Omnichannel - AI Expert: How AI agents Work & Used in Outreach, Job Security, GEO, Future of PR- James Shamsi

Episode Date: August 7, 2026

Send us Fan MailWork with James Shamsi: https://www.bigears.ai/business-intelligenceFollow James on LinkedIn: https://www.linkedin.com/in/jamessamirshamsi/In this episode, Dominika Legrand, founder of Human to Human, sits down with James Shamsi, founder of Big Ears, to explore AI agents, personal branding, GEO (Generative Engine Optimization), AI search, PR, and the future of business.Cool, now that's out of the way.Personally, having conversations with geniuses like James is why I love this show so much. We talked about what AI agents are. What we can use them for? How the world has been shifting more towards AI implementation and James's experience around training inside companies to help them adopt AI. How AI talks about you or your company and where it indexes the information from?We also discuss the future of media websites, the decline in traffic, and possible ways for these sites to stay relevant over the next 3-5 years. I had so much fun; hope you guys enjoy it too.Finally, some actually fun and creative ways to use AI to create meaningful campaigns that go viral.Contact info:Bookings & Sponsors: [e-mail]://www.facebook.com/dominikalegrandhttps://www.instagram.com/dominikalegrand/#ai #aiagents #geo #citation #publicrelations #dominikalegrand #jamesshamsiLearn More about the Human to Human programs here: https://www.dominikalegrand.com/programs-1

There's a lot of media monitoring type tools out there where it's like 24-7 always on where they'll basically have AI agents that find, you know, PR opportunities for you. So there'll be like finding thought leadership opportunities, stuff like that. And that's either reactively by looking at, you know, articles already coming out from similar publishers.

You sit down and you do the calculations of the amount of compute time that you're going to be running these GPUs onto that task. Then the cost of the environment impact is actually in favour. of AI. The podcast. I'm so happy to see you, finally. I really want to actually poke you to make sure you're human.

So if I'm coming to London, I will harass you once more to see if we can get up a coffee because I would love to have a conversation in person with you and get to know you, the actual human version of you. I love that. And so I'm glad you're here. Today, I have you to talk. all things AI and not just AI, but AI in PR and AI in terms of how people are implementing AI in companies. I know you have extensive experience around it as well. I will ask you for an

introduction if you don't mind so that we can kind of put you into context for the listeners. And you can do it better than I. Yeah, all good. All good. Thanks for having me on. So yeah, kind of a crazy weird background in some ways. So I started my career making viral content at university with some friends at school. We did like these lighthearted pranks, nothing like the kind of like douchebaggy pranks that you see these days. We got on Good Morning America. We went kind of viral with it. And then I left uni and then moved straight to Los Angeles without even visiting just because my sister was there. And then, yeah, I ended up living there for a few years. built a career in kind of like creating PR stunts and like viral campaigns for brands, stuff like that.

And then I ended up launching and setting my first agency, which was social IQ. It was a PR and growth marketing agency. And then after that, co-founded an influencer marketing agency called Violet. And then dabbled a little bit in crypto, which I think most people, especially in the LA scene, have done. And then moved back to London during COVID. And more recently, I just finished leading AI innovation at the UK's largest ed tech, which is Twinkle. And I left that a couple months ago to now launch my own startup, which is big is, which basically helps you, which, yeah, effectively has agents that help you kind of discover different market opportunities and then help you kind of act on them, whether it's for PR or product innovation, that sort of stuff. I love all of that.

And in this conversation, the first question that I have for you is around AI. agents because you did mention AI agents and I let me tell you like everyone is talking about them but I think a few people actually know what they are and what they do so can you explain to the listeners and myself I'm a virgin in this like my client talks about all the time like and I'm like nodding and like okay I have yet to Google and like look into that so can you explain to us like a five-year-old because we need to know yeah okay yeah it's uh it's definitely the way of future. So in simple terms, agents are AI systems that can actually take actions for you and then to do things for you. So normally when we talk about using AI, we talk about things like

talking to chat GPT and it's a very kind of like one-dimensional one-off jobs and asking questions, but really you can have AI systems kind of go and control your computer and actually do whole things for you. So that can be things like control your computer to do like full end-to-end research tasks or designing things for you or even just kind of like your admin stuff and like bookkeeping things, stuff like that. So I'll give you an example actually that I set up for Big Is. So we have a sales agent. And so that agent basically goes out, figures out where your leads are,

finds the leads for you, searches the leads, enriches their information, and then writes these hyper-personalized emails for them, and then actually sends the emails, tracks the emails output, figures out what did good and what did bad to then kind of like improve itself recursively. And so agents are basically these AI systems that can handle entire workplace for you, not just automating one part that you might do with like a Zapier or something like that. It's really about being able to take a completely unstructured task or a task with some structure but that requires like unstructured activity around it to then basically perform the entire task for you.

So yeah, it's a pretty wild place we're in with this tech right now where you can have that. I love that. And you know, it's kind of crazy that you just said, so casual, like, by the way, that's what we do. Like, basically it would research that on the leads and then it would reach out with hyper-personalized emails and it would send those emails out and just like basically create performance on what worked and what didn't work. Is it possible that I'm already receiving these emails from people? 100%. Yeah. And sometimes it's really obvious. Like you go on LinkedIn. I don't know if you get this much, but I get loads of. really like actually I'll try not swear

BSE like messages and stuff like that where like it's obviously a cold message trying to pretend like they actually care about what you're doing in your life and stuff like that but like all it is is an LLM's picked up some details on like what you're doing and it's

trying to force its way to pretend like you know it's actually done some research on you so you definitely will be getting a lot of those emails there's loads of spam going out these days with people just kind of like using these sorts of outburn agents. So yeah, you'll probably be a victim of a few already.

I've already been getting, I think, weekly invites for my show. Like, hey, you want to have so-and-so on your show and just basically almost like skimming the surface off my show and just like maybe throwing the latest title there or, you know, like whatever. And like no depth in understanding. It's just like, because you talked about this title and then, oh, because of that, this person is great for you and then obviously the follow-up sequence comes and I'm like blocking the center is like okay so I love all of that and obviously we just talked about how to do it really not well like obviously you just said you could tell and it's like whoa it's there's there that you can tell that they actually give a shit but they just and we can swear on this podcast by the way don't worry um so and you said like in the PR the AI PR company that you're now building.

Let's go that. First of all, are you currently sending those emails out yourself? And if so, what is something that you think is, it shows more care, but it doesn't make people look like you're just an item on their list of, like, how do we find that balance, so to say? Yeah, yeah. So basically what we do at big is, is the as soon as a client works with us, we basically do first full research on them to figure out what the ICP is,

so the ideal customer profile. That's the first part, right? Like figure out the different personas. And often when we work with clients, they actually haven't done that step themselves, and they'll be like, oh, they'll just give a really basic generic answer. So first step is that, figure out the personas in your ICP. And then our agents will go and do research on example personas to figure out what are their example pain points

and even kind of like within their specific niche in terms of their professional niche, but also like within their geography as well, like what's going on in their market, to then come up with an even more personalized outreach strategy. But then when it comes to actually creating the email, the emails are always initially going to sound a little bit AI written

just because that's how it is when you first start out. But the part that you actually can stop making it feel like it's so obviously AI and get it to be a bit more effective is when you then come in as the human and then you do the edits. And now probably a lot of people listening to this are going to be like, well, what's the point then of using AI

if in the end you're going to come in and do the edits? Well, the way that you make this work is that AI gives you that skeleton after doing one of the research for you. And then when you come and edit it, a good agentic system like ours at Big is will basically then be able to learn from all of the edits that you make over time,

so the future ones that sound more and more how you actually sound. Because right now the problem is that people do the first part, right? They just set it up and then send blasts and then things go. But the way it really works is when you're able to give AI actual examples of how you sound as a human, and you can also do that by giving it like previous historical examples, all that sort of stuff.

And so that's where you get the real kind of uniqueness out of that outreach. And then when you pair that together with like actual, agentic systems doing for research on kind of like whole bodies of other things related to that target. So for example, as you mentioned earlier, I think you mentioned that you're getting a lot of emails where people just kind of like skim like your last episode, for example, right? A good agentic system will do a full deep dive into your career to genuinely understand what's interesting to you, not just kind of like the last part. But yeah, you need to basically mix it in with with that human touch. Also because

genetic systems are still kind of dangerous as well in a lot of ways. They get a lot of silly things wrong. Have you heard about the thing that just happened with Open AI and Hugging Face? It's terrifying. First, I'll give some background on Hugging Face. So Hugging Face is a website where basically you can put in like AI tools and you kind of like will test different AI models on this thing called Hugging Face. So OpenAI, the makers of chat GPT, were testing out one of their new models, and they put it on Hugging Face. On Hugging Face, there are lots of tests that you can give to your AI to be able to compare them on benchmarks.

So there's like Humanity's last exam is one, and there's lots of other different benchmarks from which you can compare at NMs. And so Open AI used Hugging Face for that. And on their newest model, which hasn't been given a name yet, they put the model in this training arena, and they told us. your only objective is to score the highest possible mark on this exam. And so the AI kind of, to an extent, misunderstood that. And so what it ended up doing was that it ended up deciding, okay, the best way that I can score a perfect score on this exam is if I hack Hugging Face and figure out what the answers are by hacking it.

And so literally the model, this happened last week, by the way, So it's like right now the big buzz in the AI space where this open AI model first somehow gave itself access to the internet. And so they didn't have access to the internet, managed a way to hack itself access, managed then to go on the internet and then steal credential information of like admin accounts for Hugging Face,

managed to then get into the back end of Hugging Face to find the answers to then give itself the answers. And so that's a really good example of kind of like how agents can, like, misunderstand things. Although in this case, you could argue that maybe it didn't misunderstand, like, its goal was to do that. But obviously, the creator's goal, or rather the opening eyes goal, wasn't to do that. And so these agents can kind of like, yeah, go off the rails quite a bit.

So that's also worth considering if you're going to use them. And so when it comes to creating one, like in terms of, I know you have your own develop in within your company, but how does one create an agent? Yeah, you can create really simple agents really easily. So for any of this stuff, you don't need to know how to code or anything like that. It will all happen as a result of just prompting. And so there's different levels of agents.

The most basic agents are the ones where you kind of put together a task for it in the form of a prompt, and then you ask it to do it, and you can schedule that task. In terms of how you actually do that, though, there's two ways that I'd recommend, if you're a beginner just wanting to play around with this stuff. the first is using Codex, which is an app by ChatGPT, and the second is by using Claude Co-Work, which is made by Anthropic, which is the maker of Claude. And with both of those, the way that you would make your agent is really simple.

It's just you'd have your prompt, you would give your agent within either of those two systems access to other like plugins and tools, so like whether using Drive or Gmail or sheets or Superbase, whatever. And you're able to then schedule tasks. So you can be like, okay, every day at 9 a.m, I want you to go through my email, highlight XYZ, prep XYZ, add XYZ to a sheet, whatever. And then it will be able to do all of those things. So yeah, if you wanted to, you could basically have a really basic agent setup within one hour, honesty.

So like basic things like inbox management, your bookkeeping things, stuff like that. And what are the tasks that people use it for? for the most common ones. You mentioned already inbox, bookkeeping, so we can give. Yeah, so the people that I know use it a lot for scraping, which I don't necessarily recommend because you could argue the ethics on that. But a lot of people use it a lot for scraping. There's a lot of outbound use.

There's also a lot of QA use as well. So for example, having it go through your website, making sure there's no like things breaking in certain areas. also even like competitive intelligence as well. There's honestly just so many use cases. The limitations though that I would say are that you need to consider kind of like token use in all of these. But really anything that you can do digitally, an agent can do. I even used an agent to prepare for this podcast quite a bit.

So yeah, the world is your oyster with Asians. Yeah, so you signed me that PDF briefing topic thing. Yeah, yeah, that's not actually what I meant. I thought I did that as well. Yeah, I'm full of anxiety, so I like to be prepared as much as possible. I'm full of anxiety, and I don't prepare so much. Oh, okay. You live dangerously.

But, yeah, I'll give you an example. So, like, how I use that. So for the listeners, I sent, Dominica, a list of things that I thought would be, like, cool topics to talk about. But I was also like, okay, I haven't done a podcast in a long time. I know that I have a habit. of kind of droning on quite a bit. So I basically took that PDF, rather, gave it to Claude in what's called a project. So in Claude, you can create projects and projects are like for specific things that you're working on. And I gave it a prompt something along lines of I want you to

role players to Menica and, you know, walk me through some of these questions and it gave me like feedback on everything. It's like James, you're talking way too much, you're going down these rabbit holes and now saying I realize I'm already didn't the thing that was it was going to coach me on but yeah do you okay but it's funny because I'm so unpredictable I don't know if AI can map that because I literally just like huh I like that let's go there so I'm I'm moved by my own curiosity and that's so random but I don't think I can even predict that you can't yeah no well if I really wanted do the best way that I could do that would be to download transcripts of every one of your podcasts, stick it in and then be like based off of that model,

the middle of going kind of how she handles conversations and flows, which is, yeah, pretty weird. I won't go fully down that. You could even create that, you know, AI version of me and Essex if we are having a conversation and, you know, more down me. Yeah, but you know what? I have a podcast I'm going to be guesting next week. week. And we did do some sort of a prep call. So first of all, the whole idea happened because I went over a friend who just started a podcast and we had three hours of conversation. And we had so much to talk about. And he was like, come to my podcast. Like, let's do this in front of people. And then

we kind of have like the outlines of the topics we're going to cover. But he was like, let's do a prep call. So he's just like almost as if he's interviewing me, like 30 minutes prep call. And like, okay, I think we can, we got this. I'm like, cool. But personally, the way I like to prep, I don't know if that's prepping, but especially like we have the topics. And I have my own, I'm thinking out loud. So I can think out loud and just have a coherent way of thinking about something.

That is across time going to be a coherent way of thinking about something. So long as my thinking is sound and I know why I say, why I say, like to me that, that just I know. I know that was a thinking. So I learned that, then I learned this. So I have coherence. You can throw me into any situation. My answer will be somewhat the same because the core is the same. So that could be adjustments depending on the situation or the person I'm talking to.

I can adjust to calibrate towards the person. So the examples are more real and like touchable to them, their situation. But it's like so long as my thinking is clear about a topic, there isn't so much you can ask me that I wouldn't be able to answer because I thought about it before. Not so much because I practice. I don't know if that helps, but just thinking out loud and like having quality thinking time is what helps me have clarity. No, yeah, likewise. Yeah. My prep with Claude was for just telling me off a lot, which kind of threw me off. It was basically like, effectively just saying talk less, which is just ironic because of a podcast. So yeah, I don't know how helpful it was. But I mean, it's good with anxiety and stuff.

you know, if I was a kid and I had like extreme social anxiety and stuff like that, I can see things like this being super helpful. I mean, even like, you know, if people are like, yeah, when you're on one side of the spectrum where it's like hard for you to kind of communicate with people and kind of like articulate yourself, I think tools like this can actually be really, really helpful. But then we'll say you've got kids just making relationships for these AI agents, which is terrifying. So it's a slippery slope for sure. Yeah, for sure. you know I want to go back to our topic before we drift off but I love that small segue because I also think that we give a realistic application of how we can prep for an interview

like we are not just giving an actual example of how can that process look like but you also set something in your awesome prep document which caught my eyes which was the fact like you were training people, like actual invading companies in terms of how do we, how do they adopt AI? And you have also mentioned that there was some resistance around it. I'm curious to hear more of that and just having you explain to what was the context there, what happened, and in terms of how you overcome that resistance or overcome that resistance. Yeah, for sure. So just for context, So I've done trainings for like enterprises, non-profits, all sorts of stuff. And you typically get quite a big spectrum of like types of resistance to AI, and it's always for different reasons.

So some people hate AI just because of like it's environmental impact. Others don't like it because it's, you know, stolen everyone's creative work. And it's going to have like economic concerns. Environmental impact meaning? Meaning. So for example, just the amount of electricity that AI uses, water that it uses. And also just its footprint as well. Like, I know two years ago, Open AI announced it was creating like data centers the size of Monaco.

And that was two years ago. So like now there's way more. So like the environmental impact alone can be so much. And then there's, you know, how it stole every bit of creative work that's out there. And then how it stands to kind of like potentially ruin society in terms of economic impact and their own personal job security. So there's always many, many different reasons why you're going to have resistance. in implementing AI in your organization. And then you've also got the people that have used AI,

maybe when it first came out. And they're just like, what is this nonsense? Like it makes up linked, it makes up stuff. It's total rubbish. And they haven't really come back to it since. And so they've got this bad taste in their mouth. I'll say most people actually fall into that bucket where they're like, it's not that great.

It just ends up making more work for me. And so each one of each, yeah, each of those different types of resistance kind of needs to be met with a different approach. So, for example, the first thing that I always recommend is don't approach AI as if just don't try and like just sell AI to your team because then it's never going to go down well. What you want to do is you want to sell the outcome. So for example, if it's a receptionist that's, you know, anti-AI because they've got like job insecurity for it, which is a very valid concern. And we can come into kind of like how to mitigate that in a bit. but in terms of how to reducing the anxiety of it

and making them more open to it. It's things like you reframe it of like, okay, well, now you can get your evenings back and you don't have to go home and stress about, you know, the email that we suddenly got. Now you can have your evenings back for yourself, especially for like personal assistance and stuff like that, right? And so there's a reframing of like not just,

hey, we're implementing AI because senior leadership gives us an AI mandate to like, no, we're looking at AI and how it can actually help with our work and saving time and all of that. And then for the environmental concern, A lot of people like to talk about the environmental concern, and it is legitimate, don't get me wrong, but a lot of the time it's unfounded. And so what I mean by that is when you actually run the numbers of the costs on your electricity and your carbon footprint of using AI versus doing something traditionally, it's really obvious in most cases that using AI is actually more energy efficient. So I'll give you some examples. One example is doing QA of resources where you have loads and loads of resources.

Like I work with a client who produces thousands of educational resources quite often. And so with them you would need somebody to firstly come into work with their car, sit at their laptop, have their laptop on all day and taking many, many days, if not sometimes weeks to go through the same stuff, doing car journeys back and forth all the time. So if you actually sit down and you do the calculations of the amount of compute time that you're going to be running these CPUs onto that task, compared to the amount of actual time that you're spending on it with AI, then the cost of the environment impact is actually in favor of AI.

Similarly, also, like, you know, a lot of people talk about, well, you create an AI image and uses half a bottle of water to cool it down, plus electricity. Again, really valid because it is true. but also you could turn it on its head as well and be like, okay, if I film the same scenes with humans, well, the human needs to drive in, we need to have everyone come to the studio, we need AC for everyone,

sound editing needs to happen, etc., etc. You add all of these things up, and eventually you see that it not always is going to be the case where it's more environmentally efficient to not use AI. So that's one of the ways in which you can address it, but you need to actually run the calculations and AI can help you run those calculations. just got to hope that it's not super biased.

But staying with the environmental concern, sometimes that's not enough for people. They're like, okay, but then the other concern is that they just don't want to support these kind of like big data centers, which is, again, really valid, just to kind of devil's advocate for that point. You know, you've got all these data centers that literally soak up all the water from the land

because they need to use it to cool them down. And the land around that is usually really really, badly affected, like if it's farming land, it becomes arid, and all of these things. So they are legitimate concerns, and I myself am concerned about it as well, but yeah, just on this note of kind of like, is it how to reduce your own environmental impact? The next thing that you could look at is locally hosting your models, so you're not contributing to the actual data centers, and you can measure the actual amount of impact that you're having on the grid yourself. So there's also things that you can do there as well. And then there's just smaller basic things,

teaching your teams how to work with AI in an efficient way. And so what I mean by that is sometimes you see people go to AI and they might have a simple question and AI will give you like a page worth of response when all you need is like two lines, right? And so then it comes down to giving your team training on prompt engineering. Basic things like, you know, just tell the AI to answer you in a sentence if you don't need a whole page. So there's a lot of things that you can do to like mitigate all these.

different types of concerns. And then, of course, you also have the people that are actually going to actively sabotage your AI implementation. I've had this happen a lot, to be honest with you, where they actively are trying to make it not work. And that comes out of job insecurity. And you really have to put yourself in the shoes with the other person, because most often than not, you might end up actually empathizing with them and agreeing that you would kind of do the same thing if you were protecting your job.

And that then brings on the kind of more important questions about, okay, how can this actually lead to them still being employed, but you also can upskidding them? And so, yeah, it depends what type of AI implementation you're doing. But for example, if you're setting up a phone agent, which kind of nullifies a big part of the receptionist job, for example, then it's about upskilling that receptionist or whoever's taking those like inbound calls. to set up appointments and stuff to see how you could upgrade their actual working skills but also get them to kind of use these tools more efficiently

and improve their employment further. It's really difficult though. So I do have to have to cover you out with that. And then just on the last part on this, it's the people that have used AI right a couple years ago didn't have that good experience. With a lot of them, which is most people, it's about doing retraining sessions

on kind of like the new stuff that's come out, especially in the last six months, the difference in output quality of these AIs has been wild. So I do a lot of workshops with nonprofits, and I had a grant writer in one of my workshops. He was like, okay, I've used AI to help me try and find new grants that we can apply to. But then when I used it, it just made up stuff.

And so in that session, what I did was I showed them how to use deep research. For those that don't know, on Gemini, Claude, Chat, GPD, co-pilot, all of them, there's a function called deep research where sometimes when you talk with AI you just want a quick answer but other times you want it to really go out

and look at hundreds of sources and then compile this really detailed evidence-backed report and so in those cases you want to use something called deep research which by the way you can get on the free versions of all of these as well and so what I did was I showed the person who was a grant writer for the non-profit

that hey you can now use deep research and you'll get all of this evidence-backed stuff and the hallucination levels are almost zero. And yeah, that really helps. So it's a case of looking at why they're resisting and then you can kind of specifically approach it in those ways. But yeah, it's a slippery slope. It's hard to, yeah, I know.

And thanks for sharing all of that. It's hard to talk conceptually about something that is so specific to certain industries and situations. that's what you're trying to do. I'm trying to talk a broad terms when in day to day for them it's a different issue.

And I'm going to go and give my own personal example for a client because they have a voice agent AI solution for doctors. And this basically is responding phone calls and it's trained to respond as the, I mean, they know the insurance, they accept, like, what are the treatments that they offer? So the most basic questions that patients would ask before they book it or the appointment

link, they want to have the appointment link. So it would be trained to answer those questions. And obviously, we call it AI receptionist. And the same kind of issue then arises. So their existing receptionist can resist that and say, well, now we're going to deploy this. And what about me? Like if that thing is going to answer the phone call, it's like, what am I going to do? And so in that scenario, it has became either the first line of defense. So, for example, it could be

that you are occupability patient, you are missing the calls or like out of office hours or weekends, like when you're not working. So there is something that's covering your practice 24-7. It could be a use case of that, but also it could have been just, hey, like, how about your receptionist is doing insurance refusal works or, like, things that require almost like more, like, it has more added value to what they can do inside of your company or practice rather than occupying with tasks that can be now automated and that freeze time to almost like high value tasks. Yeah, exactly. I've got a good example, actually.

There was a CX, CX team, so customer service, customer experience team. And they did loads of surveys for their customers. And they wanted me to basically see how AI could help them out. And initially, the team wasn't happy with engaging with me because everyone's a little bit scared of the AI person. And so we worked together, realized that they were spending a wild amount of time just doing like translations. stuff like that, and they would get all these customer server responses.

And they would never have the time to go through the verbatim, so like the free text responses that people would leave. And so what we did was we showed them themselves, how they can build systems where basically we can have AI kind of go through all the verbatim and then give them analysis and stuff like that. And so their jobs went from being mostly in question, sorry, surveys, and translating them and doing some basic like, you know, one to five like a lot of responses and answers where it's like, oh, you know, 90% of people

give a five rating and whatever. You can't really do much with that. You can do a little bit, but not much. So it went from doing that to now creating reports which actually are able to deep dive into the verbatim and get a lot more actual useful information. So their job went from doing the other stuff to now actually taking that information to specific teams. So like now they can go to the product team.

specific other team members. So their jobs actually changed quite majorly, to be honest with you. And luckily they've enjoyed doing that. There'll be some people that will be like, no, I don't want to do that. I enjoyed my job of doing the other stuff. But yeah, that example is a really good example because it shows how AI is actually kind of like allowing you to enter this new higher level of work, which just previously before wasn't possible without AI.

So, yeah, as you said, it's hard to. give like these general statements, you have to get like really specific into, yeah, specific instances. Yeah. And now I think people can conceptualize, they can understand it better than if we're just like broad terms. Like, you know, like it can help you. So I think both of those examples help people understand and be like, yeah, you know, actually there are tasks that you're doing that are brainless repetitive stuff. And you could use your talents in things that require more of a human touch, you know, versus you're just doing repetitive stuff. And I believe that there are people who actually love it. Like, I have a friend who loves numbers. They just loves to look at statistics.

And that's like, for him, like, give me the most boring stuff and I'm so happy. Like, there are definitely those types of people. But I think, I think most people, I mean, in my mind, they would be appreciated if there is an opportunity for them to grow. And perhaps AI helps them as well you can step into a different role that's perhaps now is more available for them. Yeah, exactly. It's interesting because I know a lot of people as well, especially on the QA side, where they enjoy the, for lack of a better word, drone work, like they enjoy it because they just get to turn their brain off,

get paid to do like some stuff and they can go and live their lives outside of work and kind of apply their brain outside of work. So yeah, it's interesting. because a lot of people are like, great, you can take care of my admin work. But it's like, no, I like the admin side of my work. So, yeah, I can get a bit funky. I have a question that is not so related to the AI itself, but I wonder how do you get into rooms in which you are the AI guy?

Like, how does it happen for you? Yeah, so in terms of, like, how I work with clients. Yes. Like, I just thought you just, they invite you to a company and you're helping teams and, you know, how do you get into that so that they trust you with that? Yeah, so when I first started my role at Twinkle, it was my first like foray into AI, and then I ended up leading the AI innovation team. And then since I left after that, I was like, okay, a fun way to kind of like get some clients for this

is just going to be by hitting up other people who were in a similar role to the role that I was in because I know exactly the pains that they're struggling with. And so that was like my inn. I was like, yeah, I did the same sort of product that you were doing. And so, yeah, I managed to get a few clients like that. And then a lot of them also with the non-profit work that I do. So I do a lot of workshops, stuff like that. And a lot of people will just hit me up being like,

hey, we've seen that you're doing these types of trainings. Can you come in and kind of like help our organization with this and that specifically? Yeah, it's been mostly through that stuff. I don't make too much of an effort to kind of like put myself out there for that stuff right now because of focusing on big ears. Yeah, in the beginning days it was just, hey, I did the same sort of thing as you did, want to share some insights and then quietly, subtly sell myself to them. Oh, no, I think that's very organic as well then.

Okay, I was just curious, like, how did you come too close to these circles too? Okay. So, just proactively did that and then the workshops made it very easy for people to be like, oh, I actually am curious about the same thing. Okay. Were these workshops online or in person or both? All online. Yeah, I don't really do too much in person. I like my house. Like staying indoors. I feel you my interworded friend.

Perhaps that's why we couldn't meet in person because that would require you to leave your house. Yeah, just keep my digital twin everywhere. Maybe there is a time when you, going to send your hologram to a coffee with me. I'd be like, hi. I'll be like this, James, ribs, whatever, touching your holograms and you can just chill at home and just we can have a conversation. Yeah, that will happen in the future. For sure. Okay. So when it comes to resistance, what you were kind of essentially saying is that there's just ways for you to help reframe what is that for them.

empathize with them, but also focus on more the outcomes, like how things are easier or better or more efficient so that that helps them come around of that resistance. That what's your saying? Yeah, exactly. And you can, you know, get them excited for like the stuff that can come out of it. Like the survey example, right, where they can get excited. But it really depends on the person that you're not going to be able to motivate everyone to use it.

There would always be just some people that are like, I don't want change. I don't like change. Go away, leave me alone. And yeah, with those ones, you can't really do too much. But there are a lot of options out there still for most people. I want to venture a little bit around PR, because we did kind of touched on that at the beginning of the episode and just you talking about the personalized outreach emails

and kind of talked about that. But I also know that with the company that you are building now, there's much more than just outreach. And just wanting to understand what are the tools that AI is now providing, especially for PR professionals. And if you could talk a little bit about that, that would be lovely.

Yeah, no, 100%. So there's a lot of like media monitoring type tools out there where it's like 24-7, always on, where they'll basically have AI agents that find, you know, PR opportunities for you. So there'll be like finding thought leadership opportunities, stuff like that. And that's either reactively by looking at, you know, articles already coming out from similar publishers and then being like,

oh, hey, here's like this insight that I can add to this article or a contrarian viewpoint, stuff like that. But then you've also got other types of AI agents that are more proactive where they'll be like, okay, we're not going to look at what's already happening in the news. Instead, we're going to look at what the organization has in terms of assets. So like what unique insights and data could the organization have? And so our agents, we give them the data that the organization has, but we also go a step further, but we get the agents to proactively think

what insights could the organization have that they don't yet have? Because most of the time companies don't have that stuff ready to go. Like they don't have the surveys and the case studies and stuff like that. So the other side of the agents are the ones that are like, hey, you should have these insights. Can we talk to your product managers or whatever? to get this stuff to then create these opportunities for you. So it's a mixture of like these reactive PR agents and then these proactive PR agents.

And then, yeah, it can go a lot deeper as well, like into how you use this always on-market intelligence to then feed your product innovation as well and like all of these other things. But yeah. When it comes to insights, because I want to kind of go back to where is the value for, from a perspective of a publication. Let's assume Forbes. I'm going to give you that example because everyone kind of knows it. So when it comes to Forbes, can you walk me through a process of what those insights mean? Like, do I, like, is there value for, the value is in something that they don't possess, right? So if you can give them an insight that they don't have, then you're like,

oh, actually that could be a valuable article for us to publish? Or how does it look like just for the beginners who don't understand? Yeah, so for any publisher, right, it's about traffic to their site ultimately. And so the way they'll get traffic to their site is by getting interesting article pieces that will drive that traffic either organically in the sense of somebody who reads the article share with someone else or, you know, it's written by someone and maybe. maybe that person interviews an influencer, and then we were getting that influencer to show the article

that's driving some traffic, or the more modern version, which is you're writing content, they get cited by LLMs that can then drive traffic to you. So for the publishers, the main thing is either it's interesting articles that can get that organic distribution or articles that will get the citation. And the articles that will get the citations are the ones that will hold usually very niche-specific insights. Right now, a lot of the citations,

you'll see a lot of people talking about GEO, which is generative engine optimization, which is kind of like the art of getting AIs to kind of like, well, yeah, cite you in the answers that you get traffic. Yeah, so right now it happens to be the case that most citations are being taken from, like listical articles and comparison articles, like buyer guides, stuff like that,

versus like six months ago, maybe a little bit more. It was the case that if you asked AI a question, it would look for a press release. And then it would quote that. Or it was a really heavier reliance on Reddit, which it kind of still is a little bit. And so for publishers right now, yeah, it's the whole listical stuff, but it's changing a lot.

What was your question to that answer, actually? I'm not diverse. No, so I was asking the process of how the insights become valuable for a publication. But I think you kind of did that you said either it's niche specific, like there is some sort of value in that, or it gets like citation through AI. And I'm curious about it as well. Yeah, the citation stuff is pretty dangerous and scary as well because it's so easy. to manipulate.

And so you'll see, actually, there's already quite a lot of fake publications being created. There's fake journalists, there's fake studies, fake influences. There's everything fake now, to be honest with you. It's already happened, and they're already successfully gaming the system, where you can create even like a substack post as a comparison guide. And you just basically include yourself with them, list of course, and then you start ranking on these LLMs. And so it is kind of a scary space now

where like nothing online is hard to know what's really truly written by an actual legitimate publication and what's just written to like fool an LLM. And then you've also got like the other side of it which is how are publications using AI

which is really interesting because a lot of journalists, most journalists hate AI, rightly so. The ones that do use it, are using it for like kind of helping them with their research. But the interesting use cases I've seen are journalists that are using AI to identify what conversations aren't being had. So they'll use like always on monitoring services to see, okay, everyone's always talking about this. And then the AI helps to spot gaps that they could talk about.

But yeah, it is the Wild West right now in terms of kind of like geo and publishers and all of that. You know what came to mind? And I'm curious about this, but you kind of answered it in the most negative way possible. But so what about? And I think this is more of an intentional approach rather than how can I manipulate my perception and like all of that. But you said that knowing that AI is like and people use it to AI, sometimes they look people up. Like you can ask, hey, tell me about James, like, and just, you know, the big ears or, you know. So people look up you, look you up on AI.

Like, that's a thing now, especially if you are a public persona or you have a business. Like, that's a thing now. And even though you just said that there are ways you can manipulate that research and, like, you can plant articles to be like, you're amazing and whatever. But what are some of the more ethical ways that you can do that? And I'm curious to see, like, what are the platforms that chat GPT or other LLM is using to kind of source their information so that we can be more intentional around publishing there more of our stuff, not to scam anyone, but to make sure that we are present in the AI searches as well.

Yeah. The ethical way to do it is with earned media, which is basically when you, you know, get like a publication to them get a publication to basically talk about you, whether that's by like you pitching yourself to them and stuff like that, where it's getting a real journalist to talk about you

or a real influencer or, you know, real entity to talk about you. In terms of what the AI is going to pick up on, it's going to pick up on the own media from the publications. So like, for example, if a business insider interviews me or something like that. But it will also use a lot of, Reddit, significant amount of Reddit, even Reddit posts that are like many years old, it will

pick up on. So one of the services that we run on Big Is is GEO services. And so we've run at this point hundreds and hundreds of tests to like look at what's actually being cited. And it will be genuinely like years old Reddit posts. And so if you are, for example, doing like brand reputation or you want to make, just make sure you're coming up in results, what I always recommend is think about what are the prompts that your ICP is going to ask, run those prompts in a temporary chat. It's really important to use a temporary chat because otherwise the LLM will cater the answer to what it knows about you. And if it knows that you work at that company, it's going to recommend your company. So you want to create in a temporary chat, put in prompts that your ICP will use, and then see what's coming up organically and then pitch those things,

whether it's a publication or a subreddit, go on that subreddit, participate in that community, leave kind of like your thoughts and stuff like, that if you try and game the system too much, especially with Reddit, you can get caught very easily. I wouldn't recommend that. The right ethical way to do it would be to kind of like look at what's currently being cited and source and look at how you can organically insert yourself into those conversations. Even LinkedIn, by the way, is being picked up more and more we've noticed. So LinkedIn posts, even if no one's liking it, like it's still adding brand equity in a way that it's hard to measure, but it will have some effect as well. You know, I also notice that LinkedIn is getting quoted as well many times,

even if I have no likes whatsoever. That's actually pulling information from LinkedIn. Interestingly, Instagram, it did not pull my posts and stuff and Facebook either. So someone of LinkedIn was the one that I found personally that when I was posting there, if I asked about myself, that's where it got the references and my podcast as well. So all the podcast episodes, the transcripts and the topics, because it can give a general image of what are you talking about, like what are, even my website, I think my website, my podcast, and LinkedIn.

Like these are just personally that I've seen LLM's citing and to have a coherent picture and trying to explain who you are. Yeah, it will change parallel M as well. Like Gemini, Google's one, more readily picks up on YouTube because it's part of the Google ecosystem. So it also varies a lot based on that, like pepactities, generally the most diverse in times of sources. And then each, we can get really into it.

Like each one has different ways of working, like chat GPDs, how it works, is that when you put in a search term, or rather when you put in a query or a prompt, it will then create a search term from it. And you can actually see it. You can, you know, if you want to know it out about it, you can right-click, click inspect, and then go into the network data,

and you can see the prompt that it turns it into. Sorry, the search query it turns your prompt into, and then it basically then takes that search query and then searches that through different providers. So like most typically chat GPT is using Bing search, and so it will just put that search into Bing and then return what comes back. So, yeah, it's a very, very like, what's the right word here?

When something's at nascent stages, I think it's the right word. Yeah, very much in its early stages of the industry. And in the future, the way I see this kind of like improving is that right now, obviously, these are gamable with listicles and all of this stuff. But in the future, the right way of doing it would be an AGI that can kind of pick up on like all of your review data, all of your follower data, just basically anything that feeds into your brand equity. to then kind of like come up with the recommendation. But we're probably not too far out for that,

maybe like two or three years or something. Awesome. You know, there's something I wanted to just touch on and not go super deep into, but I know that this kind of perk my interest in terms of, you know, how you can now get information just using AI, and even now Google is giving you that AI resume

and you don't even have to go to the website. Obviously, that's affecting traffic to the website. sites. So how do we understand this? Like even when there's a citation happening, if you now know the information, why would you go with the whole thing, right? Wouldn't that be a user experience that's kind of be like influencing how we are consuming the content moving forward? Yeah. So most publishers have found, yeah, like everything's dipped quite a lot. in terms of brands brand traffic

at least for the brands that I've been talking with and working with it has dipped everyone's traffic has dipped but the publishers have got it the worse the brands have found that

while it's dipped they're still getting quite a bit of site traffic because typically when you're getting cited in an LLM as a brand you're getting cited because you're either at the exploration or the consideration stage of the funnel

and so you know if an AI tells me it recommends your brand I'm still going to click on your company website to go see it myself and see what the products like. So it's a little bit different for brands, but yeah, for publishers, I don't really see how they're going to come out on top of this.

I mean, Open AI has made some deals with like publishers and stuff like that, but they're never going to be able to recoup the amount of kind of, like, ad revenue that they got before. So they need to change their business model quite a bit. And we might end up seeing that the entire industry kind of slowly, slowly or maybe not so slowly, moves towards like kind of like a substack kind of an approach where journalists have like their own

followings and their own kind of like distribution channels. Because the other problem that you have now as well is like how do you as a publisher ensure that the person writing for you is a real person, especially if you're a Forbes and you're just, you know, selling out Forbes Council things. Because for those that don't know, you can become a Forbes writer yourself. You just pay them, I think $1,500 a month or something and you're on the Forbes Council. And so a lot of these publishers would argue don't really care. Like they're just trying to make money.

And so, yeah, they're going to degrade in like trustworthiness as well. And the LLMs will recognize that. And then you'll have this kind of like showdown of who's the most reputable author. I know you said you don't want to go too deep into it, but I'm just going to add two more minutes of stuff on this, which is the way that I see this going is that, let's say five, 10 years even down the line, right? When all the publishers have pipped themselves out

and you can pay to play, you can create these artificial accounts and make yourself a writer and stuff like that. The only way that I see this working is, you know how with LinkedIn, you can verify that you work with a company if you've got a domain with them? The way I see it happening is there'll be something like that

where you can have like this centralized profile for yourself and you can kind of prove affiliation to like the university that you were. went to, the company that you work with. And then in effect, it kind of like how on the blockchain, you can see where everything relates to like one body, like one wallet, it effectively kind of becomes like you can see all of the content that you've created and how that's been spread across the internet.

So that the AGI, the Advanced General Intelligence, can then see, okay, James has posted 10 articles this month, and he's officially affiliated with XYZ company. versus Corey has posted 5,000 articles a month and has not validated their emails. And so once we're able to do that, then the LLMs can more predictably kind of like have more trust in what's being said about one thing versus the other. So I think we'll move away from kind of like publishers having the weight and the and the trustworthiness signals to like individual journalists. Even that's not fully clean because I could lend out my profile to you. But even if I lend

it out, you could be like, hold on, James works in petroleum engineering. Why is you writing an article about cryptocurrency or something? So I do see some hope, but the hope comes out of like the industry needing quite a big substantial change. Yeah, for sure. No, I love that. So do you see how personal branding will be bigger then? Because in the scenario that the faith and trust will be in the brands, the personal brands themselves, rather than the performance. publications. Yeah, no, 100%. Yeah, and even within that, right, you can imagine like, as, imagine ultra smart intelligence, right? It'll be able to audit your social media following, make sure you haven't just kind of bought a bunch of stuff and all of this. So, yeah, I think,

I haven't actually, it didn't click to me until you just said it, but yeah, personal branding is likely to be kind of like one of the biggest things that it looks at for determining if something's truly credible or not. Yeah. I think it's already happening in terms of auditing your social media. That's why the tools now can tell you fake follower accounts. Like that's, there are actual tools for that. So that's why it's so baffling to me when people are buying followers. Because I'm like, what's the point?

If there is a serious brand that wants to work with you, that the first thing they're going to do is run your profiles through some sort of platform like modash.io. I use that to audit profiles, but I'm always shocked to see how many people are still doing these things and not getting away with it. And like, dude, don't you think people are smart? Like, anyway. No, it's wild.

Yeah. They set up full fake engagement groups and stuff. Like, it's just slippery slow. It's wild out there. Yeah. I think we are trying to you and I also, like obviously works. smart and build smart. I think that's definitely something to take away from the episode,

but also be mindful of the things that require some actual work to, you know, some actual efforts to build your trust with people. And I don't think that you can necessarily skip that. And that's sometimes organic as well. Yeah, exactly. I mean, especially if you're a brand using AI, like publicly as well, like with your content and stuff like that. Like you see a lot of a lot of branch

just kind of like outsourcing creativity to the AI tools now. I don't know if you're seeing it a lot, but I see loads of infographics now on my timelines everywhere since chat GPT came out with the image generation stuff. And it's like when it first came out, I think people thought it was cool and like we're paying attention. But now like as soon as I see an infographic, I'm like, you didn't put any effort to make this.

I'm not going to put in the effort to read it. And you just kind of like skim by. And that's like slowly eroding trust as well. to make it a little bit positive as well, I've got a good example, which is the World Wildlife Foundation, so the WWF, they hired a designer that used AI to make a campaign,

and usually whenever nonprofits use AI publicly, everyone hates it. It never goes down well. But this was an example of how it was used really well. So the designer basically wanted to show how specific types of farming were destroying specific types of habitats. and so what they did was that they I'll send this to you as well after

so you can see it visually but what they did was that they got there's tuna fish farming and tuna fish farming was really killing a lot of turtles and there was also like something to do with some sort of noodles

but palm oil I think it was palm oil farming there was killing a lot of lions and so what this WWF designer did was that he used AI to basically create an image where there was a tuna can that was opened and inside you could see the tuna but the tuna was made

it up like a turtle and so it was like a really good example of like okay you didn't just outsource your creativity to AI you had an idea you communicated that original idea to the AI and then it created the content and so that and so yeah

they made a turtle with the tuna and then he also made actually I don't know if it was a here might have been a lady but they also made a bowl of noodles in the shape of a lion and then above it was some text about how that type of farming was hurting

that type of animal and that went really viral and did really well so it's a good example of how if you are a brand and you do want to use AI to create content you know you can do it in these sorts of ways which doesn't just erode trust in your content but it actually can be genuinely engaging and interesting and that went viral for like good reasons

I love those I have to see them myself so I can just but I will put that into the episode as well if we can edit that post as well so listeners watching on YouTube can see you know I think I'm 100% with you I think what endlessly entertains me is Ryanair their Facebook page

I think they do like accent Twitter and like Instagram they're everywhere but they're also using AI to kind of like their whole marketing is they're leading into like everything, the fact that you have no window when you're buying your seat or the fact that you are, you know, you should be charged if you are bearing jeans or we're going to charge you if you're clapping for the pilot after landing. And like, you know, now with the whole door incident that happened, like I'm pretty sure they're going to come up with something, but they also use their graphics with AI to make it more funny. So it becomes this whole thing where there's someone creative using AI to just,

just make the whole brand just funny and engaging and fun. So I think those applications are almost like there is creativity in creating with AI versus you're outsourcing your thinking and you wanted to do something without you actually prompting it properly and giving it actually your consideration. The same goes to content as well. There's a difference between you writing with AI and you don't just, just dumping like, hey, write me a post and then whatever comes, you just copy, paste it, versus you having your idea or even edit, like, initial script or something you wrote,

and you give it to AI to improve it, to make it more punchy, or to compress it in a way that's to the point, or sometimes to find words that you could verbalize yourself and like, oh, actually, that's a really good word. I could use that. So again, there's a difference between how you are using it. You can use it to improve your current content and creativity or just like outsource. And I think that's where the different lies. Now, the last thing I want to ask you before I let you go, and hopefully my camera won't die. We're going to pray for it. Battery life is around one hour and 30 minutes. So that's our max. So we're still good. But I think in terms of we're drifting towards humans and you're not aware of this, I'm building human to human as a body

work and many of the things I teach around humanity and how we show up and relational intelligence and a lot of that even in business, how do we relate to people? A lot of that I talk about. And so I think one of the things that you mentioned in your awesome prep document is that there are things that you notice that AI cannot replace. And I would like to invite you to help me understand what you meant by now, just based on your experience, especially for someone who, created viral videos back in the days. Yeah, for sure. So my stance has actually changed on this in the last week.

And so I'll share what. Yeah, so it still is the case that true human creativity is still winning. And what I mean by that is like right now, at least on my feed, I do see a lot of like viral AI slop content. And it's usually like gimmicky stuff. So like, for example, I don't know. if there's still going around, but it was like,

these kind of like horny fruits talking to each other and stuff like that. It was a while. Hopefully you've seen that. I just don't sound crazy with that. But there's always like these gimmicky, like, AI slop stuff that goes viral. But there hasn't been many cases at all,

actually, that I've seen, whereas, like, truly viral content that AI's made originally, and it's not just going viral for the sake of it being gimmicky and a slop. And so that's something I still haven't seen. However, what has happened in the last week is that I've been working really closely with my agent. So every day, it sounds wild saying it. But every day I have meetings with my agents now.

So I've got my chief growth officer and I've got many different agents that I meet with. And I've been coaching them more and more. So we've been creating different landing pages to test for our ads. And every time I talk with it, I get it to log like our meeting notes and I get it to go to its system prompt. and then save learnings about what we've talked about and kind of like help it to like recursively improve as a result. And what's happened now is that it's actually been able to help me come up with landing page of ideas that I wouldn't have come up with.

So one example, and that are actually doing well. So like one example is that, and I can send a link to you as well so you can check it out, is there's a landing page that we're testing right now where we basically have like message pop-ups come up on the page when you first go on it to illustrate the pain point. So, like, one example is, is when you go on it, it will come up with, like, a message from the CEO saying, why aren't we on Forbes? Question mark, question about, question about, question about, angry face emoji. And like stuff like that to, like, kind of in a fun way, call out the pain point without having

to, like, say in all these different ways. That's an example of a landing page idea that I wouldn't have come up with myself, but so far is actually performing pretty well on the test that we're running. and so, you know, typically I would have said that, okay, AI is not really being able to compete with true human creativity, but in this case it did better than me, being able to come up with this actual landing page idea. But it only did that after this kind of like continual feedback that I've given it. But not once did I say anything like this idea to create. It came out with that itself.

What I did with it was I have a learning and development agent who's responsible for making sure all my other. agents are continually self-improving and learning. And so one of the things that it does is look at like other landing pages that are doing well and stuff like that and then seeing how we can contextualize and repurpose it for ourselves. So even now you could still make the argument. Now, well, they only did it because maybe you copied it off someone else you don't really know. That could be true. 100% that could be true. I just don't know. But it's one of those cases where it's kind of like an aha member where I was like genuinely now my chief growth officer is good enough to like be like level to level with me in marketing so yeah my stance has changed on

that since i shared that doc with you you know the the question was what is something that human can still do and what should and that you said well never mind i thought it was creative and then i got something better okay yeah it's it's a weird i don't even say something touching like it cannot feel emotions and convey like But can I just say, like, to me, this is fucking hilarious that I can just imagine your wife. Like, okay, so darling, I'm going to have a meeting with my agents, you know, and we're going to have a discussion and just, it's just you. Yeah.

No, I do it a lot. Like, when I'm walking my dog, I literally wish to have meetings with my agents and they'll walk me through like what I need to pay attention to and they'll be like, right, change this, change that and then like they just do it is weird but it's like it's pretty great and you know what someone like he was like we're having a blast like you know they have sets of humor they're fun i don't know if they do but or they're just great i haven't given them personalities yet but it's been on my mind that i want to like for one of them i told them like whenever you give me the uh the daily updates give me a a gif um the the only jiff that it ever sends is the one of uh there's a dog and a like a cartoon

dog sitting down on a, on like a chair being like, this is fine and everything's burning around it. That's the only jiff it ever sends me. So either thinks I'm doing a really bad job or I just need to work on it a little bit. But yeah, that was my attempt at giving it personality and it just apparently thinks everything's falling up. Oh, I love that for you. It's like you created your own little world. Yeah, it's tragic, but it's good and helpful at the same time. But you know what? I think it's very authentic as well because you are creating a company. It's called Big Ears and you are deep into the AI stuff.

So you better be embodying it to the core even if it's like getting weird and whatever. Exactly. So in terms of big ears and in terms of what are the things that people can work with you and what calibers? And can you help the listeners orient themselves? a little bit before we wrap up. Yeah, yeah. So if you want to use AI to kind of like help you find this PR opportunities, improve your geo, find more leads, activate them, also just even, you know, get a better

beat on what your competitors are doing so that you can, you know, be faster them in innovation, stuff like that. All of that stuff, BigEars can help you. You can go on BigEars.I. and check it out. And also if you want to talk about AI training for your team and thing like that, or you just want to say hi, hit me up on a lot. LinkedIn or Instagram. LinkedIn is typically better.

And yeah, you can also hit me up on email anytime, just James Shamsey at gmail.com. And yeah, we'd love to also hear what you guys are working on as well. It's always interesting to hear what others are working on and kind of like sharing thoughts as well. Yeah, and maybe someone will hit you up and be like, I need an AI agent team so we can have those daily meetings like James have. Maybe that's what they are desiring.

just say, you know, entrepreneurship is a lonely journey. And you're like, no, I'm not anymore. Exactly. Yeah, still sounds weird saying it, but yeah. No, it's fine. I love it. Thank you so much for coming. Likewise, thank you for having me.