AI is the enemy of bureaucracy, and most companies aren't ready

**[00:00:00]** Hello everyone, welcome to the web talk show. My name is Armando Perez Carreno and with us today is Ross Barnes. He's a founder of the Galahad Group. Welcome Ross. How are you? >> I'm good Armando. Thank you so much for having me and it's an absolute delight to be here. >> Oh, it's my pleasure. Especially before getting on air, we were talking about a little bit of your whereabouts and how much I love that area. So, I'm very excited that we're on the show today. also long distance which [laughter] always continues to amaze me and it's always good fun. Ross, can you tell us for our listeners a little bit about the Galahad group and also how you got into >> Sure. So the Galahad group um I founded um 3 years ago um and we offer AI consultancy, AI aided platform build and um AI enablement for organizations. to ensuring that organizations are making the most of what artificial intelligence can bring to them. How I got into this is um before um the Galahad Group, I was a global CTO of a WPP advertising and media agency um which under my tenure on the board grew from 15 people to 1,500 um and we were billing over 1 billion um in in media billing. So a big company but also realize that service businesses are incredibly um threatened by AI. So the adoption of AI for them is really really important >> and wanted to set something up that helped organizations not feel scared of that threat but really embrace it [clears throat] um and be first mover. >> Wow. That is I mean if you look at it from an altruistic point of view, right? It's like you're going to help business owners. Of course, it's a business, big business. But I I like that concept **[00:02:00]** because a lot of it is focused the energy is focused on enterprise and these huge corporations and and then the rest of the backbone of the economy which are like service business etc. Um it's it's uh yeah people are confused. They're scared. They don't know what to do. How does it work? Is it good? Is it bad? Is it evil? [laughter] But at the end of the day, I mean it's a tool, right? As as you as you well know, >> 100%. It's I mean every technology that's, you know, driven a revolution of sorts has always been, you know, is the tool is the tool bad? You know, is the tool evil? And it's like, well, it depends who's holding it. As with all of these things, >> um, adoption and enthusiasm and curiosity are going to be the tools that that win the day in this era, I think. >> Yeah, I I agree. I think that, uh, a lot of bad press is put on it. But the same way that bad press hit the internet and the smartphone and the computers and the industrial revolution like everything when it's when it's as big as something like this and and gamechanging people start attacking it from all angles. And at the end of the day, I mean, I was just looking at a comment yesterday in one of our shorts because one of the guests mentioned something about AI and immediately that comment was one of those like, "Oh, you're talking about AI. I won't listen to you anymore." or something like and it's because they they see it from whatever they perceive from the media about it and have no experience with it and and just think about it as this thing that will take jobs or is taking jobs and I always like to see the other side and say yes well it's like the internet yes it did take jobs at the time but can you imagine the number of jobs that it created after the fact So all that we use today couldn't be **[00:04:00]** possible without it. So it's if you look at it in a long enough time horizon, it's a good thing. >> And and and look and a reality that will I believe rem remain a re reality is people by people. People want to talk to people. Yes. People want to have you know interactions. And I think to your point but perception is reality. there was is without a doubt a you know a media ground swell that is you know is making AI seem a terrifying thing and I think if you think about it long enough you can certainly put yourself in a place where it's quite scary but we're not there yet and doesn't that mean you know I think getting on board and finding out what you can do with it rather than shying away and letting a competitor or a steal, you know, steal yards from you. >> Oh, for sure. That's an excellent point. Many businesses, especially business owners who still run their the day-to-day and they if they don't embrace it and just stay out of it out of ignorance, out of fear, out of whatever, they don't they don't they just don't want to try it. Their competitors, like you just said, they're using it right now. And it's >> just even if you don't use it for because this is one of the things that people complain about creating AI slop and content like take all that aside. just using it for helping you do a repetitive task that your staff hates doing anyway and takes a long time and is prone to errors and have it just do it automatically quickly and give your staff something else to do that's that's more engaging and actually uses our human senses. Well, that's it, right? I mean, that is it. Remove frustration, **[00:06:00]** remove friction because AI just it doesn't care what its task is. it will just perform its task >> and therefore you can give your employees, your colleagues, your clients just a much more enjoyable experience by just genuinely being more human rather you know, on a on a conveyor belt. >> Yes. I when I when I think about support and and a lot of these companies don't have support like just companies in general you don't like you see a contact page a support page >> you shy away from even sending something cuz before AI like nobody's going to answer you now with AI a lot of them can if if they want to they can have an agent that can help you with things that are common that might solve the issue quicker. And some might do it well and some might not do it well. And that's okay. Like there's people who are not going to do a good job at it, but they're trying at least. And if you like to think about it from from also the business's point of view, not not only the consumer, you have to think about like if you want to support hundreds or thousands of customers, you're going to need a lot of staff. And it's not that you want don't want to hire staff. It's just that it's not feasible for a certain size of business to have a hundred reps on the phones all day >> answering questions that have already been answered because they're generic questions or they're account questions or they're things like that. Like you can have a voice agent, a regular agent, whatever to help just take some of that off and still have your team there. >> I for one think it's it's a good deal. >> I I completely agree. And let me give you a flip side view on that is that what AI is is the enemy of bureaucracy. >> And this is something that's happening in the UK at the moment. And there's **[00:08:00]** quite a lot of research, I think I posted about it on LinkedIn this morning, is that complaints to government bodies >> since 2022, the advent of ChatGPT have increased because people are now able to go through the bureaucratic steps that an organization may have put in place to make things difficult. >> Easily because the AI will just do it. And if you're not if you're not responding to that as an organization then pretty soon a snowball is coming towards you where you know and literally I imagine with the UK government the paper is stacking up on your desk as more and more consumers cuz AI has got such a low barrier to entry more and more consumers are saying do you know what I'll just I'll just get ChatGPT to do that for me thanks When you see people doing this in the UK are they using these tools to allow them to go through, let's say, forms that would have otherwise taken them a long time to fill out versus taking a long time [laughter] to fill them out. >> Exact. I I was speaking to someone um recently about they had a HR complaint about a colleague and they they brought the complaint to the HR department and the HR department reverted with okay well you're going to have to find um significant evidence for this and here's the form you have to fill out here is the evidence you need to find here is the the amount of evidence it needs to be and this person had co-pilot on their email [snorts] and just gave co-pilot that form the body of evidence and there are all the emails and HR who normally well I'm not saying this is definitely true but would have hoped for that to be a deterrent for a **[00:10:00]** really large process have suddenly >> got the evidence and they've got to do something with it and you know that is indicative of any customer service business that is trying to put hurdles in the way of customers contacting them It's not a thing anymore. >> That's incredible. When when I hear that, I immediately think of like obviously there's people saying, "Oh, you can't give it access to your email because then it can blah blah blah blah blah, right?" But at the same time, like depending on the tool that you're using, you still have to be careful. But some of these tools will not necessarily have to read your email every day automatically. It's just that they have access to and you can tell it to do something and in that moment it will go and do the thing like you would have done. It's just faster. Exactly. Exactly. It's not as if it's actively scanning for something. It you say we've got this particular task. Here's the things I need you to look for. Can you read and look at the relevant emails as well? It's not going to read everything. It's very it's very and we must be careful about not making them people, but it's very clever. Yeah. It doesn't want to consume all of the information. It only wants to consume what's >> Let's dive a little bit deeper into that because you're an expert on this topic and and people when they hear email for some reason we imagine, oh, I gave it access now it read all my email. Come on. It's it's not capable of reading all the email. First of all, because it can't fit in its context window, but also it would need a huge database depending on your email inbox size, gigabytes and gigabytes. And it's just not not practical for it to actually go and read everything, but instead it it it will do searches and do things similar to what Judith would have done. Is that correct? It >> it's absolutely correct. It's similar to, you know, doing a a Google search, but it's more intelligent. I mean, we've **[00:12:00]** got to think of these AIs or agents as they are they are programs that are designed to complete the tasks they are set. They are waiting to be told what to do. And sure, you could say scan my email every second. Sure, you what's what's that going to do for you? But you can give it tasks or triggers. If an email from this person comes in and if if an email from Armando comes in, I need I need to see that immediately. Give me that. So, it's not reading. And it also wants to complete the task as efficiently as poss as possible. And that is not reading every single email. Just like us, you know, as you know, as humans, we see an email coming in and go, "That's junk. I'm not going to read that." It's similar. >> And even as software developers, I created a tool for myself because the like tools for managing people and projects and there's there's tons of CRM out there and things like that, right? So I have a very specific process that is different from a corporation or from many types of businesses. And so I I created my own little tool called Janus that just use internally and it has a part of it that reads email. But even as I built that I told it just like the only things I need you to process are the inbox because I clear my inbox. My inbox is always empty and I read every single email and this better man than I am on [laughter] >> I know very few people who do that but I like to keep it that way and this tool allows me to do that and when I clear something off it'll it'll put it in the right buckets for like tasks waiting on someone or myself or things like that and that way I don't have to use email like as a task uh management tool and but still I have it only read the inbox not everything because everything else is out of context. I just need you to process this, do what it needs to do, **[00:14:00]** and that's it. If I ever need more information, it can go and and fetch things, but but in reality, you set it to something that's going to be practical because things cost at the end of the day. Tokens costs, memory costs, the bandwidth costs, right? So, >> I mean, but I mean, if you apply that to how you might work with a colleague, that's exactly how you would work with >> a person. You would say this is what you've got access to. This is what I need you to look at. This is your defined task. If you're doing that, then you are performing a good job rather than oh my god, you can you just know everything about everything. Uh because that isn't that isn't helpful for either you as a user or an AI or a colleague as a as a task. >> My friend Mike Carlo, he runs PowerBI tips. there's a lot of uh >> oh nice >> PowerBI uh related fabric that sort of things and uh we we chat a lot and one of the things that that he talks about and we we talk about together is when you're trying to implement AI in a company you have to think about just like you just said as a new recruit somebody comes in you're not going to give them the keys to the kingdom you're going to give them an email address and you're going to give them a specific role and that role can only access these parts of the system and u you have control of that and you can see the log of what it can do and can't do. And if you do it that way then it's very secure because even if it wanted to do something it's limited to what its role and capabilities allow it to. I mean there's so much in that to unpack because you're completely right. So when I do um one of the most frustrating things I hear when I talk to companies about AI enablement is it's like well we've given them all claw enterprise so why isn't it why isn't it working and it's like well that's that's not what it is. You can't just give everyone a **[00:16:00]** hammer and expect them just to be finding nails everywhere. So when I train people, we spend, you know, the first day of a 3-day course, we won't even be touching ChatGPT or Claude or Copilot. We will be talking about understanding workflows, understanding because you can't truly implement AI without really, you know, getting very close to organizational design because I think one of the big mistakes businesses make is they try and overlay AI onto a human problem whereas actually an AI might want to do it a very very different way and not follow the same process that you know a naturally inefficient person might might follow. >> What's very interesting is that recently changed quite a bit. Before you would need to be very specific on how you wanted to proceed and do tasks and now it matches just what you just said where you'll give it an outcome. And if you define the outcome and the inputs and outputs properly, it will find very interesting ways to solve a problem that if you just told it step by step, it it might have been less efficient, had more errors, etc. But and I think you're absolutely right and I think there's something super crucial in there that people are I feel missing is that it will not necessarily explain that process to you. >> Oh yeah. Therefore your process the work of that workflow in your organization becomes opaque. >> So therefore understanding what the workflow is and then understanding what the AI does with that is super important. Otherwise, you know, I've been into so many um training where **[00:18:00]** someone I'll say, "Right, work through your workflow like this and figure out what goes and where and what flows into what and then someone will come back to the, you know, the show and tell and say, "Oh, I just asked Claude to do it." I said, "Okay, okay, brilliant. You just asked Claude to do it." Okay, what happens if this goes wrong? And they have no idea. You know, they they aren't able to track back any errors. they aren't able to, you know, look at guard rails or risks because yeah, Claude will do it for you 100%. And yeah, and it'll it will usually get to the right result, but usually isn't good enough. >> I think that the overlying issue with just telling it to do things and stepping back is that if whoever is doing it has never done any sort of engineering or design they can accept it as is. But there will be so much context lost in edge cases like you're saying where you don't really know what it's doing and if you ask it to explain it, it will explain it in a very strange and convoluted way where you're like what are you saying? even as an expert in >> Yeah. Yeah. >> Imagine having an employee that did that and you gave them a job and they went, "Don't worry, I've got it." And just was turning up with the right answers all the time, but then one day got something catastrophically wrong. And you said, "Why did you do that?" And you know, they answered in a way that just you couldn't decipher. It's the same thing. Mhm. I like particularly telling it in the rules and and we we might want to go into how all this works, but uh **[00:20:00]** sometimes in the in the system settings or or in in a file that explains how how things should run, etc. I like to give it some guidelines into how it should respond to human requests such that when it's explaining something to me or to a client which might be different and I'll and I'll tell it and it will explain it to me in a way that I understand and it will explain it to a client in a way that they will understand but it will no longer explain it in the way that it typically explains because it it's super unclear if you just take the out of the box way >> completely. Um well, my AI that helps me run my business. Um it has um like a it understands all of my colleagues, all of my clients, and it has an adaptive style that is built in. So, it analyzes the way that they communicate with me, the way that I communicate with them, then builds whenever we're sending something. It it knows that client X really likes to the point detail. you really whereas you know client client Y might like to be asked how their weekend was and and that kind of thing and you start to build these communication profiles and then you start to think are all of these systems that we're going to be using now as consumers as you know as um professionals going to be adaptive in that way? Are we start are we going to be able to start, you know, rather than going into uh settings and picking things, are we going to be able to start systems adapting just based on how we communicate with them and and who we're communicating with? And I think that's quite quite a profound thought. It is I don't know why this happened but when they started adding this these extra rules to Claude for example for watermarking for for EU **[00:22:00]** I started finding that though it was quite easy to spot when Claude was talking before once you you read enough we're we're very good at at pattern recognition. So, so we sort of figure out as humans, you you catch on pretty quick. But when they start making those watermark changes, I don't know about you, but I now it's just like, oh, please no. Cuz it's it's being put into a box of the potential that it can do to write so that it can agree with those rules that have been put in place. What are your thoughts on that thing? >> And couple of things on that. I think I think it is your responsibility if you're using an AI to produce content to give it as rich a context on how you as an individual communicate. >> And and you can do that and you know your emails, your posts can appear as you as close to you. But then and I spent a lot of time doing that and then you know people would ask me are your emails AI? And it was like, well, of course they are, >> cuz that's just an easier way for me to to do that and get information to you more quickly. >> The actual question. >> Yeah. It's like, are your emails spellch checked? Well, of course they are, >> Yeah. The question you want to be asking, was the information contained in that email factually accurate? If it wasn't, then we have a problem. Whether I've written it, whether an AI has written it, whether my dog has somehow got hold of my computer, you if it is accurate though, it does not matter who has written that email. You security aside, it all that content, it it comes from the person and the desire to deliver that information. It is purely a >> I agree. And also you very likely **[00:24:00]** read it and prove it or have done it enough times that you now trust the system to be accurate enough to send it. So, it's not like you just blindly some people do and I that I'm not of course uh I don't agree to because you get these emails you're like you didn't read any of this like why did you just send me the the whatever the the thing spit out but in the context that you're talking about yeah I think it's perfect because it'll give people the right answer exactly what they need to the point in the way they want to hear it and if it does that I agree with you it just like it checks all the boxes and it clears up both people's time to continue doing what they need you do >> and and you know and I don't mind now if I receive what is obviously an AI written email in response because then I go okay cool you're probably not reading what I'm saying that therefore now I no longer need to read what I'm you know we can just we can just let them talk to each other >> because that's where you are and then you know we'll figure that out and then you my systems will judge an email's content you know based on risk based on importance sensitivity and then we'll will surface the ones I do need to check. But if something is, you know, and on the 706 train and I'll be home at quarter to 8 to my wife, doesn't need to be checked because, you know, that is, you know, factually accur um when these tools keep getting better, I'm still blown away. Like we used to create parsers and things for to be able to read digital information or physical information and it was a mess because you had to have all these different scenarios of how things are coming through and can we parse them? Are there errors and can they inject things etc. But but these these newer models and agents and harnesses around them are so good at determining that sort of thing like even the language like how is a person speaking? Is it obvious that it was just given by an AI? Did they just use it for spellchecking? Did they write **[00:26:00]** it themselves or likely? Did they um anything like and the context like you're saying? Did is this important? Is this clearly a sales pitch? Is this something that I I irrelevant to me because they misspelled my name or did they use the wrong person's name because they're just using a scraped list? Like they figure it out right away. They could just read your email. It's like, oh, okay. So, you can get rid of the noise if you're getting 150 emails a day and you just get the ones that are important, but they're really good. And I think you you can tell me from your expertise, but sometimes people are afraid of, oh, I don't want it uh triaging my email because it'll miss important things. They are very good if you set them up properly at like literally figuring these out better than yourself sometimes. And when it has doubt, it can tell you, hey, I'm not sure about this. What do you think? >> And and you and and and what's amazing about the doubt part is the doubt part becomes self-learning. >> As you know, as long as you keep telling it, you know, no, you could have deleted this one or actually this one should have come come to me. It will go right cool. I've got that. So therefore, the next time this happens, I will perform the action that I should have performed. >> Mhm. And you know that just makes you know that just makes a system that is self-learning. I think your interesting thing about passing and also your interesting thing here about your own bespoke tool is something to be really aware of is that you know now well not now but more I think it's more well known that these tools are now getting very good at talking to machines >> and what is interesting about that is they are able to break down what were previously locked down systems. Let's not say anything nefarious. Let's say on consumer hardware. **[00:28:00]** >> That you know the guy that you know had reverse engineered his Amazon Fire TV >> to allow you know the the firmware to be you know what he wanted it to be you know or being able to produce um powerpoints by a direct access to PowerPoint. And then you start to think if these machines are talking to machines all the time, what is the role of software? Is the role of software something for you and I to use or is the role of software to talk to the AI that I use on a day-to-day basis? And that just changes the whole equation of for your point, I want to build a tool that does the things I need it to do rather than buying a tool and kind of trying to make it work around around hopefully. >> You'd love Mike. Uh we talking like just about that a few days ago. Um we he was bringing up the point of like should we then as engineers start building CLI tools more than more than UIs for for many things and I was like yeah I found myself a couple of weeks ago creating a I needed to send some some credentials to someone and typically you either use a paste bin or something like that or you have a a password manager that has that software and so I created did one specifically so that my agents could use and it's all CLI based. There was no UI, no nothing. It was just a way for for my customers to send me their credentials securely and I can only unlock them on my machine with a specific key. And it's all terminal based, but the agents can use it very nicely. They don't see the passwords or anything. They just just move them around. And so then I thought, oh, now that I have that and I didn't lose time on UI, I'll make one that can send them things. And that's when okay I can do like a little UI so that they can receive it via email and click and and and get it whatever you want. It's all **[00:30:00]** client based. But that thought that you just said about should we be making software for machines to use is it's amazing because it can have so many features and there's no time lost in is the layout good, does this look good or black or white? Is the contrast okay? Does it fit in a small screen? Like just forget about it. It's just going to read the code anyway. So you're right. I mean, this is just absolutely my biggest passion point at the moment because I think what is hard for I think the I won't say the general populace, but a lot of people to understand is that it's this process that the machine does not care. Right. So your point of that is that's by the way I'm going to build that. That's a lovely a lovely and and also that's the thing like you can just have a chat and go yeah I like that I'm just going to build one of those >> which which is crazy. Um but you know normally someone would want to go okay that's a really cool idea. Can you show me how it works? And it's like well there isn't there isn't anything to show you. It's it's just happening. Um and and that's quite that is quite hard when you're trying to demo you workflow solutions because there is no UI. There is no lovely little app. And I think it's getting into that systembased thinking that I think is holding a lot of businesses back >> because they're thinking, well, okay, so we need to produce something. We need to make something and and well, you just need to solve something and you and that's it. There is a technical part to this for for those listening who care that if you have your browse a website or use an application it has to take screenshots and those **[00:32:00]** parsing those screenshots take a lot of tokens. So every time it does something it has to go and some equivalent of this and uh read the screen understand it use tokens for that do something read the screen again etc. But when it's using a command line tool and sorry I didn't explain CLI is a command line tool then it can just do the actions get the output do the actions get the output it could do it in milliseconds first of all and it doesn't waste tokens on trying to understand what it's seeing because it doesn't need to at all. >> So so I mean I've this has happened to me today. I've had a um I've got a mesh mesh network here that is we're and we're quite out in the country um and it's quite unreliable and you know you just have a thought and go I wonder if I could give the credentials to Claude it could go in and just build an MCP >> and but MCP for your listeners a model context protocol is the way that a AI will talk to a system um in a very similar way that Arando explain And like you said, it's just gone on, done exactly what it needs to do, found the problem, read the logs, and everyone's got lovely Wi-Fi now. And it's like it's it's it's like it's almost a world where if something is >> just point Claude at it or point ChatGPT at it and you know, see what can be >> To your point earlier where where you said, "Oh, I like that idea." and and bringing that to your earlier point of do we really need software right because now it it's it's really about the ideas and I find it brilliant that you could say hey that's great and I could say oh one second and I could just tell my agent give me a quick prompt that I can give Ross so he can build it and it'll give me a little MD **[00:34:00]** file which is just text to send you and I don't have to send you source code. I don't have to send you anything. Just with that, then your agent is able to build it the way you like building things and it'll finish in like 10 minutes. [laughter] You have the full thing and like how it's it's it's very meta. I I was in um Belgium last week with a client and um one of their um head of AIS um we ended up watching some football in a bar and I think it's really interesting and it's like you and I right when you get people who are very passionate about this kind of thing we share our ideas freely and not only freely but for free. you [snorts] know, the opensource market is, you know, it's it's exploded more than it, you know, it ever will. But what you think about is what does that mean for commercial software development? If you and I just going, "Hey, that's do you know what? That's cool. I could add that to this thing I've I've built. You could add that to this thing you've built and we've solved a problem that maybe a business might have need needed to be spending thousands of, you know, dollars on a license." Exactly. And you find very interesting use cases after the fact. So like with Mike, we do this a lot. We're sharing. We're like, "Oh, did you see this tool that I made? Oh, that's great. Can I use it?" And then now now we have a GitHub org that we share and we'll we'll put projects up there, but then I'll add stuff to it or he'll add stuff to it. And so we collaborate with software that we're both using separately with different configs and things, but but that we sometimes I'll get something that I'm like, "Ooh, that's nice. Now I have this new feature because he thought of it for his channel." And then I have something that he's like, "Oh, that's nice." And now it's just there. But it gets to a point where suddenly you have this great tool **[00:36:00]** that maybe some people want to use and you can sell the tool because you've already solved a bunch of things by using it yourself. >> Yeah. But then you've got to, you know, you've got to commercialize that tool. Whereas you could just say, "Hey guys, >> look at this great thing." And that's and that's what people are doing. I think a key part of when I do, you know, the Galahad method of training is I when we don't when we're not touching the tools in the first couple of days is I try and get people to think that kind of everything has a shape. >> Everything you're trying to do is a shape or series of shapes. And I've got six shapes that I tell them about what you uh prioritize something, find something, write something. And then when you start to think about the things that you know you've built and you might say well I've got this thing that you know looks at my emails it prioritizes them. It then drafts responses and then it sends emails. I go okay so that's prioritize draft action. I need something that looks a bit like that. I can take your tool but adapt it for my specific use case >> because those shape those things we're trying to do you know it's just input and output the process they all look the I like that. If you look at things like shapes, then it's better for people who are not used to finding patterns to now be able to say, "Oh, there's only six. There's only so much I can put things in." And so, it's very easy to just like, "Oh, this is my process. This is what my staff does. This one fits here." And it's almost like a building block thing. I really like that concept. >> 100%. And what we'll do is we'll we'll we'll work through what appears to be a very complex workflow with um you know a very senior executive and we'll go oh actually that's a 2 3 4 1 5 2 1 there you go. And then they're able to then you know go into whatever tools they've got access to and start to build that in **[00:38:00]** a in a very simple way. You're not you know you're not talking about connectors and MCPs and plugins and APIs. You're talking about things happening in a It sounds like music when you're when you're playing, especially if you do improvisation in jazz or or other types of music where you have these chords and you have progressions and you have scales and it's all just like you said, like it can sound really complex, but then if you look behind the scenes, you see the musicians, they're just doing like 1 6 4 5 1 8 like they're just going through those patterns. And >> and it works that way. And I think as humans it sort of resonates. >> That's quite nice. Amanda, I might see if I can uh make people's use cases into little tiny pieces of music for them. That would be quite cool. >> Oh yeah. Yeah. And and uh it's the other day I was watching I enjoy all sorts of music, but particularly I think uh gospel music like uh church music. it they they the one that has really powerful like bass and chords and and and drums and they they they're very talented musicians and if you look at them suddenly I'll watch a video and then YouTube suggests a bunch of them and so I'll I'll get these people I've never heard of but they're behind the scenes they like do these little videos or shorts and you see them doing that >> live like when they're playing the it's they don't know what the pastor is going to do sometimes and So they're just following and then there's a leader and he's just like shouting things to the to the rest of the guys like 2 5 3 2 1 and then they like they and then and then they know exactly what to do because they've got those structures that now they can perform. [laughter] I mean, and what's amazing about I think music when you view it like that and if you view it in this way is there is only a finite number of places that that can **[00:40:00]** go without being unpleasant, >> you know, unpleasant to listen to and also unpleasant to play or and I think if you think about that rhythmically with AI, it's a similar thing. You know, you the reason you're doing some your process A is probably to feed process B. So, how many process B's have you got in your business that could benefit from implementing process A? What do you find as a difference between a senior executive at a larger corporation, medium large corporation, versus a founder of a business that still might might be very productive and and do very well, but maybe they have 10 to 20 employees. when you're when you're coaching them, when you're when you're training them. >> Really interesting. Um I think there is a huge attachment to legacy. >> Um there is a huge attachment to this is the way that we've always done things. >> Um and there is a real need, I think, for senior executives to tick the AI box. And often that looks like signing a contract with Anthropic or with Microsoft. There isn't really when I see a founder a founder will want to we talked about outcomes earlier achieve the outcome in the most efficient and effective way >> and that [clears throat] may be AI that may be automation that may be work you know that may be human but they're willing to do all they're willing to explore all three of those things or a combination of those three and the other thing is I find super interesting and which is why I've really really enjoyed this chat is you you never know **[00:42:00]** when you're going into a training session or a um a meeting what someone says what someone actually means when they say I know a lot about AI >> you're never sure what that means I was in a meeting this week and um guy was like yeah yeah yeah I know all about AI don't worry don't worry we you know, do you know what? I set up something that every morning my AI tells me what meetings I've got that day. I was I was like, I don't you know, in 2026, I don't you Yes, that's good. You're adopting something, but you know, there is there is so much more >> that is that is possible than like the things we've talked about today. And I think once as an organization or a business owner, you start to not think of isolated use cases like that and you start to think of all these things compounding and helping you run your business end to end, >> that's when you're really leveraging, you know, what you can do. >> Does that make sense? >> Yes. And that's a great point. I've had times when I've been called to do some sort of workshop and you hear, "Oh, by the way, this group just took another training, so take that into account." Like they already did the and you go in and you you yourself, you're always like, "Oh my god, so now they're all going to be experts. Let me do this expert level." So So I stopped myself and I'm like, "Okay, let's let's make it dynamic, right?" And so you get there and you ask specific questions to see where people are and you realize they're like still less than 101 because maybe the other training wasn't as effective or it didn't land or whatever or it just covered completely different topics that you expected. So this applies to AI to anything that that you're training and uh sometimes we we sort of shoot ourselves in the foot because we trust the what we told what **[00:44:00]** they told us before actually going in and and proddding. And when you prod like you said now it's like oh let's let's begin here. >> You're absolutely right and you look you again you're better than me because I've gone into meetings where some these guys are these are and this is no shade on these people by the way. I mean the the reason that they think they're great is because of you know the circles they move in but things are just moving so quickly. But I I have gone into a meeting where someone said right these are these are an incredibly advanced team. can you show them the most advanced things you do with with your AI stack? And I did. And people said, "Well, I I don't understand what's just happened. What what what have you just done?" And I was like, and then you have to go, "Okay, I see. I see. All right." And and you know, it's it is no it is no shade at all. And it because you know, I spend a lot of time in this. This is my full-time job. And it's just it is so hard because everybody can use AI for >> It [clears throat] is so hard to judge people's level of expertise for you as a trainer or an enabler or a builder, but also for you as an individual. So I always think I am not going to be the best person in the room >> because we've discussed things. I've learned stuff from you. Hopefully you've learned stuff from me. because that's how you get better >> is [clears throat] by not always thinking you're the uber expert. >> I I love that because I sometimes get and very often nowadays very pleasantly surprised with non-technical people using AI and how they use it. So, we'll be chatting about something and I might know all the like really advanced things and like you said like about certain things, but and you **[00:46:00]** talk to them and they're like, "Oh, yeah, yeah, I built this application that does this, this this and you're like, how did you think of that?" Cuz they're they they're so out of the system thinking that there's no barriers to stop them from, hm, maybe this won't work. And they try some stuff that you're like, wow. And you learn from someone who's not technical because their use of AI is so drastically different from that of a software engineer that it's it's mind-blowing. I I mean enjoy it. >> I completely agree and and I think that is the mistake that a lot of organizations are making. They are handing AI over to the technical people >> where you you want it to be with the people who want to solve a problem, >> who want to do something. You know, I remember being in a a meeting last year one person who was not technical had to deliver reports to a client um and they needed to get the data from um an Excel report and put it onto a web app. And there was a we had a member of um um the technology team a developer who was responsible for what connectors were allowed. And the conversation was I need to get data from this Excel report and send it to a client. So I need I need an Excel connector. And then the tech the then I'm paraphrasing and then the tech guy was no we are not allowed to install an Excel connector onto your AI system. that is not um that so we are not able to deliver that process and I was like well well hold on hold on you what you've actually said is you need to get data from something to put into something else is there a is there a way to get that data into something that **[00:48:00]** isn't Excel for example ESV oh we could do that okay is that a problem that isn't a problem we just can't have an Excel connector though the the request was meeting on a technical versus nontechnical and you know there needs to be something in between that was like we just need to solve the problem not the tech does that make sense >> that's that's an excellent way of putting it I love that example because it is many times the technical team will say where we will be quick to say no that can't that can be done that can work no that won't work that because of your prejudice from for pasta experiences etc or rules and guidelines etc. But but what you just said puts it so clearly that they need something. Many people think Excel. They're not talk the client, the customer, the user is not really thinking Excel. They're thinking a table of data. They don't care. Excel is the only way they know how to view it. But they don't need Excel. They just need the table of data. >> But that's it. Like they don't care. And then that's, you know, that's almost how to think of the AI. It doesn't care where the data comes from. It doesn't need an Excel connector. It just needs the data. >> That's amazing. What in your experience from from what I gather um you do a lot of training also with with uh different institutions, right? So, what do you find that there's a benefit or not a benefit of having multiple people in the room from different when you're doing these trainings. >> Incredibly um incredibly relevant question, a great one and I think also talks back to the shapes part you know is um so there's two parts to it. It's when you have people from vastly different departments who realizes that **[00:50:00]** the problems that they are trying to solve are 80% alike and you know they're just trying to get something from somewhere do something to it and get it to somewhere else. And if you get them thinking like that, they can, you know, stop thinking about the Excel and start thinking about the thing they want to accomplish. But the other thing that's really important is it allows departments, colleagues, organizations to think of the knock-on effects. So I had a client who was a gaming company, heavily regulated industry. Their engineering team were really good. I mean really good. And you know they were using um you know an enterprise solution and they were shipping features 100 times faster you know after a month you into all of their into all of their platforms. Heavily regulated though meant that um every feature before shipping needed someone from the legal department to look at it. >> Legal department didn't have any AI at all. So all that was happening is they're amazing, the technology team, the engineering team, they are amazing, but they're just piling to this poor legal person who's going where are all these emails coming from? I just don't have time to do that. So what we did when engineering their training is what I want you to do is I want you to educate them so that they can make your work actually see the light of day. And I think that's why having multiple departments working together, you you could just be pushing a bottleneck elsewhere and feeling very pleased with >> Yeah, that's a great way to put it. It's a not only do you learn from what other people are doing and notice patterns, but also you might see that what's actually stopping a big part of your performance is that someone in **[00:52:00]** the loop either doesn't understand something or is doing something in a slow way or they don't have the access to the tools or what you're giving them is a completely different type of input that they need and for you you just changing your output to match their input could yeah drastically affect the chain. Well, we in fact that's we we had an exercise where you we'd had four or five complex joined workflows and workflow four the end they were like well we're just going to have to we can't really define what it is until we find out what we're getting from workflow 3. And I was like well you're the last mile in the chain. You should be telling workflow three what you want what you need and then they should be telling two should be telling one. You shouldn't be being, you know, beholden. You need to deliver. You're the delivery point. Therefore, you know, nice like like you say, you can they can adjust their output if that's what if that's what you need. >> Yeah, this is so much fun. I enjoy talking about all this a lot because it's something so new and in the frontier and I I'm very interested in seeing all sorts of businesses but specifically smaller businesses and medium business being able to take advantage of this to close the gap between them and the enterprise and and grow themselves, grow the economy, grow the city, grow etc. So, so I find these tools being super useful and getting it >> not only getting it into their hands, but training them like you're doing at the other group for them to be enabled and upskilled to do all this is is an incredible feat and and super helpful for for the economy at large. >> I hope so. I hope so. I think hardly any **[00:54:00]** of this conversation has really been about AI. It's been about how you think about it, not about necessarily how you use it. You know, it is not should I be which is better ChatGPT or Claude. That isn't even a question. If you're asking that, then you know, go and have a you go and play with them. You'll find out you'll find out which one suits you If if you want to leave our audience with a remark or or a suggestion based on your experience and what you see every day in the trenches, what would that be? I would go to work tomorrow and I would spend some time in my working day to find out apart from my boss what is really annoying and find that process that you are doing every day and it is drudgery and then an AI platform at it and saying how might you do this differently here are our constraints here's what we need to get out Claude have a look at And I'd be doing that all the time. And once you get into that sort of mindset, you start noticing things that you have allowed to be unsatisfactory and you can fix them and you know there's a lot less friction in your life then which I think is a it's a good place to be. >> That's that's excellent advice. I found that people once they do that first one >> it's it's uh I don't know I don't know what what what what what's triggered in our bodies but it's like oh it's sort of a release >> it's like oh if it can do that can it do that and then that's it that's it yeah >> amazing Ross thank you so much for **[00:56:00]** coming on the show today it has been a brilliant conversation. I had tons of fun. We should do it again and go deeper into some of these topics. Um, thank you so much. What is the best place for people to find you, find more about the Galahad >> Um, galahadgroup.co.uk is our website. Started.co.uk. We are global. We work work with clients across the globe. I'm Okay. And you you can find me on LinkedIn with a photo where I look a lot younger than I do today. >> Amazing. Well, for everyone who's listening, thank you for listening to the show today. And please, if you haven't, please like and subscribe because that way you will be the first to know when an excellent episode like this one with Ross is released. Thanks everyone. And uh we'll see you in the next one. Thanks, Ross.