In this episode of the Full Throttle Leaders Podcast, host Michael Falato interviews Laura Fu, the Go‑to‑Market Development leader at DevRev. Laura explains that her team’s mission is to make every customer feel like the best customer throughout the entire journey, emphasizing relationship‑focused sales. She describes DevRev as an AI platform that provides a secure, precise LLM‑as‑a‑service by building a shared‑memory data infrastructure that links disparate data silos, enabling the AI to understand an organization’s full context. The target market is any enterprise building digital products for internal or external users, especially larger organizations that need scale. Laura also discusses her recent book, Designing for Excellence: AI in Sales in the AI‑Native World, which outlines principles for integrating AI into sales without discarding timeless sales fundamentals, and her podcast State of the AI Union, aimed at AI builders, operators, sellers, and investors. A key lesson she shares is that AI, while powerful, should never replace human taste and judgment. She showcases DevRev’s product “Computer,” an AI assistant that has access to all organizational data, remembers past interactions, and supports multiplayer collaboration, dramatically reducing manual effort in RevOps tasks such as building complex filtered reports. Finally, she provides her preferred contact method (LinkedIn) and reinforces the importance of keeping human agency in AI‑augmented workflows.
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All right, everybody, we got Full Throttle Falato Leaders Podcast today. We have Laura Fu. Laura, tell us what you do, why you do it, and what company that you're representing today.
Awesome, Michael, thanks so much for having me. I work at a company called DevRev and I run the go-to-market development team there. The goal of the go-to-market team, the go-to-market development team, is actually to make every customer feel like they are our best customer, no matter where they are in their customer journey. So all the way from prospects through to the renewal cycle. And I love the job because I think that go-to-market and sales is really based on relationships. And there's no better way to create those relationships than to nurture and develop them. So that's my role. And DevRev is an AI platform, an AI harness that allows you to use your LLM models in the most efficient and precise and secure way. And we do that by investing in the data infrastructure and making sure that our shared memory ingests and creates those relationship links between all of your data silos so that the LLM can very accurately read and understand all of your data sources.
Who— what type of companies, either industry-wise Or persona-wise, are the people that hire you are the target ICP and personas of DevRev?
Yeah, good question. And here's what I'd say. I always say that DevRev customers are any organization out there that's building a digital product for their customers, whether their customers are internal or external. So we are a— we call it the self-service company. And what we're trying to do here is make the capabilities of the organization available to people in the enterprise and outside of the enterprise, which is the enterprise's customers. So some level of scale is needed, and that means that, you know, I think enterprises with a larger number of employees and customers tend to find the most value out of Diverse products.
And I know that you told me that you just wrote a book and you also host a podcast. Is that correct?
That's correct, yes.
Well, tell me about the podcast. I think it's called State of the AI Union. Is that what it's called?
Yes, that's correct. So I've been at DevRev 2 and a half years. And in that 2 and a half years, I learned a lot about AI. I always say that I got my AI MBA here at DevRev. And since my functional expertise is in go-to-market and in sales, I've been in those roles for about 20 years now. I was able to first write a book on what's the best way to use AI in sales and how we should actually be building products that incorporate some of these design best practices that change the way we're doing sales because of AI. And the podcast sort of builds on that. The podcast is for AI builders, operators, sellers, and investors. Anything that is trying to make AI accessible to the layperson, anybody out there. And I think one of the challenges that— one of the privileges, I guess, that I have is being in Silicon Valley. You know, you walk around the corner and there's a new AI company, but not everybody shares that same privilege. And so I'm trying to get that information about AI out there.
And tell me a little bit about the book that you just wrote.
Yeah. So the book is called Designing for Excellence: AI in the— AI, sorry, Sales in the AI Native World. And we talk a lot about how there are some principles of sales that don't change just because AI is here, and the things that we need to do to be able to enhance the performance of sales teams, things that we need to think about differently, not just doing the job The same way but faster, but really incorporating some of these new things that we can do such as AI orchestration so that the rep can, can do things very differently.
And what's the best way and who should reach out to you? The best way to reach you?
LinkedIn is a really good way. My profile is Laura Zifu.
And if you had to say what was the best lesson learned Right. Okay. And this is something I learned as a jiu-jitsu black belt. You either get tapped or you, or you tap somebody, but you always learn, especially if you lose. What's something that the AI tech strategy in the last 6 months to a year that was amazingly that you learned from it because you won or you lost?
Yeah. I think the major learning is that AI is a very powerful tool, but it can never replace human taste and judgment. And if you are outsourcing your human agency in making decisions to the AI, you might want to reconsider that, because that's the thing that really helps us stand out, right? It's our human agency. And AI can do a lot of things. It can operate for us. It can be our own agents. But let's make sure that the important decisions, the decisions on taste, design, relationships, experiences, like all those are kept within Is
there a particular tech, either SaaS or AI tool that you're like, like for me, it's, I use a note-taker called Fireflies that I really love and it sums up everything I said. I can send it off and I'm done. I have an AI digital twin from Delfi.ai. So I've learned from doing these podcasts or roundtables and masterminds that I do, I'm like, let me ask people what they like, whether it's their tech, which is cool, but then sometimes it comes too pitchy. But What is something that you enjoy that was amazing that you just found some piece of tech that really changed your operational excellence?
Yeah. And since you said, since you said that it could be a pitch, let me introduce Computer by DevRef. This is our, this is our product. And I can, I can say that it has changed the way that I work. And the main difference here is because Computer has access to all of my organizational data, DevRev's data. I— any work that I do, I do not have to spend time gathering context, feeding it more information. It has all of, you know, my, my present and past history, whether I like it or not, access to all the files, and it makes it really easy to interact with. On top of that, I can work together in multiplayer mode with my teammates so that we're all working together on the same project with the same AI.
Like for me, I'll get asked, hey, do you want this dashboard or do you want me to do this? Like some of my AI tools. Is there a particular thing that it, the KPI or the end result of what it did for you is like, by using your tool, it helped me save this particular approach that I've been normally doing manually? Maybe if you have like a little TEDx story about that.
Yeah, so for example, a really, really clear example from RevOps, for example, I used to run the RevOps team. And, you know, when you run a RevOps team, every time you build a new report, you have to inherit the filters and you have to change the filters and you have to make sure that it's searching for this thing in this particular way because that was the way the information is stored, right? Okay. Now, those preferences around knowing how to ask a question and the outcomes that you want, like I wanna see anybody that attended this event and the pipeline associated with those events. If I were running in Salesforce, it would have like 7 different fields that I would have to select, like event date, and I only want to see opportunities that are owned by this person, and the type of the opportunity has to be, you know, a new opportunity, etc. Like all of those different types of things. Those preferences are already stored in memory. So every time I ask a question that is remotely like Can I see all the event attendees or pipeline associated with it? It knows whether it's for— whether I say I want to see it for EMEA, I want to see it for Americas. It knows how to query the results in the same way because the context has always been the same.
Yeah. The whole thing is if you just look at even Sales Navigator and you have to pick 25 different filters.
Correct.
Or there's a new app I heard on commercial. You walk around the car dealership and say, I'm looking for this and that, versus the old days, I want a sedan with a convertible, or it's the way you talk to an AI tool that makes it like exactly like you're talking to someone what you need versus let me click this filter, I'll hit that filter, and you're— by the time you do, you're like, this was a 30-minute filtering exercise that I don't want to do.
Correct. And it's like you're talking to the same rep every single time.
You don't
get
They don't forget. They don't forget who you are.
It doesn't forget who you are. Exactly.
Thank you for making time, Laura. Um, we'll definitely put this up on LinkedIn and YouTube in the next couple of weeks. Thank you.
Love it. Thanks so much for having me on, Michael.
