AI and Workplace Culture 2:2

Lars Nielsen (00:00.888) Hello everybody and welcome to Cultures from Hell. This is the second episode of AI in Workplace Cultures. So just for our listeners out there, if you haven't listened to the first episode, please pause now, listen to last week's episode and come back to this one. Joining me like last time is Bilal Guda and Paulina, my very beautiful co-host and co-founder of College of Culture Foundation. Welcome both back to the second episode of this extremely broad and so interesting topic. Belal Gouda (00:45.96) Thank you, Lars. It was a pleasure. Paulina (00:47.622) Thank you, Lars. Lars Nielsen (00:48.15) Okay, let's just dive into it. Paulina. And again, like everybody just go back and listen to the last episode before you listen to this one, because last week we heard about Bilal's story. And this story shows how fear of losing your job to AI can drive people to overperform. How do you replace fear-based motivation with something healthier? Paulina (01:17.84) Yeah. So maybe first of all, because when you say it like this, fear of losing your job can drive you to overperform that might be used as a technique, to implementing that exactly that fear of people, because you want people to overperform. and for me, just to go back here, fear is just never a good motivator. Never, no matter what the fear is about, So, and in this context, especially, and I think this is something that is not only relevant for people working in AI first companies, but it is actually a broad anxiety that I face everywhere when I talk to people at the moment. So this, this vague anxiety about AI taking our jobs is just all around us. Bilal is nodding furiously at this point. And so I would clearly say it is super critical to shift the focus from replacement to reinforcement. So it should not be about utilizing AI to replace humans. And Bilal, please correct me if you see this differently, but from what I heard, from what I understood from your story, this is also something that you very much encourage rather utilize AI in combination with human creativity and human empathy to create something that is actually better than either one on its own. So we should be using AI to double down on what humans can only humans can do, which is inside, which is judgment, which is the emotional intelligence, and then use the healthier message that AI is to go deeper and not just faster. And obviously, as always, don't just say it. I need and expect leaders to also model that. So don't just say AI is your co-pilot. Actually show what a good co-pilot partnership between a human and the tool AI should look like. Lars Nielsen (03:38.614) Yeah. And so I have a follow-up question to this one. I'm actually going to shoot that out to both of you. And let's go with Belal first. So in your experience, Belal, is there a point where AI can actually support well-being at work instead of humming it? You have firsthand experience here. So what is your take on this one? Belal Gouda (04:02.404) If it's used right, yes, it can. It can definitely support well-being. First thing that comes to mind is that if we use it to replace routine work that used to be just mind-numbingly tedious for people who have far more experience and value than just doing that, if it takes that of everyone's hand and allows them to spend their time doing more meaningful and fulfilling tasks, that ends up, of course, improving. There will be, and the overall will be, of the entire organization. But if it's, and it can extend to beyond that, so also to cover part of what Paulina said, I do encourage people to use AI to become more productive, but not the productivity in terms of just speed, but productive in terms of being able to deliver. higher value and higher impact using AI. And I also have like, this is a personal comment. I don't like the word co-pilot. I know it's also the name of the product. So I'm not against the product. Because being a co-pilot, so a co-pilot can also be a pilot, right? But, right, so it assumes that it can do Paulina (05:23.228) That's very true. That's a very good point. Belal Gouda (05:29.71) everything that you do, but you do it together. For me, it's a tool, not a copilot. It's a very valuable tool. It's a great, it's one of the best tools of the century. But for me, it's basically a multiplier of your existing experience and skills and productivity. the core, the number you start multiplying is you, is your value. So that's the most important. Paulina (05:58.907) And you're so right. And thank you for making that point. I will definitely avoid using that term in this context from now on. And to your question, Lars, I don't have a lot to add to what Belal said, because I also believe that if AI reduces overload or streamlines this BS tasks that nobody really wants to do, right? So that can definitely create space for teams to breathe and really focus on productivity and high quality output. And the only thing I wanted to add here is to do that, to do that takes a lot of intention, not just integration. So, and that again is a leadership task as well as the task of every person working with AI to really use it very, very intentionally. Lars Nielsen (06:55.494) And Pauline, from your perspective, what kind of leadership mindset is needed to balance efficiency on one side and empathy on the other side? And just a disclaimer, I have a cat coming in now in the picture. So everybody watching the video, I have a cat coming in in just a second and here he comes. He's very curious today. Paulina (07:11.026) you Aww, cute. Isn't he always? Lars Nielsen (07:21.462) Yes. Paulina (07:22.94) So, Lassie asked what kind of leadership mindset is needed. And I think this is the leadership mindset that I always promote here. It should be a leadership mindset of positivity and empathy. So, I need, I expect leaders to be very, very curious, not only about what AI can do, but also very positive about how AI can... help humans, how AI can be of benefit and rather, and not have it be something of a pressure button that helps me to get more out of people. it should more, so, and I think I always say that, right? I think this should, this is what leadership should always be about. Just the AI part makes it even more crucial because efficiency, is about systems and that is where AI can come into play as a tool. The empathy part and the positivity part of it, leading people in a positive way on a positive notion these days is so crucial and very, very human focused, right? And if you try to integrate humans and AI, you will definitely need both. And you need to have this this drive to really show your people that they are valued, that they are important to actually, yeah, to overcome that fear and... That AI is going to replace you. So for me, that means as a leader, should train your people. and if you're not, if you don't have the skills to do it yourself, obviously go out, find people who can do it and ideally learn how to do it yourself. so don't just tell your people randomly, just figure out prompting by yourself. That might work in, in a team like the last, but definitely not for most people out there. Paulina (09:39.737) redefine, definitely redefine productivity to also include learning, not just output, because we're at this crucial breaking point, right? If we, if we don't help people learn right now, then we're going to have a huge problem, probably already five months down the line for Belal, you can judge that better than me, but, and with what Belal said before, I really want to make the drive this point home. As a leader, should remember that the AI is a tool and your humans are still the pilot. Lars Nielsen (10:15.34) Yeah. And I think let me just put a note on this before we continue with the next question is that I remember Belal in the last episode or in the first episode that we did about this topic here, you said something about like, so if I'm working in a company and I'm just say I'm really good at using AI, right? So a task that used to take five hours, I can do in two seconds now, just to exaggerate a little bit. Paulina (10:15.644) same. Lars Nielsen (10:44.398) Then it's important for the leader to not just say like, so you're good at using AI now, so we can just put more work to actually praise that I'm being effective. So I, as the person, get praised for the work that I'm doing. And that actually stood up to me that that is really important because you just see that a lot of leaders, I'm just judging everybody here on the show. It's my show, I can do whatever I want or our show. Would maybe say like, okay, so he can take a task from five hours down to 10 minutes. So we can just put so much more work on him. But what they should actually doing is in like, wow, you're really valuable to the company Lars. I am gonna put a little more work on you, but maybe you just saved a lot of hours, maybe take a long. Paulina (11:12.838) Yeah. Lars Nielsen (11:39.948) lunch break or maybe go early today or something like that. Right. So that's, how, yeah, it just stood out to me the last time we talked about that, that, it's not something that I have to thought about that you actually have to praise people that way. So, okay. A long run for me. Let's continue. Bilal, we heard that AI productivity should be measured by outcomes, not outputs. And that's back to the topic again. Belal Gouda (11:44.486) Exactly. Lars Nielsen (12:09.846) What does that look like in practice from your point of view? Belal Gouda (12:16.232) So that means using an outcome-based framework. And this applies with or without AI. So for example, using something like OKRs, Objective Key Results. This is a very famous. There are other frameworks, but this is the most famous one. And you basically said business objectives. So we want to increase customer acquisition retention. We want to achieve this and that. And these are the key results that we can measure. And the higher we, the better we do at these results, the more we expect this outcome to be achieved. And then the entire, outcome as well becomes measurable. So using this and then linking everything that you produce in terms of outputs to how it's improving on these Q results and therefore delivering on your expected outcomes or objectives. This way you can, again, this applies without AI. So using this way, I'm pretty sure this is a very famous framework. So most of the people hearing us will probably be familiar about it. But then the question is introducing AI helps you deliver outputs faster, right? But the quantity of the outputs is not the key here. It's if these outputs that you're producing faster now are How are they impacting your key results? So my advice here is that if you become faster, you might want to reduce the cadence in which you revisit your key results and your OPR process. So if you used to do it quarterly, maybe start doing monthly to make sure that you're not moving fast in the wrong direction, that your new velocity is still consistent. is still leading you to deliver outcomes consistent with your objectives and your desired outcomes. So I would say it's the same framework, but on a much faster cadence. So this also is commitment at the leadership level, because usually this is a top-down process. Setting OKRs is a top-down process. And leadership should be aware of what business outcomes the entire organization is aligned on. Paulina (14:19.578) Mm. Paulina (14:34.588) I really like, sorry, sorry, Lars. I just want to say I really like that, that take on it. and I would just say that it's really clear, really important here to have absolute clarity on those key results done and how the key results can be influenced by, by AI, not just in terms of speed, but also do we need to have bolder goals because Lars Nielsen (14:36.832) And just go ahead, Pauline. Paulina (15:04.452) not only can we be faster, because we can maybe achieve something better quality wise, right? So I think it all comes down to those two things over and over again, right? Keep quality and speed top of your mind and to really use it with intention. Belal Gouda (15:22.546) Exactly. Lars Nielsen (15:23.042) And just to continue kind of down the same path of questions, how should companies kind of rethink productivity metrics in the AI era? Belal Gouda (15:37.512) Right, so in terms of using AI to become more productive, one of the things that we started doing at my company as well is, so AI is not only going to speed up the delivery of the actual product, can also speed up product discovery as well, right? So now you easily, so when you go to talk with your customers to figure out what they need, now you have much faster prototyping using AI that you can use. Now you can deliver MVPs in smaller increments more quickly. And therefore if you adapt your Paulina (15:59.975) Mm-hmm. Belal Gouda (16:20.656) feedback, user feedback cycle and make it also as iterative and as fast, you get to align your product with and make use of the new velocity in a more informed way. So now you're still going faster, but you're going faster in a guided way and in the right direction also thanks to AI. So this is a more This provides a lot of, needs a lot of awareness of how AI works and how we can apply it properly. And instead of just pushing the team to use AI, deliver on the same, deliver outputs on a new much faster speed, but we're not going, we're still going to review OKRs quarterly or we're not gonna update our results. We're not gonna be. we're still going to have the same cadence of touch points with customers or users in terms of collecting feedback. We're still going to get feedback by Google Forms or whatever outdated method that was applicable before AI, but now this can also be transformed to match. So if you apply it across the entire process and make sure that you're delivering the measurable outcomes, then you can still use the same metrics you used to use, but... under that new set of cadence and workflows. So that's how I view the metrics. I don't see a new metric, like a new formula that we make up to integrate AI into this formula, but I see the same formulas being applied just in a different way. Paulina (18:03.61) And I would... Lars Nielsen (18:03.662) And Paulina, when companies start to fixate on speed and efficiency, what cultural values start to disappear? Paulina (18:14.508) let me just quickly make a point to the last question before I return to this one, because I'm Bilal mentioned that you need to, really speak to customers and users also fast in shorter cycles. Right. And I think this is super, super crucial because at the end of the day, you're only being productive if whatever you produce works for your customers or your users. Right. Otherwise it's. You can just throw it in the garbage if nobody wants to pay for it or wants to use it. Right. So this is, and I think this is something that we really need to build into measuring the productivity on a, a much larger scale because we're, we will be producing products or features more quickly and therefore at a higher rate. So that should definitely be part of how we evaluate. our productivity. Now coming, coming to your question, what cultural values disappear if companies fixate on speed and efficiency alone. And that's, that's the nuance I want to make, right? If I generally speaking, I think that companies should be fast and they should be efficient, no matter, no matter what they're doing, as long as it's high quality work. But if it's the only thing that you focus on, then from my perspective, and I think Belal, mentioned something like that before as well, the attention to detail, the curiosity, the creativity and pride and craftsmanship, those will decline. that will lead to everything starting to sound and look the same. Right. And that's brings back to the exact same topic that we had last week. If we take out this human aspect of it, the person who's actually bringing the experience and the creativity to the tool, then the content gets faster, but flatter because everything, everybody produces similar results. So they Belal Gouda (20:08.828) That's what I'm Paulina (20:37.21) the teams might deliver more, but they will definitely care less because they don't have this pride in what they've delivered anymore. And I see that frequently at the moment that companies swap out thoughtfulness for throughput. But again, output without ownership is actually just noise, right? Because if, if I don't have the pride in it, if I don't own the output that I create, and if I potentially only produce output because I'm pressured to do so, and not because I've really thought it out, then there will be so much nonsense out there. And in a world where I can generate 10 slides in 10 seconds and believe me, I've tried it. It's faster than 10 seconds. What will actually set you apart is how human your thinking and acting still is and how much individuality you infuse your work with. Lars Nielsen (21:44.948) And then back to you, Bill, do you think that AI is changing what people find meaningful about the work? What is your experience from your workplace? Belal Gouda (21:57.26) My experience is that every, even since we started using AI, it is still the case that every innovation, every true idea, every idea that really was groundbreaking was disrupting to how we're doing things that led us to perform better from a business perspective originally came from a human. one of the team that, and it was gonna be the case whether we were using AI or not. So AI, as I said before, is a tool and it's a tool that I encourage everyone to use as long as they're actually still being able to produce original ideas themselves. So I'm all for providing high quality work faster. But when you say it's too fast is when you find yourself that you don't have enough time to actually stop and think about what you're building and what you want to build. and reflect on everything and the impact of what you're doing and brainstorm new ideas yourself. And not only on the individual level, when you also collaborate with other teammates, right? When there is human interaction, because just as AI is a multiplier of of human innovation, human productivity, is imagine if that human innovation itself can be multiplied by humans collaborating with each other and then multiply that by AI and then you get the maximum value possible. So this way, you can overcome all the negative downsides of AI that I don't know, three people probably said 100 % agree with every word. Belal Gouda (23:47.72) kills a lot of things, including pride in your work, which I think is part of yourself eventually, whether we like it or not, is part of work that we were trained to do, is part of who we are. It's part of us being out in ourselves, not only in our produced work. And this is why this is something that we should really fight not to lose. Paulina (24:04.156) Mm. Paulina (24:14.532) I couldn't agree more, Belal, because what's changing is the delivery of work, but what is staying and what stays the same is the human desire to matter, not just in work, but also to have that connectedness to other people. And so people want to feel proud. They want to feel seen. They want to feel useful and they want to feel connected to others. And if AI strips out all the parts where humans can shine, the creativity, the problem solving. the small craft acts of craftsmanship and then replaces all of that with automation without the acknowledgement, meaning definitely erodes for people. And on the other hand, if AI enables the mundane or handles the mundane, so humans can really focus on the mastery of the craftsmanship, then we'd see the win. So it All comes down to how companies design the experience of work and not just the tools that people will use. Lars Nielsen (25:23.294) And sorry, and Belal for you. For product teams and engineers listening, how can they protect their creativity in an AI driven workplace? Belal Gouda (25:39.6) Yeah, so there are a lot of things that actually can be done about that. So other than all the processes and the workflows that can be set in place that we mentioned on individual level when you're using AI, this applies to whatever you're using it to produce, whether it's writing code or generating a slide deck or a document or anything. Always ask yourself, Am I producing something that anyone else using the same tool could have produced something very similar? Or am I producing something that is very unique, that only me could produce it this way? AI is only enabling me to produce it faster, in a more refined way, maybe introduce better visuals, whatever it is, but this is my content, my ideas. that is being presented at the end, whether as code or whatever the media is. So this is the first thing that I always ask myself when I'm using AI to become more productive. And the second question that I always ask myself is, if this AI tool, if I'm in the middle of a project, can I explain all the decisions that is being made in that project without asking AI? So if my boss asked me on one small detail of what I'm building, right, why did we do it this way? Will I have to go back to the AI and ask it in order to be able to answer that question? Or should I have the answer and it's become very intuitive to me? Of course, we made this decision. because of one, two, three. So this is very important because this allows you to examine the level of true understanding that you have for what you're producing, brings you closer to the first point of you being actually in control of what is being produced. Another thing is, or another useful question that I use is, if the AI tool that I'm using stops working tomorrow, all the AI tools stops working tomorrow. Belal Gouda (27:45.862) Will I be able to continue this project myself, even on a much slower rate? But, or would I be completely blocked and will have to restart it? Because for example, I had the AI write it in a technology that I'm not familiar with, or I'm just using a black box that is producing something without me knowing how it's built or how it works. This is very important that to me that if AI stops working, if I decide to give it away, give it up. I should continue to produce the same output if that happens halfway. Right. And finally, and this is very important as well, because people, one of the things people care about the most is personal growth, right? Is how my experience, how am I getting better? Right. This is what makes a junior eventually senior in whatever they do. Right. So they learn and they have actual experience in the field of their work. So a good question to ask after completing a task using AI, did I learn how to do the task better after doing it? Did I get actual experience of like technical experience of the task? Do I have more knowledge than yesterday about my field or did I just learn better prompting? Right. prompting is an important skill. You should learn better prompting, but if it's the only thing you learn after each task completion, then you're just becoming a, we mentioned last time that like we don't want humans to become vessels of AI, right? So then I just became a better vessel, Like a faster AI enabler, right? So I start to lose that, that my own value. So putting all these together. this like this, this and everyone can come up with their own set of criteria. Like these are not hard coded questions that you have to ask in that specific order. But for I'm just sharing my the ones that I and this by the way, like I collected them from advice from many other people and from many other like asking my colleagues, how do you make sure that you're doing things this way and so on. So so these are not exclusive to me or to anyone. And I encourage everyone to Belal Gouda (30:10.802) think carefully about what would make them proud of their work and come up with their own list of questions that they need to ask themselves to always stay focused on not being driven away from their own human value and just become less of AI and therefore get burned out and all the other downsides that we've been talking about. Lars Nielsen (30:35.074) Thanks, Bilal. That was great insights. Paulina (30:35.632) I love these questions, Bilal. I'm actually gonna start using them for myself as well. I think they're brilliant. Lars Nielsen (30:44.3) I would be afraid of using them on myself because I'm vibe coding a lot. And I can't really ask myself that question. If AI is not here tomorrow, can I still complete the same task? Because that's a big no from my head, to be honest. Belal Gouda (30:59.154) But also to be fair, Lars, you're not trained as a software engineer, right? So what you're doing actually is a great thing because now AI is enabling you to provide value that you were never able to produce before. So now you're actually proud of what you're producing. So that's why I said this list should be per person. So you come up with your own list that makes you proud of your work. Lars Nielsen (31:21.549) Yeah. Belal Gouda (31:24.732) But if someone has like 20 years of experience in software engineering and is using AI to produce software, then the output should reflect their 20 years of experience and not become an output that someone with two years of experience would be able to produce. Lars Nielsen (31:42.03) 100%. And I would also say that one, let's call it in quotation marks here, one skill that I've learned when I started doing byte coding is I've become a much better project manager. Because suddenly I have this, let's call it a coworker or group of coworkers that I have to instruct in the same way. And you just learn when it comes to AI that you have to be extremely like good at like saying exactly what does it need. And you learn really quickly that if you don't elaborate on stuff, it just comes up with a lot of things, right? So we actually learned to go into the nitty gritty details for it to give you the best output. And I would say that the same skill would go with humans. If you have to lead a pack of humans or co-workers, if you don't go into the nitty-gritty details of stuff and you just assume that they know everything, then the output that they would produce would be as bad as an AI. Belal Gouda (32:57.96) Yes. So basically you're describing clear communication, right? So that's key to describing your needs, whether to humans or to AI agents. But I agree with you, especially managing AI agents. think this is going to become a very important skill in the, I think right now, like I was going to say in your future, think right now people need to start to do that. Paulina (33:21.628) you Lars Nielsen (33:24.568) within the next 10 minutes. Paulina (33:26.32) Hahaha Lars Nielsen (33:29.632) Okay, Paulina, so your company is called the Culture Code Foundation, What would be a, in quotation marks, a culture code for the AI error to include? Paulina (33:35.366) guess. Paulina (33:45.397) So for me, think in the AI era, the most human skills will become more and more important for any culture. so I believe that empathy should be a huge part of any AI era company. It should also include transparency, because not only do we need transparency, who is using AI to do what. Belal Gouda (33:46.92) Thank Paulina (34:15.184) So you share very openly what you've learned, what you've used AI for to improve your work results and not just pretend like you've all done this on your own in order to activate the superpower of collaborating with other team members and AI to get even better results. And then for me, the part about training and coaching is going to become even more critical than it is now. because it is a skill that you don't just teach yourself. And at the same time, prompting can be very easy or can seem very easy, but it is important to really bring your individuality into it and to bring this creativity into it. So knowing what to ask, why to ask it, when to ask it, how to... judge the quality of the output is so, critical. So that part is going to be. Crucial from my perspective. then redefining productivity because it bless you because the productivity is so often confused as simple speed. Lars Nielsen (35:30.382) Yeah Lars Nielsen (35:34.648) Thank you. Paulina (35:41.602) And I've said this over and over again, fast isn't always better. Especially if what you're producing is forgettable or irrelevant for your customers or users. So, And the next thing that I think is going to be incredibly important is really strong leadership. And that means training your leaders as well, getting your leaders AI ready, not in terms of tools, but in terms of how to design this human AI collaboration and how to evaluate the output correctly and how to value the human input correctly. and also in terms of how to positively lead your team, your team through this incredible time of, of incredibly fast change, which is a challenge. It's a huge challenge for leaders for sure. that is not something that any of us have been through in our lifetime to, to accompany that kind of a change. And therefore it is crucial that leaders get a lot of support in this time to really get the, yeah, get, get the teams supported, get the teams motivated and keep them engaged through this. Lars Nielsen (37:09.55) And then what's the... I would say this. Let's ask you both this next question and let's keep it when it comes to workplace culture because if you ask this question to me, I'll go on a rant down the path I don't want to go down to. So the question is, what's the biggest misconception companies have when they say they're AI first? And again, we are talking workplace cultures here. Bilal, please go first. Belal Gouda (37:38.674) So the official definition, as far as I'm aware, that people use mostly when they say we're AI first company, is that any task that is now considered to be perfectly done and automated by AI should be from now on all done by AI and only managed. by humans and all the tasks that AI still cannot do are so then these tasks humans should focus on them instead of the other ones. So this definition, if you compare it to how we've been describing the best way to use AI from both productivity and real productivity and also with cultural perspective, needs a little bit of addition, right? So instead of saying any task that AI can do should be done by AI, we should said that humans should now be empowered by AI tools that multiply their productivity in whichever task AI is now best known to be able to assist in. So a change of language, I think, in how companies are defining what AI first means should at the definition level, inspired than everything else that we've been discussing from policies to processes to culture and so on. Paulina (39:05.424) I love that take Bilal and I would just go even one step earlier and say that the misconception for me, the biggest misconception is that AI will solve problems that companies never properly defined in the first place. So you don't just need a definition for AI, but you also need to have clarity on everything that you're doing because AI, you cannot AI your way out of unclear goals or poor leadership or broke team dynamics. So AI is going to accelerate whatever mess you already have. So being AI first without being very, very culture conscious, is just gonna, yeah. Paulina (39:56.913) give you a culture that you deserve. You always get the culture that you deserve, right? But if you do it in this environment with this speed of change, it's a little bit like buying a spaceship before you've actually learned how to drive a car. Lars Nielsen (40:14.456) That's how most startups work, probably not. Paulina (40:17.34) You Lars Nielsen (40:19.918) Okay, so like last time, of things just, you know, time passes by really, really fast. So let's start to wrap up here with, and this is again, goes for both of you, and let's start with you Pauline at this time. What would be your one piece of advice to founders and leaders implementing AIB? Paulina (40:48.644) I would definitely say that you need to intentionally design your AI strategy and you should definitely design it around your people. Not the other way around. You cannot design your people around the AI tools that you want to use. And if your use of AI or the specific tools that you're using are leaving people burnt out, demotivated, insecure or disengaged. then you will definitely not be innovating no matter how powerful the tools are that you might have in place. In those cases, you will just automate chaos. And I would advise you to start with questions like, What do we want our people to achieve through using AI? Where does AI add clarity and where would it create confusion in our specific setup? And how do we train our team in order to get the best possible results? And how do we structure our reward systems around this new dynamic? in a company. And again, the reward system should not just be focused on productivity, efficiency, la-di-la-di-la, but it should also really, really take and focus the human side of things, the creativity, the input, the effort, the experience, all of that, that is feeding into it and the own personal growth that people will showcase throughout utilizing these tools. yeah, I think this is, this would be super crucial things because you all know this quote, right? Culture eats strategy for breakfast. And that also holds true for your shiny new AI strategy. Lars Nielsen (42:53.538) And Bilal, one piece of advice from you. Belal Gouda (42:57.156) So I will go for an advice for the individual employees who either won't use AI themselves to become more productive or are told to use AI by their AI first organizations. If you find yourself using AI in the wrong way or forced to use it in the wrong way, don't wait until you're burnt out or suffering from all these issues every day that you're not using your own experience and building on it. is a loss. So raise the flag as early as possible. Talk to your colleagues and you will find that probably if you're suffering from this issue, you'll find that your entire team is also suffering from the same thing, but no one must be the first to talk. My advice is talk to your colleagues. Be the first to raise the flag if you are aware of this and try to always make sure that you're proud of the work you're producing, that you're productive in the term of that you understand how you work. is representing you is something that only you could produce and that is actually helping the place you work at, your company or organization, to achieve its actual goals. So not only in a matter of the quantity of tasks you're doing every day, but the quality and the impact on the business and the customer. That's the most important thing. Paulina (44:21.724) I love that. Lars Nielsen (44:21.87) Perfect. And we are kind of coming to the end of another episode. It's almost up to an hour again on this one. Maybe we should do a part three at some point. To all the listeners out there, like we said in the beginning, this is the part two of this topic here. So please go back and listen to part one before you listen to this one. yeah, Billa, thank you very, very much for taking the time to come in again and... Paulina (44:32.55) Hahaha Lars Nielsen (44:50.552) give us some extremely valuable insights because you have firsthand knowledge of all of this. yeah, before we round up Paulina, the floor is yours. Where can people find you? How can they reach out to you? And yeah, if they have any questions. Paulina (45:10.724) First of all, I also want to thank you Belal. It was amazing having you as a guest for two, not just one, but even two episodes here. And thank you so much for sharing your insights. It was incredibly knowledgeable and I learned so much myself. So thank you so much for that. And to all of our listeners out there, not only if you want to learn more about what we do, but also if you want to share your own story here, if you want to be a guest on the show like Belal or if you want us to... narrate your story in an an enormous way. Feel free to reach out to me on LinkedIn or on Instagram or also to Lars, we'll put all the social media handles in the show notes. And you can also find the Culture Code Foundation either on culturecodefoundation.com or at on LinkedIn as well. Lars Nielsen (46:00.494) We'll put Bilal's LinkedIn in the show notes as well if they want to reach out to him and might have some questions for him as well. Bilal, any closing comments before we wrap up for today? Belal Gouda (46:12.742) So I just want to say it was a pleasure joining this podcast in two episodes. I literally had so much fun talking about this topic with you guys. And I believe I learned a lot from your insights as well. I think talking about something actually makes you even more aware of it than before you talked about it. like, because preparing for this podcast, I had to organize my thoughts around this and even come up with better ideas myself. So thank you for hosting me and giving me this chance. Paulina (46:40.668) I Belal Gouda (46:42.666) I'm really proud of doing these two episodes with you. for everyone who's watching, feel free to reach out through my LinkedIn. I would be happy to answer any of your questions about this or any other topic. Thank you very much for listening. Lars Nielsen (46:57.678) Fantastic. remember to all the listeners, if you enjoyed this episode, please share it, give it thumbs up, give it a review and follow Cultures from Hell on any podcast platform and on YouTube. Until next time, have a great day. Paulina (47:17.35) Good one. Thank you. Belal Gouda (47:18.76) Thank