4: We have you back on the five timer. We've got
1:07
Speaker 4: to get you a five timer jacket. Yeah, exactly.
1:11
Speaker 2: Our end of year show is a special occasion, and
1:13
Speaker 2: there's only I'm just working my way to introduce you here,
1:15
Speaker 2: and there is only one person we think of to
1:18
Speaker 2: get on our end of your show, and that is
1:20
Speaker 2: Mondalze's jeffree right, How you doing, Jeff?
1:23
Speaker 3: Good to see you, man, I'm doing going, man.
1:26
Speaker 2: Excellent, excellent. How has how has twenty twenty four been
1:29
Speaker 2: to you been to you?
1:31
Speaker 3: Sir ah?
1:33
Speaker 2: Dude?
1:34
Speaker 3: I mean, did you guys see the whole thing about Nova?
1:37
Speaker 3: Do you know the Amazon Nova? Do you guys know
1:40
Speaker 3: about Nova? Okay, not the channel? No, So when you
1:44
Speaker 3: get a chance, everyone could google it. But Nova is
1:50
Speaker 3: Amazon's language model, right, It's their AI piece of it.
1:56
Speaker 3: And recently I'm involved with again I I'm doing ax
2:01
Speaker 3: now right. So we're using next thing for nerdy stuff.
2:03
Speaker 3: We're using chatbots for nerdy stuff. I'm like basically making
2:06
Speaker 3: casse roles out of all the technologies that I have
2:09
Speaker 3: right to to make a recipe that's pretty much palatable
2:13
Speaker 3: to most at this company. But we we use Amazon.
2:18
Speaker 3: We're gonna use Amazon Connect and Amazon connect is kind
2:22
Speaker 3: of like the help desk, kind of like thing that
2:24
Speaker 3: they do. It's basically their Q system, but within what
2:27
Speaker 3: with some cool nerdy stuff tied to it. And Nova
2:31
Speaker 3: was announced Jeff Bezos was talking at this New York
2:34
Speaker 3: Times thing if you guys can see that. But basically
2:37
Speaker 3: it's large language models are small language models, depending on
2:42
Speaker 3: what you're doing currently. The biggest challenge is delivering right.
2:47
Speaker 3: They don't. They do cool stuff. You can ask it
2:50
Speaker 3: to write you an email, co politsical stuff, but in
2:53
Speaker 3: the like in the scheme of things, it doesn't you know,
2:57
Speaker 3: it doesn't get you like start to finish great, it
3:02
Speaker 3: doesn't deliver right. You can get stuff through the models.
3:07
Speaker 3: Nova is going to be. Nova's going to be a
3:12
Speaker 3: platform that allows to it'll ingest everything somebody asks at
3:16
Speaker 3: a company. So next thing has you know, a thousand
3:20
Speaker 3: employees every day, a thousand employees paying the chatbot or
3:24
Speaker 3: the you know, the ingestion point for help and they go,
3:28
Speaker 3: you know, in Germany they're looking for the bathroom code.
3:32
Speaker 3: In North America they want to know what our stances
3:34
Speaker 3: on AI. In Latin America, they want to know what's
3:38
Speaker 3: the best price for bananas? Like whatever it is, and
3:42
Speaker 3: it dumps into a delta and it basically starts starts
3:46
Speaker 3: thinking about the answer, so that in very real time
3:50
Speaker 3: or close to real time will probably be like a
3:53
Speaker 3: twenty four hour turnaround. You start getting these palatable answers
4:00
Speaker 3: that solve the issue quickly at your company. So you
4:06
Speaker 3: have this massive data lake of all of the questions
4:09
Speaker 3: that aren't being solved within like a day. By the
4:12
Speaker 3: next day, it's that you have an actionable use case
4:17
Speaker 3: and you have an actionable problem that's being solved from
4:21
Speaker 3: the l M. And there's gonna be man in the middle.
4:24
Speaker 3: I don't know if you guys know the man in
4:25
Speaker 3: the middle concept, Like, you know, it's gonna be like, hey,
4:26
Speaker 3: it starts here and there be somebody like it's probably
4:29
Speaker 3: it's probably gonna be me, you know, guiding guiding it, right,
4:33
Speaker 3: But it's dude, it's man. It's gonna be a crazy
4:37
Speaker 3: couple of years. Hopefully I can retire.
4:40
Speaker 4: So I was actually going to ask you how your
4:41
Speaker 4: NERD career was evolving. It sounds like twenty twenty four
4:44
Speaker 4: is kind of boring for you.
4:46
Speaker 3: No, man, I you know I have I'm in I
4:50
Speaker 3: am in a role here that when I when I go,
4:54
Speaker 3: you know, I went to a I went to a summit.
4:57
Speaker 3: I went to a summit with some nerds. I went
4:59
Speaker 3: to a dome be their big max conference for jen
5:02
Speaker 3: Ai for the image Imagine. And I'm working with Google. Now.
5:05
Speaker 3: We have a GCP stack here that's pretty robust and
5:08
Speaker 3: like it's just I get to kind of like I
5:11
Speaker 3: get to like go into a room with all these
5:13
Speaker 3: different doors, right, and every door is like, you know,
5:15
Speaker 3: it's Amazon, it's Google, it's Mistrol, it's like you know,
5:19
Speaker 3: it's Perplexity, it's it's I get to kind of go
5:22
Speaker 3: into all these cool little spaces and you know, it's Hi,
5:26
Speaker 3: I'm Jeff, and they're like, ah shit, you know, like
5:33
Speaker 3: my my year again. Let's go with March. In March,
5:39
Speaker 3: there was a company called Synthesia. If you guys don't
5:42
Speaker 3: know Synthesia, it is a company that you know, you
5:47
Speaker 3: can click and drag a bunch of stuff like that
5:49
Speaker 3: you have, you know, from training to whatever. It creates
5:53
Speaker 3: an avatar which is really really good, and it translates
5:57
Speaker 3: you into like one hundred and something languages, right, And
6:02
Speaker 3: I didn't really know anything about them. It has exploded
6:06
Speaker 3: at our company, right, and if you think about it,
6:10
Speaker 3: use cases for AI. Everyone's kind of been sitting on
6:14
Speaker 3: the bench going like, you know, I can you know,
6:16
Speaker 3: I could say, you know, draw me a polar bear
6:19
Speaker 3: in outer space, drinking a Coca cola, eating a chocolate bar,
6:22
Speaker 3: floating on a spaceship. Great, we can do that. We
6:26
Speaker 3: can tap into people's creativity that don't necessarily have that
6:30
Speaker 3: side of the brain working as well as others. Awesome,
6:33
Speaker 3: let's do that. But but when it comes, like you know,
6:36
Speaker 3: rubber meets the road, like from like a C suite level,
6:39
Speaker 3: they're like, uh, yeah, we could you know, that's not
6:42
Speaker 3: that big of a deal. But then you say, hey,
6:45
Speaker 3: we're going to do this big SAP upgrade. Right, we
6:49
Speaker 3: have one hundred thousand, two hundred thousand people using SAP,
6:55
Speaker 3: and all of a sudden they go, okay, well we
6:58
Speaker 3: got to translate that. We have like you know, we
6:59
Speaker 3: have fifteen languages spoken. We have people in China, Japan,
7:03
Speaker 3: New Zealand, Australia, Like, it doesn't matter where you are. Okay,
7:08
Speaker 3: what if I told you I could take your thirty
7:11
Speaker 3: five page knowledge based article click drage pick the avatar
7:18
Speaker 3: of your choice. It could even be Jeff. They actually
7:20
Speaker 3: took me to the studio. I have like a Jeff
7:22
Speaker 3: Avatar right like, hey.
7:25
Speaker 2: Yeah, you can do this.
7:28
Speaker 3: It's avatarge out there.
7:29
Speaker 4: You go many mini me.
7:32
Speaker 3: So click and drag that, and now all of a sudden,
7:35
Speaker 3: within minutes, you have your knowledge based article, training article
7:42
Speaker 3: translated into I think. Now it's like a hundred languages
7:44
Speaker 3: they could do. And it's I mean, it's it's I
7:49
Speaker 3: mean it's an explosion of information in a native language
7:53
Speaker 3: around the world at factories training and I mean we
7:57
Speaker 3: have I have I've had people reach out to me
7:59
Speaker 3: they like Jeff, oh my god, Like, do you know
8:01
Speaker 3: we used to have to hire a company and we
8:04
Speaker 3: had a guy that had to verify that spoke Japanese
8:08
Speaker 3: or spoke you know, Portuguese, or spoke brasilient. Then he verified,
8:11
Speaker 3: then he did this, then he did that. Now it's
8:13
Speaker 3: like I have people that are clicking and dragging this stuff.
8:15
Speaker 3: We have security doing it, we have manufacturing safety. Hey,
8:19
Speaker 3: don't put your hand in the oven kind of stuff, right,
8:22
Speaker 3: don't touch that, it's hot. We now translated into one
8:24
Speaker 3: hundred languages, where it used to take sometimes months now
8:28
Speaker 3: it's you know, minutes.
8:31
Speaker 4: Tom listen. Is what I love about having Jeff on.
8:33
Speaker 4: Let me just give you a couple of the notes
8:34
Speaker 4: I made before our call. I was going to ask
8:36
Speaker 4: Jeff how his career was going, how technology was being
8:39
Speaker 4: adopted at his workplace. Were there any big game changes
8:42
Speaker 4: or milestones this year? Was there a big aha moment?
8:46
Speaker 4: Is it more of just more of the same or
8:48
Speaker 4: is this different? He covered it all in like five minutes.
8:53
Speaker 2: Well, I want to know out this avatar, right, So
8:55
Speaker 2: where does the avatar come into it? Is it just
8:57
Speaker 2: like is it like a translated to cool with your
9:00
Speaker 2: avatar up top giving the thumbs up? Or is it
9:03
Speaker 2: does the avatar present the information that just a little
9:06
Speaker 2: more detail.
9:07
Speaker 4: It's a real, realistic human being reading the article.
9:11
Speaker 3: As I say with my son's I like, I'm like,
9:13
Speaker 3: I'm a real human being. I'm a human being. It
9:17
Speaker 3: is it is real facial expressions. Uh again, this is
9:25
Speaker 3: so crazy how fast it's gone. In March, Yeah, in
9:30
Speaker 3: March or April, I had to go into a studio
9:33
Speaker 3: in New York and they did like okay, they you know,
9:36
Speaker 3: full makeup, you know, they were like, okay, we're gonna
9:39
Speaker 3: do this whole thing. It's gonna you're gonna have like
9:40
Speaker 3: the most ridiculous, super awesome jeff Right avatar awesome. Now
9:46
Speaker 3: you just go to the website. You know, basically, you
9:49
Speaker 3: look up, you look to the right, you make expressions,
9:52
Speaker 3: and it eats that up and it just it does
9:57
Speaker 3: it so interestingly enough, I've we just actually had a
10:02
Speaker 3: presentation of my all of my applications. By the way,
10:05
Speaker 3: my next thing training is a syntheia avatar. Cool, and
10:09
Speaker 3: I have it for all of my team because they
10:11
Speaker 3: kept they came asking me like, hey, how can we
10:13
Speaker 3: use next thing tactically blah blah. I like, take your article,
10:15
Speaker 3: I click and drag it. I put it. It's a
10:17
Speaker 3: Jeffryight avatar. And they're like, wow, Jeff this is amazing.
10:19
Speaker 3: I'm like I know, wow. I'm like you know and
10:23
Speaker 3: I and again I'm very emphatic, right, I'm like, I'm
10:26
Speaker 3: like doing this and it uses it does.
10:28
Speaker 4: Your hands like, yeah, it looks and sound does it
10:31
Speaker 4: sound like you?
10:32
Speaker 3: Yes? Now it's even cooler, is I can? Of course
10:35
Speaker 3: the first it's so funny. Great minds think alike. Everybody
10:39
Speaker 3: was like I met the CIO and the CEO, and
10:43
Speaker 3: I don't know the CMO. And there's another guy that's
10:45
Speaker 3: out of he's out of Denmark. Really cool guy, really
10:50
Speaker 3: cool guy kept telling me like the power of the possible,
10:53
Speaker 3: Power the possible. I'm like, ah, I'm like a power
10:56
Speaker 3: the probable guy. You know, I kind of like like
10:58
Speaker 3: I like lower lower my. But this guy was like Jeff,
11:02
Speaker 3: he was like, you don't seem to understand like the
11:05
Speaker 3: like how this is booming into you know anything? You
11:11
Speaker 3: know training at Disney right, Oh, I work at Disney.
11:15
Speaker 3: I want to have like I want to have a princess.
11:18
Speaker 3: I want to have like Star Wars. I want to
11:20
Speaker 3: have the Mandalorian tell me how I don't you know,
11:22
Speaker 3: not to burn your hands in the oven kind of stuff.
11:25
Speaker 3: And it's it's a sanitized version of whatever. Like you
11:30
Speaker 3: talk about customer experience, you talk about experience. Who is
11:34
Speaker 3: the absolute best person for every customer out there to
11:38
Speaker 3: learn what they need to be taught? And it's different
11:41
Speaker 3: for everybody. Tim, you're a big fan of Pink Floyd.
11:45
Speaker 3: Wouldn't it be cool if you had Pink Floyd avatars
11:49
Speaker 3: that sound like them and everything else? Sing you a
11:52
Speaker 3: tune on how you're going to learn. I guarantee you
11:54
Speaker 3: you'll learn it better. Like you know what I'm saying,
11:57
Speaker 3: you'll you'll remember it.
11:58
Speaker 4: Right, it could ruin Pink Floyd's for me.
12:03
Speaker 3: Leave it to you Tim to come up with your jee.
12:07
Speaker 4: Ruin.
12:08
Speaker 3: Get your point though, But it's like hyper customized customer
12:15
Speaker 3: experience giving people. Again we talk about all the different
12:19
Speaker 3: generations which I'm heavily involved in. Right, you're under the
12:23
Speaker 3: age of thirty. You're not gonna want like Uncle Bob,
12:26
Speaker 3: the Uncle Bob avatar. You probably won't want the Jeff
12:28
Speaker 3: Wright avatar. You'll probably be like, you know, you know,
12:31
Speaker 3: like a who's this guy? You know, I'm not saying
12:34
Speaker 3: like you want to make like you know, post Malone
12:37
Speaker 3: or make these famous people whatever, but like there are ways,
12:42
Speaker 3: you know, you know, you know, make this training module
12:45
Speaker 3: for people under the age of thirty and make the
12:47
Speaker 3: avatar have some face tattoos you know, and you know
12:52
Speaker 3: works well with others on their neck. Right, Like whatever
12:55
Speaker 3: it is, you can hyper customize the the avatar for
13:01
Speaker 3: peoples more likely to more likely to ingest the knowledge.
13:06
Speaker 4: So Jeff, let me ask you this. A lot of
13:09
Speaker 4: what we do is to figure out the value of something.
13:12
Speaker 4: What's the ROI Have you thought about calculating the benefit
13:17
Speaker 4: to the business of all of this creative stuff? Is
13:20
Speaker 4: it that you only need to go in the studio
13:22
Speaker 4: once and now you can create all this content without
13:25
Speaker 4: without having to go in the studio again? Is it
13:27
Speaker 4: ROI for faster adoption, faster enablement? What's the benefit?
13:34
Speaker 3: Great question without going into numbers, but it's telephone numbers.
13:39
Speaker 3: The amount of money that I could already calculate we're
13:42
Speaker 3: saving by taking a Jeff Right avatar and putting him
13:48
Speaker 3: in Japanese, Mandarin, Portuguese, Spanish, like you know, you name it.
13:54
Speaker 3: And companies like ours, you know, we have a hard
13:58
Speaker 3: time calculating the value time all. You know, most companies
14:02
Speaker 3: they come in to go. You know, if you write
14:04
Speaker 3: an email and now copilot can write the email for you,
14:07
Speaker 3: like it's see and the numbers always got to like,
14:09
Speaker 3: you know, Microsoft can save you, you know, ten trillion
14:11
Speaker 3: dollars on the amount of times. And most executives they
14:16
Speaker 3: don't really that's not a dish they like to eat
14:18
Speaker 3: because they're like, yeah, but that doesn't put money in
14:22
Speaker 3: the wallet, you know, that doesn't that doesn't that doesn't
14:25
Speaker 3: really hit the road for them. But but for this,
14:29
Speaker 3: you translate. Imagine this, right, you translate a thousand, you know,
14:35
Speaker 3: ten thousand knowledge based articles and you do it in
14:40
Speaker 3: just one click. You have every language. And here's the thing.
14:45
Speaker 3: People like to see something they're familiar with. Right, you
14:49
Speaker 3: want to you know, you want a Asian or you know,
14:53
Speaker 3: I don't know, like New Zealander whatever. You can choose
14:56
Speaker 3: those avatars, and you can customize those avatars. As a
14:59
Speaker 3: matter of fact, I've been asking them for a little
15:02
Speaker 3: bit now, like and again this was just in March.
15:04
Speaker 3: I feel like it's you know, the time is such
15:06
Speaker 3: a funny thing. But what if we did like a
15:09
Speaker 3: sour patch kid right when you like to have a
15:12
Speaker 3: sour patch kid. It could be goofy, it could be cheesy.
15:16
Speaker 3: But whatever helps your employees adapt fast in the next
15:23
Speaker 3: you know, days, months, years, is going to be not
15:28
Speaker 3: even not even like the value, it's going to be
15:30
Speaker 3: like priceless. I talk about companies that are leveraging AI
15:34
Speaker 3: and companies that are like putting a pin in AI
15:37
Speaker 3: because of GRC, because of security, because of the risks.
15:42
Speaker 3: Imagine if you do not, if your company is not
15:46
Speaker 3: leveraging some form of gen AI or like I say,
15:51
Speaker 3: I say Copilot or Gemini or like you know, Meta
15:54
Speaker 3: and Meta whatever, whatever the platform is. If you're not
15:57
Speaker 3: at least giving your employees an opportunity to kind of
16:00
Speaker 3: experiment a little bit, you're not going to give them
16:03
Speaker 3: that ability to upskill and you are going to I
16:07
Speaker 3: feel like it's one of those stories that's going to
16:08
Speaker 3: play out where like C level execs are going to say, man,
16:12
Speaker 3: I really should have done everything I could to rip
16:17
Speaker 3: the knob off of of like all of the not
16:21
Speaker 3: all of the security and compliance, but like, go go, go,
16:25
Speaker 3: go go. Because if this is with AI, if you
16:29
Speaker 3: stop for a minute and go, hey, everybody, we should
16:32
Speaker 3: wait a few months. Let's see what next year brings,
16:36
Speaker 3: You're you're gonna be in the dust. You are going
16:40
Speaker 3: to be so far behind that by the time you
16:44
Speaker 3: expose your employees, the learning curve is going to be
16:48
Speaker 3: so aggressive that you're, you know, the the true assets
16:53
Speaker 3: of your company, the people. I still believe people people
16:55
Speaker 3: process tool. AI is still a tool. It's still number three.
16:59
Speaker 3: I don't belave it's not going to hop in front
17:01
Speaker 3: of humans. You know, we still have like the power button.
17:05
Speaker 3: You know, the one layer that everyone doesn't talk about
17:08
Speaker 3: for whatever reason. And I've been involved in some of
17:10
Speaker 3: these cool stuff, the one layer that goes completely across
17:14
Speaker 3: the horizontal of all horizontal power. If we just you know,
17:18
Speaker 3: if there was a solar flare and all the power
17:20
Speaker 3: goes out, these things are going to rust. AI is
17:22
Speaker 3: going to just stop the data center explodes. That's it,
17:24
Speaker 3: all right, I'll pause there.
17:30
Speaker 4: Yeah, there's a ton ton of digest I don't even
17:32
Speaker 4: know where to take it, jeff I'm having a tough
17:33
Speaker 4: time even just keeping up.
17:35
Speaker 2: Okay, So yeah, fascinating. I love it. Yes, So would
17:39
Speaker 2: you say right, I'm going to interpret what you just
17:43
Speaker 2: what you just said, and it's something that's occurred to
17:45
Speaker 2: me even I've heard echo elsewhere recently. Somewhat the most
17:50
Speaker 2: important use to put AI to presently, in the immediate
17:54
Speaker 2: present is to prepare the ground to allow the workforce
18:00
Speaker 2: who adjust and adapt to AI innovation in the near future.
18:04
Speaker 2: You need to get AI in place to facilitate that
18:08
Speaker 2: process of adoption and adapation.
18:10
Speaker 4: And could you.
18:13
Speaker 2: I was going to say, just last add to the question, Jeffrey,
18:17
Speaker 2: then you can do the whole thing can you give
18:20
Speaker 2: us some like concrete examples of where you think that
18:23
Speaker 2: adaption is going to be most pressing for from your perspective,
18:28
Speaker 2: as you know, as the you know, you're basically facilitating
18:34
Speaker 2: employee digital experience across an organization such as yours, where
18:38
Speaker 2: you want them to have that layer of support where
18:40
Speaker 2: you think you will.
18:44
Speaker 3: You know, I've said there's so many different spaces for AI,
18:48
Speaker 3: and I think the word AI is it's so inflated
18:51
Speaker 3: and people get confused. If you don't expose the people
18:57
Speaker 3: that need to at least understand the technologies now at
19:03
Speaker 3: your company, it's going to be intellectual atrophy. You know,
19:07
Speaker 3: we talk about brain drain with people retiring, we talk
19:09
Speaker 3: about new people that are coming on. You know, we
19:13
Speaker 3: spend a lot of time at work. We spend a
19:16
Speaker 3: lot of time at work and a lot of us
19:18
Speaker 3: it's I often have a I often I often find
19:22
Speaker 3: myself forgetting that I'm in this like we you tip do.
19:29
Speaker 3: We're in the IT bubble. We're here. And when you
19:35
Speaker 3: talk to some folks that aren't in it right market
19:38
Speaker 3: is like just just anything else, they go really like
19:42
Speaker 3: I assume everybody like I assume everybody saw Jeff Bezos
19:45
Speaker 3: talk yesterday, right, I'm like, I'm like, oh god, you
19:46
Speaker 3: didn't talk about your and they're like Jeff no, who, Like,
19:48
Speaker 3: oh the Amazon guy, what is he sending packages? Is
19:50
Speaker 3: the Christmas thing? Is the Christmas report? They they're so
19:53
Speaker 3: out of it. So I find myself like coming back
19:55
Speaker 3: going like oh, okay, so we're using copilot, like what's
20:00
Speaker 3: the use case? Where's the value? And I really do
20:03
Speaker 3: hate the word value sometimes because I feel like it's
20:05
Speaker 3: been so god, it's been like ram jammed into everything.
20:10
Speaker 3: Like you go to Burger King, you know the value meal.
20:12
Speaker 3: You know, like everything's got value to it, and it's
20:15
Speaker 3: like it's kind of like lost its meaning because when
20:17
Speaker 3: you try to like oh this has this kind of value,
20:20
Speaker 3: everybody has a different definition of what value is. So
20:24
Speaker 3: I think if you say, like, forget the value for
20:25
Speaker 3: a minute, let's just talk about how what does it
20:28
Speaker 3: do for you? People could be selfish, right, So I'm like,
20:31
Speaker 3: forget the value. I want to help you. Let me
20:34
Speaker 3: ask you how long does it normally take you to
20:35
Speaker 3: do an RFP. Well, you know, they asked us to
20:38
Speaker 3: do this thing, and we're trying to get different cocoa
20:40
Speaker 3: prices and we're trying to like, you know, we're trying
20:42
Speaker 3: to get like a chocolate bar on Mars, and you know,
20:44
Speaker 3: here's all this stuff. I'm like, okay, Well, if the
20:48
Speaker 3: RFP normally took you, you know, weeks, probably right weeks,
20:54
Speaker 3: maybe even like a month, depending on how robust that
20:56
Speaker 3: RFP was with you know, with copilot for PowerPoint. And
21:02
Speaker 3: I have to tell you, if you guys haven't used it,
21:05
Speaker 3: it will it'll ingest what you got. If somebody says, hi, Tim,
21:09
Speaker 3: I want to have an RFP for these things, boom boom,
21:12
Speaker 3: boom boom, it gives you a hell of a wire.
21:16
Speaker 3: Like you copy and you paste that into PowerPoint and
21:20
Speaker 3: it's like, hey, what do you think of this? And
21:22
Speaker 3: before you know it, what used to probably take you
21:24
Speaker 3: at least a week and a lot of churn with
21:27
Speaker 3: people around you to get exactly what you were trying
21:31
Speaker 3: to pinpoint, you have a pretty darn good ninety plus
21:35
Speaker 3: percent PowerPoint presentation for your customer. Right that used to
21:40
Speaker 3: take you weeks and now it takes you minutes. I
21:43
Speaker 3: mean it's clicking, drag. It looks in your inbox, it
21:45
Speaker 3: takes all the emails from the customer that said, hey,
21:46
Speaker 3: we want to have you know, we're looking for something
21:48
Speaker 3: to be this cool. Great, and now you have a
21:54
Speaker 3: fast again. Now it's to market. Right now, it's you
21:57
Speaker 3: have an extremely quick, nice, nicely polished reviewed RFP that
22:03
Speaker 3: you can send to your customer. Whereas the people that
22:06
Speaker 3: aren't leveraging it are going like, oh my god, how
22:08
Speaker 3: did you know? How did Tim's team put that together
22:11
Speaker 3: so quick? Right? How amazing? I mean I have a
22:15
Speaker 3: great friend of mine that works in an engineering firm,
22:17
Speaker 3: like you want to talk about RFPs that will put
22:20
Speaker 3: you asleep. It's just engineering stuff with all of the
22:23
Speaker 3: detail and stuff. But now if you if you plug
22:26
Speaker 3: AI into it, which they some of the big companies
22:28
Speaker 3: are right your A comms your parts like they're doing it.
22:32
Speaker 3: They have these RFP like now that you know it
22:35
Speaker 3: used to take months and I mean that they like, Jeff,
22:38
Speaker 3: it used to take us months and now it takes
22:40
Speaker 3: us minutes.
22:41
Speaker 4: Do you think there is an and I don't know
22:44
Speaker 4: what the right descriptor is ethical moral requirement to disclose
22:50
Speaker 4: that AI contributed to the output.
22:56
Speaker 3: That's a good question, Tim.
23:01
Speaker 4: In certain fields, I think there is like authorship, you know,
23:06
Speaker 4: I use it as my editor, make my content a
23:08
Speaker 4: little bit more readable. Uh, maybe prompt some ideas that
23:12
Speaker 4: are that are deeper in my brain. But that brings
23:14
Speaker 4: it to the surface, and there I feel a need
23:16
Speaker 4: to say, hey, you know what, I have a partner
23:19
Speaker 4: in this. Uh, it doesn't need to be a human
23:22
Speaker 4: in this case. It's a I'm curious in the even
23:24
Speaker 4: just in that one narrow use case the RP.
23:34
Speaker 3: Yes, I do. But in almost in a funny kind
23:38
Speaker 3: of way, like you know how we all when when
23:39
Speaker 3: auto correct, when auto correct on the iPhone like kind
23:42
Speaker 3: of came out and like people would have like sorry
23:45
Speaker 3: for the response, you know, autocorrect might have helped, or
23:48
Speaker 3: you know, please, you know, please be mindful if anything
23:51
Speaker 3: I just said, like is misspelled or stupid. You know,
23:53
Speaker 3: autocorrect helped. But but I think it's almost that's it's
23:59
Speaker 3: almost more of a legal kind of thing because then
24:02
Speaker 3: it talks that you talk about liability and again I'm
24:05
Speaker 3: not a lawyer, but we but we boy with AI.
24:08
Speaker 3: I've been dealing with a lot this year. I've dealt
24:11
Speaker 3: with attorneys way more than I ever have in any
24:14
Speaker 3: other job actually, at any other point in my life.
24:18
Speaker 3: This year. I've been talking with counsel a lot because
24:21
Speaker 3: of gdp R, because of the German Work Council, because
24:24
Speaker 3: of some of the laws like in Europe. I believe
24:27
Speaker 3: if you if you replace, if you replace of a
24:31
Speaker 3: human process with AI, you have to report it. There's
24:35
Speaker 3: like the European Union has some laws. So you know,
24:40
Speaker 3: I'm always a big fan of like being open, being
24:42
Speaker 3: transparent and getting in front of it. So I would
24:46
Speaker 3: say that if you're going to do an RFP, that
24:48
Speaker 3: you should put like, hey, you know something like this
24:52
Speaker 3: RFP was was assisted by AI to help better fit
24:56
Speaker 3: the proposal to our customer. True, I can'tine here putting
25:02
Speaker 3: the other hat on Tim. If you're the customer, are
25:05
Speaker 3: you up? Would you be insulted or upset about that?
25:12
Speaker 4: No? I think you're right on it's more on the
25:14
Speaker 4: liability side. It's more on the full disclosure versus offending
25:20
Speaker 4: a customer. But it is a good question.
25:27
Speaker 2: It is another another question, another similar to Tim's, this
25:33
Speaker 2: time with relation to productivity, Jeff. Which is I assume
25:37
Speaker 2: is that it's the sort of metapheme, if you will,
25:39
Speaker 2: that's getting the attention of your c suite around this technology.
25:43
Speaker 2: And you're talking about kind of you know, we all
25:45
Speaker 2: see it to whatever degree we engage with AI, but
25:49
Speaker 2: it really super charges productivity. Do you think there's a danger,
25:53
Speaker 2: as it were, of almost making us excessively productive, by
26:01
Speaker 2: which I mean we outpace ourselves in what needs to
26:04
Speaker 2: be done.
26:05
Speaker 3: So just so you guys know, like I you next
26:08
Speaker 3: thing in general has helped me kind of like pivot
26:12
Speaker 3: what I already what I already always knew. I am
26:15
Speaker 3: always thinking about the experience now like I always want
26:20
Speaker 3: to know the employee's experience, the customer's experience, the people's experience,
26:25
Speaker 3: Like I just I want it to be I want
26:29
Speaker 3: ultimately to to to bring about some form of happiness
26:33
Speaker 3: or a smile in my role here period.
26:36
Speaker 4: Right.
26:38
Speaker 3: And I've had this question come up before where people
26:40
Speaker 3: are asking me about, oh, if AI starts, you know,
26:45
Speaker 3: pushing productivity, and if they're if it's able to help
26:48
Speaker 3: people like do more with less, and are we going
26:51
Speaker 3: to stress people out? And are we going to have
26:55
Speaker 3: like yeah, like the redundancy are we gonna show like
26:56
Speaker 3: all these are all these things going to like just
26:58
Speaker 3: play out where it's like, you know, it's the matrix, right,
27:01
Speaker 3: It's it's the terminator scenario. And I'm bullish on humans
27:06
Speaker 3: in the sense that I believe that it's going to
27:09
Speaker 3: be it's going to be where AI gives people the
27:16
Speaker 3: twenty hour work week that we all probably want, and
27:21
Speaker 3: that is going to only lead to companies being more successful.
27:25
Speaker 3: And you know, because of talent. As things scale, like
27:30
Speaker 3: the talent that they have will be able to do
27:33
Speaker 3: better stuff, better things and have more time to themselves
27:38
Speaker 3: to be creative and do better things outside of work, right,
27:42
Speaker 3: And that's only going to lead to a company to
27:45
Speaker 3: be that the you know, the blueprint, right, the idea
27:50
Speaker 3: of like you know, the four day work week, three
27:52
Speaker 3: day work week, you know, like like all this stuff,
27:54
Speaker 3: Like if you have an incredible workforce, or let's just
27:58
Speaker 3: say even a mediocre workforce, and you're able to give
28:00
Speaker 3: them more time to do what they love outside of
28:04
Speaker 3: work by leveraging AI, you're going to have smiles on
28:09
Speaker 3: their faces. You're going to have people happy.
28:12
Speaker 4: It's a slippery slope though, right, I'm going to play
28:14
Speaker 4: the other side of the coin for you, Jeff, we
28:17
Speaker 4: work a twenty hour work week, We're getting into trickle
28:20
Speaker 4: down economics, right, Are we paid for a twenty hour
28:23
Speaker 4: work week and can we survive on that or will
28:25
Speaker 4: the companies actually provide us with a quality of life
28:30
Speaker 4: based on the productivity that we've given the company we
28:33
Speaker 4: work for. Not a question to be answered, but pondered. Right,
28:41
Speaker 4: it's all on you. You hold the keys to the future.
28:45
Speaker 3: Yeah, I you know. It's like, here's the thing. We
28:48
Speaker 3: all have to put these those hats on right, So
28:49
Speaker 3: like put your tim put your put your CEO hat
28:54
Speaker 3: on right, put your border director's hat on and ask yourself,
28:59
Speaker 3: if you knew that, what are you more concerned with
29:02
Speaker 3: the hours worked or the quality of work? It's a
29:05
Speaker 3: it's a million year old question. Would you rather have
29:07
Speaker 3: one hundred people working on a boat that are like,
29:10
Speaker 3: you know, half ass in it or ten guys that
29:12
Speaker 3: can bust it out better than ever and do it
29:15
Speaker 3: in ten minutes?
29:17
Speaker 4: What do you have to work? So the CEO and
29:19
Speaker 4: the board of directors want forty hours worth of work
29:22
Speaker 4: in twenty hours, and if I can cut my labor
29:25
Speaker 4: costs in half, I'm going to do it.
29:29
Speaker 3: Yeah. But I think with human nature, then you have
29:31
Speaker 3: people that are it is it's it's I feel like
29:36
Speaker 3: it's a that's a then you'll have people that wanted
29:40
Speaker 3: that could do twenty hours worth of work that stretch
29:43
Speaker 3: it to forty. I feel like human human nature will
29:48
Speaker 3: always find a way to fit what they need to
29:50
Speaker 3: do to like check the box. So board of directors like,
29:55
Speaker 3: we want forty hours worth of work in twenty work
29:57
Speaker 3: work work, work work humans if they're not, if they're
30:02
Speaker 3: not doing what they want to do or love to
30:04
Speaker 3: do or it's enjoyable to do, right, Like gamifying, that
30:08
Speaker 3: was like a big thing that came up this year.
30:09
Speaker 3: I'm sure we've all heard that. Gamify it, Gamify training,
30:12
Speaker 3: Gamify learning, gamify your email, gamify this, and you know what,
30:16
Speaker 3: it has legs because if you make it fun, if
30:20
Speaker 3: you make the work not always brutal, you get way
30:25
Speaker 3: more with way less. So if the board and the
30:29
Speaker 3: CEOs are going, we want we want more with less,
30:34
Speaker 3: and you're like, dude, I could do less with more.
30:37
Speaker 3: The board and this dude, the board and the sea
30:39
Speaker 3: level execs at some point in time are going to
30:42
Speaker 3: lose those good employees to companies that see it the
30:47
Speaker 3: other way.
30:48
Speaker 4: Yeah, the the market will in theory, the market, the
30:52
Speaker 4: employment market would fix itself.
30:55
Speaker 3: Yes, I mean my buddy works at Amazon. My brother
30:59
Speaker 3: wors some microsfot But I have so many friends that
31:01
Speaker 3: work at the super you know, the super elite, I
31:03
Speaker 3: say elite, the big it companies, right, and you know
31:07
Speaker 3: there's always like, oh, return to office. Oh we're doing
31:10
Speaker 3: return to office. And the smart people go like, dude,
31:14
Speaker 3: this is just a riff in reverse. Right, they're trying.
31:19
Speaker 3: They can't just do a mask. They're going to say
31:21
Speaker 3: who wants it? Who wants it? Who wants to drive
31:25
Speaker 3: two and a half hours into midtown? Who's hungry?
31:31
Speaker 4: Right?
31:32
Speaker 3: And look the twenty something year old people that I
31:35
Speaker 3: talked to in my office that are like, Jeff, you
31:37
Speaker 3: know how much a condo is in like the hood.
31:40
Speaker 3: It's like half a million dollars? Right, right, Like do
31:43
Speaker 3: you have the cheapest thing? You know, it's like the
31:46
Speaker 3: cheapest thing to find. I mean, you guys are in well,
31:48
Speaker 3: you're in you're in Pa, even God, even Pa doesn't
31:51
Speaker 3: matter where you are now. It doesn't matter where you
31:54
Speaker 3: are unless you're in like a Coleman tent in South Dakota.
31:58
Speaker 3: And that's probably like, you know, been in a.
32:00
Speaker 4: Content in South Dakota.
32:01
Speaker 3: But but it's like it's expensive. So when you have
32:07
Speaker 3: those it's interesting. It's like that catalyst. We have plenty
32:11
Speaker 3: of people that are in their mid to late twenties
32:13
Speaker 3: in the office that are you know, they make a
32:16
Speaker 3: good living, but they still live at home. And you know,
32:21
Speaker 3: they ninety nine percent of them don't want to live
32:25
Speaker 3: at home, but they're saving money to get that first
32:29
Speaker 3: foot in the door to that you know, nine hundred
32:32
Speaker 3: thousand dollars half bedroom studio, you know, with like a toilet,
32:38
Speaker 3: a sink, a kitchen, a refrigerator, all within three feet
32:41
Speaker 3: of each other.
32:42
Speaker 4: Right, Yeah, I struck up a just anecdota. I struck
32:45
Speaker 4: up a conversation yesterday with a guy sitting at a
32:47
Speaker 4: bar at the airport and he said, man, I am
32:50
Speaker 4: so not looking forward to going back to San Diego.
32:53
Speaker 4: And I looked at him, I said, said, no one
32:55
Speaker 4: ever I've been to San Diego and within ten minutes
33:01
Speaker 4: I want to live there.
33:02
Speaker 3: Yeah.
33:02
Speaker 4: It's beautiful, Oh it's beautiful. I can't afford anything, though,
33:06
Speaker 4: It's so expensive to live in the city. And almost
33:09
Speaker 4: every city is like that, though, Atlanta, Chicago, La, no
33:12
Speaker 4: matter what, New York, Boston tried living in Boston.
33:15
Speaker 3: I know, well, you guys have it. Boston has those
33:18
Speaker 3: think tanks. So you know, as soon as those you know,
33:21
Speaker 3: as soon as those big schools have people that graduate.
33:24
Speaker 3: You know, even if you go with like the one
33:26
Speaker 3: percent one percent of the population of those people graduating
33:28
Speaker 3: with those degrees are smart and got them and can
33:31
Speaker 3: hopefully get the money and knock out the rest of
33:34
Speaker 3: the people. It's it's you know, for Austin, Austin's like Texas,
33:38
Speaker 3: which is Texas is weird in a sense because it's like,
33:42
Speaker 3: you know, you could get a ranch and you know,
33:45
Speaker 3: in the middle of nowhere, but for a good but
33:49
Speaker 3: where do you go. You have to like you have
33:51
Speaker 3: to have like a jet pack.
33:54
Speaker 4: Or you're on oil well in the backyard.
33:57
Speaker 3: Yeah, I mean, I was surprised. We have a lot
33:59
Speaker 3: of cop colleagues that are going to Austin because Austin
34:03
Speaker 3: just seems to be a hot place. But it's like,
34:07
Speaker 3: you know, it's expensive. Austin's like you said, Austin's expensive.
34:11
Speaker 3: At Landa is expensive. Charlotte forget North Like, dude, North Carolina.
34:16
Speaker 3: It used to be like value. Oh hey, you could
34:18
Speaker 3: go to Charlotte get a good price. Yeah, Nope, you know, Miami, Fluck, Florida, Arizona.
34:26
Speaker 3: I mean I know people that have bought places and
34:28
Speaker 3: reload to Lake Tahoe. The Nevada side, like like I
34:34
Speaker 3: think it's called Inclined Village. If you guys know Inclined Village.
34:38
Speaker 3: It's it's interesting because he bought the place for a
34:41
Speaker 3: half a million dollars. It's two bedroom condo, and he's
34:45
Speaker 3: from he's from the North Carolina area, and he got more,
34:48
Speaker 3: more money and more value, more whatever for going to
34:52
Speaker 3: that place because there's no income tax. Nobody told them
34:55
Speaker 3: that you can get you know, twelve to fifteen feet
34:58
Speaker 3: of snow, which I don't know how, right, how how
35:03
Speaker 3: somebody gets up. I mean a single guy gets up,
35:07
Speaker 3: leaves his house with his family, right, he was like
35:09
Speaker 3: staying with his parents, left his family to buy a
35:12
Speaker 3: place in Inclined Village and didn't like google like snow
35:17
Speaker 3: or like.
35:18
Speaker 4: A right climate weather anything.
35:21
Speaker 3: Like he was like, dude, you know they get like
35:22
Speaker 3: ten feet of snow here, And I'm like yeah, yeah, dude,
35:26
Speaker 3: like Sierra Nevada, like you're you're in the You're like
35:30
Speaker 3: you're like ten thousand feet.
35:31
Speaker 4: Let me ask one question, Tom, because I think that
35:34
Speaker 4: other than the trend of prices and weather and all
35:37
Speaker 4: that stuff, what do you see as a trend right
35:39
Speaker 4: now heading into the next year. We've talked a lot
35:42
Speaker 4: about what we like, when cool. What do you see
35:43
Speaker 4: happening that you don't like that you don't think we
35:46
Speaker 4: should continue down that maybe we need to reverse.
35:51
Speaker 3: Well, you can't reverse anything anything in ninety right, But yeah,
35:55
Speaker 3: but where where? Where where do you redirect? Where do
35:57
Speaker 3: you start moving away from the jen Ai stuff? So
36:03
Speaker 3: you know, we all saw like again last year into
36:06
Speaker 3: the beginning of this year, the copywriting, the shutterstock, the
36:11
Speaker 3: all of this jen all of the image generation through
36:14
Speaker 3: from all the different platforms. I can't even name half
36:17
Speaker 3: of them, but there needs to be intellectual guidelines around
36:23
Speaker 3: how you're using other people's stuff. Music is one of them.
36:29
Speaker 3: I feel like the you know, if you guys haven't
36:32
Speaker 3: seen it, you know, make me a cool song that
36:34
Speaker 3: sounds like you know, Johnny Cash, but like with my
36:38
Speaker 3: voice and yeah and man it makes a great tune.
36:43
Speaker 3: And you know, all of the people like you know
36:46
Speaker 3: Johnny Cash, all you know, Elvis Presley. The people that
36:49
Speaker 3: have the money can throw the lawyers at it and
36:51
Speaker 3: say that's Elvis Presley in my voice. You're sued. But
36:56
Speaker 3: there's a lot of there's a lot of up and
36:58
Speaker 3: coming artists. There's a lot of up and coming vocalists,
37:03
Speaker 3: musicians that on Reddit and a lot of other forms
37:08
Speaker 3: are constantly going like did everyone forget that we're just
37:12
Speaker 3: having our stuff stolen? Like just it's the days of
37:14
Speaker 3: It's Napster again, remember Napster in Lime time, and like
37:17
Speaker 3: people just start downloading music for you know, not for free.
37:20
Speaker 3: I mean they're just stealing stuff.
37:22
Speaker 4: Or sampling, even sampling in a song without credit.
37:25
Speaker 3: Yeah, this AI is not an excuse to start stealing
37:30
Speaker 3: people's IP. And it's unfortunate right now, even the best attorneys.
37:37
Speaker 3: I have a close friend and colleague that's in the
37:40
Speaker 3: Palo Alto area, so like Silicon Valley, they're really into
37:43
Speaker 3: this whole ip thing around music. And the question is,
37:49
Speaker 3: you know, he made a great example if you take
37:52
Speaker 3: and copy and if you copy and paste Moby Dick
37:56
Speaker 3: into like chat shept the entire novel and then say
38:00
Speaker 3: write this in a steampunk kind of style and change
38:04
Speaker 3: the characters from a whale to this and about you
38:07
Speaker 3: know that, and it spits it out and you go
38:11
Speaker 3: to the attorney and they go, look, by law, IP
38:16
Speaker 3: has to be like more than seven. They have to
38:18
Speaker 3: prove more than seventy percent. Right, So you can actually
38:20
Speaker 3: even tell chat GPT make it sixty nine percent of
38:25
Speaker 3: the book and change at will make it funny whatever.
38:30
Speaker 3: And now you just rewrote Moby Dick in a different
38:33
Speaker 3: kind of context.
38:35
Speaker 2: Gentlemen, gentlemen, We've got We've only got so many We've
38:39
Speaker 2: only got so many minutes left, gentlemen. And I have
38:41
Speaker 2: I have loved a conversation so far. We've gone very,
38:45
Speaker 2: very broad, and I just want us to narrow it
38:47
Speaker 2: down a little bit. Jeff, you gave us a glimpse
38:49
Speaker 2: of that big milestone in March, and I'm just wondering,
38:53
Speaker 2: where have you seen, final theme, final topic, final riff.
38:57
Speaker 2: Where have you seen the most innovation this year in
39:00
Speaker 2: actuality that you've been able to deploy, that you've seen
39:03
Speaker 2: results from, specifically around digital employee experience and the U see.
39:09
Speaker 2: Where have you seen the most real time advancement?
39:11
Speaker 3: I mean it's sentiment, right. The sentiment campaigns and the
39:15
Speaker 3: sentiment stuff that we've been sending out has kind of
39:18
Speaker 3: given me a completely different keyhole view into like the
39:22
Speaker 3: the planet my organization at least, you know, every god
39:28
Speaker 3: every month, I always feel like I have a better
39:30
Speaker 3: grasp on what people are feeling about it, and I'm
39:34
Speaker 3: always wrong. I'm always wrong. It doesn't now Again, I
39:39
Speaker 3: always use this word globular, right, we just sent out
39:42
Speaker 3: our are we just sent out our yearly or like
39:45
Speaker 3: our bi yearly campaign for employee sentiment. And I'm always like, hey,
39:50
Speaker 3: we're killing it over here in Latin America. And it's
39:53
Speaker 3: like now everyone said that this was broken and I'm like, well,
39:56
Speaker 3: this says it's good. No, that's broken.
39:58
Speaker 4: Right.
39:59
Speaker 3: So I'm always rebaselining what the globe, what what different
40:04
Speaker 3: regions of the planet Earth feel from an experience standpoint.
40:09
Speaker 3: But I have to tell you, like the the biggest
40:13
Speaker 3: milestone and the biggest like the biggest like aha moment,
40:17
Speaker 3: I just have to I have to focus on putting
40:22
Speaker 3: together like mini communities at this company to help understand
40:27
Speaker 3: from the human element what people are really feeling. No
40:32
Speaker 3: matter of again, even Copilot or AI, you could reword
40:36
Speaker 3: something a million times on a campaign or like a
40:39
Speaker 3: you know, anything like engagement to the employee. You could
40:44
Speaker 3: do it in every techno technological way possible, but man,
40:49
Speaker 3: there is just something to that human like, hey, what
40:52
Speaker 3: do you what do you see going on in your environment? Well, Jeff,
40:56
Speaker 3: every time we go to open up a PDF, it
40:58
Speaker 3: crashes or it locks up. Really, I'm not necessarily seeing
41:02
Speaker 3: that all the time. And what's crazy is sometimes it's
41:06
Speaker 3: just little things like that that just well, it's not crazy.
41:10
Speaker 3: Sometimes it's just the littlest things like that that just
41:13
Speaker 3: ruin someone's day. You have no idea how important opening
41:17
Speaker 3: up a PDF is because you and I, like we
41:20
Speaker 3: open them. You and I and everybody on this call
41:22
Speaker 3: probably are like, yeah, I could just close it out whatever.
41:25
Speaker 3: Sometimes people don't know what they need to do right,
41:30
Speaker 3: So something as simple as a PDF freezing when they
41:33
Speaker 3: try to open it could lead to somebody like, you know,
41:36
Speaker 3: throwing a toaster across the room. And that's the emotional
41:41
Speaker 3: element that I have only found directly speaking with these
41:46
Speaker 3: global communities that I've set up around the world. Because
41:51
Speaker 3: the data and the numbers are there to guide us,
41:54
Speaker 3: they are not the freaking target. I've said this so
41:57
Speaker 3: many times when people bring up dashboards and bring up
42:00
Speaker 3: like the oh, Jeff, you know they said The target
42:04
Speaker 3: is getting people to have a better experience. The target
42:08
Speaker 3: is not ninety one point three percent of the people.
42:10
Speaker 3: So that agba, But no, that's not the target. That
42:14
Speaker 3: is just data to help guide us to a better,
42:16
Speaker 3: more blissful experience for our employees. I say, blissful. Let's
42:20
Speaker 3: start with you know, do not throw a toaster across
42:23
Speaker 3: the room in anger because of something I did or
42:26
Speaker 3: we're doing because I want to.
42:28
Speaker 4: Help can make a song. Jeff, Don't throw a toaster
42:31
Speaker 4: and anger. It sounds like so the sooner, use the oasis.
42:35
Speaker 4: Don't throw toaster and anger.
42:36
Speaker 3: Or Johnny Cash right, don't it's it's it's true, you know.
42:44
Speaker 3: And different cultures and different people around the world. You
42:47
Speaker 3: know again, I'm blessed to have as globular as a
42:49
Speaker 3: role as I do. But you don't seem to realize
42:53
Speaker 3: that every culture has a different experience, even if the
42:56
Speaker 3: problem is the same.
42:58
Speaker 4: Very cool, Very cool.
43:00
Speaker 2: I appreciate it, Jeff, I appreciate it, and I appreciate
43:03
Speaker 2: we appreciate you so much.
43:04
Speaker 4: Man.
43:04
Speaker 2: Honestly, I honestly, that first half hour about AI have
43:09
Speaker 2: my brain fizzing. I think I think you said so
43:12
Speaker 2: many prerogative, but very convincing things there.
43:17
Speaker 3: I'll stop there.
43:18
Speaker 4: That's that good time, Thank Jeff God. You learn.
43:23
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43:44
Speaker 3: Thank you so much for listening.
43:46
Speaker 1: Until next time,