Google Cloud Speech-to-Text API (Chirp) + Gemini 2.5 Flash Non-Thinking. Treat it as a searchable index of what was broadcast, not a quotation record.
00:00:26Good afternoon and welcome to another AI central point show.
00:00:30We continue with a new series of episodes in the second half
00:00:33of the year. Today's topic will be AI agents, so when
00:00:37software stops waiting for commands, I have my guests with me in the
00:00:40studio today, Nenad Raca, Sio from Aduro
00:00:44Idea, and Krunoslav Kedmenec, program manager from
00:00:48due time. Thank you all once again for your Verso Altima. Hello guys, welcome to the show. First,
00:00:51a quick question, until yesterday or even today, we asked artificial
00:00:55intelligence something and it gave answers. This year,
00:00:58we are starting to give it tasks. Are you ready to
00:01:02let software do something on your behalf,
00:01:06maybe even without asking you beforehand? Yes,
00:01:09we are, it's already safe enough, ready enough.
00:01:12Okay, great. We'll come back to that. Kruno, yes, we're doing
00:01:16that right now. You're already doing it, that will be very interesting, I think, for many
00:01:20listeners who are thinking about it. So, we already have people in Croatia who
00:01:24without problems, with full confidence,
00:01:26use agents. I actually wrote some articles about agents
00:01:30even two years ago and predicted that 2024, 2025
00:01:34would be the year of agents. I miscalculated a bit, it seems it's only
00:01:372026. And today everyone is talking about agents,
00:01:41uh, but what are agents really? What is it really, and how would
00:01:44Nenad describe the difference between a chatbot, automation, and
00:01:48actually a true AI agent? In fact, that is the most important difference, a chatbot
00:01:52answers a question, mhm, automation always does the same
00:01:55established job and there are no changes, and an agent
00:01:59"thinks" in quotation marks, it thinks, makes decisions, knows when it can
00:02:03do something and when it needs to hand over that job to a human. So, it has a certain
00:02:07level of responsibility and decision-making in all of that, mhm, mhm. Is
00:02:10an agent actually a new technology or is it
00:02:14a new level of trust we have in an already developed technology? How much
00:02:18has that change happened? That's actually the most important part, that new level of trust.
00:02:21The technology is not that new, all these parts that we are inserting
00:02:25have already existed for several years, but now we have shaped them so that we can
00:02:28truly trust them. That is, to establish mechanisms
00:02:32of trust and verification of all these agents. In fact, with
00:02:35agents we are opening a new dimension where they actually become our new digital
00:02:39employees, mhm, mhm, well yes, an agent should be seen
00:02:43as another interface between a human and
00:02:46a computer, mhm. So you no longer have a keyboard, or if we go to
00:02:50a higher level, you no longer - you write a specification
00:02:54then someone translates it into computer language, no, you now directly
00:02:57communicate with the computer and directly give it... a task. So, that's
00:03:01your intern. How did that process actually go
00:03:05in Versus Altima, and did that moment happen where you said, "Okay, this is no longer
00:03:09just a tool, this is already an agent with a certain level"? Did
00:03:12that happen? Was it a process that lasted? Uh, well, in principle,
00:03:16last year we started individually using
00:03:19AI for something we were dealing with, for some documents, for
00:03:23some review of some contracts, similar things, but those were
00:03:27islands, it was exclusively communication.
00:03:30With this
00:03:33LLM, then we analyzed what it needed to
00:03:36be, and for us, Aduro, when we
00:03:39went to try if we could use
00:03:42AI for cyber, they were the first to come
00:03:46with an agent, and it was like, "Wow, it works!" And that was the
00:03:49moment, that was even before Anthropic released it commercially.
00:03:53And the moment Anthropic released a personal
00:03:57agent, that's when it became real.
00:04:09where agents within the company already did the work from beginning to
00:04:13end, so redesign of some corporate pages, but can
00:04:16you walk us through what the agent did, what the human did? That's really
00:04:20a beautiful example where almost anyone can do it.
00:04:23Agents really like
00:04:26uh examples, mhm. This is great, you take an agent and say:
00:04:30"These are our corporate pages, this is how I'd like them
00:04:33to look." Great, then an interaction begins, which is, let's
00:04:36say, more or less something like a chat, ideas
00:04:40are developed and the agent makes a plan on how
00:04:43we will implement it. Okay, that's given to another agent,
00:04:46it codes it, then it's transferred to WordPress.
00:04:50That was very interesting, because a colleague gave the agent to transfer it to
00:04:54WordPress, but it wasn't right. Then he kept reporting, "No, this is not
00:04:57good, change this," and then he got frustrated.
00:05:12business. Perhaps it's also worth mentioning that we're organizing an artificial intelligence conference
00:05:16for entrepreneurs in Rijeka. As an entrepreneur,
00:05:19I'd like to know how long that process with agents took, for example, and how long it would have taken without
00:05:23agents if only people had worked. What's the time saving?
00:05:27Even more than 10 times, I would say that
00:05:30days are minutes and weeks are hours.
00:05:34Aha, so what you used to need to do for several weeks,
00:05:37have meetings, talk to people who would create
00:05:41graphics for you, you would make... icons, you would check all
00:05:44texts, that literally took a few days, maybe, maybe the biggest
00:05:48benefit isn't just time, but the fact that we suddenly have the capacity
00:05:52to, instead of just working, to talk a lot and decide what to do,
00:05:56we make those five versions, look at which one is the best, and practically choose immediately from
00:05:59some choices that were made very quickly and efficiently, which are complete, which are not
00:06:03theoretical ideas, meaning they are not prototypes but practically functional, in this
00:06:06case, websites. So, I say, I think many UGP members
00:06:10will be more interested in hearing this.
00:06:12And about that, Nenad, let's go back to Aduro Ideje. So, it has experience and has been working
00:06:16with agents and actually with agent operational
00:06:20centers for some time. Uh, what is that actually? How do you explain
00:06:23it to someone who is not from IT, and again, let's go back to some of your
00:06:27examples, 10 times is a huge saving, so practically 90% of time is
00:06:30saved. Does that match your experiences? Well, my experience is actually a bit less,
00:06:34but because of this part of playing around, where suddenly everyone has the opportunity to play around, or I don't know,
00:06:38sometimes when we were developing software, we always talked a lot at the beginning before we started
00:06:42doing something. And now we allow ourselves to
00:06:45start working on different versions and see which one will be the best for us. So, we have a bit
00:06:49more wasted there, but the improvement is still significant in that
00:06:52whole story. What you mentioned about what
00:06:56an agent system is, that's actually perhaps best explained if
00:06:59we consider agents to be digital employees, mhm. The entire operating system for
00:07:03them is actually their building within which they work, with their rules,
00:07:07like every company has its own additional company for
00:07:10digital people, for digital agents, who work for it, in
00:07:13which physical people can enter, can supervise it, can see what
00:07:17works, how it works, and create new agents in it,
00:07:21mhm. That's maybe now such a thing, until now we all looked at who has what
00:07:25employees, how many employees they have, how they are organized, now we will
00:07:28have a new sector that will look at how many employees there are,
00:07:32what they are like, how they are organized, how they work, how efficient they are, how
00:07:36accurate they are. Yes, I mean, that part sounds fantastic, although it still seems
00:07:39a bit abstract to a very large number of people in Croatia. So we will definitely come
00:07:43back to that. But here's a question for you, and possibly for Kruno.
00:07:46So, where is an agent used in an average
00:07:49Croatian company, or where can it be used to be actually
00:07:53most efficient, and where are these not some spectacular applications? Well,
00:07:56I mean, there are a lot of these trivial ones that everyone pushes first, like customer
00:08:00service, those are something that are very easy to explain to everyone,
00:08:03easy to understand how it works, but maybe there's that part that everyone
00:08:07forgets, they use it very often, that's the part of some kind of advisor
00:08:11in some decisions. "Aha, where we start inserting some
00:08:14documents, we are actually creating a new
00:08:17advisor with whom we can discuss some topics where
00:08:21sometimes people in the company may not have the right interlocutors, so they sometimes looked for them
00:08:25outside, now with an agent they can have an interlocutor with whom they can do that,
00:08:28analyze documents, analyze decisions, try out some
00:08:31scenarios or any such things. A concrete example, you have
00:08:35a big project with many subcontractors, main
00:08:39contracts, contracts with subcontractors, give..."
00:08:42the agent to read all those contracts and say:
00:08:46"Here you covered, this you didn't transfer,
00:08:49so no, that's not, that's not a lawyer, but it
00:08:52immediately gives you insight, especially agents are very good when it comes to
00:08:56compiling information from different sources, and of very high quality.
00:08:59We actually had an episode on artificial intelligence in
00:09:03law some time ago, and people who work on specialized systems for artificial
00:09:07intelligence in law also testified to us. So, we can always refer
00:09:10to that episode. Some people complain again, so I have to ask you,
00:09:14are we at a stage where agents save us time, as you said, or do they somehow
00:09:18create new work for us in the sense that someone still has to supervise those
00:09:22agents? Uh, I don't think that supervision is the problem
00:09:26because it's in principle like, uh, how would I say, when we had
00:09:29computers, when they came, we all became
00:09:33secretaries, everyone, we all started doing that administrative work, and
00:09:36actually, the jobs of secretaries didn't disappear, but we all became our own
00:09:40secretaries. What we are becoming now,
00:09:42we all are actually becoming managers, because we all now get our digital teams
00:09:46that we start managing. So, when you look at it that way, it's not
00:09:50taking away jobs, but it's actually defining some new roles for people
00:09:54who perhaps weren't ready for them until now. Yes, no, the question is whether it creates new
00:09:58work, because now you have to control some agents that you didn't have
00:10:01to control before. But my experience is that the scope of
00:10:05work around that has not increased, that overall we are gaining, the type of work has changed, because
00:10:08we are doing more work than controlling someone or some people who are doing
00:10:12the work for us. And people who have uh, managed
00:10:16infrastructure until now, first they managed infrastructure at
00:10:19their company, now they manage the cloud, those same people will manage
00:10:23the agent infrastructure. They will make sure everything works, that not too many
00:10:27tokens are spent, that everything functions. But we can imagine,
00:10:30building on what Nenad said, so an AI agent as
00:10:34an advisor to the board, for example, someone who will help in decision-making, I think
00:10:38that's a very interesting part and I agree, often, often neglected, but
00:10:41potentially very good. But okay, mm, I would like to
00:10:44ask Kruno one more thing, you have a very interesting project,
00:10:48so AI for Cyber is a research and development project for
00:10:51specific cybersecurity. A topic very dear to me, that's why we had
00:10:55one episode specifically dedicated to it. So, it
00:10:58is carried out with European Union funding, you managed to get that. What problem did
00:11:02you want to solve with agents? The problem is, so one of the things that
00:11:06Verso Altima does is cybersecurity,
00:11:09mhm. This is not just about IT systems,
00:11:12but also control systems for smart cities
00:11:15and control systems for industry and similar things. And
00:11:19there you have today's software, today's
00:11:22methodology is pattern recognition. Mhm, you constantly
00:11:26maintain uh a database
00:11:29of patterns of some events, it
00:11:32recognizes and gives it to an expert for evaluation to see
00:11:36if a reaction is needed. Unfortunately, there are a lot
00:11:39of false alarms, a lot of things
00:11:42where a pattern is recognized, but we know that someone is testing something.
00:11:46What we saw, as I said, that "wow"
00:11:49moment, we gave the then cobbled-together
00:11:53agent just to go, mhm, into a bunch of logs and it started
00:11:56spitting out things we hadn't even thought about.
00:12:00So we are moving from pattern recognition to anomaly
00:12:04recognition, mhm. Is something happening that doesn't usually
00:12:07happen? Have I started logging in at two
00:12:11in the morning and missed my password 10 times? Mhm, mhm, I have to
00:12:14ask right away, actually, it reminds me of some examples from other industries,
00:12:18how much time was actually lost until now on sifting through those
00:12:21false, you know, false alarms?
00:12:25And actually, how much did an agent then accelerate that and
00:12:28save time? The approach actually changes here, because the previous
00:12:31approach was to look for something, and here
00:12:35the agent looks for anomalies in everything that behaves. And the most
00:12:39important thing is that maybe people, when they looked at it,
00:12:42there was always a problem that we looked at certain different sources. Here, with agents, we can already
00:12:45look at the connection between totally different sources that occur at a certain
00:12:49time, which may have some cause-and-effect relationships. So,
00:12:52when something is hidden or concealed within
00:12:55some other events, I assume it's more efficient. Yes, for example, another
00:12:59big project we are working on is the use of agents for
00:13:02monitoring huge telecom networks. Aha, you have very
00:13:06trivial situations where somewhere in Split you have one
00:13:09device that has an old version of
00:13:12firmware. And how do you find that? So, you look for what Nenad said, you look for
00:13:16a pattern, no, you just let the agent go, tell me what's wrong, and
00:13:19it will just say in Split there's a device
00:13:22that has old firmware. Do you want
00:13:25me to upgrade it? Yes, that's what now, will you let
00:13:29the agent do it? Today he asks, today he asks you. I think that
00:13:33example will interest many companies, like where do we all have to upgrade companies, no.
00:13:36Yes, absolutely. Great, Nenad, but what happens, let's
00:13:40go back to that topic for a bit, if attackers use agents for some
00:13:44cybersecurity problems, does the speed of the attack actually change,
00:13:48how important is human defense there, does a human even have time to react or not? It's not even
00:13:52a question of maybe how fast it is, but how inventive it is, mhm.
00:13:56Right? A new level, that's a new level, because until now, that part of
00:13:59invention was special specialized people who had a gift for finding
00:14:03such things, and
00:14:06now with agents, or swarms of agents, that means we are no longer talking
00:14:10about one agent, we are talking about hundreds of them who can
00:14:14act simultaneously, who communicate with each other, who can carry out
00:14:17very simultaneous and diverse attacks and diverse
00:14:20testing of different things. So, uh, we currently in the company know
00:14:24how to use uncensored models to
00:14:27test the security of our applications. So, instead of doing
00:14:30the traditional testing of applications to see if they are secure enough and
00:14:34all that, we let an agent who has permission
00:14:38to attack the application, to test what it can do on the application, because
00:14:41simply, a new pattern will happen here and new patterns are happening, new things that
00:14:44they do. Yes, that innovativeness is always a specially interesting
00:14:48question. It's interesting to mention in this context that just these days, information came out from
00:14:52Open AI that with the latest model, they managed to solve one of
00:14:56extremely difficult mathematical problems,
00:14:58and in that way, again, to suggest a completely new type of
00:15:02innovativeness and knowledge, so let's hope it won't reflect in all these
00:15:05cyber security and other problems. I think
00:15:08it will, right? My colleague, a physicist who
00:15:12uses AI in this whole story, he said just recently that
00:15:15he was getting
00:15:19such solutions, meaning he uses AI very intensively in his work,
00:15:22meaning that he gets solutions where he sometimes
00:15:26has to think hard about the approach that AI took, and which in the end very often
00:15:29turns out to be very good, but at first it wasn't visible to him at all, mhm, that's the
00:15:33thing, how AI helps us find inventive approaches
00:15:37to something, anomalies in fact. Let's then stay on that risk for a second.
00:15:41So, today still a small number of companies use agents, but I'm sure
00:15:44that will increase, especially after they hear you, a larger and larger number, but
00:15:48then we ask ourselves, what is that part of the risk, because if we use some agents, we have given them
00:15:52access to our data, to some decision-making, how risky does that actually become
00:15:56for us, is that something companies should be afraid of?
00:16:00I mean, they should be afraid of it like anything else, uncontrolled,
00:16:03unorganized access brings problems. If it's approached
00:16:07intelligently, organized, so that you know what you're doing and what
00:16:11you're managing, what rights are given, because it's not a problem if
00:16:14the agent has the right to do what it needs to do, but if it
00:16:18doesn't have the right to do what it needs to do, it won't do the job. If it has too many
00:16:22rights, it might do too much. So it's the same thing as
00:16:25people, you need to look at its experience, gather experience in
00:16:28management and then accordingly give rights, manage rights. Fire
00:16:32is a good servant, a bad master, the same
00:16:35applies to agents. If... "As Nenad says, you know very well
00:16:39what you're doing, how you're doing it, what rights you're assigning, there are no problems. If
00:16:43you just let it go, you've thrown a match on dry grass and everything
00:16:47is gone. Okay, but who's to blame for example if an agent deletes
00:16:50the wrong email or sends the wrong offer or so on? The organization
00:16:54and those who defined the processes. The software cannot be
00:16:57blamed, because the software does what it is allowed to do. So no agent will ever
00:17:01do anything outside of what it is allowed to do and what is defined
00:17:05as its task, but it will try with all its might to complete
00:17:09those incidents that are talked about a lot. It was given the task to
00:17:13do it and they watched how it would do it. It surprised them, it surprised them
00:17:16how it did it, that's the speed, that means the speed
00:17:20at which it can happen, that's the inventiveness and speed at which it can
00:17:23be created. Yes, I think that's a special question that we probably
00:17:26won't go into today, but for example, when we have many agents on both sides,
00:17:30well, maybe it's not a bad context for my next question. So we researched
00:17:33human in the loop, hopefully an article will come out soon
00:17:37on this topic, when a human is important in the loop, when they are necessary, and when they are actually
00:17:41unnecessary or impossible to do, because as a human approving something,
00:17:44we can do, look at 10 things or maybe 100 things or a few hundred, but
00:17:48if it's about 10 thousand, 100 thousand, a million cases that we have to, the
00:17:52human brain simply cannot process it. Uh, what are
00:17:55your thoughts on this? Well, you need human in the loop, that is, a human in
00:17:59the loop, meaning where the human is, I mean, purely so that we don't have them just for formality, that is,
00:18:03that's important, you don't have them for formality, but really where they are needed, so really tasks
00:18:07where the crucial thing is that something happens, that
00:18:10something is done, but there must always be some mechanism so that
00:18:14it is done, because there are many cases when a human will be
00:18:18put in the loop just to perhaps avoid some legal
00:18:21responsibility, so it's like he will be to blame, he didn't look, but if he clicks 10 times
00:18:25he will click 11 and 111 and 1011 then the human
00:18:28will become an automaton, he will become automated, we have actually made a robot out of
00:18:32a human, mhm. What I say is, last week I
00:18:35was talking to colleagues, I pointed out where the bottleneck
00:18:39is in using AI. Yes, I
00:18:42can no longer keep up with how quickly it can analyze,
00:18:46suggest, ask a ton of things from
00:18:49different aspects, I physically can no longer
00:18:53keep up with it. So not just approving, but also the work itself with
00:18:56an agent that is too fast for us. I've heard that from multiple sides, exactly
00:18:59that experience. Then the question arises, so on
00:19:03one side we have an AI that requires human supervision, and then
00:19:07we ask ourselves, is that feasible in practice or is it just some words on paper where I was
00:19:11told that a human is responsible on paper but actually
00:19:14doesn't have the ability to do it because it's a bottleneck? Yes, but again, for that we need to know how it works,
00:19:18so there again we come back to the standard thing, enough testing, where again
00:19:22AI agents can help us because we can use AI agents to test AI agents.
00:19:25So what we said, if they can do some attacks, they can
00:19:29do anything else. An AI agent can test an AI agent and
00:19:32find ways, or problems, in behavior, points
00:19:35where it is necessary to insert truly justified human
00:19:39supervision, and you learn from it as you work with it. So all this that
00:19:43I'm saying, I can't keep up with it, but every iteration it understands better and better,
00:19:46in the end it no longer needs me. That's it, that's the
00:19:50moment when I let it do what I assigned
00:19:53it to do, but we solved it until then. My experience is that it takes
00:19:57about a week of talking and changes. Yes, I think that's the crucial
00:20:01part, that agents actually learn from us, and my experience lately is that I'm
00:20:05playing with an AI second brain, so it's a system that's developing, that has multiple
00:20:09agents connected, it constantly learns from me, collects data, so I assume that will
00:20:13also be one area that I plan to, let's say,
00:20:16deal with educationally, meaning helping people create all their
00:20:20second brains that will help them, that will learn from them and actually help them be
00:20:2410 times more efficient or even 100 times more efficient. But here we need to take into account,
00:20:27these are personal agents, right? A second brain and such things
00:20:31serve me personally. If we move to a corporate level for
00:20:35company use, then that approach no longer... because then
00:20:38uh, we cannot, we must not let someone, you know, "contaminate" the memory, the memory must
00:20:42be controlled. So access to memory in the corporate world and in
00:20:46the private world is totally different, and that is the one thing that I hope people won't
00:20:50make the mistake of trying to use private agents
00:20:53and what works well privately in corporate environments. That is good, it means separating my second brain and
00:20:57as an agent as my private multiplier of my efficiency, which
00:21:01is a fantastic thing, and corporate agents that are made and
00:21:05controlled differently and so on, great, that's an important thing for, yes, that's my
00:21:07experience, I have to separate private
00:21:10things, so if I'm looking for LED lighting for an aquarium, that shouldn't
00:21:14be part of the AI for
00:21:17Cyber project, those are two different contexts, because at the beginning, until I hadn't mastered
00:21:21those skills, then I would get strange answers, then I realized, well, yes,
00:21:24I asked it something silly within the same context and now it
00:21:28concludes that I need an aquarium for AI. Great.
00:21:31Great, let's then give one more, maybe, practical advice to
00:21:35viewers. A company comes and says, "I want an agent," we got
00:21:38interested, that sounds great. What do they first need to have, how do they start that process,
00:21:42that maybe has nothing to do with artificial intelligence? Well, first they need to have a clear idea of what they want to
00:21:46do. Okay, the second thing is they need to make a decision that they want to change the way
00:21:50they want to work, because implementing AI into
00:21:53a company without changing the way the company works is doomed to
00:21:57fail, mhm. So those are all projects that fail, they fail because
00:22:00the basic work process hasn't changed. The basic work process
00:22:04must change, because AI is not an addition to the process, it's
00:22:07an evolution of the process itself that starts working immediately after that. Then only
00:22:10then do we move on to technology and everything else.
00:22:12That's perhaps the most important message. So my background is IT, but
00:22:16AI doesn't belong to IT, yes, it's clear, did you manage
00:22:19to change processes and mindset within the company? My advice is to get
00:22:23a personal AI agent that will guide you through this process that Nenad
00:22:26talks about. I know some people who have done that and are very satisfied with it, I must
00:22:30say, even at the level of personal development, what insights
00:22:33they gained about their functioning and behavior. How much does it cost to get into
00:22:37such projects at all? How much does it cost to get into it if you approach it smartly, how much
00:22:41does it cost if you approach it the wrong way? Let's start with this one, if you approach it the
00:22:44wrong way, there are those penalties that are there for GDPR European Air.
00:22:48act, that's how much it costs to enter. in the wrong way, that means that's the
00:22:51ultimate price to pay in all that, plus lost time, plus
00:22:55lost reputation, plus everything else, to enter in a smart
00:22:58way, we can already for a few thousand euros, mhm,
00:23:02meaning these are not some abnormally expensive projects, abnormally expensive projects, meaning the important
00:23:06thing about it is that these are no longer projects, meaning it's not something that is
00:23:09created from scratch, there are ready-made things that exist, that work, that
00:23:13can be tested, because uh, I don't know, in our approach we always
00:23:17give people access so you can... try it, you can
00:23:20get a demo, you can see how that thing works before you decide
00:23:23to implement it, we don't have to enter into risky projects, let's enter into
00:23:27something small, a small process, but we provide support
00:23:30on how to redesign such things, not just, let's
00:23:34push AI into the process and then everyone who does something will have their own
00:23:37AI assistant who will ask something, because realistically, then they haven't sped up their work, I hope you
00:23:41entered that project wisely, uh, of course, first
00:23:45start with something you know well, mhm, mhm, so you can
00:23:49assess. whether what the agent writes to you, whether
00:23:52that I often pretend to be stupid when
00:23:56I talk to him, I deliberately won't tell him I want to test how he understands
00:24:00and I want to see what all I have to tell him, explain what
00:24:03documentation I have to give him so that he gives me a quality answer, so that
00:24:07he can determine the job, meaning start with something known,
00:24:11that's why I said websites
00:24:13issuing invoices review whether there are any unpaid
00:24:16invoices in the entire Excel database. you have some
00:24:20unpaid invoices, financial analyzes, some automatic reports
00:24:24so there's a whole range, super, great, we will continue to explore this,
00:24:28but for example, you are definitely, and the companies you work with, and the clients, you are
00:24:32some early adopters. We always have those who need a little more, who are skeptical
00:24:36about uh what is happening, what is developing, what would you say to a
00:24:39director who says let's wait another year for
00:24:43it to settle down a bit, then we'll see and maybe introduce an agent.
00:24:46Uh, the biggest, biggest problem you can make in business
00:24:50is not following what's happening, or waiting
00:24:53too long, mhm, and not trying things out. So, nobody says
00:24:57companies have to absolutely implement it in their business right now, but
00:25:01they have to start using it, but not in a way where we ask the chat and
00:25:05the chat answers something, but let's try to test some processes,
00:25:08see, we have the opportunity to learn. The technology is
00:25:12new, there's still no one who uh can say with this technology you can
00:25:15definitely do this, this, this, and you definitely can't do this. We're all
00:25:19trying things out here. So it has to be tested, we're all testing, we're all trying, so all
00:25:22the time spent delaying is wasted learning time.
00:25:26Those who start in half a year have already lost half a year of learning,
00:25:29those who start in a year have lost a year of learning, because transforming
00:25:33a company, what I mentioned, changing the way a company functions
00:25:37is a prerequisite for implementing AI, or
00:25:40AI agents, or digital employees, opening new departments, new
00:25:44things in the company itself, how it will work digitally, meaning these are no longer
00:25:48digital software, these are... digital employees, meaning he gives
00:25:52complete work and results, has control and supervision over him,
00:25:55super, similar processes as it was with,
00:25:58office digitalization, when we switched from paper.
00:26:02mm to computers, to printers, to networks, meaning
00:26:06to make a transformation that you know, you have to see what the
00:26:09possibilities are, as Nad says, learn what you can do with
00:26:12agents, then make decisions, hey great, an agent would help us
00:26:16greatly here and start there. Oh, great, I can only
00:26:19say how lucky we are who deal with education in artificial intelligence.
00:26:23Uh, guys, thank you very much, we will continue this conversation in the AI second point which will
00:26:27be broadcast on YouTube. I will conclude
00:26:29this broadcast about agents, they are an extremely interesting
00:26:33topic, mm, we will surely return to it, and we plan to cover
00:26:37other interesting topics such as artificial intelligence in marketing or artificial
00:26:40intelligence in the defense industry, and artificial
00:26:43intelligence, perhaps even in religion or journalism, but
00:26:47you will find out about all that in
00:26:50attention until the next AI Central Point
00:26:52broadcast!
00:27:20Every new school year is a new beginning. Let this
00:27:24one be a little more carefree, with Telemah Kids Watch with
00:27:27audio and video calls and precise GPS location.
00:27:31Stay connected. Smart kids' watch and junior
00:27:35tariff for less than 10 euros per month, no cheap
00:27:38slogans, just a good offer.
00:27:41Telemah. The global economy is entering
00:27:44a new era. Geopolitics, technology
00:27:47innovations create a new map
00:27:50of capital. Where are the opportunities for Bosnia and Herzegovina
00:27:53and the region? Answers and new perspectives. We are looking for them through
00:27:57ideas, investments and partnerships. New
00:28:01economic reality. Horizons of Capital, Asa
00:28:05Bank in cooperation with Forbs Adria, October 1,
00:28:082026. Swissotel,
00:28:11Sarajevo.
00:28:14Do you think it's easy to get into Podravka
00:28:17products?
00:28:21You have to be much better than the competition.
00:28:24Congratulations, you got the role, but
00:28:26we admit, the most important thing is origin. Because
00:28:30with us, the main roles are only given to originals from
00:28:34Croatian fields. Domestic
00:28:36in the main role. Podravka.
00:28:40Let's go to school smarter. Choose Samsung Galaxy devices
00:28:44with the Unlimited tariff for a new school year full of learning
00:28:47new possibilities. For savings, use the "pay less then trade in"
00:28:51model and 30% discount on
00:28:54Google AI pro plan. Let's go to school smarter.
00:28:58Croatian
00:28:58Telecom.