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Hello, dear listeners, Bailey here.

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Today, we are diving into the fascinating world of web three and

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decentralized databases. Join us as Andy

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and Frank interview Brennan Lanay, the founder of Quill.

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Quill is the 1st decentralized, Community owned SQL

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database solution for building advanced dapps and protocols.

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From the demand for web3 solutions to the nuances of trustless

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applications, we delve into it all. Don't be

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alarmed at Frank's absence early on in the show. He

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shows up later. As an added bonus, for the

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first time in data driven history, Andy does the intro.

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So sit back, relax, and get ready to embark on a journey that

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will expand your understanding of the ever evolving landscape of technology and

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data. Now on to the show.

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Hello, and welcome to Data Driven, the podcast where we talk about

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artificial intelligence, Machine learning, data engineering,

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and all things kind of related to to those topics.

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Frank usually does this introduction. That's why I'm kind of skipping through

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it. I'm trying my very, very best to not say,

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in any of these. Frank's gonna join us a little bit later.

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He had something else he needed to do. Our guest today

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is Brennan Lamy. Did I say that right? Brennan, both names?

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That is correct. Yes. Awesome. And, Brennan, I usually

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go to LinkedIn and read through the lengthy

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bio. And and here we go. Brennan is a

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founder and dev. That's a pretty lengthy bio. That may

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be the shortest LinkedIn bio ever, Brennan.

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Yeah. I would say, I I don't know. I'm still working on stuff to

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put there. But I I'm open to

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suggestions. I'm open. Awesome. No. I I think it's great. I think,

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you're spending your, your time wisely And you've got your

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priorities, pretty much aligned there. You're you're you're doing the

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work and then later once you've done the work you can come and fill in

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the blanks. That's the goal. That's the goal. Awesome.

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Well, why don't you tell us a little bit more about yourself? Maybe what you're

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working on, your company? Yeah. Yeah. So, I mean, my name

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is Bruno Marney, and I am the founder of Quil. So it's just

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k w I l, kinda like the Quil that you, that you can write with.

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Cool. And Quill, we are building, decentralized databases.

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So relational databases, specifically. Okay. And

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really the niche that this This fits into. I don't like to say

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that it solves an existing problem, because I think it more

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allows people to Capitalized on previously uncapitalized opportunities

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and solving some, you know, massive problem. But what a

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decentralized database is for is It allows you to build new types of

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applications with different trust assumptions. And it it also

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allows you to accrue value from your data in new

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ways. And so this very much falls into the web three space. I'll

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sort of give a high level overview here, and then, Andy, you can sort of

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choose where you want to go deeper. But with Quill, you can build

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data stores with, complex access control rules,

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complex guarantees on the scheme of the data, who's able to write to it, How

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they can write to it, when they can write to it. And you can set

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this for parties that don't trust each other. So maybe you and Frank are competitors

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or maybe you have to agree on some sort of, legal standard and collaborate in

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that way, but in all other sense of the word, you are competitors.

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And so this allows you to convene around a shared data store with rules

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set beforehand. And you can now use this, in real

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time to power both of your applications. So kinda at

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a high level, that's what we're doing. There's some really interesting caveats In value

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accrual as well, but I can sort of jump into anywhere that you want me

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to. You know, I'd love to hear more about the value.

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Yeah. So the the the real value of this so

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it might be helpful with an example. I'll try to high level, and then I

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can sort of dive into a couple examples we see right now. But so,

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you know, the a lot of companies use data as a moat.

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Data protects them from their competitors, but this also means that

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you can't collaborate on data in a lot of ways that you might like.

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And I think a cool example of this might be user identification

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data. So this is pretty low hanging fruit. And for what it's worth, I don't

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think it's, a particularly interesting example, But it is basic.

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Things like Reddit, Spotify, and Instagram, they they all have the

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concept of follower relationships, but they all have different

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applications otherwise. And I think in a better world,

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no matter what application you go and use, you would have the same

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follower relationships and the same interests on all those different platforms if you

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consented so. That is a massive, identity problem, so

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you now need a way to your identity across those as well as your your

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follower relationships and your interests. And all of those

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companies are maybe somewhat competitive with each other.

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Maybe not totally, but they are somewhat competitive. But in an ideal

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world, they would be able to convene around some of the same sets of

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data To power their application, this does give them less of

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a data moats effect, but it does make the experience much more

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convenient for your for their users. Okay. So

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now, once again, I don't think that is the most compelling, application,

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but, that's like a very high level example. It's a

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good example. I was able to follow it. And, you know, it's always a good

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sign. Yeah. Right. Glad to hear. I,

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So I'm concerned about, as a person who moves data,

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I'm a data engineer, and I'm concerned a little bit about,

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Personally identifying information, not picking on your example, I

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promise, from the for the user's

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perspective. And then also,

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that, you know, there's there's legal, stuff that goes along with

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that in some fields. I do, I do

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health care. I do financial. Those insurance. Those all

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both health care and legal come together there. Sorry. Healthcare

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and finance come together in insurance companies.

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And so It you said something

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that I found compelling. You said that you could convene around the

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data, but you could do it in such a way Where you share

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just what you wanna share, I think. And then, you, you

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know, you've got a firewall essentially or some kind of separation of

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concerns Between that and the rest of the data. So could

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you elaborate on that a little bit and, you know, specifically

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with, With regard to regulations?

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Yeah. So I I think we can sort of split this up into 2 different

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topic areas. So one of them is the the logical way of accessing data.

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So This is like your application business logic. Should Frank be

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able to should he be able to see my name, my age, my social security

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number, and what can he see from this dataset? But then

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also there is, there's sort of a an issue of

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legal regulations. So whether that's GDPR or, you brought up health

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care data. A lot of health care data, it matters where physically that

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data is being stored. And so to sort of jump into the first one, this

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actually gets to really the of our application or maybe one of the cruxes of

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our application, which is configurable access control

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for your data all within a single a single file or you

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can you can do it across multiple files, but the the idea is that you

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can do it in a single file. So we have our own language. It's a

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DDL language, data definition language called Cuneiform.

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And so with Cuneiform, it allows you to do a lot of, you know, regular

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SQL DDL for tables and And things like that, but it it

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also allows you to specify more complex access controls.

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So who can write data? Who can read data? What data can they read from

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this? And then we're also working with a couple partners right

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now designing a system of role based access control.

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So you can assign different roles, roles might apply to different individuals,

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or to different companies or really however you want to administer

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these roles. And these define, like, with business

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logic defined in cuneiform what a specific user is

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allowed to access. Moving a bit more

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to the regulatory side, this is less of a

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question of the actual features of our product itself and more

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of, a deployment issue. So you can sort of

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think of our when you're using a Quill database,

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it's distributed across multiple databases. And we

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work with clients to help them distribute those databases as needed,

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for their application. And this is, across an entire spectrum. So

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On one side of the spectrum where there are no data privacy rules, you

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could actually have a network where anybody is allowed to come in and sync this

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data from your database. They're able to To get these updates in real time,

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and then they can directly join in foreign key and, subquery

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against this in their own application. And this obviously no

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data, like, no legal restrictions, no access control

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restrictions. It's like a totally public, read only dataset.

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And then on the other side of the spectrum, you might have 2 companies that

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wanna convene on health care data. And that health care data might need to

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be geographically located in the State of Texas or maybe in the

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case of GDPR, it needs to be, 1, it needs to

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be located in European countries, but, 2, they also need to be able

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to identify what companies are responsible for storing this data

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so they can go after them to make sure they delete it. And so we

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can also make sure that, as opposed to the other example

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that you are gating who is able to store this data, Where

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they're storing it, are you KYCing the other people that are running this

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physical infrastructure that is, holding the data for your database?

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And we work with clients sort of across that whole spectrum on what they need

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for their specific deployment topologies. Well, that

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sounds Complex. I think that's the first word that comes

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to mind on that, but it also sounds like,

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an interesting collection of problems that we have with data.

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One of the reasons I get employed as a data engineer is

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to solve these kinds of problems where we keep data in one location,

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we set, we sometimes ship data to other locations

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so that other people can use copies of it. An advantage

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that leaps to mind, based on your description, Aquil

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is you don't have to make a bajillion copies of the data. You are

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able to just share, it sounds like, access. And you're,

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defining in in this language that is it, you you pronounce it, I

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believe, cuneiform? Yeah. Yeah. Cuneiform. Isn't that the Egyptian

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characters For hieroglyphics. Am I getting that

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right? Or Yeah. So Cuneiform, it was the 1st written

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language. I should now ours is Quill for us is

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spelled with a k. It's Unifor, also spelled with a k. Other than that Interesting.

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That's kinda cool. I I like it. And, yeah, it sounds

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like Based on the problems you're trying to solve, that it would

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also be a very, very flexible

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and and very, cool language to to learn. And

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and I'm just curious if somebody, someone like me so I'll use

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me as an example because I would like to know more about it. Is there

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some way that I can get in and play around with Quill, get a feel

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for it? Yeah. Yeah. So just ide.quill.com.

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So IDE and then Quill, k w I l.com. That pulls up

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an IDE. It also gets preloaded with 3 different, Somewhat

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basic examples, for a type of application you might build on

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Quill. So and I'm just pulling this up right now as a reference, but we

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have, like, an example video game that's storing data. We have, a

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token. We operate a lot in the cryptocurrency space, and then also

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an example social network. And all these show how you would use Cuneiform,

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to to do this. And it's it's very straightforward. If you know if you're

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familiar with the SQL 90 2 standard, I am fully confident you'd be able to

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look at this and tell me exactly what is going on in this Application. It's,

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it's pretty straightforward. Awesome. I'll take your word for it.

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And and I'm fascinated by the idea, the, just the whole idea

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of this. A little bit of company background. I'm just curious how long has Quill

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been around? So Quill's been around for a little over 2 years

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now. Started under a different name and doing something different,

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actually. So, we're building a decentralized

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social media. So, decentralized communication platform trying

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to incentivize serving of data in, areas where

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you're not, where you're disincentivized through data. So think Non

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Western countries where there's enforced censorship,

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and our goal was trying to serve data in those areas. No. That's

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a massively hard problem, and there's Yeah. So many,

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so many issues with, I mean, consistency and the Cryptographic,

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like, verifiability of that data that, we we were trying

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to solve that. And in solving that, we sort of solved this,

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Database use case of building this decentralized database. And we ended up just running with

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that instead because it was much more applicable to, A

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wider variety of applications than just the specific one that we were

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building. And so we spend about the 1st year building that

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social. And then Last, January or February,

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we, or yeah. Last January or February, we transitioned to

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just doing the database specifically. Okay. Well,

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I love the pivoting. I just do. I think that's always a good

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thing to go with. And, you know,

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I've seen many companies kinda go through these phases where

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they'll do exactly what you did. They'll start out trying to solve 1 problem, realize

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there's this other niche That they could really serve.

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And then later, sometimes even expand back out. That

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happens sometimes as well. But I'm old and I've seen a lot

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of companies, so that that kind of

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happens. Well, so we talked about,

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Cuneiform, which is a language. You guys, I guess, invented that?

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Yeah. You know, it's It's it's it's really a DDL

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language. Like, it's not a whole, like, you know, full, full

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language, but it's yeah. It's useful for defining access control. But, yes, that

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was That was an old house. So talking about access

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control, I know one of the, you know, one of the challenges to that

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is Row level or even cell level, you

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know, the access control. How how fine a grain do

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y'all go to? It's a great question. So, there's sort

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of 2 things I can touch on there. So the answer is technically

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both. So, with Quill, or with with Cuneiform, we

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have this concept of actions. And action, you

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can sort of think of it like a function that Anybody can call. It's like

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a it's an RPC call that anybody can call or you can set rules for

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who's able to call it, and it executes some query against the database. So

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this can be an insert statement. It can be a select statement. And so you

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might have a select statement that is able to get some users

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data, and maybe from May maybe it gets some data from a

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few rows and retrieves a couple of the columns within that row. And so in

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that way, you can sort of make custom access control for columns.

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And then another thing we have and, let me know if this doesn't make sense

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because this is a bit more of, like, a web three native concept.

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But we have we call it a caller modifier. And so what this is

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is that when you're interacting with Quill, you have a key pair, and

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this is how we do User identification. And

251
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so, when you are using, when you're using this key pair,

252
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it takes the address of that sort of thing like a public key On

253
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that, either you're signing your, your your your insert statement with

254
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or your update or your select or anything else. And it can

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use that Public identifier as a

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parameter in an action. So, let's say we have an

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application that is storing a list of user data. Let's say let's say it's

258
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just storing your your name and your age and you're identified

259
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by your by your key pair. You might only be able to go

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and update the row where the, where the

261
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caller matches your key pair. And so that means that You and Frank

262
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can both have rows in the same database, but only you are able

263
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to update yours. Only he is able to update his. You can also set access

264
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control restrictions on Who is able to read from which ones?

265
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Okay. Does that make sense? It does. That's a great example.

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And, you know, especially using, like, customers slash

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people table. And I I I'm I'm

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impressed by the answer itself. I mean, that's that's a hard problem

269
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to solve as well. So, and doing that and then

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when we talk about user access, is this something that is

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designed for use? Obviously, it's happening between

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companies. You talked about competitors. Is this is this

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setting in the wild Or are there, you know, ports open to the

274
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big bad web? Sorry. Could could you restate that

275
00:17:09,855 --> 00:17:13,289
question? I think I might have misheard you. That's okay. So I know you mentioned

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that, the database and the access control controls access

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between, competing entities, maybe companies that

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compete with each other, But they wanna share some portion of data.

279
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So I'm wondering, does is Quill hosted in such a way

280
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that it can be accessed From the, you know, the web at

281
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large, the entire interweb or Internet rather. I said

282
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interweb. I was thinking that and going, don't say it. Don't say it.

283
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The entire Internet. And and and if

284
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so, you know, what are your concerns about

285
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security? Yeah. So that's a great question. So,

286
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once again, this does sort of come back to the the 2 prongs of,

287
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Cuniform access control and then Mhmm. General network

288
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access control for your database. So cuneiform access control, you can

289
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sort of think of this like a rest API where, they they can you

290
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know, It's a client server architecture and anybody can make

291
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calls to the actions you have defined. So maybe it's get the

292
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Get the most recent, you know, record inserted into the database,

293
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or in into a table. May maybe that's an action you have and anybody can

294
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call that and get the most recent record. And so in that way,

295
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you have, I mean, configurable access control. So you

296
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can make that totally public where anybody's able to access that. You can also

297
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make it so only a specific white list of individuals

298
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that you want are able to access that. And right now, how we identify those

299
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individuals is with Key pairs. So,

300
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now we're not specifically tied to the key pair structure. This is just,

301
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it it's really just what our, early clients have needed, and so that's why we

302
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use key pairs for, user authentication. And

303
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then getting To, like, the general because you had

304
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also asked about, people, just anyone in the Internet being able to access

305
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this data. This gets a lot more into network

306
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deployment topology. And so with this, you might have

307
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a database network Where you know everybody that's running these, you

308
00:19:14,789 --> 00:19:18,630
know, the infrastructure for it, and they are running that closed. So, you know,

309
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like a private Postgres or, you know, MySQL server,

310
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nobody like, you are the only ones that are able to access that or you

311
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know everybody who's able to access it. But on the on the I guess

312
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the flip side of that, you can also Run a version where anybody

313
00:19:33,380 --> 00:19:37,140
can come and hook into your data, and it doesn't really cost you anything

314
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extra. So the white list in that case would just be

315
00:19:40,500 --> 00:19:44,085
everyone? Yeah. So, I I think a a

316
00:19:44,085 --> 00:19:47,525
useful way to think about it would be in that case, everybody is able to

317
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see the logs that are coming into your database. So Mhmm. You

318
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know, we have the the actual consensus layer. So we don't use wrap. You

319
00:19:55,110 --> 00:19:58,255
can sort of think of it like a wrap consensus layer. And then below that,

320
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we actually have the data storage. So, they can

321
00:20:01,775 --> 00:20:05,455
essentially come and be a part of that consensus layer. Maybe they can

322
00:20:05,455 --> 00:20:09,029
only, read from it, But, they can come and read from these logs

323
00:20:09,029 --> 00:20:12,570
before they're executed on the database. When you use Q2Form,

324
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that is defining access control for them coming and accessing your

325
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database. They can't see all of the logs. Does that make sense?

326
00:20:20,135 --> 00:20:23,575
It does. And it's a interesting and and very powerful

327
00:20:23,575 --> 00:20:27,390
sounding, paradigm that you've That you've surfaced there. And

328
00:20:27,390 --> 00:20:31,010
it's not that I'm not throwing off on traditional relational databases

329
00:20:31,150 --> 00:20:34,210
when I say that. It's, almost like a combination

330
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of What you would expect from relational databases

331
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or maybe even NoSQL databases, but built

332
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on top of that is a little bit more beef In the

333
00:20:45,660 --> 00:20:49,340
access control space. And that, you know, has

334
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typically been the, kind of the purview of the application

335
00:20:53,180 --> 00:20:56,845
developers. They manage that part. And it sounds like you've

336
00:20:56,845 --> 00:21:00,465
baked that right into your, your database control.

337
00:21:00,605 --> 00:21:04,450
So I I like that a lot. They're part of it.

338
00:21:04,590 --> 00:21:08,110
It's a really interesting trade off because, you know, a lot of early

339
00:21:08,110 --> 00:21:11,375
databases and this is true for, I would say, you know, I mean, Most major

340
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ones, I believe SQL Server, but I know Oracle, MySQL, and

341
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Postgres, they have baked in user access control that most people don't

342
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really use. Most people actually go for access control, you know, at

343
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their on, like, their API layer. Mhmm. But for

344
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our case, because of the unique Environments that this is being used into, we

345
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need to bake an access control logic in a different way than these

346
00:21:33,395 --> 00:21:36,995
databases already do, but we need to bake that in directly to the data

347
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itself. And that is what allows us to sort of open up

348
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new use cases that previously were not possible. Go ahead.

349
00:21:44,390 --> 00:21:47,935
Again, sounds very Powerful. And, I imagine

350
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business is growing. Yeah. Yeah. It's going quite

351
00:21:51,695 --> 00:21:55,049
well. That's that's excellent to hear. I always,

352
00:21:55,690 --> 00:21:59,130
I enjoy hearing success stories. They, they inspire me as

353
00:21:59,130 --> 00:22:02,350
well. Gosh. I'm trying to think of

354
00:22:03,595 --> 00:22:07,115
Some more stuff about it. I got I got my head around the basics, I

355
00:22:07,115 --> 00:22:10,554
think, but it's gonna be I know me. It's gonna be, like, 8 o'clock tonight.

356
00:22:10,554 --> 00:22:14,220
I'm gonna go, I should ask him this. It's

357
00:22:14,220 --> 00:22:17,980
all good. Yeah. I think you're running this 1 this 1 solo without Frank right

358
00:22:17,980 --> 00:22:21,275
now. So Well, yeah. And Frank thinks, So Frank thinks differently,

359
00:22:22,135 --> 00:22:25,175
than I do. We're we both started as,

360
00:22:25,575 --> 00:22:28,555
developers and then we moved into data.

361
00:22:29,190 --> 00:22:32,789
And in Frank's case, I had to beg him for about 10

362
00:22:32,789 --> 00:22:36,309
years to get him to go into data, specifically business

363
00:22:36,309 --> 00:22:39,755
intelligence, Because Frank is an artist at heart,

364
00:22:40,135 --> 00:22:43,895
so he already does pretty pictures, you know, and I still can't color in

365
00:22:43,895 --> 00:22:47,510
the lines. So I was like, you can do this whole analytics thing,

366
00:22:47,510 --> 00:22:51,350
Frank. You've got a good eye for it. And he got there. It was

367
00:22:51,350 --> 00:22:54,495
just he kinda Came around it at a different way. And he's told me about

368
00:22:54,495 --> 00:22:58,095
a 100 times, you were right. Should've done that years

369
00:22:58,095 --> 00:23:01,750
ago. But, And he's a he he

370
00:23:01,830 --> 00:23:05,669
because of the way he thinks, it's it's different than the way that I

371
00:23:05,669 --> 00:23:08,789
think. I kind of approach I don't know. I'm not saying right or wrong. I'm

372
00:23:08,789 --> 00:23:12,285
not Comparing and contrasting. It's just different.

373
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And and I work with a number of people in in different fields where

374
00:23:16,900 --> 00:23:20,660
It's it's very productive to work with. Frank's as a Frank's more of

375
00:23:20,660 --> 00:23:24,500
a data scientist, but he's also a data engineer. He's old school data

376
00:23:24,500 --> 00:23:28,154
science. And I I work, of course, I

377
00:23:28,154 --> 00:23:31,835
work well with him. We were we were friends before we started working together. And

378
00:23:31,835 --> 00:23:35,660
then, a handful of database administrators, I

379
00:23:35,660 --> 00:23:39,420
find it because I whenever I see a problem that needs to be solved,

380
00:23:39,420 --> 00:23:43,125
my developer roots are my first response. That's my knee jerk.

381
00:23:43,285 --> 00:23:47,045
Let's go write some code, you know, to do this in some language and try

382
00:23:47,045 --> 00:23:50,825
and figure it out that way. And my DBA friends are all, well,

383
00:23:51,070 --> 00:23:54,590
You know, we can store some business logic here in a view or a store

384
00:23:54,590 --> 00:23:58,429
procedure and access it that way. And it's it's it's

385
00:23:58,429 --> 00:24:02,014
a different approach. I but I'm You know, I know enough

386
00:24:02,014 --> 00:24:05,855
about both to be dangerous, I'd say. And that's why I'm I'm very it's

387
00:24:05,855 --> 00:24:09,534
very appealing to me. I I've done a little bit of web work, there

388
00:24:09,534 --> 00:24:13,330
for a while. Not not in your

389
00:24:13,330 --> 00:24:16,870
league. I built a website that began to get a little popular

390
00:24:17,410 --> 00:24:20,695
and I hired a web developer to take a look at it

391
00:24:21,735 --> 00:24:25,255
And he looked at it. He cut he his first response to me was, this

392
00:24:25,255 --> 00:24:28,830
looks like an engineer built it. And I'm like, I am an

393
00:24:28,830 --> 00:24:32,510
engineer. That's I thought I took it as a compliment. You laughed because you know

394
00:24:32,510 --> 00:24:35,945
it's not a compliment. Yeah. It's interesting.

395
00:24:36,164 --> 00:24:39,765
We I kinda suffer from the same thing. You know, very very

396
00:24:39,765 --> 00:24:43,370
engineering focused. We have a very engineering focused culture. Like, everyone at our

397
00:24:43,370 --> 00:24:46,670
company writes code, even the guy that does our finances and payroll.

398
00:24:47,130 --> 00:24:50,810
Wow. Everybody here is now in different amounts,

399
00:24:50,810 --> 00:24:54,595
obviously, but Sure. Everyone writes code, and so when it gets to a bit

400
00:24:54,595 --> 00:24:58,115
more of the creative side, I I don't wanna say

401
00:24:58,115 --> 00:25:01,720
we we struggle there, but it's where we have struggled a bit in It's something

402
00:25:01,720 --> 00:25:05,240
we've gotten quite a bit better at. But, yeah, we you can tell our

403
00:25:05,240 --> 00:25:09,080
applications were built by engineers. They're it might not be the prettiest

404
00:25:09,080 --> 00:25:12,505
thing in the world, but they're they're very Pragmatic. Yeah.

405
00:25:12,505 --> 00:25:16,264
Absolutely. So And and see, I don't even notice, when I

406
00:25:16,264 --> 00:25:19,780
see things like that. I don't I don't even notice them. But Frank's back so

407
00:25:19,780 --> 00:25:23,540
we have to stop talking. Well, talking bad about him. We can talk about him

408
00:25:23,540 --> 00:25:27,385
still but we only have to say the good things. Welcome back, Frank. That's

409
00:25:27,385 --> 00:25:31,225
funny. Thank you for your patience. One of these days, I will explain all

410
00:25:31,225 --> 00:25:34,659
of this publicly to our listeners and And whatnot, but,

411
00:25:35,059 --> 00:25:38,899
there's a good reason for my absence there. Yeah. No.

412
00:25:38,899 --> 00:25:41,779
I heard about, it it I heard this funny thing, and this is how Andy

413
00:25:41,779 --> 00:25:45,095
and I met where, you know, you You said these apps look like they're written

414
00:25:45,095 --> 00:25:48,935
by engineers. And that's kind of this back and forth

415
00:25:48,935 --> 00:25:52,620
Andy and I have about, like, Design and whatnot.

416
00:25:52,679 --> 00:25:56,360
So Rank food designer. Yeah. So Brennan

417
00:25:56,360 --> 00:26:00,059
was explaining to me that everyone at Quill codes.

418
00:26:00,755 --> 00:26:04,054
Really? Even the even the finance people. Interesting.

419
00:26:04,434 --> 00:26:07,635
Well, Fortis, we're we're a 7 person team. You know, it's not like we're a

420
00:26:07,635 --> 00:26:10,940
we're a huge company. But, yeah. Everybody I mean,

421
00:26:12,039 --> 00:26:15,640
everybody knows how to code and writes some amount of code.

422
00:26:16,039 --> 00:26:19,055
They might not have done that when they came in, but they they picked it

423
00:26:19,055 --> 00:26:22,735
up in one way or another. How do people react to that? Do they like

424
00:26:22,735 --> 00:26:26,355
the idea, or do they kinda bristle? Or you tell them in the interview

425
00:26:26,440 --> 00:26:30,279
That, hey. We're doing this. So it's interesting. We it's

426
00:26:30,279 --> 00:26:33,320
not like we hire people, like, yeah. You will learn to code when you come

427
00:26:33,320 --> 00:26:36,745
here. It it's almost just an inevitability. We're we're solving a very

428
00:26:36,745 --> 00:26:40,424
technical product for a very technical group of users. Right. And

429
00:26:40,424 --> 00:26:44,190
so it's sort of inevitable that, you know, you're you're gonna learn how to

430
00:26:44,269 --> 00:26:47,870
How to code to some extent, working in that job,

431
00:26:48,029 --> 00:26:51,470
really no matter what, like, what role you have. And so it it's not like

432
00:26:51,470 --> 00:26:54,955
a hard fast rule. We have the company where you to learn how to code.

433
00:26:55,455 --> 00:26:58,894
It just it inevitably has happened every

434
00:26:58,894 --> 00:27:02,680
time. So Interesting. Yeah. And Frank, the

435
00:27:02,760 --> 00:27:06,440
I'll give you my understanding of a synopsis of of

436
00:27:06,440 --> 00:27:09,180
what what their database does.

437
00:27:09,960 --> 00:27:13,765
It's It's like a relational database, but built

438
00:27:13,765 --> 00:27:17,525
into it is this user access control. And

439
00:27:17,525 --> 00:27:21,250
it's, like, coupled, to that to the extent that they

440
00:27:21,250 --> 00:27:25,010
can do not only row level, but row column level security and

441
00:27:25,010 --> 00:27:28,145
access control. Interesting. How do I do, Brennan?

442
00:27:28,685 --> 00:27:32,165
Yeah. No. I I'm I I I think that's good for a high level overview.

443
00:27:32,165 --> 00:27:35,480
I think it's good for a high level. But I'm happy to sort of jump

444
00:27:35,480 --> 00:27:39,100
into any of the specifics that you'd like, Frank. So

445
00:27:39,159 --> 00:27:42,575
so tell me, How do you

446
00:27:43,615 --> 00:27:46,735
how does that work? You do role level control or cell level control? Is it

447
00:27:46,735 --> 00:27:49,955
is it role based access control, attribute access control,

448
00:27:50,370 --> 00:27:52,950
Some combination? Yeah. So,

449
00:27:54,289 --> 00:27:58,005
kind of neither. So, we do authentication with key pairs. So

450
00:27:58,165 --> 00:28:01,685
anybody who wants to use a database, they have to have a, a public

451
00:28:01,685 --> 00:28:05,225
private key pair, like an e c v e c d s a key pair.

452
00:28:05,650 --> 00:28:09,330
And you can set rules for what keys are

453
00:28:09,330 --> 00:28:13,155
able to do what in your database. And and so we have

454
00:28:13,155 --> 00:28:16,835
our own language for defining this. We call it cuneiform. It's

455
00:28:16,915 --> 00:28:20,755
cuneiform was the first ever written language. We thought that might be fitting

456
00:28:20,755 --> 00:28:24,429
for our our language. And so our language, it's a it's a DDL language.

457
00:28:24,429 --> 00:28:28,190
So, it sort of specifies the structure for your database,

458
00:28:28,190 --> 00:28:31,250
and then all of your DML is done with, SQL.

459
00:28:31,865 --> 00:28:35,705
But, with this DDL language, you can specify what

460
00:28:35,705 --> 00:28:38,904
we call actions, and you can sort of think of these like RPC calls or

461
00:28:38,904 --> 00:28:42,290
functions Where, they they're gonna execute some

462
00:28:42,290 --> 00:28:45,890
DML against the underlying database. So this could be an

463
00:28:45,890 --> 00:28:49,695
insert or an update or a delete or it can be a select. And you

464
00:28:49,695 --> 00:28:53,455
can set all these interesting rules for who is able to do this, when

465
00:28:53,455 --> 00:28:56,975
they're able to do this, do they have to transfer some sort of

466
00:28:56,975 --> 00:28:59,820
value and able to do this Either once or every time they do it,

467
00:29:00,940 --> 00:29:04,620
or do they have to have, some role that applies to them that

468
00:29:04,620 --> 00:29:08,255
allows them to do this? And, You know, since we're able to identify

469
00:29:08,255 --> 00:29:12,014
people by their key pair, when Andy comes in and uses

470
00:29:12,014 --> 00:29:15,510
and, you know, interacts with the database, I can tell that he is distinctly different

471
00:29:15,590 --> 00:29:19,350
from you, and I know what Andy is allowed to do. And there's even

472
00:29:19,350 --> 00:29:23,095
a small amount of programmability that can be fit into that. So, you

473
00:29:23,095 --> 00:29:26,535
know, when Andy is hitting one of those actions or RPC

474
00:29:26,535 --> 00:29:30,260
calls, that might give him, results or

475
00:29:30,260 --> 00:29:33,220
allow him to do certain things that you would not be allowed to do if

476
00:29:33,220 --> 00:29:36,360
the database is configured that way. Interesting.

477
00:29:37,435 --> 00:29:41,195
Interesting. So you have really fine grained control over what who can

478
00:29:41,195 --> 00:29:44,955
do what? Yeah. You know, I I might hesitate to

479
00:29:44,955 --> 00:29:47,650
say Fine grained because it's

480
00:29:48,510 --> 00:29:52,270
it it is fine grained. You can really set whatever, however you

481
00:29:52,270 --> 00:29:56,095
can think to specify what someone can do in SQL, you can you

482
00:29:56,095 --> 00:29:59,855
can really do that with access control. But we don't implement

483
00:29:59,855 --> 00:30:03,350
it with a fine grained approach. I think a lot of the time, databases that

484
00:30:03,350 --> 00:30:05,850
are really trying to iterate on the access control front,

485
00:30:06,710 --> 00:30:10,390
they they get really into row and column level

486
00:30:10,390 --> 00:30:13,304
access. And that's not quite what we do.

487
00:30:13,945 --> 00:30:17,465
We sort of see our role as, you know, an iterating for access

488
00:30:17,465 --> 00:30:21,210
control on 2 different layers. The first one is on the actual consensus

489
00:30:21,269 --> 00:30:24,570
layer. So, you know, if you think in a traditional data system, this is where

490
00:30:24,710 --> 00:30:28,549
your raft consensus logs are are sitting before they get executed on your data

491
00:30:28,549 --> 00:30:32,265
layer. We don't use Raft, but, so that is the

492
00:30:32,265 --> 00:30:35,705
1st place where we able to have access controls. So this is, you know, network

493
00:30:35,705 --> 00:30:39,029
wide access control, Who can read what data coming in?

494
00:30:39,330 --> 00:30:43,010
And then secondly, we define, and this is for more

495
00:30:43,010 --> 00:30:46,685
client server access control, or for people that are trying to

496
00:30:46,685 --> 00:30:50,525
read from the database, at any point in time, but you can think of

497
00:30:50,525 --> 00:30:53,805
this I don't wanna say like a REST API, but a little bit more like

498
00:30:53,805 --> 00:30:57,310
a REST API than traditional database where you can have

499
00:30:57,310 --> 00:31:01,070
preset queries and, preset functionality that

500
00:31:01,070 --> 00:31:04,254
certain people are able to do or Certain groups of people are able to do

501
00:31:04,254 --> 00:31:07,934
in certain instances. But the ways

502
00:31:07,934 --> 00:31:11,450
that you can combine these things, You can you can you can

503
00:31:11,450 --> 00:31:15,290
combine it to do very granular access control, but that's not really where

504
00:31:15,290 --> 00:31:19,105
we attack the problem. Where did you get the idea for this?

505
00:31:19,105 --> 00:31:22,785
Because this is fascinating. Yeah. So it's interesting.

506
00:31:22,785 --> 00:31:26,200
It's been a little bit of a of a of a ride. So,

507
00:31:26,440 --> 00:31:29,580
we started by building a a decentralized

508
00:31:30,039 --> 00:31:33,020
communication platform. So really trying to incentivize,

509
00:31:34,305 --> 00:31:37,905
serving data in places where you're otherwise disincentivized. So

510
00:31:37,905 --> 00:31:41,665
think non Western countries where there's enforced censorship or IP

511
00:31:41,665 --> 00:31:45,220
blocking. How can we incentivize people to use things

512
00:31:45,220 --> 00:31:48,980
like HTTP tunnels to, spread data? Not

513
00:31:48,980 --> 00:31:52,585
really hard to build a business on that. And so sort of how we

514
00:31:52,585 --> 00:31:56,185
iterated from there was we took the data infrastructure for that, and we started

515
00:31:56,185 --> 00:32:00,025
providing that as a stand alone service. And this is actually where the access control

516
00:32:00,025 --> 00:32:03,580
part of this Really interesting. We started talking to a

517
00:32:03,580 --> 00:32:07,420
lot of projects that, you know, they're building some sort

518
00:32:07,420 --> 00:32:11,145
of data store. They have some data intensive application, but they're not

519
00:32:11,145 --> 00:32:14,825
looking to build that as a data moat. They're looking to build that as a

520
00:32:14,825 --> 00:32:18,505
composable, you know, data building block that other applications are

521
00:32:18,505 --> 00:32:22,080
able to directly import. Just like how you import a line of code or, you

522
00:32:22,080 --> 00:32:25,520
know, a package of code into your application, you should be able to do that

523
00:32:25,520 --> 00:32:29,039
with data as well, assuming you you're applying to all the different access

524
00:32:29,039 --> 00:32:32,585
controls. And so what we're helping a lot of customers do

525
00:32:32,585 --> 00:32:36,284
now is they can take their different datasets and,

526
00:32:36,664 --> 00:32:39,880
people whether they're collaborators, clients, or competitors,

527
00:32:40,340 --> 00:32:44,100
they can use that data in the ways that, that that

528
00:32:44,100 --> 00:32:47,160
the, you know, originator the original data creator specifies.

529
00:32:48,174 --> 00:32:52,015
And then also they can set interesting mechanisms for how value accrues

530
00:32:52,015 --> 00:32:55,695
back to them. But it's really just been a process of

531
00:32:55,695 --> 00:32:59,490
iteration from, You know, that initial idea of building shared

532
00:32:59,490 --> 00:33:03,090
data stores and then, building more complex access

533
00:33:03,090 --> 00:33:05,029
control mechanisms on top of that.

534
00:33:06,924 --> 00:33:10,605
Does that make sense? No. It makes a lot of sense. It's a fascinating it's

535
00:33:10,605 --> 00:33:14,210
just fascinating, because every time you think that we've we've we've Kind

536
00:33:14,210 --> 00:33:18,050
of solved all the problems, particularly in the in the in the

537
00:33:18,050 --> 00:33:21,810
data storage, in the data querying side of things. There's a whole new

538
00:33:21,810 --> 00:33:25,095
layer that gets on call unfolded, and There's just enormous

539
00:33:25,315 --> 00:33:29,075
opportunity, and, it's really cool because, like, I'm reading your bio, and, like,

540
00:33:29,075 --> 00:33:32,675
you were still in school when you started this company, like, that's and you you

541
00:33:32,675 --> 00:33:36,330
started Your first company when you were 16, and you had

542
00:33:36,330 --> 00:33:40,009
15 you had 15 employees before you even go on 15 or

543
00:33:40,009 --> 00:33:42,909
16 employees before you even go on to college, man. That's that's impressive,

544
00:33:43,745 --> 00:33:46,865
I have to say. Yeah. I mean, I appreciate it. It's honestly just been a

545
00:33:46,865 --> 00:33:49,424
lot of being in the right place at the right time. Not my first company.

546
00:33:49,424 --> 00:33:53,050
It was not a tech company. It was Digging holes and, cutting

547
00:33:53,050 --> 00:33:55,630
down trees and digging up bushes in Idaho.

548
00:33:56,890 --> 00:34:00,445
But that was that was my first company. And then this

549
00:34:00,445 --> 00:34:03,805
one, I started, during COVID on a gap year, from

550
00:34:03,805 --> 00:34:06,785
college. But Very cool. It's honestly just been,

551
00:34:07,970 --> 00:34:11,329
Being in the right place at the right time and, doing something that people find

552
00:34:11,329 --> 00:34:14,929
interesting. That is so cool. I mean, like, you think

553
00:34:14,929 --> 00:34:18,525
about the last couple years, A lot of people would say, oh, it's a terrible

554
00:34:18,525 --> 00:34:22,125
time to start a business, but we've seen a couple of instances where it's actually

555
00:34:22,125 --> 00:34:24,844
turns out to be a really good, like we talked to a bunch of folks,

556
00:34:24,844 --> 00:34:28,139
some, So probably by the time this goes out, the shows will be out, but,

557
00:34:28,139 --> 00:34:31,980
like, this whole there's this whole opportunities that I think are

558
00:34:31,980 --> 00:34:35,475
just popping up left and right because of data, Because of AI,

559
00:34:35,535 --> 00:34:39,375
because of, you know, distributed applications and stuff like

560
00:34:39,375 --> 00:34:43,030
that. There's just it it's We're gonna look back on the

561
00:34:43,270 --> 00:34:46,730
as these as the good old days of entrepreneurship and and opportunity.

562
00:34:47,830 --> 00:34:51,284
Yeah. Hopefully. And and, you know, I I I would say that is actually,

563
00:34:51,685 --> 00:34:55,364
like this the last, year, maybe

564
00:34:55,364 --> 00:34:58,800
18 months has been probably the only time where we could have

565
00:34:58,800 --> 00:35:02,400
started a a, a product like this. So

566
00:35:02,400 --> 00:35:05,985
particularly in the growth of web 3. A lot of our beachhead markets

567
00:35:05,985 --> 00:35:09,525
are sort of bridging that gap from, the traditional

568
00:35:09,745 --> 00:35:13,460
space to web 3. We find a A lot of

569
00:35:13,520 --> 00:35:17,119
our initial partners, they have a lot of their clients are

570
00:35:17,119 --> 00:35:20,820
based in the traditional world, but their data engineering problems

571
00:35:20,880 --> 00:35:24,485
are uniquely solved by what is provided in web 3. And

572
00:35:24,485 --> 00:35:28,245
there's enough demand for this, for our specific solution to

573
00:35:28,245 --> 00:35:31,920
to warrant a product. You know, it's only really existed in the last,

574
00:35:32,320 --> 00:35:36,160
year or so. And so yeah. I you know, whether

575
00:35:36,160 --> 00:35:39,605
or not this is a good time to start a business, I would say, 1,

576
00:35:39,605 --> 00:35:42,885
I don't know, but also, I don't think, I I care too much. Like,

577
00:35:43,765 --> 00:35:47,610
the need for what we are doing has really only just started existing, But it

578
00:35:47,610 --> 00:35:51,450
very clearly does exist, and that's that's something that's pretty exciting

579
00:35:51,450 --> 00:35:55,135
about it. So you said web 3, and I It's interesting

580
00:35:55,135 --> 00:35:58,815
because when when most people think of web 3, they think, they

581
00:35:58,815 --> 00:36:02,655
think blockchain. Right? And thanks to SPF that is kind of

582
00:36:02,655 --> 00:36:06,260
cratered, I would say, although I I I am still don't

583
00:36:06,340 --> 00:36:10,040
the crypto kids better not hate on me, like, I'm still a believer in blockchain

584
00:36:10,100 --> 00:36:13,695
as a whole, as as an idea. I don't think I think currency is only

585
00:36:13,695 --> 00:36:17,135
one of the things that you can do with it. And

586
00:36:17,135 --> 00:36:20,895
2, the the the metaverse. Right? And obviously, I think the

587
00:36:20,895 --> 00:36:24,609
metaverse, Obviously Facebook is stumbling on it like but

588
00:36:24,609 --> 00:36:28,049
but it's interesting that the data portion of it is probably more

589
00:36:28,049 --> 00:36:31,845
relevant than any of the other 2 and you don't hear the negative press about

590
00:36:31,925 --> 00:36:34,965
Kind of this distributed data stores in into the,

591
00:36:36,965 --> 00:36:40,579
I I just interesting. I think that you're part of the web 3. Have

592
00:36:40,579 --> 00:36:44,180
you found that the labeling yourself part of web 3 has been a,

593
00:36:44,980 --> 00:36:48,734
has turned from a positive to a negative, basically? Yeah.

594
00:36:48,734 --> 00:36:52,575
I think so. Yeah. You know, some people, they might get

595
00:36:52,575 --> 00:36:55,295
kinda turned off on it. You know, you might talk to a candidate, and when

596
00:36:55,295 --> 00:36:58,950
we say we're because we do classify ourselves as a web 3 company.

597
00:36:59,170 --> 00:37:02,930
Right. And when we say that, they're like, oh, like, you know,

598
00:37:02,930 --> 00:37:06,595
I I don't really believe in that cryptocurrency stuff. And I I I

599
00:37:06,595 --> 00:37:09,735
think that's fine, but I don't think web 3 is cryptocurrency.

600
00:37:10,275 --> 00:37:14,035
Right. I mean, web 3 is a new type of distributed application

601
00:37:14,035 --> 00:37:17,350
or distributed databases, honestly. We do,

602
00:37:18,070 --> 00:37:21,770
I I I would say not just distributed, permissionless. Decentralized

603
00:37:22,230 --> 00:37:26,075
Mhmm. List. That makes sense. With Web 3 applications were able

604
00:37:26,075 --> 00:37:29,835
to relax a lot of the trust assumptions that are

605
00:37:29,835 --> 00:37:33,490
made in other applications, in particular trust assumptions Between

606
00:37:33,490 --> 00:37:36,070
the client and the server. And so

607
00:37:36,850 --> 00:37:40,630
that's like, just forget about cryptocurrency and the metaverse

608
00:37:40,795 --> 00:37:44,635
And tokens with dogs on them and everything else, that is what web

609
00:37:44,635 --> 00:37:48,315
3 is. It is relaxing trust assumptions in, you

610
00:37:48,315 --> 00:37:52,079
know, otherwise More traditional, you know,

611
00:37:52,079 --> 00:37:55,380
client server and oh, not in client server, but it's just like general,

612
00:37:55,920 --> 00:37:59,685
computer architecture models. And so that's what we are doing. You

613
00:37:59,685 --> 00:38:02,725
know, I don't really care what the price of cryptocurrency does. I don't own any

614
00:38:02,725 --> 00:38:06,565
cryptocurrency. Right. We're just building, you know, trustless

615
00:38:06,565 --> 00:38:10,230
applications. That's a good way to put it because when you, you know,

616
00:38:10,550 --> 00:38:14,150
you're obviously your company's doing well and and and and you're growing and

617
00:38:14,150 --> 00:38:17,405
and you've had a pretty, you know, good run. Well, so you just said web

618
00:38:17,405 --> 00:38:19,985
3 and I'm like, but but you're doing well.

619
00:38:21,244 --> 00:38:24,845
I was like, but but but then then then then like, you know,

620
00:38:24,845 --> 00:38:27,920
after you That's why I wanted to ask that. Now you explain it. You're right.

621
00:38:27,920 --> 00:38:31,680
Like, web 3 is, you know, it's kind

622
00:38:31,680 --> 00:38:35,435
of like, kinda like Beyonce. Right? Like, nobody hardly anyone remembers

623
00:38:35,515 --> 00:38:39,215
What group she was part of. Right? I think, God, Destiny's Child.

624
00:38:39,435 --> 00:38:42,715
There were like 3 or 4 singers in there. Right? But but, you know, one

625
00:38:42,715 --> 00:38:46,520
of them one of them Has the the the fame and staying

626
00:38:46,520 --> 00:38:50,200
power, the other ones not so much, no disrespect to them, if the

627
00:38:50,200 --> 00:38:54,035
weird off chance that they're actually listening to a show About AI and data

628
00:38:54,035 --> 00:38:57,795
science, but, you know, no. I just it's just interesting, like,

629
00:38:57,795 --> 00:39:01,155
you know, and we think of all these technologies, like, I'm old enough to remember

630
00:39:01,155 --> 00:39:05,000
1 web one o. Right? And all the crazy ideas,

631
00:39:06,020 --> 00:39:09,539
particularly one of them was, you know, downloading Java

632
00:39:09,539 --> 00:39:13,305
applets. Right? Downloading software from The Internet and

633
00:39:13,305 --> 00:39:16,825
running it locally. Right? Well, that's called the app store now, we don't even think

634
00:39:16,825 --> 00:39:20,185
about it. Right? But obviously, there are a lot of things that failed in that

635
00:39:20,185 --> 00:39:23,380
era. Right. Same thing with web 2 point o, we're kind of saw that kind

636
00:39:23,380 --> 00:39:26,740
of come and go, and I think the same is gonna be true here, you

637
00:39:26,740 --> 00:39:30,265
know, like, you know, did we really need, You know, sock

638
00:39:30,265 --> 00:39:33,865
puppets to sell us stuff, you know, sell us dog food. Right?

639
00:39:34,665 --> 00:39:38,400
And but, you know, I remember very early

640
00:39:38,400 --> 00:39:42,240
on there was a startup called, they were all the Java people

641
00:39:42,240 --> 00:39:45,760
who made Java basically, started a company called Castanet or

642
00:39:45,760 --> 00:39:49,265
Rumba, I forget Which one it was. But their big thing was they wanted to

643
00:39:49,265 --> 00:39:52,725
create what we would call an app store, but for applications.

644
00:39:52,865 --> 00:39:56,580
Right? And and that idea Resurface somewhere completely

645
00:39:56,640 --> 00:40:00,480
different and now it's just part of, like, just the daily world we live

646
00:40:00,480 --> 00:40:04,015
in. So it's it's interesting. I think that We always seem to

647
00:40:04,015 --> 00:40:06,515
remember the Hindenburgs of history, but not necessarily

648
00:40:08,655 --> 00:40:12,309
kind of the The the the the stuff that actually does work

649
00:40:12,309 --> 00:40:16,069
out. Oh, absolutely. And I I think that'll be the the case with,

650
00:40:16,230 --> 00:40:20,055
you know, web 3 as well. A lot of the

651
00:40:20,055 --> 00:40:23,735
people, in particular, a lot of the really loud people that we're that we're

652
00:40:23,735 --> 00:40:27,550
operating in web 3, you know, now that the The the prices of things

653
00:40:27,550 --> 00:40:30,270
are down. They've kinda gone on to whatever the next thing it is they're gonna

654
00:40:30,270 --> 00:40:34,109
do to try to make a quick buck. But the people that are building really

655
00:40:34,109 --> 00:40:37,914
useful and interesting things, Most of them will stay around. You know, some of

656
00:40:37,914 --> 00:40:41,535
them will fail. You know, businesses fail. But,

657
00:40:42,075 --> 00:40:45,820
you know, it's something I've noticed, because I was also here when web 3 was

658
00:40:45,820 --> 00:40:49,340
really popular, right, when when working in web 3 was the cool thing to be

659
00:40:49,340 --> 00:40:53,035
doing. And something I've noticed is that The

660
00:40:53,035 --> 00:40:56,715
people that are building actually useful applications and solving actually

661
00:40:56,715 --> 00:41:00,395
hard problems, they're still here. You know, they're not

662
00:41:00,395 --> 00:41:04,060
as loud as the other people that were here Or but that that's fine.

663
00:41:04,060 --> 00:41:07,900
Like, the the actual core problems that we want to

664
00:41:07,900 --> 00:41:11,494
solve are still being solved, and and I I think that there's a lot of

665
00:41:11,494 --> 00:41:13,674
value in solving those problems. And so,

666
00:41:15,174 --> 00:41:18,819
there's less people, but there's a higher concentration of High

667
00:41:18,819 --> 00:41:22,500
quality people building in the space now, and I think that's what matters. Well and

668
00:41:22,500 --> 00:41:26,055
now that it's quieted down some, y'all can get more work done. That

669
00:41:27,395 --> 00:41:31,234
is, very true. That's very

670
00:41:31,234 --> 00:41:34,630
true. Yeah. Which has also been quite

671
00:41:34,630 --> 00:41:38,470
helpful. Well, we are gonna transition, to

672
00:41:38,470 --> 00:41:42,035
the questions part. I hope you got a copy of Questions in advance. If you

673
00:41:42,035 --> 00:41:45,634
didn't, I put them in chat. So if you'd like to, peruse

674
00:41:45,634 --> 00:41:49,394
them. The very first one is, I think you've explained

675
00:41:49,394 --> 00:41:52,400
it, But, it's a it's a softball,

676
00:41:53,260 --> 00:41:56,539
for you. How did you find your way into data? Did,

677
00:41:56,859 --> 00:42:00,545
data find you or did you find data? Yeah.

678
00:42:00,545 --> 00:42:04,145
So I kinda inadvertently found my way into data. So I wanted to

679
00:42:04,145 --> 00:42:07,585
solve this other problem that was present in the messaging

680
00:42:07,585 --> 00:42:11,330
application. And, that really required me to dive I

681
00:42:11,330 --> 00:42:14,610
don't wanna say super deep into data. It required me to dive super deep into

682
00:42:14,610 --> 00:42:18,025
a few things, but it was in building

683
00:42:18,025 --> 00:42:21,385
infrastructure for that that I found that there there was a real

684
00:42:21,385 --> 00:42:24,745
opportunity if I went and, you know, doubled down and went even deeper into

685
00:42:24,745 --> 00:42:28,370
data. And so, you know, for me, it was really just

686
00:42:28,510 --> 00:42:32,190
kinda looking at, at what the market wanted, you know, when we're

687
00:42:32,190 --> 00:42:35,885
working with design partners and potential customers, What is their feedback? And it

688
00:42:35,885 --> 00:42:39,005
kind of pointed towards going deeper into data. And so that's how I found my

689
00:42:39,005 --> 00:42:42,670
way into it. Nice. Interesting. So what's

690
00:42:42,670 --> 00:42:45,170
your favorite part of your current gig?

691
00:42:46,510 --> 00:42:50,349
So I would say, like, the the team I work with. So our

692
00:42:50,349 --> 00:42:53,265
team is really tight knit. Most teams now are remote.

693
00:42:53,885 --> 00:42:57,645
Almost every startup now is a remote startup, especially in the,

694
00:42:57,645 --> 00:43:01,210
you know, quote unquote web three space. We're in person. So,

695
00:43:01,610 --> 00:43:05,290
you know, the entire team is in the room right next to me. And, honestly,

696
00:43:05,290 --> 00:43:08,250
we're all really close. We all really believe in the problems we're solving. We do

697
00:43:08,250 --> 00:43:11,925
believe we're building a better and more fair Internet. And so that

698
00:43:11,925 --> 00:43:14,965
makes it really fun to work here, you know, even if the hours might be

699
00:43:14,965 --> 00:43:18,539
a little longer than they would be at another job. It's

700
00:43:18,539 --> 00:43:22,299
it's really fun to work here. We all really get along, and, we work well

701
00:43:22,299 --> 00:43:25,965
together. And so that's certainly my favorite part. And you're in Austin now. Right?

702
00:43:26,125 --> 00:43:29,965
We are in Austin. Yeah. Our team is a really thriving tech scene right

703
00:43:29,965 --> 00:43:33,805
now. Yeah. Yeah. If you're if you're young and work in tech, it's the the

704
00:43:33,805 --> 00:43:37,089
place to be. And so it's very Awesome. Awesome.

705
00:43:37,710 --> 00:43:41,070
So we have 3 complete the sentence statements, not really

706
00:43:41,070 --> 00:43:44,369
questions. The first is when I'm not working, I enjoy

707
00:43:44,510 --> 00:43:48,135
blank. Yeah. So I am I'm a

708
00:43:48,214 --> 00:43:51,655
not a I live in Texas, I guess, not as much. But, I'm a really

709
00:43:51,655 --> 00:43:55,480
big skier. So I grew up snow skiing. That's

710
00:43:55,480 --> 00:43:59,079
cool. Yeah. I I'm from Idaho, and so it's kind of a

711
00:43:59,079 --> 00:44:02,694
common thing there. And so, yeah, I did a ton a

712
00:44:02,694 --> 00:44:06,375
ton of skiing growing up. I do, I ski raced. I do backcountry

713
00:44:06,375 --> 00:44:10,135
skiing now. So a lot of, like, hiking, skiing, like, like, avalanche training, stuff

714
00:44:10,135 --> 00:44:13,960
like that. Yeah. I would say that if I, you know, if

715
00:44:13,960 --> 00:44:17,775
I was no longer working, and I I couldn't,

716
00:44:17,775 --> 00:44:19,694
You know, I I love what I do, and I would do it, you know,

717
00:44:19,694 --> 00:44:23,295
even if I wasn't making money doing it. But if I was no longer working,

718
00:44:23,295 --> 00:44:26,250
I would probably go skiing. Very cool.

719
00:44:29,030 --> 00:44:32,250
Another complete the sentence. I think the coolest thing in technology

720
00:44:32,390 --> 00:44:36,055
today is? Yeah. So,

721
00:44:36,595 --> 00:44:38,615
I'm I'm a little torn here. I think either,

722
00:44:41,475 --> 00:44:45,320
permissionless networks. So, I mean,

723
00:44:45,620 --> 00:44:49,300
people usually think of this as cryptocurrency layer ones, but I

724
00:44:49,300 --> 00:44:53,035
think it extends sort of beyond that. But Any network that is permissionless and

725
00:44:53,035 --> 00:44:56,735
allows people to it it functions as as a protocol,

726
00:44:57,115 --> 00:45:00,690
and it doesn't have biases towards individuals. I think that's really

727
00:45:00,690 --> 00:45:04,290
interesting. It has a lot of potential, or SQLite. I really like

728
00:45:04,290 --> 00:45:08,055
SQLite. I think it's a really awesome piece of technology. I know it's

729
00:45:08,135 --> 00:45:11,895
Not exactly the newest thing, but I think it's still of the things I've

730
00:45:11,895 --> 00:45:14,635
worked with, SQLite is really cool. Nice.

731
00:45:15,575 --> 00:45:19,119
Alright. Our last one, I look forward to the day when I can use

732
00:45:19,119 --> 00:45:22,960
technology to blank. Oh, interesting. Interesting

733
00:45:22,960 --> 00:45:23,460
question.

734
00:45:28,075 --> 00:45:31,755
I think for me, I I'm really looking forward

735
00:45:31,755 --> 00:45:35,515
to being able to use and I I I think we're we're almost

736
00:45:35,515 --> 00:45:38,270
there. But being able to use,

737
00:45:39,290 --> 00:45:43,050
AI programming to help us write unit tests and get full

738
00:45:43,050 --> 00:45:46,895
context of our code base, I've been using GitHub Copilot

739
00:45:47,035 --> 00:45:50,555
for, I think, maybe 9 months now, 8 months now, and it's

740
00:45:50,555 --> 00:45:54,370
honestly changed my life. It's I don't know if you guys have

741
00:45:54,370 --> 00:45:58,210
used GitHub Copilot. Would highly recommend trying it. It

742
00:45:58,210 --> 00:46:01,875
has just my productivity has skyrocketed. And

743
00:46:01,875 --> 00:46:05,715
now it's only able to handle a fairly small set of context. Like,

744
00:46:05,715 --> 00:46:08,755
I believe it only has context for the file or maybe a couple of the

745
00:46:08,755 --> 00:46:12,350
most recent files you've worked in. But, you know, there

746
00:46:12,350 --> 00:46:16,190
there have been a couple, demo models, and, unfortunately, they're in private beta

747
00:46:16,190 --> 00:46:19,775
right now. But where there are AI AI models that

748
00:46:19,934 --> 00:46:23,694
can help you generate unit tests, and they can read through an entire

749
00:46:23,694 --> 00:46:27,474
package of code you've written and see, oh, you might have a security vulnerability

750
00:46:27,615 --> 00:46:31,079
here, or, Are you sure you actually meant to expose this in your

751
00:46:31,079 --> 00:46:34,839
public API? Just those are sort of a lot of the foot

752
00:46:34,839 --> 00:46:38,645
guns I still find myself running into. And I think we're almost at the

753
00:46:38,645 --> 00:46:42,345
point where, that that, is is solved.

754
00:46:44,609 --> 00:46:48,450
Wow. Very cool. Would highly recommend trying out Copilot if

755
00:46:48,450 --> 00:46:52,130
you haven't. It's been it's been pretty crazy. I will check it

756
00:46:52,130 --> 00:46:55,905
out. Yeah. I've done a couple of demos with it, you know, just to

757
00:46:56,065 --> 00:46:59,684
it's kinda like, you know, walk through, follow the instructions type stuff.

758
00:47:00,400 --> 00:47:03,839
It's not the same as when you're trying to solve a real a real problem,

759
00:47:03,839 --> 00:47:07,359
real world problem. So I know enough to know that. I was still

760
00:47:07,359 --> 00:47:10,455
impressed, But I haven't yet taken it to that next level.

761
00:47:10,995 --> 00:47:14,835
Yeah. You know, it it's not super useful for writing large blocks

762
00:47:14,835 --> 00:47:17,895
of code. Mhmm. It is useful as autocomplete.

763
00:47:18,309 --> 00:47:21,990
So, I mean, like, a place I use it,

764
00:47:21,990 --> 00:47:25,510
most of our stack is in Golang. Golang has pretty verbose error

765
00:47:25,510 --> 00:47:29,025
handling. It's really helpful with that.

766
00:47:29,425 --> 00:47:33,265
Like, just with that alone, it's doubled my productivity because it pretty much handles all

767
00:47:33,265 --> 00:47:36,600
of the error handling for me. Wow. So That's impressive.

768
00:47:39,860 --> 00:47:40,600
Very cool.

769
00:47:44,455 --> 00:47:48,135
Share something wait. Which question did we

770
00:47:48,135 --> 00:47:51,920
do? Yes. Just share something that's next in that list, But that's

771
00:47:51,920 --> 00:47:55,120
my list, and it may be out of order. No. No. No. It is. Here's

772
00:47:55,120 --> 00:47:58,880
something, different about yourself. But remember, we like to keep

773
00:47:58,880 --> 00:48:01,845
our Itunes, clean rating. Yeah.

774
00:48:04,065 --> 00:48:07,905
Oh, man. That's a that that's I think that's the toughest

775
00:48:07,905 --> 00:48:11,330
one yet. I I had scanned through these

776
00:48:11,330 --> 00:48:15,170
questions before the podcast, but I, I

777
00:48:15,170 --> 00:48:17,110
did not think of this one.

778
00:48:20,595 --> 00:48:24,410
Man, let me think about 1 for a sec. I don't

779
00:48:24,410 --> 00:48:27,849
know. If you don't mind me asking, what would, what would your answers for this

780
00:48:27,849 --> 00:48:31,450
be? And maybe that'll help me come up with something. Oh, I mean, like, one

781
00:48:31,450 --> 00:48:34,775
of 1 of mine was, because we did this on on each other. We should

782
00:48:34,775 --> 00:48:38,535
probably reupdate, Andy. Because I used one of my

783
00:48:38,535 --> 00:48:42,090
first jobs was I was an EMT in the Bronx. Okay.

784
00:48:42,310 --> 00:48:45,610
Yep. And for me, I I have a similar one to Frank.

785
00:48:46,310 --> 00:48:49,865
I played guitar in a country rock band. Okay.

786
00:48:49,865 --> 00:48:51,565
Wow. That's that's really cool.

787
00:48:53,865 --> 00:48:57,005
Oh, man. I already brought up the the skiing thing. That one's tough.

788
00:48:57,890 --> 00:49:00,930
I mean, how did you here's here's 1. I'll help you out. Like, how did

789
00:49:00,930 --> 00:49:04,770
you start a landscaping company? Like like, when you were 16, like, how many 16

790
00:49:04,770 --> 00:49:08,035
year olds do you know that just say, you know what? I'm gonna, Like, how

791
00:49:08,035 --> 00:49:11,875
did that happen? Like This is impressive. Sure. Yeah. The the thank

792
00:49:11,875 --> 00:49:15,155
you. I appreciate the help here. No problem. It's,

793
00:49:15,555 --> 00:49:19,380
so I I grew up in Idaho, and we were we're a ways outside of

794
00:49:19,380 --> 00:49:22,260
Boise. And so we had quite a bit of land, and it wasn't, you know,

795
00:49:22,260 --> 00:49:25,765
nice. I mean, it it it built around. It's just like a Great place to

796
00:49:25,765 --> 00:49:29,605
live, but it wasn't like, like like you know, we had to do it

797
00:49:29,605 --> 00:49:33,365
like firebreaks, you know, a lot of irrigation work, things like

798
00:49:33,365 --> 00:49:36,460
that. And so, growing up,

799
00:49:37,000 --> 00:49:40,520
we wouldn't you know, me and my brothers were really young, we had a guy

800
00:49:40,520 --> 00:49:43,080
who would come and help us do that. But as we got older, we started

801
00:49:43,240 --> 00:49:46,984
our family did it ourselves. And he hired me,

802
00:49:46,984 --> 00:49:49,545
and I would just kinda help him as an extra hand. He did this for

803
00:49:49,545 --> 00:49:53,065
people all over. And I just kinda had a realization not that far into the

804
00:49:53,065 --> 00:49:55,770
job. It was like, man, I could definitely do this myself, and I think I

805
00:49:55,770 --> 00:49:59,610
could, you know, probably pay myself a little bit better.

806
00:49:59,610 --> 00:50:03,345
And so I just, I I started small, started

807
00:50:03,345 --> 00:50:06,305
with 1. Like, I didn't immediately quit my job or anything. I did quit my

808
00:50:06,305 --> 00:50:10,145
job fairly quickly. But, I started with a couple small clients

809
00:50:10,145 --> 00:50:13,460
just seeing if it was something I can handle. None of it was rocket science,

810
00:50:13,460 --> 00:50:16,900
and so I figured that out. I started scaling up more

811
00:50:16,900 --> 00:50:20,660
from, like, you know, mowing lawns to fire

812
00:50:20,660 --> 00:50:24,315
breaks And digging in drainage ditches, a little bit of demolition work.

813
00:50:24,315 --> 00:50:27,915
It's just a a bit higher margin. But, yeah,

814
00:50:27,915 --> 00:50:30,940
honestly, just started 1 step at a time. I got 1 client. I got 2

815
00:50:30,940 --> 00:50:34,780
clients, and then I got 10. I had a couple buddies that would

816
00:50:34,780 --> 00:50:38,140
come out and help me. And it was just really you know? As opposed to

817
00:50:38,140 --> 00:50:41,965
a business like like this one where it's, It was very technically focused,

818
00:50:41,965 --> 00:50:45,725
and you're raising VC dollars and things like that. This was, I I

819
00:50:45,725 --> 00:50:48,605
I worked out of a Ford Escape until I could afford a pickup truck. And

820
00:50:48,605 --> 00:50:51,599
then I bought a pickup truck, and then I So it was it was it

821
00:50:51,599 --> 00:50:54,240
was a little bit of a different process. But, yeah, that was kinda how I

822
00:50:54,240 --> 00:50:58,000
got into it. No. That's cool. That is cool. Do you listen to

823
00:50:58,000 --> 00:51:01,605
audiobooks? It's funny. I just saw that question.

824
00:51:01,665 --> 00:51:04,645
I just got an Audible subscription 2 days ago.

825
00:51:05,025 --> 00:51:08,770
Wow. Yeah. One of my coworkers recommended a book to me, And

826
00:51:08,770 --> 00:51:11,410
I don't have a lot of time to actually sit down and read, but I

827
00:51:11,410 --> 00:51:15,109
walk a lot. And so, I got Audible for that. So,

828
00:51:15,490 --> 00:51:19,325
I'm It's a really good book. Would really recommend. It's called

829
00:51:19,325 --> 00:51:23,005
Children of Time. It's like if you're into sci fi Mhmm. It's like a

830
00:51:23,005 --> 00:51:26,630
postapocalyptic sci fi book where, they're humans.

831
00:51:26,630 --> 00:51:30,310
They've they've left Earth, and they're, I I forget how far, but they're

832
00:51:30,470 --> 00:51:34,310
they they've been traveling for, like, 2000 years, and they're now trying to recolonize a

833
00:51:34,310 --> 00:51:37,945
new planet. And it's just sort of all the I

834
00:51:37,945 --> 00:51:41,705
don't wanna spoil too much, but, it's about that. But it it's it's really

835
00:51:41,705 --> 00:51:45,270
good. If you like sci fi, I would highly recommend. I'll check it out.

836
00:51:45,270 --> 00:51:48,330
And, you can check it out too to our listeners.

837
00:51:48,710 --> 00:51:51,990
Audible is a sponsor of the show, and you go to the data driven book

838
00:51:51,990 --> 00:51:55,464
.com Or the data driven book .com depending on how you want to pronounce

839
00:51:55,464 --> 00:51:59,065
it. Andy assures me that that link is

840
00:51:59,065 --> 00:52:01,565
working and, I have my faith in Andy.

841
00:52:02,839 --> 00:52:06,519
It was working a couple of hours ago. We did another recording. It's a

842
00:52:06,519 --> 00:52:10,065
2 recording day, and it's working then. Yeah,

843
00:52:10,065 --> 00:52:12,625
no, no. It could have been, it could have been my setup. Cause I was,

844
00:52:12,625 --> 00:52:16,385
I was doing some weird stuff with DNS to get something else working on. It's

845
00:52:16,385 --> 00:52:19,770
always DNS Frank. It's Always DNS.

846
00:52:21,950 --> 00:52:25,630
So where can people I'm sorry. Go ahead, Andy. That's okay. You you do it,

847
00:52:25,630 --> 00:52:29,385
Frank. I was gonna say the same thing. Where can people learn more

848
00:52:29,385 --> 00:52:33,145
about you and what you're up to? Yeah. So, I mean, the first one is

849
00:52:33,145 --> 00:52:34,765
just our website. So quill.comkwil.com.

850
00:52:38,310 --> 00:52:41,830
I've also got a Twitter. That's probably the easiest way to get to me. So

851
00:52:41,830 --> 00:52:44,970
my Twitter is just my name, so Brennan underscore Lamy.

852
00:52:45,835 --> 00:52:49,595
But you can also find links to Quill's Twitter and inevitably to

853
00:52:49,595 --> 00:52:53,115
to mine as well on our website. So I would say the biggest one is

854
00:52:53,115 --> 00:52:56,800
just go into quill.com. It's probably the easiest.

855
00:52:56,800 --> 00:53:00,640
Okay. Excellent. That sounds good. Yeah. And, any

856
00:53:00,640 --> 00:53:04,424
parting thoughts? No. I don't think so. I mean, really, thank

857
00:53:04,424 --> 00:53:08,025
you thank you all for having me. I it it's hard to find

858
00:53:08,025 --> 00:53:11,720
people that, are as passionate about, you know, weird data engineering problems as I

859
00:53:11,720 --> 00:53:15,400
am, and so it's really been a pleasure. Awesome. We're

860
00:53:15,400 --> 00:53:19,225
happy to talk to other people who are into Data engineering, too. Well, that was

861
00:53:19,225 --> 00:53:22,345
quite the show. Alright. I'll let go of it. It's always good to hear a

862
00:53:22,345 --> 00:53:26,000
good entrepreneur origin story. One last thing

863
00:53:26,000 --> 00:53:29,600
before you go. We know you're busy and we appreciate you

864
00:53:29,600 --> 00:53:33,095
listening to our podcast. But we have a favor to

865
00:53:33,095 --> 00:53:36,234
ask. Please rate and review our podcast on Itunes,

866
00:53:36,454 --> 00:53:40,230
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867
00:53:40,230 --> 00:53:43,450
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868
00:53:44,230 --> 00:53:47,910
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869
00:53:47,910 --> 00:53:50,555
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870
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That means more people listen to us, spreading the joy.

871
00:53:55,815 --> 00:53:59,060
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872
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