AI Unleashed: The Future in Focus ft Luke

Your best sales reps will be your worst offenders. Yeah, right.

Yeah.

I was a little bit different, but I learned that in being a signer. Right. So I learned the importance of data and all the little tweaks, and I started to like that side because it was interesting to me. So then I applied that to my sales, and, like, that's. I was able to dial everything in. You know what I mean? Hey, guys. Welcome to another episode of Coffee Is for Closers. I'm here today with Big Luke, and we're going to be going over a cool thing that he's building and a bunch of other stuff to do with calendar management and coming up with a singular source of truth when it comes to the data of salespeople and all the filthy reps that won't do their data.

But, yeah, make it easy for them.

Yeah, give us a background. My background of why you're smarter than me and most of the people listening.

Oh, that's a troubling thought. Yeah. So I have a technology background. Been building tech companies my whole career. Been involved in some pretty exciting businesses over the years and some unmitigated disasters along the way as well. Today I run a studio called Superluminal. So we build all sorts of really interesting tech for people, mostly in AI at the moment. There's a ton of AI, and then we also have our own internal projects as well.

Okay.

And that's where the project we're talking about today comes from.

Yeah, exactly. What are some of the projects that you worked on? Can you talk about them?

Yeah, for sure.

G14 classified. Yeah.

Yeah. I mean, we've built some great software for trading, for trading platforms. There's one where we're doing AI analysis of 40,000 companies per day and sort of putting it through the lens of value investing and making some. Some assessments of each company. We're doing a lot of work in education, trying to map between different syllabuses and educational content, and very difficult to try and do that with classical computing. But AI has a really strong hand to play with that. We're doing some other interesting stuff for sales teams for one of our clients, where we're sort of consolidating all of this useful data around leads and projects and so on, and then turning them into these little customized podcasts that you can listen to. So while you're driving to your sales meeting, you can be sort of getting briefed. So some of the synthetic AI stuff that's coming out is incredible.

So synthetic AI?

Yes, synthetic voice AI. So it's sort of a long way from what you might think of as the sort of robotic sounding stuff from, you know, back in the day. It's, it's really hard to tell that it's not a real voice. And so being able to kind of get briefed on things as you're driving to a meeting, you know, our thinking with AI is that there's a lot of concern around people's jobs getting replaced and so on. And I think a lot of that will be figured out over time. But I think in the meantime there are a lot of excellent opportunities to help enhance human relationships rather than diminish them or replace them.

Yeah, I think like I know when I hear AI because in the space that I'm in, I think it's just a lot of people who have like chat GPT prompts. Yeah, right. So like when, when you said like what's like. So the thing we're, we're sort of talking about and the thing that we're kind of doing together is this calendar system that can read everything and do everything and there's an AI component to that. But like what is the difference between something like a real AI system that does this kind of stuff or just someone who can run a prompt on GPT? I don't really know that much about it. I mean, I obviously do, but for the people at home, explain, are there different types of AIs or is it all kind of running off the same thing? There are large language models.

Yeah, I think they, without. I'll sort of avoid going like too deep into that topic. But suffice to say that conversational AI, which is ChatGPT and things like that is one type. And then I think the best way to think about it is in terms of how you interact with it. It's not always typing and obviously now you can increasingly speak with them verbally as well. But it's also around the sorts of data that you put into these systems and they data and insights that you can get out of them again. Okay, so I think that without getting into the like technical delineations between those systems, I think that's a good way to think about it. You know, I think for a lot of people, AI equals chatbot or some permutation of that. Whereas, you know, with the system we'll be talking about today, you know, you see AI at work doing the heavy lifting, trying to figure out insights and then the way that that's output is not conversational AI. It's fully, fully integrated into the product in a way that the end user doesn't need to kind of see behind the curtains of how that's being figured out. It's not relevant to them doing their job better. We're just giving you the punchy insights to do your job better, which is.

Essentially what computers did. Yeah, I mean, like, the first time, it's like, you know, instead of.

Yeah, you don't need to know how it does it.

I don't know how a computer works.

Yeah.

I don't know how my phone works. I just. I remember I made them as. My dad's a bit of a boffin, right? Like, he was a kind of an inventor tech guy. He was the first person on the Internet in Australia. He was contracted by the Australian Patent office to figure out how to get the patents from the US So he hooked up an acoustic coupler with a fax machine and then managed to piggyback off Internet through the fax network in the U.S. right. And then basically had a fax machine that was just live printing every patent, every patent request as it came in.

Amazing.

It's kind of an interesting way to do it, right? With fax paper, you know, I mean, Fortune. Yeah, I remember that stuff was. It was back, but, yeah, that's what he did. He went to bunch of other stuff. But I remember, like. Remember I made the mistake once of going, like, how's a phone work? He was like, well, it was like an hour later, I very much regretted it. Yeah, I know how a phone works, but. Yeah. So, like, you know, I think it's like, it's one of those things. Right. Just makes. I always see it as, like, it's just gonna make everything. Like, it should make everything better and more creative because you're taking out the menial.

Yep, I think that's right. And a lot of the stuff that we're building is kind of put through that prism of. Rather than just saying, okay, well, we've got this new shiny object. How do we just use it in everything? It's. How do we look at the commercial objectives that we're trying to achieve and then leverage that technology in service of that?

Right.

Because I think when you do it the other way around, God knows a lot of capital gets torched just building fluffy stuff. I think blockchain is unfortunately an example of that as well, where people just got so enamored with blockchain that they just wanted to build stuff with it rather than saying, well, what are we trying to achieve? What's the best technology to do that?

Gary Vee just yarned at everyone to buy NFTs. Right?

Yeah. Yeah. I think Gary Vee should go back to Wine library. That was his.

Yeah.

Prime days, man. I love that stuff.

Yeah. Yeah. All right, so what do we. What's this new product? Explain it to me.

Okay, so Rev Base is, I guess, working for sales professionals, trying to help them, I guess, fill in some of the gaps in some of the products that are already out there today. Yeah, I think maybe. One preliminary thing I would say before we get into the specifics of that is obviously there are a ton of sales tools out there. Unfortunately, I think that there are some really key components of what people need to be doing that are currently left to boring, repetitive tasks for humans.

Yes. Right.

And so that's where I think you and I have really started to meld minds on that and say, well, how do we find those boring tasks and sort of pluck them out and make it trivially easy? Which is better for the teams because, like, no one wants to do those jobs. And it's better for the management and the executive who need the data coming out of it. So having now talked around it, what the actual features that we're looking at are, things like making sure that sales teams are able to really easily update the statuses of each of their calls, make sure that they can understand where the gaps are in their calendars and what the opportunity cost is of those gaps, and then using that as more of an input into what is actually an AI system is start to generate insights that we can feed back into those teams so they can optimize their scheduling and their calendars around what's going to get them the best results.

Yeah. And a lot of this came from the fact that we met through Ben, and I think I was just complaining. I think it was like. So having run a lot of sales teams now, it's got to be close to. It's getting close to 100, I'm pretty sure. And I'm running the biggest one I've ever run right now, which we have 12,000 sales calls in the month of May right across a number of different, like, lead partners. So you've got, like, slightly different marketing coming from different places, coming into, like, a singular thing, having none of the systems are really structured to kind of handle all of that, you know, and so you have like two or three systems running at once, all of which sort of like, don't want to play nice with each other that much, you know what I mean? They'll play nice with other stuff, but not with these. With each other, right? Which is, I'm sure, is by design. Same way when you plug right it.