00:03:24 · Ruby Justice Thelot, Angela McNea
[00:03:24] S1: Right. So I'm curious, did your time previously at Palantir as an FDE, is that when you started thinking about how do we put these things into production or into real world environments as opposed to just purely having the technology? [00:03:38] S0: Yeah, Maya and I joke a little bit. So my co founder and our CTO, she and I were at Palantir together for four years. So I joined as an FDE and then switched to the product side after about a year, spent the rest of my time there. Maya joined exclusively as a software engineer on the product side. And it's funny, we joke that we were spoiled by solving hard problems because of the types of things, the kinds of problems that we were exposed to and that we were working with. And so when we started our company together, that sort of same ethos, those tenets of, okay, how do we provide the right tools to solve critical problems and power mission critical workflows and agents, that was in our DNA. [00:04:30] S1: I see. Yeah, that makes a lot of sense. So do you find that there were companies that were sort of developing their own in house systems and they were just sort of reinventing the wheel over and over? Or were there B2B companies that were all kind of doing the same thing? What did you see specifically?
00:04:46 · Angela McNea, Ruby Justice Thelot
[00:04:46] S0: We saw kind of two buckets of things. Of like, okay, companies, okay, I want to solve invoice processing, I want to solve procurement automation, I want to solve marketing automation, I want to build my reconciliation flows, whatever it may be, buying individual sort of vertical tools specifically for those things. So you're assembling and your vendor management problem goes pretty wild. And then we were seeing a pattern where companies were like, okay, cool, we've built some really neat things in those individual business units. Why can't we take that and why can't we move them somewhere else? So that was sort of bucket one. And then sort of bucket two is, okay, everyone can be a builder now. That's not a predator, that's exciting. And the nature of software development is changing. But when everyone's a builder and people are creating a lot of these systems, you can build these big capability maps, but the operability of a system is often right, a big challenge. So how do you when you construct and build these, like, sort of, like assembled stacks with all these different pieces, these building blocks, what does it look like when, you know, you change your sort of, like, you know, coding provider behind the scenes, or when this team turns over, or we've, you know, all of a sudden we need to load test this dramatically, and we were seeing a lot of those stacks sort of fall over. [00:06:14] S1: Okay, I see. [00:06:15] S0: So, what is the operability of the system that's created?
00:06:15 · Angela McNea, Ruby Justice Thelot
[00:06:15] S0: So, what is the operability of the system that's created? [00:06:18] S1: Yeah, when did you start to see that this was a problem? I think this was like, you guys raised in 2025? [00:06:24] S0: We raised our A in 2020 Yeah, yeah, So Maya and I left in spring of twenty twenty three. [00:06:34] S1: Early in AI days Our [00:06:38] S0: thesis from the beginning was the glue, the harness, the control, the governance, all of these pieces were going to be important. And it's been fun to sort of watch your hypotheses play out live. And we've always been sort of pragmatists in how we build. We're like, okay, this is a challenge for people now at the best of times and this is just going to be compounded when builder ecosystems grow, model providers expand and grow, you're going have frontier models and sovereign models and local models, it's just going to compound. [00:07:15] S1: Very prescient bet that you guys were making. So I'm very curious about what inspired you to write Every Good Decision is an ensemble. Because we see now, we talk a lot about model routing and how it's very important to have something that can choose what level of model based off of some sort of cost trade off. And then you sort of make the... You zoom out and make the argument that everything has always been this sort of ensemble and not just like one model or entity making decisions. Whether it's how the judicial system works or whatnot. I'm curious, how does that connect to Thread AI?
00:07:54 · Angela McNea, Ruby Justice Thelot
[00:07:54] S0: Yeah. So, again, was seeing this explosion in conversation around routing. And there are real important conversations to be had, we're seeing it with our enterprise customers of like when is it too expensive to use this kind of model or the latency is too high or there are real tradeoffs around the specific nodes. The interesting part to me is that the actual hard part, the technology behind a router, don't think is as interesting as the The hard part is the application around how the business person or the engineering teams decide what is the logic of what models do we pick, what are the things that we're trying to optimize. And then you have to predefine all of the decisions upfront, saying like, okay, well, we've decided that this is what a hard problem is. This is the shape of a hard problem is. We've decided what is expensive. How do you define expensive? Is it expensive in time, in people's time, in money? So you have to predefine all of these like, business and, you know, esoteric and abstract things ahead of time before you even get to, cool, now we just need to, like, something to help me route between these systems. And so, we define, we build our platform so you can build these kinds of routers natively in our product. But we spent a lot of time on those decision gates explicitly and those logic gates because we were seeing like in the real world, those were the actual barriers to putting something in production. [00:09:34] S1: Yeah, I see. I want to
00:09:34 · Ruby Justice Thelot, S2, Angela McNea
[00:09:34] S1: Yeah, I see. I want to Ad[00:09:36] S2: shout out our sponsor, Lovable. You know, the app you've been meaning to build? The internal tool, side project or product you'd otherwise lose a weekend to? With Lovable, you get software you can ship today. That includes an editable code base you can inspect and change, plus two way Git GitHub sync. Lovable also handles the backend and infrastructure, including managed Postgres, auth, storage, hosting, payments, and more, so you don't have to wire it all up yourself. And through Lovable's MCP server, you can create and deploy your project directly from the agents you already use. Turn ideas into software people love with Lovable. Lovable. Dev. Now onto the episode. [00:10:14] S1: So I think, like, you know, the topic of agent failure can be very high stakes Mhmm. Specifically with anything to do with defense or anything to do with national security. [00:10:25] S0: Mhmm. [00:10:25] S1: So I'm curious about your, you know, your, like, defense threat AI and how it helps in defense use cases or defense providers?
00:10:25 · Ruby Justice Thelot, Angela McNea
[00:10:25] S1: So I'm curious about your, you know, your, like, defense threat AI and how it helps in defense use cases or defense providers? [00:10:33] S0: Yeah. Being a dual use company was very important to me and Maya from the beginning. And there's no more demanding customer than the US Department of War, Department of Defense. And our same primitives, same building blocks that we use in those environments are the same that power our enterprise work. And I could talk about sort of from the beginning, Maya and I sought out Hard Problems We Want. Our goal was to help companies and organisations and institutions, like, fix hard problems and help people. So a lot of our work... The one that we sort of talked about publicly recently is we are doing some research with Army DevCom. And a lot of that work is around manual deconfliction. So how do you help people get accurate information at the right time when you're sort of building and maintaining existing systems, control systems, and innovating new ones? So how do you help the scientists, and how do you also help the warfighters on the ground? And again, that's probably one of the most demanding environments I can think of. [00:11:48] S1: Yeah, totally. I mean, I'm just curious if you could paint a picture of the stakes for agent failure in this industry, but also others.