No Priors: Artificial Intelligence | Technology | Startups
00:00:00 · Jake Stauch, Elad Gil, Sarah Guo
[00:00:00] S0: This is the ultimate moonshot in enterprise software. These agents that go off and do work for you and magically discover all your problems and solve all your problems. And I think no one's really figured out how to do this well. [00:00:09] S1: This is kind of the OpenAI hugging face incidents or other things where agents are given a task and then [00:00:13] S0: they do something that's unexpected. The agent becomes pretty competent. They could theoretically just start writing code that could take action on all your systems, and that is an unbounded security risk that I don't think anyone's gonna be able to take anytime soon. On the one hand, you want these to be very autonomous without somebody babysitting babysitting them. Them. On the other hand, autonomy is very scary in the enterprise. Serval is the boundary. Serval is the guardrails. We are the way that a large enterprise with a lot of rules and approvals and process and politics can adopt these tools safely and comfortably at scale. [00:00:48] S2: Hi, listeners. Welcome back to No Priors. Today, Elad and I are here with Jake Stauch, cofounder and CEO of Serval. Serval, with all the speed of the African wildcat, is trying to attack ServiceNow and more broadly bringing the power of cogeneration to IT and enterprise teams overall. Welcome, Jake. [00:01:08] S1: Jake, thanks for joining us today on No Priors. [00:01:10] S0: Thank you. Great to be here. Maybe you could tell us a
00:01:10 · Jake Stauch, Elad Gil, Sarah Guo
[00:01:10] S0: Thank you. Great to be here. Maybe you could tell us a [00:01:13] S1: little bit more about your history and how you started Serval, and what what is the problem that you started with, or why did start working on this to begin with? [00:01:18] S0: Yeah. So background, Serval is enterprise automation, enterprise service management. The idea is you can ask questions and get help at work and automate a lot of the parts of the job you don't enjoy, and we do that through cogen agents. So that's the... What the company does. We compete with companies like ServiceNow, is historically the big legacy provider in the space. I discovered this category actually working at a previous company called Verkada, where we sold enterprise physical security products to IT teams, spent many, many years talking to IT teams, figuring out what to build for them. And one of the things I love to to do with these teams is ask them, what do you spend the most money on, and what do you hate the most? And ServiceNow would top a lot of those lists. And so I was always interested in this category of maybe there's a better solution here, but it wasn't clear for most of my time there how you'd ever beat ServiceNow. They're a great company. They've done so much so well, and why would you be able to compete with them? [00:02:10] S2: What was frustrating for users about it?
00:02:10 · Sarah Guo, Jake Stauch
[00:02:10] S2: What was frustrating for users about it? [00:02:13] S0: I think so hard to build in the platform. So it's a very robust, customizable, powerful platform that can map to all these enterprise workflows fundamentally. It's a workflow automation platform, and so it can do so much, but every idea you have for doing something cool, you have to go and implement, and a lot times you're bringing consultants to implement it. So it's always kind of running six to twelve months behind where you want it to be, and it's fine if you're building something that's gonna last five, ten years, like a big onboarding flow, and nothing about your business is gonna change, so you can invest all that upfront effort, and then it gets deployed, and it works for a while. But for just trying to keep up with all the automation that you wanna build, ServiceNow is not able to catch up. And and then it's very expensive, and it keeps getting more expensive over time, so that frustration of it's not keeping up with where I wanna go as a business, and it keeps getting more expensive, that's what was driving a lot of the frustration.
00:02:59 · Elad Gil, Jake Stauch
[00:02:59] S1: I think one thing that you mentioned that's really interesting about what you do is if you look at the world of AI adoption, a lot of the really early adoption is coding agents. Yes. And that's engineers using it to build applications for their business, for products, other things. And what you folks have been doing is really pioneering expansion of the category in terms of saying, We should let anybody internally, an IT person, etcetera, build internal products or tools that can be used broadly across the enterprise. You're basically providing coding agents for all the internal stuff for people who often aren't that adept at coding. [00:03:32] S0: So can [00:03:32] S1: you talk more about that? Think it's super fascinating. Yeah.
00:03:32 · Elad Gil, Jake Stauch
[00:03:32] S1: you talk more about that? Think it's super fascinating. Yeah. [00:03:34] S0: Love this idea of coding agents for the rest of us, because we think so much of the early enterprise adoption in AI has been engineering teams. And if you think about why that is, there's a lot of reasons. Obviously, early adopters and a lot of different technologies, but also they're able to build and experiment with these tools because they have this process of code review. It's very safe for even a 19 year old intern to build something very powerful and then go through this process before it goes into production. We wanna bring that same capability to the rest of the enterprise, so we build a platform that brings coding agents to IT departments who then can bring it to HR and finance and people teams and legal teams. And they can do it because under the hood, it's coding agents, but then you have all these abstractions and guardrails and controls. So things go through approval. They go through a staging and, approval cycle and audit trail and all of that. And so it's how do you build a system that makes it easy for everyone to be a builder. And the core insight here was that IT actually wants to build stuff. And for most of the world, they don't have an engineering department. They have an IT department. Most companies have an IT department, not not a a team of software engineers. And so IT is what's building and configuring technology for the company, and we are building essentially the AI platform for them. How does how does that
00:04:41 · Elad Gil
[00:04:41] S1: run into things like all the different more, like, workforce agents that are being developed, like Dot from OpenAI or, you know, some of these things where you almost have a virtual assistant that will go and do things for you?