Startup Spotlight: How Scale AI is Redefining Federal Defense with AI | The Pair Program Ep33

In this episode, we hear from Ben Youngs and Kathryn Harris, leaders at Scale AI. Get an inside look into this startup’s mission of accelerating the development of AI applications, from the world’s largest tech companies to the federal government.

They discuss:

• The key problem that they’re trying to solve: how to augment workflows so humans produce higher quality, more effective work.
• The work their team is doing at Scale AI and how they’re bringing AI into the defense and intelligence sectors.
• How they hack bureaucracy by really knowing the customer and their specific needs.
• What they love about being part of the team at Scale AI!

About the Guests:

Ben Youngs is the Head of Solutions Engineering - Public Sector at Scale AI. Prior to Scale, Ben worked at In-Q-Tel, the strategic investor for the Intelligence Community. At IQT, Ben led investments in enterprise software. Prior to IQT, Ben supported multiple IC and DoD customers as a contractor designing, building and maintaining large-scale data and analytics platforms.

Kathryn Harris is the Head of Growth (Defense) at Scale AI. Kathryn is a strategist and growth executive advancing national competitiveness through defense and commercial technologies.

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Welcome to The Pair Program from hatchpad, the podcast that gives you

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a front row seat to candid conversations

with tech leaders from the startup world.

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I'm your host, Tim Winkler,

the creator of hatchpad,

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Mike Gruen: and I'm your

other host, Mike Gruen.

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Tim Winkler: Join us each episode

as we bring together two guests to

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dissect topics at the intersection of

technology, startups, and career growth.

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Hello, everyone.

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Welcome back to another

episode of The Pair Program.

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I'm your host, Tim Winkler,

joined by my cohost, Mike Gruen.

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Mike, how's it going?

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It's going all

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Mike Gruen: right.

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Um, I, I failed you.

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I know you reached out to me and

you wanted to know what topic we

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should cover at the very onset.

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And I totally, I was like,

Oh, I'll get back to you.

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But I haven't,

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Tim Winkler: did you

come up with anything?

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I do.

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Um, and I'm drinking it right now.

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Have you, you heard of this brand?

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This drink brand?

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No, I have not.

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Have either of you been?

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No, I'm intrigued.

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Yeah.

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So it is essentially it's an energy drink.

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Um, and it's a beverage brand

that's been getting more and

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more popular amongst kids.

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I'm not one of those kids, but I, I,

I've been hearing about it quite a bit.

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So, uh, it's a drink created

by the YouTube personality,

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Logan Paul, Logan Paul.

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Um, and it's been buzzing in the news

recently, uh, I've been getting a lot

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of scrutiny by the FDA because there's

an insane amount of caffeine in it.

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So it has 200 milligrams, uh,

per, I guess, 12 ounces, and they

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equate that to basically like six

cans of Coke or two Red Bulls.

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And they specifically market it

to kids, but there's a, a notice.

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It's like, if you're under the

age of 18, you're not supposed

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to be able to purchase it.

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So I don't think anybody's checking

IDs or anything, but I was just

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curious if either of you had, had

tried it or purchased it for your kids.

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Cause I'm, I'm enjoying, uh, and

it's completely marketed to kit.

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You can tell like this one's

actually called ice pop, right?

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So it's like, nice, exactly

what you would think.

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And it tastes delicious, but.

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You know, by the end of this, if I'm

not bouncing off the walls and it's

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just a note that the prime prime

is working, it's magic, but get

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Mike Gruen: it anywhere.

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Your cherry vapes are

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Tim Winkler: sold.

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Yeah, cherry vapes will

be sold alongside of it.

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Yeah, it's, it's funny though.

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But like, it's, it's quite genius

with, uh, so they, they tagged a, uh, a

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sponsorship or partnership with, um, UFC.

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So it's like the official drink of UFC.

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And so, I don't know, you, you

started getting these partnerships

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and next thing you know, it's, yeah.

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Every kid is trading at the

cafeteria, uh, the table.

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So, so

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Mike Gruen: did you specifically not

name them for those of us like, or

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for any particular reason, because

the people on the, who are just

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listening to the audio aren't going

to necessarily know the brand, but

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Tim Winkler: I'm pretty sure I'll

have to just promote it in the,

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in the show notes at the end.

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Um, cool.

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Let's, uh, let's give our listeners

a quick preview of today's episode.

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So.

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Today we're going to be talking a little

bit about artificial intelligence, uh,

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specifically examining some use cases.

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And how it's implemented in

more regulated industries like

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defense and national security.

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Um, so that for those newer listeners to

the show, you know, we've been driving

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a little bit of a light mini series

of episodes that dive deeper into the

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marriage of commercial tech and government

and specifically areas like defense tech.

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Space tech, energy, climate tech.

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And so for today's discussion,

we're really going to be pulling

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back the curtain on how AI is being

applied within the defense sector.

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Uh, and we've got some fantastic, uh,

guests joining us, uh, with a specific

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use case from a very reputable AI

company called scale AI, uh, Catherine

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Harris, who is the head of growth

for scale AI as defense vertical.

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And also notably served as a

senior advisor at the Pentagon and

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Ben Young's, the head of federal

solutions engineering at scale AI.

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So Catherine and Ben, thank you both for,

for joining us today on the pair program.

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Thanks.

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Good stuff.

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All right.

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Now, before we dive into the

discussion, we do kick things off

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with a fun segment called pair me up.

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Uh, this is where we kind of

all go around the room, shout

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out a complimentary pairing.

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Mike, why don't you lead us off?

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So,

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Mike Gruen: yeah, at the risk of

possibly doing a dupe, I, I seem to

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recall having done this one, but I

couldn't find it listed anywhere,

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uh, mojitos and, uh, plantains.

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Um, this is the time of year when I

go to Baltimore, there's a restaurant

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called, uh, little Havana's, uh,

and I made some friends there

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and this, we just sit out on the.

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Out on the outside area, uh, patio over

to looking the harbor and, uh, drink

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mojitos, eat plantains and have fun.

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Tim Winkler: Sounds great.

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Sounds like the time of

weather for it right now, too.

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Exactly.

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Yep.

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Yeah.

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Um, cool.

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Yeah, I don't think I was hoping you

were going to call me out if it was.

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No, it's not to do.

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All right.

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Awesome.

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Awesome.

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We actually have a running

board for the guests.

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We have a running board of just,

you know, it's been like 35 plus

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pairings that have been not just from

us, but then like 2 other people.

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So usually we get bourbon or some sort

of a food type for, for one of them, but,

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uh, uh, haven't heard the mojitos one yet.

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So we'll, we'll slide.

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Um, all right, cool.

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I'll go.

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Uh, so my parents going to be the cereal

aisle, um, and anxiety, uh, partially

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because, so I went to the grocery

store the other day, just picking up.

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A couple of items and I'll preface

that my wife is usually the

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one that goes grocery shopping.

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She loves it.

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Me not so much.

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So for me to intentionally go and

grab groceries, um, it's a little

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overwhelming and I don't quite

know the lay of the land very well.

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It usually takes me a little

bit longer to find what I need.

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So anyways, I wind up in the cereal

aisle and I'm scanning the shelves,

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just kind of walking back and forth.

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And I'm not joking.

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I think I was there for close to

15 to 20 minutes in this aisle.

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And I think I just had like a blank

stare across my face primarily because

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I'm in all just like the sheer amount of

cereal that lines these shelves and kind

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of questioning, you know, what kind of

Cheerios, you know, do we really want?

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And I started to count like the

number of different types of Cheerio

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boxes that were being offered.

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And I'm, and I'm not joking.

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There were 17.

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different kinds of Cheerios, 17 of these.

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And you know, when you have that

many options, it's just, you kind

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of get that decision fatigue.

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Um, and so I had a light wave of

anxiety hit me, you know, wasn't sure

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if I was making the right decision.

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You know, should we get the new,

the new flavor that just came out?

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Some cinnamon, berries, swirl,

anyways, long and short.

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It's a ridiculous amount of

cereal, um, that our grocery

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stores are pushing out and decision

overload led to extreme anxiety.

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So my, my, uh, pairing is

cereal Isle and anxiety.

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Um,

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Mike Gruen: did you say fuck it

and walk away with your cart in the

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Tim Winkler: aisle?

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I think at one point I probably was

going to, but it was, uh, I had to bring

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something back and walk away empty handed,

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Ben Youngs: um, a lot of, uh,

a brightly colored, uh, cereal

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boxes marketed to children.

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A lot of good options there.

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Yeah, I

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Mike Gruen: think you

have a theme going today.

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Uh, yeah, stuff, things marketed

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Ben Youngs: to

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Kathryn Harris: kids.

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I was going to say maybe, maybe

lay off the caffeine drink

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next time you go shopping.

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Tim Winkler: It's a

good, it's good advice.

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I actually think I ended up going

with a, like a lucky charms.

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Um, Oh, lucky charms oatmeal.

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So they make like cinnamon toast

crunch and lucky charm oatmeal now.

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So as I just said, forget

the cereal, um, moving on.

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So, all right, I will, uh, I'll

kick it over to our guest now.

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So, uh, Catherine, why don't

you go ahead and give us a quick

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intro and tell us your parent.

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Kathryn Harris: Sure.

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Uh, hey, great to meet you all.

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Uh, yes, I'm Kevin Harris.

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Uh, I run growth at scale.

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Uh, for the past 5 years, I've been

in different, uh, venture backed, uh,

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commercial technology firms, bringing

that tech into DoD, spent a number of

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years at the Pentagon as a DoD civilian,

and then started my career at SAIC.

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So all around defense technology,

uh, for, for many, many years.

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Uh, so my pairing, I'm keeping

it on the food and summer theme.

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I'm going to go with, uh, fresh

peaches and living in the moment.

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Right now is peach, uh, peak peach season.

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And I think they're one of the

only, you know, fruits or vegetables

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where you have to bite and season.

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You cannot bite out of

season and enjoy it.

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And so right now just

enjoying it, living it up.

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And then at the end of the season,

I'll wait 11 months till next summer.

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Uh but just kind of live in the

moment, enjoy it now, and appreciate it

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Tim Winkler: and that's what I'm doing.

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Solid.

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Summer peaches.

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Can't uh can't beat it.

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It's a such a great fruit.

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Ben Youngs: Yeah.

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It's a favorite to bring down to the pool.

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Yes,

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Tim Winkler: absolutely.

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Um, it reminds me, um, my wife and I

took a trip outside of Grand Junction,

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Colorado to a little town called Palisades

and they're just notoriously known as a

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tourist destination for their peaches.

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Um, one of the things that stood out.

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So it was the right time of year is

about July a couple of years ago.

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So, um, perfect time to

go and pick some peaches.

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Awesome.

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Uh, Ben, uh, how about your

intro and your pairing?

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Ben Youngs: Yeah, thank you.

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Great.

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Great to be here.

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I'm Ben Young's, uh, lead,

uh, the, the federal solutions

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engineering team for, for scale.

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I've been with the company

for, uh, just under a year.

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Um, prior to that, I was, uh,

spent six years at, uh, Incutel.

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So the strategic investor for

The intelligence community

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and department of defense.

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So I kind of, um, did a lot of work in

evaluating startup company technology,

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especially in the enterprise software

worlds, um, looking for opportunities

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to bring innovative technology into

the government space and, um, actually

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going and kind of vetting and engaging

with a lot of those companies.

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So did six years there.

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And prior to that, I spent a decade

in and around government as a

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contractor, primarily building.

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Um, large, uh, large scale

analytics systems, geospatial,

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uh, platforms, the like.

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Um, so, uh, my pairing today, uh,

maybe not the most exciting thing,

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but with a, uh, with a nine month

old, uh, infant, it's something

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that's, that's increasingly rare.

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I'm going to go with, uh,

coffee and a good book.

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Like on a, nothing better to me

on a, you know, weekend morning.

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Nice quiet day.

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Um, and just being able to grab a

coffee and read for a little while.

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Um, and, uh, use that

as a form of meditation.

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Nice.

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Tim Winkler: Oh, that's great.

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What's a, what's a book of choice that

you're, that you're reading right now?

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Ben Youngs: Oh, gosh.

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Um, I, I usually kind of stick with, uh,

with a lot of, uh, nonfiction, but, uh,

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I'm currently reading is that the three

body problem, the fictional, um, uh,

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science fiction book, really interesting.

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So I'm just on the first book of that.

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So I'm kind of right

in the middle of that.

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I, I, uh,

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Mike Gruen: I started that last summer

as an audio book and I was like, this

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is not working for me as an audio book.

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Ben Youngs: I

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totally hear you.

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I don't know, you know, the first

half of it, I was like, I'm not

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sure if I'm tracking everything.

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It gets better.

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Um, but you know, I think I need to

be better at kind of cutting sometimes

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when I'm, when I'm not feeling it, but

I'm going to stick through this one

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and I'll let you know how it finishes.

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Awesome.

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Well,

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Tim Winkler: and kudos

on the nine month old.

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I've got a seven month old.

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So I think one of my parents was, um,

newborns and expresso machines because,

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I mean, you know what it's like, right?

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I mean, it's the sleep is, uh,

it is not quite what it once was.

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Ben Youngs: That's for sure.

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Yeah, for sure.

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Well, congratulations to you as well.

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Tim Winkler: It really is.

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Um, awesome.

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Well, yeah, we're, we're

excited to have you all.

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Um, like I mentioned, we're going to Be

talking a little bit about, you know,

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AI applications in the defense sector.

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Um, and we are, uh, obviously, you

know, talking to you all coming from

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a San Francisco based AI company.

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Um, love to, to hear firsthand.

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You know, some of these real world

use cases with how it's transforming

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the defense industry, um, discuss some

of the challenges that startups and

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commercial companies face, you know,

when implementing AI solutions, how they

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can overcome these obstacles and such.

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Obviously, there's a lot of cultural

challenges of AI adoption and defense.

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So breaking down some of that in

the discussion to help technologists

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and founders who are tuning in.

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Uh, you know, help them navigate

those waters and and do so as

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efficiently as as possible.

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Uh, 1st off, why don't

we, uh, have Catherine?

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Why don't you kick us off and

provide us a little bit of

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background and context on on scale?

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AI?

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Because, you know, you you're considered

a dual use technology company.

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And you have some commercial

applications for your tech, not

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just defense and national security,

but you can shed some light on

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scale AI and the kinds of problems

that you all are solving at large.

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Kathryn Harris: Yeah, certainly.

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Um, so CLI has been around for a

number of years, founded by Alex Wang,

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really got our start, you know, on the

commercial side in the autonomous vehicle

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industry, uh, doing data labeling there.

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Um, have grown quite significantly on

the commercial side, and a number of

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years, uh, got involved on the defense

side, helping with data labeling

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for, uh, intelligence missions and

functions and have expanded that

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to the Department of Defense and

other, um, federal civilian agencies.

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Corporate headquarters

is in San Francisco.

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Federal headquarters is in Washington, D.

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C.

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We have a global footprint and are

really very lucky on the federal side.

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That we have all of the business

functions in place to work with.

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You mentioned a lot of

the cultural barriers.

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There's a lot of administrative security.

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Business functions that commercial

companies require to do work

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with the federal government.

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And we're very lucky that we've been

able to invest in those and have really

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great federal partners to help us get

those accreditations and really put our

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commercial technology to the full use

across a range of duty and until missions.

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Tim Winkler: Awesome yeah, I'd

love to peel back some specific

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projects that you all are working on.

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Um, I'm going to kick

it to Ben real quick.

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Um, Ben, if you maybe can provide our

listeners with a little bit more clarity

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on your specific role too, because I think

this plays into the conversation, you

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know, the role of solutions, solutions,

engineer solutions, architect, it's.

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Something that can be defined very

differently from one company to another.

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So, you know, maybe explaining your

role and then we can jump into some

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examples of some of these successful

AI implementations that you all are

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working through in the defense space.

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Ben Youngs: Yeah, happy to.

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Um, you know, it's interesting.

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I think of myself kind of as

coming from the technical world.

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Uh, Been hands on for a long time.

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Um, and now really in this role, head

of, uh, solutions engineering, we

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actually support our go to market team,

which, which Catherine runs part of it.

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And so, um, really what, what it kind of

boils down, um, on, on our side within

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the company is we, uh, work very closely

with our business development teams

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to engage with potential customers.

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So, um, thinking of kind of pre deal

almost like pre sales engineers, um,

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Where we're going out and doing a lot

of the, uh, Opportunity scoping from

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a technical perspective, requirements,

gathering, understanding specific use

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cases that customers may have, um,

really, you know, when the, when things

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are working well, we're, we're learning

more about those customers and, and

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what really they need on their side,

you know, what existing systems they

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have, what their data is like, you

know, all their various pain points

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that they're really trying to address.

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Um, and we try to.

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Absorb as much of that as we can,

you know, in, um, collaboration with

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our business development partners.

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And then we take that information and go

back to our internal engineering teams,

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our product teams, all of those groups,

um, and, and really kind of figure

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out what, what sort of solutions and

capabilities that we can bring forward.

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And then that can include actually

building out demonstrations

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and proofs of concept.

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Um, hoping to scope specific efforts from

a contractual standpoint, helping with

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proposals, all of that sort of thing.

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So wherever we can come in from kind

of a, a first, uh, first tier of

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technical support for our, uh, for

our sales folks, um, being involved

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in, in trying to kind of figure out

how we can bring our technologies,

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uh, to address customer needs.

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Tim Winkler: Yeah, uh, it's, it's a,

it's a position that obviously is super

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important to the business at large.

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Uh, it's not easy to find that

right balance of someone that

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can do the customer interfacing

and the back and forth between

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the technical side of things.

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Obviously coming from a technical

background is, is a pretty important and

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understanding some of those key areas.

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Let's let's talk about some of those

areas, you know, maybe playing out a

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scenario of, um, of an implementation.

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I think, you know, there's a lot of,

um, it's tough to really, I don't

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know, uh, unpackage some of these,

you know, what might seem like

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such large scale implementation.

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So, uh, walk us through 1 that that you

would say is, you know, maybe 1 that's

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You know, a success, but also something

that, you know, has been, you know, uh,

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uh, easier to kind of wrap your head

around, uh, for, you know, some of these

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defense oriented projects, um, Catherine

Benway, either of you can can lead it off.

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Kathryn Harris: Yeah, I mean, I think

just before getting into specific

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examples, I'll just pick up a little

bit on some of the themes that.

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That Ben had talked about in his role and,

you know, sort of how we partner together.

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Um, 1 of the things that I love about

business development in general, and

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working with solutions engineering

teams is it's actually not selling.

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And a key thing Ben said is

about learning and listening to

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customers and really unpacking them.

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And I think, you know, for us working

in the federal sector, the technologies

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and solutions we're selling.

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They're not commodity solutions, um,

and being sort of early technology and

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working with a lot of early adapters

requires a lot of not fully customized

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solutions, but a lot of hands on and, you

know, a lot of missions and organizations

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across the federal government.

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Um, their missions are so diverse

that their needs are really unique.

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And so being able to sit down and

spend time with them and unpack their

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mission and learn and listen and not

just understand what are the technical

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requirements, but what's the, the

overall mission that they're trying

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to achieve and then also understanding

it and the business context of how.

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D.

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O.

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D.

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acquires and implements and sustains

technology can be very different

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across different customers.

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And so when we sit down, you know, or,

you know, at the beginning of a journey

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with a new customer, it's it is a

full range of all of those topics that

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we really unpack, which I think, you

know, makes it interesting, exciting.

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And each deal is different each day.

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And each customer is different

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Ben Youngs: in some ways.

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Mike Gruen: I think one of the other

things I'm curious if you guys when

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you're engaging one of the things

so I was in that role for a little

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while, uh, on the customer facing

government side selling into Intel.

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Um.

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And, um, I, I, I like to think of

myself, I was lucky in that I was

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both the pre sales and the post sales.

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So I, my vision, what I was working with

them on, I was then getting to deliver on.

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So I knew how it was all

going to come together.

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And I think 1 of that's 1 of the

big challenges is when you have 2

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separate units and you have somebody

who's out there, um, coming up with

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that solution and then communicating

that back to the engineers.

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That's, that's like 1 of the challenges.

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Um, and I'm curious, like, how,

how you sort of handle that.

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Um, cause it can create good tension

and it can create bad tension

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Ben Youngs: for sure.

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Yeah, I can take that one.

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So yeah, we're aligned, you know,

so, so the, the SCT, my SCT, um,

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is, is largely pre sales focused.

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Um, we have field engineers, um.

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That do most of the, the, um, post deal

kind of, uh, technical work, of course,

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in collaboration with our engineering

team, software engineers, machine

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learning engineers, that sort of thing.

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Um, and, and quite honestly, there,

there can be some friction there, right?

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So there's, uh, sometimes the, the

tendency, uh, in some spaces that, uh.

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Kind of design this whole thing and then

throw it over the fence and say, all

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right, we've got a contract in place.

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Now you need to execute on it.

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It's almost like, uh, um, uh,

developers and ops folks, right?

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Like, we've built the software,

now you need to, to maintain it.

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Um, I, I think how we address that is

certainly just, you know, really having

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good communications skills and having

good relationships with those other teams.

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Um, but it's also having

processes in place.

426

You know, so we're, we're engaging.

427

Um, you know, with our engineering team

specifically, like they're almost hungry

428

for this information from customers,

like what we're getting from these

429

conversations, they want to know, like,

what are people interested in, what are

430

the things they care about, or like,

why are people asking for these sort

431

of features or, or, or capabilities?

432

So they, they want to hear from us,

which is a good position to be, and

433

they want to hear that information

and understand kind of why.

434

What customers are looking for and

why they want those sort of things.

435

So, um, that's all part of the process.

436

We try to bring those engineering folks

and the software engineers and as soon

437

as we can in the process, and they

support us every day and, you know,

438

helping to be able to better articulate

our capabilities and that sort of thing.

439

Same thing for the field engineers.

440

We have a formal kind of, uh, process

for handing over work when it goes

441

from kind of the pre deal to post deal.

442

Um, but, but it really does have to be not

just a handoff, but kind of a continuous.

443

We're all on one, one larger team.

444

And, you know, there's going to be,

there's going to be times where we

445

need to surge and support, um, RFE

counterparts and vice versa too.

446

And I can think of A variety of examples

where, uh, we've called in our field

447

engineering folks to help us with things

that help us actually go out and, uh,

448

talk to customers, potential customers.

449

So I think, you know, to, to really

the, the biggest two things are kind

450

of, uh, um, process and, and, and

communication and, and, and establishing

451

maybe three things, of the org.

452

Yeah, I'm

453

Mike Gruen: sure the, the relationship

building is like a critical part, right.

454

That you have to have that trust.

455

And it's like, look, I didn't do Mike.

456

I'm not malicious.

457

I'm not trying to make it hard for you.

458

So let's, you know, if you, if you

know that that going in, then it

459

makes everything else a lot easier.

460

Um, so that's cool.

461

Um, and I think 1 of the, um, the 1 of

the things that I saw, because there were

462

in that team that I was on, we also had.

463

Separate that we're doing, you

know, pre sales and then there's the

464

implementation engineers and where

I saw that relationship work best.

465

It was when, you know, they could

actually explain like, this is

466

actually what I was thinking.

467

Like, it wasn't it was a lot of

like, meeting and talking it through.

468

And then the person who's doing the

implementation was like, oh, I understand

469

why you think you can do it that way.

470

And that makes sense.

471

Or yeah, I think now I understand

why you think you can do it that way.

472

But like, here's how we'd

actually have to implement it.

473

And um, and so it was a good

education back and forth and they.

474

Okay.

475

Helped each other.

476

I think that's an important part and

it's not just throwing it over the wall.

477

Um, so that's

478

Ben Youngs: great to hear.

479

Yeah, go ahead.

480

No, go ahead.

481

I was just gonna say yeah, I think

you know, uh, oftentimes in a startup

482

You know, there's there's not those

kind of formal processes in place.

483

I think as we've matured as a Certainly

as a federal business unit but I think as

484

a company overall having those processes

to when we're scoping an opportunity and

485

we're thinking about You know, what would

this look like if we were to actually

486

build something, um, for a customer?

487

Like, what would this look like?

488

And are we asking the right questions?

489

And We're actually kind of documenting

this and having these conversations both

490

formally and informally that everyone,

you know, when the process is working,

491

everyone's kind of on the same page there

instead of the, we're going to do this.

492

We talked to the customer and hey,

engineering team, go build this.

493

I think over time, we've gotten better

at, at kind of understanding what needs

494

to happen as part of that process.

495

And everybody feels pretty

comfortable with that.

496

And there's no surprises there.

497

That's awesome.

498

Kathryn Harris: And when you say

that that process, I think is even

499

more important for a product company.

500

I mean, I think a lot of the, you

know, companies that work with the

501

federal government, you know, their

services companies, or they build

502

custom widgets that the government

that owns, but, you know, company

503

like scale and many others, you know,

being product companies where we.

504

Build technology, you know, with our

own resources and own that IP and

505

then try to build something that can

service many customers that internal

506

feedback loop of understanding customer

needs across different customer sets,

507

building it into the product, deploying

it and having a feedback between, you

508

know, business development, execution,

delivery, product engineering,

509

I think is even more important.

510

Mike Gruen: Yeah, I totally agree.

511

I still remember that moment after I

joined the company as I and like having

512

that engine talking core engineering

and talking to them about the things

513

that I was seeing and the changes

I want to make to the corporate.

514

It was a product.

515

Right.

516

And as I and getting that, like, yeah.

517

Oh, this engineer, he's a,

he knows what he is doing.

518

We're gonna give him access to the

actual core engineering report, like as

519

one, you know, and, and being able to

submit pull requests and stuff like that

520

back to the, to the main application

and being able, you know, and having

521

that trust between the, the two and

being able to explain and, and making

522

the product better, like identifying

those things and overall making both

523

the, by doing the government work,

making the commercial product better.

524

Um, and I think that

that's an important part.

525

Ben Youngs: How do you guys,

526

Tim Winkler: oh, sorry, I was gonna

say like, what are some of the actual

527

like use cases that are being applied?

528

Um, I think this is something that,

you know, I'm personally intrigued in.

529

Um, you know, we, we work

a lot of companies that are

530

building, you know, defense tech.

531

Products that maybe are, you know,

satellites that are helping, you know,

532

warfighters on the front lines, but maybe

a couple of these AI specific scenarios.

533

I'd love to hear more about that.

534

Kathryn Harris: Yeah, so, um,

I think a simple way to start

535

thinking about it is, um, on the

battlefield and off the battlefield.

536

And, you know, there's a lot of interest

in, you know, um, how AI could be

537

used for warfighters and lethality.

538

And there's a lot of ethical concerns.

539

And I think there are a lot of.

540

Operational use cases that are very

ethical and areas where we're involved

541

wasn't happy to talk about that.

542

But 1 area where there's a

tremendous growth that we're seeing

543

is sort of back end admin support.

544

I mean, you think about

the Department of defense.

545

It is probably 1 of the largest

enterprises in the world,

546

largest employer in the U.

547

S.

548

Tremendously large health care system,

huge global supply chain system.

549

It has its own educational system,

research system, judicial system.

550

I mean, it's it's almost,

you know, it has so much.

551

Um, and so if we can help the Department

of Defense make better decisions, invest

552

its resources, have more efficient

business functions, make the everyday

553

lives of soldiers, sailmen, sailors,

airmen, Marines, Coast Guardsmen,

554

Guardian, and their families, uh, just

have a better experience, that's great.

555

And so one of the areas that we're focused

on are things like that, just basic, um.

556

Administrative business functions

and applying against that.

557

And certainly you see that growth, um,

in the commercial sector as well in all

558

kinds of verticals and industries, um,

on the more sort of operational side,

559

you know, core war fighting functions.

560

Um, we see a lot of applications on

intelligence and computer vision, um,

561

and autonomy, autonomous systems, uh,

planning, helping, uh, military planners.

562

Understand their environment, develop

plans, develop courses of action,

563

be able to do that very quickly.

564

Um, so a lot of different use cases

for both sort of, you know, traditional

565

war fighting as well as, um, you

know, back office administrative,

566

uh, business functions as well.

567

Tim Winkler: Yeah, I always think it's

an interesting, um, concept with, I

568

think I was reading an article from

Palantir back in the day where, you know,

569

they were doing user research, right?

570

They're using user research and, you

know, war settings, um, you know,

571

flying in with, with some soldiers to,

you know, get that feedback firsthand

572

on how they're using XYZ product.

573

It adds a level of, you

know, it, it, it, yeah.

574

Intricacy that, you know, isn't really,

you know, this widget that, you know, you

575

can just kind of bounce back user research

from this product person to this user.

576

Have you all experienced that?

577

I mean, that's 1 of those things that

makes, you know, really gathering product

578

feedbacks a much different level than,

you know, a different B2B setting.

579

Ben Youngs: Yeah, absolutely.

580

It can be challenging.

581

I mean, um.

582

Talking about the various kind of

challenges and working with federal

583

customers, especially as you get into

sensitive or classified environments that

584

you know that that sort of feedback loop.

585

This is a little bit more difficult

and can definitely make it more

586

challenging to help bring that feedback

in and adjust course and kind of

587

the capabilities you're providing.

588

Um, so.

589

There's a variety of

ways to work with that.

590

Certainly it's being able to have people

that come from those, those environments

591

and can, can be in those environments

and, and kind of see firsthand what's

592

going on and talk to those users directly.

593

Um, but it's going back to kind

of what we were talking about

594

in having those conversations

even pre deal with customers.

595

Um, Continually engaging with with various

groups and and most of the time listening

596

and and just learning about use cases and

what they're what they're looking for and

597

trying to roll that into our capabilities.

598

It's a there are a variety

of challenges around that.

599

It's different on the federal side

than maybe having commercial products

600

where you're getting direct, you

know, you're getting a Uh, through

601

your support channels and email and,

you know, probably all these various

602

different forms of inbound feedback.

603

Um, oftentimes it's not like that

on the federal side and you have

604

to go out and solicit feedback,

uh, directly from customers.

605

So it's, uh, it's definitely

a different way to work.

606

Um, but that's kind of on us to, to

make sure we're proactive and going

607

out and having those conversations

and, and, and asking our customers

608

or potential customers for feedback.

609

I can't tell you how my, oh, sorry.

610

Kathryn Harris: I would say a

really interesting example of that.

611

Um, we have a contract now

where we're deploying, um, uh.

612

A large language model solution

that end users can directly interact

613

with, and it's intended to be used

as part of a military exercise.

614

And there's probably 10 different

user groups globally distributed in

615

all these different organizations.

616

And it was a really

interesting lesson to me of.

617

When you put a product in the wild where

users take it and we had one user group

618

that used it for a completely different

purpose, something we had not considered

619

and but they got a lot of value out

of it and they really enjoyed it and

620

actually we're working with them to spin

out a separate contract directly with

621

them and have them be able to continue

to use the product in a different way.

622

And so I think sometimes, you know, we

have our ideas about how our technology

623

and products can be most useful, but

actually putting it in the hands of

624

users and letting them run with it.

625

Um, They surprise us.

626

And I love that.

627

Mike Gruen: That's awesome.

628

That's actually sort of what I was

going to ask about was like, um, I

629

know from my experience again, um,

the people I most likely talked to

630

was not the operator, but someone

who was responding to someone else.

631

Uh, so it always felt like I was working

with gloves on, like I never got, I

632

never got to talk to the end user.

633

Um, and it was always

a very difficult dance.

634

Um, And then when we finally, you know,

I got all the clearances and we got

635

all the things and we finally got to

talk to some of the analysts that were

636

using our product and seeing, and I was

like, Oh, wait, that's not what I meant.

637

And it's interesting to see that

that's, that's just the way it is

638

and it's something you have to be

639

Ben Youngs: prepared for.

640

That's

641

Tim Winkler: awesome.

642

Yeah, Ben, your, your background

was really fascinating to me.

643

Um, you know, with your experience at

In Q Tel, you know, and, and correct

644

me if I'm wrong here, but you know,

what you're looking across like the

645

portfolio and determining, you know,

which of these technologies from

646

these companies can best serve these

different agencies across defense,

647

national security and intelligence.

648

Um, and how Maybe explain to us how,

like, how valuable that experience

649

was when you're now working internal

for a product company and how you're

650

using that experience to benefit

how scale does business, you know,

651

within defense and national security.

652

Ben Youngs: Yeah, for sure.

653

Um, you know, so I, I focused on

enterprise software and largely, uh,

654

infrastructure type technologies.

655

So you can think of cloud and dev

tools and those sort of things.

656

Um.

657

But it was tremendously beneficial,

but first to get a broader kind

658

of understanding and access to a

variety of different customer groups.

659

So certainly it was pretty much all of

the intelligence agencies in the country.

660

Um, a wide variety of, of, um,

Department of Defense, um, organizations.

661

Uh, to include, um, additionally

federal law enforcement and, and, and

662

those sort of organizations as well.

663

So I had a, before working in detail,

a fairly small sliver of experience

664

with, with some of these groups, which

was great, but, but then to kind of

665

be able to see that across the board

and how one, the, the, the challenges

666

and, and kind of use cases from,

from one organization to another.

667

That was really, really interesting

just to see kind of, um, how broad in

668

a sense, uh, you know, the, the, the

types of work these groups are doing,

669

but then also at the same time, kind of

looking at it and then like realizing

670

that all of these organizations in

a lot of ways have the same problems

671

that any large commercial organization

would have with kind of the added.

672

Uh, challenges and restraints and,

uh, dealing with sensitive information

673

and, you know, not being able to be

connected to the Internet all the time.

674

All of that sort of stuff.

675

So understanding kind of the core

core challenges kind of across

676

the board, and that's just like,

when I think about it, it's, um.

677

You know, too much information, whether

it's the or I see really prolific creators

678

and and collectors of information,

but the challenge of being able to

679

process and make sense of all that

information, um, is just not really.

680

Kind of a human solvable thing

at this point with the volume and

681

velocity of data that's being created.

682

Um And so that, that's kind of the biggest

thing that I took away from my time there

683

and certainly applying that to scale.

684

How do we make the human, um, operator,

analyst, lawyer, um, uh, contracts person,

685

like, how do we help them do their job?

686

We kind of augment their job

in a, in a way that, that can.

687

Uh, less than that burden and have them

focus on kind of higher quality work and

688

not the, you know, I need to spend 90

percent of my time just evaluating data

689

or curating data or any of that stuff.

690

So I think that's been kind of

the thing that I continually go

691

back to and think about when I'm

talking to potential customers.

692

Like, what sort of capabilities can

can we provide a scale that just helps?

693

Helps anyone would have been these

communities do their jobs more

694

effectively to save them time to help

them, um, do higher quality work.

695

Um, all of those sort of things.

696

I think, um, you know, leveraged a lot of

those experiences from working at and then

697

apply them, you know, to the conversations

and the customers we have at scale.

698

Tim Winkler: Yeah.

699

And then to flip that to you,

Catherine, so your, your experience,

700

you know, just doing some research

and it's, it's pretty broad from

701

working with big contractors that are

on the services side, then working.

702

Almost in the customer's seat, right

at the Pentagon and then, uh, had

703

a couple of commercial stints there

that were still kind of catering

704

to, uh, the defense side of things.

705

Um, so some startup experience there

and then probable, um, how have those

706

kind of, and then a professor as well.

707

So how is that kind of a unique, uh,

diverse background applied to you

708

and how you're Most effective and

catering to your customers at scale.

709

Yeah.

710

Kathryn Harris: Um, I think very well.

711

So I really enjoy being

in business development.

712

I know a lot of people don't particularly

people that come out of government

713

and out of the military, they think,

you know, sales is uncomfortable.

714

Um, but I don't, I, that's

not been my experience at all.

715

I think because I have a lot of customer

empathy because I've been in those shoes.

716

And I think one of the unique

things about scale and many other.

717

Companies that work in the federal

sector is we really are mission driven.

718

Many of us come from having served

in some capacity, supporting

719

government and warfighters.

720

So, really understanding what

it's like to be in their shoes,

721

understanding the culture and the

bureaucracy and the communications

722

and the contracting constraints

and being able to work with them.

723

To be successful in the context

that they're working in has

724

been been super helpful.

725

Um, and, you know, my experience

teaching at Georgetown.

726

I taught a course called hacking

for defense, which is applying

727

the lean startup methodology

for national security program.

728

That's not.

729

Uh, you know, coding, hacking class in

that sort of sense, but how do you have

730

the bureaucracy by by, um, lean startup

methodologies and really it's based in.

731

Customer discovery, which is exactly what

we do in business development of getting

732

in and we've, you know, we've talked

about this examples of sitting with your

733

customer and sitting with your partner and

seeing how they're using the technology

734

or, you know, what are the workarounds

that they're trying to use today?

735

Because they don't have access

to the tools that they need.

736

Um, and so I think for me, having.

737

You know, engineering background, uh,

having worked at the Pentagon, knowing

738

the missions, knowing the language,

knowing the customers, and then applying

739

that lean startup methodology in a

business development role in a startup.

740

It's just been a really great, you know,

intersection of skills and experiences.

741

Um, and just really honestly,

very lucky and happy to be

742

where I am in the role that

743

Tim Winkler: I am in.

744

Yeah, the, the term hack the

bureaucracy is something that

745

we've been hearing quite a bit.

746

Um, you know, we've talked to, I had a

couple other folks on the pod, you know,

747

since we've been doing more of these

types of discussions, but everything

748

from folks that are consulting, just

helping, you know, uh, organizations.

749

That aren't in defense, but just, you

know, civic tech, uh, you know, with

750

even like, you know, recreating, you

know, the web web design for some of

751

these, these companies or these, these

agencies, you know, it's just a very

752

different style of thinking going back

to Yeah, they don't always think of it

753

as like a product or they have users.

754

Sometimes you hear project management

quite a bit, where a lot of times

755

it is product management, but

they don't really call it that.

756

Right.

757

So it's just kind of a

different style of thinking.

758

Um, hack the bureaucracy is, uh, Is

1 that certainly has been making its

759

way onto the, uh, onto the podcast.

760

So, um, yeah, I'll give

761

Kathryn Harris: you a specific example

from this week, actually meeting Ben

762

and I ran with the new customer, um,

potential customer, and they were

763

very excited about some of the data

labeling capabilities that we have.

764

And you could just tell

from the conversation.

765

They just they really wanted to lean in,

but there was something kind of holding

766

them back and I brought up contracting.

767

Like, how are we going to get this on?

768

Like, it's great that you want to

partner with us, but we have to put

769

a contract in place and we have some

contracts available to us that other

770

departments and agencies can use.

771

And as soon as I said that, he said,

oh, my gosh, you've just answered.

772

That was my biggest concern.

773

I just, our acquisition process is so

slow and it would take us a whole year.

774

And I didn't want to commit because I knew

it takes a long, but if you have an easy

775

button and a way that we can work with

some other customers that you're already

776

working with in our organization, and if

you can simplify that for me, then, then,

777

yes, let's keep having this conversation.

778

And so I think just being attuned to,

you know, it's not just the mission

779

or the technology, but in government.

780

In this big bureaucracy, there's I.

781

T.

782

There's security.

783

There's contracting.

784

There's where's the money coming from?

785

What kind of money is it?

786

When did the money come from?

787

All of these different things

that you have to account for.

788

And if you understand that system and

can be empathetic and help customers

789

navigate all of those little things to

get to yes, and to get to a deployment,

790

um, sometimes they just, they just need

someone to help them through that process.

791

Um, and you know, people like Ben and

I and others in the company, we've, you

792

know, been in those shoes and seen it

from different angles and can really just

793

guide our customers through that process.

794

Tim Winkler: Yeah, it's a

massive obstacle isn't it?

795

Just like the acquisition process.

796

So, um, sitting in their shoes,

uh, certainly gives them a sense of

797

relief of, of helping them handholding

them through it, you know, kind of

798

white glove, white glove experience.

799

Um, I, I am curious, uh,

I've got two, two questions.

800

One, you know, you all both

have, have joined within a year.

801

So what was it, you know, when

you all were interviewing, um,

802

that kind of sold it for you?

803

Uh, what, what was it that.

804

You know, made you believe and buy

into what scale AI is doing, what

805

convinced you that this, this company

is doing something very different.

806

Ben Youngs: I can, uh,

I can start with, yeah.

807

Um, as after, after nine months on

the job here, I think, you know, when.

808

Going back a year or so when I was

having conversations with various

809

people kind of looking at this role,

I think, um, You know, I thought I

810

had a pretty good concept of kind

of the landscape of of technology in

811

the federal space and what's getting

traction and what's not and what should

812

be getting traction all those things.

813

And, um, I felt like AI for quite

a while or machine learning and

814

AI, I think we're things that, um.

815

People talked about, but there wasn't

significant energy around that, right?

816

It was like, yeah, sure, we'll, we'll,

we'll do this, but, but not really

817

putting the effort in on the federal side.

818

And so I think what was exciting to me

just from kind of a technical perspective

819

was like, the time seems right.

820

Broadly, but also in the federal space

where people are actually thinking about

821

this and they've kind of gotten to that

moment where it's like, oh, this is real

822

and there are ways that we can apply this.

823

And if we don't do it, we're going

to fall behind, whether that's

824

our adversaries or fall further

behind than the commercial world.

825

So it felt like the right time

and the right technology for me.

826

And when I looked at it from a scale

perspective, it was, of course, you

827

know, having a really good feeling.

828

Um, from the people I talked to

at the company, but, um, the, the

829

energy around the company and the

mindset around kind of how we were.

830

Going to help companies kind of wherever

they were in their, their AI and ML

831

journey, but like that, our whole kind

of, um, point of existence was we're

832

going to help help companies build out

their, their, um, capabilities and that's

833

whether it's data labeling, whether it's,

um, doing, uh, model development, testing

834

and evaluation, whether it's kind of a

new generative AI stuff, like Gail was.

835

Taking this more infrastructure

approach to AI and ML and we're not

836

necessarily going to build all the

tools or all the model, but we're

837

going to help you get to get to, um,

you know, build out your practice.

838

I thought that was that

was really interesting.

839

Um, maybe the final thing I just

talk about would just be like the.

840

The emphasis on, on being mission

focused and really putting a focus

841

on federal work and supporting

the country and national security.

842

I mean, if you've ever heard, um, our

CEO, Alex talk, he's extremely patriotic

843

and wants to support and wants the U.

844

S.

845

To, to, to compete and win and AI

and that, uh, kind of coming from

846

that national security background.

847

That was really exciting for me to hear.

848

And, and, and frankly, like,

I don't know that that.

849

Yeah.

850

Um, same sort of mindset exists

in a lot of, in a lot of startups,

851

uh, with some notable examples.

852

So I thought those kind of those

couple examples were things that really

853

drew me into scale and ultimately,

um, convinced me to come over.

854

Cool.

855

Kathryn Harris: Yeah, very

similar themes for me.

856

I think from a technology perspective,

scale is a leader in a lot of ways.

857

And that was just really appealing

to be kind of on the cutting edge

858

of, um, you know, technologies,

um, and be part of that journey.

859

Similarly.

860

The commitment to national security

and defense was very appealing to me.

861

Um, 2 companies.

862

I was at before 1 was a pure play defense.

863

Another was dual use commercial defense.

864

Um, and it was just very important to me

being at a dual use company that they,

865

they were 100 percent behind defense and

understood that the sales cycle is longer.

866

It's a, it's a different business model,

but, um, committed to it, not just

867

because it makes business sense, but

for, you know, patriotic reasons as well.

868

Um, and then, you know, for me,

the, the size and the culture of

869

the company was very appealing.

870

And that's just a personal decision.

871

Uh, I enjoy being at

smaller ish companies.

872

I interviewed at a lot of other larger,

more established, uh, publicly traded

873

companies that had gone from venture

back and had some kind of exit.

874

Uh, and we're now public and

it's just a different culture.

875

And I like being in that small.

876

Kind of, you know, gritty, creative,

you know, it's a little bit of a

877

grind, but you're all in it together

and just really, really working hard.

878

Those those kinds of groups.

879

Um, and and that's kind of the

culture that we have right now.

880

And I really enjoy it.

881

Mike Gruen: I think one of the things that

really helps with that sort of culture

882

that is, um, when it is mission driven

and there is this, everybody understands

883

why we're doing what we're doing.

884

And I think that also helps in

bringing the group together.

885

So that's awesome that you

guys have that culture and

886

Tim Winkler: it's, we hear this term a

lot of like, you know, operating like

887

a startup, but you've got the stability

and backing of a large organization

888

and some resources at your disposal

to really implement and be innovative.

889

I think.

890

Thank you.

891

That is nice because the flip side

of being, you know, in that small,

892

scrappy startup, you know, if you look

at what's happening in today's market,

893

right, one of the reasons that we put

we're pushing more of this content

894

is because there's a huge level of

instability and early stage commercial

895

startups that are looking for ways to,

you know, technologists are looking and

896

interested in defense tech, because there

is a level of You know, spend that's

897

going to get applied to this market.

898

That's necessity.

899

Um, so, you know, being able to, you know,

what, I guess, what's the size of scale?

900

Do you have like a ballpark, um, head

count, uh, where, where the company sits.

901

Kathryn Harris: I think our federal

sector is about 100 people right now.

902

Okay.

903

On the commercial side, I'm not sure.

904

Ben Youngs: Yeah, 600 plus.

905

Um, so, uh, definitely a

later stage startup, both

906

from funding and overall size.

907

Um, yeah, I mean, so this is the

first startup I've worked for.

908

Uh, Catherine definitely has more

startup experience, but I've worked

909

around a lot of startups over the last

several years and have seen, um, you

910

know, a lot of companies go under.

911

I've seen a lot of companies really Really

try to push to get into the federal space.

912

It's really, really hard for a

variety of different reasons.

913

And so I've, I've seen a variety of

companies that have, um, you know,

914

attempted to make that make that

push into the federal space and

915

maybe do that for a year or two.

916

And, um.

917

Have some success or, or some teams

that have, um, you know, ultimately

918

made the decision to, to, uh, de

emphasize or, or altogether kind

919

of leave the federal space, um,

just because it is that difficult.

920

And it's, it's really important that,

that we have startup companies and

921

innovative technology that want to work

in this space and can work in the space.

922

Um, but I think, uh, oftentimes

companies, um, don't appreciate how

923

difficult it can be to, to work in

the, in the fed space or, or don't have

924

the patience to work in the fed space

or whatever the scenario may be, but

925

it's, um, it's, it's really critical.

926

And I'm glad to see, you know, this

more recent push of, of defense tech

927

and national street back and fed

tech, all of those sorts of things.

928

Really important.

929

Um, and, but I think there's

still a long way to go in, in

930

making it easier for companies

to, to engage with the government.

931

For sure.

932

It's

933

Tim Winkler: interesting to

see the different applications

934

from, you know, what's stemmed

up from the, the war in Ukraine.

935

Uh, we're seeing a ton of emphasis and.

936

Uh, like drones or very low

earth orbiting satellites.

937

Um, that, that has been a space that has

really taken off, uh, just also with the

938

most recent advancements and space travel,

like reusable rockets and whatnot, uh,

939

it's interesting to see how those, uh,

technologies are really changing so fast.

940

Um, we've had some really interesting

companies and guests come on that

941

are, you know, really scrappy

small companies, but, you know,

942

they're doing really big deals with.

943

Large organizations, uh, in the

government, because there's a need for it.

944

And I like the other piece of that

is like, there's a want, they know

945

they need it and they want it.

946

So how do you break down that barrier?

947

Um, and so our, our hope is to,

if anything, from making this

948

content is to, to help educate and,

and, you know, give folks some.

949

Motivation to know that it can be done

just takes takes a little time and

950

a strategic process to put in place.

951

But, um, I think that's all for

the for the main discussion.

952

I've got more questions, but I want to

be mindful of the time and, uh, you know,

953

jump into into this last segment here.

954

So I'll transition us, um,

into into our final segment.

955

So 5 second scramble.

956

I'll ask each of you a series

of questions, uh, try to give me

957

a response within five seconds.

958

We're not going to air horn

you off if you go over, um,

959

and, uh, some will be business.

960

I'll be personal.

961

Um, I'll go ahead and start with, um,

with Ben, uh, Benny, are you ready?

962

Yes.

963

Let's do it.

964

All right, let's do it.

965

Um, explain scale AI to me

as if I were a five year old.

966

Ben Youngs: We, we build infrastructure

for teams to be successful in,

967

in AI and machine learning.

968

Tim Winkler: How would

you describe your culture?

969

Ben Youngs: Uh, go get her culture, do

what needs to be done to get the job done.

970

Tim Winkler: What kind of technologist

would you say thrives at scale?

971

AI?

972

Ben Youngs: Oh, uh, someone that's

adaptable that, that has that kind of,

973

uh, intellectual curiosity that likes to

learn about a variety of different things.

974

Tim Winkler: What can folks be most

975

Oh, uh,

976

Ben Youngs: man, I, I have to mention

generative AI and our large language

977

model work that we're, we're doing.

978

And just the amount of energy and

excitement that's around that.

979

I think the things we're doing

specifically for our customers,

980

national security is a huge

step forward, uh, for them.

981

So really excited there.

982

Tim Winkler: Nice.

983

If you could have any superpower,

what would it be and why?

984

Ben Youngs: uh, gosh.

985

Um, yeah, I think, uh, I'm at the limits

of how much information my brain can,

986

uh, can hold in at this, at my advanced

stage now, I'd love to have a, a, a

987

more, uh, significant memory capacity.

988

Mm,

989

Tim Winkler: that's that's a great answer.

990

. Um, if you had to pick one fast

food joint, To be established as the

991

first fast food restaurant on Mars.

992

What, which one would you go with?

993

Ben Youngs: Oh, I don't know.

994

This might be against their kind

of geographic and regional rules,

995

but I'll go in and out burger.

996

Tim Winkler: Yeah, that's true.

997

It's a gotta, gotta double check

and see if they're going beyond, uh,

998

some of their West coast locations.

999

Ben Youngs: That's right.

00:51:49,224 --> 00:51:50,255

It's time to do it though.

00:51:51,675 --> 00:51:54,435

Tim Winkler: Um, what's

something that you'd like to

00:51:54,444 --> 00:51:56,705

do, but you're not very good at.

00:51:59,210 --> 00:52:02,450

Ben Youngs: Um, I mean, uh, I'd

love to be a better developer.

00:52:02,450 --> 00:52:06,910

I, I am by no means a developer and I

wish I had that, that kind of brain, uh,

00:52:07,200 --> 00:52:09,490

uh, uh, chemistry to be able to do that.

00:52:09,490 --> 00:52:12,949

So I have to put in a lot of work

to be, uh, minimally kind of, uh,

00:52:12,970 --> 00:52:14,869

capable and, and, uh, development.

00:52:15,500 --> 00:52:15,850

Nice.

00:52:17,110 --> 00:52:20,400

Tim Winkler: What is a charity

or corporate philanthropy

00:52:20,400 --> 00:52:21,760

that's near and dear to you?

00:52:23,150 --> 00:52:25,500

Ben Youngs: Um, animal related.

00:52:25,510 --> 00:52:32,365

So, uh, certainly I support my local,

uh, um, Arlington Humane Society

00:52:32,365 --> 00:52:36,005

and the great work they do and and

certainly uh national causes related

00:52:36,035 --> 00:52:39,935

to that as well amongst other things

but definitely animals uh are nearing

00:52:39,935 --> 00:52:40,245

Tim Winkler: deer.

00:52:40,695 --> 00:52:44,455

She adopted a dog from the Animal

Welfare League of Arlington.

00:52:44,835 --> 00:52:45,884

That's great.

00:52:45,894 --> 00:52:46,164

Yeah.

00:52:46,165 --> 00:52:46,475

Yeah.

00:52:46,595 --> 00:52:47,145

Fantastic.

00:52:47,700 --> 00:52:51,170

Um, what's something that

you're very afraid of and why,

00:52:53,400 --> 00:52:56,530

Ben Youngs: uh, I'm not going to,

not going to use like, uh, you

00:52:56,530 --> 00:52:58,320

know, AI, uh, takeover or anything.

00:53:02,830 --> 00:53:07,450

For someone else, I mean, I'm going

to go with, uh, with just being a new

00:53:07,470 --> 00:53:09,050

parent and that sort of mode you're in.

00:53:09,050 --> 00:53:11,990

I'm always just being nervous

about anything your child is

00:53:11,990 --> 00:53:14,260

doing and their well being.

00:53:14,260 --> 00:53:14,960

So I'll go with that.

00:53:14,970 --> 00:53:18,020

Just kind of generally

speaking, I just want to jump in

00:53:18,020 --> 00:53:18,260

Mike Gruen: there.

00:53:18,310 --> 00:53:20,500

Kudos for starting a

new job with a newborn.

00:53:20,510 --> 00:53:23,480

That was so did you do a trifecta

by a house at the same time?

00:53:24,840 --> 00:53:28,570

Ben Youngs: Luckily, but I will

say the timing was, uh, was

00:53:28,600 --> 00:53:30,190

really interesting for sure.

00:53:30,190 --> 00:53:32,044

And it was, uh, it was, uh, Okay.

00:53:32,245 --> 00:53:36,185

A life experience that, uh, was,

was challenging, but rewarding

00:53:36,185 --> 00:53:37,345

all at the same time too.

00:53:38,275 --> 00:53:39,015

Unintended.

00:53:39,125 --> 00:53:39,365

Yeah.

00:53:39,945 --> 00:53:42,095

Tim Winkler: So it's a good cultural

plug though, for scale, right?

00:53:42,105 --> 00:53:47,124

It's like, Hey, like, you know, taking new

parents on and trusting that they'll do.

00:53:47,235 --> 00:53:47,714

Ben Youngs: Absolutely.

00:53:47,714 --> 00:53:51,245

I'll, I'll put my recruiting hat on

and say, you know, they were fantastic

00:53:51,245 --> 00:53:55,315

and gave me the time I needed to, to

be a new parent and to do that, the

00:53:55,335 --> 00:53:59,425

paternity thing and come back somewhat

refreshed and get back to work.

00:53:59,845 --> 00:54:00,464

Tim Winkler: That's great.

00:54:01,800 --> 00:54:02,960

Um, all right, last question.

00:54:02,990 --> 00:54:08,380

So what is, or I'm sorry, who would you

say is the greatest superhero of all time?

00:54:09,870 --> 00:54:15,109

Ben Youngs: You know, I'm not a huge, uh,

superhero guy, but I will say of all the

00:54:15,110 --> 00:54:20,290

superhero, uh, uh, superheroes that I'm

aware of, I've always been a Batman guy.

00:54:20,400 --> 00:54:22,250

Um, so I'll, I'll go with that.

00:54:23,050 --> 00:54:23,490

Number one

00:54:23,490 --> 00:54:23,930

Tim Winkler: answer.

00:54:24,280 --> 00:54:24,910

It's the right choice.

00:54:24,910 --> 00:54:25,760

It's the right choice.

00:54:26,720 --> 00:54:26,940

Awesome.

00:54:29,350 --> 00:54:29,600

Ben Youngs: Good.

00:54:29,680 --> 00:54:29,990

Tim Winkler: Good.

00:54:29,990 --> 00:54:31,500

Uh, good answers, Ben.

00:54:31,580 --> 00:54:32,870

Um, all right.

00:54:32,870 --> 00:54:34,100

Catherine, are you ready?

00:54:35,300 --> 00:54:36,290

As ready as I'll ever be.

00:54:36,660 --> 00:54:37,909

Okay, let's do it.

00:54:37,920 --> 00:54:41,519

So what is your favorite

part of the culture at scale?

00:54:42,930 --> 00:54:44,750

Kathryn Harris: Uh,

it's very collaborative.

00:54:44,950 --> 00:54:48,180

Um, I think we talked about that between

engineering, business development,

00:54:48,190 --> 00:54:51,340

marketing, delivery teams, IT security.

00:54:51,490 --> 00:54:53,360

It, it really feels like

we're all in it together.

00:54:54,645 --> 00:54:57,715

Tim Winkler: When you went through

the interview process with scale,

00:54:57,715 --> 00:55:01,265

what's something about that

process that you felt was unique?

00:55:02,485 --> 00:55:04,285

Kathryn Harris: I felt

that's a great question.

00:55:04,325 --> 00:55:06,475

I had a wonderful experience.

00:55:06,494 --> 00:55:12,505

Uh, the recruiter that I was working with,

I felt like, um, told it to me straight.

00:55:12,575 --> 00:55:15,274

I mean, everything was,

uh, very transparent.

00:55:15,854 --> 00:55:17,455

There was no bait and switch.

00:55:17,475 --> 00:55:21,775

Once I got inside the company and started,

it was exactly as I expected it to be.

00:55:22,005 --> 00:55:24,045

It was a very, uh, transparent process.

00:55:25,915 --> 00:55:31,135

Tim Winkler: Aside from defense,

what commercial use cases and

00:55:31,135 --> 00:55:34,034

AI are you most excited for?

00:55:35,515 --> 00:55:39,285

Kathryn Harris: Uh, I think I don't

know a lot about it, but healthcare

00:55:39,285 --> 00:55:43,364

and biology and medicine, I feel

like it could be extraordinarily, you

00:55:43,364 --> 00:55:45,635

know, transformational applications.

00:55:47,905 --> 00:55:49,815

Tim Winkler: Who is

your biggest role model?

00:55:51,300 --> 00:55:52,710

Kathryn Harris: Ooh,

that's a good question.

00:55:52,740 --> 00:55:53,890

I have, I have a lot.

00:55:53,890 --> 00:55:58,350

I have, I'm at a point in my life now

where I have a lot of dear friends

00:55:58,570 --> 00:56:00,239

who are just doing amazing things.

00:56:00,270 --> 00:56:04,860

Women that are in different

roles, a lot in stem medicine,

00:56:04,890 --> 00:56:07,380

business owners, um, that are just.

00:56:08,120 --> 00:56:11,430

Just really crushing it on the market,

but also in their family lives and their

00:56:11,430 --> 00:56:13,340

personal lives and really well balanced.

00:56:13,370 --> 00:56:17,510

Um, and so not any 1 person,

but sort of a family of.

00:56:17,850 --> 00:56:20,090

Of friends and role models

across different industries.

00:56:20,785 --> 00:56:21,025

Tim Winkler: Cool.

00:56:21,185 --> 00:56:21,565

Nice.

00:56:22,085 --> 00:56:26,715

What is a charity or corporate

philanthropy that's near and dear to you?

00:56:27,705 --> 00:56:32,435

Kathryn Harris: I focus a lot on

engineering education, uh, uh, and

00:56:32,445 --> 00:56:35,775

particularly women in engineering and

STEM and trying to grow those fields

00:56:35,775 --> 00:56:38,714

and disciplines and just help others

kind of come up through the ranks.

00:56:39,575 --> 00:56:39,915

Awesome.

00:56:40,915 --> 00:56:44,755

Tim Winkler: Uh, layup, uh, here

from the, uh, initial pairing.

00:56:44,755 --> 00:56:46,015

What is your favorite cereal?

00:56:47,425 --> 00:56:47,785

Ben Youngs: Ooh,

00:56:47,875 --> 00:56:48,775

Kathryn Harris: uh, yeah.

00:56:49,015 --> 00:56:50,005

I'm not a cereal person.

00:56:50,865 --> 00:56:51,165

Good for

00:56:51,170 --> 00:56:51,315

Ben Youngs: you.

00:56:51,315 --> 00:56:52,185

Yeah, I

00:56:52,190 --> 00:56:56,295

Kathryn Harris: don't, avocado toast

and scrambled eggs or breakfast person?

00:56:57,225 --> 00:56:59,085

.

Tim Winkler: So you just breeze right through that aisle?

00:56:59,085 --> 00:57:01,845

You're not, yeah, it's, there's

nom not distraction off.

00:57:02,225 --> 00:57:02,445

No

00:57:02,835 --> 00:57:03,125

Okay.

00:57:04,065 --> 00:57:08,145

Um, what's something that you're

good at but you hate doing?

00:57:09,750 --> 00:57:10,930

Oh, um,

00:57:13,790 --> 00:57:19,190

Kathryn Harris: it's tough on house

chores, like cooking and cleaning.

00:57:19,190 --> 00:57:23,010

I have a dishwasher to empty

that I need to get after.

00:57:23,370 --> 00:57:23,750

Tim Winkler: Yes.

00:57:24,110 --> 00:57:24,280

Yeah.

00:57:24,280 --> 00:57:24,949

I don't blame you.

00:57:25,240 --> 00:57:26,010

I outsource that.

00:57:26,660 --> 00:57:30,720

If you could live in a fictional

world from a book or a movie,

00:57:30,720 --> 00:57:32,080

which one would you choose?

00:57:37,179 --> 00:57:37,989

Ben Youngs: Uh, I'll say this

00:57:37,989 --> 00:57:40,440

Kathryn Harris: cause I just saw

a clip on, on how this movie was

00:57:40,440 --> 00:57:43,920

made recently, but avatar, um,

it's just such a beautiful scenery.

00:57:44,800 --> 00:57:46,870

It feels like it'd be

a lovely place to be.

00:57:47,285 --> 00:57:48,435

Tim Winkler: You saw the new one.

00:57:49,215 --> 00:57:51,465

Kathryn Harris: No, it was an old

one, but it was a video of how the

00:57:51,465 --> 00:57:54,905

actors made it and all the gear that

they had to put on and how the book

00:57:54,905 --> 00:57:56,514

was about how great their acting was.

00:57:56,574 --> 00:58:01,855

But when you actually had raw footage of

them acting without all the CGI, just how

00:58:01,905 --> 00:58:05,845

cold of an environment it actually was

and how much imagination they had to bring

00:58:05,845 --> 00:58:07,815

to the roles to bring out the emotion.

00:58:08,440 --> 00:58:11,780

Which is pretty neat to see, which

is probably true of like most CGI,

00:58:11,830 --> 00:58:13,690

like probably all CGI movies today.

00:58:14,150 --> 00:58:15,770

Tim Winkler: Yeah, they

make it so immersive.

00:58:15,770 --> 00:58:18,060

It's like you feel like you're

a part of that environment.

00:58:18,170 --> 00:58:19,010

It's really, really neat.

00:58:19,850 --> 00:58:23,629

Um, what is the worst fashion

trend that you've ever followed?

00:58:26,219 --> 00:58:27,010

Kathryn Harris: Oh, so many.

00:58:29,770 --> 00:58:33,300

So, you know, they say like the early

00:58:33,560 --> 00:58:35,430

the low rise jeans and all of that.

00:58:38,575 --> 00:58:40,845

I would say probably,

probably that fashion trend.

00:58:42,845 --> 00:58:45,045

Tim Winkler: Everybody's got a

good answer for that question.

00:58:45,045 --> 00:58:45,891

Although I will say,

00:58:45,891 --> 00:58:47,445

Mike Gruen: I think you're

the first one that said, Oh,

00:58:47,445 --> 00:58:48,575

there's so many as opposed to

00:58:52,885 --> 00:58:55,685

Tim Winkler: Um, what was

your dream job as a kid?

00:58:56,365 --> 00:58:56,705

Oh, I

00:58:56,705 --> 00:58:57,805

Kathryn Harris: wanted to be an astronaut.

00:58:58,045 --> 00:58:59,555

Hands down very early on.

00:58:59,575 --> 00:59:00,875

That was, that was the dream.

00:59:01,430 --> 00:59:01,710

Tim Winkler: Nice.

00:59:02,720 --> 00:59:03,499

That's a great answer.

00:59:03,500 --> 00:59:06,650

And then last one, uh,

favorite Disney character.

00:59:08,080 --> 00:59:09,170

Kathryn Harris: Ooh,

that's a good question.

00:59:11,310 --> 00:59:13,000

I don't really watch a

lot of Disney movies.

00:59:13,230 --> 00:59:16,860

I just recently watched, um, this is

an older one, but I think it might

00:59:16,860 --> 00:59:21,390

be a Pixar movie inside out about a

girl and all of her emotions and how

00:59:21,390 --> 00:59:22,800

they take on different characters.

00:59:22,810 --> 00:59:27,700

And I just thought it was The way many

Disney and Pixar movies are both great

00:59:27,700 --> 00:59:31,160

for kids, but when you watch it as an

adult, it sort of hits differently.

00:59:31,440 --> 00:59:32,980

Uh, and I was just really

impressed with that.

00:59:33,450 --> 00:59:33,750

Tim Winkler: Cool.

00:59:34,620 --> 00:59:35,040

Awesome.

00:59:35,230 --> 00:59:36,330

Uh, well, that's a wrap.

00:59:36,340 --> 00:59:38,170

Those were great answers

from both of y'all.

00:59:38,280 --> 00:59:41,460

Um, hopefully it wasn't

too, uh, intimidating.

00:59:41,530 --> 00:59:45,350

Um, I wanted to thank you both

again for, for being great

00:59:45,350 --> 00:59:47,420

guests and, uh, you know, I know.

00:59:47,655 --> 00:59:50,375

We're excited to continue tracking

the innovative work that you,

00:59:50,385 --> 00:59:53,945

you guys are doing at scale

and be doing for years to come.

00:59:53,945 --> 00:59:55,745

So appreciate y'all spending

time with us on the pod.

00:59:56,855 --> 00:59:57,135

Awesome.

00:59:57,135 --> 00:59:57,205

Thanks for

00:59:57,205 --> 00:59:57,485

Mike Gruen: having

00:59:57,485 --> 00:59:57,595

Ben Youngs: us.

00:59:57,605 --> 00:59:57,795

Thanks.

00:59:57,995 --> 00:59:58,145

Yeah.

00:59:58,145 --> 00:59:59,075

Thanks Thanks so much.

00:59:59,105 --> 00:59:59,705

A lot of fun.

00:59:59,855 --> 01:00:00,375

Appreciate it.