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Lee:
Welcome to the Event Engine podcast. This is your host, Mr. Lee Matthew Jackson. And today we have on the show all the way from Peru, the one and only Martin Suttill from 54 Solutions. I managed to say it this time, mate, because what is this? The second time lucky. Welcome to the show. How are you, mate?
Martin:
Hello, Lee. Very nice to see you again and to be back on the show. Thank you for having me back. I’m very well.Thank you.
Lee:
Excellent. Well, you are back. For the folks who aren’t aware, I have another podcast called Trailblazer FM. Martin was with us about six years ago talking about moving or running his agency out there in Peru. Fascinating episode. I highly recommend people go ahead and check out that. But a lot has changed for you. Could we get, first of all, before we go into what’s changed, can we just have a little potted history of the world of Martin, what you’re doing and how you ended up where you’re at, and then we’ll jump into the meat and potatoes.
Martin:
Yeah, sure thing. So moved to South America about 20 years ago now.
Lee:
When you were two?
Martin:
Yeah, that’s right, when I was two. Very young. I just started to learn to walk. Then as things grew, I’d worked in the agency world in London before, and I just started working as a freelancer for companies in the UK UK and also the people while I was travelling in different areas that I was in. It just snivelled from there. I think a lot of people have a similar thing, freelancing, and that turned into an agency for web development work, where we initially started outsourcing our services to UK agencies because we are Chief of Development in Latin America. Then that just scaled and we now full service agency, working with companies in US, UK, and also locally here in Peru and other countries in America. That’s what we do, mainly WordPress, web development, analytics, Analytics, those are our strong points. That’s where we’re at. But we have now diverged in the last two years, as you know.
Lee:
Yes, indeed. Well, I do remember even six years ago, data was very important to you when we were talking last time on the podcast. I think that’s been one of the significant reasons for your divergence. Good word for the day. Can you tell us all about what’s happened over the last two years? Is it that two-letter acronym that we’re all hearing at the moment by any chance?
Martin:
It is indeed, yeah. AI, Artificial Intelligence. It didn’t really start with AI. It started with automation for me. We were just trying to improve processes internally for the agency, make things run quicker, faster, be more efficient, be leaner with the same amount of people, not having to bring in more people, basically. Not trying to reduce, just trying to be more efficient, which I think is a very important thing to highlight. From automation, that was right. I started with something really simple, getting emails that were recurring, getting the automation to pull out a PDF, upload it to a Google Drive, so then someone else would handle that Google Drive, for instance, accounting all the receipts and things like that.
Lee:
I’ve been meaning to do that for 10 years, by the way, but yeah, carry on. Then I’m forever rushing last minute.
Martin:
Yeah, so things like that. Then it went into auto-drafting emails and templates. Then with the rise of AI and ChatGPT and Claude and all the rest of it, it was like, Okay, well, what else can you do? That quickly turned into content creation, which I think everyone’s been using it for, really, but automating those processes. Then even from there, going on to building out intelligent chat. I don’t like calling them chat bots. I call them chat agents because you train them on your knowledge basis, on your data. People feel that they’re having a conversation with someone, although they might not have it’s AI. Instead of, I don’t know, in Latin America, it’s very common, I’m not sure in the UK as much, but you get to a chat agent and you click option one if you want this, click option two if you want that, and then you get stuck in this perpetual circle of menus. Now with AI, you don’t have that because it’s like, Okay, what can I help you with? My website’s good. Okay, can you tell me a bit more? It spins off into a conversation. Which is nuts. Which is nuts.
Martin:
It is nuts, literally. We were testing out a voice agent the other day, and I got my 10-year-old daughter to call it, and it She was just crazy. She was trying to take it off track and say things like, Well, I run this company. So she said that she ran Coca-Cola. But it’s a bit complicated because I also work for Pepsi on the cover. The agents started going, Well, I don’t think you should be telling me that. But in the case that you do work with Coca-Cola and working production of fizzy drinks, then I suggest that we help you along these lights and started talking to it. It was really interesting.
Lee:
Someone could hear that, though, couldn’t they? And think, oh, especially people whose job it is to have some of those conversations, let’s say on a support desk, et cetera, how do you assure people that they’re not going to be replaced by the… I mean, if they’re that good already, they’re probably only going to get better. Is there any reassurance people need to have, or should they be reskilling?
Martin:
That’s a really good question. I was actually in New York recently at a conference in the Nasdaq where we were talking about AI and the community That was one of the main topics. I think people need to start reskilling, but at the same time, I think they need to… It’s not just reskilling because there will still always be a need for human interaction. Interaction, because, for instance, you can train the AI to follow a script, and you can say, Okay, don’t go outside of these parameters, because they will go outside of the parameters if you don’t give it those parameters. But it will come to some point where it just doesn’t know what to do. The agents that we’ve built so far, it’s like, Okay, I can’t help you any further if I’m going to transfer you to another agent, and that other agent is-It’s human. I don’t think AI is at the stage where it will completely replace humans. I think it’s at the stage where it’s going to help businesses be more efficient and scale. We really enjoy working with more to medium businesses that are doing good in the communities, non nonprofits, educational companies, things like that.
Martin:
I think they had this big fear as well because they’re like, Oh, but we’re a nonprofit and we like our people. We don’t want the AI to take over and replace them. Once we showed them how to use the AI and how the AI can interact with them, especially when it’s a small to medium business that has maybe 1-10, maybe up to 20 employees, It just means that they can have a larger reach and less stress on their teams once the implementation has been done for it. I think that is a bit of a myth that AI is going to replace you. It will replace a lot of people. For instance, call centres will have to adapt. I’m sure a lot of companies will, things like that, or support agents will be reduced But it just maybe means that those people will be able to focus on other areas of business.
Lee:
I think as well. Hearing what you were saying there, the virtual agent, the AI agent, can get you so far. Maybe in a support situation or whatever, that will help reduce the human amount of calls that to happen because certain things can be answered by AI in order to get something sorted out. Maybe an exhibitor is going to call up the event organisation to ask, Where is it I order my stand assets? The AI can absolutely, Yeah, no problem. You should go to this website because the AI can totally do that. But if the exhibitor might say, I’m not happy with the quality of the service or whatever, then the AI can now hand you off over to a human who has empathy, who has authorisation to do and say things, etc. That person who has that skill can now focus on doing that skill and hasn’t had to field hundreds of basic calls where people are just asking, Where is it I go and order my stand assets or whatever that might be?
Martin:
Yeah, Absolutely. I mean, if we look at it in the context of event management, I was listening to your podcast because you were at that EventTech.
Lee:
Yeah, that’s right. Event Tech Live. That was just a few weeks ago. Yeah.
Martin:
I was listening to your last couple of episodes, and it’s really interesting people on there and talking about the different ways that they work in the event space. The Because I was thinking, how can AI help both? You had the guy Tito, is the app? Yeah, the payment app. That could be done. I know he’s made a great app. I had a look at it. Very simple. We’re really quick to use. But that, again, the AI, someone could use a chat widget, could do a phone call, and they could say, Yeah, sure. You need a ticket? Okay, no problem. Here’s Take their payment details over the phone, if it were, or over the chat, or produce the link from the payment process or whatever it may be, Stripe or Tito, whatever, and just immediately get them the tickets, or someone could call up and say, I ordered my ticket, didn’t arrive. It can go off, it can find it. If we look at it in an overall way, automation, there’s so many platforms. I know you’ve got a great platform for people running their events. The problem is for a lot of people that we see is they don’t know how to synchronise all this data between their different platforms.
Martin:
You need a central, a lot of people call it a CDP, so a customer data platform, and that needs to be integrated with different APIs and things like that. If you do have a centralised place, you need to automate all these processes to talk to the centralised place. In the middle of that, you could also have an AI agent or several AI agents that deal with different aspects of that that can be support, marketing, I think I went a bit off path.
Lee:
It’s all right. I can see that you think of this at night imagining these.
Martin:
Yeah, I was just imagining this like how it would work. But that’s the cool thing now with technology is that you’re not stuck with any one tech stack, and you could test out different systems with the APIs and all the rest of it, connect them. But yeah, I’m just thinking, I don’t think it’s going to take people’s jobs away. I just think it’s going to make people’s jobs easier.
Lee:
And change the way I think customers interact with the businesses that they’re working with, et cetera. For me, it will normalise, perhaps with voice or just with text chat, me talking to a computer to end up getting a payment link in that example you gave, or me talking to an AI agent using voice because I’ve used ChatGPT voice, for example, and it is very much like talking to a person. I know there’s a slight delay. I know it’s AI. I’m comfortable with that. The more exposure I get to that, the more comfortable I’ll become. For me to then have that conversation and for the AI agent to then say, I’ve text you a link to pay for your ticket. That, to me as a customer, is an advantage. If I can get my ticket easier, like Tito do with their easy platform, if we had an AI agent doing the same thing, I can get my ticket easier. I don’t have to wait in a queue for a human to talk to. That’s good for me. That’s the benefit. The benefit to the event organisation there is that they are able to field the real important questions, the complaints or the upsells or anything that requires a human brain, a human mind and a relationship, et cetera.
Lee:
I think there’s an awful lot of win-wins. You’re right, I think it’s a myth. You’re right in the reskill element that some people will need to reskill. I think one of those skills is simply being good at using the tech that’s available, i. E. AI, getting used to how AI works because that can help people do their own jobs.
Martin:
Yeah, I mean, exactly. You probably heard this as well, being a nerd, similar to me. I don’t know if I deny all knowledge of being, how you say, nerd? You just ask AI. Sometimes I’m down, I’m like, I’ve got this idea. It’s not going to give you the perfect response it might do. Prompting is the key to everything. But you can say, Well, help me create better prompts. Help me do this. And Then at the end of it, you do still need a human to review what the AI has produced, be it content. I mean, we use AI to help us produce content. We also help. We get contracts. Sometimes I’ll have a meeting with someone, for instance, like we are having now, and that will be recorded and I’ll get the transcript. From that transcript, it will all regenerate an outline of a contract. That takes me a lot of time, but I still need to go through it, check it off, make sure-Sanity check, yeah, for sure. Yeah, it’s energy check. Again, Again, I don’t think it’s going to replace us. I think it’s just a new tool that we need to learn.
Lee:
I mean, that’s a great example of use cases. Why don’t we do that just for a little bit is throw in some use cases for businesses or even some more use cases. For me, what I would do in that same scenario from the transcript is I would ask AI, Hey, what did I promise to do? What are the action points or what are the actions from this particular meeting and who are the owners, et cetera? Because AI can pretty much do all of that as well. Write me an email recap for me to send to everyone, including what we each said we would do and timelines and all that stuff. That’s there for me. I might even say halfway through Martin answered a question and it was awesome. Create me a blog based on that. Again, from that simple meeting, we now have some really good content. Obviously, human needs to edit that content, but we’ve got some content from that as well, which I found phenomenal. I’ve used AI predominantly in those ways. Equally for the show notes for this episode, they will be AI generated. I’ll go through them afterwards, but I’ll say extract the wisdom from this episode.
Lee:
What are the key things that Martin shared that will have a real impact for our target audience? I can tell the AI, Hey, our target audience is event tech suppliers and event and exhibition organisers. I can even say what their main pain points are, et cetera. Then the AI, with that context, will then look through the transcription of this, sorry, the transcript of this episode and come up with some pretty epic notes, saving me hours because I would have to relisten to several times. Whereas now I feel like you and I can have this conversation once and relax, and I can then put this through AI later on, and it’ll just remind me of all the cool stuff we’ve said to each other. Then we can put that into some really good show notes. If I rewind 10 years ago, back at the beginning of the Trailblazer podcast, I was having to make notes whilst we spoke. I was having to listen to the episode straight away afterwards to remind myself so I could write the show notes. The show notes were never as quality because I would end up having to rush. I still had business to run.
Lee:
I still had everything else going on. I’d have to listen to the recorded episode at two times or three times speed just to remind myself what we talked about. I’d also be tired and it was just harder to do. Now, things like even that are a breeze. Another use case, and then I’ll let you take over with a few, is when somebody sends me a contract like an NDA, I’ll put that into AI and I’ll say, Hey, are there any gotchas in here? I don’t have time to read this, but is there anything here I should be not signing up to? That saved my butt a few times where AI- That’s interesting.
Martin:
I haven’t actually done that. That’s a good one.
Lee:
Top tip. You I’ll get it here first. I’m sure someone else invented that before I did, but I always do it. I’m just like, What should I get some advice on? Or is there any reason I shouldn’t sign this? Or is that clause typical or is that restrictive? It’s very, I would always say that nothing beats talking to an actual lawyer on stuff like that. This is just some help. It’s a real professional. I don’t need to say.
Martin:
If it does come back and say, Well, you should check subsection 2 or whatever it might be, then you go and talk to a lawyer and say, I don’t understand this.
Lee:
Can you help me with it?
Martin:
Yeah, exactly.
Lee:
What are the use cases have you seen for AI? It doesn’t have It wouldn’t be just ChatGPT either.
Martin:
Let’s look at it this way. You said your podcast is for event tech and event organisers and all the rest of it. You will go through the notes and you will know how to pitch it or change it so it resonates with them and their pain points. When you start with AI, I think that’s always you need to look at your pain points and maybe look at what manual recurring tasks you do a lot of and how AI could take those over. For one client, for instance, they get an insane amount of support email, I’m not allowed to say what product they sell, but let’s say they run an e-commerce store and they sell some tech products. What we did with them, or What we’re doing, we’re still refining it, is we went through six years of support emails and got all the context out of it, got all the personal information out, so no names, no email addresses, stuff. We then are training the AI to go through all of those, categorise it, and now we’re building an AI agent that will automatically respond to emails as they come in, but at the moment, they’re just being put into draft.
Martin:
So then everyone can like, Oh, okay. Was it responding? Yeah, that’s correct. Okay, and then we’ll send it off. So I think that was a really interesting use case that we’re building out. Another one that we’re pitching is for a directory. We have a client that has a very complicated directory and filtering system, and the people that use it are users that have disabilities, so either vision impaired or sometimes motor impaired. The idea is to build an agent that can respond via voice, obviously by typing, that will help them find the right consultant for their needs and their disability instead of having to click on all these different philtres or get someone else to do the searching for them. Then it’ll be like, I need a therapist in Dallas, Texas, that can do online therapy, or whatever it may be. Then I would just spit out the results.
Lee:
I think that’s a good example as well, isn’t it, of how the way we interact with tech is going to change? Because I was talking yesterday to a colleague. We would go out at lunch for a walk to get our steps in. Got to be done. 10k steps, apparently, is good for you. We were talking about what we let our kids use. Do we let them use the phone at what age? Do we teach them to use computers, et cetera? I piped up and said, Yeah, but in 15 years time, I wonder how we’re even interacting with technology anyway. Are people selecting philtres and buttons anymore anyway, or are we having as plain a conversation as you and I are having and not even holding anything? I don’t know. Is it all built into the glasses now? Do we even need phones? Will we have laptops in the future? I don’t know. That blows my mind. It makes me daydream.
Martin:
Yeah, I had a friend, or I have a friend who’s a product designer. Years ago, he used to work at Microsoft. He’s now gone on to a very popular Swedish furniture design store, which you’ve probably heard of. Starts with a little I. He, years ago, I’m talking about 15 years ago, he designed as a concept. It was just the flattest screen that you’d ever seen. I was like, That probably will happen, and we’re dying to see it now. These really flat screens, things like that. People with glasses and going like this in front of their eyes. It is starting to happen. So, yeah, It’s moving at such a rapid pace. I think that’s another reason that companies and individuals need to basically start interacting with it. Or you’re going to get left behind.
Lee:
I think what we’re saying here is we’re going to need to start because tech is changing rapidly. AI will help us become more productive, give a better service, et cetera, even used for the basics without necessarily removing people from the equation, i.e. People aren’t necessarily going to lose their jobs. They’re probably going to be able to focus on other things or things they are more skilled and suited to rather than fielding hundreds of calls. Maybe they’re only dealing with the 50 people per week that really need assistance, whereas the others, 100 or 200, could be filtered through AI, et cetera. There are definitely tonnes of examples. I think the other thing, especially… Well, that’s their key takeaways for me. The other thing or the other area as well is the handling of data. There is so much data. There are so many data points. The more tech we have, the more data points we have. I think AI will come into play there, I assume as well, helping us to understand what we actually have, what we’re looking at, what we can take away from it, etc.
Martin:
Absolutely. I haven’t dived into that area of it yet. It is something that I’m looking at. It’s on my to-do list. The thing is, it’s such a vast area. You can do everything. I know I came from the data side of things, and I’m a bit of an analytics nerd and things like that. But right now, I’m just like, what can this do with other stuff? Not just the generative AI, which is what everyone’s talking about. That’s really what made this explosion, because if you think about it, AI has actually been around for a lot longer. It’s already incorporated.
Lee:
I was talking to AI in the ’80s. I think it was Eliza on the BBC micro.
Martin:
There you go.
Lee:
I will find the name. I’m going to put a link to that, folks, so you can see what that was. Really cool Essentially regurgitated what you said back to it, but it felt like you were having a conversation.
Martin:
Yeah, well, there you go. The Siri, Alexa, Google Assistant, that’s all AI as well. It’s been around. We just took it for granted. This is explosion of generative AI. But data is a very sensitive area as well. I think that is one big concern from companies, uploading their data to these different platforms, to OpenAI, to CRO, whatever. We have had concerns with that from different companies, and we are looking at… There are solutions where you can self-host a lot of the things so that your data is private. There is a bit of concern around that, I think, coming up.
Lee:
I’m glad you raised that. Because event organisers, especially if you’re handling identifiable information, especially here in Europe, etc, then we’ve got to be very careful. Where are we uploading that information to? You mentioned self-hosting. I believe we can use, is it LLaMA, for example, from Facebook. That was it. Got there in the end. Llama from Facebook is something that can be self-hosted. They have things with several billion parameters, which means I believe you’d need a really big, juicy server, but they smaller versions that can still manipulate data on a private server in a private environment should people need to. I’m certainly aware of that. But for anyone listening, do not, for the love of all things, upload a spreadsheet of people’s data to any online AI. Need it be said, but just don’t. My worry would be that that information will at some point accidentally be leaked by the AI in an answer to somebody else. Maybe when somebody’s asking about someone who’s Lee Jackson, which I’ve done, I’ve asked AI who Lee Matthew Jackson is. My worry would be is if a company had lots of my personal information and my address and everything, and they’d uploaded it to AI, and somehow Or accidentally, that then became part of the response in the future by whichever AI was being used.
Lee:
I know I’m catastrophizing now, but I don’t know. Maybe.
Martin:
I mean, I don’t… Yeah, to be honest, and this is why everyone needs to check the terms and conditions of everything, but have you checked the terms and conditions of ChatGPT?
Lee:
No, but what I could do is the terms and conditions through ChatGPT to say, Are there any gotchas?
Martin:
Yeah. That’d be interesting to know. No, of course not.
Lee:
All right, use Claude then. Actually on that then, before we wrap up, because you did mention there are a few, Most people all have heard of Claude ChatGPT and Grok, which I’ve never touched in my life.
Martin:
Which one? Sorry, we’ll read the last one.
Lee:
Grok, the one on Twitter? That sounds like you’ve not heard of it.
Martin:
I haven’t looked it.
Lee:
Great. All right. Well, let’s ignore that then. Unless you know of any others like LLawn or et cetera, is there a strength for the different platforms that are out there? Should I lean on ChatGPT for certain things and Claude for others, or is everything just the same?
Martin:
I’ve been playing around with Claude, which is from Anthropic, ChatGPT from OpenAI, and Gemini, which is a Google one. I tend to find that Claude seems to be better for the results I want, especially when it comes to text generation and coding. Sometimes we’ll throw problems that we have with our code, and I’ve thrown it to ChatGPT as well. And Gemini, it is good. I think we just decided to… We used it, we were like, Yeah, it’s okay, but it’s another expense on the bill. So we’re just like, No, take that off. We just generally use ChatGPT and Claude within the company. I’ll throw in a pro tip here for people. If you do want to use these platforms, you can obviously sign up for the pro accounts that cost you, I think, 20 bucks on both per month per user. But if you use something called typing mind, typing mind.com, you can buy a licence on there. We have, I think, 10 licences, and you can plug in your different API keys for Claude or for ChatGPT or for Gemini. Using the API, it’s way cheaper. We end up spending probably around $15 across five users per month.
Lee:
Can I throw in another top tip? Yeah, sure. If you want to get money off those keys, go to OpenRouter. You can use an OpenRouter key, which supports multiple LLMs. They seem to be cheaper to access Gemini, you can access Claude, you can access ChatGPT, OpenAI, et cetera. But you can also access absolutely heaps as well of other ones, including the The Latest LLaMA with something like so many billion parameters that are in there. It also gives you access to MathGPT, I think it is. Oh, wow. Aida. No, AIDA is a programme that uses it. Hang on, let’s have a look. Models. What are the models around here? There was one… Yeah, you got Cohere. Obviously, the one’s from Amazon. Mistral. Mistral is pretty good, actually, for texture and for coding, actually. Like you, I found Claude the best for code. I use Linux a lot, so I found that Claude is also good for helping an average Linux user work out how the heck to fix because I break things nearly every other day. But yeah, if you look at that, it’s one key which gives you access to absolutely heaps of these models, which is really impressive.
Lee:
I think you might be able to put that into typing mind. I’m guessing. I don’t know this for a fact, But if you pop that into typing mind and then use that. I also self-host, but I don’t know if they do a service, something called Lobe. I think it’s LobeChat. That, I think, works quite similar to typing mind. I’ll send you a link to that. I’ll put a link as well in the show notes so people can check that out. I just span up a Docker on a server and then popped in my open route to key. Lo and behold, I’ve got lots of mini chat windows I can have on specific topics and I can use different LLMs. It’s pretty cool just to sit and play and chat with. The thing is, though, you see, I’m playing at it. You’re doing it in real business day to day. On that, for any company who is exploring like I’ve been exploring and would like to lean on someone like yourself who’s been doing this for an awful lot longer and has an awful lot of extra tools, what’s the best way for people to connect with you, mate?
Martin:
I’d say the best way and the fastest way is via LinkedIn. You can just Google me, Martin Suttill, S-U-T-T-I-L-L.
Lee:
Are you the only one?
Martin:
I am the only one.
Lee:
Let’s have a look. Yeah, there you are. Oh, and you even come up as a video Look at that. How to use AI to automate ads. We didn’t even mention that, did we?
Martin:
Oh, that was a webinar I did. Yeah, I’m part of a measurement analytics group. We do monthly talks. That was a long time ago. I’m surprised that came up.
Lee:
It’s nice when you got a name that not many other people share because all your results come up. It’s probably also a curse as well. So Google Martin, Martin, so still connect with him on LinkedIn. We will put all of those links as well in the show notes, including the very old episode that me and Martin did together. That was fascinating as well as journey over to Peru and as well, all of the services that we’ve mentioned in here. I’m sure Martin would love it if you connect with him to tell him what services you’re using. But also I would recommend you do connect with Martin and tell him what problems your agency or event agency is having and see if Martin might have some solutions that can help you. I would highly recommend you’re working with him. I’ve known Martin for, going on eight years now. Eight years, that’s a long time, and he’s a good guy. So mate, thank you so much for hanging out with me and just nerding out over AI for like 40 minutes. We need to do it again. I love it.
Martin:
Yeah, no, it’s really good. I enjoyed it. So yeah, happy for anyone to reach out to me and talk and any problems they’re having, and then we can see what solutions we can offer. Absolutely. That’s 50 cool solutions.
Lee:
There you go. There might be 54. There’s 57 varieties of Heinz, isn’t there? Is that where 54 came from?
Martin:
No, 54 came from… I was looking for a name for the company, and at that time we were based in Argentina, and it was like, Well, we’ll do web solutions. Eileen Cove for Argentina is 54.
Lee:
Makes sense. 54. Brilliant. Yeah. It makes perfect sense. I’ve also got a use case that I’ve just remembered for AI, now that we’re in the everything’s going to fall apart near the end of the episode mode. There was some hammering or something whilst you were talking earlier, but don’t worry, AI is going to get rid of that later. We’re going to put our entire voice tracks through AI and it’s going to remove all the background noise and make you sound like you were in a studio the entire time. That’s usually with Adobe Enhance, they’ve got a really good AI model for audio improvement, and I can feed it through and it will just make you sound.
Martin:
That’ll be great because I actually had the noise reduction turned on. My neighbour is apparently doing some remodelling.
Lee:
I mean, let’s hope AI can fix that. I’m sure it will. Let us know if you heard the hammering. Because if you did, that means AI did a terrible job. Well, I hope they get their house sorted out soon and that they’re not doing all of that beyond 11:00 at night. We’ll have you on again soon, mate. Oh, and also, I believe you’re going to come back soon and talk on the Trailblazer podcast. So when you do that, I will make sure that I come back to this episode’s show notes and add that link in as well. So you can go and listen to that episode over on the Trailblazer FM podcast, folks. So if you are listening in several weeks time, go ahead and check the show notes out just in case there’s another new episode from the one and only Mr. Suttill himself. So with that said, let’s say goodbye, mate. Cheerio.
Martin:
Goodbye. Thank you, Lee. Take care.
Lee:
Bye-bye..
