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

Oct 17, 2023

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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Transcript
Tim Winkler:

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.

368

:

Um, 1 of the things that I love about

business development in general, and

369

:

working with solutions engineering

teams is it's actually not selling.

370

:

And a key thing Ben said is

about learning and listening to

371

:

customers and really unpacking them.

372

:

And I think, you know, for us working

in the federal sector, the technologies

373

:

and solutions we're selling.

374

:

They're not commodity solutions, um,

and being sort of early technology and

375

:

working with a lot of early adapters

requires a lot of not fully customized

376

:

solutions, but a lot of hands on and, you

know, a lot of missions and organizations

377

:

across the federal government.

378

:

Um, their missions are so diverse

that their needs are really unique.

379

:

And so being able to sit down and

spend time with them and unpack their

380

:

mission and learn and listen and not

just understand what are the technical

381

:

requirements, but what's the, the

overall mission that they're trying

382

:

to achieve and then also understanding

it and the business context of how.

383

:

D.

384

:

O.

385

:

D.

386

:

acquires and implements and sustains

technology can be very different

387

:

across different customers.

388

:

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

you know, at the beginning of a journey

389

:

with a new customer, it's it is a

full range of all of those topics that

390

:

we really unpack, which I think, you

know, makes it interesting, exciting.

391

:

And each deal is different each day.

392

:

And each customer is different

393

:

Ben Youngs: in some ways.

394

:

Mike Gruen: I think one of the other

things I'm curious if you guys when

395

:

you're engaging one of the things

so I was in that role for a little

396

:

while, uh, on the customer facing

government side selling into Intel.

397

:

Um.

398

:

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

myself, I was lucky in that I was

399

:

both the pre sales and the post sales.

400

:

So I, my vision, what I was working with

them on, I was then getting to deliver on.

401

:

So I knew how it was all

going to come together.

402

:

And I think 1 of that's 1 of the

big challenges is when you have 2

403

:

separate units and you have somebody

who's out there, um, coming up with

404

:

that solution and then communicating

that back to the engineers.

405

:

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

406

:

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

how you sort of handle that.

407

:

Um, cause it can create good tension

and it can create bad tension

408

:

Ben Youngs: for sure.

409

:

Yeah, I can take that one.

410

:

So yeah, we're aligned, you know,

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

411

:

is, is largely pre sales focused.

412

:

Um, we have field engineers, um.

413

:

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

kind of, uh, technical work, of course,

414

:

in collaboration with our engineering

team, software engineers, machine

415

:

learning engineers, that sort of thing.

416

:

Um, and, and quite honestly, there,

there can be some friction there, right?

417

:

So there's, uh, sometimes the, the

tendency, uh, in some spaces that, uh.

418

:

Kind of design this whole thing and then

throw it over the fence and say, all

419

:

right, we've got a contract in place.

420

:

Now you need to execute on it.

421

:

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

developers and ops folks, right?

422

:

Like, we've built the software,

now you need to, to maintain it.

423

:

Um, I, I think how we address that is

certainly just, you know, really having

424

:

good communications skills and having

good relationships with those other teams.

425

:

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

about for scale heading into:

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.

::

It's time to do it though.

::

Tim Winkler: Um, what's

something that you'd like to

::

do, but you're not very good at.

::

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

love to be a better developer.

::

I, I am by no means a developer and I

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

::

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

::

So I have to put in a lot of work

to be, uh, minimally kind of, uh,

::

capable and, and, uh, development.

::

Nice.

::

Tim Winkler: What is a charity

or corporate philanthropy

::

that's near and dear to you?

::

Ben Youngs: Um, animal related.

::

So, uh, certainly I support my local,

uh, um, Arlington Humane Society

::

and the great work they do and and

certainly uh national causes related

::

to that as well amongst other things

but definitely animals uh are nearing

::

Tim Winkler: deer.

::

She adopted a dog from the Animal

Welfare League of Arlington.

::

That's great.

::

Yeah.

::

Yeah.

::

Fantastic.

::

Um, what's something that

you're very afraid of and why,

::

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

not going to use like, uh, you

::

know, AI, uh, takeover or anything.

::

For someone else, I mean, I'm going

to go with, uh, with just being a new

::

parent and that sort of mode you're in.

::

I'm always just being nervous

about anything your child is

::

doing and their well being.

::

So I'll go with that.

::

Just kind of generally

speaking, I just want to jump in

::

Mike Gruen: there.

::

Kudos for starting a

new job with a newborn.

::

That was so did you do a trifecta

by a house at the same time?

::

Ben Youngs: Luckily, but I will

say the timing was, uh, was

::

really interesting for sure.

::

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

::

A life experience that, uh, was,

was challenging, but rewarding

::

all at the same time too.

::

Unintended.

::

Yeah.

::

Tim Winkler: So it's a good cultural

plug though, for scale, right?

::

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

parents on and trusting that they'll do.

::

Ben Youngs: Absolutely.

::

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

and say, you know, they were fantastic

::

and gave me the time I needed to, to

be a new parent and to do that, the

::

paternity thing and come back somewhat

refreshed and get back to work.

::

Tim Winkler: That's great.

::

Um, all right, last question.

::

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

say is the greatest superhero of all time?

::

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

superhero guy, but I will say of all the

::

superhero, uh, uh, superheroes that I'm

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

::

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

::

Number one

::

Tim Winkler: answer.

::

It's the right choice.

::

It's the right choice.

::

Awesome.

::

Ben Youngs: Good.

::

Tim Winkler: Good.

::

Uh, good answers, Ben.

::

Um, all right.

::

Catherine, are you ready?

::

As ready as I'll ever be.

::

Okay, let's do it.

::

So what is your favorite

part of the culture at scale?

::

Kathryn Harris: Uh,

it's very collaborative.

::

Um, I think we talked about that between

engineering, business development,

::

marketing, delivery teams, IT security.

::

It, it really feels like

we're all in it together.

::

Tim Winkler: When you went through

the interview process with scale,

::

what's something about that

process that you felt was unique?

::

Kathryn Harris: I felt

that's a great question.

::

I had a wonderful experience.

::

Uh, the recruiter that I was working with,

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

::

I mean, everything was,

uh, very transparent.

::

There was no bait and switch.

::

Once I got inside the company and started,

it was exactly as I expected it to be.

::

It was a very, uh, transparent process.

::

Tim Winkler: Aside from defense,

what commercial use cases and

::

AI are you most excited for?

::

Kathryn Harris: Uh, I think I don't

know a lot about it, but healthcare

::

and biology and medicine, I feel

like it could be extraordinarily, you

::

know, transformational applications.

::

Tim Winkler: Who is

your biggest role model?

::

Kathryn Harris: Ooh,

that's a good question.

::

I have, I have a lot.

::

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

where I have a lot of dear friends

::

who are just doing amazing things.

::

Women that are in different

roles, a lot in stem medicine,

::

business owners, um, that are just.

::

Just really crushing it on the market,

but also in their family lives and their

::

personal lives and really well balanced.

::

Um, and so not any 1 person,

but sort of a family of.

::

Of friends and role models

across different industries.

::

Tim Winkler: Cool.

::

Nice.

::

What is a charity or corporate

philanthropy that's near and dear to you?

::

Kathryn Harris: I focus a lot on

engineering education, uh, uh, and

::

particularly women in engineering and

STEM and trying to grow those fields

::

and disciplines and just help others

kind of come up through the ranks.

::

Awesome.

::

Tim Winkler: Uh, layup, uh, here

from the, uh, initial pairing.

::

What is your favorite cereal?

::

Ben Youngs: Ooh,

::

Kathryn Harris: uh, yeah.

::

I'm not a cereal person.

::

Good for

::

Ben Youngs: you.

::

Yeah, I

::

Kathryn Harris: don't, avocado toast

and scrambled eggs or breakfast person?

::

.

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

::

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

nom not distraction off.

::

No

::

Okay.

::

Um, what's something that you're

good at but you hate doing?

::

Oh, um,

::

Kathryn Harris: it's tough on house

chores, like cooking and cleaning.

::

I have a dishwasher to empty

that I need to get after.

::

Tim Winkler: Yes.

::

Yeah.

::

I don't blame you.

::

I outsource that.

::

If you could live in a fictional

world from a book or a movie,

::

which one would you choose?

::

Ben Youngs: Uh, I'll say this

::

Kathryn Harris: cause I just saw

a clip on, on how this movie was

::

made recently, but avatar, um,

it's just such a beautiful scenery.

::

It feels like it'd be

a lovely place to be.

::

Tim Winkler: You saw the new one.

::

Kathryn Harris: No, it was an old

one, but it was a video of how the

::

actors made it and all the gear that

they had to put on and how the book

::

was about how great their acting was.

::

But when you actually had raw footage of

them acting without all the CGI, just how

::

cold of an environment it actually was

and how much imagination they had to bring

::

to the roles to bring out the emotion.

::

Which is pretty neat to see, which

is probably true of like most CGI,

::

like probably all CGI movies today.

::

Tim Winkler: Yeah, they

make it so immersive.

::

It's like you feel like you're

a part of that environment.

::

It's really, really neat.

::

Um, what is the worst fashion

trend that you've ever followed?

::

Kathryn Harris: Oh, so many.

::

So, you know, they say like the early

:

::

the low rise jeans and all of that.

::

I would say probably,

probably that fashion trend.

::

Tim Winkler: Everybody's got a

good answer for that question.

::

Although I will say,

::

Mike Gruen: I think you're

the first one that said, Oh,

::

there's so many as opposed to

::

Tim Winkler: Um, what was

your dream job as a kid?

::

Oh, I

::

Kathryn Harris: wanted to be an astronaut.

::

Hands down very early on.

::

That was, that was the dream.

::

Tim Winkler: Nice.

::

That's a great answer.

::

And then last one, uh,

favorite Disney character.

::

Kathryn Harris: Ooh,

that's a good question.

::

I don't really watch a

lot of Disney movies.

::

I just recently watched, um, this is

an older one, but I think it might

::

be a Pixar movie inside out about a

girl and all of her emotions and how

::

they take on different characters.

::

And I just thought it was The way many

Disney and Pixar movies are both great

::

for kids, but when you watch it as an

adult, it sort of hits differently.

::

Uh, and I was just really

impressed with that.

::

Tim Winkler: Cool.

::

Awesome.

::

Uh, well, that's a wrap.

::

Those were great answers

from both of y'all.

::

Um, hopefully it wasn't

too, uh, intimidating.

::

Um, I wanted to thank you both

again for, for being great

::

guests and, uh, you know, I know.

::

We're excited to continue tracking

the innovative work that you,

::

you guys are doing at scale

and be doing for years to come.

::

So appreciate y'all spending

time with us on the pod.

::

Awesome.

::

Thanks for

::

Mike Gruen: having

::

Ben Youngs: us.

::

Thanks.

::

Yeah.

::

Thanks Thanks so much.

::

A lot of fun.

::

Appreciate it.

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