When Marketing & Engineering Collide: Navigating Alignment in the Age of AI
The relationship between engineers and marketers has never been so central as it is in the Age of AI. As we all seek to learn and educate our customers on new tech, how can we partner with our product engineering org to maximize everyone's knowledge and success?
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Welcome everybody. Welcome to the other edition of Pipeline Summit.
Today we're talking all things marketing, pipeline, demand generation, and we
're really
lucky to have Ashley Kramer here with us today. Ashley Kramer joins us from Git
Lab.
She is the chief marketing and strategy officer and she's been so kind to spend
some time with us
today. Ashley, given this audience are marketers, can you talk a little bit
about GitLab? If you're
a developer, everybody knows GitLab. But marketers might need a little bit of
an introduction,
so tell us a little bit about GitLab. Yeah, no problem. Thanks for having me on
today.
So basically at a nutshell, GitLab has a software platform we call it a DevSec
Ops
software platform that companies across the world use to deliver their software
in a secure
and fast way. And so we provide the software that people use to build their
software.
And so it's a pretty cool concept because as a marketer, we also use GitLab to
build GitLab.
So it's a really big opportunity to tell that story to the world, help people
figure out how to transform their DevSecOps practices. And that's a little bit
about GitLab.
Thank you and developer security operations. So you are selling into the DevSec
Ops persona.
It's appropriate to hear with us today because the title of the session is when
engineering and marketing collide. You're perfect for this session given your
journey.
Because usually when you see marketing colliding with something, it's typically
sales.
But given the rise of artificial intelligence and everything we're talking
about today,
you're perfect given that you started your career as a working at NASA, quite
literally,
and you've moved throughout engineering organizations. And now you're the CMO
and Chief
Strategy Officer at GitLab. So tell us a little bit about what that journey has
been like.
Yeah, it was interesting. I did. I was a computer science major. And as you
mentioned,
work at Det NASA or Oracle, some other companies in the capacity of a software
developer.
And then it turned out there were two problems with that. One, I wasn't very
good at it. And two,
I wasn't passionate about it. And I think that's okay because it gave me the
space level knowledge
of what it takes to develop software. And so I made some pivots throughout the
years into product
and then into product and marketing, product and engineering, as far as
leadership capacity.
And when I landed at GitLab, it was kind of perfect because what I market and
sell to our customers
is something that would have removed that pain that I experienced as a
developer. So I have that
empathy for who we're selling to and the challenges. And so it was sort of a
perfect circle for me to
to go through that journey, become the CMO of a company that sells to this
audience. And the last
piece I'll say, which is super cool, is I bought GitLab when I was at a company
called Altarix.
I was running product and a portion of engineering at the time. We were having
issues with quality
in our software, other things. And we brought GitLab in. There's still a GitLab
publicly
referenceable company today. And so I've been a buyer too, which is kind of a
cool part to the story.
Very cool. Very cool. So when you think about-- So GitLab's obviously been
leveraging AI and
machine learning. And you've been building AI into your workflows and your
product for a long
time. I'm somewhat familiar with your product. And by the way, thank you so
much for being a customer
as well. Absolutely. When you think about this sort of rapid-- What I like to
call sort of
more accessible AI, generative, it's funny to think that it was only November
30th, 2022,
is when OpenAI released or GA Open Chat TPD, which is amazing. So it's not that
long ago,
but it seems to have been the hottest topic on the planet. We talk about it as
a platform shift.
We've both been working this industry long enough to have experienced platform
shifts
from on-premise to cloud and mobile and social and all these platform shifts.
This one is extraordinary. Can you talk a little bit about how you think about
what this is going
to mean to businesses and how they're going to start to adopt some of these
rapidly emerging
technologies? Yeah, I mean, I think there's two ways to look at it. On the
first hand,
everybody right now seems to be when it comes to generative AI obsessed about
two things in particular. You mentioned one, chat TPD. I'm just going to go
type something and
magically exactly what I once going to appear, which doesn't always happen.
And the second piece is something's going to help me write my code for me. And
that one's
specific to the GitLab use case. And so we have competitors, a big competitor
in the market,
that came out with that one, a really flashy way to, hey, we're going to make
developers more
successful because we're going to help them write code. And so that's the first
piece in where you
have to start sort of peeling back and saying, but is that how software is
delivered? Is it just
about writing the code? Because our perception at GitLab is it's way more. We
talked about being
a DevSecOps platform. You have to plan. The product managers have to plan what
's going to happen.
Fellovers have to write it. They have to test it. They have to integrate
security. You have to get
it to market. And so while there's a lot of hype and buzz around these certain
features or
capability, we are grateful that we've been a platform since we were founded in
2011. We have
one end-to-end workflow that can make these professionals really successful.
And so we want
to integrate AI throughout, which means we might not be first to market with
some of these capabilities
like code completion, but we want to be the most secure, fast follower. And we
want to make the
entire process engineers successful across the entire process, not just allow
them to produce
a ton of code faster because if it's not secure, it's not at quality, it's not
merging with other
code. It's just going to sit their still. So that's the first piece. The second
piece is when you're
typing things into chat, GPT, we've seen the articles. Are you sure you know
where your
confidential information, if it is, is going? Is it being used to train other
models? When you're
using some kind of code completion, are they going to take the code that you're
putting in and the
refactored output and use it for maybe a model that your competitor might go
leverage? And so
that's the second piece is we spend a lot of time at GitLab talking about the
large language
models, the LLMs, and can we keep, we sell to highly regulated, very big
enterprises that this
isn't an option to leak their IP? And so the second piece is once we break
through the hype,
what is happening with your data? You can put this in your personal life too.
You can put this in
pipeline generation. Like, do you deeply understand if you're sharing any of
this in the world and if
that's okay? Yeah, you make a lot of really good points. You're talking about
the reality of
leveraging artificial intelligence in enterprise, really, you're thinking about
things like governance,
you're thinking about privacy, data security, transparency. These are all like
things that you
got to have to leverage this in the enterprise, right? That's right. I also
completely agree that
the infrastructure between whatever sort of corpus of data you have in those
workflows and these
large language models, like that's where you're building kind of defensible AI.
That's where you're
building something very unique. We share the same sentiment and we're learning
here as well and
we're learning there's a lot to do. It's not as easy as making an API call to
open AI.
So as you think about this world for marketers, right? I mean, there's a lot of
very clear use cases
for developers. They've been using this for a while, right? But as it relates
to marketers and
some of the capabilities that this unleashes, like, what are the things that
immediately come to mind
for you? I think of all of the things that a marketer, no matter what role you
have in marketing,
all of the things you wake up and you think, I have to go do this today, right?
The mundane,
the, I think about all of the things that you can automate because, you know,
when this all
started coming out, I got the question all the time, is this going to replace
my job, particularly
in certain roles? And my answer is no, it's going to make you a lot more
effective in your job because
you're going to automate all of those things that you don't like to do. And
then you're going to
actually use your brain for what it's there for, which is the creative side,
the thing that AI can't,
you know, cut through the personal interactions, the whatever it is depending
on your role,
you'll be able to spend more time on that and differentiate that way when it
comes to your role
in marketing. Agree. And that's a lot of people have sort of used this concept
of a co-pilot,
whether you're coding, whether you're writing some content, whether you're
generating imagery or
graphic design, you know, a co-pilot is, I think it's really a good term. It's
also a great way to
ease into AI because it's human in the loop. And it's a great way to start
really testing
as LLMs as powerful as they are. They make shit up. That happens. We all know
this hallucinations
are pretty commonplace. And the first sort of realization I had around, you
touched on something
I think pretty important, which is like, say, I'm going to come for all of our
jobs, right?
And, you know, my first experience with mid-journey, which I'm a, I'm a junkie.
I love it. Stable
diffusion in mid-journey. You can usually find me popping around in there. You
very quickly
realize that somebody who has a firm grasp on a lot of design concepts is going
to be able to do
a lot more with this tool. It's not about, you know, I think everything's going
to have a natural
language interface, apps and data. You're going to use a natural language
interface to communicate
with it. But the more you know about something, the more leverage you're going
to get from it. So,
I do agree with the fact that it's going to do a lot of the work that you roll
your eyes at in the
morning. That's ideal. But I also think that people who have a firm grasp or
domain expertise
around something are going to be able to be that much more effective with the
technology.
At Qualified, we've really challenged everybody in our business to think about
how they're going
to use it in their specific business function. And I've seen you're an advisor
to a lot of companies.
A lot of those are Martec companies. What's the thing you say to that? When you
talk to companies
and marketing leaders, what's the thing that you drive home in terms of if you
're not thinking
about this, you're making a huge mistake? Well, for me, number one is if you're
not thinking about
keeping people's data private. And you mentioned it, it's on my LinkedIn, so I
'll say it. But I'm
an advisor for Jasper AI, which is the content side of the house. And I just
went to their
company kickoff and did a fireside chat. And we're looking at using that at Git
Lab. But I won't
even let my team touch it until we have the legal, we understand what's
happening, what models are
being leveraged because particularly as a public company, that's a giant risk.
If anything that
we're putting in is going to be shared. And so for me, that's the number one
thing. I'm on a board
of a company too. It's not it's not Martec, but same thing they were using one
of our competitive
products. And I said, have you read the terms on that? Are you sure you
understand what's happening?
That's the first thing. The second thing is I worry when new hype comes out, it
's AI right now.
It's going to be tool here tool here tool here tool here tool here like I want
consistency. And I
told the team there in our own courage, you offer this to give me one place to
go, whether I'm a CMO,
whether I'm a day to day user of the product or platform that you're selling,
put the analytics
in there do everything in one place and drive people to that don't be just
another tool,
because there's going to be 50 million of them by the time we get out of, you
know, this whole
hype cycle, be the one that everybody comes to everybody can get the
information they need from.
Makes perfect sense. You have a DevSecOps platform, so everything you're saying
resonates with me.
One of the things that we think about a lot, and we share your sentiment with
regards to governance,
data privacy security, because I like to say that as it relates to AI,
especially in the enterprise,
we're at step three of a 10k or, you know, 100 yards into a marathon, right? It
's very new.
It's nascent. Obviously, it's exciting. Obviously, it's powerful. And obviously
, you're not going to,
you can't afford not to invest here. You know, I think people feel that. But at
the same time,
we see companies forming AI councils. And I think that's really smart. I think
that they
have a centralized place to sort of ask the right questions about if we're
going to onboard a vendor,
you want to make sure that they're responsible in their AI development and
their practices and
their governance. This is something we talk about a lot here. Do you think that
marketing teams,
I mean, engineering teams probably have this top of mind, I think. How about
marketing teams? Do
you think marketing teams have the same rigor in terms of the process to adopt
AI technologies
into their business? I think it's the responsibility of the company to ingrain
that, for sure. And
I will say, you know, we did that from the very beginning at GitLab. We had,
you know, the company
message, we repeat it. We're not allowed to use certain things like chat TPT on
our work computers.
Do I still think some people are probably? Do I think it's engineers? No. So,
so do I think we need
to continue repeating that message? Yes. Because the fact of the matter is you
and I are probably
more technical than some marketers out there. So like when you start talking
about LLM and
hallucinations and IP being shared, I think it's harder sometimes for them to
conceptualize what
that means. And so it's continuing to repeat that message and continue to help
them understand at
the right level why this could be a risk. Translate's another personal life too
, by the way. It drives
me nuts when I see people on social filling out these like surveys and putting
their picture in
and I'm like, oh, there's just capturing all of your data. This is why my
parents are not allowed on
on certain social sites. They will participate in those. Yeah, 100%. You know,
I think that the
onus does fall on the company to, you know, when we sell products into
companies like we're very
proactive at, you know, these are the questions you should be asking. And here
are the answers to
those questions. You know, we really do feel like you need to lead, be privacy
first. That's,
we think that's very important. And I think a lot of us, we've got a lot of
sales force DNA in here
and at Salesforce, obviously, we, you know, we really need to convince everyone
that your data
was okay in the cloud. You didn't need to sort on premise. So privacy first is
a, I think it's a,
it's an important motion here. When you, you've got a pretty big team at GitLab
. And, you know,
when you think about, you know, not only the entire company, but you're just
your entire marketing
team, like what kind of process do you have for evaluating and introducing new
tooling and new
technologies across the various marketing teams, your average company?
Yeah. I mean, I have, I have a VP leading each functional area. And that does,
it is a large
team because sales development, it's different in different companies. It does
report under me
in marketing and they're the ones that actually discover that VP was the one
that came to me and
said, it's time to replace what we're using. We want to use qualified. And so
we call them the
directly responsible individual, the DRI who will be leveraging the tech the
most is the one for
to go and seek out and strategically figure out where it fits. Then we have a
marketing ops team
who then takes it and figures out how's it going to fit into our stack.
Think the boring stuff like licensing, we're still paying on this. What are we
going to do
about that? And then I have that person as the responsible individual right now
of the privacy
side and saying, okay, let's take two double clicks, go talk to legal, make
sure that we understand
if this is going to keep our information, whatever we're using for it safe and
secure. And so it's
sort of functionally, you find what you need to, and I am pushing the AI thing
right now, I think
at GitLab, we're thinking a lot about AI in our platform. I don't know that we
're thinking
enough, at least in marketing about AI to improve our business practices and
our processes and
those types of things. Yeah, absolutely. And it's kind of interesting because
you see both
side of the coin, right? You're building, shipping, selling, supporting
products that are leveraging
AI and you're having those conversations at the same time, you're consuming new
AI products as well.
You're obviously a perfect person for GitLab, given that you've had, you have a
very strong
technical foundation, you have a lot of experience as an end user of that
product literally.
When you think about GitLab and how you're operating, do you think that the
engineering team
and the marketing team are thinking about AI in similar ways or do you think
there's,
they think about those things differently? So what we did when the hype cycle
started
earlier this year, that's when it really started taking off is we formed a
cross-functional group
that includes engineering, product managers, marketing, and a few people from
the field,
like we have field CTOs that are in front of customers all day. They met every
day for a while
and now we have the forums, like the Slack channels. And so I think the answer
in this case is yes,
not always, but when it came to AI, because this was such an important focus,
we really fostered
that interaction. We're asking the field to bring us back the clear feedback,
okay, you just
demoed this or the customer just tried this in beta, did the messaging land for
them and is the
product working and are we messaging it the way that it should be working? And
so in this case,
yes, because of the way that we've done it, not always though when it comes to
engineers
and marketing. We speak marketing and they are deeply technical and bridging
that gap,
critically important. That is actually, that's exactly what I was going to ask
you next,
given that you've made this journey, you've made this transition and knowing
how much you had to
learn along the way, how do you bridge those two worlds at GitLab? In my case,
because I have that
background, I try to lead this by example. And a lot of the team that I've
brought in have been at
other technical companies, but I have a code word for them, which is not a code
word at all,
which is this is too much marketing speak. And so it's at some company at Sales
force, it was probably
great, honestly, because you were selling to go to market leaders and that
works. That's why they
use the celebrities for all of their promotions and everything, but it doesn't
work in DevSecOps.
And so I personally try to lead and then the team follows the lead of this
maybe too much
marketing speak. We also are not afraid to float something by our CISO or our C
TO or our product
leader and say, hey, does this land for you? Because you are the people we're
selling to at
other companies. And so we have that collaboration as well. Yeah, absolutely.
Actually, I feel like
I could talk to you about this all day. You have a fascinating journey. We're
big fans and we really
appreciate you joining us today and sharing some of your insights. So thank you
very much. Yeah,
appreciate the time. Enjoy the conversation. Thanks.
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