EP 53: From Data Everywhere to Insight Anywhere

If someone in your business can't be— can't have good conversations with customers, clients, and prospects and so on and so forth because they're too busy, because they are doing admin tasks or pushing paper around or fighting a spreadsheet and things like that. But AI stops that from happening, frees up their time for them to go and meet people, go and have a coffee, go and actually catch up and have a proper conversation, go and talk to people and do more of the people stuff. Then that's great.

The capabilities are doubling every 6 months and the cost of intelligence is coming down by a factor of 40 a year at a data center level. That's just absolutely mind-bending because you can just see the path that effectively the cost of compute is coming down. But you look at that in the trend of the cost of intelligence, the cost of intelligence is trending towards zero. So it's going to get cheaper and cheaper and cheaper to do the thinking in something that isn't a person. And that's going to create some societal challenges.

Hi, I'm Freya. Welcome to the Skynet Chronicles: Business in the AI Age, the podcast that dives deep into the world where artificial intelligence meets business. Join us as we explore the latest trends, challenges, and opportunities in this ever-evolving landscape. From innovative startups to established enterprises, we'll uncover the secrets behind the successful integration of AI technologies. So grab a cup of coffee, sit back, and get ready to unlock the mysteries of business in the AI age.

Well, good morning, Jackson, and welcome both to the podcast and to Project Rising.

Indeed.

I'm doing the annoying, naughty thing now. I'm banging on the table, which I'm not allowed to do.

Drum roll, I suppose. Drum roll.

So let's start at the beginning. Um, and by beginning, what brought you into your love of technology?

Oh, that is the beginning. Um, I was the, I was the nerdy kid in school, and in my primary school— I grew up in Cornwall, and we— it wasn't, it wasn't a lot of technology in my primary school, to say the least. Um, there was not a lot going on. And in my primary school, eventually we had access to these really old basic computers, which I loved playing on these. I think they were Windows 3.1 machines. And eventually we got this Windows 95 machine on a trolley. And it wasn't for every class, it was on this trolley and it would go around on this trolley to each thing. But I think when we had 4 distinct classrooms, and as soon as this thing came into the primary school, I was like, I'd want to get involved in this. So somehow I self-appointed the person that would actually look after it and go around from classroom to classroom showing the other kids how to use it. So I was, I was right in there with, with, with tech in a primary school. Um, I loved anything to do with computers, I loved everything to do with, with digital stuff. Anything that I could get my, my hands on that was, was techy, I loved.

Yeah.

Um, and I think that started it And then eventually got— we got a hand-me-down computer at home. My dad had the— I don't know what— DOS green screen computers. Sort of giving away my age a little bit. Not, not that old, but he had those that he used for various different things, and I kind of got into some of those. Um, but it was the, it was the hand-me-down computer we got at home. That was a Windows 3.1 machine I started learning on, and Okay, going on a bit, but one of the big things that got me really into, um, programming and software was that my neighbor gave me, I think it was 42 floppy disks to install— not, not floppy, I think they were the— I don't know if they were the big disks or very floppy. It was, yeah, but it was a lot of them to install Microsoft Flight Simulator. Yeah, to try and get running on this 3.1 machine that was just It was never gonna work really, but somehow it did, sort of. It was very low poly.

But you could just about take off and sometimes crash the plane into the ground.

Yes. And the internal speaker that was designed for the bleeps of boot up did the audio, sort of. Very crude, but it did it. Yeah, I loved that stuff.

And gaming's come a long way from that, hasn't it?

Yeah. Yeah, so even pre-getting into PCs and computers and things like that, I was desperate for a games console when I was— must have been 5, 6, and I got a Master System, Sega Master System. Um, I was desperate to get into that kind of thing. I loved it, absolutely loved it. I was always a generation behind though, unfortunately. I think without my family, couldn't quite afford all the latest tech. We're a generation behind. My friends then were moving on to Mega Drives and newer tech, and I was still on the Master System. I loved it.

Don't you wish you'd kept it? They're worth a fortune now, aren't they?

I've still got it.

Excellent.

I've still got it. I say I've still got it, my mum's still got it.

I sold my N64, which I used to play GoldenEye with the double joystick controller, and I loved that. You could have a controller in each hand.

Never did that.

One for view control, one for fine positioning triggers. It was absolutely outstanding. And we had the memory upgrade in it. It was a great machine and I sold it along with all of the games and it's one of the regrets of my life. But now there's a company that are making a new version of it which completely upgrades the graphics. So it still runs the original games. So I think I might have to get a new Nintendo.

Yeah, I've still got an N64. It's not mine. I re-bought one. As an adult. I got it off eBay with— it was almost like a job lot of just a big case full of games and stuff I've never even heard of. Um, but yeah, I never, never did the dual controller.

Was amazing, as was, um, Wipeout. I think it was Wipeout 97. That was just amazing, but that game crashed a lot. When it was working, it was brilliant.

Yeah.

We played a lot of that at uni, too much.

I don't remember games crashing on the PlayStation, and then— well, actually, I take that back. PlayStation was a bit twitchy, so I didn't go down the N64 route. I was, I was Sega, then went to PlayStation, um, Sega, this Master System, Mega Drive, um, somewhere in there. We was from some show or an event my dad picked up what was called a 32X, I think, which was the 32-bit extension for a Mega Drive. You plugged it in the top and it could play then 32-bit games, which were full 3D. And I think there were only two games we could get our hands on. One was a racing game, which was very cool. The other was a completely inappropriate for a 10-year-old, 11-year-old fighting game that was really gory. And when my mum saw me playing this, she was like, "No, I'm not having that." It was a bit much. But that was it, that was all you could get for it. But we repaired— somehow we got it repaired. We bought it broken.

Yeah.

And my dad was determined and somehow he got— he managed to get Sega to replace it, repair it, sent it off, they repaired it, sent it back, and it was good as new again, it was working. But they were quite rare. I don't know if we've still got that. Somewhere, because those are quite rare.

We ended up buying a, a second Nintendo Wii because the first one died, and we loved Mario Kart so much that we had to have another one. But we have acquired a lot of consoles as the kids have— I could say it was— I can blame the kids as they've grown up. It's not really because they haven't bought any of them. Um, but it's nice to have toys to play with occasionally, isn't it?

It is, yeah, yeah.

And you're playing one of the Dune games at the moment, aren't you?

Yeah, yeah, for my sins. Um, I'm not been into the Dune universe that much, and my partner got into the Dune universe and gone to the films, and I really like the films, and I picked up on it. She's been reading the books, and then Dune Awakening is— I've been following it for a while. Oh, this looks interesting, this looks like my kind of thing. It's not had great reviews. It's suffered quite a bit from development issues and launch issues and so on and so forth. I thought, you know what, gave it a few months for it to go through its sort of patches and improvements, gave it a go. I'm— I can admit that I probably sunk probably, I think, 120 hours into it over the last year.

I mean, over a year, that doesn't seem so bad.

Mix with other games. How do you find time for gaming?

I don't, I don't find enough time for gaming. I do enjoy it, but it's, it's too far down the list, so it happens very infrequently nowadays. But yeah, I'll get back to more of it at some point. But there's just so many fun things to be playing with at the moment, and if I'm playing with new capabilities, it feels like Christmas Day quite often. Um, with majority of the computer games that I love, they just require more time than I can dedicate to it. Yeah, so I don't end up doing it. I'll just play 5 minutes of a UFC or something silly. Yeah, get sore thumbs and then go and do something else.

Yeah, I'll go back to retro games every now and then. I'll play through emulators and I'll get, um, I'm quite a big fan of the Command Conquer series. Yeah, so I'll go back and play Red Alert and Generals and things like that.

Command Conquer is essentially the format that got me into coding, so it was Dune 2 just being able to go in and change the maps on that first sort of strategy game with real-time conflict. Yeah, building those maps and editing them made me feel like a god, and that's what got me into code because I just loved that, that feeling of power and control and the fact that I could use computers for something that I wanted to do, almost bend it to my will. And then seeing how businesses are struggling and seeing what's possible with the technology and just going, look, we can connect the dots here. And apply this incredible power for good within businesses is what keeps me excited and ultimately takes me away from computer games because I'm too busy playing with new AI capabilities.

Yeah, yeah, there's a massive part. I mean, there's almost too much to— it's almost too much to consume. There's so much going on. I mean, I've massively got into— I don't like the term vibe coding because I am— my background is development, my background is code. Yeah, I I guess to a certain extent I know what I'm doing, but the acceleration of that— yeah, I've got into that again, and it's, it's really— the last few months has really, um, it's brought the excitement back into it because it's, it's fun. Yeah, it's like having teammates that you can build stuff with, and suddenly there's so much. I just opened the lid on this and it's, it's fast.

Well, and if you combine it with teammates that you're having fun with, then it's exponential, isn't it? And I think we both come from a background of, if you can look at a problem and see a way to solve it, and you can solve that problem for one business, there's a lot of repeatability and reusability in there. So when we started talking around the concept of— excuse me— tools and the toolkit that we'd been working on, it just seemed like a natural synergy because we're, we're already doing the same thing with the same childlike excitement over the toys and that passion for sharing it more widely. So it felt like the natural thing to do, to join up and see where we could take it.

Yeah, yeah, it's funny because that, you know, how we, we didn't really know much about each other, especially when we started up. We were both— and we ended up with very similar names.

Yep, very similar company names, very similar. But ultimately, yeah, what we were doing in the more recent years too. Yeah.

And then moving on. Yeah. To recently and then going, oh, actually, yeah, we— you like doing this stuff. I like doing this stuff. What happens if— yeah, absolutely.

It's exciting times, I think, for both the technology and what can be done now for the benefit of AI into the sort of the small businesses that we love helping. But also what we can build together within Project Rising is just so exciting.

Oh, absolutely.

Yeah, I—

the technology itself is, is, is vast, even for, for me knowing my way around a lot of this stuff. Even for me, it's, it's complicated. I can't even imagine, you know, the complexities of any business getting into this going Where do I start? This is fast. And the speed as well. Yeah. You know, in the course of the last few years, how far things have come with AI, with technology, with live coding, video, so much.

Yeah. I mean, the capabilities are doubling every 6 months and the cost of intelligence is coming down by a factor of 40 a year at a data center level. That's just absolutely mind-bending because you can just see the path that effectively the cost of compute is coming down. But you look at that in the trend of the cost of intelligence, the cost of intelligence is trending towards zero. So it's going to get cheaper and cheaper and cheaper to do the thinking in something that isn't a person. And that's going to create some societal challenges.

Oh yeah, yeah, for sure. Yeah, this is a topic that comes up a lot. It's a really— that's one that I'm really interested in. I mean, I don't have a huge amount of background in the kind of economics of these things, but I do find it fascinating, the impact it's going to have on employees. The stuff that I've always helped businesses with around efficiency, you know, it's always been based on helping people do less of the stuff that they shouldn't be doing. The really inconvenient stuff, the really tedious stuff, the stuff that makes people go into an office, "I don't want to be here." And there's a huge ability with AI, of course, to replace all of that heavy lifting. Yeah, we've seen things with AI going, "Oh, it's drawing all the nice pictures, it's creating all the video, it's being creative." Okay, that one aside, we use it for a lot of the heavy lifting of stuff that we shouldn't be doing, the stuff that, you know, they're doing the laundry. Kind of in business. Yeah, has huge potential there. Um, and that's— it's exciting, but I can imagine from an economist point of view it's quite scary.

Yeah. And I think for a business, when they're looking at all of the different tools and products that they have across them now and how they connect the dots between them, they've— many businesses have got into a CRM as opposed to just having a contact list in a spreadsheet. Some still have the contact list in a spreadsheet.

Yeah, surprising a lot.

And actually, that's just as usable for AI as the CRM is. Yeah, I'm having a system and a process and quality data can be really confusing. And I think that there's, with all of these new tools and capabilities that are coming out, it's just getting easier and easier to have a list of subscriptions rather than necessarily something that's actually moving the needle within the business. So if we can have a conversation with an owner-managed business and go, here's what you're struggling with at the moment, here's a path to reduce that so you can free up your people to do more peopleing, to spend more on the time, on the things that they love. And using these capabilities, you can increase the amount of opportunities you've got. You can increase the profit from each deal you close. Then that's a really compelling narrative that can help lift the technical non-technical businesses in the area we're in up and not be left behind by this AI revolution. And that really excites me.

Yeah, absolutely. Yeah, I— it is scary for a lot of people though. You know, we saw a talk the other day about the jobpocalypse.

Yeah.

Um, as a topic. And I think for a lot of people, technology is kind of scary, especially when it's, you know, it's been framed as it's coming for your job and That can be quite intimidating.

It's not a good way, not a good sales pitch, is it?

No, not at all. But then it's affecting a lot of industries, especially around development, creative, and things like that. But the people that are using the tools are going to be the ones that really, really succeed. Yeah, they're going to be the ones, the businesses that adopt the tools, the businesses that go, actually, this is going to be helpful. And I really like what you said about, you know, getting people to do more peopling. It's, you know, if someone in your business can't be, can't have good conversations with customers, clients, and prospects, and so on and so forth, because they're too busy, because they are doing admin tasks or pushing paper around or fighting a spreadsheet and things like that. But AI stops that from happening, frees up their time for them to go and meet people, go and have a coffee, go and actually catch up and have a proper conversation, go and talk to people and do more of the people stuff. Then that's great. That's not just efficient, that's just a— that's a nice evolution of the role.

People buy people. And actually, the reason we're here together now is because of us both finding time to go out networking, to talk to businesses, to understand what's required, and to have those conversations over coffee, beer, food, whatever it takes in order to get to know the real challenges of business and get to build stronger relationships. So the more that we can help businesses do that, the better. Okay, so what worries you about the rate of AI?

Oh, what worries me about the rate of AI? Um, that's a really good question, and because there's several answers, uh, several topics. I think people not— I think we touched on a little bit, which was general public not adopting, being scared of AI, being fearful of AI, that it's coming for their jobs, that kind of thing, and not looking sort of beyond that point and going, okay, well, what actually difference is this going to make long term? The speed at which we're moving is is kind of scary.

Yeah.

You know, we've got things with like Claude Opus 4.6 showing some strange responses to behaviour and doing some interesting things with circumventing, not circumventing rules, but finding creative ways to do things that it was effectively stopped from doing through some basic rules. I do wonder where that's gonna go with AI. The speed at which we're moving, where I'm not gonna say like we're gonna have a sort of Skynet type future. I don't know if that will go the way. If I was to put money on it as a where is it gonna go, I think we'll all, it won't be a terrifying future. It'll just be a very relaxed future. I think we'll be very, a lot of things will be taken over by AI, but I'm gonna go way off topic there into a different area.

So you think we have a future of effectively great abundance where AI and robotics frees up time and increases the output of society as a whole so that we have the ability to choose what we do with our time?

Yes, but I think that in itself will create a whole different type of problem because I don't think the human race as a very work hard, we do things kind of— suddenly being— we're basically facing a time where actually we might not have to do as much.

Yeah, a lot of people get their, their reward function from the job they do. If you, you meet somebody new, one of the first questions is, what do you do for a living?

Yeah.

And you can see the personal validation they have when they share what they do, sometimes with pride, sometimes with, I hate my job, but but it delivers value to a lot of people. So how do they get that if that's being done by something else?

Yes.

And how is their lifestyle funded?

Yes. And I think that is where it comes to, back on the Jobocalypse thing, that is a factor of fear in it, I think, as well, is, you know, something that— what if AI replaces something that gives me purpose? And then as a developer as well of code, that's a writing code, I used to like really doing that. I've adopted AI into my workflow because actually seeing results faster and not doing some of the grunt work, setting up projects, the same thing over and over again, dependencies and all this kind of stuff. Actually the speed at which I can skip over that and get to the good stuff, that seeing it work, seeing it prototype, seeing it, messing with it and playing with it. Is the bit I really enjoy. And getting there is good. So I've— it's not a fear for me for that. It's— that's been a good thing.

For me, the joy of coding was the idea to the dopamine hit of I've got a bit of that idea working. And I can still get that. So I'm working in combination with AI and I'm making sure that the idea that I've got is described in a way with enough detail that it's gonna get delivered. And I get the dopamine hit when I see it working. Now I haven't directly delivered that, but that relationship, that's a strange word to use, but that relationship that I've had with the AI has delivered the outcome that I wanted. And I really like having a nicely kept short lawn in the garden in the summer, but I didn't like asking my son to mow the lawn on a regular basis. So I got a robot lawnmower. And now I've got that nicely kept lawn and it looks after itself. Yeah, the lawnmower tells me at the end of the season, can you put me out and can you put me in the dry now? It's getting too cold and wet outside. But that has allowed me to enjoy the garden more because the time when I would have spent in the garden at the weekend, I'm then not forced to do a list of jobs. So I think that almost symbiotic relationship we have with technology means we can get more done for personal reward. I'm looking forward to the ability to read more books, to spend more time outside, to spend more time playing, producing music, because we've just been so busy doing everything that is our day-to-day. And I think working in combination with AI is going to give people a lot more freedom and time, providing they're using it in the right way. And for a common good.

It's going to be an interesting few years, the next 10 years. The way the industry works, the way that even capitalism works, the whole society and machine with AI is going to be really interesting because it does change a lot of things. Yeah, about the way we work.

And I don't think anybody can really read the tea leaves and say definitively what's going to happen. So if you were to look on a short window and we say 18 months, what sort of changes do you expect to see in the next 18 months?

Bring that focus back into that short term. I mean, at the moment we're using tools which are, still require a lot of human intervention, a lot of steering.

Yeah.

You know, especially code tools. But even over the last few weeks, we've now seen things like Claw, the Clawbot, an agent spawning, and Claude— get the two, their names mixed up, they sound so similar— spawning agents that can do sub-work. Before, it's just what I'm using at the moment is mostly me and one AI to do things, and it's systematic. We do something, then we test it, play with it, move on to the next thing. I saw a guy the other day that did a test where he was like, well, can I build something entirely overnight? I'm gonna write a very short prompt of what I want from the app, pop it in, and then just walk away. And by the morning, I should have a fully running app that I can download in TestFlight. So gone through the entire process. You know, not just building a working version I can test on my machine, but actually, deploying that code into an app environment, getting it installed in TestFlight. So going through the TestFlight online process of uploading the app and installing it and so on and so forth so that it was ready. That's, I mean, that's only happened in the last few weeks, it seems to me. So in the next 18 months, it's really hard to tell the speed at which it's moving. It's vertical now.

Do you think that there's a, a lag between capability and adoption? Because we can see what's possible in terms of analyzing, understanding videos, producing videos, understanding, well, text, audio, video, image, producing output and cutting across those modalities and a really detailed level of reasoning. But actually deploying that, the capabilities that exist now within businesses, there feels like there's a comprehension gap.

Oh, massive. Yeah, no, so this day, so this, this, it comes to my experience from working on my own before joining Project Rising, which is, is amazing how many businesses are sticking with the way things have always been done. And we talked about spreadsheets being still, people using spreadsheets for a CRM. I see it, the people I've worked with, people I help, people I even mentor are using the most basic tools that are advanced if you spin back 10 years ago. But there is this massive lack of adoption, massive lack of competency, and also massive lag promoted by fear as well around how does this work? How would it possibly work? What kind of impact's gonna make? There's, we like our comfort zones. As humans, we're quite comfortable in doing things the way that we've always done them because they're safe and they're predictable and so and so forth. And so moving from one piece of technology to a seriously advanced piece of technology is quite a big leap of faith. So yeah, there is a huge lag in businesses adopting this technology, but then there's becoming a huge gap between the businesses that are adopting it And the ones that are not are getting left behind quite quickly.

Yeah. We had an interesting sales conversation with a customer last week where part of their process involved the creation and population of a spreadsheet. And you and I were having the same thought internally, which was you don't need the bloody spreadsheet.

Mm-hmm.

But actually within their business, in terms of getting the first phase of change deployed, the easiest thing for them to adopt was for us to populate the spreadsheet automatically rather than have a human populate it. And then them use that spreadsheet. Now we know that that's not a, not really making the most of the technology as it exists currently, because that's an extra step and it could be fully automated across the process. But by minimising the change that they were experiencing, we were still giving them amazing capabilities that was going to save them hours per week. And we just had to bite our tongues a bit about the fact that we were giving them the output in a spreadsheet because that's what the way they needed to see it for now.

Exactly. Well, you, you soon hit up against change management.

Yeah.

You know, in the, in our territory that we operate within, although change management is a specialist subject in its own, and it's very much to the psychology, psychology of people how they operate. That is a perfect example.

They did.

And we're like, this is our safe first step, although it could be magical all the way through to practically fully automated. Didn't need the spreadsheet at all. I probably didn't even need a view on it. Just need an output to say yes, no. Just a huge small human intervention at the end. But that's a big leap. It's a big scary leap.

It is.

So yeah, little, little steps. But that's, that's the thing, you know, you can do that and go, okay, well, we've now got this spreadsheet, it works perfectly well. What's the next little iteration to make this a little bit more efficient? A little bit more efficient.

It's baby steps, isn't it? And some businesses, the, the best change that we can deploy is one that is utterly silent and it just does magic. We've got another customer where they put a transcript from a meeting, so they're using Fireflies to record the meeting. They take that transcript and they put it in a folder that says add new transcripts here. And an hour later they've got the output in the folder that's called the output next to it. And for them, that's the perfect model. They don't need to know how that output's been produced. It's just giving them something that's super, super easy for them to use. So I think often within new system development we get all caught up in the customer journey, the perfect user experience, the best interface in the world. And often the best interface is one that somebody isn't actually touching. And if we can deploy AI in a way that is seamless and invisible in a business but delivering benefit, then that's, that's the ideal, isn't it?

Yeah, yeah, absolutely. I mean, that's user experience 101— less friction. What is the minimum amount of friction? And if it's something that can operate with little friction, little intervention, little requirements from you to even do anything, then great. And those are the admin tasks that drag people down. It's the amount, the sheer amount of intervention required for moving data around in a business.

And that's a beautiful place to bring us into your first major experience within Project Rising of data in lots of different places on our sales process. So you've been building something over the past week and a half or so to help with that. Tell a bit about that journey that you've been on.

Sure. Yeah. So not to throw Processors under the bus too hard, but it's a very—

The plumber's always got leaky pipes.

Yeah, true. But it's a— it's typically the kind of business that I've always worked with as they've grown. The tools and the systems and the process they use haven't kept up. And I've suffered it myself, suddenly realizing that I am the silo of all information. I am the wiki. What if something happens to me? That was the worst case scenario. I was like, what if I have a car accident? How's the business gonna run? How is it gonna operate? And there's a book, it's just a, To preset this, there's a book I absolutely love called The E-Myth by a guy called Michael E. Gerber. And have you read it?

I haven't.

Absolutely recommend it.

Will do.

Generally the premise of the book, The E-Myth is the entrepreneurial myth. And the story of the book is basically how a lot of entrepreneurs are born out of, I could do this job, I'm not getting paid enough for this job, I'll go do it myself and get paid more.

Right, everybody should laugh at that point.

Yeah, yeah, it is the— it's the key thing. It's a— yeah, yeah, and it happens all the time. Um, I did this, I went through that process, and it's not a great use of the word, but he— but I quote, he uses the word the entrepreneurial— can't say it— entrepreneurial seizure. Um, don't like the term, but It's the way he's written it, where they suddenly, somebody has that entrepreneurial moment. I can do this. I'm gonna get paid. I'm gonna go ahead and get it, get business and get money and so and so forth. And so they go out of it and they go out in what's called the technician. And Michael splits it up into 3 things, the technician, the manager, and the entrepreneur. The technician is the strongest personality. And what people do is they go out and they start working in the role and they start doing the thing. And before they know it, spin on a bit, they build themselves a job. If they escape that and the entrepreneur does start to kick in a little bit, they start to hire people. And what happens as a business grows, you start hiring all people in, they come in with their own ideas, they're coming with their own influence, you've got bits and pieces all over the place and it becomes a sporadic mess, but somehow it works. And I think that's probably what I came into with the sales process in Project Rising was it is working. You're selling, you've got projects going through, you've got proposals being written, you've got things being signed off. To a certain extent it is working, but it's fragile. Something goes wrong in that process or one person in that process—

Or somebody isn't updating the CRM appropriately.

We're not pointing fingers at anybody, Tim Davies. The things start to slip. And the problem is those issues compound over time. So the more you're not updating the CRM, the more that problem becomes normalized. And before you know it, you've got thousands of records in a CRM that don't have enough information attached to them because it's become part of the normal process. The process was never changed. So that got me right in there with the, okay, what is it? It also started with a question. I pretty much came to you and went, Tim Davies, what is your sales process and can you walk me through it? And I will admit you did look a little bit scared.

Did I? Did you see genuine fear?

A little bit. Realisation that I've brought someone in to work with sales.

I knew it was broken and was waiting for that question to be asked.

Yeah.

And we were able to dive straight into specific deals that were in flight and go, okay, here you go, have a look at this one. And that then just lets you, okay, where's all the information?

Yeah.

Well.

I knew the answer. I knew the answer would be a cringe and a worry, but that's absolutely fine. That is literally what we'd been talking about, you know, for almost months actually before I joined. We've been having these conversations about what can we do and how can we make things really work and sing? So getting into that sales process, big task. And so I started looking into it. And one of the things I quickly saw was that, yes, you do have information all over the place. You've got really good data. You know, using things like Fireflies as an AI note-taker and transcripts for meetings is gold. Every business should be using note-takers. Even if you're really good at taking notes.

You can't beat a physical record of a meeting.

Yeah. It's great because it aggregates so much more data than you can possibly capture. And for me personally, I know that the reason why I have an AI note-taker in meetings, or even if I just had transcripts, it doesn't have to be AI-powered, just transcripts, because I'm really bad at writing notes. I like to talk and I gesture and I'm engaged with the meeting and I like to look people in the eye. I don't want to be doing this sort of thing. And I like to be fully involved. But that means you've got a lot of data in Notes, got a lot of CRM data, we've got a lot of email data, we've got other bits and pieces now starting to pop up all over the place. And quickly I could see that the individuals involved in those projects are highly knowledgeable. I could ask you about something and you'd be able to tell me all about it, a particular client, particular projects, and so forth, including a lot of legacy knowledge as well. You know, we have one particular one which when I asked about it, oh, actually had a whole legacy piece of background to it. And I didn't know that. I couldn't get that from the CRM because it was not noted. And I couldn't see that from any of the recent transcripts because it wasn't discussed. Because it wasn't relevant. But you have that knowledge. And so getting my teeth into this, I started to realise, okay, very quickly, it's very difficult. And I asked you very early on, I said, oh, can we not just feed Firefly straight into HubSpot? And you said it's not.

Well, yes, it just doesn't actually do what it says on the tin reliably.

Bingo.

Same with emails.

Exactly. So, okay, okay, well, so we're trying to force these systems that don't really talk very well to each other in lots of different places. And I think, well, I still want the CRM to be the source of truth because somewhere needs to be the source of truth.

Yeah.

If I ask a question, tell me about that client, the first place to go to should be consistent.

But it's not the data master, is it?

No.

And it's okay to have separate data masters?

Yes.

And you need a brain in the middle, don't you?

Bingo. Which is exactly what I decided to call said thing that I'm working on, the sales brain, um, which combines the two parts. One was my general knowledge of the sales process within Project Rising, how you operate, you know, how you talk to leads, how you communicate with people, the follow-up, the processes you go through. When and how you produce a proposal, the questions and things that you ask during meetings for particular products like, you know, the Reach app.

Yeah.

And as I was learning about that, I was also learning about the questions that you typically ask clients in meetings, which help them decide if that is suitable for them and how it can help them. I didn't know any of that. I learned it. And I could go back through old transcripts and pull out even more information from those. Which is great for me. Lots of, lots of harvesting details, a lot of digging. Yeah. So when I started to look to build, which is a kind of prototype version at the moment, is a sales brain that is a client profile somewhere that actually takes all that information from lots of different places. Like I said, masters of information. So transcripts, emails, calendar events, SharePoint. Yeah, SharePoint as well. Yeah, exactly. So we've got documents in SharePoint, we've got Excel spreadsheets that have been used legacy-wise for pricing structures, which are slowly getting replaced with newer tools that are currently being built, which are fantastic. The things that Ollie's been working on are so cool when it comes to the project documents and proposals. And eventually that will be used instead of older sheets for pricing.

Yeah.

And there's lots of these pieces of information everywhere. So what the SalesBrain is going to do is bring all that information into one place, build a client profile, and expose all that information to me in a list so I can see all the conversations that I've had. It's then going to do something magic with that. Now it's magic in a way to me because this is AI magic. This is technology indistinguishable from magic. Although I know how it works, I'm going to get my sales brain AI to aggregate that information together and pull the relevant bits to build a deal profile. So the current conversation that's having with a client about a certain thing that they want, there's lots and lots of pieces of information in there. Lots of conversations, hour-long conversations that could span months. I don't need to go back through all of those. And to challenge somebody to go back through all of those, a salesperson, is quite a lot of heavy lifting. So the AI can go in there and pull out all the relevant information, just key bits, and aggregate that into one sheet of answers. This client is interested in this thing. They are showing this kind of enthusiasm. They've got these kinds of future plans. They've got this kind of, uh, let's say growth plans, future plans, their current positioning, their finance, their budget, without having to trawl through all of those old systems.

And here's the history of when the last contacts have been made. So you've got all that in a central place.

Exactly.

It's magic. And it's magic actually that applies in any business. And so the conversation we then had is this is a tool that needs to be in Toolkit. We're effectively prototyping on our own problem. But every business has the same challenge. They might have different data masters, but we just have a universal connector that goes to the right information source, and then we can have something that enables any sales team to perform at a higher level.

Exactly.

It just excites me so much.

But it's the one critical thing that you said about not changing the way people do things too much, and this is a change management thing. I'm not building a tool that circumvent or replaces any of the existing tools we use. And one of my really key rules in building this is do not replace the CRM. That is, it's written at the start of my spec, not to replace the CRM. I don't want to duplicate anything. There's no point because one, duplication, major data problem. Two, asking people to do something different to what they've already done and what they're used to is really difficult. And if they can carry on doing things which are perfectly fine, using the transcript notes, having meetings, emailing, that's all fine. That's all perfectly fine process. And I can do something with that data that takes no effort for them, then that's great. So then it happens, as you said, magically in the background. There's no resistance to it. There's no inconvenience to it. It doesn't slow down any of the existing processes and it just works.

And I think we will have a situation where actually the CRM becomes up to date because when things are seen and identified by the sales brain that aren't represented in the CRM record, they can easily be added. So we can log this, this meeting happened, this call happened, this email exchange happened, even if it isn't represented in the CRM currently because one of the connections hasn't worked, for example.

Yeah.

So we're not getting away from that. Excuse me, the Data Masters, where we're leveraging the information within the business to accelerate the decision-making. And the power that comes from those insights that we can then give to a suite of agents to take action, it's just so exciting, so powerful.

Again, it takes off the heavy lifting that people can do more peopleing. Yeah, you know, the, the going into CRM and typing up a task to go, I've got to remember to go and I'm doing the typing on the desk now, the typing up and doing that. So you've got 10 clients, you can type all these tasks, go look in my calendar, when can I, when can I fit it in? I think I can get some time in that day to follow up with that client. What if they're not available? There's so much. It's tedious. It's painful. Now you hand that over to an AI agent that can go into your calendar. And send an email to a client, say, hey, are you available on this date? Oh no, I'm not available on this date. Can you do this date? AI checks it. Yeah, that's fine. I can actually do that. It comes back to you, say, by the way, I've booked you a meeting with this client for a follow-up because they've been— they're in the sales brain. We haven't spoken to them for a few months. It's about time. They've shown some signals. By the way, I've noticed on LinkedIn they've been posting some things. You as a salesperson, that just makes your job easy. You just say, okay, great. I will have a phone call with this client and I will do the peopling.

Absolutely. Free up the people in time.

That is, that's the number one thing I love about AI is freeing up time. Absolutely.

So this tool is going to make an impact within Project Rising. Well, it already is, but tomorrow, the next day, the day after, and then how we make that into a universal tool so that it can be used by any small business to accelerate their sales processes. Is going to be really interesting.

Yeah.

When we started our conversations around tools and a toolkit and IP, what went on in your mind? What, what made you think that we need to— that there's benefit in working together on this?

Uh, toolkit and Product Rising's approach to the toolkit that you're, you're developing and we're now developing. We're developing. Yeah, it was, it was your— when we first spoke and now that we are developing it, it's accessibility and access to these tools and systems that are— there are so many different things and a lot of them are very high, high requirement. You take any kind of existing AI tool and they're big, scary.

Yeah.

A lot of integration, a lot of requirements, quite heavy on the technical side as well. You have to be fully involved in it. And the thing that I loved about Toolkit was these are little and often things that solve very specific problems that need solving. They're not complicated. They're not going to require me to have an IT degree to understand how they work. I can just use them. And I really love the idea that as a client, I'm not beholden to some one big complicated system I have to fully integrate everything with. I can pick and choose the stuff that is relevant to me that is going to make my life easier today. And I can start today. I don't have to, you know, go through a long tedious process of onboarding. I like that.

That outcome-based still excites me now. And one of the tools that we're just doing final testing on is a subscription finder where a business can simply connect, give authority, and it goes off behind the scenes and reviews all of the subscription emails in all of the company email accounts and brings back a list and says, here's all the subs you've got. Now, you've always done a great job of keeping a check on the subs within a business, but as you scale in terms of people, it gets away quickly.

Yes.

And I think this is going to be a compelling tool for almost any business to just very quickly see, okay, here's the list, here's the repetition, here's the opportunities. Actually unsubscribe from that, that, that, that, that, that, that, that, that. The agent executes the unsubscribe process, and here's the money that you've saved by directly using Subfinder today. It's a silly little tool in the grand scheme of things. It's not something that's going to change the world, but the benefit in terms of immediate cash flow to a business is huge. And I know Ronan's had a lot of fun building it. It's, it's one of these tools where we're effectively, we're testing early career talent on a specific project, giving them feedback on a regular basis. He's working on it around his studies, but has now got it to the point where it's going to deliver benefit to lots of businesses and will be able to just roll it out within the toolkit to anybody that wants to use it. Yeah, I love it.

Yeah, no, I love the idea. You're right, the scale— at a small scale, yeah, I can look through bank accounts and then some credit card bills and go, oh, that's probably a waste description. I couldn't even imagine trying to do that for a company that's got 100 employees. No, the stuff they must be subscribed to, it must be vast.

And things get hidden under— some will be under direct debit, some might be standing orders, some might be on a debit card, a credit card. And so we're effectively ignoring all of that noise and just going straight to the source of you're sending subscription reminder emails. We can see all of that detail. Let's extract from that put it in a simple table and go, here's your opportunity, what would you like to save today? Yeah, it's just making things easy to use.

I mean, I had a subscription once that went straight under my radar because it was quarterly. Yeah, missed it and didn't— just didn't notice. I'd see the email, forget about it, and then yeah.

So we struggle to look out 18 months ahead, let alone 10 years ahead. What differences do you expect in the next 6 months?

Differences in AI itself, the industry, or differences in the way businesses are approaching it?

Pick your interpretation. Okay. I don't think businesses adopting is going to have changed a lot in 6 months.

No, and I don't even think in it. I think there's still going to be businesses using spreadsheets in 5 years and 10 years that I'll be probably running off them.

If they were very successful in the first place, they might continue to be without using any AI over that time.

I still think they'll probably have AI. It's just that a lot of old ways of doing things, because they're so people relevant.

Yeah.

You know, it's 10 years in someone's career is 10 years. That's, they'll probably still be there doing things and going through the ranks and stuff like that. But there's things that they've learned in their original way of doing things are probably still relevant and they'll still be doing it in the same way. It's not until an entire generation is starting to replace people in a business that you'll start to see adoption of technology, especially younger generations that are literally growing up in school with AI now. It's the way we do things. It's what we test things with AI, we challenge with AI, we learn with AI. And they'll go into business and go, you haven't got anything that I can use.

If the businesses are recruiting early career talent.

True, true.

So coming back to the 6 months then, we don't think that businesses adopting is going to be a big change.

No, no. But I think the speed at which, um, AI is developing at a phenomenal speed, in 6 months we're going to see a lot less big tools. I think things like big SaaS products, they aren't— I mean, the threat at the moment to massive SaaS products is that most people can now build a SaaS product in a weekend that replicates, you know, things that the big players have done for years.

I don't know how secure those solutions will be, but they can definitely replicate the functionality.

Yeah, but that's the thing, you know. Yes, they'll be probably insecure. Yes, they'll have API keys exposed all over the place. But the people learning these, how to build these tools, are learning those problems really fast as well.

Yeah. And more importantly, the AI tools will be able to tell them, wait, you've left this exposed. You've got your API key here. We can't do that.

Yep.

So that will improve.

Yeah. I built a plugin the other day for WordPress. Very simple thing, but I, but it had the ability to upload files. I thought, well, this is quite risky because I'm uploading files into you know, a directory, those files, how could that be exploited? And I challenged Claude code to go and find the issues, go and look at what could potentially be exploited here. And it highlighted— I thought of a few things myself that could definitely be exploited, but it highlighted more stuff than I even would have thought of. And it helped me patch those things.

Yeah.

I thought that was fantastic.

I think the sooner that there is a dedicated agent for penetration testing that can be used by any of these AI models while they're developing something so that it's automatically identifying the potential exploits and fixing them on those early builds. Yeah, you can just see it's going to happen.

Well, that's, that's, that's certainly a thing I think is going to happen in the next 6 months, is swarms of agents doing things as opposed to, you know, singular points of— it's not just, I'm just not talking to ChatGPT anymore, I'm not just talking to Claude, I'm now setting off an instruction and agents are working between themselves, AI agents working between themselves to complete that goal. Yeah, and each of those agents is a specialist in its own area with its own knowledge, with its own experience. And experience is not the right word, but expertise in those different areas. And then we'll come back with a complete solution. It won't be something that I'll piecemeal put together myself anymore, you know. And I, and I'll be doing that from my phone whilst I'm on the sofa, sending that instruction off.

It'll go. So effectively, anybody that has a good idea and can describe that idea in a way that they want to be able to make the most of it, can become the master of their own technology destiny. We'll see how good the ideas are, won't we?

Indeed.

I think the challenge that we'll continue to see is a lot of businesses don't have the breathing space to come up with those ideas, to take a step back and look at what could and should we be doing in that space. So solopreneurs will be able to go, I want an app that does this. Um, and many of them will think, I, I've made an app now, I can make my million and retire somewhere. Not that you can retire on a million really, but, um, and then they'll say, actually, the challenge isn't in making something. It was never really in making something. It was getting people to use that thing in the first place. And so that change management piece is going to come back because sure, Joe Bloggs in their bedroom can build a SaaS solution to manage their accounts, to manage their customer relationships, whatever else they need. But they've still got to use it. Will they? So I think we'll still see an adoption challenge with technology, and we're just going to see a huge volume increase in the number of things that are built. And in the short term, I think that probably increases the need for software developers. Because they've actually got the understanding of how to build something in a way that it's going to be a great user experience rather than just however Claude or GPT or anything else decides to imagine an app. We've seen with our wireframe designer, you can build beautiful wireframes, they all look quite similar. And I think we'll get to that same level of same sameness in output that you see where you can immediately identify something that's GPT copy just from the structure, the use of language. We'll see the same with images, we'll see the same video, we'll see the same with applications. And people with a keen eye will be able to go, well, you've just used Claude to build that, and I can tell because of ding, ding, ding, ding, ding.

Yes, I think that's starting to happen. Already. And I've noticed in some of the builds that I've been doing where putting together basic UI, there are starting to become patterns in the way it interprets those things. And trying to nudge out of those patterns is quite difficult. It's clearly the way it's learned how to, you know, how to make a box, how to make a button.

But it just comes down to how you make the request. And so in the same way as you— if early on within ChatGPT you'd said, write me a 500-word blog about cheese, it would be cheesy. If you were specific and said about Stilton, the heritage tasting notes, you're going to get a completely different quality of output. And now we're seeing the same with code. If you provide a repository structure, language specifications, detailed libraries that you should use in order to maintain look and feel and consistency, you can get high-quality output, but we know that because we've been in there and been exposed to it. Whereas if you're vibe coding something, you're just at the whim of, I've got an idea. Yeah, that looks roughly right. Actually, can you make that color a bit greener? Yeah. Can you move that button? It'll do those sorts of things, but it's not going to give you the consistency yet that matches specific company objectives.

Absolutely. Yeah. And we're seeing developers that are writing less code, they're becoming architects. They are now becoming designers of systems that before they would get bogged down with a lot of the base level stuff to build things. But now their knowledge has been translated into the overall architecture of a system, how it all works, how it all flows. Case in point for individuals who are not used to these kind of things, someone that I knew was building a wanted to build his own platform. He was using Glovable.

Yeah.

And went down the route of building it out and starting to see real good progress, really excited, loved it. Oh, this is great. Didn't work. Why didn't it work? And it's just those considerations around, well, it's following this exact path that you're explaining to it and doing exactly that, but it's not considering the bigger components of how it works. Eventually did get it to work, a lot of nudging, and Loveable itself suggested something. Oh, it suggested a way of handling these tokens that would expire with invites. So you'd invite users to the platform, the token would expire after 30 days, and that would re— and then you'd have to resend it again. Perfectly logical. However, the way it built it would somehow mix it in with the parent account so that after 30 days, the parent account is expiring.

Bish bash bosh, gone data.

Yes. And logically, I can see where, how the AI came to that conclusion. Well, I'm sending an invite, the invite's expiring, so therefore expire the account, right?

Yeah.

So it got there through logical, but because the chap hadn't thought of it from an architecture point of view, he hadn't thought of it as a, you know, what if scenarios, things like that, you end up with a major problem and Yes, leading to catastrophic data loss in a public production-level product. Wow.

I think almost the role is bigger than architect. So architect is great for seeing how the system works, but I think the role of business analyst and business partner from IT to business in corporate has always been one of the most underlooked roles and actually is the most impactful one now. So understanding what a customer needs, seeing how technology can be applied to solve that, and describing that in a way that can then be built is a role that's going to continue to exist because it combines that peopling, that understanding of a broader space with what's possible, and doesn't necessarily need to be involved in the build. That build process can be automated, but I think our roles will continue to be in that space.

That's exactly actually where I've been over the last sort of 10 years. Yeah. You know, going from the sort of coalface of doing design work, pushing pixels around in Photoshop and things like that, to being the person that actually talks through these business problems, identifies those business problems, identifies those opportunities, sees the faults in process that get easily overlooked and forgotten about because they just become normalised. And yeah, you're right, that is a huge evolution of my role in these conversations with clients. I'm not sat there saying, oh, we should use this piece of technology or this piece of code or this tech stack. That's not relevant. They want to know how is it going to impact my business? What changes is it going to make? How is it going to affect my bottom line? Am I going to get more time? Am I going to get less time? Am I going to have more problems, less problems? And exploring all of those things that come down to real business-level issues, not just software. Yeah.

And it's how we create unfair advantage in how we apply that technology into a business that will be so influential. We've got a lot of businesses to help. We ought to stop talking and crack on with it.

Indeed. Yeah.

Fantastic. Welcome. So glad you're with us, Jackson.

No, I really, really enjoy it so far, and I'm really looking forward to what we're going to get up to. It's going to be great fun.

Definitely.

Awesome.