Latest / AI for Founders with Ryan Estes / Jazz Fusion in the Agentic Era

Transcript

Jazz Fusion in the Agentic Era · AI for Founders with Ryan Estes

0:00
Your AI agents are leaking your data right now and you have no
0:03
idea. In 12 months, regulators won't
0:05
care if it was a human, an agent, or your dog that caused
0:08
the breach. They're still going to find you
0:09
into oblivion. Every Claude subscription you
0:11
handed out, every cursor seat, every.
0:14
Let's just try this MCP server real quick.
0:16
All of it is a paper trail you can't see.
0:18
The company that figures this out owns the next decade of
0:21
enterprise software. So you're a founder building in
0:24
healthcare, legal, or fin services.
0:26
You don't need to invent the security stack, but you do need
0:29
infrastructure to ship your wedge 10 times faster.
0:32
So if your agents are working while you sleep, who exactly is
0:35
accountable when they make a decision you didn't approve?
0:38
Welcome to AI for founders. I'm Ryan Estes.
0:40
Today we're sitting down with the chief strategy officer of a
0:42
private equity backed Unicorn protecting data for the most
0:46
regulated companies on earth. You'll learn how a marketing
0:49
operator turn himself into a builder in 12 months, why the
0:52
gap between intent and data just collapsed, and how to position
0:55
your startup so the next compliant wave lifts you instead
0:58
of drowning you. This is for founder shipping and
1:00
regulated industries, AI agent builders and operators who
1:04
refuse to get caught flat footed.
1:05
Slide into aiforfounders.co like a saxophone solo.
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you, leave a review because every five star rating is a high
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it. Thank you.
1:28
All right, let's get into it with Tim.
1:32
Tim, how you doing? Welcome to the show.
1:34
I'm good. Thank you, Ryan.
1:36
Appreciate it. All right, here's the challenge.
1:38
So just talking before we started here, we're both huge
1:42
jazz fans, or should I say jazz nerd would be probably more
1:46
technical. So the challenge is to to rope
1:51
jazz metaphors through this whole conversation as much as we
1:54
can. Sure, before it gets.
1:56
Into my grass. That's a good idea.
1:59
Awesome. Let's talk about your company
2:01
and your role within the company.
2:03
We're talking about kiteworks and people can find
2:06
kiteworks@kiteworks.com or just Google it.
2:08
It is a venture backed Unicorn. So we're going to talk about the
2:13
company, we're going to talk a little bit about you and I want
2:15
to talk about the really kind of innovative AI tools that you
2:18
have coming for your customers, which sounds really interesting.
2:22
So kind of give us an introduction to to kiteworks and
2:25
and your role there. Yeah, and just slight nuance,
2:28
but PE backs, not venture backs, it's.
2:33
Pardon me, Claude got it wrong. No worries.
2:36
It's it's actually interesting. I was at a we have two main
2:41
private equity companies that are backing us, 6th St. and
2:44
inside partners, pretty well known in the the tech ranks.
2:50
But I was at a conference that 6th St. had and you looked
2:56
around, it was ACEO, Chief strategy officer, chief
2:59
financial officers. And you looked around and
3:01
everybody in the room at, you know, the CEO sea level that was
3:05
there was kind of like me, like late 40s Gray hair, you know,
3:11
been down the road a few times, a lot of mistakes kind of a
3:14
deal. And if you go to a venture
3:18
backed company conference, everybody's like 27 to 38 and
3:25
just a lot of energy. It's a very different dynamic.
3:29
Those two, those two types of funding organizations really
3:32
target different types of companies.
3:33
That's the only reason I set it up.
3:35
And to say that in the context of kiteworks.
3:39
So Kiteworks has been around as a business for 2324 years, but
3:46
it was formerly Kai Works, the artist formerly known as
3:50
Excelion. Does that count as my first jazz
3:52
reference? Because I said artist, I mean
3:54
Prince is. Kind of I'm I'm following.
3:56
I'm following. So Artist, formerly known as
3:59
Excelion, started out as a secure file transfer company.
4:05
They were in the Magic Gartner Magic Quadrant as Enterprise
4:09
File Sync and Share that's sort of got commoditized as a as a
4:13
technology and as an industry Magic quadrant away.
4:16
A lot of stuff went away, but the company at about I'd
4:20
probably say that it's a year 15 was generally struggling.
4:23
It was a 30 million in revenue was sort of losing money, to be
4:27
honest. And the board brought in the now
4:33
current CEO, Jonathan your own, and he saw what was under the
4:38
the hood of this. And he came from the Israeli
4:42
secret units, Secret Service unit, I guess I'm not sure
4:45
exactly what it's called, but it's 8200.
4:47
And he spent his life looking at signals.
4:51
And he saw under this technology the ability to look at
4:57
visibility, see signals of how data was moving in and out of an
5:00
organization and realized that there was a there there that
5:04
wasn't quite getting to market. And brought in this vision of
5:10
creating, expanding the platform to cover all methods and unify
5:16
all methods in which data moves in and out of an organization.
5:22
Which, you know, again, Harkins back to his 8200 to sort of say,
5:25
like, data's moving over here. What does that mean?
5:27
Data move is over here. And so he built out the platform
5:31
to cover not just file share, but e-mail as a channel manage
5:36
file transfer, AP is secure file transfer protocols, basically
5:41
any way that data could move in and out organization built out
5:45
that platform to cover all of those systems.
5:49
And I came on five years ago now.
5:52
I came on actually as the the Chief marketing Officer.
5:55
And there was a little bit of brand confusion in the market
5:58
because the company was still called Exelion, but they had
6:01
this product, this platform that was called Kiteworks.
6:04
And actually some of the market thought that Kiteworks was
6:08
competitive to Exelion. So there was just general brand
6:11
confusion. I said, look, Exelion's kind of
6:14
a weird word. It's hard to say, it's hard to
6:15
spell. Nobody remembers it.
6:17
And you, you're sitting on this nugget of a brand called
6:20
Kiteworks. Although it's a weird name, it
6:22
doesn't really reflect what we do.
6:23
People know what it is, so let's elevate the the brand of this
6:28
platform. Kite works to the name of the
6:30
company was able to convince him to do that.
6:32
That turned out to be a good idea.
6:35
Much more brand recognition. And from that time on, we've
6:40
been able to extend the vision through fulfilment of, of his
6:46
his ideas, create a policy layer on top of all of those different
6:49
channels. And really we operate now as the
6:53
control plane for data moving in and out of an organization.
6:57
And now to tie this all back to AI and what's happening with,
7:04
with all of that, especially agents, we just see AI and
7:07
agents as another pathway that data moves within and in, in and
7:12
out of an organization. So we've launched and continue
7:15
to launch technologies on our platform to manage those that
7:19
data flow as well. Nice.
7:22
So kind of in a nutshell, you know kiteworks providing a
7:25
secure compliant platform to exchange information for
7:29
businesses and excelion and kiteworks were maybe in conflict
7:33
with each other. So by simplifying, you're able
7:35
to find a much larger market for probably what felt a little bit
7:40
incomprehensive in the in the beginning, it, much like Louis
7:45
Armstrong, kind of took a challenging art form, which is
7:47
jazz, and brought it to the masses and expanded the market.
7:51
Yeah, that's, that's true. We're more like, let's call it
7:55
like a Herbie Hancock sort of fusion jazz scenario for a
8:01
while. But I think we've we've smoothed
8:03
it out and look, honestly the the data challenge, the data
8:07
security challenge is the challenge.
8:10
Like if you think about all security in the sort of
8:13
historical capacity, they've been putting security layers on
8:17
the perimeters, on the cloud, on the endpoints.
8:20
It's all about like infrastructure security.
8:22
But the end of the day, it's all focused on protecting data.
8:26
And we're able to bring that security layer down to data
8:30
itself and in control, which is why we call it the control plane
8:34
that data. And, and again, now in the day
8:37
of AI and agent, the whole focus has, has really shifted towards
8:42
what data do I have, where's it going, what people are using it,
8:46
what agents are using it? And we're able to provide that
8:49
that clarity for people. And now more than ever, truly, I
8:53
mean, you guys are in a great position because like, I mean,
8:56
the data flowing off my desk is kind of insane.
9:00
You know, I, I'm like, how is it possible that I've maxed out,
9:04
you know, Claude Pro and it's Wednesday like, dude, it's
9:08
bananas. You know, so it, it's essential
9:11
work for companies and you guys have seen explosive growth and
9:16
I, I think, you know, your role has had a lot to play with it
9:18
because the, the brand, the go to market, these are all things
9:21
that encourage confidence. How long have you been a
9:24
watermelon man? I I'm gonna assume that means
9:30
how far the pepetic guy works or in in general.
9:33
There's a Herbie Hancock reference.
9:35
I got watermelon. I can't remember what that means
9:39
in terms of how long specifically, but I've.
9:43
Been with no as far as like your role.
9:46
My role, So I've been doing marketing in tech for 20 years,
9:54
maybe a couple years longer than that.
9:56
I became the chief strategy officer here three or four
10:02
months ago. The reason reason for the shift
10:05
was one is I just, I'm all set on marketing.
10:10
I got that T-shirt. I I kind of know what to do at
10:12
this point. Got the system running, got it
10:15
in good spot. But I also see saw an
10:17
opportunity to drive a lot more value, a lot more shareholder
10:20
value and a lot more value to our customers by really taking
10:25
the lead on internally how we as a company adopt AI from a
10:30
productivity standpoint, from an execution standpoint, from
10:34
rolling out products and also how AI can provide value to our
10:40
customers. So it's Chief Strategy Officer,
10:43
but if I were really to focus it down on what that means here at
10:47
Kite Works, it means how can we drive value through AI
10:52
internally and externally for our customers.
10:54
So I've been doing, I've been doing that officially for four
10:58
or five months, but unofficially since November 23rd, 2022, when
11:05
I first logged in the ChatGPT and and looked at my wife and
11:10
said, OK, this, this is a thing. Quick side note for founders who
11:16
are using AI to write content, you've probably noticed this.
11:19
It's incredibly fast, but it doesn't really Dr. meaningful
11:22
traffic. And honestly, that's because
11:24
most AI generated content is just average.
11:27
There's no real insight, no depth, no structure, missing
11:31
things like internal linking, and Google's getting very good
11:34
at filtering that out. So instead of trying to just
11:36
prompt better, I actually came across something interesting
11:39
called Neenah. It's a system that combines
11:42
human strategy and review with AI writing to create high
11:45
quality SEO optimized blog content that's actually designed
11:50
to rank and keep ranking. What I like about it is that
11:52
it's done for me. Their team handles the topic
11:55
strategy and the content review and data markups for Google and
11:59
turns blog posts into actual long term traffic assets.
12:03
So if you're a founder thinking seriously about organic growth,
12:06
this is one of those things worth paying attention to.
12:08
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12:11
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You make the show, Casey makes the money.
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12:57
That's GETHOW. di.com takes a couple of minutes to get started
13:02
and Casey gets to work immediately.
13:04
That's gethowdy.com. Yeah, yeah, that was a a wild
13:09
moment. I remember everyone was passing
13:11
around JavaScript, so making like Twitter, like bots and
13:14
stuff like that, you know, incredible.
13:16
So, you know, working with it from 2022 essentially, man,
13:20
that's you're an elder stage. Yeah.
13:23
It was, I mean, really I just for some reason for me, it
13:26
clicked instantly and I spent a year and a half thinking, why is
13:30
everybody not spending all day, every day using this thing?
13:34
I mean, I was pulling teeth in the company, outside of the
13:39
company. Anybody that would listen, I
13:41
would try to explain like you got to spend 2 to 3 hours a day
13:46
in these systems so you understand how much value they
13:50
can drive and you can become an expert at it.
13:53
And that will in turn drive value for you and your
13:57
customers. Yeah, yeah.
14:01
It's kind of fun to think about. Like when chat came out.
14:02
I mean, I think it still holds the record for the fastest
14:05
growing product of all time, which is incredible.
14:07
But it was kind of a psychedelic experience kind of playing
14:09
around with ChatGPT in the early days because it was so wildly
14:13
incorrect all over the place. I mean, it's really come a long
14:16
way. All of the LLMS have of, like,
14:19
being pretty precise, you know, and you can kind of check it
14:21
against each other. And of course, there's plenty of
14:24
like Tik Toks out there of ChatGPT getting incredibly
14:27
wrong, but it's definitely in a different age.
14:29
So that's really interesting. The the a strategy of like
14:34
delivering AI. So maybe talk a little bit about
14:38
initiatives and like how you early on kind of identified
14:41
opportunities with AAI within kiteworks.
14:44
Obviously AI is ramping up compute all over the place, so
14:49
it falls into the pocket really easily.
14:51
But is there any kind of specific tools or you, you know,
14:54
kiteworks agents in the pipeline?
14:57
Yeah. So there's a couple ways I could
14:59
talk about this. I think I'll I'll talk about it
15:02
in in that context. And we, you know, if you want to
15:05
wax philosophic about AI from a productivity standpoint, happen
15:09
to do that as well. But you know, like I said at the
15:13
beginning, I just look at AI. Let me back up.
15:19
So if you think about SAS in general, it's a, it's a, it's a
15:25
layer that sits between someone having intent and data.
15:32
And now the someone has become someone in something intent and
15:38
data. And as you know, with phrases
15:41
like Saspocalypse and all of that type of stuff, that that
15:45
that layer in between is changing dramatically.
15:49
So before you had to sort of to understand how to use different
15:53
software, there's entire professions that blew up around
16:00
software leverage, how to how to create a better marriage between
16:04
intent and data using specific types of software.
16:07
You saw people whose job titles have the name of the software in
16:11
it. And you go to any company and
16:13
there's entire divisions of people with the phrase sales
16:17
force in their title. And it's really because there
16:21
was just all of that complexity of the software, the SAS tools
16:26
in order to get the value out of connecting intent with data.
16:29
And that complexity is for all intents and purposes gone.
16:33
And there's people's comfort levels that are keeping this
16:37
sort of historical SAS model alive.
16:42
But when you get a cohort of people who understand that that
16:48
complexity is gone and can look at an AI system and say, you
16:51
know what, I can just connect my intent with this set of data
16:56
using CLOD and strip away all requirements of understanding
17:03
how a particular software works and just use natural language to
17:07
leverage the data. You get a complete
17:10
democratization of data, leverage and intent and and you
17:15
scale out the ability for people to do good things with data, but
17:20
unfortunately also bad things with data.
17:22
And they're doing this through the proxy of AI agents.
17:27
And so for us at Kite works, when we look at data as the end
17:32
game of of what we need to protect or what we need to allow
17:36
enable customers to protect and control.
17:38
We see that in order to do that in the age where anybody can
17:44
spin up an agent to leverage data, you have to put controls
17:47
and guard rails at every single data layer based on the
17:52
different types of you're out there.
17:54
So we rolled out a technology and a control plane that maps
18:01
individual assets to individual agents in sort of, and I'll just
18:07
dumb this down as much as possible just to get the point
18:09
across this Excel sheet. Yes, no, this agent in terms of
18:14
use, access and sharing capabilities, this Word doc, yes
18:18
or no access, sharing and use with this agent and all that
18:23
matrix so that we can help our customers really get control
18:27
over their data as assets and their agents that are going to
18:32
be leveraged by their employees to ensure that they protect the
18:36
data and they remain compliant. So that's we rolled that out
18:40
three or four months ago and we're getting a lot of great
18:44
uptick and and real positive response because that is a real
18:49
challenge for companies right now.
18:50
It's a little long winded, but I think I think I got there at the
18:52
end. You did, you nailed it.
18:56
You know, and I'd love to to talk about this too, because
18:59
everything is moving so quickly. And so when we're talking about
19:02
compliance and guardrails, this is stuff that's not really
19:05
probably going to come to fruition for 12 months until
19:09
kind of like there is some kind of like legislation or the, the
19:14
rules start to stack up. It'll it'll start to filter out.
19:17
So what companies are then going to be responsible for is
19:19
auditing like all this agentic stuff that they were doing to
19:22
make sure they were compliant. And if they don't have those
19:26
that kind of like end data now, like what are they going to do
19:29
in 12 months when they're hey, hey, what have you been doing
19:31
for the last year and a half? You know, so it, it is like kind
19:34
of there's a CYA component of like jumping on board of this
19:38
really, really quickly, you know, as fast, you know, I mean,
19:41
because we're talking like what it was probably 6-7 months where
19:43
everyone's like, OK, GPT subscriptions for everybody.
19:46
And then everyone's like, OK, actually Claude code
19:48
subscriptions for everybody. OK, what are we doing with
19:51
Openclaw? Like, and all this stuff is
19:52
going to, you know, over time, they're going to start to be
19:54
like, hey, these things were out of compliance.
19:57
So these things weren't governed properly.
19:59
We're going to need to go back and you're going to need a
20:01
report on that. So having some of that insurance
20:04
now is probably really important.
20:06
Yeah, exactly. I mean, it's, look, it's a real
20:09
bitch's brew of problems if if you think about it from a
20:13
regulator's standpoint. The the and here's the thing,
20:19
regulators don't give a RIP. What caused the data exposure?
20:26
It could be, it could be an orangutan, you know, an agent
20:30
doesn't matter to them. They just know that this set of
20:33
data has PIIPHICUI, all the IS and that it can or can't do
20:40
these things in in an ecosystem. And so companies need to really
20:46
understand that, yeah, there's no regulations yet on agents.
20:52
There will be eventually, but there are still the same
20:55
regulations on data and they don't care what entity caused
20:58
that exposure and you're going to get fined.
21:01
So any sort of policy constraints that those
21:06
regulations dictate that our customers have been applying to
21:09
their data sets with people just need to be done with agents as
21:13
well. Yeah, 100%.
21:16
Yeah. And with compliance, you know,
21:18
you don't need a weather report to see which way the wind's
21:21
blowing, you know what I'm saying?
21:23
That's. That's that's that's, that's a
21:25
good stretch to jazz fusion of the 70s.
21:28
I like that one. Diffusion theme is fun.
21:32
This is good. You like the diffusion jazz?
21:34
Yeah. Yeah, I like it.
21:37
It's good. That's that was kind of my
21:38
intro. You know, you got to, you know,
21:40
Miles Davis, the stuff he was doing in the late 70s and then,
21:43
you know, Pharrell Sanders and all those guys.
21:45
That's good stuff. Yeah, what's a weather report
21:49
was Steve Winwood. Is that who spun out of weather
21:53
report? Well, it's been a while since
21:55
I've listened to those guys. I think he did.
21:57
It was like Wayne Shorter and Jocko.
21:59
Yeah, you know the story about Jocko, how he died.
22:04
No. He was he was I rumor has it he
22:08
was a real asshole basically, and he he melted off at to the
22:15
wrong bouncer at a bar and he the bouncer beat him to death.
22:22
I think he kicked his eye. Yeah, it's kind of AI, don't
22:26
know that I'm I'm struggling to tie that to data security, but
22:30
it's a. Fun story.
22:33
It's a fun challenge. It's it's very two different
22:35
pockets of my brain trying to like shake hands here.
22:38
Yeah. Nice.
22:42
How about a little bit more about you, you know, it, it's,
22:46
you know, to go from kind of like more of a maybe sales and
22:49
marketing all the way into strategy and AI.
22:51
That's, that's a bit of a stretch.
22:52
You know, talk a little bit about that journey and kind of
22:55
why why you ultimately wanted to go in that direction and you
22:59
found kind of a blue ocean there.
23:00
Sure. So I think even throughout my
23:04
career in in go to market, I always I've always been a
23:07
builder. So I've looked at how do I build
23:11
systems to operate more efficiently and deliver value in
23:16
any case, as effectively and efficiently as possible.
23:20
So I actually started the first few years of my career, I was in
23:25
nonprofit fundraising. I worked at the Purchase College
23:32
for Performing Arts in just north of New York City doing a
23:35
lot of grant writing things like that's where I kind of got my
23:38
chops in, in jazz. And when I got I, I, I'm sort of
23:45
got connected with the guy who was doing some consulting around
23:50
tech and we got together and we just kind of fell back backwards
23:54
over Mark be building a marketing agency in New York.
23:58
And for 10 years we built this marketing agency and, you know,
24:02
bootstrapped it from like $0.00 and Morley the intern as an
24:06
employee to we had about 50 employees and close to 10
24:10
million in revenue. And I my, the most enjoyment I
24:14
had under that were building systems in to deliver value to
24:18
our customers. And so I would work with
24:21
outsourced developers and sort of wear kind of like a product
24:24
management hat while delivering services to a customers, while
24:28
selling, while trying to, you know, make payroll.
24:31
And it was a lot of work actually.
24:33
You learned a lot. But the, the, what I enjoyed the
24:36
most was the, the product building part of it.
24:38
And so I just kind of as I went through my career, when client
24:42
side, I just kind of always hold on to that, that product
24:45
building part. And the biggest bottleneck for
24:48
me was always finding a good developer, communicating well to
24:52
the developer where they understood the the scope of what
24:56
was required. And then the feedback loops of
25:00
like testing and, and, and getting ultimately what we
25:03
needed. And once, you know, I got past
25:07
the O question answer, this thing can write kind of a deal,
25:09
which is a big part of go to market.
25:11
And the coding started getting really quite good and I could
25:16
get to most valuable product or MVP is very quickly and skip all
25:22
that other stuff and just kind of really take direct control
25:27
from a product management to coding to an outcome.
25:32
I just went all in and you know, I didn't know what ACLI was a
25:38
command line interface was a year ago.
25:40
I had no clue what that was there.
25:43
I didn't know what a container was.
25:45
I didn't know what Kubernetes was.
25:46
I didn't know what Digital Ocean was.
25:49
And now I have more clod code, command line interface tabs open
25:54
on my computer every morning and all day long then I do browser
25:58
tabs. And so it just for me it was
26:02
natural to get into this environment where I could, I
26:06
could build ship value to both the company in terms of customer
26:12
value through our product to our company in terms of product
26:14
efficiency and to communicating our message out through the
26:18
marketing organization that it was just so natural and I
26:24
enjoyed it so much that for me it's not work.
26:28
Yeah, I just counted. I've got 9 terminal shells open.
26:32
It's great right now. Crazy, right?
26:35
Yeah. You know, and this is kind of a
26:37
a part of the opportunity, I think right now with with AI,
26:39
which is really kind of intriguing, is that if you are
26:42
kind of a person where it sounds like at the root of your story
26:45
is kind of communication, you know, which is to say, you know,
26:49
communication is kind of magical.
26:51
And we have language where I say purple squirrel and you have
26:55
that vision inside your head. And if I can communicate that
26:57
clearly, awesome. You know, with our work, it's
26:59
like generating desired outcomes.
27:01
Like I want you to feel this way and gain this thing and you hand
27:05
it somebody and they get it. It's magical when you can do
27:07
that. And you know, jazz is very
27:09
similar. You know, I think I really
27:10
respond to that, that form of music because it describes
27:14
experience and emotion that words have a hard time.
27:18
It struggles with, you know, and largely it it it's like kind of
27:21
a it's like a somber, at least my favorite stuff, the Bill
27:26
Evans and the the the modal jazz stuff it or you know, I love the
27:29
Mingus stuff too. So there's kind of like an
27:31
unhinged, there's a attention and there's always like this
27:35
beautiful release, you know, so the, the position for like using
27:39
AI to generate outcomes is you get to kind of skip the
27:41
middleman sometimes, you know, get it puts you in the position
27:44
where people that are much more outcomes driven, communications
27:49
driven, they're kind of in the driver's seat now, you know, and
27:53
it gives them the tools to kind of be able to design.
27:56
Yeah. And you know, the other analogy
27:58
to jazz on this is you kind of build in the moment.
28:02
A lot of times with with jazz, I mean, there's a general
28:05
framework and there's a structure.
28:06
And you know, if you, if you listen to, you know, a love
28:12
supreme at this one club, in general, it's going to be the
28:16
same at another club. But there's a lot of
28:19
improvisation that happens in the moment.
28:21
And I think with AI you, it offers you the same creative
28:26
outlet where as you're building, you start to realize this other
28:32
note you can play, we'll have this other outcome.
28:35
And you kind of see where that takes you.
28:37
And there's this exploration that happens and you know, the
28:43
the fact that it democratizes that exploration to anybody who
28:47
can use words, which is everybody pretty much.
28:52
I think people who look sort of narrowly at what that means in
28:56
terms of value. Look at it in now and tomorrow.
29:00
But if you, if you look at it in the context of if you can see
29:05
the forest through the trees and you look at 5-10 years from now
29:10
and the the road map begins with if you can use language, you can
29:14
build anything you can dream of, then I think we have a different
29:18
shaped world in five years. Not just like, oh, there's less
29:22
jobs or, you know, the SAS apocalypse have I think the
29:26
world changes. And so you know that's I bring
29:29
that sort of philosophy when I look at the strategy of and what
29:35
we're trying to deliver to our customers is what's the world
29:38
going to look like especially when it comes to information in
29:41
the next 3-4, five years. 100%, yeah.
29:45
The improvisation is going strong all over the place, but
29:48
you need the head to bring it back.
29:50
And maybe that's what kite work is.
29:52
You know, it's like, it's like, OK, John, you're stretching it.
29:55
But we're coming back to the main theme of my favorite things
29:58
here so that everything like stays tight.
30:01
We're at the time of the podcast where we're entering the Quantum
30:03
Round. Are you ready?
30:05
Sure. Yeah.
30:08
OK, OK, good. What does that mean?
30:10
So I want to be make sure we're we're a cat.
30:17
Yeah, exactly. Is there a cat in the box or
30:19
not? That's the question.
30:22
No, I want to be. Real clear because we have, you
30:24
know, thousands of founders listen to the show when and how
30:29
they should engage with Kite works first and foremost, Yeah.
30:33
I look. When I first started here, when
30:36
you do go to market and you work in new tech long enough, there's
30:39
something called the total addressable market or a Tam.
30:42
And that kind of gives you a good sense of how far a company
30:45
is going to go. And because there's competition
30:49
in every Tam, a Tam's only certain certain size, There's a
30:53
certain amount of the Tam that's been already captured.
30:58
And you do that calculus and you know how far the our Tam as a,
31:02
as an organization is, if you have a pulse and you have a
31:06
company, you need us. So because all companies have
31:10
sensitive data that they need to protect from exposure, all of
31:14
them could be financial data, it could be customer data, it could
31:19
be health data, depending on how regulated you get.
31:22
So, you know, if you're a founder and you're looking at,
31:25
hey, where's my data and how controlled, what kind of control
31:31
layer do I have on top of that data to ensure that I'm not
31:34
exposed? Because as a, as an owner or a
31:37
operator of a business, the worst thing that could happen to
31:41
you is that you get exposure to the point where you get fined or
31:46
sued or lose business because of brand reputation that it all
31:51
three of those things are a killer.
31:54
So, you know, if you have a pulse of the business, you
31:57
should look up kiteworks.com because there's a value that we
32:00
can drive to your organization. Now, having set the Tam for
32:04
everybody in the world, I'll bring it down to a smaller group
32:09
that find the most value out of us most quickly.
32:13
Companies in highly regulated industries.
32:17
Financial services startups, Legal startups.
32:20
Healthcare startups. Any company going to.
32:24
That's going to do business with the federal government or any
32:28
company that's going to do business with a company in the
32:30
federal government's information supply chain.
32:33
The more sensitive. The data, the more regulated the
32:36
data, the more pressure there is to control its exposure through
32:40
humans or through agent workflows today, yeah.
32:44
At the end of the day too, you just sleep better, right?
32:47
I mean, a part of the, the wild, intoxicating thing about right
32:51
now is there's so much excitement, so much enthusiasm,
32:53
but there's like a nagging thing in the back that's like, I don't
32:57
know what I don't know. I don't know what my exposure is
32:59
like right right now, 'cause I'm moving so quickly.
33:01
I'm just hoping that Claude gets it right, you know?
33:04
So, you know, Kai works, gives you Peace of Mind where it's
33:07
like, OK, we're we, they've got our back.
33:09
Yeah, 100. Percent and again it's
33:12
especially in this Wild West of of AI and agents, you gotta get
33:15
the gotta get control on your data 100%.
33:19
Cool. You mentioned Jonathan as being
33:20
kind of like a influential leader for you and obviously did
33:24
great things with with kiteworks.
33:25
Are there any other, you know, CEOs or leaders you really
33:29
admire somebody you might put on the bandstand?
33:32
Sure, I. Mean.
33:34
Jonathan's the the CEO. We also have an incredibly
33:37
talented chief product officer who heads up the the build of
33:42
the kiteworks platform. His name's Yaron Gallant.
33:45
He is also from the 8200 unit. But he has an interesting story
33:50
is he was part of the small group that invented the WAFF,
33:53
the web application firewall. I have never invented anything
33:56
even close to his impactful as the the web application
34:00
firewall, which every application on the planet needs
34:05
due to PCI and a number of other regulations.
34:08
So I'm surrounded by talents and, or by talent and, and I'm
34:15
standing on the shoulder of giants by a large stretch of the
34:18
imagination. And then of course, I have an, a
34:21
whole career of mentors that have kind of helped me along the
34:25
way. But you know, if I look at Kite
34:28
Works as an entity, any anybody with AC in it and works at Kite
34:32
works is, is incredibly good at what they do, Yeah.
34:38
Mentors have been like really important to me in my life as
34:41
well. It it really helps kind of steer
34:43
you in good directions. Is there any way you kind of pay
34:45
it forward and and mentor other people?
34:48
Yeah, and. I mean, I hope I do.
34:53
I would say like. Like I don't, I don't say I set
34:56
out to mentor. I'm, I'm not looking across my
34:59
organization or other companies and saying, oh, here I'll just
35:04
be a mentor of, of this person or that person.
35:07
But what I just try to do is ensure everybody knows all of
35:13
the mistakes I made, why they were mistakes and why the
35:17
decisions that I'm making now are informed by those mistakes
35:21
and that they're not, I'm not just women yet.
35:25
You know, it's the Gray hair came early.
35:29
And I want people to, to take lessons from all of the Hard
35:34
Knocks that I, I had to take so that we can execute effectively
35:38
as a, as a team and, and get things done.
35:42
And, you know, in those lessons, I hope that people look back and
35:48
say, you know, I learned enough from from Tim's leadership to
35:53
call him a mentor. That'd be that'd be great for
35:56
me, but I don't I'm not mentor seeking.
36:00
Yeah, totally mentee. Seeking.
36:02
Yeah. Amazing.
36:04
You met. You mentioned Hard Knocks.
36:06
Any notable failures you want to share?
36:08
Or perhaps, you know, times you were singing the Blues and the
36:11
abstract truth. Yeah.
36:13
Yeah. Well, I mean look the.
36:17
When you're in go to market sales and marketing, there's
36:20
failures every week, high highs. Low lows.
36:25
That's why I love sales. You try.
36:27
Things they don't work. The key is just to realize that
36:32
that's part of the process and also to surround yourself with
36:37
people who also realize that's part of the process that don't
36:42
see failures as a way to, or as a, as a source of flames that
36:49
you work gasoline on to keep everybody distracted from your
36:52
insecurities. That's a real thing.
36:55
By the way, I've worked in enough organizations to be able
36:58
to, to spot people who are insecure in their own values.
37:02
So if somebody else over here makes a mistake, they'll pour
37:05
put fire on it. So everybody keeps distracted by
37:08
that. So they don't see how they're
37:09
not driving value. And and so, you know, I I get
37:15
back to kind of the team that Jonathan is built here and you
37:18
know, my colleagues and and stuff like that.
37:21
You know, Kite works is definitely an organization.
37:23
We have tremendous value to our customers, but I think part.
37:27
And parcel of that is. The the organization that
37:30
Jonathan has built is a group of people who have kind of been
37:33
there, done that, have made a ton of mistakes and know that
37:40
you get nowhere by throwing gasoline on the flames.
37:43
And so we're all just kind of going together and trying to
37:46
make mistakes and learning from them all the time.
37:49
And that's, you know, that's how that's how companies progress
37:52
and how you actually get shit done.
37:55
I love that. I think that's particularly
37:57
important for for young founders to hear, you know, people that
38:00
are chasing the VC, they're not ready for private equity
38:03
investments where they only want to invest in people where the
38:05
weight of the world has crushed their dreams.
38:08
But I, I, I had a, I had a great analogy.
38:12
Somebody was talking about failure and was saying it's like
38:14
very similar to a muscle that, you know, for a muscle to get
38:16
stronger, you actually have to push it towards failure.
38:19
You have to encourage failure. So, you know, you don't get
38:23
comfortable with the feeling of it, but you kind of understand
38:26
the terrain because ultimately that's how you mature.
38:28
And it's the people that persevere at the end of the day
38:31
that win, you know? Yeah.
38:33
And it's. Brutal and it sucks.
38:35
And I found myself occasionally saying, when do I stop learning
38:39
lessons? Enough with the lessons already,
38:42
you know. At some point you want.
38:45
To be be on the side of you know, I know it all and we're
38:50
good. Just trust me.
38:53
But never get there. I I found myself in a.
38:55
Similar position where I'm like, I already knew this, I didn't
38:58
want to be reminded. Yeah, yeah.
39:01
Enough with the lessons. Amazing.
39:03
This has been so fun. Aside from work stuff like are
39:06
you you have any fun experiments with AI or like little things
39:09
that you're working on in building?
39:11
Yeah. So I have a 16 year old and a 13
39:18
year old. Interestingly enough, they hate
39:20
AII. Can't figure out why.
39:22
I think it's because I love it so much and they just want to
39:24
not like what I like, 'cause they're 13 and 16 year old
39:27
girls. But my.
39:29
Wife and I have a. Challenge balancing all of the
39:31
stuff we do and all the stuff they do and coordinating and
39:34
organizing and planning and all of that stuff.
39:37
So I built an app that plugs into our Google Calendar and
39:42
connects to Twilio and connects to Claude.
39:48
And we have a personal assistant that texts us reminders.
39:53
We can text the personal assistant back and say, put this
39:57
on the calendar And it just kind of coordinates and keeps us all
40:02
In Sync with like, who's picking up Olivia tonight and who's
40:06
dropping off Emma tomorrow? And.
40:08
You know, it's Dad going to New York on Sunday and that's,
40:11
that's actually been very, very helpful.
40:14
A little bit of a life hack there.
40:15
Oh, that's brilliant. I'd love to learn more.
40:17
I have. I have a 18 and 17 year old.
40:20
So yeah, it's like, OK, my daughter's coming back from
40:22
college this week. My son's got football practice
40:25
starting up his contact camped. I mean, with kids, especially
40:28
teenagers, it's just like, where are you guys going?
40:30
Like, what's happening? Yeah, Yeah, it's.
40:33
So that's kind of a fun one. I build cool.
40:35
I love it. I want to give a shout out to
40:37
Monterey Jazz Festival. I know that's a nonprofit that's
40:40
near and dear to your heart and just amazing.
40:42
You know, this has been so fun talking about jazz.
40:44
Maybe we'll wrap this up with your favorite horn player, your
40:48
favorite piano player, your favorite rhythm player.
40:53
Wow, OK, so Horn player, it's probably somewhere between.
41:03
I mean, I hate to go Miles Davis, but man, he's good.
41:07
It's hard to beat him. Yeah, I think, I think.
41:10
I'm going to stick with him. It was.
41:12
It was either that him or John. John Coltrane.
41:15
And then from a piano standpoint, is that what you
41:18
said? Yeah.
41:19
Piano, Piano. Thelonious Monk, rhythm.
41:27
I don't know on that one. What about you, you know?
41:32
Rhythm and so like bass and and drums, I, I would put Mingus up
41:37
there. I think his his compositions are
41:41
probably the best, you know, in my opinion, horn players right
41:45
now. You know, I've been listening to
41:49
a lot of. Paul Desmond, you know, I kind
41:52
of slept on Paul Desmond for a long time.
41:54
Of course, you have Take 5. He's he's got like this godly
41:57
sound. But I've been going deep into
41:59
his catalog and he is gorgeous. I really like him.
42:02
I like Oliver Nelson a lot. And then piano player, I love
42:06
Monk. I would probably say Bill Evans,
42:08
though. I like that kind of Moody stuff.
42:11
I like Vince Garaldi a lot too. You know, you got to bring that
42:14
out at Christmas. Yeah.
42:16
We have a lot of his albums up at our cabin in the Sierras.
42:22
No TV allowed at the cabin, only in a record player from the late
42:28
70s and the speakers to match and real records, real albums.
42:34
And we have a lot of Fitzcarraldi up there.
42:36
So good call. Nice.
42:38
Yeah. Amazing.
42:39
It's. Kiteworks.com, if you have data
42:43
and you have a pulse, you need to go check it out.
42:47
Well, take care of you, Tim. This has been awesome.
42:49
What's the best place for people to connect with you online?
42:52
I think probably. LinkedIn, I, I, I shut down
42:55
Twitter a couple, a few years ago, I found myself addicted to
42:59
it, shut down Instagram, shut down Facebook.
43:02
I couldn't do it anymore. But I'm pretty active on
43:04
LinkedIn. So it's, you know,
43:07
linkedin.com/freestone. I can be contacted there sweet
43:11
and I'll put all the links. In the show notes, I'll see if I
43:14
can get a little musical samples of some of these folks we were
43:17
talking about. But I loved, I loved the the
43:20
fusion angle. It was a blast.
43:21
Tim, thank you so much for joining me.
43:23
Yeah. Thanks a lot.
43:24
I had fun, Ryan. Appreciate it.
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