Christian Martinez - How Finance Can Augment Intelligence using Generative AI
Updated: Apr 12
Episode -18: In this episode, Christian Martinez, Finance Automation Manager at the Kraft Heinz Company, shares his insights on embracing AI in the world of finance. We explore the use of generative AI like ChatGPT alongside traditional automation tools like Alteryx, Tableau, and Snowflake, and discuss how Python programming is becoming increasingly accessible for finance professionals.
Christian also sheds light on the decision-making processes behind choosing AI tools and how focusing on fundamentals can lead to better results. From machine learning algorithms for forecasting to web scraping for pricing strategy, and automating tasks in Excel and PowerPoint, we delve into the myriad of applications Python has to offer. We also discuss the potential growth of single-use applications, the importance of soft skills like storytelling and stakeholder management, and much more. Don't miss out on this captivating conversation with Christian Martinez!
Audio Podcast Links
Where to find Christian:
Medium - https://christianmartinezfinancialfox.medium.com/
LinkedIn - https://www.linkedin.com/in/christianmartinezthefinancialfox/
- Alteryx: https://www.alteryx.com/
- Tableau: https://www.tableau.com/
- Snowflake: https://www.snowflake.com/
- ChatGPT: https://www.openai.com/chatgpt/
- Python: https://www.python.org/
- Google Colab: https://colab.research.google.com/
- Jupyter Notebooks: https://jupyter.org/
- Cody: [Website](https://getcody.io/)
- Dedupely: https://dedupe.ly/
- Blinkist: https://www.blinkist.com/
- Glenn Hopper: [LinkedIn](https://www.linkedin.com/in/glennhopper/)
- Zane's Superhuman Newsletter: https://superhuman.beehiiv.com/
- "There's an AI for That" List: https://theresanaiforthat.com/
[0:02:55] Automation and Generative AI for Global Teams
[0:04:59] Benefits of Chatbots and Automation for Business Process Improvement
[0:07:12] Use of Python in Finance
[0:14:04] Machine Learning Tools for Python Script
[0:15:51] Discussion on Low-Code Tools for Business Knowledge Management
[0:20:10] AI and Automation in the Finance Industry
[0:25:58] The Role of Hard and Soft Skills in the Age of Automation
[0:30:23] Exploring the Benefits of Entrepreneurial Thinking and Data Democracy
[0:32:16] Exploring Disposable Apps and Tableau
[0:36:21] Conversation Summary: Exploring the Benefits of Chatbot Summarization
(0:00:03) - Technology in Finance (15 Minutes)
In this episode, we chat with Christian Martinez, Finance Automation Manager at the Kraft Heinz Company, about his work in finance automation and the tools he uses to help teams around the world. We discuss the use of generative AI like ChatGPT alongside more traditional automation tools like Alteryx, Tableau, and Snowflake. Christian explains that Python programming is increasingly accessible for finance professionals, who can use tools like ChatGPT to learn and debug code quickly. He shares examples of Python use cases in finance, such as machine learning algorithms for forecasting, web scraping for pricing strategy, and automating tasks in Excel and PowerPoint.
(0:14:46) - Using AI to Achieve Business Objectives (10 Minutes)
We explore the decision-making process when considering whether to develop AI tools in-house or purchase off-the-shelf low-code tools. For startups, using pre-built tools is more cost-effective, as they can focus on their core product and user base. There are numerous AI tools available for various industries to automate tasks and save time. Finance professionals should focus on fundamentals and use AI strategically, rather than trying to reinvent their entire business. For small businesses, evaluating low-code tools based on their specific needs is a more efficient starting point'
(0:24:48) - Developing Skills for Career Prospects (8 Minutes)
We dive into the potential negative consequences of AI advancements and automation in the finance industry, particularly for those in non-leadership positions. Developing a combination of technical skills, such as programming and using AI tools, is essential for augmenting intelligence and staying relevant in the job market. Additionally, focusing on soft skills like storytelling and stakeholder management will be crucial for success. As data democracy and AI tools become more accessible, it will be the quality of thought and ideas that sets individuals apart, rather than their ability to code'
(0:32:31) - Using Apps Once and Tech Stacks (7 Minutes)
We discuss the concept of single-use applications and their potential growth in the market. One example mentioned is d jubilee, an app that removes duplicate contacts from databases. We also share our favorite apps in both personal and professional contexts, such as Tabula for data visualization and Blinkist for book summaries. The conversation touches on the capabilities of GPT-3, including summarizing books and even creating fiction stories based on user prompts. Finally, we learn where to find more information about Christian Martinez, our guest in this episode, on LinkedIn and Medium'
(0:39:24) - Exploring Soft Skills and Finance (1 Minutes)
We delve into the importance of soft skills like storytelling and stakeholder management in the context of finance and AI. Additionally, we touch on the writing efforts focused on deep chatbot b d and finance topics. Looking forward to catching up in six months to see how these areas have evolved'
[0:00:00] Christian: So those are the three main things forecasting, web, scrape, bin and then automating tasks that we have been used by them for right now it has been seen by 100,000 people and generated almost 700 likes and reposit 100 and so on because a lot of people are really interested in all of these new tools, right? How to use all of these new AI tools to augment your intelligence. So let's not replace it, but just to augment it and to be basically do better analysis, better things with your time.
[0:00:38] Adam: Hello and welcome to Tech for Finance where we help finance professionals leverage technology to level up their lives. I'm your host Adam Shilton and in this episode we're chatting with Christian Martinez, finance Automation Manager at the Kraft Heinz Company conference speaker on AI and finance and founder of the Financial Fox, a project to democratize machine learning and data analytics. Christian started his life in Mexico, but has traveled the world holding jobs in places like Switzerland, Australia and the Netherlands.
[0:01:07] Adam: Christian founded the Financial Fox in 2017, before then starting at Kraft Heinz as finance supply chain and fpna Analyst in 2018 and since then he's held positions as management accountant, senior financial controller, and now Finance automation manager. Christian was also named one of the 30 under 30 in the accounting and finance industry in Australia in 2021 and won the EMEA Data democratizer Award in 2022.
[0:01:32] Adam: Christian is also a Manitan furniture and has traveled to over 65 countries. Before we start, if you like what you hear today, please make sure to subscribe to Tech Finance on your favorite podcast platform and on YouTube. So thanks for joining me today, Christian. It's great to have you on the show.
[0:01:49] Christian: Great, thank you. Thanks for having me.
[0:01:51] Adam: No worries at all. So we'll get straight in because I.
[0:01:54] Christian: Know that you don't have a huge.
[0:01:55] Adam: Amount of time this morning, Christian, but it would be good for you to take us through what it means to be a finance automation manager. I'm sure there's lots of people that are quite envious and potentially a job that's in high demand right now. Do you want to give us a bit about what you do at the moment?
[0:02:12] Christian: Yeah, definitely. So I focus in finance automation, especially in the supply chain, finance industry and function. So basically like manufacturing, logistics and procurement. And then we do the finance part of it.
[0:02:27] Adam: Right?
[0:02:27] Christian: So in our company we have two international tunnels. One is the US and Canada and the other one is the rest of the world. So I'm in that second one of the rest of the world, which means basically that my scope is around 22 countries, more than 40 factories, more than 30 warehouses, like different teams around the world. And the idea is to help them define their teams around the world with analytics and automation.
[0:02:55] Christian: So what exactly do that? Well, we use a series of different tools like Altrix, Tablon, Snowflake and more recently Chat GPT to try to automate different processes across the world and basically to give time back to the business to do more and better analysis.
[0:03:18] Adam: So you mentioned chat GPT there. We'll come back to that in a second. I think as some more of these tools evolve with the likes of Bard, still not great yet, and Bing Chat, we might in the future need to refer to it as Generative AI. Right. For now, obviously, everybody knows as Chat Dpt. Thanks for outlining some of the tools there, which you mentioned are analytics tools, right. The first question I have on the Generative AI side of things with the advent of these new AI technology is previously you might have some sort of robotic process automation platform to either connect data or automate the clicks that a human would do.
[0:04:04] Adam: How are you finding that's different now? Because Generative AI isn't. And if this then carry out this task, it's more of I'm seeing it at the moment more aligned with soft skills rather than automating hard stuff. So I don't know what your perspective is.
[0:04:21] Christian: Yeah, and it's actually very similar to what you said right now. For the automation automation part, we are still using Alteryx, for example, that basically carry all of the tasks and it's like, okay, we push a button or something like automatically every day, every month or something, and then all of the script occurs and then different functions happen. But then we use mostly right now, since I chatted with team, just as you said, to ask questions about how to improve certain process or to learn about certain areas of the business or the world, even the supply chain, let's say.
[0:04:59] Christian: And then to really get more creative on our solutions in terms of both analytics and automation. So some use cases, for example, is like sometimes we are still trying to use, let's say, Python to do different things apart from all of the other tools I was mentioning. So then, now with Chat, it's very easy to just go and then you describe what you want to do and then it generates the Python code for you. So then you tweak it maybe a little bit, but it's basically there, right?
[0:05:32] Christian: Or we already have, let's say some Python codes and then we have some mistakes or some mirror or something. You can also put it in JAVD and it tells you where exactly the mistake and how to fix it. So we are trying to combine these technologies, but for sure we're not using JAVD Yacht for the automation part as much.
[0:05:53] Adam: But there has been recent updates to say that Openi are moving towards plugins for Chat Dpt, right. This has made the ecosystem even bigger, right. So instead of now speaking to a chat window or using the API as a developer, would you've now got more of a Zapier type set up whereby you can say right, well, Chat GPT interact with this app and interact with this app. So I think it's going to be really interesting to see what way that goes and it's fab. So going back to the point there that you mentioned about Python.
[0:06:25] Adam: So obviously you work in a larger, very large organization, and I'm always keen to tease out some of the things that may be more usable for smaller businesses. But before I ask you that, I guess the first question is there is always a topic of conversation in finance teams about upskilling. What skills do we need to focus on whether it's hard or soft? So of course, there's endless posts on LinkedIn about improving your Excel skills. There's endless posts about all sorts of other finance specific skills that people might upskill. But more recently, I have heard talk of finance teams wanting to get more up to speed with development languages and taking more control over a code piece.
[0:07:12] Adam: Now, obviously, traditionally to learn Python, you'd need to be a developer and maybe have your 10,000 hours worth of experience in doing that. And I know you've got that because obviously you've done quite a lot of work with Python. But are we seeing now that with sort of a basic nursing in Python, you can use tools like Chat GPT to basically correct from scratch? Or do you still think there's a really big gap between businesses being able to do that if they've got no development knowledge?
[0:07:39] Christian: Yeah, to be far. Ever since I started learning Python, maybe like four or five years ago, I realized that learning Python is very easy because it's very close to the human language, to three image. So then it's way easier than learning other things like C plus plus or Java. Whenever I started that phrase that you were mentioning, the financial tax, the whole idea was to democratize the access to using Python for finance professionals. And we taught them very simple workshops step by step.
[0:08:18] Christian: And the same design defendants, professionals that do the workshops, they really started to use Python within weeks. So you don't really need those 10,000 hours for that specific programming language. Now, having said that, maybe you needed like a couple of weeks, so maybe two weeks doing a couple of projects and then you could use Python at least for basic stuff and even for more analytics soft. Now with JPD, that become hours because now you can really even use judgment to learn Python and also to do the whole code in part for you. As I was saying before, if you have mistakes to tell you where the mistake is and even to explain the code after it does it for you, you say like, okay, what exactly is this doing this doing? And then it explain for you. So then now those couple of weeks that it will take you to learn Python, to do it in finance now, it will be done in one day.
[0:09:17] Christian: So it helps reduce a lot. But, yeah, I did want to mention that at least, like the way we used to write up the financial fox, you didn't need the 10,000 hours, you needed just a couple of weeks tonight. Yeah.
[0:10:07] Adam: But it's all about asking those questions, isn't it? Because there's a difference between saying, generate me the code for this, and then pretend I'm an idiot, generate the code for this and tell me how it's all broken down.
[0:10:22] Christian: Yeah.
[0:10:25] Adam: Finance teams maybe aren't as up to speed with what you can do with a language like Python. What are some of the use cases that you're seeing for being able to program with that sort of language?
[0:10:38] Christian: One of the main use cases that use it is for machine learning algorithms. So basically for forecast things in the business, it can be like sales, it can be like layover, spend. It can be basically how much inventory do we need and so on. The second part is for web scraping. So basically to go on the web and then just retrieve data, let's say prices in Tesco supermarkets or Albert supermarkets here in the Netherlands, and then to understand what's the price of each item, for example.
[0:11:12] Christian: And then create like a sales model to generate which is the best price to optimize the pricing strategy, for example. Now, the third one that is especially for people that still are using a lot of Excel PowerPoint is basically to automate different tasks of, like, okay, before some of people in Apna, they go to Excel, they create a model. There's Excel table in there, and then they have to copy and paste that in PowerPoint. And maybe they that like 50 different times every day. So with Python, you could automate that speed and they're like, okay, whenever something happens, then basically it will do that copy base of that table automatically for you.
[0:11:54] Christian: So those are the three main things. So, like forecasting, web scrap, bin and then automating tasks that we have been used by them for.
[0:12:07] Adam: But it is reliant on you having access to data in the first place, right?
[0:12:14] Christian: Yeah, correct.
[0:12:15] Adam: I'm going to need to connect it to a data source for that plan.
[0:12:20] Christian: Yeah. For these three specific examples, the forecasting part, for sure, you do need the data. The data part for the web scraping, then it basically grabs the data from all of the websites. And the third one on the automated tasks, you don't really need data, but you do need a task to be done. But for the version of machine learning, for sure you do need data. And that's one of the things that takes the most amount of time and the most important parts to generate, let's say a good forecast.
[0:12:56] Adam: Fine. And what I'll do in the show notes of the podcast is I'll include some links with some use cases and a more detailed breakdown for all of these because some of the listeners won't completely understand what web scraping is, for example. So I'll provide the links and reference material for that in the interest of time to save you having to explain in more detail because I appreciate we don't have all the time in the world here, which is which is great.
[0:13:19] Adam: So on the machine learning side of things, and previous guest I had was Glenn Hopper, I don't know whether you're familiar with the name, he's doing quite a lot of work in the AI space, especially in finance, and he sort of broke down the building blocks of starting to be able to use AI. So first is people and process. So it's pointless in trying to build an understanding if your data is rubbish. Likewise, it's pointless trying to automate a process.
[0:13:45] Adam: It's a bad process. And he gave some examples, some data tools. But coming back to that machine learning piece that you mentioned earlier, are there any locations that you're using for machine learning that you plug in your Python script into?
[0:14:04] Christian: When you mean applications, let's say like.
[0:14:06] Adam: A web application, that algorithm or whatever it is.
[0:14:12] Christian: Okay, yeah, it's more like, let's say you can generate the algorithm by using Python and writing the code there. But then you do need a tool to run that algorithm. So one of the easiest ones to start with is from Google and it's called Google Cold app. That is basically like a Wall Street but for coding. So then you go in there and then you type your title script and then it run it for you. And then either it generates new data, for example, or it automates task, for example, or something.
[0:14:50] Christian: So that's one of the web apps that it's used in conjunction with Python. The other one is, let's say there's another one called Jupiter Notebooks that is basically the same thing. It's like a notebook wherever you block your code and then it will run it for you.
[0:15:12] Adam: Google colab and Jupiter's node groups.
[0:15:16] Christian: Yeah.
[0:15:17] Adam: Node groups. Okay, fine. I'll put those in the Show Notes as well. So thanks for that. And in your view, one of the positive things about AI is it's now becoming easier to develop, easier to use tools. So from your perspective, if a finance is looking at a problem and thinking, right, do we either bring in somebody with experience in Python or learn Python ourselves with the help of chat GPT using in the example of machine learning stuff like Google colab and the other one that you mentioned.
[0:15:51] Adam: Or do we just buy an off the shelf low code tool because there's tons out there now. So what is your mentality when it comes to picking your battles? Essentially? What is that decision criteria?
[0:16:06] Christian: Yeah, that's a very good question and especially when you mentioned that you are trying to do a lot of advice also for startups, right, for smaller companies. I do think that for startup companies is better to go with the off the shelf tool that it's already built. And then, as you said, normally the pricing is not that much. There are some that, okay, you can pay €10 or £10 per month or for a couple of months or something and it's already built for you.
[0:16:41] Christian: There's this use case that I was thinking actually even in a large enterprise of how to input all of the documents that you have on the business, all of the business knowledge, like, okay, we have these factories, we have these processes, we have these people and so on. And to use chatty for people to basically be onboarded into the business that they can use, let's say in a similar fashion to ask questions and generate the answers. So I was simulating how to do it and then I discovered over the weekend there's this tool called Cody that is basically done that. So you just upload either like Powerpoints or, like spreadsheets or documents or something about your business, and then it generates the same UI, the same user interface of Chat DBT.
[0:17:33] Christian: But then now all your information is there. And then obviously, because you want your information private and everything, you have to pay for this all. But again, it's like less than 100. Then if someone would go to develop this tool, for sure it wouldn't take €100 in terms of time of a developer or even any financial to try to get it done right. So then I do think that having these off the shelf apps already built by another company, it's really useful.
[0:18:14] Adam: That makes sense. And what did you say it was called? Cody. C-O-D-I-E-C-O-D-Y-O-D-Y okay, like ten every day, isn't it?
[0:18:27] Christian: Yeah, actually, just from that note yesterday was literally compiling this list of new AI tools for finance. And one of these was coded, but then I have a bunch of others. And then I finished the list because, again, it was for my self interest. But then I was like, okay, I'll put into LinkedIn. And then I just put yesterday. And I think right now, it's just been seen by 100,000 people and generate almost 700 likes and reposit 100 and so on, because a lot of people are really interested in all of these new jobs. Right?
[0:19:08] Adam: And I'll put the link to that in the show notes as well, because I did see that yesterday. So people can pick up on that. Another resource that's pretty good is a newsletter called Superhuman by I forget his second name, it's called Zayn, but I'll put him in the show notes as well. But there's a ton now because AI is so prolific and I think if we're not careful, we're going to get overwhelmed pretty quickly.
[0:19:33] Adam: So I think it's great to see the lists now. And I did this again over the weekend is I was looking through finance, AI tools and all of that sort of stuff. The other thing to be aware of as well is with the advent of really fast development of these concepts and these apps, a lot of them are still in pre release stage I was going through. And my use case, as I mentioned to you before we started, is speeding up the production of the podcast because I just want to spend time speaking to intelligent people. I don't want to spend time writing up show notes and writing up transcripts. I don't want to do that.
[0:20:10] Adam: So I went on this site which had a load of AI tools. I'll put that in show notes as well. I think it's called there's an AI for that. Again, there's so many. And I was clicking through all of them in the use cases and they all say, sign up to waitlist, sign up to waitlist, sign up to waitlist. And what they're doing there is they're essentially gauging marketplace interest. And I think the general rule that people are saying is that if you develop a new idea and you get a 30% conversion rate of people that visit the landing page, for example, it's an idea that should be built.
[0:20:43] Adam: But likewise, I think we're going to see a lot of these tools that people are signing up for, but they don't get the level of interest that they wanted and they just don't get developed full stop. When people are looking through these tools, it's great to see the art and the possible in the future, but just be wary that don't spend a huge amount of time rebuilding your business around these tools, especially if a lot of them are still in pre release stage, right?
[0:21:07] Christian: Yes.
[0:21:09] Adam: But it's great. I love seeing all of this stuff, but I'd say it's just going to be a challenge in keeping up. And I always go back to principles whenever I write about this, is don't lose track of the fundamentals. AI isn't going to slow down. It's going to become easier to use. And I personally believe the concept of prompt engineering in the future is going to disappear because AIS are going to get better at learning to infer what we mean. So I don't think people need to get bent out of shape on learning how to ask machines questions, even though I think in the short term there's probably an argument for that focus on fundamentals and then use AI strategically as opposed to thinking oh my God, we've got to completely reinvent our business. Right? I don't know whether you agree or whether that aligns with your thinking.
[0:21:55] Christian: No, definitely it does resonate a lot because as I said, there's a lot of different tools. So you have several big rich ones that are aligned to your business fundamentals. As I said, some of them, they will throw the line and it's like plug and play. But then some others you would need to fundamentally change the way you do your business and maybe those ones are not the best decision for someone to go into at first.
[0:22:24] Adam: So in your view, again, coming back to the small business example, I mean, you've got years of experience working for a large enterprise and your belt, you mentioned some Python examples there of the different applications of Python. But taking a step back from that, would you recommend a small business trying to use AI to better achieve their objectives? Is it as simple as just assessing some of the low code tools out there, picking the challenge?
[0:22:54] Adam: We need a better forecast. Right? Well, what AI enabled tool is best for that? Oh, we want to spend less time in spreadsheets. Right, well have a look at whatever business intelligence platform is best for that application. Is that what you'd suggest as a starting point or do you have a different theory?
[0:23:12] Christian: No, definitely for startups specifically, it's way better to just browse which tools are available already out there and then to try to see which ones they can use. Right. And not just in finance, but even for startups that normally try to focus more of like, okay, what's our product like and where we are trying to achieve what would be our users and so on and so on. And how to capture those users, for example.
[0:23:41] Christian: And I just like to automate tasks again, not just in finance, but in anything. As you were mentioning, if you do like a podcast, for example, how to automate certain tasks so that you can spend more time talking to people. There are also a lot of video creators that is the same thing. Maybe some of the videos, they really spend time on that, but then to create them, to make them shorter and then be able to publish them in YouTube shorts or TikTok or something.
[0:24:09] Christian: Now there are tools that they do that automatically for you or maybe like some part of the editing. So in every industry I do think that there are a lot of use cases and then if you start browsing as a startup founder or as a person that works in the startup on all of these tools, then it will be really useful on how to save time and do more things with your tab, basically.
[0:24:35] Adam: Thanks for that. So finance profession specifically, there has always been talk about automation replacing people. And it's not just in finance, it's over everything. And I've been listening to some interesting topics recently about artificial general intelligence, which is meant to be like getting to that singularity moment where machines become more intelligent than people. And it's humans that are, I won't say controlled, but basically the intelligence is the machines, not the people.
[0:25:16] Adam: Some people are predicting different horizons of that. We've got some people saying two years, we've got some people saying 20 years and I'm trying not to think about the negative consequences because actually I'm personally quite excited by this. I'm an optimist and I think more free time to do stuff like play golf, spend time with kids, all of that sort of stuff, I'm all for that. But for the people that are looking at their careers and thinking, well, there's still quite a lot of admin that I do as part of my role or I'm not in an fpna role and I'm not in a leadership position, does that mean that my job is at risk of automation?
[0:25:58] Adam: How would you advise that people think about that? Are there any skills that people can be focusing on that you think are going to stand the test of times are likely to improve their career prospects? I mean, how are you thinking about ways that finance can protect their careers as AI and these tools become more advanced?
[0:26:16] Christian: Yeah, no, that's a pretty good question and I actually asked myself that question whenever I started, let's say getting into finance. Like even I did the education part and then I was like, okay, which type of skills do I need in order to again with all of the admin of new technologies and again, that was like ten years ago, but I discovered that there were like two set of skills that I needed. One on the soft skills part and the second one in the technical skills part and I still seem to be very relevant. So the first one in the technical skills part is programming.
[0:26:56] Christian: And now it's not even really just like code at programming, but even how to use all of these new AI tools to augment your intelligence, to not replace it, but just to augment it and to be basically do better analysis, better things with your time. And the second one, it was storytelling and stakeholder management. So I think on the part of soft skills, that interaction that you have with other people across your business, especially in fpna, is very important. And also that ability, like in finance and fpna as well on telling stories and basically communicating concisely and simple ideas, it's really useful. So those two set of skills I think are the ones that are the most important to have.
[0:27:47] Adam: Yeah, I'll link to in the show Notes as well, but I saw recently, was it yesterday you released, I think on Medium, how to drive business success and build strong relationships with different stakeholders in fpna, right?
[0:28:00] Christian: Yeah.
[0:28:01] Adam: So I'll link to that in the show notes. I'm guessing it comes back to what you've just said there. You're trying to provide advice with Financial Fox on more of the developer side of things, but I guess with this sort of content, you're trying to boost awareness of those soft skills, right?
[0:28:19] Christian: Yeah, definitely. I also got very huge alphabet like soft skills and the importance they have for people in their careers. And especially if you develop them early, then you would be able to really grow into your career.
[0:28:36] Adam: Yeah, because if we take my kids generation again, we talked before the podcast, I've got two and a half year old and a nine month old. Their career prospects are going to be drastically different. They're not going to need to learn how to write Excel formulas. They're not going to need to really I don't think they're going to need how to learn to code. So it's very much about how do.
[0:29:03] Christian: We.
[0:29:06] Adam: Improve that ability to ask, I guess, better questions and how do we forget about more of the hard stuff. I'm not saying that the hard stuff is going to go away completely, right. But when we look about the way that work is likely to shift, it's going to be the people that are the creative thinkers, the people that are able to think in more abstract ways that can have the real advantage, especially, as you say, if they're augmenting their work with the use of AI. Right. And there's a whole separate conversation about the way that the current education system is potentially flawed and we're moving towards a world where everybody's got tailored education that's specific to their unique skills and all this sort of stuff. As I say, it's a conversation for another time.
[0:29:56] Adam: All good. So just to paraphrase you, then, essentially you still believe that there is in the short term a case for developing hard skills, coding how to leverage AI tools. But obviously in doing that, we've got to get a balanced view that says, right, well, it's not just about the hard stuff. It's about how do we present better, how do we communicate those concepts, and how do we improve our work there. Okay, cool.
[0:30:23] Christian: Yeah, definitely. I'm just as well, I remember when I was a kid, so my parents, especially my mom, she's a very huge advocate about these entrepreneurial mindsets. And then when I was younger, like 20 years ago, like 25 years ago, being an entrepreneur was very different to being an entrepreneur right now. Right. So it was not about the technology. Like, okay, like social media, the ads, like smartphones, they just exist. Anything.
[0:30:54] Christian: But they always told me about that entrepreneurial thinking as the ability of solving problems and really to start more with less. And then I grew up with that. And then even in my different schools. At first they put me for kindergarten and for primary school and so on, all of those schools. There were also very huge advocates for that for that entrepreneurial thinking. And I didn't really understood the value of it until I went to Australia. And then I was like, okay, now I'm trying to solve all of these different problems at work and things like that, and all of the tools that I received from my brands and from those goals, they were really helpful. And then that's one of the key points that made me become like myself. Entrepreneur with the financial voice in Australia 100%.
[0:31:48] Adam: And it's good that you had kind of that moment where everything came together. I love hearing stories like that and it's obviously working well for you, right? All good. And I suppose that the last point on that. And coming back to the whole point around data democracy that we've been talking about, once all of these tools are available to everyone, we're then moving into a territory where it is quality of thought and ideas that's the game changer, not whether you can build something or not.
[0:32:16] Adam: So imagine a world, anybody can develop anything. The people that are going to do well are the people with the best ideas, not the ones that can code. Have you heard of the concept of disposable apps?
[0:32:30] Christian: It no.
[0:32:34] Adam: Obviously, in the physical world, there's the concept of disposable things, whether it's a biodegradable, paper carp or things that serve a single purpose and then are disposed of with the ability to now create apps and tools so quickly. Now are people forecasting, if they're not doing it already, that people are going to be able to focus on a challenge and it could be something trending, it could be something happening in an industry and saying, right, well, I've got a couple of days to sort that problem.
[0:33:07] Adam: Let's build an app. People only have to use it once and then they get rid of it. The only example that I can think of really off the top of my head right now is HubSpot. Sometimes when people implement HubSpot they'll accidentally import duplicate contacts like I did. And there is an app that you can get called Deduply, basically get rid of all your duplicates. Now there's a case to say that you only ever really need to use that once, right?
[0:33:34] Adam: If you're working with a lot of data, then you might pay for the subscription to make sure that your database is always cleansed. But that is a use case that says, right, well, we've gone out, use it and get rid of it. I think we're going to start seeing a lot more of that pretty soon.
[0:33:48] Christian: Yeah, definitely. That's a very interesting thing as well because I was even in what I do in files in the automation part, we try to develop these tools for people in our business. As I was saying, with using Altrix and so on. And normally we always focus on, okay, how can the tool be flexible enough that it can be used as much time as possible? But it's a very interesting concept, what you said as well.
[0:34:20] Christian: Maybe there are some use cases that only need to be used once, but then it's very just to rebuild something quickly and then they just use it once, as I said, with the yeah, there we go.
[0:34:32] Adam: So, food for thought.
[0:34:33] Christian: A food interesting.
[0:34:35] Adam: See where things are going to come. So the last question, because I know we've come up to time and you need to get away, is I'm always keen to know what people use personally as part of their tech stack. If you like, have you got a favorite in like your personal it could be professional as well, but in your personal life that you couldn't live without that you absolutely love all the different tech stack itself.
[0:34:59] Christian: Like, it's professional. But the one that I love the most is Tableau. Tableau? Tableau is a data visualization tool that is very similar to Power bi. There's like different competitors. But then I have used it a lot in terms of, as I was saying, that part of the data storytelling and how to tell a story with numbers, especially to leadership people across the company. And I just think that that's one of them. The best tools on my armadex right now.
[0:35:30] Adam: Very good. And you don't like, have a favorite phone app or anything that you use in your personal life or anything like that?
[0:35:37] Christian: In my personal life, I was using quite a lot one month ago, this app called Blink List.
[0:35:45] Adam: Oh, yeah. Blank list.
[0:35:47] Christian: And then it's basically for people that are saying it's an app that gives you book summaries and then it's kind of like read it for you or they tell them in a very simple, unconscious way. And I thought, that's really great. I was using it for a couple of months, especially to know certain books, and then if I really like them, then I bought the book, but then if not, at least I get a gist of it. Now I use this word that Chad Deputy can do exactly the same and it can even give you chapter summaries.
[0:36:21] Christian: So one of my favorite books is the Lean Startup. And then apart from just saying to Chad Liberty, like, give me a book summary for The Lean Startup, you can say, give me a book summary for chapter one and it gives you for chapter two, and so on and so on. So in a way, it's even better than linguist. And obviously it's afraid. But I have to say, until a couple of months ago, linguist went away ever since.
[0:36:49] Adam: I didn't know it could do that because I did ask Chat GPT to do some book summaries for me and it came back. And this was, I think, Gpt-3 when it first came out and it came back saying something like I can't summarize copyrighted material, or something like that. I can't remember the warning, but okay.
[0:37:08] Christian: I didn't try the first. I think I end up trading from last week onwards and it summarized them very well.
[0:37:16] Adam: Okay, that's interesting to know. But again, there's been a question, definitely a conversation for another day. But if you're producing copyrighted content and then a chat bot can just summarize it so people don't have to read it at all. I don't know whether there's a great hack, don't get me wrong, especially books that have stood the test of time, like the Lean Startup. There's probably a lot of information in the public domain on it, right?
[0:37:46] Christian: Yeah. For example, when I was using Bling list, it was more of like okay, get the summary. But then if I really like it, then to buy the book, right, because it's weighed it's so much better to read the actual book than get the summary. But then there are also so many books that maybe for you personally they are not that good. So then with this ability you can at least save your time and then read the summary and say, okay, it's not for me, it will be for a lot of other people, but then I don't need to buy the book because it's not for me. Right, but then with the others, then you are still encouraged to buy the book. So then it really depends on how they see it, I guess, or even as a last just case I realized as well, I'm trying to put a little newsletter about it. But basically chattypti can also create fiction stories for you.
[0:38:41] Christian: So it depends on the prompts that you put, but then you can put your favorite TV show and then you put like okay, I want a book similar to The Big Bang Theory bought about finance analysts and then it creates and again you can put like write me the first chapter, the second chapter and so on. And then okay, now I want something to happen with an met ride, with an asteroid coming to Earth and they're destroying everything and it works.
[0:39:10] Christian: It's really more like funny use case but then it can also be used as a help for writers, like actual writers to okay, get more ideas or to test different things and so on. I do. The possibilities are definitely endless with never.
[0:39:32] Adam: Ending and I get very good now. I appreciate that. Excellent. So where can people find out more about you, Christian? Where do you want people to go?
[0:39:40] Christian: Yeah, definitely. So the main one is just LinkedIn. So if you don't put my URL for that, that would be great. That's the main thing that I'm using to promote my thoughts. And the second one is Medium. So I do hope that Medium is like a place for different professional blocks type of thing. And then I have been trying to write a lot now, especially about Chat Liberty, but I always write about finance and fpna. And as you were saying about these soft skills like storytelling or stakeholder management. So those are the two main things.
[0:40:14] Adam: Yeah. Very good. Excellent. So I'll put all of those as links in the show notes, but Christian really appreciate you coming on it's. It's been an excellent conversation and maybe we can have another catch up in six months to see how all of this has evolved. So no, really good. Thanks again for your time.
[0:40:28] Christian: Definitely great. Thanks for having me.