Rethinking AI: Why Collaboration, Not Replacement, is the Future of Work with Tim Lidman (Clyde AI)

Well, hello and welcome to the super Connector Show, where I'm delighted to be joined by Tim Lidman, who is the co founder and CEO of Clyde AI. He's previously worked at Cisco and SAP and a company called think Tank, which was acquired by Accentia, and he then joined ac Centia as one of the directors managing director, I believe, but he's now developing this new AI native collaboration platform that helps humans in AI work together on real problems and real outcomes. So, Hi, Tim, thank you very much for joining me today.

Thank you Paul for having me. AI. Obviously everyone's talking about AI. I think every conversation and every event that we run or every meeting that I have, at some point comes up.

So do you an your own words? Do you want to explain a bit more about what Clyde is and who it's for? Yeah? Absolutely, let me let me explain that brief and I think to understand what Clyde is, it's helpful to briefly jump back in time to the previous startup that I rand that you mentioned it's called think Tank, and you know, you mentioned something before we started recording, which was that it seems to be, you know, a big, big hammer just looking for nails, right, It just seems to be this technology that is constantly searching for use cases.

As opposed to the other way around. And Clyde very much was born out of the almost the exact opposite of that. And so if you look back at think Tank. That we ran for eight years before accenture about it, you know, think Tank was a collaboration platform that helped primarily consulting firms drive their client engagement and collaboration in in a far sort of different different way.

So instead of showing up with PowerPoint, excel Miro, whiteboards and sort of myriad of tools, they would show up with think Tank, which had a very structured way of guiding a group from a problem to an outcome. And it was based on decades of research in sort of behavioral science and the specific topic. That was called Group Decisions support Systems. And what it was is it was research in how do you not just go through a series of steps, but how do you do that in a way where everyone has a common understanding, everyone's aligned, and that the outcome you get to is effectively bought into, which means it's a decision that's going to stick.

And so when Accenter bought us in twenty twenty one, you know, I operated as a partner there for about four years thereafter, and this is right when Jenai hit, So this is now twenty twenty to twenty twenty three, and what I realized was that AI was becoming progressively more advanced to the point where it could actually start automating parts of i'll just call it the consulting workflow, which is an oversimplification, but you can start automating parts that it previously really couldn't do.

One of the challenges I had with think Tank was there was always, even though we were supporting sort of the end to end engagement workflow, if you will, of how you engage with a client and collaborate with them, there was still a lot of human, heavy manual effort that was going into parts of that process, particularly around being able to do the heavy lifting of actually designing, for example, a workshop and the. Wheel reinvention that was going on. And constantly having to sort of design these new experiences, the real time synthesis that had to happen when actually engaging with a client.

So you know, think about panicked coffee breaks, having to organize post it notes and try to theme them and make sense to them. And then the kind of the poor analyst at three in the morning that has to put all this together into some client ready output and you know, ready give that to a client for for output you know, the next day. So I saw these all these areas where if you used AI effectively, you could really compress a lot of that quite expensive in manual effort. And so you know, leftic censure to then go build Clyde with the with the hypothesis that the AI could really take a lot of that effort out.

Now, at the same time, if you look at what was happening in consulting, in what's currently even happening. More so in consulting, you know, all the senior leaders the industry are pressuring their people to heavily use AI. You know, they're basically saying, if you're not ten x more productive, you know, you're out. Or you know, if you don't adapt to AI, you're out.

Some large firms. Are even measuring their people on AI use through tools and having that as the basis of their performance review. Right, So there's this insane pressure to adopt AI but one of the challenges is is on the ground. What's happening is these consultants are having to stitch together multiple llms right as part of their workflow.

They're having to learn how to be you know, prompt engineers, context engineers, loop engineers, and. Effectively having to learn all these skill sets. Whereas the promise of AI and LLMS is, you know, you've heard this whole software is dead argument, right, this whole acalypse all that right, And the premise of that is that SaaS forced you to align to their paradigms, but AI allows you to talk to them in natural language and kind of puts the onus on the LMS to interpret your paradigm.

And it's kind of shifting that whole dynamic. But I call kind of light bs on that whole story because lllms are still forcing us to adopt to a whole paradigm of their logic and being able to set all the right context bring in all the right skills, pick the right models, you know. So it's becoming this just this replacement of another big piece of noise, and so the consultants are then creating these Frankensteins of different lms different skills. They're using traditional tools, where they've just slapped AI assistance on all their legacy tools and then they're left to go figure that puzzle together while still.

Doing their normal jobs. Right, the traditional always are working. And so as I had that hypothesis of oh wow, we could take a lot of WAISTE out of the system, this sort of market convergence is happening at the same time, and so it was all very very timely, and. So then when we set out to build Clyde and now we'll get to what Clyde is.

One thing we realized very quickly when we were building Clyde is that there are still lots of things that humans are very good at and that humans should remain good at that AI probably shouldn't take over. And some of those things are. You know, invention of new information, right being able to actually idate and create together AI still based on pattern recognition, right until they find a completely new technology paradigm. That's always going to be the case, and so AI is not able to invent new information.

So that was one area where as. We were building Clyde, we realized we have to build UX on top of what we're building that allows people to brainstorm ideas together. That allows people to theme things together, That allows people to work through and process information themselves. And what we started doing is we literally wrote this list down of what are humans really good at and.

What is AI really good at? And yeah, the humans were emitting information, Like I said, it was also making informed you know, human judge decisions, right, so being able to really take all aspects of something and make an informed decision. AI, in my opinion, is still very terrible at making certain disc decisions. Yet Microsoft published a report that said that I think it was thirty eight percent of all use now of AI is used to drive decision making at the enterprise level.

We still believe that humans have to do that also until they automate leadership and CEOs, Driving change and actually implementing decisions is another thing that we think humans. Still need to be able to do. And so so. Then what we did is we we use that as a guiding principle in building Clyde.

And so what we ended up building. Was a platform that allows a user to give Clyde a problem. Our main user is a consultant, So you know, a consultant would give a problem of you know, I need to build a proposal for this client or my client needs to optimize their supply chain, whatever the problem the consultant has. And then what Clyde does is triggers a workflow that has all of that behavioral science research I was talking about sort of built into it.

And the first thing Clyde does is Clyde will assess your problem and work with you to actually refine it to a place where it is a well defined sort of problem statement. And what this does is in the process of doing that is it extracts the intent and the context from the user without you having to be an. Expert prompt engineer. Right, so we're putting the onus on us as a platform to be able to really understand what the users trying to do, and then in the back end translate that to Okay, this problem then requires a combination of these different models, you know, at these levels of difficulty, you know, in terms of you know, the medium to hide a maxim effort models, and you know, we sort of then translate that to how AI can help.

The other thing we do is we then. Assess what type of expertise is going to be required to solve this problem, and that can either be human expertise or AI expertise. And in the case where it's human expertise, Clyde actually has capability to invite other people into this workspace too, you know, explain to them what their role is going to be, that they need to provide ideas, they need to make decisions, you know, they need to get bought in whatever it is we're asking for them to do.

And then in the case where AI. Expertise is needed, a library of AI advisors inside of Clyde, where you build an AI advisory team based on your problem who then come in with their own lenses and perspectives as you're sort of. Working through your problem. And then once Clyde has all that, then Clyde's pulling in all the right human ux i'll call it, for the people to be able to engage and pulling in all the AI expertise needed.

And then at the end you end up with a customized output that's been iterated through the lenses of all the humans and all the AI to the point where you have this you know, aligned output where you can also show the breadcrumbs of how you got there. And that is probably a very lengthy explanation of what Clyde is. But let me pause. Let me pause there, and hopefully that starts setting the scene a little bit.

Yeah, No, that was that was excellent. I mean I was following that, and I think you've explained it really really clearly. What I like about it is that it sounds like, well, you are bringing the best of human and intelligence with artificial intelligence together. You're not You're not not trying to replace humans with AI.

You're you're putting it to best use, but you're you're I think that's the problem that a lot of AI tools or companies are doing, is that they're saying that they're going to replace humans and that you don't need humans anymore. But you you know the value of that, and there's there's a lot of resistance, understandably in these companies that are very I have a lot of intelligence smart people working for them to adopt AI tools because that's that's their whole business model, isn't it.

So if you're if you're offering something that's sitting in between, then that's going to be more appealing, particularly for a company like Accenture, and I know there's and small companies, small companies as well. It's clever. It's clever what you're doing, like it sounds unique. I'm I'm not aware of anyone else that's that's doing this.

I saw on your LinkedIn profile as well as same before. I like the way you explain how a lot of AI it's just like a sidebar or a summary button or it's it's like, it's very it's amazing technology that's trying to find a reason to be used in a lot of cases in other software, not yours, like other SOFFA, like pretty much all the tools that I use, all of a sudden, it's AI powered or AI enhanced and I didn't ask for it, and it's just there, and most of it doesn't do a lot. It's going to make my life better, but but it sounds like yours will.

So what are you gonna say? Yeah, no, I was going to say that. I think we're also going through this sort of natural maturity curve of a powerful new technology, right, and AI, I think is one of obviously the most accelerated and powerful. Technologies we've had in a very very long time.

And I think as you go through the sort of you know, pick pick your business book that talks about this here, right, there's infinite ways of explaining this, but you obviously get the initial you know, that kind of hype cycle right where you've got the early adopters that show up on LinkedIn and show how they've hacked their entire life, you know, using AI, and you know it's this utopia, and and then you sort of start getting to where I think we're at now, which is that you know, we've we're not past the hype cycle, but we've we've progressed to a point where people have already tried to, for example, automate entire workflows using AI, and they've had time to fail doing that.

Right. There was that report that came out it's a little dated now, but you know, MIT came out with that report that said ninety five percent of all and AI pilots had failed, right, And a large reason that they had failed was that I think a lot of people that didn't necessarily have domain expertise and a connection to a specific user group and use case, they just tried to big bang automate you know, very very large, complex processes and they just failed because what they didn't realize is when you're driving that level of change, you have to meet people where they're at, right, and then bring them along to the level of transformation you're going for, Whereas I think a lot of the sort of frontier builders that they're trying to just take the flintstones and put them into the jetsons like straight away, right, and just kind of miss everything in between.

And so one thing I believe very passionately about, and you know, since our focuses is very much with in the consulting space at least for now, is that right now, consultants are still largely using PowerPoint. They live in PowerPoint, they use Excel, They manage all their knowledge with you know, massive share point OneDrive type setups. Right, they have lots of stale content sitting on you know, shared links that never get updated. Now, yes, of course they're all using AI and experimenting with AI and trying to embed it, but the reality is that they're they're coming from that place.

And so what I think about in terms of helpful AI is how do we how do we go from that current state and allow them to still operate in that workflow but just incrementally making it that much better and then and then always just being a little ahead enough of the user that they can see the innovation in the progress to inspire them to move. On, but not so far ahead. They just they're just like, okay, great, I love that, but I have no idea what I'm supposed to do with you. And so I think I think it's good when you told about the bread crumbs as well, so you can see the trail and like how it got to where it is.

I think that's that's clever because instead of just coming up with a solution or the suggested solution, you're like, well, I don't know where you've come with it. That that sounds amazing. Like just recently, I've done a few things with our business where I've fed in quite a lot of information and it was just like, okay, based on all this, what do you think we should do next in our company? And it came up with some amazing suggestions, right, and all of that it sounded incredible.

It was like, well, I'd love to do all that, But what it didn't know. It didn't actually know the practicalities of doing that and what the limitations and our on our resources and time constraints. It didn't have any understanding of that. So yes, it's there's that and then I had just randomly had another thing where I talked about something else and it gave me some suggestions on some audio equipment to buy.

Right many years ago, it used to be a DJ I'm thinking about picking up my headphones again and get back into it, and it recommended what I should do. And then and then it made us a recommendation on the type of speaker over another, and I asked him that why you why have you chosen that one? And then it backtracked. It was like, yeah, you're right, thinking about it again, we probably shouldn't have said that, We should have said the other one.

I was like, well, after, how do I know I can trust here? Because no, it's it's a really valid point. And and the trust that the breadcrumbs is particularly important for many reasons, but one is really on trust. We've reached a point now where everyone assumes that everyone is using AI, you know, to be more effective, but nobody really knows how people are using AI.

And so what ends up happening is you you submit let's say you submit a proposal. Say you're a consultant, and you submit a proposal for a you know, a fifty dollar ERP transformation or you know, some some large program and the client gets the proposal and they have the reaction of oh, well, you've clearly used AI and you know you chatchupt this and we don't know how or where, but I saw a few dashes there that are clear AI giveaways, and you know, I no longer trust the integrity of this proposal.

And then when you combine that with these high profile things that have been happening where you know, there there was my favorite one is not consulting related, but there was a case in New. York Google about where a judge. Had both the defense and the prosecution deliver their their arguments and was able to see that both of them. Had used AI to generate their arguments.

And both of them had actual false data, false assumptions, and sources that simply weren't even true in both of their arguments. And so the judge just threw the whole case out said, you guys, this is not it's not feasible. And so when you start having those levels of trust issues, one thing that our early adopters really enjoy is being able to you know, for example, if you're building a proposal for a client, being able to show the client that this is the process we went through, right.

This is where we came together as a team and brainstormed all these different ideas of how to help you. This is where AI came in. We used these ten AI advisors that gave these inputs. There's also inside of CLIENTE an agent called our fact checker advisor that will go in and actually cite the sources of all of the sort of information you've used and then also give a confidence score of we know that these sources are ten out of ten dependable, but we know that these are kind of tenuous arguments that we still believe in but probably requires a bit more validation.

And so imagine delivering in this era of AI trust issues. Imagine delivering a proposal to a client where you're actually showing your. Work more on there if you do that, rather than that's the thing if you're saying, look, we've used it in these cases and then this is where we've used our own intelligence and research into it, and they're going to appreciate that more. Yeah, there's probably a reluctance to people don't want to admit that they've used day Eye, But like you say, people just assume that you have Useday, I you might as well show where you have and where you haven't.

Yeah. Yeah, it's like it's like the It's like. If you go back to the days of the Internet, right, Like I remember I'm I think, I think I'm young enough where I was. Wikipedia was introduced.

Right when I was in uh he's like some middle school for going to the high school, and I remember that all the teachers were terrified that we would use Wikipedia, you know, to to do our research, whereas you know today it's a foregone conclusion. Of course, you're using the internet to research your your papers, and as long as you cite things properly, then that's that's no problem. And I think this is it's a very similar evolution, but we're right in the middle of it now and people are still confused about it, not entirely sure how it's going to shake out.

So yeah, I think anything that bridges that trust gap right now is critical. So what's I know, we've we've talked about the bigger businesses that you work for, but like who who is using Clyde at the moment or who do you think? Who do you want to use it? Can anyone use it?

So that's yeah, that's a very interesting question. So I'll tell you the intended answer and then I'll tell you that the real answer, and there there's an overlap between the two. So it's intended for you know, consulting firms to be able to to use this as something really built for them, built for their workflow. And that's where the majority of our.

U you know, of our revenue and and our concentrated sort of usage is sitting. And they're very much using it for you know, the proposal example I mentioned sort of that sales pre sales side of things, but they're also using it in in delivery and how they delivered their clients. And they're what they're trying to do is they're trying to solve problems around, you know, one being able to access all of the expertise that their firm has. So one of the challenges is I have I have some clients that have delivered literally thousands of large scale programs, but one of their problems is that when their consultants show up to a client, their consultants don't have all of that knowledge at their fingertips.

And historically you've solved for that by bringing in a person who has you know, thirty years of industry expertise that can go talk to the CIO of you know, a huge aerospace. Company or whatever. That expertise doesn't scale particularly well, right if you're trying to do that across hunges of project and so in Clyde. The other thing you can do is you can actually build custom advisors that have your firms specific expertise, IP and knowledge built into it.

And so, you know, let's say you have expertise in you know, finance transformation or CRM transformation, whatever it might be. You can go in and design an advisor inside of Clyde that has you know, ACTME consulting expert. You give it access to your whole knowledge base, You give it several examples of successful projects proposals, and then when you're in your engagement, you can literally bring that advisor into the workspace and just as you're working through requirements, that advisor can both reactively respond to questions, so tell me where we.

Did this before, what risks did we find, what went well? That kind of thing, and. It also will scan what's happening in the session and proactively come to you and say I wouldn't do that because that caused, you know, two hundred thousand dollars of scope creep, you know, in these five projects or whatever it would be. And so the large consulting firms are really using it to bring in their own expertise into the platform also sort of drive some consistency around how their consultants are delivering.

Another thing that Clyde has is if you buy it at the team or company level, it has this thing we call the team memory that we'll be. Able to. Surface, you know, a specific way that you want things delivered, if your company has a specific methodology, Clyde can work within those guardrails. As you use it, the brain of your specific company will start to grow inside of Clyde and you can actually start to get a smarter, more improved Clyde that specific to how you run and how your team runs.

And so that's really at that sort of large consulting level where we're finding use. Now we have some unintended use which is very interesting, which is we've also had a very unexpectedly large amount of self serve sign ups since we launched. So we launched in April with our commercial version, and since then we've had four thousand individuals sign up. We have a free version that you can access, so you just go to Meetclyde dot com.

You can literally just sign up for free as an individual and just start using the platform. And then there is a consumer sort of version that is you know, twelve dollars no, sorry, nineteen dollars a month, and then there's a pro version that actually gives you access to not all, but a large portion of the capabilities of Clyde. And so what we found was we found this incredible cross section of people just signing up. We've We've had everything from you know, one man band consultants, as you'd probably expect, but then we've also had third grade teachers sign up because they feel like they want to improve their curriculum delivery and an underfunded environment.

We've had healthcare professionals that want to improve how they serve their patients. We've had small business owners that are thinking about sort of launching a new business idea or you know and sort of looking through that. And then we've had people that. Are just straight up saying, hey, I'm thinking about a career change, you know, help me work through how I might do that.

And so there's been this unintended use of people that want McKinsey level outcomes but are just sort of using it for their their day to day problems. Our focus remains very much in the consulting vertical because we believe there's a lot of acute sort of pain there and and a lot of things we can be very helpful with. But we're not. Turning off this this consumer approach, and I'm curious to kind of see where that goes and that's going to drive any scale or volume.

That's that's interesting. Well on that, I mean, I can totally see how the large companies can find it valuable because yeah, like my I've worked for some big companies. I've worked with Sage, big huge software company, and I've worked for British Airways as well in the past, and work with government organizations. And my partner and other other people called to be work for large organizations as well, and at that institutional knowledge that there's there's a lot of times where particularly my partner should be in a meeting and then people talk about stuff and she has to remind them that they've done that before, or it hasn't worked before, or like you need people like that who are remember what happened before and before to stop people making mistakes.

So I can only imagine a huge company like Accenture and others out there that so complex that their own organization, but then the companies that they're brought in to advise on as well, how difficult it must be to filter through all of that and and and and stay on top of things. Did I read someone as all your your you're like guiding people through, You're keeping people on track as well through through the process. Is that right? Yeah?

I mean one of the things that that Clyde will do is once Clyde has locked in that that problem statement, right, and you's sort of worked with you to understand this is truly the problem we're solving for. And then it then. Sort of locks in on a goal and then is its focus is to get to that goal. But then it also has some some built in sort of caveats of what needs to have happened to get to that goal.

So to get to that goal, I mean, let's so first off, some goals are very very simple. Some goals don't require you know, multi stakeholder alignment and you know, massive engagement. Some some problems could be as simple as you know, give me the pros and cons of relocating to Denver. It could be sort of some simpler simpertis, but assuming there's a little more complexity behind the problem, what Clyde will do is Clyde will as you're working through the problem, Clide will assess, Okay, have we involved all the people that need to be involved to reach this goal?

Right? Are they aligned? Right? Have they been brought into the process.

Have we made all the decisions that we need to make to reach that outcome? So there's another feature inside of Clyde where when you're ready to make a decision, there's something we have a trade off have called a trade off analysis feature, where Clyde will populate everything that you've learned about the problem by engaging with humans. The other a advisors and Clyde will populate this little looks like a little matrix that has options of certain decisions you can take, and then it will have all of the sort of call it the criteria of that decision.

It will have all of the research that's gone into the trade offs, but then it will ask. The human being to make the actual decision. And this kind of goes back to that I think AI could be great at facilitating decision making, but shouldn't make all the decisions. And so we have that built into the product where the human being that actually makes the decision and can go back and forth with Clyde until that decision feels like it's something that they can click and they have to click an actual button that says I am making this decision right, So it's very it's very intentional.

And then once that decision is made, there's another feature inside of Clyde that will then surface right towards the end of your session. It'll surface all the decisions. You've made, all the actions you've agreed on, and actually have you work through those before. Getting to your outcome.

And so by the time you reach that outcome and it provides you the summary and the actual content you were looking to create, it's it's not only kept you on track, but it's also made sure that you've done certain. Things that maybe you wouldn't even normally do. In your sort of if you did never used AI, maybe you wouldn't do these things. But these things are the.

Absolute best practice of how world class consultants would go about sort of getting to an outcome. MM, yeah, I love that. Keep me on track and it's probably quite satisfying as well, like clicking on the buttons as well, when you're making some progress and achieving something. Yeah, there is so much time wasted as well, isn't I Like with trying to corral people and get people on board and making sure people are doing what they say they're going to do, and there's always some resistance and people have got their own agendas, and like even making sure that people are really locked and bought into an outcome or working towards a solution.

Yeah. I mean one thing I experienced so many times in the I'll just call it the analog consulting world is you know, countless workshops. I mean we're talking dozens of workshops across hundreds of people where you're just constantly going through this. It's just this minutia of needing input from all these people and then having all those people having understood it, then having them buy in, but really buy in, not just fake buy in, and and the iterations.

That that takes. I mean, the cost of that. Is just both from an actual cost financial cost, but also just mental effort, cognitive load. I mean, it's it is a huge part of.

The waste that goes into delivering these these programs. And then the other challenge is I can't tell you how many times I've been in a workshop where I can tell, based on all the experience I've had in the research I've had exposure to, I can tell that a group is not aligned and that they don't have a shared understanding of a problem. And then people try to then rush to the solution, and I can just tell that any solution you come up with, you might as well just throw away because you didn't spend time reaching a common understanding of what you're solving for.

And again, I just think that. People, you know, historically have relied on expert facilitators and very very experienced, highly paid consultants to actually be able to navigate that. And I think now, using technology such as Clyde, I think we have a way of almost democratizing that that expertise so that more people can actually get a group to an aligned outcome. And if you think about consulting specifically as an industry, you know, without getting into the boring economics of consulting, the foundation historically of consulting was the pyramid, right called the consulting talent pyramid, where you have the senior partners at the top, and then you have the analysts at the bottom who are doing a lot of the.

You know, a lot of the. Coalition of information note taking, you know, their learning so that they can become more senior climate pyramid. AI is removing the bottom layer of that pyramid, right, and it's doing a lot of the tasks you know, very effectively and faster than what these out of university analysts we'll be able to do. And unless we find a way to enable these these young professionals with tools to add more value early on, right, there's going to be a huge challenge there already is a huge challenge of people just not being able to find work out of out of university.

And I have a contrarian point of view, which is, I don't think the answer is to just simply, you know, fire everybody, or you know, kind of get rid of fifty percent of the. Workforce or thirty percent or whatever the number is. I think we need to upscale from that lower end. And just like if you want to go back to the industrial revolution even right, instead of instead of just eliminating everyone that was on the assembly line, now that you know machines can do it.

We need to find things for those people to do that that elevate them and. Actually bring society up a whole level. So I don't know how we got to there, but I'm throwing out all my big, all my big statements. No, no, that I totally agree there.

I think there's a responsibility and the duty of people who run businesses to do that. It's not just about cutting jobs to make more profit. You know, there's like, what what's the point of a business? It's not just to make money, is it.

It's to make a I think to make a positive contribution to society or the community that you're in as well. And if you can give meaningful work to people and and remove some of the boring, repetitive work but allow them to do what a human can do that a I can't do, then amazing. That's that's what people should be doing with the with the time and the and the resources, using using tools like yours, like get everyone using yours and start start becoming an expert and how to use cride more effectively.

Yeah, I'm gonna just randomly you might or might not have you have you have you ever read recently the Pope. Do you know much about the Pope pub ly? Do I know about the Pope? Yes?

I mean so he wrote something recently, right, which is all about this. It's all about it's like a warning about Russian too much headlong into adoption of AI and technology at the expensive humanity. So he's not he's not saying don't use AI and don't use technology, just saying it's like a bit of a warning. It's like, look, you like, business owners and leaders and politicians have some sort of duty of care to people to to try and educate them on how to make good use of this.

Otherwise there will be there will be millions of people lose their jobs and don't know how to come back from it. You talked about the Industrial Revolution. There's the northeast of England, which is where I'm based. You know, it was all coal mines, ship buildings, steel works.

You know there was but in the eighties, nineteen eighties, all of that just shut down, declinent and there was about one hundred I thought it was more. There was about one hundred and seventy thousand people lost their jobs from the coal mines across the UK, and one hundred and fifty thousand of them were in the northeast of England, and forty years later this part of the Northeast still haven't recovered from that, And so I added a bit of research like, apparently it's millions or potentially going to be affected by new technology across the world, and they might not they might take them forty years to recover.

So anyway, people have a responsibility to educate themselves on how to use these tools. But also I'm putting on it sounds like you're in an enlightened leader. So you're you're going to make You're going to educate people on how to use these and you're not saying just suck a load of people. You're saying, but you're not.

You're saying how how AI and humans can work together collaboratively, which which I really. Like yep, yep, yep, yep, And I mean enlightened might be a strong word. I think there's I think there are also very sound business reasons to do it this way as well. You know, one thing that that frustrates me but humanity of me now and then, is that.

We don't we don't seem to learn from mistakes. There seems to be this inability to societally learn from mistakes. And I think that if I think about how cliss it's going to be successful over time, you know, and hopefully create create a category. Is if we do this sustainably and we actually drive this change incrementally right and and have people experience value from the beginning of using Clyde, which means we have to meet people.

To some extent where they're at right, I. Think that doing it responsibly is actually going to generate the most revenue. And profit as well. So it's not entirely idealistic even it's also it just makes business sense to do, you know.

I think one of the one of the worst things you could do as an AI startup is max hype what you're selling and then have to spend you know, two years catching up to the hype that you've sold, right, Whereas if you're able to deliver that value from day one and then sort of keep the hype on track with value delivered, I. Think you're going to build a better company. Also on the point of just AI industry in general, in terms of responsible AI, I think we're in this quite unprecedented situation as well, where the leaders of the AI frontier models are begging for regulation.

I mean that to me is astounding to have a because the normal tension is that the innovators they push the limit and then there's natural tension where they are then held back so that everything is sort of safe, done well. And then that tension is what drives drives. All the mechanics. Whereas now the governments.

Certainly aren't able to keep up with any of the speed that's happening, right, they just don't have the infra structure to regulate in time, right, And so these large frontier models, I'm convinced that they're all sitting with models that they haven't even released because they understand that they can't. Like it's just going to create societal havoc, right, and they're just gonna be able to go hack into everything and you know, just be too far advanced. And so back to what also makes business sense is as an AI startup owner, is I think we have this opportunity to self regulate for the first time, and anything I've seen, I'm sure there's some precedent which I'd be interested if anyone does have a precedent where an industry is self regulated.

I'd love to hear about it, but. I think, well, imagine if every AI startup, not just the big guys. Not anthropic, not open Ai, but every AI. Startup had some principles around doing things in a responsible way, not just being one hundred percent about you know, human replacement, but also about augmentation and upskilling, and that extends to also environmental factors like all of it.

Right, if everyone had that as part of their driving principles, I think we could look back at this in fifteen years, twenty years and call it a huge success story, right of how we were able to all do that, if we let three companies and the governments try to figure it out, I think we'll look back in fifteen twenty years in a similar way to how we're now looking at social media right where you know Australia banned for under sixteens. I think you guys just did too right. It was proposed, but it hasn't been brought in.

It hasn't been brought in yet. I thought it did, but I think people are realizing now that you know, there are certain parts of social media that are inherently dangerous and need to be regulated. I don't think we can wait fifteen twenty years for AI to to reach the same conclusion as far as the industry goes. So so yeah, I think responsible building is going to lead to better business outcomes.

Yeah, it sounds. It's a long read, but and you don't need to be religious to read about it. I think you would find it interested in reading the popes. It's called an encyclical, which is just like a really long essay.

Okay, but it's called what's it called. It's called Magnifica Humanitis. Magnifica Humanitis. I am going to read that.

Yeah, it is a long read, but it's action all about AI, which is well worth reading. And a lot of what you've said there is basically what the popes saying. So he's had a lot of experts feed into this. You know, it's not it's not just the pope sitting there in the vatic and just coming up with them.

So you know, I'm going to read it. I I have to admit I have never in my life been been paraphrasing the pope. That's that's well. I had it mentioned in a podcast.

I was like, that sounds just the way they were talking about it. Because I'm into technology obviously, and I was just like, all right, I'm gonna I'm going to give it a read. It took me. It took me about a week to read it of like an hour a night or an hour a day of getting there, and it was.

It is an enjoyable read. It's it's not a difficult read. It's just a long read. But there's there's some really really good things in there about about the importance of just taking a bit of a pause before we before it's too late, and I think a lot of a lot of it is kind of aimed at the say, the leaders of the frontier models and and the political leaders and just so that they don't make any any massive mistakes.

But yeah, it's it's it's it's good. So what's just obviously well, I think you've explained everything that you're doing really really well in it and definitely very compelling, and I can see the need for for what you're doing, and I think it's it's valuable. I'm definitely gonna encourage more people to take a look at what you're doing, Like big businesses and small businesses that are that I work with. How are you finding it when you when you're talking to potential clients or customers or your users of it.

Are you do people get it? Or are they resistant or they like what's what's going on in the in your world? Yes, I would. I would say there's a few categories of conversations I think you've got.

You know, if I take the PI chart of all the. The customers and potential customers I talked to, you know, I'd say ten percent of them are in that early adopter category of. Being very curious, being very open to. Experimenting, being very open to disrupting their own ways of working.

And obviously those are the most by far, the most productive conversations because that's where you're going. To get, you know, a lot of. Courage, early courage to really prove out some initial value, right, and that's where we have, you know, a handful of some real trusted, initial cohorts that that are doing that. Then there's a very large chunk of I'm overwhelmed already type conversations right where people are you know, quite honestly saying like, Hey, this looks fantastic, I just don't even have that headspace to consider what you're doing because I'm overwhelmed, I'm inundated.

I have one hundred AI tools and I'm. Just trying to figure out some basic, basic approaches to this, right, And I would say that's still that's still a you know, a solid half of the market. That I'm talking to. And then you have these other sort of chunks.

You have the never AI crowd, right, and then those obviously I'm not gonna spend a ton of time, you know, investing marketing resourcing too, because they're gonna come around when they come around. And then you've got the hardest bunch, which is sort of the ones that are not in that ten innovator early adopter category, but they're still open, but. They're very cautious. And that's where the customer acquisition costs is the highest, because is we're having to invest a lot of time to really educate and really sort of help help them understand not just what we do, but also AI.

And I think that's one of the other hard things about breaking into into this market. You know, I think from the outside in, I think everyone looks at it and goes, oh, AI, it's just. Everyone's just rolling around in money and it's just. A hype, and you know, it's like Scrooge mcduc everyone's just diving into crews.

But the reality is. That it's you're having to do a two step sale where you're having to one educate on the merits of just AI and then you're having to educate on specifically how Clyde is different than a thousand other potential sort of solutions. So it's it's interesting and it's and it's kind of this paradox moment of I have so much excitement around me, which energizes me. And there's people that are just very excited about.

Clyde, but they but it's not a build it and they will come like, you still have to do the work. You still have to really partner and spend a lot of time, Yeah, both educating and working with early adopters, which which is fun. It's just it's also a lot of work. Yeah.

Yeah, Well things like this, these this video interview in the podcast, it like contributes to that. But I've been thinking a lot about this, Like fifteen years ago I worked for it, well just under fifteen years ago I worked for I mentioned before stage, big huge software company Footy one hundred, very successful company, but back then they were a cloud denier, right because they were making so much money from desktop software, you know, like CDs or floppy disks. I've worked with them twice.

SAGE that like my first job after union, and then I went back thirteen years later. But even back then, it was like a lot of it was educating people on what SaaS was, what what cloud software was. So we were trying to sell this new technology and the benefits of that and the cost savings and you know, and then we had saved. It was very reliant on a network of resellers like accountants with the big resellers for their software, and they didn't want to know because they couldn't make much margin or profit from selling this low cost SaaS software.

They were they were selling big, big ticket desktop software, so you couldn't rely on them. So a lot of what we were doing was a new business acquisition. It was all like top of the funnel, pre funnel any anything and everything we do to raise people, raise awareness. So events, networking, PRF, once, your video, social media blogs, you name it.

And some of it stuck, some of it didn't. There's a lot of work went into that. Yeah, it's funny now with fifteen years later, they're getting disrupted, disrupted. The SaaS companies are now being disrupted the way the desktop software was being disrupted by AI.

And yeah, it's like people, even I'm a little bit overwhelmed. Like if someone I get a lot of messages or connection requests or emails from people and they lead with AI, and even though I'm into it, it turns me off a bit when people lead with a I. It's like, it's actually it's more the problem and the solution that I'm interested in. I'm just sort of taking for granted.

I'm just assuming it's got AI in there now able to view thing, So I think you're doing that anyway. But yeah, that's hard, isn't it When you're trying to educate people on the that that you've got to be your focus. It's not just about the I and what it's the it's the problems and what the solutions that you're that you're providing. Yep.

So it's it's classic. Have you have you read a book called The Jolt Effect? No, I'm not. I love it.

You just just hit me up with all these great. So The Jolt Effects a really good, really good book, and you can listen to an audiobook as well. But they've analyzed millions and millions of sales calls, and I know your background sales so that this won't be new to you. But the classic sales is painting this future utopia.

You know, come with us, use our solution. Everything is going to be great, Your life's going to be transformed, everything's going to be amazing. Right. But what they've worked out through all these calls analysis they realized that even if people know that, it's the fear of not the fear of missing out, it's a fear of messing up there.

They're worried that even if they really know that this is what they need, they're worried that their colleagues won't make use of it, or that once they buy this solution that they won't be able to make good use of it. So that you don't need to read the book now, But the general gist of the book is that having to spend more time on the after sales, like the ongoing support that you provide with people once they've decided to work with you. That's what people are scared of, is they make a decision to buy it and then it doesn't work, not through your fault, but through their fault, because because them and their colleagues don't know how to make good use of it.

Yes, yeah, so you probably already doing this, but it was just that that's just worth worth the looking at that book and what they what's what's in there? I'll check it up for sure. It's googled it and it's Yeah, it makes a time of sense. It's very very good because I'm not a salesman.

More more I can sell, but my background is more market in community engagement and partnerships, and I always had other people alongside me to do the sales. I was all like lead gen in the really raising awareness of what we're doing. So yeah, so exciting. So when yes, but still I know you've been working on this for a while, but you said, it's it's only since April that you've been actively on boarding users.

And yeah, so we so we, Yeah, we raised a bit of money at the end of the end of last year and then used that to you know, build out, build a slightly broader team. We're still still small. They call it tiny teams these days. Then the trend.

But then yeah, so then we spent spent spent a few months basically hardening the m VP that we had built in the fall of twenty twenty five and then yeah, April launched watched the first sort of comer version And by commercial version, I mean, you know, mature enough for self service onboarding, mature enough from a UX standpoint to to sort of put put out to the world. So that was in April, and then yeah, our goal, our goal for the rest of this year is to what once see where the unintended experiment ends up as far as the four thousand users that that's tracking to hit ten thousand by the end of the year, so we'll see where what all those guys are up.

But then from a business standpoint, you know, our goal is really too you know, serve the consulting space very well. And then into twenty twenty seven, you know, the vision for the company is, you know, very much to be the place where sort of AI native collaborative problem solving happens. Right, And if you think about that, just consulting makes so much sense to start with. Because they have that acute pain.

They just do it every day. It's just inherent and what they do in terms of problem solving. But I mean, I see a world where all all companies could effectively benefit from this approach and then extending all the way out to yeah, democratizing expertise in a collaborative way to the entire world. I mean, if you really think about the big, big picture vision.

So yeah, we're just itching, itching towards that every day as best we can. Amazing, very very exciting. I'm sure you'll do very well well of it. And I know you've got experience of working in the UK as well as the US obviously, so you are you have you got customers in the UK or Europe or is it mostly the US at the moment.

No, we do. We do have customers in the UK, so some large actually some large professional services activity in the UK, and then then a couple of boutique uh batique firms as well. Yeah. I lived in London for ten years and so I have I have a bit of a natural sort of network coming out of London that we've that we've certainly helped educate.

And Europe is I mean, I've always seen Europe is I mean, you know, there's all the the oh GDPR and it's so hard to sell to Europe and all this kind of stuff, But I've always found Europe to be a place that actually helps drive early adopter type activity like both in the UK where I'm from Sweden, you know, huge hot spot for early adopter innovation. Several several customers and colleagues out of the Netherlands that have always been early to adopt. So yeah, I think Europe is going to be one of our one of our hotspots.

Cool. I hopefully I can help you help you a bit with things like this. I saw something the other day. I don't I don't know.

I didn't look at any great deal of it, but apparently the again in the northeast of England apparently were one of the hot spots for AI adoption in the UK. So I don't I don't know why. I don't know why that is or what that means. But I know there are there are a lot of tech tech people in the Northeast.

But I don't know whether it's just I don't know why that is. Obviously it's not London, but just in terms of the rest of the UK, the Northeast is. Maybe maybe it's maybe it's tied to my theory of why Sweden has so many you know, unicorn startups and so on. You know, in Sweden, the the amount of people per square foot square meter a lot less than you know, downwards warmer, and also because it's freezing up there, right, historically they've had it's kind of innovative die, right.

It's just there's no people, it's cold. Yeah, so we have to we have to, yeah, just do what we have. To innovate and with and with what you were sharing about the northeast, you know, in the eighties, and so maybe that has forced a need for innovation. Yeah, that you know, previously it wasn't it wasn't as acute.

Yeah, no, that's good, good points. Yeah, I mean definitely that. I mean I'm into history as well, but the Northeast, throughout history, the northeast of Inglis has been very good at innovation and invention and creativity and coming up with, like we are readion problems solvers. But what they've had to do is that they've had to go out of the region to make it successful.

They've usually been very good at coming up with the ideas, but then they've needed to sell it somewhere else or exported around the world. It's funny how the psyche, Yeah, the collective sort of psyche area is still still there. To the state so yeah, I think you're onto something with that. Awesome.

So I know you mentioned it before, but we'll say it again. If people want to have a closer look at what you do, and if they go to meet Clyde dot com, yep, and they can have a play around. Did you say they can sign up for a free free trial or just a free version. Yeah, there's a free version.

It gives you a number of credits to help you get through a couple a couple of sessions and then and then from there if if you if you like it, you can obviously upgrade from there. And yeah, and if you're consulting firm, when I have a more specific conversation, then you know I'm LinkedIn, very easy to reach. It amazing, right, Tim, really enjoyed that. Thank you very much for doing that today.

I think we'll leave it there and we'll get the shed all over on all. This will be on Facebook and YouTube and it'll also be on all the podcast platforms as well. So thank you very much.