The five ingredients every strong team has, before they even touch AI - with Daria Rudnik

0:01 Welcome to the show Mind Blend. I'm your host, Karen Chong, and

0:05 I'll be diving into the minds of incredible people, each an

0:08 expert in their very own way. Together, we'll uncover insights

0:12 and share ideas so you can be inspired and empowered to

0:16 navigate your own unique journey in life.

0:19 Ready to get curious and discover what's possible?

0:22 Let's blend. So a few episodes back, I'm mind

0:30 blended with Collette Mason about how we can make AI work

0:33 for us, not replace us. But the conversation doesn't

0:37 stop there. There's so much more we have to

0:39 explore about what happens when AI and human truly start working

0:43 together. So today I'm joined by Daria

0:46 Rudnick. Daria sits right at the

0:49 intersection of AI, leadership and human connection.

0:52 She's a leadership coach, team architect.

0:55 And then we'll go a little bit more into that and hybrid

0:57 intelligence strategist who helps leaders in their teams

1:01 build clarity, trust and real connection in an AI driven

1:05 world. Hi Daria, welcome to Vine One.

1:08 Hi, Cameron. Thanks for having me here.

1:09 It's it's yeah, I'm very excited to have this conversation.

1:12 Yeah. So I'm sure our listeners are

1:14 intrigued by now. What do you mean by team

1:18 architects and hybrid intelligence strategies?

1:21 So tell us a little bit more about your journey and how you

1:25 got to where you are today. Yeah, well, my, my background is

1:30 an HR and organization development.

1:33 I started my career in Deloitte and then I moved to achieve

1:35 people officer for mostly tech and telecom companies.

1:39 And look through throughout my career, I, I, I've seen

1:43 disruptions that you said various disruptions that teams

1:47 face, teams face like merges and acquisitions like setting up in

1:51 other countries. And what I've noticed is when

1:55 organizations have strong teams, they are much more successful in

1:59 any organization transformation that's happening.

2:01 They are much more successful in dealing with, I mean, global

2:04 disasters like financial crisis or COVID or like whatever it is.

2:08 But when the teams are not strong, when like the culture is

2:12 very diluted, it's, it's very hard for leaders to move their

2:16 organization forward. And I've seen examples of like

2:18 failures where the companies were just acquired and, and

2:23 dissolved. They were not existent anymore

2:25 or they, they go bankrupt. A lot of it because the teams

2:28 were not ready for for this change.

2:31 So since ever that time I started to study and see how to

2:36 design amazing teams, how to build those teams because they

2:40 don't just happen on the road whenever like families of the

2:44 team, universities are the team, schools on the team.

2:46 And the first time we really join a team is when we're

2:49 joining workforce. And now we're expected to be a

2:51 team player, like work in a team or when manager grows into his

2:56 first managerial role, they say we need to build a team.

2:59 How do you do that? Yeah, they didn't teach it.

3:02 It's not about delegation and control.

3:05 I mean, no. So you need to design the team,

3:09 you need to build a team. And so it's a special effort,

3:11 it's a skill. There are certain tools and

3:13 techniques that you can use in order to practices that you that

3:17 you need to implement in order to build this this great team.

3:20 That's why I kind of call myself A-Team architect because I

3:23 helped leaders build those kind of teams and design them.

3:26 But he also mentioned about hybrid intelligence and that's

3:28 kind of a new thing when AI is joining the workforce and

3:32 influencing team dynamics, organizational dynamics, how we

3:35 work together. It's and it's not just work how

3:38 we think, collaborate and make decisions.

3:42 And that's a totally used skill and kind of understanding of how

3:45 to work with the AI so that you don't delegate too much, you're

3:50 still in control, that you still own the work that didn't have

3:53 intelligence to do that. So let's set the scene a little

3:58 bit for our listeners. We are at the time of this

4:01 recording close to the end of 2025, we've seen layoffs with

4:06 reasons such as we're optimizing our resources and now we don't

4:09 need nearly as many people with the help of AI.

4:12 And you also see sort of like this pressure coming up from

4:16 leadership or founders level C-Suite of mandates of we need

4:23 to use more AI or we need to use AI and all these projects and

4:27 things like that. Because you work with teams and

4:30 leaders directly, what have you, What sort of emerging patterns

4:35 have you noticed? It's, it's kind of from the

4:39 employee perspective, there's sort of fear.

4:41 There's a fear that AI will replace me.

4:44 And even more, it's not that AI will replace me, it's the

4:49 manageable thing that AI can replace me, which is not like

4:53 you mentioned layoffs. There were a lot of layoffs

4:55 labeled like AI driven lay layoffs but like to be honest

5:01 most of them are economically driven layoffs and AI is just a

5:05 nice cover for many of them. And we've seen, I think so too.

5:09 Yeah. And we've seen situation when

5:10 people kind of think, OK, now AI can do that for them, we can

5:14 save some money. They have to rehire those people

5:16 back because, well, no, AI cannot do all the work for

5:19 humans. It can support you can do more

5:24 with the same amount of people, but doing more with less people.

5:28 Well, not. Not yet.

5:31 Yeah, I am glad you pointed out the not yet because you know,

5:35 we're actively training it. The models are getting improved.

5:38 At some point it can do more than what it can do today.

5:42 However, we need to keep the lights on.

5:44 And it's, I definitely believe that it's more how you can make

5:49 your people more efficient so you can do more of what's

5:53 important for the organization, not just do more.

5:56 Yeah. What about leaders like, what

5:58 are like the ones who advocate like, yes, we should just use AI

6:02 and replace half of our workforce or the ones that are

6:06 sort of pressured by their management of incorporating more

6:10 AI in like your team. Like what have you seen with

6:14 that layer? A lot of companies are

6:16 experimenting with AI and we are at this experimentation stage

6:20 when lots of AI projects are initiated from various parts of

6:25 organizations, sometimes from the top, sometimes from the

6:27 bottom, sometimes like multiple AI projects in various

6:30 functions. But together with that, we also

6:33 see that AI is not bringing regional investment as a as we

6:36 hope it will. So I mean we're still like

6:39 trying to figure out how that how that should work.

6:42 So the latest, the main question is they will have to use AI,

6:47 Everyone will have to use AI. We we can understand that.

6:50 But the question is like why? Yeah, I'm not against that at

6:54 all. Yes, why and how?

6:56 Like what is the reason? What is that we want to use AI

6:58 for and what are the norms, how we're going to use it?

7:02 Because I've seen situations where kind of people just dive

7:05 in, OK, let's use AI for everything, and then that causes

7:08 team disengagement, loss of motivation, and eventually loss

7:12 of productivity and effectiveness.

7:15 So you you help companies build effective teams.

7:18 High performing teams. Name some characteristics of a

7:22 high performing team. Oh, I can have you 55.

7:26 Yeah, name as many as you want. I guess while while working with

7:30 teams and like not just the favorite, not just in practical,

7:34 but like, yeah, reading literature and scientific

7:37 literature about how like great what what does it make to be a

7:40 great team? I came up with five major

7:43 pillars of any successful team, high performing team, team that

7:47 is more self-sufficient, more autonomous, that can manage

7:51 themselves and they don't need leader for every decision.

7:54 So the first thing is they have they have a clear purpose and

7:57 that's pretty obvious. Yes, you need to understand why

7:59 you're together. And the tricky part here is not

8:03 every team has that. So if if you have a bunch of

8:05 people and like just being reported to one manager, that

8:09 doesn't make them a team. They become a team only when

8:11 they have a shared purpose, something that they can achieve

8:15 together by collaborating and and working together and not

8:20 just by combining the individual contributions.

8:22 So that's, that's the one important part.

8:25 The second one is linking connections.

8:28 When people are connected within the organization, there were a

8:32 lot of connections manager to employee, but what about like

8:36 people employee to employee, people, team members to team

8:39 members And more importantly, what about the connections of

8:42 this team members to other, to their stakeholders.

8:45 So it's not just the manager who goes out to the boss, to the

8:49 stakeholders, to peers presenting the results.

8:51 So it's people, team members go now to their stakeholders,

8:55 understanding their needs, presenting results, taking

8:59 responsibility for the mistakes that they've made.

9:01 So that's the second part, linking connections.

9:03 The third one is integrated work.

9:06 And that that's what many leaders are missing is how do we

9:10 work together as a team? What are our team norms?

9:13 What is what do we support in terms of behaviour?

9:16 What kind of behaviour do you want do we want to see in our on

9:19 our team and what kind of behaviour we never want to

9:23 tolerate? So what is not tolerated on our

9:26 team? So this team knows how many

9:28 meetings do we want to have? Like what are the communications

9:31 channels that we're going to use?

9:32 It creates a lot of clarity and it removes frustration from

9:36 people. OK, what's next?

9:39 The 4th 1 is collaborating decisions.

9:42 How do you make decisions on your team?

9:44 Because you as a manager, you don't have to make all decisions

9:46 on your own. And then finally, knowledge

9:49 sharing and feedback. How do you as a team learn and

9:52 grow together? How you learn from your

9:54 mistakes, how you give feedback to each other, how you collect

9:57 feedback from your stakeholders? So those five pillars, clear

10:01 purpose, linking, connections, integrated work, collaborative

10:05 decisions, and knowledge sharing is what will make your team

10:08 click. Have you seen anything that like

10:13 you, let's say you have a client that you help them build high

10:18 performing teams. Do you, have you seen any cases

10:21 where they used to be performing great, but recently they've

10:25 started phasing out certain things that they're doing

10:30 because of changes in technology?

10:32 Have you seen anything like that?

10:34 Well, I have AI have an example of a of a team.

10:37 I'm not sure they were like super high performing team, but

10:39 they were recently like they were pretty decent before AI, it

10:44 was a customer success team. They were like working with the

10:47 clients, pretty happy together, engaged, working well.

10:52 It's a good team and at some point, and they were a good

10:55 team, they were curious about new things.

10:57 So they implemented and started using AI quite a lot.

11:01 So they they had that conversation with clients.

11:04 The conversation was recorded. They had a transcript of this

11:07 conversation. AI generated insights from the

11:09 conversation. They uploaded it to CRM.

11:13 Some of the items went to backlog and then AI helped them

11:17 generate agenda for the next meeting with the client.

11:19 So I mean, a lot, a lot was automated.

11:21 Everyone was happy. They had lots of time.

11:24 They had to like pick up the projects that they didn't have

11:26 time for before they had some time to breathe and kind of OK,

11:31 relax and not behind all like the days all the time.

11:35 But here was what happened next. At some point during the, the

11:40 team meetings, they, they couldn't like recall some of the

11:44 things they used to know about their clients.

11:47 They used to know they're like, like, you know, but now they,

11:51 they keep forgetting they need to go to the, to the CRM to look

11:54 at their insights that they have not generated that were created

11:58 by AI. They couldn't prioritise items

12:00 for, for the backlog because, OK, they didn't have this

12:03 understanding what's more important for their clients

12:06 because again, they, they were not the ones who generated those

12:09 items. It was AI and they started to

12:12 feel like they're losing connection with their work.

12:15 They became just operators, putting data from one source to

12:17 another operate, helping AI do the work for them.

12:20 But they lost the meaning. They lost meaning, they lost

12:23 engagement and like eventually they lost productivity because

12:26 they were not so much involved in everything that's happening

12:29 by their clients. And that's when I joined this

12:31 team and kind of helping them to, to be like, to regain their

12:36 like get the engagement back and productivity and become more

12:40 efficient with AI and how they use AI.

12:44 And So what they did is well, they started again with, with

12:49 why with a clear purpose. Why, why are we using AI?

12:52 Like what are we using AI for? What's what's in it and what is

12:55 what should stay with us as a team?

12:58 What's our word value proposition for organization for

13:01 our clients? Again, this, this understanding

13:04 and feeling of what the clients need and being able to support

13:07 their needs the best way possible is what should stay

13:10 with them as humans, as teens. And some of their automated work

13:14 can be created by AI. And the next thing they did is,

13:18 I don't know if you've heard about it.

13:20 There's a research called Your Brain on ChatGPT that tells that

13:24 if you like ask AI to do something and then like try to

13:29 edit it, your brain is disengaged and it stays

13:33 disengaged for like the whole project.

13:36 But if you do something, if you initiate the draft, if you do

13:38 something 1st and then ask to edit it or get some input, your

13:43 brain stays engaged longer. So what they did is they before

13:48 generating insights from the conversation and from the

13:50 transcript at the end of each conversation, when the

13:53 conversation was over, they kind of just was speaking, speaking

13:56 some things that they thought of this conversation, their

13:59 feelings, they got the insights, the idea, and then AI generated

14:04 insights based on what manager said and they're trusting the

14:08 conversation. So they were the first one to

14:10 give this input. They still own the conversation,

14:13 they still own the result. And then, well, they had team

14:16 meetings when they looked at those insights, looked at the

14:20 backlog and they were like, really, really go deep into that

14:24 and analyzing what's there and saying, OK, this is relevant,

14:27 this is not relevant. So they they they became part of

14:30 the process rather than just the observable support AI is doing

14:34 for that. Yeah, you know what?

14:36 That sort of made me think of two real life scenarios.

14:40 One, phone numbers. So now you just hand your phone

14:45 to whoever they put the phone number in, you call them to like

14:49 give them your own phone number. That was the transactions.

14:53 So the numbers have not even gone into your brain at all.

14:57 So it's kind of similar to that. Another one is if you are, if

15:01 you work in a restaurant and you're the person taking the

15:03 order and you pass it to the chef, you may remember what it

15:08 is, but that was like really just the level.

15:11 And you may not even remember if there's like 100 customers.

15:15 So what you pointed out about you being the first engaging

15:21 your brain, I think that's like a really, really good point

15:23 because there are many things that we are starting to do it

15:26 like that. If you have to go somewhere, put

15:29 the address in the GPS, you may not remember how you get there.

15:33 I know that happened to me a few times.

15:36 So by them kind of taking back that ownership of the insides of

15:41 the idea, how have you seen them gone back on track?

15:48 Well, they started having this conversation, well, first of all

15:51 between themselves when they started, when they, they engaged

15:54 in team meetings discussing the outputs, the inside the backlog.

15:58 Well, not only they understood it better because they.

16:02 Understood it better. OK.

16:03 But they also had again had a chance to talk.

16:05 We love connection with people. We love working together.

16:09 We love like seeing how ideas are built on ideas that we

16:14 share. Something someone fixed it up,

16:16 what's the question? And that not only helped them

16:21 understand better their clients, but it also helped with the team

16:24 climb and how they feel together.

16:26 Yeah. And I feel like they may have

16:28 insights that AI will never be able to generate for them

16:31 because we understand situations differently.

16:35 And you sort of have to feed all the new ones into AI for it to

16:39 give you like a well-rounded suggestion or insights.

16:43 So I'm glad. So what you were describing like

16:46 it never touching their brain, is that what you call cognitive

16:49 offloading? I mean it's it's it's a, it's a

16:52 term and this term is actually what you like properly described

16:56 with phone numbers and GP and GPS.

16:59 It's deal with that for quite a while right there when we

17:03 offload some of the information from our brain to technology,

17:06 which is good. I mean, there's so many, like

17:08 there's so many things we need to remember.

17:10 So that's so much information. We don't need to remember it

17:13 all. So at some point, cognitive of

17:16 loading is helping us to, to live with this excessive data

17:20 that we have around us. But when you offload too much,

17:24 when you like, one thing is a floating data numbers and things

17:28 like that. The other thing is when you

17:30 offload decision making. And that's when things go wrong.

17:33 And that's, that's the difference between like

17:36 automation and AI, because with automation, you don't expect

17:39 anything from a machine. But with AI, we kind of think

17:43 we're talking to a human being. We kind of have a real

17:45 conversation. We kind of assume that this

17:49 thing is telling us the truth, that this thing knows, which is

17:53 not true. So that's why it's very

17:56 important to be mindful about how much do you want to upload

17:59 to AI and at this, you know, lose this connection with your

18:04 work. So what in your opinion?

18:07 So besides data and like everyday business scenario, what

18:12 else would be suitable a suitable category of information

18:16 to offload and what they people should definitely not offload

18:21 like you mentioned decision making.

18:22 Yeah, I mean, there are lots of things we can offload.

18:24 Whether we cannot and should not offload is something that needs

18:27 empathy and and human to human connection.

18:30 And a great example is you never, should never fire a

18:32 person with AI, with the help of AI.

18:35 And there was A, and it's true and it sounds ridiculous.

18:39 There was a company that was a post on LinkedIn and some CEO or

18:42 CEO or some of the company they mentioned, like a relay of lots

18:46 of people here was an AI tool you can like reach out to and

18:49 talk to make you feel bad about that.

18:53 Oh, that's that's, that's so bad.

18:57 This post was bleeded but Internet remembers everything so

19:00 the screenshots are there. But yeah, things like that

19:03 should never be delegated to AI. And if you work with again, high

19:07 sensitive data, obviously, and be very mindful about like who

19:12 is getting access to that data. And again, it thinks AI telling

19:18 us they're not true. I mean, it depends on how you

19:20 train this AI, but it's if it's generated AI, they're not true.

19:23 They have probabilities that AI predictions based on what it

19:28 knows. So and always checking,

19:31 rechecking their output that AI gives you is a critical skill.

19:36 For now, at least, we'll still need to do that.

19:40 Do you have any good success cases like we can step away from

19:45 just focusing on AI? How has your biggest success

19:49 been going into a team and trying to fix, quote UN quote,

19:53 fix their issues and turn them into a high performing team?

19:57 Great question. I'm a lot of indicators of of

20:01 high performing great team. One of them is how much revenue

20:04 they can generate, how much they can perform.

20:07 I've been working with company that.

20:09 Increased performance 3, three or four times.

20:13 But they were really pretty good team to be honest.

20:16 So the transformation they they've been through was, was

20:20 successful because they're very good team.

20:23 But I have an example where there's a lot of conflict on the

20:26 team. It's it's a manufacturing

20:27 company and the CEO reached out to me say, hey, like I have a

20:30 lot of conflict on my team. People cannot make, make

20:33 decisions together. They think the ID is better.

20:37 So when I joined the team and we started having those

20:39 conversations, team sessions, it happened that that well, people,

20:46 all of them, they were really engaged and they're really

20:48 motivated in company success. They just saw it differently.

20:51 Some saw that they need to focus on quality, others so that the,

20:56 the, the most important thing is distribution channels and things

20:59 like that. So one of the things we did

21:02 together is apart from like being clearly, clearly being

21:06 clear on the purpose of the team, we created a list of

21:10 behaviours like what are the behaviours that the team wants

21:14 to see and wants to support and want to see more of like sort of

21:19 the keep it up behaviours, behaviours that need to stay on

21:22 the team. And what are they cut it out

21:24 behaviours, behaviours that they're not going to tolerate.

21:28 So they had the list, they had the list of keep it up behaviors

21:31 and carried out behaviors and all.

21:34 Eventually they, they had like they started to have meaningful

21:37 conversations with each other. They learned how to work

21:39 together. They moved forward and I think

21:43 it was a success. But the most interesting thing

21:45 happened about six months after when the CEO reached out to me

21:48 and said, you know what, we're moving fine.

21:51 We're going in in that direction.

21:53 A lot of conversations, lots of argument, but they're not like

21:57 personality conflicts, but people really bring in some

22:00 ideas and challenging them. Yeah.

22:03 And the team decided that the sales leader needs to go.

22:08 Why? Because she didn't follow the

22:11 keeping up behaviors and she constantly demonstrated some of

22:14 the cut it out behaviors and the team mentioned that several

22:18 times. She didn't change and and the

22:20 team, they decided that she needs to go.

22:23 It wasn't C the CEO, it wasn't like the divorce.

22:26 It was the teams that she's not part of our team because she's

22:29 not following what we agreed to follow altogether.

22:34 I think that's that's a great example of TNB more

22:36 self-sufficient brand. They don't need their leader to

22:39 make every decision. They can make decisions on their

22:42 own. If they can solve problems on

22:43 their own, they can be more autonomous and they moving

22:47 without delay because they can make those decisions and they

22:51 can, they can do that. Are the clients that you work

22:54 with, are they like more concentrated in certain

22:58 geographies or you work with different people in different

23:01 continents? I actually, yeah, I was

23:04 counting, OK, how many countries?

23:05 I've been working with people in India, in Zimbabwe, in Latin

23:08 America, US mostly it's North America and Europe, but

23:12 Australia, yeah. And it's, it's, yeah.

23:16 I I love this opportunity to work with any like people from

23:21 any country like due to again, due to technology.

23:24 Yeah, 'cause what I wanted to ask is, you know, like I know

23:28 one of your effort is to help teams be like, to avoid burnout,

23:34 both burnout for the leaders and burnout for the team.

23:36 And in the example that you gave, the team can make

23:39 decisions themselves so they don't have to go to a leader

23:41 every single time. That hierarchy sort of depends

23:45 on the culture. To some cultures, that is fine.

23:49 Some cultures you the final say, still come from the top.

23:53 So how? How do you balance the culture

23:57 versus the nature of a high performing team and how to keep

24:01 people from burning up? That is, I mean, that's I love

24:04 that question. And and the the the best thing

24:08 about like a high performing team and how they're formed is

24:11 that the team themselves, they people on this team, they decide

24:14 what works for them best. If they think that the manager

24:18 need to have a final word, they can do that.

24:23 The cultures were like company organizational cultures.

24:26 When they say you work hard, you work 1212 hours a day, like

24:31 you're not getting promoted for five years, but you'll get in

24:35 return like rapid growth or healing skills or whatever.

24:39 So it's it's a very clear contract and a very clear

24:43 agreement. So you can have any type of

24:46 culture you want I guess, as long as you sit together and

24:50 agreed on your team norms and team goal.

24:54 I haven't really thought about it that way, but that is a very

24:57 good tactic to kind of frame people's mindset before they go

25:02 into how do we get to become a high performing team.

25:05 So there's this like cycle of you have farming, storming,

25:09 norming, performing. So that's a typical cycle of any

25:16 team. Some teams may skip some.

25:18 Some teams may be stuck in Yeah Storming, for example, and they

25:23 come to you. Yeah.

25:26 But again, it's not a cycle. It's it's more like a spiral

25:28 because like with with any new challenge, with any new member

25:32 coming in, coming out, you go through the same cycle again

25:36 over and over again. So and then it's important for

25:39 men to kind of catch those cycles and make sure that to

25:42 help team go through that cycle because they will repeat.

25:46 Yeah. Now with technology like what

25:49 would be something that any leader or team members who are

25:53 burned out, anyone listening who wants to make a change so that

25:58 they can use AI to help them better, What would be something

26:02 that you would suggest they start?

26:05 To actually depends on the on the stage of AI and like

26:09 wireless. Yeah yeah in the company like

26:13 personally for themselves where they are because I mean I know

26:16 there were people who are using AI daily, but companies just OK

26:19 thinking should we do it? Should we not So they are in the

26:22 different like levels. But well, first is being curious

26:27 about what's there, like how it works, being curious about like

26:31 not only how should I use it, but also like what's really

26:35 happening when AI produces some outcomes.

26:37 Like the thing I mentioned that it's not true, it's predictions

26:41 like how actually LLMS work and start trying it out, make

26:46 mistakes, be mindful about the outcomes again, like repeat the

26:52 cycle, learn something else, try it out, share with other people,

26:56 see what they're doing. And that's how we learn.

26:58 Yeah, the theme of curiosity, what has been floating through

27:03 the whole Mind Blend series so far, is like to keep an open

27:07 mind and iterate, learn from your mistakes.

27:10 Yeah, well, that's that's the drive of the progress.

27:13 Yeah. What would be your worst case

27:15 study? That it's always something that

27:18 you talk about as like casual family gathering or dinner party

27:22 or something. I have AI, have an.

27:24 I have an example. I was, I was having a

27:28 conversation with the CEO when I found one company and well, they

27:33 said that they value, I think it was either transparency or

27:37 honesty, like transparency or honesty, probably honesty was

27:41 their value and and they wanted and they want to build honest

27:44 relationships with their customers.

27:47 And he talked a lot about that. But like throughout some

27:50 conversations, trust, hey, it was trust.

27:54 So he was talking about trust and he wanted to build trustful

27:56 relationship with with the customers.

28:00 But like while talking to that person I found out that he's not

28:05 paying full salary for the employees.

28:08 OK. Like using some like kind of

28:10 schemes to minimize taxes as OK. You talk about trust, how people

28:16 can trust you if you're doing things like that and like the

28:19 response was OK, You don't understand how to lead a

28:21 business. You cannot lead a like you

28:23 cannot run a business if you don't do things like that.

28:26 I mean, what happened a few months after that?

28:29 Is that one of the suppliers so brought bad product and and some

28:35 of the customers got quizened because of that product.

28:39 Wow. OK.

28:40 And I mean, if you if you build your relationship on trust, you

28:45 need to make sure everyone can trust you.

28:48 But if you build, if you like, if you're trusting here and not

28:51 trusting there, make sure you control everything like very,

28:54 very thoroughly. Because the trust is one thing,

29:00 but like if you're lying on some other things, it like it

29:04 destroys your culture and finally it destroys your

29:06 business. So that is a great example of

29:10 how I declare values and not actually part of the company and

29:14 how it can do in a company. Yeah, like you mentioned it in

29:18 the beginning, like the pillars of high performing team, like

29:21 shared values. Yeah.

29:23 So for this last part, let's play something out of the

29:27 ordinary. So I have a few rapid fire

29:30 questions. Just like really quick whatever

29:33 comes to your mind, say it. What's 1 human skill you think

29:37 is underrated in the age of AI? Well, we simply talked about

29:42 curiosity. I have this curiosity in my

29:43 mind. I think like we, we

29:45 underestimate curiosity and we underutilized curiosity to be

29:48 more curious and open to new things.

29:51 Yeah, I am 100% with that. So you've worked with, like

29:56 many, many continents, What culture taught you the most

30:00 about teamwork? It's it's not like culture, it's

30:04 again that don't put labels from people based on their origin.

30:08 Like see the human we as a leader, you have 10-8 people on

30:13 your team. We can learn about them as human

30:16 beings without labeling them like based on their culture.

30:20 Yeah, yeah, I see this a lot. It's not intentional, but people

30:25 will be called Oh the the, the Scottish guy like the Chinese

30:31 guy. Yeah, know them by their name.

30:33 Call them by their name. OK, When you feel mentally

30:38 overloaded, what's your go to way to reset your mind?

30:42 I studied practice in Tai Chi was in Canada.

30:44 I love it. Tell tell me more like I'm

30:47 interested. Well, like I used to do yoga

30:51 like long, long time ago. And I went, OK, I need to get

30:53 back to yoga. I could get back to doing yoga,

30:56 but I couldn't do that. It's important.

30:58 My husband shared a video with me and like a lesson and I was,

31:04 I was impressed with the wisdom is that can't let go together

31:11 with with the body movement and and the wisdom for me was very

31:15 important. And the point is that we you

31:18 cannot achieve anything with force.

31:21 This force is just one black powder, one thing, but you need

31:25 to be able to release, and that is as powerful as force if you

31:30 do it right in the right way. And this balance between like

31:35 moving forward and releasing and letting go is what I'm

31:40 practicing in my business and life.

31:43 And Tai Chi is is really helping me with that.

31:47 Interesting because I see people in parks sometimes doing Tai chi

31:52 in the morning and like I have a mental image of the movement

31:56 just because like I grew up in Asia.

32:00 But interesting that helps with business too.

32:02 So complete this sentence. I wish AI could.

32:09 I wish AI could change the world for the better.

32:11 I'm not sure if it's possible. Well.

32:16 This is why we're having this conversation today.

32:19 Like, I think if we can early on adopt A healthy mindset of using

32:24 AI and how we should use it to help us, partner with us, even

32:29 not just like an operational tool.

32:31 If more people can think of things like this, then yeah, we

32:36 can change it for the butter. Like we have so much more

32:38 information. Humans.

32:40 Can yeah, it itself will not do anything.

32:44 I, I do want people to walk away with like knowing this AI

32:49 shouldn't be used on its own. We should always be the humans

32:53 in the loop. Well, thank you very much for

32:56 having this conversation with me, Daria.

32:59 I will leave your information in the show notes so anyone who

33:03 would like to continue this conversation, they can get in

33:05 touch with you or you can leave us a comment and we'll keep the

33:08 conversation going. Thanks for having me.

33:13 Thanks for listening to this episode of Mind One.

33:16 Maybe you enjoyed the conversation.

33:18 Don't forget to follow and share it with anyone who needs to hear

33:20 it. And let's keep the conversation

33:22 going. Connect with me on LinkedIn or

33:25 leave me a comment. Until next time, stay curious,

33:29 keep exploring, and let's continue to blend our minds and

33:31 discover what's possible.