Navigating the Challenges of Distributed Teams and Communication in the Tech Industry

Thanks for doing this, Kole. How are you feeling?

Na, asko. Yeah, I'm good. Cold, but good.

Yeah, here you go, here you go. We got like -1 first in this year. Feels a lot more colder than, than what you see, you know, temperature-wise.

Yeah, it's Well, depending on the format of the forecast, it's going to be -4°C where I am on Friday.

So, okay, that's even colder.

I boosted that on Saturday morning.

Yeah, I boosted all temperatures where I could in the home, just reset my thermostat just to be on the safe side.

So, um, anyway, I coach kids' football, so I have to get up on Saturday morning. There you go.

Any goals in this year? You know, we're just in the new year. Anything special coming from Corey in 2024?

I'm going to try and diversify a bit more, I guess. I, you know, since leaving UBS, etc., I've been kind of concentrating on venture capital space and I guess kind of doing smaller versions of what I used to do before.

Okay.

Right. But I'm kind of wanting to experiment a lot more this year. I think also I'm going to try and take, take a little bit more time and try new things as well, still in the tech space, but, but more in other areas. So, um, some of the things I've been playing around with are things like, uh, coding in AI for graphics and things like that, just to see what's available out there, um, and maybe take some time to, to kind of learn about some of the newer subjects and newer topics around things like robotics or autonomous tech and that kind of stuff.

That sounds cool.

Just a, just a kind of get into, get into more tech again.

Okay, so before we jump into AI, which I know, you know, is the topic you love, tell our listeners who's Gordon.

Um, I'm— I was kind of counting this last year, so I'm kind of a 30-year-old veteran of technology, IT, uh, mainly in corporate space, uh, but in the last 5 years or so specializing in startups and venture space. So small businesses, helping small businesses either find money investment, or helping to build businesses going forward. So I've been in technology all my life. I'm happy to say that I'm a tech geek. I love tech, any form of tech. You know, everything from making Legos over Christmas for my kids all the way through to building AI systems, etc. I love, I just love tech.

So am I right to say that you have, you know, the full spectrum of, of the depth in technologies, meaning, you know, you work for enterprises, we have huge amounts of headcounts, you know, you work for startups, we have small So how the whole, you know, shebang affected your experience?

Yeah, yeah, I've been very lucky. I started my career with a company like British Telecom in the UK, did pretty much every role there was to do in British Telecom over the time I was there, other than climb up and down telephone pole. I did build telephone systems, etc., but that kind of stuff. Ended up as CTO there, running their large-scale business contracts and stuff for big big outsourced businesses, then moved to client side working with various industries, ended up in financial services. The last 3 roles were in organizations like Credit Suisse, Bank of America, UBS, etc., as CTO, CIO type roles. I've run teams as large as 30,000 people all the way down to 5 people. That's it. I've, you know, I've been lucky, again, lucky enough to, to build businesses, run businesses. I've been exposed to operations, I've been program director, various other things. So I've I consider myself very lucky that I've had the opportunity to kind of learn all this stuff because it does, it does come in very early.

I do agree. So in the spirit of the show, from your perspective, what is the one main thing which influences tech growth for the companies?

Good question. One thing. It's very hard, isn't it? I would say based on recent experience. Yeah, it is. I think based on recent experience, it's It's confidence in what you're doing. Being able to describe what you're doing clearly, simply, in a language that is non-tech to a non-tech person is a huge value to anybody really, right? And the problem is today— well, not a problem, the value is today the mainstream media has grabbed onto technology like never before. More people know about technology like never before, more people have access to technology like never before, right? So, you know, anybody who's got a smartphone with them will have technology that is capable, you know, was more capable and more powerful than the computational systems that launched rockets to the moon and all that kind of stuff. Everybody knows that kind of thing now. So technology is more pervasive than ever. But I think to make technology successful, you've got to be able to explain it easily and and well. And too many people get buried in the emotion and passion of what they do, and they forgot that, you know, they forget that technology has to be useful to somebody, right? Otherwise, there's no point in doing it.

That's such a good shout. I do see a lot, especially coming from tech founders, where they, they look at the idea as their baby, and, you know, they fail that important step to actually, you know, talk with the market and go like Does anyone need this? And, you know, is there a need to add scale as well?

Well, I think it's also, if you're too passionate and too buried in what you do, and you can't explain it well, you may understand it. But if you don't explain it to everybody else, they're not going to know what it is. And I've always, you know, I learned a long time ago that when you look at a new piece of technology, I don't ask what the technology is, I ask, what can I do with the technology? Right? How is it going to be useful to me? Because technology is developed every single day. And as you know, it evolves every single day. So today you may have the best thing since ever, but tomorrow somebody will come up with a better idea. And you then got to make a choice. If you're the guy with the— no, you know, if you're the person with a better idea, and you can't explain it to people, you're getting nowhere. And I've come across a lot of situations, and probably in the last 3 years or so, where people are enamored with building things themselves, when actually If you look at the technology that's evolved and developed and available today, you're better off actually, in some cases, just using technology that's available to build what you want, rather than writing everything from scratch, for example.

That's integration versus— sorry to jump in, Colin. Yeah, continue.

Well, it's— I call it exploitation rather than anything else, right? Because you've got to be able to leverage the vast amount of skills and technology capability that exists in the world today. And everybody's becoming more technologically advanced today. I mean, again, I came across a project the other week where the person who developed the technology had never dealt with technology before, before she decided to come up with the idea. But she was stuck because she was so enamored with building everything herself that she couldn't move forward. And the reality was, in, in one or two meetings, me and a couple of the others just said, look, you're better off not building these things and just partnering because it'll get you to market faster. And, you know, in the time since we've had that conversation, you basically released 2 new versions, right? Whereas before it was taking us 6 months every cycle to go through the version control.

So that buy versus build, isn't it?

That's what I bet.

Sorry, buy versus build. So it's, is that decision? Yeah, yeah, yeah. Well, again, especially tech founders trip off because they can do it So, you know, they ask this question wrongly. It's not about how, it's about who, because you likely can come up with the how yourself because, you know, you're the tech guy, you're building the tech. But it's not always, you know, the answer. Sometimes just buying what's already done and just, just having a much quicker time to market is it.

Yeah, as I said, it's exploitation. It's, you know, I know that you can do certain things, for example. So if I was writing a piece of code and I know you've already written a piece of code, the likelihood is I trust your ability to write that code. Why would I not use your code and work with you rather than spending 6 months trying to write my own version of what you've already done?

Yeah, that's a very—

at least get the concept to market, right? Get the concept to market. You know, I don't know, I may be able to develop a better version of what you've got, but I don't necessarily need to prove that yet. I need to prove the overall concept first. So let's, you know, work together, get the product to market, test it, because if the product isn't viable in the market, there's no point in me writing a custom version of your code.

Yep.

For example, right?

Okay. All right. So talking about innovations, let's, let's dive into AI, right? So, yeah. Should we say generative AI or AI as a, as a general term is okay?

I think AI in general term is okay. I mean, there are various, there are various levels of AI. So when I say AI, I mean true neural networks, artificial intelligence, not necessarily just machine learning.

Okay. So machine learning has, let, let's define it from your perspective as in, Maybe let's start with how generative AI works, or, you know, general AI, like actual neural networks, just to give some idea how you think about that definition of AI.

I use a classic definition, the original 1970s or so definition of AI, which is that it's a machine system that is capable of thinking for itself and developing its own ideas effectively. Okay. Now, obviously, you can kind of ignore the point about the, the kind of faculties of a human being developing that system, right? Because some people would say that the falsehood is in the human being. If the human develops the AI, is it truly, is it truly capable of doing everything it's capable of, it could do over time, right? So, you know, human beings develop certain things in a certain way. We behave a certain way. We're conditioned to behave in a certain way depending on where we grow up, what we learned, who we were, who are we with, etc. Those, those conditions are often passed into how we code, for example. So if we code an AI, is that AI truly capable of being an artificial intelligence, or is it just going to be a facsimile of what we want it to be? Right. So when I look at AI, I look at neural networks. And neural networks, because I, my computational— I did a master's in computing, and I, you know, I did essentially computational graphs and things like that as part of my research paper. So to me, a neural network is essentially essentially a self-learning system that is capable of developing knowledge by its own means through rules and learning and through data, but effectively is capable of evolving into something on its own, not necessarily something that was developed for it by its coding owners or coding developers.

So there's a big difference between machine learning and AI?

Yeah, machine learning is a set of data rule sets that are designed to create heuristic rules that will produce a certain set of results according to a set of data inputs. And as we all know, the more data you provide, or the more widespread the data is, the more capable that machine learning becomes. But you've got machine learning, you've got deep learning, you've got various other forms of learning as well. I, I stick to the concept that actually, to me, an art of a true artificial intelligence system is a neural network. It's something that has the ability to grow and expand on its own without any real guidance or dictation from any human being.

Do we have any such systems right now, as a, you know, to your knowledge?

Oh yeah, yeah, there are loads. I mean, we've seen them, you know, we've seen Google has them, IBM has them, the big companies have started playing around with true neural nets. And we've probably all seen the memes online when you get, you know, you get Google arguing against Bing or whatever and that kind of stuff. So those systems do exist. And they are becoming more prevalent, and people are beginning to get access to this technology without actually knowing it. You know, you've, you've probably no doubt dealt with all the media fuss around things like ChatGPT, etc., etc. ChatGPT is just one example. It just happens to be a known name that people have stuck to, and, you know, it's now become synonymous with AI, and it is an AI, but it's an AI that does specific things. With specific data, and there are different versions of it that does other things with other forms of data.

Okay.

A true AI is capable of generating.

So we can easily predict, and we've probably seen this right now, where these generic machine learning solutions or AI maybe even goes to non-tech industries, healthcare.

Yeah, it There will eventually become a time when every industry is impacted by AI of some kind. It's beginning to affect now, but, but there will— there's also an argument saying, you know, at what point will AI take over every role that exists today, every kind of job that exists today? And I would argue that actually there are some jobs that AI can't do or shouldn't do. Um, repetitive tasks tend to be the kind of square sweet spot where AI tends to be replaced, replaceable in terms of human beings and stuff. And in areas like medical, medicine, even things like construction, there are beginnings of kind of very early-day exploitations of AI technology, starting with machine learning, obviously, because construction is essentially a rule-based system, is a rule-based process, right? You construct to a certain set of rules, you build homes to a certain set of conditions and architectures and specifications. So, you know, there are a lot of people starting with the machine learning level, and then progressing upwards to other things. ChatGPT came on the scene, and with things like DALL-E and various other things like that, people began experimenting with ChatGPT to create architectural designs for buildings. But again, those buildings actually are not— to me, they're, they're, they're great illustrations of what a building could do, but they're not buildings that you can actually really build without going through further definition with human beings or other systems to create buildable constructs. Right, they're great visuals, no doubt about those great visuals, but those AIs are still not capable of building yet a system that's, that can be built today without further tweaking.

Okay, so if we ask the question, how generative AI or AI in general will reshape the enterprises, Currently how it looks, it's, it's all automation of repetitive tasks. That's where the majority impact is happening, isn't it? And then if we push the boundaries, that's still early stages. From your point of view, how quick that will change? Because, you know, when people talk about technology innovation, it's very exponential. So, you know, there are people saying that in 5 years, we, you know, we're going to have a totally different you know, global market landscape and a lot will be driven by AI services or products?

Yeah, I mean, I think there are several things that will happen over the next 3 to 5 years, probably possibly earlier. The faster the timeframe depends on the legislation. So the legal, law makers, effectively, the, you know, governments and institutions, etc., that govern the industries that we work in, etc. Right now, governments, etc., aren't really, you know, they're working towards embracing AI, but they haven't really embraced AI yet, right, to the point where it can truly become mainstream because there are still laws and governance around things. So things like mortgage applications, for example, people have been using machine learning to make mortgage applications easier, faster, and quicker forever. The thing about those is you still require a human being to assess the final result. Because you— it's the legality of that decision, right? So is a machine-made decision as legally binding as a human-made decision? Well, you can't sue a machine yet, right? But you can, you can technically sue the developers of that machine, or you can sue the company that owns the machine, but you can't sue a machine. So, you know, at a kind of big corporate level, using AI for that kind of stuff is fine, but independent financial advisors using using AI is kind of slowing, is not as fast in terms of adoption, because you've got issues with, with the legalities of the outcomes that have been presented by the machine learning systems. You then got other cases where adoption will occur once people get over the fear of AI. There's still a kind of, I still see a 50/50 mix in the marketplace right now. If you go and take a look at the media of people who are propagating fear and paranoia and others who are just proposing that they should just be free rein on AI. And you've no doubt heard of the kind of various stories being pushed around about Elon Musk proposing controls and various other things, which is odd to see considering he was one of the first investors in things like OpenAI. I mean, those controls are required, right? Because we can't— a lot of people won't allow machine systems to run free rein for various reasons. Um, so we have to come up with controls that allow the development of innovation without stifling innovation, really.

Okay. I mean, my view when all this situation with Elon Musk started around, you know, uh, fearmongering and sort of pushing the regulations, I feel like he's just trying to stop Microsoft from taking majority of the market share. It's just like, I did like that. That's how I felt like that. That was my initial opinion. I was like, you know, they, they sort of taken a huge amount of market share when it comes to, you know, with the ChatGPT. And I was like, you know, big companies, Tesla and, you know, Meta and Google, they have their own products. And you maybe you don't want to give someone, you know, the majority so quickly. So that was my thought. But I do buy into it. And when you talk about regulations, I think about blockchain and how many years it actually it's taken for it to become you know, a lot more than like speculative black market, I don't know what's going on type of financial asset. And that was like, that's what, like, that's almost like 15 years now. So do you think AI will move faster than that?

I, I think AI will move faster for two reasons. One was blockchain was confusing, right? Blockchain, blockchain's entry into market was on the back of Bitcoin, really, for the, for the general person on the street, right? If you go and ask anybody in the street what they think of blockchain, even if they know what blockchain is, they'll first think of Bitcoin. And the good sides and bad sides of Bitcoin just cause issues with blockchain. And you know as well as I do, you know, the reality is blockchain in the form of, you know, the raw technology into the distributed ledger, it has its use cases, but the majority of the first and second generation use cases were just not correct. People were just using it for the wrong things, or people were just using it because it happened to be a flashy thing. It was the latest shiny thing that could attract investment from people that really understood, didn't understand what they were doing. And that's what caused the problem, and that's what caused the delay. Now what you're seeing is people who settled down have begun to really look at the value of a DLT system and where it could be used, and they're now only using it where it's necessary rather than thinking, 'I'll just apply everywhere,' right? It's the same as encryption technology, for example. You know, one of the things I argue with people all the time is, do you have to have 256 AES encryption for everything that you do? The answer is no, because if you've got low-value data and you want high processing speeds, applying a 256 AES to it, it's going to slow everything down and it's going to make everything more complicated. So the reality is you apply the technology to what you want, and I think Bitcoin got caught out in that. First generation, first generation, second generation applications were just— people were just using Bitcoin because— sorry, people were just using blockchain because it just sounded good. They really didn't understand what they were doing with it, and in some cases having blockchain in that system overcomplicated the system. AI is different. I think AI is more being led now by people, as to your point, who are looking at using AI as a, as firstly as a means to remove repetitive work from various procedures and processes and practices in a business. And that's a perfectly valid use case. And then what they're then now beginning to do is they're beginning to extrapolate and stretch the capability of the more modern, the more capable AI systems out there, to look at areas where AI can be truly a complementary activity, a complementary technology to the human being. So medical, medicine, etc., could be interesting. Architecture is a case in point, right? You can, you can use an AI system to generate hundreds of thousands of designs for a given site. And they could do that in minutes, whereas you would take a junior architect days, months, and years possibly, do the same thing. A computational system can rapidly speed up that process in terms of the, what I call the feasibility process of it, right? You can say, look, what is possible? You can ask speculative questions of an AI system with zero, relatively zero cost. Whereas doing that with a human being in a traditional way, using even using junior developers, junior architects, and junior engineers takes time. Whereas a computational system will say, actually, if I have no constraints, and I'm not worried about anything, what is possible. And that's a question that has been very rarely asked in every industry, because it's normally the pioneers and the kind of crazy people, if you like, that in those industries that don't care about the boundaries and don't care about constraints. A machine system has no real constraints other than what you tell it to do, right? So you get to a point that says, you know, I want to design a bike is Is the way we've designed a bike the most optimal way of designing a bike? Well, that's based on human design practices, right? A computer may see it differently.

One challenge. So the company I currently work for, which is enterprise, they have rules around AI and it, it, especially about public services of AI, like ChatGPT, you know, Grammarly. Yeah. They just simply don't want people to, you know, leak what potentially could be, you know, a very important information, right? And as well, there's some rules around don't trust what AI says, you know, has a tendency to hallucinate and things like that. How do you think this will get overcome by enterprises who actually should be using AI to just purely for automation purposes?

Um, good question. It's— I see it the same way that cloud was originally. If you remember back in the days when cloud first became— came to market and companies like Google and Microsoft came and and Amazon offered cloud services to enterprises. Enterprises were the last bastion of control. They basically said, no way would I ever put my system out in the cloud. They started building their own internal clouds and then started realizing the value of the cloud, actual technology and the principles of cloud. And then they began experimenting externally, albeit small, but then grew and grew and grew. Now you get to a point where most enterprises, most large enterprises, actually are using external clouds. In various forms. They either use cloud services, or they're using raw clouds in the form of Google hosting, AWS hosting, etc. Okay, that, that process took time, because it came down to familiarity, it came down to overcoming fear, right? Because it's the loss of control factor. It's like, well, I know what's in my data center. I mean, I had this when I was at BT, right? I know what was in my data centers, because it was my data centers. I designed them, I run them, I manage them. If I'm trusting Google, I have to then trust them with a large proportion of my business. And in the very early days of cloud, there were issues, there were instability problems, etc. You know, various— we've heard famous issues of, was it Netflix systems falling over because they were running on Amazon, for example, right? Those kind of things have been overcome. People learned, the systems matured. So we need to do the same thing.

We, you know, when you think about the adoption curve, right, the enterprises will be the laggards effectively, and the innovation will get pushed by much smaller businesses which are not in any situation where they care about that. They just want to use the tools, you know, get the automation in place, just push it.

And yeah, it's a balanced risk factor. Most enterprises today, as I said, are using AI in compartmentalized situations. But it will become a point where, you know, AI, AI services become available, right? So anybody who uses Microsoft today, technically has the ability to deploy AI across their entire enterprise. In fact, they already do, whether they know it or not. So inside the Microsoft, if you're using Microsoft 365, you've got various levels of AI embedded in that system already, that are pervasive to your enterprise, whether you choose to or not. Now you can turn these things off, but some of them you can't really turn off completely because they're still there. So it just comes with the thing. Yeah. And I think you get to a point where the enterprise will have no choice. It's going to be inevitable, right? It's a case of if the whole of the street is going into AI and you're the only one not in AI, you're kind of being a little bit silly. It's the same thing that happened to cloud. As soon as the market street went to cloud, Everybody on the street needs to go to cloud because that's where the work is done. That's where the cloud— that's where the majority of the business is done, etc. It's like basically saying, you know, I don't want to go into that park over there, I prefer my own park. If you're the only person in the park, you've got no business partners. Same thing happens with cloud, same thing is going to happen with AI. As soon as people realize that the fear can be managed, that it can be controlled, that you can, with proper policy and application, make sure you're doing the right things. You know, the point you make about people fearing the, the, you know, loss of data, for example, is a valid problem, though, right? It is. In order for you to go and get Grammarly to do its work, you've got to send your data to Grammarly, and it has to do its own thing. You've got to get over that fear. And it will happen. The benefit balance versus the fear balance is going to become overweight at some point towards benefit. Because again, you know, people are going to be doing it, people are going to be using it, you're going to have no choice at some point. You know, the whole of the market that you're selling into is on AI, is using AI in a cloud somewhere, you've got to be there. You can't stick it out yourself.

So that's a good recommendation and a shout. So if I'm, you know, say small startup, maybe 10 to 40 people, is there anything On top of your head would be as a suggestion of how businesses can leverage AI today to have impact on, you know, potentially all operations. Yep.

Absolutely. Commodity services would be my starting point. Every business is essentially the same, whether they're small or large. Every business will need a finance function and an HR function. Maybe even a legal function, etc., etc. And, you know, if you're a small business, you've got to decide as a business manager where to apply your investment, where to apply the available capital. And I would always advise people to apply in places where there's definitive IP or definitive value in what you do, right? So if you're a code— if you're coding shop, then obviously developers and stuff like that. But if you're a 30, 40 person organization, do you need your own HR team? Probably not. Do you need your own accounting team? Probably not. Do you need a dedicated legal support team? Probably not, right? You can go to various forms of AI tools, etc., that are out there today, or you can go to even raw things like ChatGPT and do it yourself, right? And get ChatGPT to give you a very basic but structurally correct framework for legal documentations, HR, and so on. You know, every single day, if you look at some of the listings that are out there, there are several websites out there that you can go as a business user and say, right, I'm interested in these kind of things, and it will tell you the, the number of AI systems that exist today that you can subscribe to that will give you those services for free. Yeah, and that, that is everything from financials to trading, right?

That is the thing.

So look at the commodity things that cost money and avoid them because essentially there's no need to buy this kind of stuff until you're ready. Do you need it for yourself, right?

Yeah, very good shout. And that is the first wave of the products, at least, which I seen coming in the last year, which is effectively an abstraction on top of like ChatGPT, which is targeting one specific problem. And, you know, you got some product marketing emails, you know, research and things like that. And it's just like, you know, services on top of ChatGPT, just having a good prompts effectively in the back and just gives you an interface. And that was the first wave. I mean, it's very interesting to see how the second wave of these services, you know, will look like. But, and if you look from—

yep, it's interesting you ask that question because the wave in kind of personalized adoption of AI has followed the wave of the original personal information managers, the PIM systems, if you remember all the way back. So if you remember all the way back to those, you know, handheld devices we used to all carry around with us in terms of identifying, you know, managing our day, our diary, and all that kind of stuff that evolved into the BlackBerry, right, which is now into the smartphone and stuff. We carry those kind of personal systems and those AI systems with us every single day. I mean, pretty much every single one of us that has an either an Android phone or an iPhone does that already, right? We have, we have very sophisticated AI systems sitting in our phone or connected to our phone that we use every single day. And we are probably using services that are based on AI or processed by AI. But we don't actually see the AI bit of it yet. Because we're getting the services in some other form, even things like, you know, restaurant recommendations and mapping systems and all that kind of stuff, right? There are various forms of AI, various levels, we take advantage of every single day. I think to your point is, it's businesses need to decide, small businesses need to decide what's more valuable to them, first of all, and then, and then buy the services in as AI services and secondary services to help their business grow, because that will give them the ability to, to make themselves operate at a much higher level. And they have the facilities that every other business has. I mean, I've been using an online secretary, effectively a virtual secretary for years. And it does help because I don't, you know, I manage like 6 or 7 diaries, and that thing, that system manages it all for me. That's a significant amount of time because to me, the one commodity that we've never— nobody has yet solved is the loss of time. That's the single most important commodity to me, right? And I've learned that over time, that, you know, if I can save 5 minutes a day, that's 15 minutes every working— 25 minutes every working week. That's only half an hour working week. Just because I don't have to mess around with my own diary, right?

Um, yep, that's a good job.

The other example I use is things like, you know, things like Amazon, for example, is a service, but it's a service that's provided by the else, you know. I buy a lot of stuff through Amazon because actually that saves me almost an hour a week, you know, because I don't have to drive to the shops or those kind of things, right? That, those kind of supplementary commodity services are where I would advise small businesses to look and say, well, look, Do you really need your own internal? Is it really worth it to have that internally? Just buy externally until the point you're big enough to afford your own, then, then do it, right?

So you mentioned 7 diaries, Corey. Is that— what's that about? Like, how that came to be?

So I have— I, I keep my diary separate. So I have a personal diary for what I do. I have a work— I have 2 work diaries. Um, and then so, so sometimes I have a diary for if I, if I start a large contract, contract, for example, I set a diary up for that and that keeps, keeps everything separate. Then I have diaries for the other things I do. So I, I coach a football, I coach two football teams, for example.

Nice.

I have a diary for footballing events and things like that. I keep them separate because it's easier just to keep them separate. Um, and I can chop and change accordingly depending on what I want.

So you, you basically have 7 diaries or even more and use AI to, to bring them together and give you like a one holistic view of how your day and week look like. That's actually quite cool. Yeah, I need to, I need to explore that because I got 4 diaries and I'm like always sort of, you know, because I have multiple screens so I can look at all of them at one time. But having one over this, that's a good job.

Yeah.

So you do consultancy work, right? And that, that's where that different diaries comes from. So remote team management. So let's jump in the next, next topic. Yeah, so I'll give you this context from my perspective. Uh, I have a couple of teams in Europe and Asia and Africa, and they all sort of has to be, you know, under the same bucket of, of deliveries. And because they're all remote teams, right? I, I found myself not really caring that much about their career progression, team gelling, you know, all these like social elements around the teams. And it all became almost like a project management, right? So which, which was different role for me coming from, from, you know, this remote but like distance setup or hybrid teams where I meet the team and, you know, I hire for the team and things like that.

Yeah.

So when you consult businesses, I imagine you are in a very similar situation. I mean, how do you look at running remote teams in general?

Well, first of all, I think it's a necessity today. You know, Brexit aside and other things, the world is evolving and the availability of what I call nearshore or on-site coders and developers is becoming rare. It's quite hard, you know, the competition is quite high, especially in London, for example, right? So I think, first of all, I would say it's a necessity to do kind of nearshore offshoring services. But I think of these as technical services rather than external contracting. So I'm not buying individual contractors from a third party, I'm buying a service. And that service is typically related to doing a project or to doing a part of a project. So I give them, you know, maybe I give them the front end to do, or I give them the back end to do, or give them a part of the front end, whatever. To your point, I think there are 3 aspects that I'd look at that I think are important to consider when you're doing this. Um, one is culture. Um, you know, it, uh, you know, it's fair to say that different developers will develop different way based on the culture in which they grew up, right? So Indian developers develop differently than South African developers, for example. That's not to say one is better than the other, it's just something you've got to consider because conceptually one may know more about one thing and the other may not, right? So certain concepts may not be as prevalent in India as it is in the UK, for example. Therefore, you've got to educate and overcome those cultural issues. Practices are different as well. So although everybody supposedly claims to operate to the same standards, you know, when you talk about Agile or whatever, there are— I have found there are localized interpretations. So you can't go into these relationships assuming that your version of Agile is their version of Agile. You've got to do that correlation and figure out that. And sometimes you Sometimes you've got no choice but to trip over it, right? Where you kind of have to learn through practice. Because you can't really do a kind of compare Agile books at the beginning of every project, right? Because that's going to slow things down. The third thing then is conceptual or conceptualization. The way developers think about coding, and how you code the actual, you know, physical program, again, tends to be different depending on different locations. Um, what I always try to do is I always try to work with agencies that have a, a higher than average or a large proportion of people who've worked multiculturally, multinationally. So, you know, I do a lot of work with a company in Bulgaria right now. I have a project in actually Lithuania as well, and I know the two organizations I'm working with actually have a high number of developers who have worked in different countries. They have more diverse backgrounds, more diverse experience. And by doing that, I always guarantee that I'll have a higher level of understanding, a higher level of acceptance earlier on in the project. Because most of the stuff I do is, is not necessarily unique, but conceptual in nature, right? I'm doing something new. I'm not trying to repeat something that's already been built. So I have two problems then. I have to then educate the developers who probably have never heard of these things before or never worked in these industries. So take construction, for example, where I have to explain how the concept of actually building and modeling a building should work in architectural terms, and then having to explain that to a developer who's probably never come across an architectural design before. But all I want them to do is to develop the construct that allows me to model that building in 3D space. So that's one area where, you know, you do this. So I think those 3 things are things— important things to consider. The rest of it is then down to practice, procedure, and what— not so— regimentation. But I don't mean strict regimentation. I mean, basically, I have a process that I've learned and built over years to say when I work with third-party service developers or service agencies with a master service contract. I go through a specific routine, everything from the point at which I specify and source them all the way through to the way I work with them. I have a very specific routine of how I work with them, including down to things like when I want updates, how detailed the updates are. You know, I don't need to know that a developer was ill yesterday. But I do need to know what that illness caused in terms of impact, for example, right? So to your point, when you do these kind of service relationship, third-party service, you know, far-reaching service relationships, your emphasis is more on managing the activity rather than managing the development itself. Because you don't, you know, I'm not, you know, you and I won't be involved in a low level. We will be involved in the coordination space. And I, my leverage point is the quality of the outcome. Whereas if I was running, as you and I were running a team, we would be able to go all the way deep into the QA level of the coders themselves. And you know, if they were, if they were on-site coders, we'd be able to see them, etc., etc. If they're, you know, in a different country, you don't have those privileges. And you shouldn't, right? You should, you should trust them.

I like the definition managing the activity a lot more than anything else. So I want to take us back into the very first point where you said that the development in London is actually becoming rarer. So when I always looked at the, you know, offshore services, or, you know, building teams yourself, for me the cost was the driving force. Are you saying right now that, you know, the market is not only the cost but an actual lack of Thailand pool when it comes to UK? Yep.

Okay.

Um, yeah, yeah, yeah.

Um, you know, Brexit is definitely a cause. Um, there has been a definitive slowdown or an available— a lower availability of developers. Most, you know, most Eastern European developers have gone back to Eastern Europe. Um, the availability of developers from places like India, for example, slowed down as well. So You know, if you want experienced developers in London, you've got to pay for them basically, and there is a higher level of competition for those developers. But also, I think it's also true that the economic conditions worldwide is causing developers to be less mobile, right? They tend to stick with longer-term contracts now, and actually there's an argument to say that most developers will favor full-time employment rather than contracting work. And it's something that is impacting the market. You're always seeing it every day, right? It's impacting. And the level of impact is worse depending on skill set. So we've always known that data scientists, for example, are very skilled and very rare. But now if you want Python developers, for example, anywhere in the Square Mile, you're fighting a lost cause unless you're developing. So if you're in the financial market and you're looking for an experienced Python developer with 5 years or more skill set, you're, you're asking, that's a lost cause. It is really tough.

And that effectively, as a business owner, you are forced to just expand your, you know, searching radius effectively and go outside London and look at others. Do you think the, the, you know, the pandemic and work from home, uh, had impact on this, or do you think the markets will sort of do 360 and come back to something which is less favoring that offshore module?

It's actually, it's a good question. I think it had some impact, but I think the impact was in two forms, right? One was that all this kind of staying at home, etc., etc., unless you had the mindset to do so, very few people did anything when they were at home. Most of them just kind of chilled out and relaxed, right? There were some people who obviously went and tried to relearn and kind of, you know, redevelop themselves and and learn new skills, etc., because they either lost their jobs during the pandemic, or they, you know, they were forced into a position where they realized that they wanted to do something different, for example. So I think there was definitely impact there. There's no doubt about that. Whether that impact has continued, I would say some of it has continued. But it's more a case that people now realize there is actually some truth in the value of homework balance, work-home balance, work-life balance, or whatever standards you want to choose. Because people did realize that actually you can work from home and still produce output, and it's good output. And for years, enterprises have tried to hold people to an office location because it's always been considered to be a control point, right? But actually, that control point is very expensive, you know, especially in locations like London, right? Canary Wharf office space per square foot is massively expensive. So if I could do the same, if I'm a business owner and I can have a distributed workforce working from home, where I'm not incurring the office space, but all I'm doing is providing them possibly with internet, whatever, or other services, and I then go back to what we discussed earlier, leveraging web-based services as much as possible, right, so Microsoft 365, etc., etc., then the reality, my operational cost base is very, very low, right, my overheads are very, very low, but the output remains the same, if not better, because of simple things like, you know, an office person, if they have to travel to work in London, the travel time is dead time. Whereas an office worker who's working at home, they'll get out of bed, make a cup of coffee, straight to work, etc. They'll often work longer hours because they don't— they can either bleed into the dead time, or actually they find it more useful to work when they're more comfortable working rather than being forced to work. And I think that's different as well. So there is I think there's been positive negatives. There's been a lot more kind of home development going on. So some of the stuff that I've come across where, you know, the development team is effectively the distributed development team, they don't, they don't come into the office anymore. In fact, a couple of startups I'm working with already don't actually have an office. All of the development is distributed. And then, and then the, the concept of using kind of service-based development contracts is more of a volume-based thing. If I need, if I need access to known good skills, and I need to do something within a certain defined timeframe, I can't really afford the time it takes to build up a team, recruit the people, train them up to my skills, etc., etc. I give that to somebody else to do. And that, those two skill sets, or those two opportunities, actually is quite useful for a technology company today.

Okay. So one big challenge from distributed teams which I encountered is the communication.

Yeah.

When the teams have different time zones. So communication in general, I mean, if we are, you know, distributed, but if we are synchronous teams, meaning that we are online at the same time, the communication become a lot easier because, you know, you have Slack, you have Teams, and if people are, you know, good with those tools, the information actually flows quite okay. But if we are synchronous teams, meaning that you work while I'll sleep and I'll work while you sleep, then that, that's where my main challenge is, because the details are getting lost when the shift changes. And when the new, you know, shift comes up, they basically don't know where to continue. So if you have any experience around that, like any tips, um, how one could manage—

yeah, no, it's, it's a good point. It's one of the biggest learning curves I had to go through. The asynchronous nature. So back in Bank of America, for example, I had development teams in the US, in Europe, and in Asia, right? So the asynchronousity of that process was even worse, because I had 3 time zones to deal with, actually 3 more. So that comes down to what I said earlier, I've developed essentially a regime, a process, if you like, that I use for managing this type of development contract service. Where things like the requirements are, are more formally documented than they would be normally, for example, right? Everything is shared within a shared document, etc. So regardless of who comes in or who, who picks up a piece of work, whether the shift's working or doesn't really matter to me because the definition of the requirements in a single place and people can always go to it. The other thing I think is important is leveraging technology to do the work. So it comes down to the individual behavior. But for example, when I use Slack, if I get a Slack message at 9 PM at night, where developer unknown in India is asking a question, then I will respond to it. Now, I'll take a choice. Obviously, I don't want to do that every single time. And I don't want to spend hours responding to it. But if the question is, hey, you know, I've looked at this requirement, and 'You know, we think we should do this and you're asking us to do that, which do you want?' The answer is, I can answer that, right? It's to me, the timeframe is if I can spend 5 minutes answering that question then at 9 PM, rather than waiting till the next cycle, then I've saved myself a lot of time. I've saved them time as well. So I tend to be a bit more, I guess, accommodating about it. Because if I can use tools like that, you know, whether it's Slack or ClickUp or those kinds of things, and keep track of these things, then it makes it easier for the continuity to take place. But you're absolutely right, if you're not careful and you don't deliberately manage the continuity or put constructs in place, a framework in place to manage continuity consistently, you will run into issues. And again, my, you know, the first couple of projects I did using third-party service providers in Thailand, for example, suffered the same problem, right? Not only did we have a language issue, we had an interpretation issue. But because we didn't define the requirements clearly enough that allowed both sides to communicate using, you know, using some form of translating context, then it basically meant that their development drifted. So by the time, by the time I got the output, all I could see was the wrong things. I couldn't, I didn't have time to adjust them in flight. If you want to adjust them in flight, you've got to manage them in flight.

Yeah. Um, so my go-to solution is to think about a place which I, which I call source of truth. So meaning that, yeah, you have different communication channels— could be Teams, could be Slack, could be Skype, could be emails, could be just meeting conversations. But if there's a new information point, a decision being taken, like, it has to come back to that source of truth, and it needs to be be, you know, be an update. And yes, it all works out often that it's a, it's, uh, it's some, some type of development ticket because everything, you know, effectively flows around development. You have a ticket, as long as you, you know, write this ticket well up, you have acceptance criteria, everyone knows what that ticket is delivering, and then, you know, the comments are always fed in. I mean, conceptually it sounds like great, but Practically, it's actually not that easy to, to get it done, and you have to police it to some extent, which goes back to that, you know, your definition of, um, you know, managing the activity, right, rather than the whole development. Because like, you, you know that activity is necessary to have that information flow, so you manage that activity. You have to police to some extent, then it becomes some, some type of habit or cultural element, and then it you know, works better.

Yeah, yeah, yeah.

All right, so we're running out of time. Yeah, go, go finish.

You, you have to, you have to, um, you have to plan. You have to plan way more than you would if you had your own team, and there's no doubt about that.

Yeah, 100%. That, that's a trade-off you pay with the, with the offshore racing teams, and there's some other trade-offs, you know, but that's one which comes up like day one. Like if you have that, that's going to be one which will meet you straight off the get-go. So I really wanted to touch on tech funding, and I just looking at the time, we have like a couple of minutes left. You know, I, I know you, you help startups to raise money, and you know, you have your take on the process. And you know, we know the market is changing currently, you know, 2024, the market is like— I mean, it started being not great, you know, uh in 2023. That's the main reason why I stepped out from startup scene, because the liquidity, the money is just not there. And, you know, investments are much, much harder to come by. So can you give us your take on the market, on what the founder should be looking at if they're looking to raise money, and just anything else you think would be useful for, you know, for people looking for money this year?

Yeah, sure. Um, so first of all, I agree, you know, the market is in a bad place right now, and it continues to be in a bad place. To be— I mean, to be fair, it's a continuation of what happened in 2008, right? The market really hasn't recovered from that point of view. It's only been exacerbated by recent issues like Ukraine and other things like that. It's just given people an excuse to, to almost think harder or, or slow down the process of investment. What What has also occurred is people beginning to look for more clarity and more proof points when they, when they make investment decisions. Um, there was a lot more speculation in the early days, right, 2, 3 years ago, a lot more speculation there is today, whereas people are now much more careful about their investment. So I would say if you're, if you're a founder and you, you know, of a tech business and you're looking for investment, the 3, the 3 things I would say are critical to to do is one, be very clear, as we said earlier, be very clear about what your business is and what it brings to the market. Are you doing something new? Are you doing something different? Are you doing the same thing but in a different style, or you're just copying somebody else? None of those answers are wrong, by the way, right? Because you can, you know, you can be the— you can be like the Indian version of Amazon and still make billions of dollars, right? And that's still a cool thing. You've got to be very clear about your plan and expectations. Because people who daydream all day about being the next unicorn are suicidal. People, people know they're not looking for the next unicorn anymore. If you can make $100 million a year as a business, you're doing well, right? The likelihood of making another unicorn is really exceptional. So don't, don't overestimate. And the third thing is be very clear about what type of funding you want and from what type of funder you want the funding from, because not all money is made equal. And although money may be the same color, they don't all come with the same expectations. So venture capital investors will think differently to, you know, different family office investors, for example, right? A private equity business will think differently to a venture business, etc. You've got to be very clear about what you want, but also be very definitive about what you want from the investors, because it can't If you're— all you're looking for is money from an investor, you're in the wrong business. You've got to be able to leverage those investors for more than just capital, because today an investor investing in a business today will want a deeper relationship. They're, they're no longer just going to spread back money around anymore because they need to be clear that the money they're putting into a business is actually going to do something useful. And it comes, it comes down to outcomes again, right? Is do I know this person has the ability to do this And is the market willing to buy what this person is building? Those two questions have never changed in real terms. The value of that question has changed, but the questions themselves have remained ever since the first days of venture capital business. So if you're a tech founder and you can answer all three questions very clearly, very simply, you stand a better chance of getting investment capital. There is money out there, but those people are going to expect a lot more from you when they're making their investment decisions. They're no longer going to say, yeah, cool product, here's some money. It's okay, we need to have more conversation, the process is going to take longer, right? You're going to have to explain yourself better in a deeper way. You may be asked to give away slightly more equity than normal, etc., but you can earn that back, right? So don't— a lot of people come to me and say, you know, I'm being asked for too much equity here. It's like, well, there's always ways of negotiating equity back on base of performance. You can get performance-based equity returns. So don't freak out simply because somebody's saying, well, I'm looking at the risk involved, and the risk involved means I need to have a certain amount of equity in order to justify the investment. There's nothing wrong with that conversation. You shouldn't run away simply because people are asking for more equity. You should only run away if they're asking for a lot more equity but not enough for the money they're giving because that's exploitation. And unfortunately, that's happened as well. That happens too.

Any specific metrics people should be like— let me rephrase that. Did anything change around the metrics? Are we still looking at the same as we were looking a couple of years ago, or because of the market conditions, things such as you're making revenue is like the most important now?

Yeah, so there has been— I think I'm seeing a bifurcation in the market. So there are people who are willing to accept concept based on, on— so if you're investing in technology, for example, they're investing, they're prepared to invest in concepts, but they would expect more, more equity in return for that investment because there's more risk, right? But there is, unfortunately, there has been a marked shift towards expectations of revenue as well. And I think that, that has caused a lot of the problems that you're you're kind of relating to, because if you're, if you're, you know, if you're a graduate straight out of university and all you've got is a great idea and possibly a prototype, for somebody to expect you to have taken a million dollars or a million pounds worth of revenue or some kind of revenue into a project is just not sensible. It doesn't make any sense, right? But investors are, you know, and they would say they're doing it correctly, investors are using that as a benchmark and saying that actually is a way of protecting themselves, but what it actually is doing is limiting their market space, right? So they're limiting, limiting their marketplace and say, I'm only ever going to invest in companies that have revenue earning, have already generated revenue. Well, I've seen enough companies who've generated revenue and still fail. Revenue isn't the only source of value. You've got to define the market value and whether or not revenue is sustainable. Just because I go to you and say, hey Mike, you know, In the last few years, I've developed, you know, $2 million worth of revenue. I need £20 million worth of investment. If you say yes to that without looking at the market viability, you're kind of suicidal. And founders need to understand that dynamic. They need to understand and say, look, even if you don't have revenue, you've still got to explain the potential of the technology. Same thing again, right? Is, is what you're doing valuable? And is somebody prepared to pay money for it? And if those two things are true, then you've got something worth talking about. If those two things are not true, then you need to go back and start again. Because just because you have the greatest idea in the world doesn't mean anything. Most investors will want some kind of return, especially their venture capital investors, right? They have a very shorter, much, much shorter time frame of expectation. Uh, family office and private equity business will have a much longer time frame. Okay, so again, investors correctly.

So come back, come back to the point, um, the second point of the plan and expectations. What would you like to see in the plan? Is it just go-to-market plan? Is it the plan of launching, making first million? Is like, what's some key points about how that plan should look like?

Um, yeah, I typically like to see a realistic plan. You know, I don't like seeing plans where somebody comes to me and says total addressable market is 20 billion, therefore I think the market is 20 billion. That's just pointless. It has to be practical. It has to be achievable, and there has to be data points to support why that plan would work versus other plans. Yeah, so that's the kind of issue. So the model I tend to use is like what I call a 1-3-1. So essentially, it's not my idea, it's somebody else's idea, by the way. So essentially, you have a defined problem, you come up with 1 to 3 options for solving that problem, and you pick a recommendation. So long as those things exist in your plan, then it gives me some sense that you've actually thought through your plan and that there is genuine reasoning behind why those dates, those activities, and those timelines play out in your plan the way they're going to play out. What I don't like seeing is people just putting dots in a chart somewhere and saying, you know, I expect to gain revenue in a year. Okay, how are you going to do that? What are you going to do? The how and what is important, right? Again, how, what, who, you know, how is it going to happen? What's going to happen? Who's going to do it? Right, that, those kind of things, those, those, the detail behind the plan is more important in some cases than the plan itself because I want to know how and why things are happening. So the more planning you put into your plan itself, the more value you put into your plan, and the less conjecture in your plan the more likely you are to receive investment, because the more speculation and conjecture you have in your plan equals more risk. And if you apply more risk into your plan, even if somebody wants to invest, they're going to want more protection, downside protection, in return for the money they invest. So they'll either invest less money for less equity, or they'll invest the money you ask for, but they'll want more equity as downside protection. That's just, that's normal natural law. You can't stop that, right?

And it makes you feel different as well. Once you do that homework, effectively, you know what you're doing. It makes you a lot more confident, confident in conversation around the money and, you know, what you're asking. And so I've seen, I've seen some pitch deck and some pitch processes where Well, what's the word you said? Um, it's basically just dreams, right? It's like, you know, next unicorns, you know, here's market, you know, I'm gonna get that amount.

Yeah.

And then once you start grilling around and actionable items around how you're actually gonna get that done, everything becomes—

yeah, one of my old bosses has a phrase, it's called naivety driven by passion.

Right. That's a good way.

You can be passionate about a subject and you'll type it, but if that causes you to be naive in what you're trying to say, then you're never going to convince anybody.

Yeah.

You know, if I say— if you say to me you're going to generate a million pounds by the end of the year and I ask you how are you going to do that, you can't answer the how, you're not going to get very far. You can, you can be as passionate as you want about a topic, but unless you know how, you can't convince investors that they're going to trust you. Or If an investor does trust you, they're probably going to force you to do things their way, which is the last thing you want, really, right? It goes back to what I said earlier, that when you ask for investment from an investor, especially a venture capital investor, you also need to be very careful about what else you need from them, because they may impose things on you as well. Oh yeah, right. As a venture capital investor, to limit their risk, they can say, well, actually, I don't trust your business plan, I'm putting a finance manager on my own into your business. That's just another way of losing control of the business. You don't really want that to happen.

How does, how does the pitch marry the plan? Are we saying that you get the plan done? And by the way, 1-3-1 is, is, is an awesome framework. So you, you do this and then you sort of get the best bits into the pitch, or the pitch is a thing of the past and, and, and in the current markets, people want to see a plan.

The pitch is still important. You still gotta, you still gotta excite people about what, what it is that you're doing, right? So the product, the service, you know, who you are, those things still play a valuable part in the pitch deck. And, and I would still include those because you still, you still have to do a selling job. A plan is just a means to an objective, is a, is a route plan to an objective, right? It's a way of achieving an outcome. That's all a plan is. But the plan also allows you to account for issues that you may not have accounted for. What the plan tells you, tells you and me, is the plan allows you to define your business, but it allows me as the investor to understand what you will be doing and how you will be doing things to get to the outcome. If I understand that, I understand when changes occur, I understand the previous, the pre- and post-change. If I have none of the pre-information and you're asking me to change, then all I'm dealing with is chaos, right? And if I'm dealing with chaos, then the reality I may have— I may have put— may as well put my money on the stock market. It would have— it would have generated me more value because there's at least stability and there's, there's, there's some form of trending in the stock market that I can account for based on analysis, right? I cannot account for your passionate emotion as an individual. And that's the one thing that I find founders get drawn out by, is they try to— they, they're overroared by their passion for the topic of what they're trying to build. They forget that actually what they're trying to build is a practical business, right? And they're asking for other people to, to take the risk in putting their money in on your passion. Passion doesn't buy business. Passion doesn't make businesses. Passion gets you really excitable It gets you very emotional, um, but it doesn't do much more than that.

Okay, so there's a lot of, you know, young entrepreneurs in tech space at least who effectively have an idea, you know, they think they got something. Yeah, they probably got no revenue right now, and, you know, they're looking to raise pre-revenue, right? Any advice to them, as in how would you approach such situation? Like, I don't know, there were two, there were two practical ways.

One, one is working with accelerators is still a good, good option. So there's quite a few of them, uh, quite a good, you know, a few good ones in the UK. Entrepreneur First, etc., are examples where they will put you through a framework process that will help you mature your idea, mature your business until such time as investable. Right? So it'll give you all of the assets and, and structure and framework to get you to an investable point. Um, if you want to be more speculative than that, then look at, look at angel syndicates, look at angel investors, look at angel networks. So again, there are loads of those available that are there. Those networks are, are populated by kind of less, I guess, less experienced investors. They're not professional institutional investors. They're not likely to ask you as many, you know, tougher questions as most investors would. And in some cases, what they'll do is they'll be able to speculate more and take more risk. But the same thing still applies, though. You've still got to have a good definition of your business, and you've still got to understand or present some value of what you're trying to do, some indication of what you're trying to do in form of a plan of some kind. You still need those basic structures.

Let's say you have a history of success with, with starting ventures and making into a business, so that makes things easier. And then, you know, you have a network, so, so you have people to go to. So this theoretical individual comes to you, Cory, and goes like pre-revenue raise. How much equity would you take in that? Because, you know, my understanding is that if I'm angel investing, like, I'm gonna take a lot more you know, than the hedge funds would be once you're actually in that position to raise that money?

Yeah, I mean, angel investors will always want more equity anyway, proportionally compared to a traditional venture capital investor. Your history and your track record is important, no doubt about it, but it's only important if you're kind of working in a similar space, right? So if you, let's say you have a track record of building, I don't know, games, apps, mobile games, right? And you've sold, you know, you've built and sold 3 mobile games in the past and you've got a 4th idea for a mobile game, great, your history of development and your skill set and your previous experience counts for a lot, you know, that's a big tick in the box for a speculative investor. But if you say, all right, I've sold 3 previous games and now I'm going to develop a restaurant app, then the questions will still apply. It's like, why would you do that, right? What What makes your experience in developing app, you know, gaming apps suddenly applicable to restaurant app? How are you translating from one to the other? What leads you to go from one to the other? What experience have you got from one to the other, right? I know you can build games, but what do you know about the restaurant industry? Those questions are still going to be asked no matter what happens. You can't avoid those. What you can do to help yourself is plan, right? You can say, you know, if there's any if there's any aspects of the gaming environment that lends itself, such as gamification, bonuses, tokenizations, those kind of things that you've developed in the games that you've developed in the past, if those are translatable to a restaurant app, then you should say that, for example, because that just lends, it just helps the translation work better.

Okay, I do feel that to some extent it might be a waste of time Like, uh, so if you have an idea, bootstrapping could be an option, you know. If you really believe in, like, you have something, you know, just put your own money, you know. I don't know, take a loan, take it to a place where you can actually be a viable candidate to raise money, because it takes time to raise the money, and it will be your time, right? If you're alone or with a partner, one of you it's going to be full-time for one person for a prolonged amount of time to actually, you know, get the data room together, you know, go through the pitches and, you know, land that money. Yeah, you're probably better investing that time into the product and actually getting it built out to the point where you can potentially actually raise the money. And, you know, the bootstrapping feels like a much, much better, uh, yeah, yeah, you know, path, at least in this market.

To be honest, it'll be, it'll be a question that would be asked.

Yeah, yeah.

So to be honest, it'll be a question that would be asked anyway.

Why, why are you—

I would expect an investor to ask you, yeah, whether or not— yeah, whether or not, you know, why do you need to raise money if you're, if you're a successful entrepreneur having sold, you know, previous generations of apps and businesses? Why aren't you doing this yourself? Why aren't you bootstrapping yourself?

Yeah.

And, and it is a question that founders do need to ask themselves, right? If they, if they— to your point, if they, they bootstrap it themselves, they've just generated they've created value and equity in their business that then puts them in a stronger position when they're negotiating external funding.

Yep.

So if they go, if they go with nothing, then they should, they should start from nothing.

Exactly. And a lot, at least from what I, from what I've seen in just like, you know, global markets, as in like LinkedIn and founders and startup communities, is they want to raise the money because they don't want to put their own money in. So they effectively just want to offload the whole, yeah, operational risk to someone else and basically go, yeah, give me money, I'll build this out, see what happens. And that's just not how you're going to raise the money, so it's just going to be a waste of time. So let's say you do the— you do the beginning.

It's unrealistic.

Yeah, yeah, there you go. Let's say you do the beginning, right, you know, and you, you are the point where you can actually raise VC money. So you mentioned the importance of actually finding the right fund to to raise the money from. Can you talk a little bit about that, why that's important?

Um, yeah, it's important for certain reasons. One is the, the nature of the world as it stands at the moment has meant that funds are diversifying everywhere. So you've got US funds operating in Europe, European funds operating in the US, people just trying to find opportunities to invest, right? Because the, the market of investable projects has kind of declined slightly. well, actually, in some cases, a lot. So, and the metrics for investment have changed in terms of the criteria for investment, why you would invest, where you would invest has also changed. So to me, I always advise people to look at who they're taking investment from because, A, taking an investment from a certain organization today may prevent you taking more investment later on because that organization represents a potential constraint. So one recent one, for example, is I dealt with a startup that took some investment from essentially a gentleman in Saudi Arabia. It was a small investment, not a huge amount, but it was nevertheless an investment. It was measurable. They took it on very, very early on in their business life, kind of somewhere between Series A and— sorry, seed and Series A. They took that money on, and then when they went to, to raise a Series A, they went out to the general market, and they had very strong interest from, from a number of Israeli investors, investment houses. But when those Israeli investment houses found the Saudi Arabian investment, they, they kind of weren't really interested anymore in that investment. Same thing happens if you, um, if you have like Chinese investors, for example. Sometimes there are connotations and constraints or kind of, uh, expectations of what Chinese investors might or might not do. Now, I've never come across any kind of situations where anything nefarious has happened. I have heard of some, right, but I've never come across it personally. But you do need to investigate what your investors are willing to do because also you may be able to leverage an investor. So let's say two investors are— you're asking for $5 million and both investors are prepared to give you $5 million. You should look at the investor that's prepared to do more for you, or maybe help you more, or maybe give you more opportunities. Because at the end of the day, $5 million, $5 million is the same, right? So you can take $5 million from an investor that can help you go to market. Maybe they've got specialism in this space, or maybe their portfolio already covers some of the areas that you, you work in already. They are more likely to, A, understand what you do B, be able to help you in another way other than providing money, and C, be able to provide you guidance on a one-to-one basis as an investor in the business, especially if they're sitting on your board, for example. That will be probably more valuable to you in the long term than the money itself, right? Most, most situations I've found tend to play out that way because those investors will be no pun intended, invested more in your business, they are more willing to associate with your business and more willing to help your business grow because it helps them. An investor that doesn't have any, any, you know, any kind of external excretion value is unlikely to be interested other than, I need reports off you every month, for example, because I put £5 million into your business and, and I'm dealing with that purely as an asset transaction rather than a value transaction. And that's really why I advise people to think about the investors themselves, because the investors are important. Who they are in your cap table, what they represent in your cap table, and the amount they represent in your cap table will have considerations downstream. And you may not know what those are now, but you're still going to understand what they are going downstream.

Is it possible to end up with the cap table which is an uninvestable moving forward.

Oh yeah, absolutely. Yeah, absolutely. Um, okay, probably in the last 5 years I've seen probably 10, 10 of those companies where you can receive— you can create an uninvestable cap table for 2 reasons, right? One is the people in the cap table are— toxic's the wrong word, but essentially they're not amenable to further investment, right? You can create a cap table where those shareholders may become activists in some way, shape, or form, and they are the ones that are causing some form of instability in the business. And that causes the, the, the, the business itself to be uninvestable. Because as a new investor, why would I put more money into a business when there are previous shareholders who have more leverage on the company than I do, who have more influence on the company than I do? And are doing some weird things with the company, right? The third situation is when the cap table potentially is so big, as in you've got lots of tiny investors and you've done lots of friends and family rounds, for example. If the cap table is huge, it's very hard to clean it up. And if your shareholder agreements are not consistent enough or defined well enough, those kind of situations can also lead to an uninvestable business because new capital tends to want to be clean capital. And if I was coming in, say, at Series B or C, I'd want to know that my money has a greater or equal leverage than the previous generation. And that, that could be an interest, you know, that could be a problem if those shareholder agreements don't allow that to happen, for example.

That's a very good shot. I think founders don't, you know, they get blinders a bit when it comes to raising money, especially if it's the first time. They just look at the, yeah, at the fact that they're gonna get capital and, you know, they'll be able to spend it. And, you know, yeah, you're absolutely right, finding someone which gives you money but at the same time is there to teach you how to multiply that money is such a, you know, yeah, much better transaction. And then, you know, conclusion is that taking money, it's a two-edged sword, right? You have to do that correctly as well, and because you can cause just an investable cap table or some other issues moving forward where you unable to raise more money or lose control of your business. It just comes with, with the risks to you as a founder as well. So Last question, Corey. Anyone in your network would you admire and think would be a good guest for the show?

Yeah, several. You want the names now?

Yeah, yeah, if you don't mind name dropping, you know, we'll get them invited.

So based on what we discussed, you know, what your intentions are for the podcast, there's one guy in particular. So there's a guy called Thomas Davies, who is the CEO of a business called Temporal. They are a very, very interesting software business. They're doing some really cool things in terms of organizational performance management. The software itself is an AI tool and is very, very helpful to help businesses understand the kind of true implications of their organization. So, you know, you had ERP systems and you had, you know, they're developing also, you know, RP system and organizational resource planning system. Thomas is interesting for two reasons. One is he came from a tech background. So he was one of the senior managing directors at Google. He left Google to start his own software business. So I'm kind of thinking that he might be a good conversation to have, because he can, he can talk about the transition from being a technologist, developer, delivering technology to enterprises from Google, to becoming essentially a startup CEO of his own, and still having to deal with many of the same issues, right, in terms of how do I develop things, etc., etc., but from the context of his own personal case. So he would be one person I would definitely recommend speaking to. I can think of a couple of others as well, if you have kind of specific topic points that you want to talk about.

Yeah, Thomas Davis, it's all good. We'll try to get him on the show. And, you know, thanks for name-dropping. So thanks for doing this, Cory. That was lovely.

Yeah, if you need a If you need a contact for those, let me know. I'm happy to introduce you.

I will, I will reach out, definitely. Thanks again. Uh, we're just over the hour. I mean, it's actually an hour 20 minutes. That, that, that went past quite quickly for me, so that was lovely. A lot of information, and I'm sure listeners will enjoy what you just said. So thanks for doing this, Corey.

All right, brilliant. Thank you. Cheers. No problem.