Sahil Aggarwal Podcast Transcript
Sahil Aggarwal joins host Brian Thomas on The Digital Executive Podcast.
Brian Thomas: Welcome to The Digital Executive. Today’s guest is Sahil Aggarwal. Sahil Aggarwal saw the gap between what AI could do and what his own company was built for. Rattle had over two hundred customers and a working product, but no matter how much the team pushed, making it feel AI native still felt like driving a Ferrari at twenty miles an hour.
So in twenty twenty-five, he made the call most founders avoid: scrap it all and build from the start. That company is Von. Von is the intelligence layer for revenue teams. It connects to a company’s entire go-to-market stack, from Salesforce and call recordings to emails and data warehouses, and handles the operational work that buries most rev ops teams.
Pipeline analysis, forecast prep, board decks, territory planning, Salesforce updates, all in plain language. Customers like Bloomreach, Cresta, and Qualified use Vaughn to do it in minutes what it used to take days without adding headcount Well, good afternoon, Sahil. Welcome to the show.
Sahil Aggarwal: Hey, thanks for having me, Brian.
Brian Thomas: Absolutely, my friend. I appreciate it. You’re hailing out of San Francisco. I’m in the Kansas City area, so I always appreciate when people take time out of their day to traverse time zones and calendars to get here. Thank you again. And Sahil, if you don’t mind, I’m gonna start with your first question.
You started your career convinced the biggest inefficiency in enterprise wasn’t the product, it was the workflow around it. Where did that conviction come from? Advising pharma at ZS, running your own practice, your time at Mutiny, and how has that thesis held up now that you’re building Vaughn?
Sahil Aggarwal: I’ve spent the last decade in B2B sales, doing it myself, building software for B2B sales, and working with large pharma on their sales efficiency.
And I’ve met thousands of people in sales, and nobody has ever said in the last decade that they’ve won a deal because of a product or the software that the sales team was using. It has always been the workflow around it. It has always been people convincing other people to buy their software and why they should choose to tackle the problem right now, or why they should choose to invest in their solution and not in anyone else’s.
So I think it is very clear that the thing in B2B sales has always been people, and people are a lot of workflows cobbled together. So that’s where the conviction has come from, is just this decade of experience doing this and talking to thousands of people. The other thing, if I can quickly add, Brian, what I’ve seen is that software pre-AI was always very rigid.
And what that means is that if you log into Salesforce or Workday or any of these large enterprise software, you can only do one thing in them, at least in that particular UI. But that is not how people work, especially in the sales and marketing domain, and that has been a huge challenge at least pre-AI. And now AI is untangling those workflows.
Brian Thomas: That’s awesome. Thank you, and I appreciate it. And love the backstories here. We always talk about that here on the podcast is, a founder like yourself or any executive, someone that’s trying to make the world a better place. This guy kinda say that all the time, but, you found a gap in the market here, obviously doing B2B sales for ten years for big pharma companies.
The bottom line is that friction was always in that workflow around that process, and you talked about that. And AI has always been limited in that sales and marketing domain, and what you’re building is, I think, phenomenal. And again, it’s because you have a vision, you saw that gap, and you’re there to fix it.
So thank you. Sahil, you’ve said AI has revolutionized the workflow for people who build things, but nothing has revolutionized the workflow for people who sell those things, and that’s what you’re building with Vaunt. Why has the go-to-market been left behind while engineering got transformed, and why is now the moment that finally changes?
Sahil Aggarwal: Just a quick point of clarification that what I’m building right now, Von, is not just for pharma sales, but for larger B2B sales. The underlying technology has shifted, Brian. We were in the system of record era for the last twenty-five years, which has been tools like Salesforce for sales, ServiceNow for IT, Workday for HR, GitHub for engineering code repos-repositories.
And post-2022, which is when OpenAI and ChatGPT burst onto the scene, and now Anthropic, the era is system of intelligence. And the thing is that now you need to rethink the entire form factor around this technological shift. If I can use an analogy, I’ll use the analogy of moving from steam engines to internal combustion engines.
When that shift happened in the technological landscape in 1890s, it took Henry Ford ten years to build the first production-ready car because he had to rethink the entire form factor. He had to go from a carriage driven by a horse to the first Ford car that we all saw. Because it is such a huge change in how we do things and how we build software, engineers were the first ones to change their own workflow And Cursor, which was the first application on the engineering side, these were two kids, four kids out of MIT who were in their third year or fourth year of MIT who basically decided to build Cursor and change the engineering workflow because they were basically building the software for themselves.
I think that will happen to go-to-market as well. It just takes a little while for people to wrap their hand ar- head around the new technology landscape. Hopefully that’s what we’re doing with Von, but time will tell.
Brian Thomas: Thank you so much. I appreciate that. You talked a bit about, to start right out here, clarification again, I know your platform’s not strictly related to the farm industry, but more the larger B2B market.
So get that, and I appreciate that. But you did talk about the analogy between, with Henry Ford, right? That go- moving to steam to internal combustion engines. It took Henry Ford a lot of work and time to really recreate that whole manufacturing process, and I appreciate you sharing that. And a- an example you provided was the creators of the Cursor team and, and what that took to get there.
So again, really appreciate what you’re doing and, and sharing your insights here with our audience. Sahil, your message to revenue leaders is blunt: stop head counting your way to quota. You’ve pointed out that sellers spend less than thirty percent of their time actually selling, and quota per rep hasn’t budged in a decade, despite years of productivity investment.
How does Von change that math, and what should a rev ops or sales org look like when the answer to growth stops being hire more people?
Sahil Aggarwal: We’ve all heard of the statistic that seventy percent of a seller’s time goes in admin work and preparing for a meeting and doing follow-ups after the meeting. We actually ran a new study based on more than a thousand sellers, and we looked at their calendars directly to see how much time they were spending in customer-facing activities.
And Brian, it was less than fifteen percent. So that statistic has actually degraded in the last five to seven years, and not improved. When we think of AI, AI won’t be impactful if it does not solve a pressing problem. And I think in sales, the pressing problem is this fifteen percent that people spend on customer-facing activities, which means that they have eighty-five percent of their day, which is more than six hours a day, that is available for them.
That to me feels almost criminal, which is you have so much bandwidth available for people, and yet you are hiring for more headcount rather than trying to utilize the existing team that you have and giving them more pipeline. So what changes is with AI, AI’s biggest impact is productivity improvement.
An engineer is five X more productive than what they were before. It’s very clear. It’s you– it can be measured in terms of not just the lines of code that they’re written, that they’re writing, but also in terms of the number of projects and deliverables they’re able to ship. In the same way, a seller can now take on far more pipeline because AI can help them prep for that meeting, create follow-up material, create quotes, update their CRM, and also strategic thinking, which is what else should I do in this particular sales deal to go win this?
So I think that’s why it’s like a great solution meets a amazing problem, and that’s where the biggest impact of AI will show, which is finally we can start increasing quotas per seller dramatically that have not moved in the last twenty years.
Brian Thomas: That’s awesome. Thank you. And you talked about that seventy percent, that sellers, their time goes to admin work, but you took it a step further.
You said diving deeper into the seller’s calendars, you found it’s really only fifty percent of the time dedicated to sales, and that’s like a light bulb right there. There are so many inefficiencies in this process, so why not figure out what the inefficiency problem is versus hiring more people? I thought that was really important.
And of course, AI can do a lot of these other tasks so that the sellers can keep their calendars full. So I appreciate that. And Sahil, the last question of the day, if you could briefly share, as AI compresses management layers and RevOps becomes an infrastructure layer where leaders run the business in chat, where do you see revenue teams and the entire go-to-market tech stack five years from now? And what has to be true for that future to fully arrive?
Sahil Aggarwal: I will tackle the second question first, which is what has to be true for that future to fully arrive. And I would say the models are more than capable enough today that the future is already here. Dario Amodei, who is the founder of Anthropic, which is the lab behind the amazing model Claude, he said something a few months ago, which was, “If we stop developing any further models from this point on, that still would not stop the amazing impact of AI in the society because the capability of– capabilities of the model is already so much higher that it hasn’t distilled into the society yet.”
And even the current Fable models or Opus models, we are barely scratching one percent of its capabilities. So I don’t think anything has to be true from a technological standpoint for the future to fully arrive. The future is already here, it’s just not evenly distributed. I think what changes in the revenue team and the entire go-to-market tech stack is there is a layer that is building on top of systems of record like Salesforce, which is a system of intelligence.
The previous layer of system of records will tell you what you need to work on, but this new system of intelligence layer will actually do the work for you. What that means is if today a revenue organization is, let’s say, a couple hundred people and generates half a billion in revenue, that same team should be able to generate three to five X of their previous number, keeping the same headcount.
So I don’t think roles are eliminated because people are just so much more productive and they can do more. But I do think that a company’s ambition of how much a dollar goes in into the go-to-market organization and what comes out the other side has to dramatically change. And that has to be a three to five X multiple of where they are right now in terms of their go-to-market investment.
In terms of tech stack, I think the system of intelligence will be the place where people will live and get their work done, and I think that’s what Marc Benioff from Salesforce realizes as well, and that’s why he is all in on Agentforce and not as much on Salesforce.
Brian Thomas: Thank you. I appreciate that. And those insights are important. Mark Benhoff obviously knows he has a big vision. He knows what he wants, and he’s doing a great job there, and I appreciate you highlighting that. But let’s talk about what you, you said earlier. These models today are more capable today to do all this work, right? The CEO of Anthropic, you mentioned, said that if they stopped advancing AI today, we still have not fully optimized the full power of AI, which I thought was pretty interesting.
And again, I’ve been using Claude’s Opus model as well, and it’s phenomenal. Can’t believe what it does. I’ve tried everything I can get my hands on, and it’s amazing, so, so I appreciate that. But yeah, the new level of AI today can truly do the work of humans in this space. We need to focus on leaving the humans to focus on sales time and doing that human connection.
So again, most appreciated. Sahil, it was such a pleasure having you on today, and I look forward to speaking with you real soon.
Sahil Aggarwal: Thanks for having me. I enjoyed the conversation.
Brian Thomas: Bye for now.
Sahil Aggarwal Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
