The Future of Human Connection in the Digital Age

Thanks for listening to the AI for Sales podcast with host Chad Burmeister. This episode is brought to you by BDR.ai, Nooks.ai, and ZoomInfo, the go-to market intelligence platform.

Nooks.ai is the agent workspace for intelligent outbound. By pairing human judgment with AI execution, reps focus on relationships, not busy work. Join Intercom, Deal, and over 1,200 customers who use Nook's AI dialing, coaching, or multi-channel AI sequencing to double their pipeline.

And ZoomInfo gives your revenue teams the data and insights they need to find, engage, and win their best customers, helping you move faster, work smarter, and grow revenue at scale. Want an introduction to one of our sponsors? Head to www.scr.

ai forward slash intro and unlock your direct line to more closable pipeline, powered by AI. Until next time, keep leading the AI for sales revolution. And remember, in sales, time kills deals. But in AI for sales, AI kills time.

So, Sunil, how has AI transformed the customer experience in your industry? I think customers now expect a level of integration of the latest and greatest and everything that's been hitting the market. Like we know ChatGPT launched November of 2022, and it rapidly permeated every aspect of everyone's lives. And they knew that this new capability is out there.

And I think when people say AI, it's changed over the last two decades, right? It's taken different forms and shapes. But I think now the real point is, hey, how can this technology that I now used in a personal way at home become part of work? And I think the time it took for this to become available and usable in work was super fast, right?

So the expectation on enterprises and companies just became very, very rapidly something that customers said, hey, how are you now imbuing this stuff into your product? How are you making part of the experience? Because the amount of leverage that we get from it is significant and we need to make it available. Well, we have a small tiger team that created an AI solution inside of our company recently that does prospecting.

It does the research of the person. It does a whole lot of things. And when I put the framework of what it is we delivered into Gemini and said, here, frame this from a business value perspective. And what it put out was, you know, it could take an average of 30 minutes to two hours to go research a person effectively.

Right. They say three pieces of information in three minutes was Steve Richard at Voresight. He always said, but most reps do zero pieces of information in zero minutes and they just blast all emails. Now you can let the AI, it researched 600,000 contacts for us in the course of about two weeks.

And now when the rep goes to push send, all that research is just delivered, saving hundreds of thousands of research hours, many of which would never have been done only by the top two or three people on the team. But you have to articulate the business value in those kinds of perspectives. Two times better response rate, 50% better click-through rate, more pipeline, more revenue, less headcount. You just explained the new baseline.

That's the expectation from the customer. Hey, I can use Claude Co-Work or Claude Code off the shelf, and I can get something up and running in this way. I can go and produce CIA style dossiers on every prospect that I'm talking to and have this thing run in a swarm autonomously overnight and populate my CRM and I'm ready to go. So it's like, okay, that's the baseline.

So how are you going to come on top of that and add value, right? And this is the nuance. This is how you have to talk to customers about, hey, where are we in the stack? Where do we fit in?

Wow, that's just so compelling. So speaking of where do we fit in, let's share a little bit about Tribble while we're here. Yeah, happy to. So look, we started the company in 2023.

And the goal was always to think about go to market in a different way and leverage what we saw as the tsunami of capability that was coming at us. And it became very clear to me that, hey, a lot of the stuff that I was doing when I was at Salesforce, specifically when I was helping go to market teams, everything from enablement to industry expertise, to ultimately running a product as a GM. how do you get your internal folks aligned on what it is you're putting out there how do you get your customers to understand what you're selling and how do you get your ecosystem and partners to also get enabled on the stuff you're putting out there like that was always a problem because when you sell something deep in a vertical or a complex product it is hard to bring everyone along for the journey so you end up having a lot of inefficiency taking the form of enablement documentation people have to learn this stuff like it's a phd how do you short circuit all of that when you have these intelligent models that have within their parametric weights, all of this knowledge encoded, and you can just use that as a shortcut mechanism to create just-in-time content, create just-in-time, whether it's emails, top of the funnel, like you guys did, right?

Or it's actually progressing deals or understanding insights about people that are attending in meetings and then using that to have a better meeting. All of these things were pieces to be pecked away. And we saw that in 2023 and said, hey, how do we start building towards that? So the first product we launched was RFP automation.

And the reason we picked that is we thought of it as if we can train on your company's data, we can understand where data lives in all the systems, like whether it's SharePoint, Google Drive, your CRM, your ERP, whatever the case may be. And we deeply understand it and we're able to answer an RFP on your behalf. We've essentially answered a large number of questions that your customers have about you. And that's a good data foundation on which we can build more complex capability.

So that was the first product we brought to market. And right now we call that product Tribble Respond. So it's anything related to an Excel file that you may get as a tech vendor with a series of questions to a bid packet someone selling into the public sector gets for like a 10 month sales process, which is 10 PDFs with a whole bunch of Word documents. And they've got to write like a 70 page proposal as a response.

We cover the full gamut of what you would come back with as a customer. And then on the other side, one of the other products we launched is what we call Engage. And the reason we kind of looked at it as not just the part of the process where you respond to the RFP but if you think about it when you have that nine month sales process if one of the steps in that process is an RFP that not the first time you talking to the customer You have the first call with the customer They give you some information Second call they tell you they going to take you to RFP Third call they send you an RFI right It like the preliminary thing.

Should I even consider you? Fourth call, they get all the vendors together and then they ask all the vendors questions or the vendors can ask them questions. So we looked at it as how do you collect all the data on those touch points to inform the actual proposal response? So what engage does is it actually comes along for the ride with the people using it it listens to the call and it coaches them in real time and it tells them hey ask this collect this data this is how it's going to help you when you're actually going and bidding on this thing so i'll pause there for a second yeah that makes a lot of sense i mean i think a lot of companies try to skip that step and go to the you know let's just not worry about the data and let's just provide you with the tools of what you should say using public information.

But the real secret sauce is in leveraging the information that you've generated from those RFPs, like you said, and all the other data sources that you're able to tap into. So it makes a lot of sense. How has it changed? Obviously, with LLMs, on the earnings call recently, there was one SMB customer who said, hey, I had 10 employees and we were doing X million in revenue.

We moved to three. And that was an interesting use case because most people are saying how, oh, it doesn't affect jobs. Well, in this case it did, you know, down to three, but they were able to use 20 agents to increase revenue by $3 million. So they went down from 10 to three people in the company, and then they increased revenue $3 million.

And it was, it was pretty, pretty compelling story. Um, how are you finding that AI is impacting the, I guess, the employee headcount and agents? And talk to us a little bit about your feelings and what you're seeing there. Yeah, I think it's, I don't know the specifics about that example, but it's compelling, right?

If, hey, if I'm able to reduce the number of people I need to run a business by, you know, in this case, 70%, that's quite that's quite something right and i think um the way we've seen it and the way we've talked to our customers is less about employee less employees but more like hey most customers are not in a zero-sum game they're going after a bigger market they're all looking for growth they just want to do it more efficiently so the conversation is hey can you get more leverage per person because if you look at the jobs to be done like the employment agreement or uh the job posting for an individual and you see all the tasks that they're assigned.

If I go and do that and I go look at the top 10 tasks versus the top bottom 10 tasks, which one of those tasks can I factor out? And they don't have to just do those anymore. So then, you know, the equation then changes. Do you need as many people in that role?

Probably, but you'll get more output from that many people, right? And that's another way to think about how does that impact growth and revenue? So I think it's a nuanced way of just, hey, can we grow more efficiently? And can we get more leverage out of the individuals that are already there?

And should we think differently about how we position this role? Like, should the role evolve, right? If we remove some of the work that's repetitive, mundane, that agents can take off their plate, we should probably do that. Yeah, yeah, yeah.

Well, and I just think through the RFP process and how painful that is, because a lot of those come to the BDM department. Hey, we need this done by tomorrow. You just kind of laugh and say, I don't even know who to send you to inside of the organization, much less how we're going to get it out by tomorrow. And I would think with a tool like Dribbble, the possibility of actually getting that out by tomorrow would actually be a real thing instead of calling the customer and saying, we're going to need a couple of weeks to compile all this information.

I mean, Chad, that was the baseline when we launched in 2023, right? Like that was like the LLMs at that time. And at that time, no one knew what an agent was. So we were just talking about leveraging.

I think they call it generative AI, right? Now that's a dead term. So you basically did things faster, right? That gave you the ability to like rapidly respond.

So in your example, 24 hour turnaround with Tribble, no problem. You can get it done right away. But what we realized over the last few years working with customers is actually you don't want to just respond faster. You want to respond better in order to win, right?

That really is what you're trying to do. So in order to do that, if you're just focused on AI to speed things up and efficiency gains, I think you're missing the plot. And I just state that broadly because really why you're doing this is to say first, where do we focus our efforts? We got to not bid on the 30% of things that are just going to burn time.

The competitor wrote it. It smells like it's someone else's game to win. You want to stay away from that and you want to deploy your resources on things where you're more likely to win. But where do you get that intel, that insight?

So we've thought about it more as like the holistic opportunity stage one till close, as opposed to just a stage where you respond. And that for us is the goal. Like, how do we help you win more? Nooks.

ai is the agent workspace for intelligent outbound. By pairing human judgment with AI execution, reps focus on relationships, not busy work. Join Intercom, Deal, and over 1,200 customers who use Nook's AI dialing, coaching, or multi-channel AI sequencing to double their pipeline. Yeah, that's great.

It reminds me of RingCentral. I worked there for three or four years, built out a big BDM presence there. And the play was, hey, it's not just moving to the cloud so you can save 70% on your unified communications. communications.

It's you can access a whole lot more features without having to put a big stack of hardware in your closet at the dentist's office. You can access call center technology. You can access so much more IVRs and now Gen AI and talking to an agent and all of those things. But to your point, it's got to be higher quality, not just speed.

So that makes perfect sense to me. Do you have a case study maybe that you could share of a deployment or talk to us about the real world? You know, what do people see when they deploy this kind of technology? Yeah, one of our biggest customers I like to talk about is UiPath.

They're an automation company themselves, right? And I think what really interesting about their technology is they gone really deep into verticals They got very concrete use cases on automations like financial services healthcare large public company We helping their field teams with RFPs but also with this engaged product, really thinking about how the reps can show up in a more consistent way and collect the data that they need to in order to execute deals well. I think from an ROI standpoint, one of the things that their CMO at the time shared with us after leveraging our tech just for a few months is that team that they had, the centralized shared service team that was answering RFPs.

They were planning on adding a couple of heads. I think this was in like 2024. And after using our tech for just three months, they didn't need to add the additional head count. So coming back to your point earlier, we didn't see, there wasn't a compression of the team, but it was just, hey, with the growth we were having, we were planning on this extra capacity for that team, but now we can use that extra capacity for other sides of the business because we're getting the leverage out of the tech.

And I think you see flavors of that in every aspect of this kind of process. Yeah, yeah, yeah, I love it. I just, another example, I heard that recently we hired 20% more salespeople. And then that means we didn't have to hire, you know, through attrition, we didn't have to hire other people in other departments.

So you can be more strategic in where you deploy resource inside of an organization. It's not about the headcount reduction. It's about growth and expansion. Recomposition for growth.

I think that's, I like that way of framing it. Cause it's, it's the zero sum mentality is not a good one. It's like, how do we grow together? Yeah, that's right.

Talk to me about balancing automation with personalization. I mean, as I think through your engaged product and I think about a, we're just doing a basic training on what is a stage two opportunity from in the new world that we're living in. What's stage two op? And then you start talking about all the different products and alignments and everything that you guys do.

How do you balance the, all these technical requirements with personalization? And how do you balance AI and personalization? I think the users expect personalization in order for them to get value out of the tool. And what I mean by that is, as an example, like they talk about engage, right?

You're walking into a meeting. So similar to how you folks had that agent that's doing research on prospects, we do it across the deal. We do it across all deals that have had and have happened in the past with this account. So we get this account level intelligence.

We call it deal intelligence, right? And what it does is when you're about to walk into a meeting with Chad, you know, every touch point we've ever had with Chad across all calls, across all meetings, deals, everything that's happened. And you're coming and very informed and in a multi-step process that is months long, you're able to walk into every meeting with context of the previous one. Right.

And we actually generate this thing called a briefing packet, but we also generate slides and we say, Hey, like use this deck in the meeting, you know, in the beginning of the deck, we'll say something like in our last call, we covered X, right. And it will just, this is work that good salespeople already do, but this is what I mean by personalized chat. So it's personalized to that engagement of that rep with that customer at that moment. Right.

And if we can nail that and we do it consistently, then not only are we preparing them for the meeting during the meeting, we're able to nudge them and say, hey, last time you forgot to ask this question, make sure you check this off. And we're doing that in real time and we're checking off the boxes in front of them. Right. So that's how we can personalize it to that engagement.

And I think that's when it gets adopted. What? Right. Because they're getting value out of it in real time.

Yeah, that's amazing. As a CEO of your organization, I'm sure you run into all kinds of new technologies, right? When Gemini came out not too long ago, everybody, you know, that's the talk of the town for a couple of weeks. And then all these new technologies.

Is there anything that you're seeing out there that's, you know, hey, stop and listen. You got to pay attention to this type of technology around AI. I think everyone should try using Cloud Code or Cloud Cowork. And I think it unlocks where this tech is going.

And I think everyone says 2026 is the actual year of agents. Everyone marketed agents for the last two years. But now you actually have a level of autonomy that can be delegated to produce something more complex. And I think of these things as like waves of complexity thresholds that can be surpassed, right?

So what I mean by that is like, you can ask it to create all of Salesforce, right? Two years ago, and it comes back and it's like a landing page and it's like a few buttons. Okay. Fast forward two years, it creates like a super simple opportunity data model.

And then today it might create like an opportunity data model and then some infrastructure in the backend for config flows and things of that nature. But every iteration of these things are getting the capability to produce more complex output. And it's a function of how long they can run autonomously, right? Like how many hours.

And I think there was like a recent chart and study from the METR Institute. Like we are at this exponential curve in terms of models. That's why I specifically go to Claude because I think Claude's latest model, Opus 4.6, it runs unattended for something between 18 to like 90 hours in the testing that they've done, which is absolutely mind-blowing, right?

So that's something that pay attention to because things are changing really, really fast. Wow. Well, and I think I missed something in the State of the Union the other night that was brought up to me. And that is that these big companies are going to need to provide their own power sources for their own power for these big models.

And that makes a lot of sense because there's a lot of draw against the grid. So we've got to come up with new solutions. I think Elon's is let's just ship it all to space. And so it'll be interesting to see where all that goes.

but uh indeed interesting times ahead um what about the ethical side of all of this because i think of my friend henry shuck the ceo of zoom info and he's done a good job saying hey even though we don't have to do it this way we do it this way because of ethics and that's related to contact information right if you want to be out of our system you just submit a form and you're out Well, legally, they don't have to do it that way, but they did it. They made an ethical decision.

Whose job is it to make sure that the AI doesn't run away with the show and that we're making ethical AI decisions This is a really tough one right Because as much as we as consumers of the AI and I saying when I say we anyone who does not work at OpenAI XAI Anthropic and any other of the large labs, you kind of really are adding layers of control and trying to nerf a thing that is very capable and powerful. So they ultimately are driving their alignment programs around ethics and trust and what they want these models to do um we have less control right it doesn't say that we can like we can change our behavior within our span of control so like there there is something to hey very capable systems if not controlled at the very core it'll be very difficult for us to control them in the wild and someone will always be able to like exploit them and do things with them so and i think i think the large labs are all making an effort to align these things correctly.

But when I think about ethics and trust, we really think about it more from the perspective of, hey, how do we keep the human in the loop for as much of the process as possible so that they're validating the different pieces of steps? One, to bring them along for the ride because they need to continue to be involved in the process. We remove them from the process only when it's inefficient and they don't want to be there. But if it's something where you want the human touch, you should have it there and you should have the knobs and dials to help them involved because I don't think humans are going anywhere for a long time, right?

We're going to get in the way of these things getting over. So from that perspective, I think ethics and trust takes the form, at least for us, of, hey, how do we give transparency to our users and accountability for the things that we do anytime we're given any autonomous access? Yeah, I love the perspective because I don't know if we've covered that yet on this show in this question that the big LLMs are are indeed taking it on. I remember on one of the holidays, I was able to take a picture of the family.

And then I said, Okay, make up a joke, and then make it so that everyone in the family laughs and build a video. And it was like, it made the joke, everyone laughed. And I was like, wow, this is dangerous. Like I could have anyone told a joke to anyone, and then people laugh, and it could create a really bad impression in the marketplace.

And so then it went away, Like a month later, I was like, oh, I can't do that on that tool anymore. But Chad, this is why this topic is so fascinating. And I think a very, very, very difficult problem to solve. The aha moment I had about this problem, and it's just broadly alignment.

When you have something that is very powerful and very capable, and it knows well enough what you want, right? Like, for example, let's say I'm an all-powerful AI, and I've got a lottery ticket that is a winning ticket for a billion dollars in one hand and i've got nothing in the other hand and i say hey chad pick a hand and then you look at me and say hey i pick your right hand but i know you really wanted the thing in the left do i listen to your free will or do i override chad and say no no this is what's good for you take the billion dollar lottery ticket it is impossible to program that yeah yeah so it's like what do you give up right and i think that's like the crux of it right and it's like that propagates down into the myopic like little things that we got to figure out but That's the funny one.

So it's easy to just say, hey, that's the big lapse problem, but that's what they're tackling with, right? That's the kind of thing that they have to figure out. Yeah, it's very interesting. And a lot of times my answer is that it's above my pay grade.

And as a faith-based person, I just have to believe. Okay, last question before we wrap. And that's around the skills that sales pros need to have in this new world. What are you telling your reps?

You know, hey, go out and do what? Meet people, shake their hands, sit down across the table from them, look them in the eyes, have real conversations, real connections. Email is about to blow up and become unusable. Phone calls are going to become automated and unusable.

Every digital touchpoint will become almost commoditized and free. So what survives? It's the human element. And it's the most unintuitive thing for me.

If you asked me 10 years ago, what's the first job to go away? I would have thought parts of sales would be easy to automate. It turns out that's probably one of the last jobs that it stays. that's good yeah i took this um communications course a master course in communications for a year two eight hour days on weekends one hour a week with the professional i still pay her weekly to meet um on an hourly basis to continue to enhance and up level my communication skills they don't teach it in high school and elementary school and even college very well it's like, okay, one class, you're done.

And it's a lifetime of learning to be a good communicator. So I think that skill is going to be something that blows up in value when everything else goes to a commodity. Yeah, that's great. Well, Sunil, I've really enjoyed the conversation.

Thanks so much for being here. If people want to find Tribble and find you, how do they connect? Just go to Tribble.ai or email me directly, Sunil at Tribble.

ai. And happy to talk to anyone about any of the stuff we discussed. All right, everyone, if you're looking to enhance your RFP process, and then engage better with your customers, this is the way to do it, especially if you've got a highly technical product or a lot of different product lines, I would think that would be the one that would benefit the most. So call Sunil, call the company, check it out.

Thanks, everybody. And thanks, Sunil, for being here. Thank you. Bye.

Thanks for listening to the AI for Sales podcast with host Chad Burmeister. This episode is brought to you by BDR.ai, Nooks.ai, and ZoomInfo, the go-to market intelligence platform.

Nooks.ai is the agent workspace for intelligent outbound. By pairing human judgment with AI execution, reps focus on relationships, not busy work. Join HubSpot, Deel, and over 1,200 customers who use Nook's multi-channel AI sequencing to double their pipeline.

And ZoomInfo gives your revenue teams the data and insights they need to find, engage, and win their best customers, helping you move faster, work smarter, and grow revenue at scale. Want an introduction to one of our sponsors? Head to www.scr.

ai forward slash intro and unlock your direct line to more closable pipeline, powered by AI. Until next time, keep leading the AI for sales revolution and remember, in sales, time kills deals. But in AI for sales, AI kills time.