1
00:00:01,440 --> 00:00:05,520
This spring commencement speakers across the country have been getting booed off stages for

2
00:00:05,520 --> 00:00:11,879
telling graduates that AI is the future when it should be those graduates future. So.

3
00:00:11,920 --> 00:00:17,920
Meanwhile, this is all happening. Marketing ops teams are also getting leaner, job listings are

4
00:00:17,920 --> 00:00:22,360
down, and people who built careers on technical fluency are starting to wonder if that's still

5
00:00:22,360 --> 00:00:28,200
enough. Darryl Alfonzo has lived both sides of this, and today we find out if the optimism still

6
00:00:28,200 --> 00:00:32,640
holds out. Welcome to Making Sense of MarTech podcast I'm Jacqueline Friedman. AI is

7
00:00:32,640 --> 00:00:37,800
transforming marketing, and the ops professionals who embrace it will thrive. I too have said that

8
00:00:37,800 --> 00:00:44,320
as well, but it sounds great as a general rule of thumb, but it feels differently after you've been

9
00:00:44,320 --> 00:00:50,960
laid off or made redundant because quote unquote, of the excuse, which is an excuse of AI. So

10
00:00:51,000 --> 00:00:56,280
today we are very fortunate with our guest, who's had the rare credibility of navigating this

11
00:00:56,280 --> 00:01:02,429
moment from the inside as both a practitioner who's championed AI adoption. And as someone who

12
00:01:02,470 --> 00:01:06,629
went through his own reckoning with the job market. We're going to pressure test the optimism.

13
00:01:06,669 --> 00:01:10,589
Look at the numbers that make people uncomfortable, and figure out what the people

14
00:01:10,589 --> 00:01:14,629
telling us not to worry about actually are getting right, and what they're just completely

15
00:01:14,629 --> 00:01:19,669
glossing over. So first and foremost, a little bit about Darrell. He's the marketing operations lead

16
00:01:19,669 --> 00:01:24,989
at the Pelham Group. Before that, he led marketing operations at two of the most data intensive,

17
00:01:25,029 --> 00:01:31,309
operationally complex environments in tech AWS, aka Amazon Web Services. And indeed, which is a

18
00:01:31,309 --> 00:01:36,989
little ironic considering the job market right now. And he's literally wrote the book on this

19
00:01:36,989 --> 00:01:42,629
field, and it's called the MarTech Handbook. And he's also the author of the Marketing Operations

20
00:01:42,629 --> 00:01:46,709
Leader newsletter. So you were laid off last year and you've called it a wild roller coaster. What

21
00:01:46,709 --> 00:01:51,070
do you think everyone is feeling? And as a result, this experience has given you something. Most

22
00:01:51,070 --> 00:01:56,349
martech commentators that are saying these things don't have it's skin in the game. And also when

23
00:01:56,390 --> 00:02:02,979
you're talking about real job market realities. So welcome, Darryl. I'm so excited to have you.

24
00:02:03,019 --> 00:02:09,619
Thank you. I have gone through all of that. Yes, I am still I am still

25
00:02:09,619 --> 00:02:16,380
optimistic. You know, I'm like a forever optimist. I'm happy to talk about that. And yeah.

26
00:02:16,419 --> 00:02:21,139
Hot take. I actually think that a lot of the layoffs maybe some of the more reasons not, but

27
00:02:21,139 --> 00:02:26,459
especially at the beginning of the AI movement, were actually due to bad business practices and

28
00:02:26,460 --> 00:02:32,859
not really AI. Yeah, yeah, I think it's still to date. Yeah, a lot of the tech companies, especially

29
00:02:32,860 --> 00:02:39,259
tech companies over hired in the war for talent, you know, and in the war for talent was hiring

30
00:02:39,259 --> 00:02:44,699
engineers and software developers with nothing with it for them to do. They hired them in order

31
00:02:44,699 --> 00:02:48,979
for their competitors not to get them. So you actually had just a bunch of people saying, like

32
00:02:49,020 --> 00:02:55,899
hanging around. So now rather than admit that, uh, we didn't really do this correctly, they

33
00:02:56,020 --> 00:03:00,329
like, this business model is not really great. Or talent models not really great. They blame it on

34
00:03:00,329 --> 00:03:06,849
AI. Yeah, perfect. It's a good. It's a good scapegoat. It's a good scapegoat. Yeah, well, let's dive in

35
00:03:06,850 --> 00:03:13,689
because. Yes. All right. So rapid fire Amazon or indeed which one had the most absurd

36
00:03:13,689 --> 00:03:20,609
meeting culture. Because I know at least one of them has a crazy one. Amazon with the 20 minutes

37
00:03:20,609 --> 00:03:27,169
reading in silence memo meetings for sure. Without a doubt. What bothers me the most is that you have

38
00:03:27,169 --> 00:03:34,009
to delete everything after the fact. Like nothing can stay present and like document it and

39
00:03:34,009 --> 00:03:40,329
record it. But I don't understand the philosophy of that specifically.

40
00:03:40,769 --> 00:03:47,329
Um, okay. What was your first martech tool? Constant contact. Ooh, that's a good one. I'm still a fan. I

41
00:03:47,329 --> 00:03:53,249
think I like MailChimp more, but it's a good gateway drug. Both of them.

42
00:03:54,209 --> 00:03:58,710
Okay, you've written that most sea level executives don't distinguish AI from basic

43
00:03:58,750 --> 00:04:04,109
automation. So give me the most ridiculous AI claim you've heard from a leader. Something that

44
00:04:04,110 --> 00:04:09,469
made you question whether you should correct them or just let it be. I actually don't like the whole

45
00:04:10,350 --> 00:04:15,589
AI is going to is going to single handedly make us $1 billion business or something like that,

46
00:04:15,589 --> 00:04:21,149
from, especially from the scale ups. I think right now you're already seeing most of the use cases

47
00:04:21,150 --> 00:04:27,469
are just internal and efficiency use cases. And most companies. Their problem isn't efficiency.

48
00:04:27,470 --> 00:04:33,709
Oftentimes it's just like lack of direction strategy or, you know, bad leadership

49
00:04:33,710 --> 00:04:40,269
practices. That's shocking. I don't like that claim. Agreed. If you could delete one more tech

50
00:04:40,269 --> 00:04:47,149
vendor from our entire industry. Which one and why? I think that, you know, they

51
00:04:47,150 --> 00:04:53,069
do a lot of it's like kind of customer bullying where you have to use all of their products in

52
00:04:53,070 --> 00:04:59,939
order to get the most benefit out of AI or like Agent Force. And, um, I don't like that

53
00:04:59,939 --> 00:05:05,499
business model. And I think that it's, uh, already led to, like, several really bad decisions. So I'm

54
00:05:05,540 --> 00:05:11,779
not a fan of that. You're not alone. And Adam Greco likes to call it sweet fatigue because sweet

55
00:05:11,779 --> 00:05:17,659
fatigue. Good one. Why would one company want an entire suite when you could have Best of Breed

56
00:05:17,660 --> 00:05:24,060
that all work together? Mhm. You wrote a job hunting survival guide based on your experience,

57
00:05:24,060 --> 00:05:29,259
what is a piece of advice that you wouldn't have deemed necessary two years ago. And it is today, I

58
00:05:29,260 --> 00:05:36,179
think that two years ago and especially four years ago, I think that if you

59
00:05:36,499 --> 00:05:42,099
knew your stuff and you were pretty reputable and you had like a good network, I think within the

60
00:05:42,099 --> 00:05:47,179
job market you would be just fine. And I'm glad you referenced the job survival guide, the one

61
00:05:47,179 --> 00:05:53,219
that we did with Humans of MarTech. And a lot of it is just essentially do anything like be

62
00:05:53,249 --> 00:05:57,329
willing to do things that you wouldn't be normally willing to do. Be willing to take a step

63
00:05:57,329 --> 00:06:03,130
down. Be willing to take a pay cut. Be willing to take a fractional job because now's not a good

64
00:06:03,130 --> 00:06:09,290
time. And you know if as long as you have a good paycheck and you're able to learn and exercise

65
00:06:09,290 --> 00:06:16,169
your skills, especially around AI. That to me is a win today. You know, until things sort of settle

66
00:06:16,170 --> 00:06:21,890
down in the future, if it ever does. Yep. I'm in full agreement, and I never would have said that

67
00:06:21,929 --> 00:06:28,249
because my my initial thing is get the job that you want and get the salary you deserve and

68
00:06:28,250 --> 00:06:35,209
everything and all that still is true. However, it is not always the reality. Nope. Not

69
00:06:35,209 --> 00:06:40,609
at all. And yeah, I definitely think in the long run you should focus on getting something you

70
00:06:40,609 --> 00:06:46,409
like to do and that challenges you and that you enjoy, you know? But right now people need to pay

71
00:06:46,410 --> 00:06:52,319
their bills. So getting back to these boos at commencement ceremonies, they really become their

72
00:06:52,320 --> 00:06:57,519
own story that's spreading like wildfire. And the graduates are really pushing back in real time

73
00:06:57,520 --> 00:07:01,680
about AI as your future messaging. But most of us who are listening to this are already in the

74
00:07:01,720 --> 00:07:08,519
workforce, and so we don't exactly get to boo the speaker in the same guttural, visceral way. And

75
00:07:08,519 --> 00:07:14,320
so we start to figure out what's actually true, what's fact, what's fiction, and how we can work

76
00:07:14,320 --> 00:07:21,319
within it. So how do you read this cultural moment? I think it's symbolic of

77
00:07:21,799 --> 00:07:28,799
what's happening between technology and business leadership as a whole, because what I

78
00:07:28,800 --> 00:07:35,639
think is happening is that business leaders themselves, unless you're like the head of OpenAI

79
00:07:35,960 --> 00:07:41,319
or the head of anthropic or whatever, actually don't really know what to do or what to expect

80
00:07:41,319 --> 00:07:48,199
out of AI. Only recently has Claude been like the number one choice for, you know, developing

81
00:07:48,199 --> 00:07:55,149
vibe, coding or doing most work related things. A year ago was ChatGPT. So the speed at which

82
00:07:55,149 --> 00:08:00,310
things are changing and the leaders are changing makes it really so that we can't anticipate

83
00:08:00,310 --> 00:08:06,429
what's going to happen. But I think that leaders are continuing to pretend that they do know AI is

84
00:08:06,430 --> 00:08:12,029
our future, and they don't even know what that means. So I think that it's it's very out of touch,

85
00:08:12,030 --> 00:08:17,548
just like how these, you know, commencement speeches are not realizing what's really

86
00:08:17,549 --> 00:08:23,029
happening is that these students need inspiration for because they're going to be the next

87
00:08:23,030 --> 00:08:28,630
generation of, of people going into the workforce. They don't need some sort of AI talk. It just

88
00:08:28,630 --> 00:08:34,029
doesn't make sense to me. Agreed. And also, the students already know AI better than they do at

89
00:08:34,030 --> 00:08:41,030
this point. Yeah. If anything, it's like you old, old man. You old phony. Like we know what it is.

90
00:08:41,030 --> 00:08:45,989
We know how to use it. We're using it on the daily for different things. But also we are not

91
00:08:45,989 --> 00:08:52,099
replaceable at the same time. Yeah, yeah. And I guess most people in this industry are still

92
00:08:52,299 --> 00:08:58,779
really trying to meet the gap in leadership on what they understand is AI versus automation. And

93
00:08:59,420 --> 00:09:04,859
you think that is wrong? Tell me why. My first thought is we've had automation for a really long

94
00:09:04,860 --> 00:09:09,738
time and it's just workflows. If this then that, then do this then do this. You daisy chain them

95
00:09:09,739 --> 00:09:13,419
together. Right now people think that's AI because they didn't have a good understanding of

96
00:09:13,419 --> 00:09:19,700
automation in the first place. So now all of a sudden, anything happening automatically is AI,

97
00:09:20,140 --> 00:09:26,738
right? It's it when AI is really like either like a probabilistic, you know, large language

98
00:09:26,739 --> 00:09:33,620
model or AI making decisions based on different criteria and learning at the same time.

99
00:09:33,620 --> 00:09:40,259
So they are very different things. I think that the challenge becomes when it comes to executing

100
00:09:40,299 --> 00:09:46,179
tasks. What we've really needed is, is a smart person running and orchestrating automation for a

101
00:09:46,179 --> 00:09:53,169
long time. I think that personally, I don't think it is worth, you

102
00:09:53,169 --> 00:09:59,089
know, dying on this hill because leadership is just going to, you know, has already gone through

103
00:09:59,090 --> 00:10:05,409
the gates anyway. You know, a lot of my advice that I've been talking about has just been leverage

104
00:10:05,409 --> 00:10:11,689
this time, leverage the fact that everyone wants to use AI, and people like you and me know that

105
00:10:11,689 --> 00:10:17,249
this isn't really AI, but if you show it to them and they think it is, you win. I really think that

106
00:10:17,249 --> 00:10:23,329
that's the way that I look at it. So the World Economic Forum says if 41% of employers plan to

107
00:10:23,329 --> 00:10:28,249
reduce their headcount because of AI. I would dare to say we're already at 85% in terms of those who

108
00:10:28,250 --> 00:10:34,928
are reducing. And meanwhile, anthropic CEO said AI could eliminate half of all entry level white

109
00:10:34,929 --> 00:10:41,169
collar jobs within five years. Really inspiring stuff here. So you came out of a layoff and

110
00:10:41,169 --> 00:10:45,529
immediately started writing about how marketing operations professionals can thrive. Are those two

111
00:10:45,530 --> 00:10:51,950
things intention or you genuinely not worried about the job security of the marketing office

112
00:10:51,950 --> 00:10:58,389
function. I have two minds when it comes to this. The first one is that the mission

113
00:10:58,390 --> 00:11:04,269
of my writing has always been to elevate the marketing operations professional, because I've

114
00:11:04,270 --> 00:11:08,348
always thought that they were worth a lot more and deserved a lot more credit than they were

115
00:11:08,349 --> 00:11:14,229
getting, and that hasn't changed. I really think that the really great operators out there are

116
00:11:15,150 --> 00:11:21,390
problem solvers, and they use technology and people and process and just

117
00:11:21,630 --> 00:11:28,389
ingenuity to drive business results, and I'm always going to hold that. And I

118
00:11:28,389 --> 00:11:33,349
feel like because there aren't that many people sort of preaching that message, I feel like I'll

119
00:11:33,349 --> 00:11:38,029
always be carrying that flag up the hill, even if it's like just me, you know? Because I do feel that

120
00:11:38,030 --> 00:11:42,029
if at least one person kind of sees, like, hey, that is the direction that we have to go, then it'll be

121
00:11:42,030 --> 00:11:48,460
worth it. Having worked with a lot of technology and marketing technology professionals that

122
00:11:48,900 --> 00:11:55,699
weren't as passionate as I was. It definitely seen how AI

123
00:11:55,740 --> 00:12:02,139
can replace some operations folks. There are some people and it's like, it's your choice, right? I'm

124
00:12:02,140 --> 00:12:06,939
not saying I'm not judging you. There's no harm in this. But there are a lot of operations, people

125
00:12:06,940 --> 00:12:13,059
that are just ticket takers or project managers, and they just take a request. They build it in

126
00:12:13,059 --> 00:12:18,340
whatever and now and they return it back, like glorified customer support, especially if it

127
00:12:18,340 --> 00:12:25,020
doesn't require building things. Those people I do think are, um, in danger of being

128
00:12:25,020 --> 00:12:30,099
replaced. The best of us aren't. And I'm hoping that more of us become the best of us. If that

129
00:12:30,140 --> 00:12:35,580
doesn't sound cheesy. So no, it doesn't sound cheesy at all. It's really just everyone. Yes,

130
00:12:35,580 --> 00:12:42,059
things are moving at a pace that is hard to keep up with. However, your interest and willingness to

131
00:12:42,099 --> 00:12:49,049
learn is what's going to set you apart. As long as you stay curious. If you're interested. Your job is

132
00:12:49,050 --> 00:12:54,329
not going anywhere. Or at least. Yeah. The concept of your job is not going anywhere. Maybe that

133
00:12:54,330 --> 00:12:59,969
specific role is not at the same company, but we need creative thinkers. I think so, and like, you

134
00:12:59,969 --> 00:13:05,168
know what? Like, I obviously I didn't want to get laid off, but. Oh, of course not. Yeah. And especially

135
00:13:05,169 --> 00:13:09,128
at that time, like it was really important that we would have health insurance because our baby

136
00:13:09,129 --> 00:13:15,849
needed something and it was a rocky time. I wasn't quite happy in the role that I was in. You know, I

137
00:13:15,969 --> 00:13:22,928
didn't feel like I was making the impact that I could have and that over long

138
00:13:22,929 --> 00:13:29,409
periods of periods of time kind of gets to you that as I use AI every day, more and more in my

139
00:13:29,409 --> 00:13:36,090
job, I can't help but think that there's other operators going like, hey, I could do this. What am

140
00:13:36,090 --> 00:13:42,489
I doing? Maybe I should lay myself off. You know what I mean? And I feel like, if anything, if it'll

141
00:13:42,490 --> 00:13:47,400
give people like an opportunity to kind of try something new or go go to something where they

142
00:13:47,400 --> 00:13:52,080
can actually make feel like they can make a difference. It's worth it because like looking

143
00:13:52,080 --> 00:13:56,520
back and coming out on the other side, I actually wouldn't have changed what happened. I would have

144
00:13:56,559 --> 00:14:00,559
like, I don't want to go back there. I'm happy where I am. Like, I'm happy. Like making a

145
00:14:00,559 --> 00:14:06,999
difference. And I get that. That's very I am privileged because it's not like, you know, I

146
00:14:07,000 --> 00:14:10,919
couldn't pay my mortgage and they were taking away my house. Like, I definitely get that. But I

147
00:14:10,919 --> 00:14:15,719
will say that I wouldn't be surprised if more people that are going to be getting impacted by

148
00:14:15,719 --> 00:14:22,599
the changes find something that they really like to do. Yeah, I wholeheartedly agree. Even though it

149
00:14:22,599 --> 00:14:29,279
might take longer than one would like, there's always a reason for that door to close, and it

150
00:14:29,280 --> 00:14:35,039
just means a new one is opening. It might take a couple more doors to close before you meet that

151
00:14:35,039 --> 00:14:40,280
destination, but isn't that life? It's all a journey. But I wholeheartedly agree. It's like no

152
00:14:40,280 --> 00:14:46,709
regrets, even if it really. at the time, and it was not. Seriously. Seriously.

153
00:14:47,109 --> 00:14:53,630
Mentally, you know. For your own family, everything you can. It's it's a lot. It's a lot of burdens.

154
00:14:53,630 --> 00:14:58,949
People are having to take on every profession. That doesn't have to do with that has to do with

155
00:14:58,950 --> 00:15:04,949
knowledge, work or expertise. It's it's literally everything. So, you know, I think that right now

156
00:15:04,949 --> 00:15:10,149
it's just a time to like, be resilient and roll with the punches because you're not alone. If

157
00:15:10,189 --> 00:15:15,789
you're worried, you're not. Everyone is. Yeah. I think, um, one of the most beautiful things that's

158
00:15:15,790 --> 00:15:21,829
come out of a lot of this pain is a lot of communities are popping up like there's in the,

159
00:15:21,870 --> 00:15:27,430
like, mops and life cycle space. The village Randy Levy has created and there's a bunch of different,

160
00:15:27,469 --> 00:15:34,468
just safer spaces where folks can help kind of make introductions and help give

161
00:15:34,509 --> 00:15:39,670
critiques or even just honestly having anyone else who's going through a similar thing to talk

162
00:15:39,670 --> 00:15:46,340
to Because you're not alone and lay off. Used to be this big flag on someone's

163
00:15:46,340 --> 00:15:52,379
resume. And I know when I was at Grammarly and hiring, we had to change the policy where it used

164
00:15:52,380 --> 00:15:55,859
to be, like, oh, if they've been laid off, like, let's really double click and make sure everything's

165
00:15:55,859 --> 00:15:59,819
okay. But it came to a point where, no, no layoffs are so common now that it's clearly not the

166
00:15:59,819 --> 00:16:05,619
person. Seriously, it's you're lucky if you haven't. Like, it's more likely that you've been laid off

167
00:16:05,659 --> 00:16:11,619
like given the numbers. Exactly. And you are only particularly lucky if you got laid off and

168
00:16:11,620 --> 00:16:16,099
actually got a severance package versus those you got laid off and nothing else, people get lit. Mhm.

169
00:16:16,340 --> 00:16:22,979
So most teams at least I talk to their inheriting a Franken staff and a huge backlog. They're most

170
00:16:22,979 --> 00:16:28,979
certainly not getting a blank slate a tabula rasa. You know the ideal. Create what you want. Choose

171
00:16:28,980 --> 00:16:35,139
your own adventure. So what does strategy first mean when you're still mid mess when you join a

172
00:16:35,139 --> 00:16:41,610
company? I like the idea of two concepts I think will really help in this situation. One is the

173
00:16:41,610 --> 00:16:45,808
working backwards concept where you where we figure out what are you actually trying to

174
00:16:45,809 --> 00:16:52,249
accomplish. And like what what does success look like, like in six months? Do you have a

175
00:16:52,849 --> 00:16:59,289
efficient lead management process? Do you have data that marketers can trust, build

176
00:16:59,290 --> 00:17:05,329
audiences and activate on? You know, do do you have a good sales handoff? Like what does what does it

177
00:17:05,329 --> 00:17:10,609
look like 3 or 6 months down the road and then work backwards to build the technology and the

178
00:17:10,610 --> 00:17:16,529
processes that support that? Now the other thing that's really going to help is just this idea of

179
00:17:16,530 --> 00:17:22,770
really quick wins and things that you can work together on to help improve things. One of the

180
00:17:22,770 --> 00:17:29,369
things that people don't like realize is that when you're creating your work together with

181
00:17:29,370 --> 00:17:35,209
people, if you like, want to fix an entire marketing automation platform that is complete

182
00:17:35,250 --> 00:17:40,309
trash, that can take a really long time, especially at a big company. It could take months and months

183
00:17:40,310 --> 00:17:47,150
and months and that sort of slowness. The drag can get become incredibly

184
00:17:47,150 --> 00:17:53,949
frustrating. And you also can start to blame people like, oh, it's the it's it, it's legal. It's

185
00:17:53,949 --> 00:18:00,150
this. You just started getting into these fights. I think that we overlook how important it is to

186
00:18:00,189 --> 00:18:05,629
establish a good working relationship of people that feel like when they work together, they win.

187
00:18:05,630 --> 00:18:12,389
So even if some things are, like not as impactful, like maybe setting up a new JIRA intake

188
00:18:12,389 --> 00:18:17,589
process or, you know, setting up a new cadence of like, this is the roadmap, this is how we're going

189
00:18:17,589 --> 00:18:22,589
to accomplish things because things get accomplished together. You realize, oh, we're on the

190
00:18:22,589 --> 00:18:28,149
same team, we can do this. But when people work together, they go really fast. And like the

191
00:18:28,150 --> 00:18:33,669
opposite is true. If they don't like it's it really sucks, you know, and I've I've been in both

192
00:18:33,670 --> 00:18:38,739
I've been in more places that sucked than it moving really quickly. Yeah. There's nothing quite

193
00:18:38,780 --> 00:18:45,139
like when you have a dream team where you have full trust and you all see how this maybe

194
00:18:45,139 --> 00:18:50,619
monotonous task ladders into the bigger picture and realize what the level of impact it will

195
00:18:50,620 --> 00:18:56,778
become as a result. I think some of my favorite days working were literally like 4 to 5 hour just

196
00:18:56,779 --> 00:19:03,499
working sessions where like, all right, this is monotonous. Let's just chit chat and you take this

197
00:19:03,499 --> 00:19:08,619
half, I take that half and let's try to get it done as quickly as possible. Yeah I agree. All

198
00:19:08,660 --> 00:19:14,419
right. I was a little nerdy and grabbed some lines from your newsletter. So you always push for

199
00:19:14,420 --> 00:19:20,779
accurate, clean, real time data for years and you continue to hit walls. And so now you're saying

200
00:19:20,779 --> 00:19:26,859
that the frame that finally opens those doors is AI needs good data to function, which makes total

201
00:19:26,859 --> 00:19:32,779
sense. And that works because executives care about AI. It means you get budget. But is that

202
00:19:32,780 --> 00:19:37,969
slightly cynical because you're using their confusion to get budget for work that should have

203
00:19:37,969 --> 00:19:44,449
been funded regardless. Yeah, I guess I guess it's kind of cynical. There's kind of a means to the

204
00:19:44,449 --> 00:19:50,089
end, at the end of the day, like if you kind of like cut some corners, I think it's fine. I think

205
00:19:50,089 --> 00:19:55,010
you could take it all the way through to, to the other side, where you can actually be really

206
00:19:55,010 --> 00:20:00,249
cynical about a lot of things that happen in business, you know, all the way from what I said

207
00:20:00,289 --> 00:20:07,089
before about fake AI goals and fake AI futuristic planning, to all the things that Wall Street is

208
00:20:07,130 --> 00:20:13,969
actually based off of, you know, it's all based on potential and probability and guessing.

209
00:20:13,969 --> 00:20:20,449
It's like legal poker and people cheat. So like, I think you could take that

210
00:20:20,449 --> 00:20:27,449
cynicism and go take it much farther than getting buy in for data improvement. But one

211
00:20:27,449 --> 00:20:34,289
thing I will say is it's not wrong. You really do need good data. And I think that

212
00:20:34,290 --> 00:20:40,359
what's actually happening is that executives, because they feel like they're going to be left

213
00:20:40,359 --> 00:20:46,959
behind, are willing to do and really like, you know, because it hurts to create new budget and it

214
00:20:46,959 --> 00:20:52,599
hurts to like go to the CFO and ask for more money. But they're willing to take that pain

215
00:20:52,600 --> 00:20:59,560
because they want this thing so badly. And now, finally, we have it. And you know, I am not ashamed

216
00:20:59,560 --> 00:21:06,480
of doing that. And also, it's not a lie. So I agree, it's one of the sequential steps in

217
00:21:06,480 --> 00:21:13,399
order to achieve the goal. You're making bets on actual data. Yeah. Like the way that I

218
00:21:13,439 --> 00:21:19,959
phrase it is, are you going to let your AI SDRs loose on like, wrong people's information? You know,

219
00:21:20,000 --> 00:21:25,919
like, there's so many potential problems that could happen if you have you're using AI and bad

220
00:21:25,920 --> 00:21:32,799
data. There's so many. It's just so agreed. Okay. So we've been talking about the data piece. But also

221
00:21:32,800 --> 00:21:39,189
now if we think about the execution layer, if AI is absorbing that just general routine,

222
00:21:39,189 --> 00:21:45,629
what does the role of someone who's executing actually look like in three years? So there's a

223
00:21:45,630 --> 00:21:52,510
couple of different ways that I think this could go. On one hand, you have the elevation to more

224
00:21:52,510 --> 00:21:59,149
strategic and more technology orchestration type

225
00:21:59,229 --> 00:22:05,109
roles. You know, where. And this is kind of like in Mira's career progression. You know, if you build

226
00:22:05,109 --> 00:22:11,789
emails like for real living or build websites for a living, if automatically you have a tool that

227
00:22:11,790 --> 00:22:17,709
does that for you. Now, you don't have to do that anymore. You start to do things like connect email

228
00:22:17,750 --> 00:22:23,229
to the revenue channel or connect other channels together, connect it all to the website. So the

229
00:22:23,269 --> 00:22:28,229
sort of like each level of abstraction that you go up, you're actually like adding more value to

230
00:22:28,229 --> 00:22:33,698
the business. So I think it could go in that direction for some people. For some folks, like the

231
00:22:33,699 --> 00:22:39,660
people I mentioned earlier that actually enjoy that type of work, that ticket taking, they I think

232
00:22:39,660 --> 00:22:44,859
will be probably let go or moved or their role will be repurposed into something else.

233
00:22:44,860 --> 00:22:50,740
Unfortunately, we're seeing that already in a ton of different industries. All share at one of the

234
00:22:50,740 --> 00:22:56,259
companies that I worked at. They let go of the entire marketing team not because of AI, but

235
00:22:56,259 --> 00:23:02,899
because the future, which was like more of an enterprise go to market focused

236
00:23:02,900 --> 00:23:09,819
type future. The current marketing team didn't have the skill set to do it right, so they had to

237
00:23:09,819 --> 00:23:15,660
repurpose those roles. Unfortunately, like if you asked me, hey Daryl, our future is like making

238
00:23:15,660 --> 00:23:22,339
commercials for the Super Bowl. You know, I'd be like, I'm not the guy, you know what I mean? I don't

239
00:23:22,339 --> 00:23:28,979
think I could do that kind of factual. And then I think, lastly, there's this vision that I first

240
00:23:28,979 --> 00:23:34,688
heard about from Paul Wilson, which is the future of marketing operations, is just a prompt, and I

241
00:23:34,689 --> 00:23:40,849
think that we are starting to see that with all the MSPs and how everybody is connecting

242
00:23:40,849 --> 00:23:44,409
everything to cloud code, so they actually don't have to go into other platforms and they just do

243
00:23:44,410 --> 00:23:50,369
everything out of Claude. So we're getting closer and closer to that direction. But I will tell you,

244
00:23:50,530 --> 00:23:57,449
you have to know what to ask cloud first, and it can give you some direction. But the number of

245
00:23:57,449 --> 00:24:04,249
times that I take a look at something that AI is outputted and just from like experience and being

246
00:24:04,250 --> 00:24:09,249
able to know what's important and what's not and what's a waste of time and what's not, I really

247
00:24:09,249 --> 00:24:13,729
think like, oh, if you try to replace me with Claude, like, good luck, you're going to be so rude.

248
00:24:14,050 --> 00:24:20,409
Oh, that is my favorite response. Just good luck. I mean, that's one of the

249
00:24:21,010 --> 00:24:25,609
I think it's cathartic for folks, but particularly in our roles, we typically have keys to the

250
00:24:25,610 --> 00:24:30,389
kingdom not because we want them, but because we have to have them from an administration

251
00:24:30,430 --> 00:24:36,789
standpoint, and there's nothing better than when you are laid off or the whole team is laid off

252
00:24:36,790 --> 00:24:42,948
and everything breaks because everything was connected via you sometimes are the integration

253
00:24:42,949 --> 00:24:48,429
user or the admin. And so all of a sudden they're like, oh no, everything's not working. And so

254
00:24:48,709 --> 00:24:52,870
there's at least some solace that like the dumpster fire is happening without you. Seriously,

255
00:24:52,870 --> 00:24:57,068
I'm one of those people that looks for stuff to do, you know, as I'm sure like you do too. It's just

256
00:24:57,069 --> 00:25:02,469
like, hey. Yeah, how how can we, like, make things better? Like, that's a that's a very operations

257
00:25:02,469 --> 00:25:07,949
person, in my opinion. You're just trying to make things better. And, you know, even when I got back

258
00:25:07,949 --> 00:25:12,108
from parental leave and when I was, I took a really good amount of time for parental leave

259
00:25:12,150 --> 00:25:17,789
because indeed, it is awesome that way. I had set up the team and I had like multiple team members.

260
00:25:17,790 --> 00:25:22,549
I had set up the team to where they could operate without me for several months, and when I came

261
00:25:22,550 --> 00:25:29,339
back, they did a good job and I started. Yeah, I started to think like, what am I gonna do?

262
00:25:29,539 --> 00:25:34,419
You know, crap. And I found stuff to do. But there are people that that were in the same position

263
00:25:34,420 --> 00:25:40,019
that didn't look. And I think that we were primarily a remote first culture, but if we were

264
00:25:40,020 --> 00:25:45,219
all on site, it would be the equivalent of people just kind of coming in, walking the halls and

265
00:25:45,219 --> 00:25:52,179
going like online shopping at their desks. And that is not just indeed, oh, of course, that bloat

266
00:25:52,180 --> 00:25:59,139
exists in so many everywhere. It's primarily large, established and enterprise

267
00:25:59,140 --> 00:26:05,780
companies because things are easier to hide through not just silos, but existing processes

268
00:26:05,780 --> 00:26:10,979
that they've outgrown or no longer apply. But they can kind of just make it happen. I mean, almost

269
00:26:10,979 --> 00:26:17,139
every financial company, particularly banks that I know of, takes like anywhere from 3 to 6 months to

270
00:26:17,140 --> 00:26:21,979
send one email. It just hurts my brain. It's like you're you have to pencil push. I don't doubt it.

271
00:26:21,979 --> 00:26:27,889
Yeah, my brain literally doesn't work like that. It doesn't work. Yeah. I don't get it, I cannot compute,

272
00:26:28,729 --> 00:26:35,049
but things I can compute. There's a data point and I want you to sit with it. So. MIT found that AI is

273
00:26:35,050 --> 00:26:41,569
only cheaper than humans and 23% of tasks. That means a quarter of tasks only.

274
00:26:41,610 --> 00:26:48,329
And for example, this was recently announced that Uber's CTO blew through the entire company's AI

275
00:26:48,369 --> 00:26:55,249
budget for 2026 in 4 months. And that was just on token costs. And

276
00:26:55,250 --> 00:27:02,089
also, Nvidia's VP of Applied Deep Learning says compute now costs his team more than the people

277
00:27:02,089 --> 00:27:08,489
using it. So the pitch has been working. It was relentless about cost savings, but the reality is

278
00:27:08,530 --> 00:27:15,010
actually it's ballooning budgets instead. So is this potentially an economic case for AI

279
00:27:15,050 --> 00:27:21,369
replacement to maybe be built on math instead? Or maybe the humans are cheaper? Ultimately, I wasn't

280
00:27:21,370 --> 00:27:26,479
aware that it was more. Some teams are spending more money on compute than like people's salaries.

281
00:27:26,479 --> 00:27:32,399
And I think that that's crazy. I do think that today that might be true. I don't think that will

282
00:27:32,439 --> 00:27:39,399
be true tomorrow or like down the line. And I say that because technology typically becomes

283
00:27:39,399 --> 00:27:45,198
more efficient and like in the case of like hardware, like smaller, if you think about the

284
00:27:45,199 --> 00:27:50,959
first computers, they took up entire rooms and you're just like, how is this worth, like running a

285
00:27:50,959 --> 00:27:57,759
calculator? Like, I don't think so. And the USB stick of. Yeah. And I do think that from a

286
00:27:57,760 --> 00:28:04,359
technology standpoint, the electricity and compute costs are going to go down. And probably with

287
00:28:04,359 --> 00:28:10,400
AI the needs will probably go down to like we're going to figure it out. But that's just me being

288
00:28:10,400 --> 00:28:17,318
an optimist. I do think that the danger lies in trying to automate

289
00:28:17,319 --> 00:28:23,039
everyone's job with AI. And just like buying all the tokens in the world that, you know, the token

290
00:28:23,040 --> 00:28:29,590
cost would be crazy. So I do think that that's a very real concern now. And it's just yet another

291
00:28:29,590 --> 00:28:36,588
proof point of like, don't lay off all your ops people just yet. Like, I don't think you have

292
00:28:36,589 --> 00:28:41,469
a map to to get to the where you want to go. So that's what I think. So it's safe to say you're

293
00:28:41,469 --> 00:28:48,029
not a fan of a token leaderboard. Yeah, it's the quality over quantity

294
00:28:48,430 --> 00:28:55,029
conversation and it's so rudimentary. Why would you want a quantity of

295
00:28:55,029 --> 00:29:01,468
tokens used per person, per day, per month? You name it over outcomes in actual quantity. That

296
00:29:01,469 --> 00:29:08,349
is the whole point. AI should augment what we do so that we're empowered

297
00:29:08,349 --> 00:29:14,669
to and from this is, you know, little philosophical. But like from a a workers perspective,

298
00:29:14,710 --> 00:29:19,390
productivity is the only thing a company cares about. So why wouldn't you want to make your

299
00:29:19,390 --> 00:29:24,779
workers more productive? But they need to know when and when aren't use cases to do that.

300
00:29:24,780 --> 00:29:31,059
Ultimately, they'll cost you more because of that token cost. That said, you're right the cost of

301
00:29:31,060 --> 00:29:37,859
credits and tokens will go down just like any other technology. But you know, I'm I'll go ahead

302
00:29:37,859 --> 00:29:44,259
and say it. There's some data centers going on fire. So like, maybe not, I don't know, maybe not.

303
00:29:44,300 --> 00:29:50,259
There's a bunny under fire and, uh, under question. Yeah, there's more coming. And I think that, like,

304
00:29:50,260 --> 00:29:56,579
when these sort of like constraint or like scarcity of resources problem comes up, I think

305
00:29:56,579 --> 00:30:03,260
that myself included, we forget about discovery and innovation. And they actually discovered

306
00:30:03,260 --> 00:30:09,819
that Nvidia like for some reason has these graphics chips that really support AI really well.

307
00:30:09,819 --> 00:30:15,698
And then like, what are we going to discover next? I really do think that especially with Nvidia's

308
00:30:15,699 --> 00:30:19,579
growth and just success, we're going to see people that are going to try to figure out another way

309
00:30:19,580 --> 00:30:25,529
to do it. Never discount human ingenuity, that's for damn sure. Yeah. Yeah. Brought to you by our

310
00:30:25,530 --> 00:30:30,489
sponsors. If there's one theme that's followed me at every stop in my martech career, it's trying to

311
00:30:30,489 --> 00:30:34,969
get good data into the hands of marketers. That's why I'm so excited to tell you about our sponsor,

312
00:30:35,010 --> 00:30:39,729
High Touch, the leading composable CDP and AI decisioning platform companies like Domino's,

313
00:30:39,770 --> 00:30:45,289
Chime and Ritzy and PetSmart trust High touch to power their data. And here's the kicker 90% of

314
00:30:45,289 --> 00:30:49,929
customers have a real use case live in production within their first week. That means you can

315
00:30:49,930 --> 00:30:54,649
implement a world class CDP in months rather than the usual years long headache. That's why top

316
00:30:54,649 --> 00:30:59,249
brands choose high touch to personalize every customer interaction at scale. See what high touch

317
00:30:59,249 --> 00:31:05,209
can do for you at high touch. And now back to the hot seat. From your perspective, at what point does

318
00:31:05,249 --> 00:31:11,890
augmentation just mean we'll need fewer of you? Research is showing that 79% of employed women

319
00:31:11,890 --> 00:31:16,930
are working in jobs that are a high risk of automation, compared to 58% of men. And this is, of

320
00:31:16,930 --> 00:31:23,470
course, as in high income countries, particularly the reason why Asus is marketing ops skews

321
00:31:23,670 --> 00:31:29,629
heavily female, and I know some of the best operators are women. And so I guess why is this

322
00:31:29,630 --> 00:31:36,269
not a topic that keeps being discussed out in the open, like whether it's at industry conferences? I

323
00:31:36,349 --> 00:31:42,389
know at least amongst my peers, we're talking about it. But I'm curious from your perspective,

324
00:31:42,510 --> 00:31:47,150
why is this not making it onto the conference room agendas? I think that's really interesting. I

325
00:31:47,150 --> 00:31:52,509
didn't know that it's skewed female. Why is this not being discussed? Executives are there's a much

326
00:31:52,510 --> 00:31:57,429
lower probability that executive will be female or in technical roles. And it wouldn't be a female

327
00:31:57,429 --> 00:32:03,910
that you can like go back to, you know, number one, like sexism. And then also

328
00:32:04,190 --> 00:32:11,148
just the whole entire like educational and like cultural thing of like women being directed into

329
00:32:11,189 --> 00:32:16,150
certain roles and men being directed to certain roles because of either like they people think

330
00:32:16,150 --> 00:32:22,900
women are two are more emotional at versus logical, which, you know, isn't true. So I think

331
00:32:22,900 --> 00:32:29,060
that that's definitely a larger question. I will say I do have some experience with diversity

332
00:32:29,060 --> 00:32:35,099
issues, um, especially within within marketing. And I feel like there's some parallels. So for example,

333
00:32:35,139 --> 00:32:40,739
in most of the marketing teams and marketing ops teams that I've been in, everyone's been white. I

334
00:32:40,740 --> 00:32:47,659
don't think that that was a coincidence. I think that marketing in general, I think tends to lend

335
00:32:47,660 --> 00:32:54,419
itself to more classical like type stereotypes, is the first issue. I also think that if you don't

336
00:32:54,460 --> 00:33:00,180
intentionally think about it, you usually just look and hire people that kind of look like you,

337
00:33:00,180 --> 00:33:06,180
and you try to you get along with people that look like you. And I think that all of us, like me

338
00:33:06,180 --> 00:33:13,139
included, need to try to push ourselves to work with, collaborate with,

339
00:33:13,140 --> 00:33:19,490
and hire people that are very different, especially thought differences. And, you know, you

340
00:33:19,490 --> 00:33:25,929
and I were talking about this earlier, but like, it's so great to work with my co-host that humans

341
00:33:25,929 --> 00:33:32,650
of martech, right. Because Phil, I, I feel like is very opposite of me. Right.

342
00:33:32,690 --> 00:33:37,929
Very organized. Wants to make sure that there's like a theme for each podcast, whereas I'm more of

343
00:33:37,969 --> 00:33:41,569
like shoot from the hip. I'm going to come up with this crazy question on the spot just from like

344
00:33:41,569 --> 00:33:46,849
looking at the person's face, you know, I'm going to know what to say. Um, and honestly, there are

345
00:33:46,849 --> 00:33:51,848
times to both of those sort of like, skills or strengths are useful. There are like different

346
00:33:51,890 --> 00:33:56,769
times, you know, so like my shoot from the hip makes me a really good moderator. If you're

347
00:33:56,769 --> 00:34:03,010
hosting a, you know, podcast that reaches a lot of people, I think the quality should be higher. You

348
00:34:03,010 --> 00:34:07,848
know, I think there should be more planning and I think more people should follow suit. We're trying

349
00:34:07,849 --> 00:34:14,609
here every other podcast. I, I beg you to do that. No, seriously. My

350
00:34:14,610 --> 00:34:20,638
rants done. I think it's just it's important to like consider this type of like diversity in

351
00:34:20,639 --> 00:34:25,360
general when we're like working with people and choosing who to work with. It makes me think of

352
00:34:25,360 --> 00:34:30,560
the structural choices and how we can go about fixing it. And for me, top of mind is trying to

353
00:34:30,560 --> 00:34:37,319
take the bias as much as possible out of the hiring process and building in scorecards

354
00:34:37,319 --> 00:34:44,279
frameworks where you ask the same questions, but you ask questions so that

355
00:34:44,280 --> 00:34:50,278
you can see how the person thinks, see how they get to a certain conclusion, and also as a result,

356
00:34:50,320 --> 00:34:57,279
hopefully your bias is sorted because you've already defined what a good answer looks

357
00:34:57,280 --> 00:35:02,359
like. Do they hit these points? If they exceeded that, that's a whole, you know, a different

358
00:35:02,360 --> 00:35:08,679
stratosphere versus okay, they responded, but it wasn't. Didn't even discuss. I'm like, okay, this may

359
00:35:08,679 --> 00:35:13,478
be a two out of five as opposed to a five out of five response. And so there can be some more

360
00:35:13,479 --> 00:35:20,029
objectivity to, without a doubt, a very subjective process. Speaking of people needing a

361
00:35:20,030 --> 00:35:26,909
job, I want to talk back to the personal stakes. So we've talked about your optimism and where it's

362
00:35:26,909 --> 00:35:33,628
been meeting a lived experience and what that reckoning actually is producing. And you've stated

363
00:35:33,629 --> 00:35:38,589
that AI won't replace marketing ops because most marketing and go to market problems are

364
00:35:38,590 --> 00:35:45,589
fundamentally people problems. I agree, and that AI falls in this gray area of quote unquote

365
00:35:45,629 --> 00:35:50,589
business. But you also just went through a layoff while writing and teaching this. So like what did

366
00:35:50,590 --> 00:35:57,310
you experience with regards to this thesis? Did it hold up? Did you find it to be true? I'm

367
00:35:57,310 --> 00:36:01,590
curious to learn more. One of the things that I kind of learned throughout the process is how

368
00:36:01,629 --> 00:36:06,948
little control you actually have on some of these larger things, and I will tell you, and I might get

369
00:36:06,949 --> 00:36:11,710
in trouble for saying this, but that indeed the company really grew and rose and fell with the

370
00:36:11,710 --> 00:36:18,499
economy, you know, because indeed makes money when you have people posting jobs and

371
00:36:18,499 --> 00:36:23,219
people applying to jobs. And when the market goes up, that goes up too. When it goes down, it goes

372
00:36:23,220 --> 00:36:29,659
down too. So regardless of so many GTM improvements that you do, you you couldn't like

373
00:36:29,699 --> 00:36:35,979
help that shift. I worked at Amazon too, and that was very much the case. Like so much depended on

374
00:36:36,340 --> 00:36:42,779
Black Friday or seasonality is seasonality everything. It was so it was so big deal. So that

375
00:36:42,780 --> 00:36:48,259
personally helped me with the layoff. Because honestly, even if I was the best marketing

376
00:36:48,260 --> 00:36:53,819
observations person in the world, times ten like it still would have happened. So I was reflecting

377
00:36:53,820 --> 00:36:59,019
on that part of my journey, and I think that it was actually a nice it was a nice realization.

378
00:36:59,020 --> 00:37:05,379
What I continue to double down on is that there will always be a need for smart

379
00:37:05,419 --> 00:37:09,979
operators to figure out how to solve problems. I just think the nature of the problem is going to

380
00:37:09,979 --> 00:37:16,569
change, you know? And whereas we used to spend so much time being in HTML and CSS

381
00:37:16,570 --> 00:37:23,289
or like duplicating databases. Like I've spent so long doing that. I now will be able to do

382
00:37:23,290 --> 00:37:28,489
something completely different. And now the things are like, how do we get everything connected to

383
00:37:28,530 --> 00:37:35,089
cloud code? How do we enable marketers? We're all using, you know, AI. And the problem now

384
00:37:35,090 --> 00:37:40,289
is how do we make sure they don't smack our customers in the face with 100 emails that they

385
00:37:40,289 --> 00:37:47,249
can create in two minutes? You know what I mean? So the job has now changed, but the goal is still I

386
00:37:47,250 --> 00:37:52,330
have a really like, optimistic and like aspirational view of marketing in general. And and

387
00:37:52,370 --> 00:37:58,929
for me, I think marketing is there to create just an amazing customer experience, which is what it

388
00:37:58,930 --> 00:38:03,249
used to be like from the beginning. That's why there's like when they talk about like packaging

389
00:38:03,250 --> 00:38:09,409
and pricing and placement, like marketing is so much more than just promotion. And if marketing is

390
00:38:09,409 --> 00:38:14,550
so much more than just promotion and like the sort of like governor of the experience then.

391
00:38:14,590 --> 00:38:19,469
Operations is so important because we're the ones that actually get it done and actually make

392
00:38:19,470 --> 00:38:25,668
things happen. I'm still very hopeful for the smart operators out there that are still being

393
00:38:25,669 --> 00:38:32,388
curious and still working hard. I agree, and I think a great metaphor for those who are curious,

394
00:38:32,389 --> 00:38:39,148
if you think about aviation, pilots are still doing the same job they were doing 100 years

395
00:38:39,149 --> 00:38:44,069
ago, but they're not having to do every single thing. There is a little bit more of monitoring,

396
00:38:44,069 --> 00:38:50,709
there's more radar. There's I don't know, I'm not a pilot, but you can be a little bit

397
00:38:50,710 --> 00:38:57,589
less, you know, pedal to the metal at all times paying attention. Then one used to be in

398
00:38:57,590 --> 00:39:03,669
terms of at least, you know, simple commercial flights. And that's a testament. Like you need to

399
00:39:03,669 --> 00:39:09,669
have a human. We're not in the Waymo stage of airplanes, but at least right now, those pilots are

400
00:39:10,389 --> 00:39:15,739
so high in demand because they know how to fix it when things go wrong. And in my opinion, that's

401
00:39:15,740 --> 00:39:21,299
where the operators who know what they're doing will succeed the most. Because you don't go to a

402
00:39:21,299 --> 00:39:25,739
doctor hoping just for a great outcome. You go to the doctor who knows how to fix it if something

403
00:39:25,740 --> 00:39:32,499
goes wrong because things go wrong. And it's how the cleanup, how you're taking care

404
00:39:32,500 --> 00:39:39,259
of afterwards is what really differentiates good from great, in my opinion. But good

405
00:39:39,260 --> 00:39:45,820
operations is incredibly creative. Like you have a finite set of resources and oftentimes a really

406
00:39:45,820 --> 00:39:51,099
lean team to accomplish things that typically require like sometimes millions of dollars to do,

407
00:39:51,139 --> 00:39:56,699
like big migrations or like understanding the data and like we figure it out. And I think that

408
00:39:56,699 --> 00:40:03,579
that whereas you can do those things faster with AI, like curiosity and creativity, isn't AI's

409
00:40:03,580 --> 00:40:09,769
Bhag like unless you tell it to you need that like driver to do it. I wholeheartedly agree, It's

410
00:40:09,769 --> 00:40:14,889
why I love our industry so much because for me, it's right brain and left brain. And just to be

411
00:40:14,889 --> 00:40:20,968
creative with our solutions and also very analytical and direct with how we're going about

412
00:40:20,969 --> 00:40:27,728
it. And so 100%, that's why it fulfills me. Okay. I want to push you on something that you've also

413
00:40:27,729 --> 00:40:33,449
referred to, or we're just going to keep drilling you on the hot seat. So you've argued that

414
00:40:33,449 --> 00:40:40,209
marketing ops should evolve into the new COO of marketing, and that operational leadership is what

415
00:40:40,290 --> 00:40:46,209
future proofs the role. So here's what I keep thinking about. So when tactical skills get

416
00:40:46,249 --> 00:40:51,609
automated, every ops professional's instinct is to claim the strategic high ground. What happens when

417
00:40:51,610 --> 00:40:57,329
the C-suite realizes they can get AI generated strategic recommendations without the operational

418
00:40:57,330 --> 00:41:04,128
complexity that comes with them? I want to key in on the chief operating officer role first,

419
00:41:04,129 --> 00:41:10,799
and to me, that person and you kind of think of like Sheryl Sandberg, like of

420
00:41:10,799 --> 00:41:17,600
Facebook back in the day. What does that person do? And it's almost like their goal is to bring the

421
00:41:17,639 --> 00:41:23,519
CEO's mission to life. You know, the CEOs want to set the vision with the board, hire the leaders,

422
00:41:23,520 --> 00:41:30,159
and from a business, from a running the business standpoint, COO, whatever comes up, they have to do.

423
00:41:30,199 --> 00:41:36,919
And for me, I've always been thinking that the marketing operations leader should step into that

424
00:41:36,919 --> 00:41:43,279
role. And right now it's a nice blend of overseeing the technology, but also being a little

425
00:41:43,320 --> 00:41:48,359
bit of like a chief of staff and like understanding what the marketing leader needs. And,

426
00:41:48,920 --> 00:41:53,878
you know, even at my work sometimes. Right, I'll see things that I know is stopping the entire team,

427
00:41:53,879 --> 00:41:58,119
like the fact that we're not using Monday correctly. We're like, everybody's using it

428
00:41:58,120 --> 00:42:02,559
differently. There's no like, alerting system. People are still sending messages to their back

429
00:42:02,560 --> 00:42:07,429
and forth over email. And when you look at that and you go like, this is incredibly inefficient.

430
00:42:07,469 --> 00:42:11,269
We're not using a project management tool. How we should be. And that typically is not. Doesn't fall

431
00:42:11,270 --> 00:42:16,029
into the realm of like a martech operator, but you can see how much it's going to help. And you see

432
00:42:16,030 --> 00:42:22,908
that the CMO is not going to do it, you know. So I think that it's like operators should be

433
00:42:22,909 --> 00:42:29,789
called to step out of their boundaries and step out of their, you know, safe zones and start to get

434
00:42:29,790 --> 00:42:35,229
into things where, hey, if we solve this problem, which increasingly become people stuff, if we

435
00:42:35,269 --> 00:42:41,269
solve this problem, things will move faster. And then I think your point on execution, I still

436
00:42:41,269 --> 00:42:48,110
don't think that we're at that stage. I was on this webinar with Zapier. They're leading in

437
00:42:48,110 --> 00:42:54,509
implementing AI throughout GTM, and when you look at it, most of the use cases were internal

438
00:42:54,510 --> 00:43:00,429
internal efficiency use cases. I think that we're at the stage where we're still just making things

439
00:43:00,430 --> 00:43:06,779
more efficient and not taking over the full execution, right. So you still have

440
00:43:06,780 --> 00:43:11,620
salespeople talking face to face with customers, and they still need to close the deal. They still

441
00:43:11,620 --> 00:43:18,100
need to sign the contract. Even with plug, like, there's still this human element of like, AI can't

442
00:43:18,100 --> 00:43:23,819
continually learn and improve the website and the platform without the guidance of. So. So I think

443
00:43:23,820 --> 00:43:28,899
that people are thinking that execution is all just like knowledge work and PowerPoint making

444
00:43:28,899 --> 00:43:34,619
and automating emails where the actual revenue drivers of the business aren't that. I still do

445
00:43:34,620 --> 00:43:40,300
think it's important for operators to step into the CEO role, and I think that when people refer

446
00:43:40,300 --> 00:43:46,019
to execution, I think it's internal. I think it's just like making admin work much faster, which is

447
00:43:46,019 --> 00:43:52,099
good, but it's not what's going to move the needle for the business long term. I wholeheartedly agree,

448
00:43:52,100 --> 00:43:56,739
I'm a big fan of the concept of separation of church and state, particularly operations from

449
00:43:56,739 --> 00:44:03,539
marketing. But I see Mops, rep ops, sales ops, any ops under

450
00:44:03,580 --> 00:44:10,529
operations, And then essentially their client is the marketers in the marketing team and their use

451
00:44:10,529 --> 00:44:17,129
cases and their needs. Because yes, we kind of have to reach across different

452
00:44:17,129 --> 00:44:23,529
aisles that are not our domain. To your point, project management can be also customer support.

453
00:44:23,530 --> 00:44:29,329
Like, oh, did you realize we could get your data here so that actually your sales rep knows more

454
00:44:29,330 --> 00:44:36,329
about this and it's really just thinking outside of the box and being willing doesn't make it easy,

455
00:44:36,330 --> 00:44:40,489
especially if you're navigating at a large company. It's really hard to do that, and people

456
00:44:40,489 --> 00:44:47,169
can be protective and need to be a little bit more open minded. But to your point,

457
00:44:47,209 --> 00:44:53,888
I agree. I think the best CMOs these days were operators of some sort within an

458
00:44:53,889 --> 00:45:00,888
operational lens, and we need more of them because without it, CMO has the hardest job. It's the

459
00:45:00,889 --> 00:45:07,589
most likely to get cut. It's the most, Most undervalued, which is mind boggling to me,

460
00:45:07,590 --> 00:45:14,350
but I think there is more rigor that can come into play if there's someone who knows how to

461
00:45:14,350 --> 00:45:21,230
speak to the business value in addition to what marketing value comes across. Yep, absolutely. All

462
00:45:21,269 --> 00:45:26,109
right. This might be the hardest question. I feel like everyone is always talking about how we are

463
00:45:26,110 --> 00:45:31,789
living in this golden age of marketing operations, and we keep collectively telling ourselves a

464
00:45:31,790 --> 00:45:38,669
story that I don't feel like fully matches the data. Do you think we're in a golden age, or do

465
00:45:38,669 --> 00:45:43,349
you think we're on the precipice of something more? I think that I'd love to. To think that I

466
00:45:43,350 --> 00:45:49,909
think that if marketing operations, which I was saying, like a couple of years ago, could lead AI

467
00:45:49,909 --> 00:45:54,789
when it comes to GTM, then I think it would be the golden age. I don't think that that's happening. I

468
00:45:54,789 --> 00:46:01,189
think that most teams are being force fed to use AI by leaders that feel like they're going to be

469
00:46:01,189 --> 00:46:05,698
missing out if they don't do that. Marketers honestly that are just trying random stuff. I saw

470
00:46:05,699 --> 00:46:11,059
this joke the other day where it's just like, oh, I spent the entire weekend clod coding this, this

471
00:46:11,100 --> 00:46:15,899
app so that now people can schedule a meeting with me. And I spent, like, wasted so much time

472
00:46:15,899 --> 00:46:20,299
doing that where, like, you could have just used candy. There's a bunch of that happening. It's

473
00:46:20,300 --> 00:46:25,300
definitely not the golden age for marketing ops, because a lot of our jobs are is being taken by

474
00:46:25,300 --> 00:46:31,899
AI, and it's been so interesting to have a front seat. I literally downloaded my

475
00:46:31,899 --> 00:46:38,619
entire I downloaded my entire US database and I put it into into copilot, and I

476
00:46:38,740 --> 00:46:45,579
had it do full on consulting data recommendations. And I

477
00:46:45,620 --> 00:46:51,859
kid you not, the recommendations were better than I could have done. Like it pulled out insights

478
00:46:52,340 --> 00:46:59,179
faster and better than I could have. And I think that that's scary. That is scary. I've had

479
00:46:59,179 --> 00:47:03,369
Claude write some of my posts and I'm just like, Holy crap. This is better than what I could have

480
00:47:03,370 --> 00:47:07,809
done. But it doesn't like change the fact that, like, I won't stop making content. That's like the

481
00:47:07,809 --> 00:47:12,249
thought comes from me. It's just that things are things are changing so quickly. I think that

482
00:47:12,250 --> 00:47:18,929
instead of a golden age right now is either a tipping point and I'm

483
00:47:18,930 --> 00:47:25,569
not afraid for myself or for you or for, you know, my colleagues out there that I that are so

484
00:47:25,570 --> 00:47:30,010
smart and always curious and always trying to make things better. I'm not worried, but I am

485
00:47:30,010 --> 00:47:35,729
worried for a good number of, of marketing operators that that again like the ticket taking

486
00:47:35,810 --> 00:47:42,810
like the button pushing they. Yeah, we hate being called that. But there are some people

487
00:47:42,810 --> 00:47:48,169
that do that and that's what I'm afraid of. I agree, and to your point, I don't think we're in a

488
00:47:48,209 --> 00:47:54,609
golden age. I think actually we're in an enlightenment era where more is being revealed

489
00:47:54,610 --> 00:48:01,279
than anything before. For your example, like you're able to better analyze your entire audience,

490
00:48:01,280 --> 00:48:08,119
you're able to enhance what you already were doing. But we're learning so much

491
00:48:08,120 --> 00:48:13,439
more, and it's going to be interesting to see how it all plays out in the end. But I think

492
00:48:13,440 --> 00:48:19,479
regardless. Like we started off with, you know, students are booing about AI and they're not

493
00:48:19,479 --> 00:48:25,599
wrong. That's also, I think, a really important heavy tension of like, yeah, they're not wrong. It's

494
00:48:25,600 --> 00:48:32,560
also not great. It's both it's good and bad. And it's we have to figure out where and when to use

495
00:48:32,560 --> 00:48:39,080
it. It's just it's like any other tool. Where is it actually helpful and optimizing what we're doing

496
00:48:39,559 --> 00:48:46,280
and where is it actually giving us tech debt quite literally a financial debt. Totally. It's

497
00:48:46,280 --> 00:48:53,279
like a first principles thing. And I think that like it always goes back to what you said,

498
00:48:53,279 --> 00:48:58,319
where if you're shooting bullets into the dark, not knowing where your target is shooting so much

499
00:48:58,389 --> 00:49:03,229
faster is not really gonna help. I do think that it's that quality over quantity. What might be

500
00:49:03,229 --> 00:49:08,389
interesting is now that a lot of the technical aspects and the execution aspects will be sort of

501
00:49:08,430 --> 00:49:13,429
automated and taken over, the case can be made that now the most strategic and the most creative

502
00:49:13,469 --> 00:49:20,389
are going to win. And maybe that's where we'll be at I don't know. Yeah I think so too. What

503
00:49:20,389 --> 00:49:25,508
do you know now after all of your not just work experience, but particularly the layoff experience

504
00:49:25,509 --> 00:49:31,029
and seeing both sides of it. What do you wish someone had told you before the layoff happened

505
00:49:31,030 --> 00:49:37,349
so that you could better approach it? It's not personal. Uh, there's like bigger factors

506
00:49:37,350 --> 00:49:41,989
happening. Like if you believe in destiny and everything happens for a reason, this is part of

507
00:49:41,989 --> 00:49:47,030
it. So I think telling myself that there's going to be a lot of personal growth that you would not

508
00:49:47,030 --> 00:49:53,949
want to go back on, I think is so important. And also, I already knew this when

509
00:49:53,949 --> 00:50:00,619
I, when I got laid off. But you have to reach out for help, not just for a job referral, but

510
00:50:00,620 --> 00:50:06,899
for yourself. And there was this Harvard study done of, you know, students that were going through

511
00:50:06,939 --> 00:50:11,379
Harvard, and they were they hit the, you know, the first year, which was one of the most difficult.

512
00:50:11,379 --> 00:50:18,138
And it showed that when finals came, the people that tended to just, like, hide away in the library,

513
00:50:18,179 --> 00:50:23,379
shut themselves and isolate them. Not only do they have a tougher time, they didn't perform as well

514
00:50:23,379 --> 00:50:28,859
than the people that form study groups that would talk, that would talk things out. It's very

515
00:50:29,059 --> 00:50:35,779
counterintuitive to when you're going through something. You actually have to reach out more, you

516
00:50:35,780 --> 00:50:39,819
know, because you don't feel like it. You might feel embarrassed or ashamed, but it actually helps

517
00:50:39,819 --> 00:50:46,499
you get through it faster and it makes you, like, really understand it more so that that would

518
00:50:46,499 --> 00:50:53,459
be my like advice is to like, lean on your network not just for jobs, but for support because

519
00:50:53,459 --> 00:50:58,768
they'll help you. They'll help you get there. Yeah I agree. And if I were to add a piece of advice on

520
00:50:58,769 --> 00:51:04,648
top of that, if you think of your network as only a referral maker, you're thinking about it way, way,

521
00:51:04,649 --> 00:51:10,329
way wrong. Because I've seen folks say like, my network is not working, it doesn't do this. And

522
00:51:10,330 --> 00:51:14,409
it's like, well, is it actually a network or is it just professional connections you've made on

523
00:51:14,409 --> 00:51:19,370
LinkedIn? I don't know. So to your point, yes, community is is of the utmost importance.

524
00:51:19,370 --> 00:51:25,969
Everything from Mike Rizzo's community to email geeks, but wholeheartedly agree. Okay, Daryl, this

525
00:51:25,970 --> 00:51:31,889
has been exactly the kind of conversation that's honest. And I think just more of what our industry

526
00:51:31,889 --> 00:51:37,290
is needing to hear from and not the, like, very shiny, sugarcoated version, but the one that you

527
00:51:37,290 --> 00:51:41,809
know, folks are having in the hallway after the meeting, we're like, oh God, that didn't go very

528
00:51:41,810 --> 00:51:46,969
well, did it? And your consistent work helping practitioners run their teams like businesses

529
00:51:47,050 --> 00:51:51,850
helped reduce friction and grow their careers. And it's really landing differently, I think when it

530
00:51:51,850 --> 00:51:56,429
comes from someone who has had to apply it to their very own situation. It's not just, you know,

531
00:51:56,470 --> 00:52:00,710
preaching to the choir, it's you're practicing what you're preaching. And so before I let you go,

532
00:52:00,749 --> 00:52:05,989
I've got to ask, who is someone we should have on the podcast? My friend Maya James is a great

533
00:52:05,989 --> 00:52:11,668
revenue marketing leader. My friend Rosemary just got a job leading marketing operations at

534
00:52:11,669 --> 00:52:18,549
ServiceNow. Awesome person, great conversation. And I'm I'm excited to be part

535
00:52:18,549 --> 00:52:23,388
of the podcast next chapter. I'm excited to what you're going to do with it. And yeah great

536
00:52:23,389 --> 00:52:29,429
conversation. Thank you. All right. Last but not least. Where can folks find you and follow along

537
00:52:29,429 --> 00:52:35,989
on LinkedIn. And my Substack is called the Marketing Operations Leader. Awesome. All right,

538
00:52:36,030 --> 00:52:41,510
Darryl, thank you so much. We I'm so appreciative. And I feel like it's been a long time coming to

539
00:52:41,550 --> 00:52:48,188
finally have this conversation. Totally. So thank you so much. Thanks, Jacqueline. I thank you so much

540
00:52:48,189 --> 00:52:53,269
to Darryl for coming on the podcast. And there's a couple takeaways I want everyone to recognize

541
00:52:53,270 --> 00:52:58,539
from that conversation. Most of the layoffs that have happened over the past number of years are

542
00:52:58,540 --> 00:53:04,939
blamed on AI, and it's actually just a cover for really bad business strategy and talent strategy.

543
00:53:04,979 --> 00:53:11,659
They've been over hiring in the war for talent so that competitors can't take those folks. And as a

544
00:53:11,659 --> 00:53:15,899
result, there's a lot of people with nothing to do. Which that just means that the layoffs are

545
00:53:15,899 --> 00:53:22,259
getting blamed on AI, when in actuality it's not that. And so it means if your job hunting right

546
00:53:22,259 --> 00:53:28,859
now, you're not competing against a machine, you're competing in a market shaped by years of really

547
00:53:28,860 --> 00:53:35,739
bad business decisions, and they're finally catching up. So it's not personal. Please don't

548
00:53:35,780 --> 00:53:41,540
take it that way, even though it will, without a doubt personally impact you also. There are two

549
00:53:41,579 --> 00:53:46,459
tiers of marketing ops professionals right now. We've got the ticket takers who fulfill requests,

550
00:53:46,459 --> 00:53:51,699
and problem solvers who use technology, people and process to drive outcomes. Which means the job

551
00:53:51,699 --> 00:53:58,049
that you need to be doing today is making sure everyone knows which one of those two you are. And

552
00:53:58,049 --> 00:54:02,809
also, if you're looking for tips and tricks on how to maybe uplevel yourself from being just a

553
00:54:02,809 --> 00:54:09,769
ticket taker. Darryl's newsletter and a great place to start. Lastly, MIT found AI is

554
00:54:09,770 --> 00:54:16,089
only economically viable in a quarter of tasks, and with Uber's CTO burning through an entire

555
00:54:16,090 --> 00:54:23,050
2026 AI budget in four months, it means that the replacement narrative your leadership keeps

556
00:54:23,050 --> 00:54:28,850
selling you is built on math that is not going to hold up to scale until we hit some sort of

557
00:54:28,850 --> 00:54:33,810
economies of scale. And so to that end, thank you so much for tuning in to the making sense of

558
00:54:33,810 --> 00:54:39,009
martech. See you next time. And a special thank you to Christine Murtaugh, who edited this episode. And

559
00:54:39,009 --> 00:54:42,849
an extra special thank you to Jenna Carter for believing this passion project meets business.

560
00:54:42,889 --> 00:54:43,970
Stay curious.