The Dev is in the Details

Cassandra Vranjkovic from AIQ Nexus on leadership, vulnerability, and curiosity in the age of AI | The Dev is in the Details #16

• Lukasz Lazewski

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► How to lead teams in times of complexity and rapid AI transformation?

In the latest episode of The Dev is in the Details, Cassandra Vranjkovic – a technology and digital transformation leader who helps organisations navigate AI with clarity and purpose  – shares her thoughts on leadership in the AI era.  

We talk about how curiosity, continuous learning, and the ability to ask questions – not just answer them – can help leaders navigate the AI revolution. Cassandra shares proven strategies and tools that support her work on a daily basis, and explains how to tell if your ideas are truly feasible. Besides, we explore the future of robotics and the innovations in manufacturing. 

It’s not about incorporating AI into every aspect of our lives, but rather about doing so with clarity and preserving the human touch in a world dominated by AI hype.  


► Our guest 

Cassandra Vranjkovic is a technology leader, strategic AI advisor, and mentor for tech startups. As a founder of AIQ Nexus, a company focusing on guiding businesses through AI adoption, and a lead consultant at NetMonkeys, a managed service and software provider, she bridges the gap between executive strategy and practical innovation.  


► In today’s episode:

  • Cassandra’s take on learning to say “I don’t know” as a leader
  • Why passive learning is not enough in the case of AI 
  • How to assess what’s really valuable for your business and what’s just buzz  
  • The difference between human-to-human and AI interactions
  • Practical advice for leaders on learning and applying AI to your organization


► Decoding the timeline:

00:00:00 - Embracing vulnerability in the leadership roles

00:05:07 - Cultural impact on learning by failing  

00:06:54 - How different industries approach feedback, conversation, and innovation

00:10:18 - The difference between being curious and completely overwhelmed

00:13:28 - How to filter out the noise

00:17:28 - The importance of collaborative learning and interacting with a prompt

00:20:34 - Human-to-human interaction vs AI interaction

00:24:32 - Self-diagnosing where AI brings real value, not just hype 

00:29:20 - The common reasons for pushing back the projects  

00:32:15 - The importance of understanding the basics

00:40:39 - The role of collaboration in successful AI integration

00:46:01 - Examples of AI implementations that support people on a daily basis

00:51:38 - A look at robotics as a dark horse in AI implementations

00:56:36 - Impact on workforce transformation and the role of business in setting an educational path

01:01:58 - The practical ideas on where to start learning about AI as a leader


► Resources mentioned in the episode:

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The Dev is in the Details is a podcast where we talk about technology, business and their impacts on the world around us.

Do you want to recommend a guest or discuss with us further?

Connect with Lukas on LinkedIn or write to us at podcast@llinformatics.com.

Cassandra:

I mean, what does happen if your navigation fails and you're out at sea? That exit strategy of your workforce, what are you doing to upskill them? Because there'll be other companies out there doing this as well and you will get awash with people. So go talk to the people, understand some small wins you can have on the ground level, and then you'll start freeing up more people to come up with more ideas and to innovate faster.

Lukasz:

We're living in a time when AI evolves daily, teams are dispersed and traditional leadership rules no longer apply. The most powerful traits for leaders today may not be technical, but deeply human. My guest, Cassandra Vranjkovic, is a technology and digital transformation leader who helps organizations navigate AI with clarity and purpose. As the founder of AIQ Nexus and lead consultant at NetMonkeys, she focuses on strategy ethics and enabling teams to use AI to enhance productivity and insight rather than to replace people. Cassandra, I'm really glad to have you with us. Let's jump in.

Cassandra:

Thank you, Lukas, it's a pleasure to be here.

Lukasz:

So you often talk about how AI puts leaders in unfamiliar territory. Can you share what embracing vulnerability looks like in practice, especially for leaders who are used to having answers?

Cassandra:

I think leaders are in a really difficult position right now because the world has changed massively in not even three years and what's been pushing that change has come from a fairly niche industry in itself. Not many people knew what AI was or, you know, really understood what it could do to the workplace. Our experience is more in the blockbuster movies and all the terror things we always saw about what would happen to us and I had practiced this. So I think one of the biggest things and it's the hardest thing to overcome in this is actually anxiety, and it's a real beast to try and overcome in these situations, because I think it's far easier to get to the top of your game than it is actually to stay there, because once you reach that kind of level, you get these kind of views that are put on, you get responsibilities and accountabilities you just inherit from the position you stand in now, and so your people look up to you. People expect you to have the answers, to be able to lead the way, and so I think the biggest thing, the first thing that I often say to people, is actually learn to say I don't know. It sounds like a really simple thing to happen, but actually, when you're sitting there in that meeting room and everyone's sat there looking at you and someone's asked the question, the whole room turns and looks at you and you're so used to having the answer there it is really difficult. So actually, you know, I haven't got a clue, I don't actually know, but I'll go find out. Um, and that's kind of like that's the second half of it. Is that going and finding out? Because we're used to learning? Perhaps we listen to a podcast in the car in the way or two from work? You know, you read an article. Something pops up on your social media, whereas I think we have to start giving learning as much weight as we do doing our day-to-day job. You're actually taking that time, blocking a calendar for two, three hours in the afternoon and intentionally going out and learning something. Um, it's not something you can really do on the fly now. You need to be able to go and talk to people. You need to be able to put yourself in an environment where the conversation is happening and you can learn from what others are saying and all of that. So it's having intention and learning, learning to say I don't know, being absolutely okay with doing that because it is fine, regardless of what you might feel in that moment. When it happens to you. It's perfectly okay to say I don't know and going out to actually learn with intent, giving yourself that space, that capacity to actually take in information.

Cassandra:

And I think the next thing, which is almost closely related, really is around admitting mistakes, and a mistake isn't necessarily a negative if you learn from it. You actually learn more from making errors than you do from being successful. So that product you come out with, that service or that business idea you have, at the end of the day is going to be more sustainable if you've been through the mill with it and got some scars from it, because it's going to be more well thought out than if you'd got it right first time. So failing is a really good way of actually learning as well and actually listening to the feedback you're getting from people. Why did it fail? What's your customers telling you? What are the people you work with telling you? What's that feedback loop saying to you about that and using that information and feeding it back into that loop and then sharing those challenges.

Cassandra:

You're not on your own. So be able to sit there in a meeting, say I don't know, but I'm gonna go find out, and then give yourself the space as well to make mistakes and surround yourself with people where you can have those conversations, share those challenges, come up with ideas. You know, have the stupid ideas, have those ones that don't even seem related to what you're talking about, and building that conversation and building that network around you, I think is really important. So it's kind of a it's a hard thing. It sounds really simple, but it's actually being a human being and being kind of having anxiety and being top of your game. It's actually a really difficult position. That adds more stress and more weight to being in that position for me.

Lukasz:

So do you think there's a cultural impact, like would you consider that in UK it could be completely different than the rest of you? Or in the US, for example, right, the trait and idea of learning by failing and then learning from that is rather encouraged on the other side of the big pond, right? Well, in Europe we consider that a failure is a failure, right, and it's a shameful thing, right, rather than learning and everyone appreciates that someone took an effort. What are your thoughts on that and cultural impact?

Cassandra:

I think definitely there's a cultural impact. I think it's not just from the kind of country or the area you reside in, but also the industry as well. So a lot of high performing teams, especially if you look at the world, where people stand to make an awful lot of money. You know there are some jobs out there where they turn over an awful lot of money for a single employee. They're going to be an awful lot of pressure to make the right decision. You know the their value is broken down in two seconds rather than months. You know they're perhaps not on a quarterly cycle. It might be.

Cassandra:

What did you do today? How much money did you make us today? So all of those kind of feed into it. And it's also due with the workplace as well. I've worked in numerous companies within the UK within the same industry and encountered completely different cultures from within that you know the top-down approach, where leadership know exactly what they're doing. They set the goals for the year and then it's everyone underneath them is there to deliver those goals. And I've also had the flip side, where actually it's the bottom-up approach, where you know they listen to the people on the ground and go okay, what's your experience, what are you struggling with, what have you seen? And actually having that feedback loop come up the chain as well is really useful, and that's the kind of taking the signals from your environment and feeding those into the process of strategy.

Lukasz:

And any particular examples of industries which are on the two opposing sides of the spectrum.

Cassandra:

I mean high level.

Cassandra:

I think kind of the creative industries are much more open to kind of feedback and that conversation.

Cassandra:

When I think we step into like insurance or regulated industries like banking and things like that, that's very everyone's used to living by rules and processes and this is how we do things and that mindset bleeds into a lot as well. But I think it's always nice when I step into the creative industries and those kind of companies that perhaps do artwork or they do beauty and things like that, because it's much more of a collaborative environment. It's much more of a kind of lesser rules and more chatty, so they're used to kind of that back and forth and calling each other out, whereas kind of the, the companies that stand or the industries that stand to make more money are perhaps more competitive, and that's less of that kind of we're in this together to achieve this goal and more of this. How did I get, how did I do better than the other person? How did I win this? More, especially when you're winning deals, it's bled into everyone to win, win, win.

Lukasz:

Sure, and I can get pretty addictive, I can imagine.

Lukasz:

But how do they in those industries, how do they innovate them, you know, in the fintech or insurance?

Cassandra:

It's the from what I've seen them do and I've seen somebody that successfully and not so successfully is giving people the space to play.

Cassandra:

So it comes back to again letting people make mistakes, but giving them a safe environment to bring in new tools, to bring in some, some activities that perhaps you wouldn't do in your everyday life and perhaps don't have a purpose.

Cassandra:

There's a tangible link to actually the work they do, but it's perhaps not driven from the outset of the goals that have been given to them for that quarter and let them have that space. So maybe it's a Friday afternoon project, maybe you give them a whole day or half a day and go. You know what your day-to-day work is, Monday to Thursday, and then on Friday you do your Friday project and that could be something completely different. And that then allows people also to move around in those teams and interact with people they perhaps wouldn't do because it might be the task or the job role that someone's been given. They have a whole bunch of skill sets outside of that or experiences or knowledge or ideas that don't necessarily feed into that role they're currently employed for and that freedom gives them that space to then actually go and explore those and interact with other people and broaden their horizons too fascinating.

Lukasz:

I know some of the tech companies right Google, as we like are famous for giving people 20% of their time to work on a project which can benefit company differently kind of of personal. But I believe Gmail was created this way actually.

Cassandra:

Yeah, I think NoBookLM came from kind of the same kind of concept. It was just a side project, something off the side of someone's desk. They got tasked with it and it just evolved into this thing.

Lukasz:

Pure creativity, without any expectations. How would you call this?

Cassandra:

I'd call it a lot of fun. I've always enjoyed working those kind of those companies that allow that kind of activity. It's the impact it has on the workforce as well, because you're kind of trusting your workforce to actually go do something as well.

Cassandra:

You're not just saying we're gonna manage your time. Monday to Friday these are the hours you'll work, but you kind of hand some of that authority back to your staff and let them inform you, and it helps build that relationship up as well. And it is great to like see people demo things and give them the kudos back and go. Actually you've done a really good job. This was, you know, not what we expected, and it fuels that through all that creativity, imagination.

Lukasz:

Absolutely. It's a sense of freedom right instead of control you give more . Yeah,, brilliant. And because there are so many new tools and developments, like you mentioned right in the las t last few years, um speed and the pace of all the changes are significantly higher than I ever remember right from from the last 20 years in technology. I mean, how do you establish a difference in people being curious and trying different things versus being completely overwhelmed overhelmed by all of these new ideas, new

Lukasz:

tools?

Cassandra:

I think it's a struggle. I don't think the actors have changed. We've always had this issue of news coming at us. It's just been amplified over the last few years. So I think the same role will still sit there and this is kind of how I try and view it. So if you look at before the dot-com boom, we had people driving around and selling VHS tapes out the back of their cars like the bootleg versions of movies, and the actor still exists. The difference is now they just a microphone and social media to and instead of selling VHS tapes, they're selling information and news. So it's kind of weeding out those people and kind of identifying who's really surfaced deep before you start kind of following what people say, because there's a lot of noise at the moment and this is the struggle when there's money to be made out of something, everyone wants to talk about it, everyone wants to look like the expert in it, everyone wants to be kind of amplifying themselves and getting the recognition for it.

Cassandra:

I think the easiest way to not come overwhelmed is not necessarily don't sit and watch the outside world and take it all in. Start from yourself and work outwards. So what are you actually looking for? If you're looking to bring something into your business, what do you actually need to focus on? What's causing you the biggest problems? Where do you want to improve the most? What new product do you actually need to focus on? What's causing you the biggest problems? Where do you want to improve the most? What? What new product do you want to launch and start from there and work outwards? So set your learning goals and set the goals of what you're going to go, look at and say you know what? We spend an extraordinary amount of time doing this one thing. We want to solve this one problem and go out and find something for that.

Cassandra:

If you go, if you start from the outside world and work inwards, everyone's going to want your attention. Everyone's going to be sending you things I get. I mean, I've got over 10,000 unread emails in my inbox at the moment from newsletters and product things I've just given up. My email is now dead to me. I have a few little notifications that go off through someone I know, but other than that, I'm not interested. It's the same, like with my LinkedIn messages the amount of people who I don't know that reach out to me that are trying to sell me something off of my services.

Cassandra:

You know the information is coming out as hard and fast, especially in a world of 24-hour news as well. How quickly do we forget that things have happened? Because the next news stories around, the next new clickbait articles come out of a slightly misrepresented kind of piece of information. It's, it's overwhelming and it's madness, so it almost say they don't start in the outside world. Switch that off for a moment and actually look at what do I need and go out from that route and start looking from that direction and ignore everything else. Nothing else matters. You'll get there eventually when you have your next problem to look at and the next product you want to build, but that can wait till later. You can't do everything and so just kind of draw a barrier around it a little bit and protect yourself.

Lukasz:

And I get that part, but that's very binary.

Lukasz:

How about filtering out who is a real expert from who pretends to be one, because there's so many people who, like I don't know on my LinkedIn. You know, whenever occasionally I have a look at the wall, I see people saying like "I brought that course how to use chat, gpt, and I'm like you know what I mean. I don't know if we need yet another course on that, or would you? Would it be better off to just give people some examples of of inputs, outputs and ideas of what to ask it and let them play themselves? At the end of the day, they, you know, they have to experiment with it and everyone has a different context. So it's really interesting because some of them I call power users who just aspire to be those experts and some could really be experts.

Lukasz:

There are people who do AI for 15, 20 years. They build custom neural nets and all of that LLM, buzz and fast. They downplay it a bit and say look, same technology against the bigger data, but there's still no intelligence or independent thinking. That's on its own in it. Yeah, two questions in one, I guess. First one is how do you filter these people, or should we at all? Maybe it's just like you mentioned what our needs are. And the second one is about the hype part.

Cassandra:

So, the way I kind of do it for myself and filter out the noise is actually I actually speak to other people. I get recommendations from other people who are also doing the same, looking around that I'm doing. So some of the podcasts that I follow, some of the people that I follow and kind of follow, follow the advice off with a pinch of salt, obviously, because they're not involved in your world. They don't have context of what your issue is and, as you just get recommendations from others, if you try and if you googled it or if you typed a keyword into any social media platform, you're going to get hit with thousands and thousands of results. So that's the number one way I do it and you quickly get people going.

Cassandra:

I don't know that's rubbish and you know people are very open to putting something down and that's when they are talking it up. So that's the number one way I would actually do it is speaking to other people, getting their kind of. Who do you follow? Who do you like? Why like them as well? Um, exactly like who who've had followers? I mean, it's very difficult to do this from a standpoint unless you have access to the analytics. But who's had like.

Cassandra:

If someone's suddenly had a thousand new followers on social media in the last three days, I'm always much more cautious of them than I am someone who's got a thousand followers over the last three years and if people have been coming back and actually listening to the information and reusing it, that's much more kind of valuable in my eyes than it is someone who suddenly hit the scene and taken off on all their kind of user engagements and things. But then for the hype, when it is hard, I see some of the headlines that come out sometimes and they're absolutely ridiculous. If you have any knowledge at all about what the underlying story actually is versus the headline, it's difficult. But I think it actually requires effort and I think this is the biggest problem with what we have going on right now is people don't put that effort into actually understanding what's underneath. They read the headline and maybe the intro kind of paragraph and kind of up there and think they understand. But you have to kind of read that article. You have to read an article or see a story on something similar that's talking about the same thing, and how many of those actually kind of agree or get to the actual baseline of what the story is?

Cassandra:

Because we have to remember social media, newspapers, any kind of news outlets. They make money of us by clicking and reading their articles. They're actually their priority isn't telling the truth or giving the full story, and also the people writing these things or giving information perhaps don't know either. That's not their specialism. So how do people make money out of you? You know what are you giving up by interacting with their content. You know that's always a big question for me as well so.

Lukasz:

We're wired to love a good scandal, right?

Cassandra:

Oh, absolutely. Like some of the headlines I've seen recently, it there's like the most boring story ever. They've made it sound like an absolute tragedy.

Lukasz:

Brilliant. So not only passive learning and on the surface learning, as you say, but also that's not enough. So what are the better practices to do it?

Cassandra:

I think you have to come back to how we're built. A lot of our interactions have gone hands-off recently. You can learn online from an online tutor, you can take your news in from online, you can do your shopping online, where you actually limit all these interactions. But humans aren't built that way. We're built to actually interact with other humans and our brains work by building our own neural networks, just like we have in AI, and the way we strengthen those is actually by utilizing the revisiting ideas.

Cassandra:

So if you're going to sit there and watch a YouTube video or read an article and that's kind of the breadth of your method of learning you actually don't get that far because there's no back and forth, there's no exercising your mind in this sense. So it's like it's like walking a path through a grassy field. You walk it once and that's going to disappear. It's the grass is going to bounce back up and that path is going to go away again. If you walk that path every day, suddenly like an actual path is going to develop through the grassy field. So having a conversation with someone, having them challenge your idea, having to build out that idea with someone, it exercises your neural network and actually reinforces those connections.

Cassandra:

So when it comes to, later on implementing an idea or writing down something yourself, those memories are more embedded. So the passive learning literally just allows you to memorize something, whereas having that back and forth, challenging your thinking, having to justify your thinking or why your idea is good, or expanding upon it, actually is actual true learning. And so you don't just repeat what you heard. You actually then can flip it on your head, you can understand why it doesn't work, why it does work, and then you can actually utilize that in different contexts as well. So rather than just repeating the words off a YouTuber, you can actually use that knowledge

Lukasz:

Sure, so like interacting with a prompt, I suppose right as an example in practical example.

Cassandra:

Yeah, you could do it.

Cassandra:

I mean you can do it with AI. I do it quite often when I've got something, I've got a feeling, I've got a good idea, or I know roughly where I'm going with something, but ask the AI to challenge you back, find the problems you know, tell me why I'm wrong, or anything like that, and then you have to almost argue it out with the AI. It's a good way. I mean it doesn't be at all going and sitting in a coffee shop with someone else and having them criticize your idea in any way. But you can use the AI in that sense to actually kind of draw out the problems and you've got to solve them on the fly with it, because obviously it's got a lot of knowledge base itself. It can challenge you in multiple ways and it will come up with things you've never even thought of. So you can say to it if you're coming up with a product for your customer, you work in the medical industry.

Cassandra:

Find the problem's my idea. Now you go. Oh, now you work in retail. Find the problems my idea. And you've got to turn it around and actually get down to the core of your idea, rather than that surface level things.

Lukasz:

I almost feel safer when I do that with an AI than I do it with another human being, right, because the scrutiny of the AI doesn't really hurt my ego. Well, another human being can do that right. So, while I'm all for human-to-human interaction, I wonder if this is getting less and less popular because of that element, because of that safety.

Cassandra:

Absolutely. When it comes back and says you're wrong, it gives you a chance. You can pause, you can stop. There's that pressure if you're in front of someone else to come up with something very quickly and you can walk away if you want. You can walk away for two days from that conversation. You come back. The AI is still going to be there. Your friend's going to have left the coffee shop. They're not going to answer your call next time.

Lukasz:

Yeah, okay, that's interesting, and how there's no way around it. Is there like any ideas or?

Cassandra:

How do you mean?

Lukasz:

Well, because in one way, we're saying it would be good to have a human factor and not drop that, but on the other hand, there is certain emotional load and price to pay when being vulnerable in front of other human being. So there's no really. I don't really immediately see anything how to tackle this. And why wouldn't I, for example, default to always just talking to my you know, prompt friends in my browser?

Cassandra:

No, there's not and it's, and it's kind of almost that well-roundingness that being out with another human being is doing to you because it's, you know you're talking to an eye about a very specific thing and it's challenging you in a very specific way. But being out in an environment, you know you've got that one-to-one person in front of you. You're responsible to them and to the conversation that's happening between you. But you're also out in public like who else is listening to your conversation.

Cassandra:

There's all of those challenges as well, and so it's a different form of exercise for your brain to cope with all the things, and it's both a negative and a positive, because you might shut down in that situation and kind of want to escape faster than sitting and talking to your AI, so you might not get as deep into the idea. There's always positives and negatives to every situation, so it's like a different form of exercise for your brain being out there in the real world.

Lukasz:

Yeah, and one thing that came to my mind now is that AI is always pleasing. So even if it criticizes, it's not really honest or direct, while a friend will be. They'll say "Lukasz maybe give up on this already. This is your fifth attempt at that." You know. Well AI will be like "oh, this is brilliant, you just have to think about this and that and suddenly I don't know. Compliance issues from AI standpoint are not so hard to beat, while human being will tell you listen, this is years of I don't know legal paperwork. I love not to get that sorted for your medical device.

Cassandra:

Yeah, and I think that's where the responsibility needs to sit with us. We can't forget AI's a tool. So we are in control. So, yeah, it's quite frustrating. I kind of have to tell my AI to be like more strict with me, be more blunt with me, because I don't want someone to tell me, sit there and tell me I'm great the whole time so I'm not going to get anywhere, but we're in control of that.

Lukasz:

Exactly. I've seen those cases where people were using I don't know which one it was, doesn't matter which of the providers and tools, to kind of self-diagnose for psychiatric challenges and at the end the tool was so reassuring that they told them i"t's fine to not care for other people, it's fine to do this you know, everyone does that every now and then and it was really scary to see what kind of conclusions it led people to. It's basically reinforced their. You know, maybe not evilness just yet, but it could lead to evilness.

Cassandra:

Oh, you can see how it escalates, can't you?

Lukasz:

Exactly, exactly. So I was like really shocked and and there's a reason why doctor will says you know, stop right. This is like crossing cultural boundaries or something when you tell them. But then again, probably people are way more open to the AI before they're open to their therapists, for the same reason as we just talked about. So, changing the topic a bit, there is a tremendous pressure now on businesses and business leaders to be AI- ready, to be AI- adopted companies and startups and maybe even entire industries. I don't completely get that from a perspective of average on-the-street vendor selling bread or bakeries or places where we go to buy our meatloaf. So what are your thoughts on that and how, as individuals and organizations, we can stay grounded in that strategic and ethical decision making process on where does it make sense, where does it bring real value, versus just a buzz and fuss for investors and being trendy?

Cassandra:

Yeah. So this is a question that I hit in every business I go into. That's the question of why are we doing things? So what I have myself is a really basic Excel template where it's actually a calculator and it's got around 15 questions in it, all from things like: how many people does this impact? Does it impact one person, does it impact the whole company, right through to how difficult is this for people to pick up.

Cassandra:

You know it may have an amazing impact on your business, but if no one can get to grips with it, then you're in a bit of trouble and there's several areas it steps through around cost reduction, around efficiency gains, and actually then score out five and you then say can they say each question one to five? Very simply, because we don't know the actual impact it's going to have until we do it, five being brilliant, one being not very good, and at the end of that that actually gives me kind of a final score on it. To say kind of this is a high score, this is a low scored one. And it really helps me because when you go into a business, you rarely just have one thing you're trying to do. It's 50 of them. Everyone has thing you're trying to do it's. You know there's 50 of them. Everyone has an idea. Everyone's got the best idea as well, and it's tend to be whoever shouts loudest gets their project done. So this allows me then to go through and everyone gets asked the same questions. Everyone kind of has the same scale they rate out of and then at the end of it I can say well, actually you know what this idea here, although immensely boring, it's actually scoring very high for how much impact it will have across your business, and it then allows them to focus on which ones should actually take priority and which ones should get the resource and the time and the money to actually be delivered, because some of them sound fantastic, because they've come up with this really sexy idea and it utilizes all this new technology, and the minute you break it down, it's not actually going to have any impact. It's just exciting, and it is a struggle not to get distracted by all of those ones that kind of sound amazing. Um, and it's really simple.

Cassandra:

Calculated is what I use and just rank them all the same way. There may be ones that impact only one person versus the whole company, but maybe it transforms their role completely and it's low cost, in which case then yeah, that's great. You know, why shouldn't you do it? Um, if it's quick, it's cheap and it's going to change the world, that's fantastic. But that's kind of how I do it with them. There's probably more ways of doing it, but I like that essence of being able to look at the total score, and give me an indicator of you know very easily, where should I be focusing?

Cassandra:

But also going back to people and allowing that two-way communication of if someone that really does believe like their idea is really good and they really do want it, to be able to pinpoint in each of those kind of questions and go actually it's scored really low here. You know, perhaps you need to look at. You know maybe it's, you know the cost of it's actually too high at the moment. You know it could be something that in a year's time is really cheap. Again, as the cost comes down, we can revisit it.

Cassandra:

Or, if you need a different approach to it, but you can break it. Rather than approaching it as the whole idea and kind of this big thing you've got to tackle, break it down into the components of it and say, actually you know what. It's too difficult to use means you want a simpler way of implementing it, or it costs you much money. You need to find a cheaper implementation. Or maybe simply you know what it doesn't really help anyone. You know it's, it's exciting, but it doesn't really do a lot, and you can then actually focus in on those bits that will add more value to it. Then someone can go away and they can come back and go. You know what I've re-imagined the way I'm going to do this. Still the same idea, but it's done differently. And now look at the score I'm getting. It just gives people that mechanism to work with that feedback loop.

Lukasz:

Would it be, would you be okay with uh sharing this self-diagnosis uh excel with our audience ? afterwards

Cassandra:

Not exciting or pretty, it is very basic.

Lukasz:

I think it's a really cool methodology that you, you know, put together. Why not to, why not to share it? You know people could self-diagnose as well in their businesses or their day-to-day activities. That would be brilliant. Thank you, super. And what are the most common reasons for pushing back when you're having those, you know, diagnosed sessions and then discussions within the team?

Cassandra:

Usually I mean predominantly when you look at kind of when you're into a business. I hold workshops. Quite often I will have kind of 10 to 15 people in a room and you know I like that free form conversation when anyone can throw up an idea at any point and we can have a full discussion about it, of why it works and why it doesn't. And the three common kind of business objectives I get given at the start are like increase efficiency, reduce cost and deliver more to our clients. And I think you have to go one step further than that and this comes out later in the discussion but it's around the environment you create for people.

Cassandra:

Um, often an idea can can look quite good on paper, but I think you have to take it one step further when you start getting deeper into the implementation process. So, for example, I've seen lots of kind of financial systems, ERPs, all of those guys at the moment that are bringing in co-pilots. They're bringing AI into the system to simplify the role. And if you actually look at what the role was before on the kind of business metrics, yes, it increases efficiency. It reduces the time to market. On these things they go from this is a week-long job and we've reduced it to three hours. Isn't this amazing? And on paper looks fantastic, but if you actually look at the experience of the user, they've gone from analyzing data to solving problems, doing investigations, to what now the experience is. The AI does. It gives a summary, and then they press okay. And then it was the next thing, and the AI does it. They read a summary and they click okay, and we call it human in the loop. But actually what have you reduced that person's role to someone who's used to being involved in the information, talking to people interacting as part of their job, you know that environment you've created for them is boring, it's dull. They don't utilize any of their skills, their knowledge or the experience and you've reduced their role to button, button pushing, as we saw with, like cookie notifications and things. People very quickly, just it pops up and out of habit, you click okay and you move on with your life. You know you're going to start bringing that same environment into that work, and then you get employees who are disengaged, they leave, they get bored, they start making mistakes.

Cassandra:

hey the ideas I think have to go beyond once. You can prioritize on quite a high level and what you should focus on, because the outcome is important. How much how much impact will it have on your business is incredibly important. But on that next stage, I think you have to be very careful on how you implement and that's where I actually see a lot of pushback is actually later down the line and you have to say actually, what's experience like? What environment are you creating? What are you doing to your team? Because people don't want to be bought, they want to be your personal productivity is a huge thing, but you don't want to take it so far that you're bored and you've got nothing really left to do.

Lukasz:

our mean my question for, in this scenario just described, wouldn't be better to since the job is now downgraded to simply just pushing the button, to hire someone much cheaper and simpler, right to just push the button, and not necessarily to replace the individual who was doing the entire workflow before, but to give them a higher oversight in the structure of now, multiple button pushers instead of one person doing a single work stream during a work week and, I don't know, reviewing a handful of companies.

Lukasz:

Now they can review hundreds of thousands of companies in the week with the same person at the top, knowing all the process, knowing all the details, being able to deep dive and pick the pearls, even after the AI and after all the manual labor of button clicking. What do you think about that? Because you immediately are of a higher scale, right, bigger scale. Individual kind of gets promoted, has a bigger data set. It can still be exciting and I don't know, maybe we don't even need button pushers, to be honest, right, maybe it's just one big button and he puts that, and now he has hundred thousands of these little let's call them AI workers who execute all of these in parallel, right, and then, based on certain criteria and querying the data, the analyst can still fetch the pearls of the data that he wouldn't be able to do and find in the past in that amount of time, in that pace.

Cassandra:

Yeah, I think this is definitely around the augmentation of people, rather than taking them away from the process, because you still need that knowledge and experience to know if something's gone wrong, because why it's gone wrong. And I think if you remove that person from the process entirely and just had button pushers come in, for example, they won't necessarily spot something that's wrong when it goes wrong. And also, if it happens, how do they troubleshoot? Because you can't really get under the hood of AI too well. You have to have that knowledge and learning experience to be able to challenge what is essentially your thinking underneath.

Cassandra:

And I think this is the way we kind of have to view how workplaces are going to change in this kind of orchestration role rather than the doing role. And I actually had a conversation about this this morning where someone was telling me they're very senior in a company and they were saying about how they no longer try and figure out how they're going to do the job. The turn they think in is how do I craft this prompt in order to get the AI to do it? That's now the thought process they go through. It's not where do I get this spreadsheet from or where does this data and what do I do that with? It's is that how do I convey what I need to happen to the AI? How do I structure what I have, the information I have and my instructions in a way that AI is going to understand. Like that's the thought process that people are starting to go through and I don't think we're even realizing it's happening that much.

Cassandra:

You know we have these big papers that come out to talk about these changes in the way we collaborate and how workforces will change structure, but we're starting to do it on an everyday basis. I do it with mine now. You know I get through a document, a long document. You know, am I going to sit and read 40 pages? No, I don't. I put it into my AI and I have a conversation my age, I pull out as much as I possibly can from it about what I'm interested in. So I think you do, you bring out, you bring this AI in and rather than having that button pusher that's just going to sit there and push things, you can give them more responsibility. You can expand the horizons and you know, maybe they had capacity at one point to do the set number of jobs, but now they can do that in, you know, a fifth of the time. What else can they do? What other skill sets do they have? What else can you expand one?

Lukasz:

Or interests, right, exactly. I don't get it. And there's another aspect of it, the downside which I see, which is, you know what would be the good comparison in the past, when human beings were sailing, they would use stars for navigation, stars and maps, right. Eventually, we ended up inventing GPS and navigational computers and semi-autopilots for the boats as well. Which means, if now current generation starts sailing and just learns how autopilot works and GPS to say, say, I want to go from this point to that point, shortest route or whatever safest route, what happens when it fails because we are losing the basics? It's almost like I don't need to know math. I'll ask AI what the solution for this equation is. Right, what's the remedy for this? That you still want people to understand the basics?

Cassandra:

I think your analogy is quite on point there, because I mean, what does happen if your navigation fails and you're out at sea? Like what actually do you do? Because you don't just float around and hope for the best. We have now technology. Like I say technology, you get a flare out and you shoot a flare up the sky and people other people supporting services understand that you're in trouble and they come and help you in a full situation. Hopefully you don't just end up floating in the middle of the Atlantic for too long or you know there's people that pass by and things.

Cassandra:

I think that's perhaps a way we need to start looking at it is the way the world is moving. I don't think we're going to have a choice with people who are growing up now aren't going to have the same experiences and hold the same knowledge as us, but building those services around them. So those of us who do hold the knowledge, creating that environment for them, they can turn to us and ask for help. They can shoot that flare into the sky and say something is going wrong here. So maybe a consultancy start to change and, rather than coming and helping you, you know, decide how you're going to move forward. They also provide a kind of safety net for you as well, on expertise. When something does happen coming to you, or maybe it's an area within your business, maybe that's where your, your supervisors and team leaders start to come in. Those people hire up the business and, rather than having people who just manage teams, their role changes to actually, you know, they provide that supporting service to help elevate people when they are struggling.

Cassandra:

I think we can't really look at things in isolation and say, you know, we're going to forget this knowledge, because we don't forget knowledge. We still make bread, we still have bakers who bake from scratch. You know, I made caramel this weekend from when I was making a pie. You know, we can, we have the informational sources to find it out. So you know, just drop off into darkness. But in the same vein, I think we have to make the conscious effort to make sure those things are there, those safety nets do exist. I think if we just kind of hope for the best and we hadn't patched that flare or hadn't created a service of the Coast Guard, you would be floating out of the Atlantic forever. So I think we need to approach how the environment is laid out to support these things.

Lukasz:

I like that. So in that analogy I brought up, if I understood you correctly, you mean, instead of investing in a backward knowledge, in knowledge of the past of an individual as well, when generations move forward, we build next level of support nets such as, in my example, coast guards, patrols, predefined routes that ship are taking so there's other traffic that can pick us up, instead of saying, like you know what, no matter what happens, you will still be able to navigate, or put a little sail up and then you navigate by. You know you use wind to propel your ship or whatever else that as an individual, I'm ready for every scenario. Instead, the entire system is ready for any scenario of any individual.

Cassandra:

Exactly we're used to doing it without physical safety.

Cassandra:

You almost need the same approach to knowledge and services. You know, when we're going to physically get harmed, we're very quick to spin up a service that's going to save us. You know, we have medical professionals, fire service, coast guard, we have all those things and we can do the same with knowledge and expertise. You know, maybe this is where companies start partnering perhaps more with, maybe, universities or research hubs and bring in that kind of. I know that large scale companies may even be able to afford to kind of carve out a division for research and knowledge and keep hold of that, like you have your enterprise learning departments and things that exist within these companies. At least it perhaps that just expands and gets more capabilities and more skill sets brought into it.

Lukasz:

And to even run the simulations. Right. Universities could just specialize in running exit scenarios for sailors, airplanes, whatever. Interesting. That's an interesting thought. Okay, this entire thing requires a huge amount of collaboration and you know same direction, course on the same direction. How do you help, or what's your experience, in breaking down silos and working across different skill sets, and especially when the new tool can also be threatening right to individuals or entire teams?

Cassandra:

I think, because the whole point about it being threatening to teams and people, it's always something I think I overreact slightly to, because I was trying to drum down the point that the technology is not doing anything. You know, the internet didn't do anything to us. Dotcom boom didn't actually cause anything. It's leadership, it's leadership decisions that do these things. So it's very much in the hands of business owners and leaderships of areas to actually control this as well. So we're very much kind of, I think, things like you've got corporate structures now, so you've got your department, you've got your team, you've got, you know, all these business silos that are happening. There are practices I've seen with varying success, depending on how they're implemented.

Cassandra:

But you have things like there's a concept of squads, which is where you still have your, your structures out there, where you have your engineering team, you have your, your data analysts, but then you build a squad which they have a responsibility maybe it's a particular product or a business service and they all work together and it brings in the specific skill sets from each area. But they work as a team and they operate as a team, so they're sharing knowledge, they're collaborating and working day-to-day, day-to-day together, like typically departments would do. That works, I say, depends on how well the culture handles that, because you have two reporting lines effectively then like almost like a project reporting line, because you have a responsibility, but then you also have the reporting line of the engineering team and the data analyst team. So you also become having two managers which is sometimes difficult to navigate of who do you listen to and who do you follow. And then on the other extreme level I've actually seen is where large companies have actually taken on a gig economy and rather than people having job titles or responsibilities, they have skill sets.

Cassandra:

So you literally go into the company directory and, rather than searching for the engineering team, you type in someone you need a php developer or you need a data analyst who's used to working with in the beauty industry, and you pull up people by that way and then start grouping people together who work well together and their skill sets complement each other and start building teams in that fashion, depending on what it is you actually need to do.

Cassandra:

So it is very kind of you can go from very rigid and I think that then causes a little bit of siloness, that's the word, into the learning and collaborating, or you can get people to mix and match and you know these, these squads or this gig economy doesn't have a fixed structure. So when the strategy changes or the project changes, they all mix up again and they meet a whole load of other people and I like speed dating in the project world. So they kind of meet new personalities, they meet new skill sets and that's always interesting. But then to me nothing really beats getting people into a room, taking them out of their work day, get everyone into a room and throw a discussion at them and see what happens as well.

Lukasz:

I agree, but I expect that because business owners and shareholders obviously have slightly different incentives than workforce people. So there could be it could mean a death of full-time employment, right? Because people would just be in that pool of specialists with specific skill sets and they would be brought up for a few weeks to a couple of months for a project on a project-on-project basis and literally everyone would be a freelancer like.

Cassandra:

I think, I'm not sure I agree, to be honest with you, because I think I can't understand where you're coming from. But I think if you know you run a business, you run, you have a product set, you have a service set. You know you have something you're delivering to your clients. If you only do something once and then get rid of that team that did it, how are you innovating because that doesn't even delivered once and then are you going to just assume that project is the end of the road and that's it, or are you going to build and innovate on it? And plus, also, you know those skill sets that people, people don't just hold one skill set, they hold multiple. So maybe you know I've run into people in my work life where they do.

Cassandra:

You know, I used to work with someone who was a personal assistant but it turns out she was actually a career marketer but she just didn't do it anymore. But she was very, very high up in the marketing world and had an awful lot of experience. But because she kind of came into the PA world after that, no one really knew because no one got to know her. They just got to know her job title. So I think people have multiple skill sets that then will get reused across the business and they also take that again back to the knowledge point. They then take that knowledge with them as well.

Lukasz:

Yeah, that's true.

Cassandra:

I think that's sometimes where businesses struggle is if they replace people with the AI. Only so much of your business knowledge is actually written down. Those relationships with your clients and things like that aren't existing in the AI. So I kind of don't agree with you there, I'm afraid.

Lukasz:

Fair enough.

Cassandra:

I think in the real world it will be different.

Lukasz:

I like that. I mean. History also shows that what you're saying is correct, right. Even during industrialization, certain jobs got squished, right. They no longer were like manufacturing, right, like it's all gone automatic now, but there's more specializations and more technologies in manufacturing that require still more people to do it, even if there is machines and you know software to do that too. All right. And what are your favorite examples, actual examples of AI implementations and deployments that support people on a day-to-day basis?

Cassandra:

I think my most favorite one is actually the least interesting. I've been part of large-scale projects that sound, on the surface, incredibly intelligent and complicated, but there's a few little AI apps out there now that I use every day and make a huge difference. So, for example, like Gamma AI, which they make presentations and documentation for you. The amount of time that has actually saved me and actually all my documentation actually looks so much better now because it, you know, I write brain dump into the AI, like just waffle at it basically, and it will produce this perfect presentation with images. It's all correctly formatted. You know, it is far better of a job than I could ever do and it's done in a minute.

Cassandra:

So as soon as I get go, it's just running through it and I spend my time perhaps updating the images if I want a different stylization on it or like a slightly different image on it, or perhaps sometimes changing the layout of the text, so I can now have an ability to convey the information I need to convey in a much better, much more organized fashion.

Cassandra:

So people are benefiting around me as well, because, rather than having something I've put together which, you know, the sentence structure isn't quite correct or you know the flow of information doesn't quite go properly. I can then take something that's kind of my head waffle and put it out to other people who can then reuse it within my business. So, for example, I've got things around practices on how we work. You know that when we go into, when a client asks for this particular thing, you know as far as the client's concerned, they're asking for this one small thing, but actually what they're asking for is this whole amount of work in the background, and so I've documented all of that, and documentation is something I hate doing. It is.

Cassandra:

It's not interesting, but I've managed to from transcripts I hold from previous presentations, all those things. I put all that information into there and say I need a document and I need it for this intention. And it will then go through and do all of it for me and laid out in such an easy to read way so the next time someone gets that client question, come in, they can flick that up and actually work through it and be like, right, this is great, what we need to do. I'm gonna say it does it in less than a minute. The time is spent with me getting the knowledge out of myself or collecting it together and it's done and it's beautifully. It looks beautiful, looks professional, that's like. My most favorite things are the most boring tools out there

Lukasz:

Super, and the output is pdf or powerpoint?

Cassandra:

Power point, pdf, it goes to Google Docs, you can create a website on there. You know, there's all these different formats. It's all just about formatting it into a framework that it already has.

Cassandra:

All the key AIs in there for your image generation, and they've obviously done a lot of work in the background, because all the well, majority of the AI imagery comes out with perfect wording on it, which is something I've not been able to get many of the tools to do independently, so it's really some work in the back end, which of course makes it look really good as well, because, people, how did you do that? I'm like, wow, it's a secret,

Lukasz:

So no putting that one into the episodes notes. Then okay, super any others?

Cassandra:

I think I mainly sit between that and NotebookLLM.

Cassandra:

Um, I actually love the night that feature in NotebookLLM. I'm a massive geek and I love learning and being able to take all, take all the information I go across, I find articles, I find youtube videos, I find all these different sources of information and put them into one notebook and then being able to one converse with it is really helpful.

Cassandra:

Because when I don't completely understand something I can push it a bit further to kind of normally simplify the language, but being able to explode it then into a mind map then basically breaks it down by subject and category, and being able then to explode those. So once I feel comfortable, actually kind of at that level understanding it, I can go into more and more detail. And the audio overviews are great. I've spent a lot of time actually formatting a prompt, so normally you get out of it kind of a 18 to 25 minute audio overview out of the standard issue. I've managed to create myself a prompt where I'm now getting kind of 90 minute podcasts out of it, so I can then actually sit and actually listen in detail to actually what's going on and the fact you can interrupt. You've now got a beta version where you actually interrupt the podcast and you come on as a as a caller in the, in the show and you can ask them to revisit a topic and like so you can actually be interactive with it. And the amount of learning I've done is so much more than sitting there and reading, like through a textbook or in the traditional sense or sitting online in a classroom with a professor, so being able to revisit the topic over and over again, like the AI never gets tired of me, like no matter how many times I get it wrong, it will keep re-explaining to me. Um, so I sit majority of time like with NotebookLLM in my learning world of trying to throw things in. Especially with so much information out there, there's something new comes out as well. You can put it in and understand how this new information now impacts the previous information you had as things change, because you can build a timeline in there as well, so you can start to see how those changes happened over time and actually what journey this technology went through, which helps.

Lukasz:

I'll ask you later for links to these guys, to these tools, because this sounds fantastic. I definitely want to share those in notes for this episode. It almost feels like everything we talk about, the tools even that you mentioned. They are very useful for people who work with computers, who work in the office, who work in the services, who work in consulting. But how about manufacturing? When do you think robotics will catch up with the current wave of AI at the next level?

Cassandra:

I love this subject because it's one thing I've never got to work with. I have managed to get someone to buy a small robot that now lives in our office as our office pet and it's fully enabled and you can talk to it and get it to dance and things like it's my favorite thing.

Cassandra:

Um, I think the world of robotics is hugely interesting because I think it's also the dark horse. Um, if you look at the what's been happening over the last year, I think it's absolutely insane. I was reading the other day that costs have gone down 30% in 12 months alone, which is a huge drop when it comes to production of these robots. And if you look, you know you've got figure making the, that they've got a manufacturing plant that now makes the robots, so robots are making robots. You know you've now got China that have brought out a robot that can change its own battery, and so you've got that continuous working that's going to be happening. And also, it's kind of scary, but the old old Star Trek kind of fans around the voyager. They've basically built the borg. This has now come to life. So you've got, the latest version of figures come out and it's on a single neural network called fig, called helix. So they are running in a shared mindset, essentially all running off the same knowledge. So when they train a robot, they're not just training a robot, they're training all robots forever. So if you work in a warehouse, for example, and you hire yourself 10 robots to do the jobs. You've got 10 different tasks that are being done. You've not got 10 robots that can do 10 tasks you in one each. You've got robots that will forever be able to do all the tasks you have, and so if you get, then get your 11th, 12th robot that comes in. They already have that knowledge and how to do those all those 10 tasks, which means your workforce. You could even just bring in one robot and have it work systematically around your manufacturing plant or wherever, and learning one task at a time, and then every robot you bring it past that point is going to hold all that knowledge, which I can't even really begin to comprehend what that actually means in terms of how hard that's going to explode once it hits a price point that's relative for retail. You've got China that are producing robots that are in people's homes and kind of. They're much more accepting in the East around, kind of having robots in society, which I think is one of the huge problems, but they're producing them at like $16,000. You can get yourself a robot, but then you've got a figure that are coming out. I think they're about £120,000 at the moment. But they've been working very closely with BMW in their manufacturing plant and they've been learning how to put together cars, how to walk around the plant, because you've got to think people are still there so they have to go to navigate not just around kind of these machines and where they pick things up and put them down, but also these erratic objects that are running around them and and leaving pallets out perhaps in the way and things like that. So there's a lot more they need to learn. But then figure of also, I think kind of probably about five months ago now started an experiment with putting 400 of these robots into people's homes. So there was a video released earlier on that I saw where robots learning to do the laundry it's getting, the washing it's putting into the washing machine. Now every robot on that network now knows how to do laundry and it's just insane.

Cassandra:

And I think the biggest challenge, attention if us is going to be in society, because you know, robots are kind of harder to ignore. With AI, it's kind of this magical thing that no one really sees, whereas robots are going to be much more physically present in our lives. And how will that impact us? Um, but in the business world kind of, you know, what do you need to make that actually come to life so you can start to utilize these. You are going to have an environment, especially initially, where you might have one or two robots in there that are going to be doing tasks.

Cassandra:

But how do they interact with people? How well are your people actually going to take it? What other obstacles do your people create for these robots? How do you lay out your warehouse so a robot can actually navigate around in the most efficient manner? Where are they most helpful? All these sorts of things, and also like the running costs. Yeah, it's great. Okay, you know a robot can run 24 7. You know it doesn't have to take breaks, it doesn't have to be fed, but it does consume electricity. So an outside influence is going to be is what's the price of electricity and our services? That's going to be a massive influence, because if that suddenly spikes, if you've got a robot-enabled workforce running around you and suddenly the cost of electricity goes through the roof, what's that going to do for your business? Do you suddenly bring in as many people as you possibly can? You've got to have these thoughts in place.

Lukasz:

Yeah, I mean, on one hand, this could be mitigated because factories could start building solar panels and windmills, whatever else, to be more independent, right, even off the grid. But I'm wondering about something else, about the argument. We just saw the conversation part we mentioned where we agreed that, workforce transformation means that people have another job. Right, and I think this is way more likely for someone who works with computers already than, for example, for people who are doing physical work in the factories or warehouses these days. And I wonder.

Lukasz:

So here's like a like 100% example, which I don't know how to evaluate as a progression in the career for humans taxi drivers and truck drivers. Right, like, self-driving cars, we already have them, it's, there's no even need for a debate. Right, they work. It's now just legislation and scope in which they're being deployed, because they're just deployed at singular cities or singular areas in the US, or maybe somewhere in designated areas in Europe, but eventually, during our lifetime, we'll see every single cab and every single truck converted to a self-driving vehicle. So the question is what all the drivers are going to do? Right, that's one example.

Lukasz:

Another is the same with the factories, like if today we have hundreds or maybe even thousands of people somewhere, eventually it's just going to be less and less and down to zero. Right, because some you won't even need that much electricity, I would argue. Because you need to heat the factory, so people are not freezing and you need lights because they need to see. Robots don't need to see. Right, the sensors will see through infrared in the night, so the factories could be just those big, dark, black buildings.

Cassandra:

Rather depressing film.

Lukasz:

Yeah, exactly. They're constantly running 24 hours right. No sleep, no food. Food could still be more expensive to grow and deliver than actual electricity for the robots, and this is even without any S-based scenarios, like you know, robots going rogue or anything like that. So I think the impact on society is going to be unbelievable.

Cassandra:

It could be absolutely huge. And this goes this kind of relates back to kind of the industrial revolution we saw as well, because there were people then who you know. You say they lost their jobs, they lost their businesses because they didn't innovate. I think this is kind of it's an employer's responsibility as well as a personal responsibility around.

Cassandra:

This is something I also talk to customers about is around that period of time when you actually are, you have more workforce than you actually need and my clients do decide to take that route of reducing workforce, and something I always push for is that exit strategy of your workforce. You know what are you doing to upskill them, because there'll be other companies out there doing this as well and you will get a wash with people on the lower level skill sets that are going out all competing for the same jobs that are existing at the moment. And it's actually that kind of that process you go through of making people redundant. You don't just give them the statutory redundancy and say you know, good luck. You set them through an educational path, helps them learn, maybe, like with people within the factories who you know that a robot might start doing their role. Robots are going to need engineers. They're going to need people that fix them.

Cassandra:

They're going to need people that retrieve them out of situations and things like that there is initially how quick it's going.

Cassandra:

Even then, if you look back at the industrial revolution and you kind of say, like loads of people lost their jobs because of the invention of electricity, how many jobs now exist because of the invention of electricity? Electricians alone are one of them. But I think there's going to be lots of roles that start cropping up. I mean, I don't know about you, but I asked this question to some people, when they bring this topic up is you know, is this what you wanted to do when you were a child? Did you even know the job you're doing now existed? Did it exist? Um, so kind of these roles will start to expand and start to pop off out of nowhere. But I don't think in reality, all these people are just going to lose their jobs and lose their roles.

Cassandra:

I think if, as long as employers are helping them, being a good company and this kind of ethics comes in as well is helping these people grow their skill sets, and helping people kind of expand their knowledge base as well. You know people have more skills than we kind of assign to a job role, like I said earlier on. So maybe there's some people you've got in your warehouse that are actually really good at relationship management. You know, maybe they know your business, they know your products, they understand what turnaround times they could possibly get out the door. They know your business really well. So actually, maybe you start putting them in front of customers. Maybe they just need coaching on the way they speak to people. You know things like that so you can start to reuse that knowledge and that experience people have. So, yeah, I'm hopeful.

Lukasz:

No, no, no, I think it's going to be a positive outcome either way. I'm an optimist in that regard, but I'm just wondering if this is going to be, you know, the transformative moment where we will all be on constant holidays because the machines will continue working for us.

Cassandra:

Oh, that's the kind of the goal, isn't it?

Lukasz:

Yeah.

Cassandra:

Yeah, exactly and I think it's not just kind of a workforce thing. Obviously. It's a governmental thing as well that needs to come into. It is a far bigger problem than we can ever gain to on this show.

Lukasz:

Absolutely t So, my last topic is, tell us a little bit more about uh ideas where to start for to leaders who are impacted by this and they just, they just feel lost and they don't know where. You know how to start catching up, what, what's the best point where they could start learning? Start applying some of this in practical terms to their organizations, no matter what these organizations are.

Cassandra:

I think this goes back a little bit back to what the discussion we were having earlier on is, and I think actually the best advice I have is for leaders to actually go talk to people on the ground level, understand what their struggles are. They do the job day in, day out. They interact with your customers. They interact with your product, they do your services. You know what are the things they would change. I mean, we've all got those things in our job role. We go like this is 2025, why am I still doing this? Well, this is, you know, not valuable use of my time.

Cassandra:

Dig out all of those things, because if you start approaching on a ground level and start solving those problems, you start giving the workforce more capacity to actually start dreaming bigger and using their imagination. They're less tired, they've got less mental load on them, so they can actually have the energy to think as well which is a really big thing to actually come up with these ideas. So I'd actually say go have a conversation, whether it's be you take some key people out for a coffee or you announce an all staff meeting that you want ideas, but develop a way of people be able to surface these ideas to you. It may be like a group chat in your company messenger where people can just throw ideas in or something, but start, I see it best, come from the bottom up and start servicing those smaller ideas, because when you also start, you don't want to go through the big projects first. They kind of have the most risk and the most complex. So start with a few small projects on the bottom, some simple ones that everyone understands what needs to happen, what the concept is, and then work through it that way, because what you don't want to do is approach something big that no one understands or has an idea how to do, as well as using new technology, because you're just making it harder on yourself than necessary at that point. So go talk to the people, understand some small wins you can have on the ground level and then you'll start freeing up more people to come up with more ideas and to innovate faster. So it's a journey. It's not something you can do overnight and people also appreciate it. They'll appreciate being listened to. If you feel heard and feel respected, they'll start bringing more things to you.

Lukasz:

Oh, yeah, I agree, and I like the idea of co-production, basically in that term.

Lukasz:

Cass, thank you for bringing clarity and humanity to this topic that's often filled with buzzwords. You have reminded us that the leadership in the AI era isn't about having every answer, but more about staying curious, creating space for real learning and knowing when to ask better questions instead of pretending to know it all. To our listeners, thanks for tuning in to Dev is in the Details. If you found today's episode useful, share with a colleague or a friend navigating the change, and if your team is facing complexity or leadership is being stretched by rapid transformation, we're here to help. Until next time. Thank you, Cass.

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Lukasz Lazewski

Host
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Pedro Paranhos

Co-host