The Future of Digital Workers

**Prabhav Jain** (0:00)
As a company, we're really obsessed with customer outcomes. So, if I can do something without using agents, I will, right? Ultimately, all that matters is our customers getting the results that they're hiring our digital workers for.

**Joe Schmidt** (0:12)
Hi, everyone, and thanks for listening to the a16z AI podcast. I'm Josh Schmidt, a partner here at Andreessen Horowitz, and today I'm talking to Prabhav Jain, the CTO of 11x. For those who don't know, 11x is building autonomous digital workers that automate go-to-market workflows, helping organizations increase efficiency and cut costs. But what does it really mean for a product to be agentic? AI agents have become one of the most hyped concepts in tech today, often used interchangeably with automation, co-pilots, or even simple workflow tools. But true agentic systems go beyond static rule following. They need to plan, reason, and adapt dynamically to new information. They don't just retrieve answers, they make decisions, improve over time, and operate in environments where outcomes aren't always binary. In today's conversation, Prabhav and I dig into what it takes to build AI agents that work in the real world. We'll talk about where agents are already making an impact, where they still struggle, and how 11x has navigated some of the hardest technical and product decisions in this space. We'll also cover how the AI infrastructure landscape is evolving, how to balance orchestration versus true autonomy, and what the future of agentic experiences might look like. It's an exciting discussion that you'll hear after these disclosures.

**SPEAKER_3** (1:24)
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**Joe Schmidt** (1:47)
Rabaf, thanks for being here, man.

**Prabhav Jain** (1:48)
Thank you for inviting me, yeah.

**Joe Schmidt** (1:50)
All right, so maybe we'll start this with maybe a high level question. A lot of people talk about agentic experiences today. You know, it's really good marketing, but maybe I'd like to just take a step back and start by asking, what does an agentic product mean to you?

**Prabhav Jain** (2:02)
This is a great question. I think the term agents and sort of agentic experience is thrown around a ton. If you're using LLMs at any level, you're now an agent company, which means every company out there is an agent company. But, you know, for us, agents really have to plan, reason, reflect, think, get better over time. To me, that is the definition of a true agent. And the agent problems that really sort of interest me are the ones where the answer isn't clear. There isn't a right answer. Even a human wouldn't have the right answer. What makes a piece of writing good, right? That's really hard to quantify. That's what really excites me about agents. The user interface and the user experience really matters. Over the last 25 years, we have been trained to understand what that means in mobile interfaces. And now you have these agents coming up which aren't deterministic. They change what the output, every time you sort of call them. And that's a very new thing that we have to kind of train and explain to prospective customers that like, hey, this thing doesn't quite always work the same way. So that's a really interesting concept that's come up with agents now.

**Joe Schmidt** (2:55)
Yeah, it's interesting, like, not always working the same way. I guess the thing that I'm always tied to is like, what is effectiveness? And how do you think about these agentic products that you're building or maybe you've seen, are they more effective than humans? Or is it really just like, hey, is this orchestration and we're just making rules and trying to build different experiences?

**Prabhav Jain** (3:14)
You know, what I've seen is that, especially in like code generation, I sort of count that as like true agentic companies, because not only can they like generate code, plan what they're going to write, generate the code, then run it, see errors that come up and then keep going. And I think that part of the ecosystem is quite mature now. I think for like B2B, like verticalized agentic applications, it's quite a bit more complex. Again, you can run code and see if it runs. But for these applications, they're much more complex.

**Joe Schmidt** (3:39)
Maybe say a little bit more about that. What makes these B2B applications more complicated and harder to solve for?

**Prabhav Jain** (3:45)
There's a lot of people involved. For us, for example, we saw to go to market teams, what makes good content? What makes the lead that you're reaching out to a true ICP lead for you? Again, just kind of subjective. And so I think that's what makes it trickier, whereas for a piece of code, it kind of runs and does what you tell it to do.