Why AI is a Game-Changer for Finance Professionals - Insights from Christian Martinez

Welcome to the Future Finance show where we talk about everything from business to intelligence to super intelligence and everything in between.

What has surprised you the most about the capabilities of generative AI and how it's being used or could be applied in fpa?

I feel the main one, the code I feel is like really democratizing the access of code. All of these bigger technologies for every FPA person now.

So what are some of the other technologies that have you excited?

One of the things that I really think is very useful.

What percentage of FP&A professionals do you think have that sort of dashboarding and storytelling?

I would say right now either from 50 to 60%.

I was going to go a little lower. The number that just popped my head is probably 30, 40%.

Should all finance folks be able to code?

I definitely believe that all finance professionals need to have data analytics skills. Having those right type of data analytics skills for your position, I think that is key. Microsoft will use that. They were going to be integrating Python completely natively in Excel.

What are your thoughts on Prompt Engineering?

Essentially we try to teach them how to think differently about handling these tools.

I think it's very similar to learning Future Finance is brought to you by qflow AI, the strategic finance platform, solving the toughest part of Planning and analysis. B2B Revenue align Sales, marketing and finance seamlessly speed up decision making and lock in accountability with qflow AI Foreign.

This.

Week'S episode we welcome Christian Martinez.

Christian is one of those rare unicorns.

Who understands finance and Python code and artificial intelligence and machine learning with equal skill.

Also in this episode, Paul talks about the value of learning AI and I.

Talk about OpenAI's steps towards artificial general intelligence. Thanks for joining and let's dive on in all of the great endeavors in human history started with a decision. From early voyages across vast and unknown oceans to the discovery of the double helix structure of DNA, our choices have defined not only the world in which we live, but our humanity itself. For leaders, bringing a vision to fruition requires myriad decisions, big and small about people, projects and principles intertwining to create a holistic outcome. Great leaders rise above baser instincts, emotional responses and distractions. They draw upon all of the skills, tools and counsel at their disposal. This is how great decisions are made. While Presidents have cabinets, CEOs have boards, and Macbeth consulted witches, modern leaders are increasingly incorporating data and analytics to guide decisions. With the help of data science, they are able to better discern signals from a vast ocean of noise. However, to lead effectively in the age of AI, managers must Be able to understand and trust this.

I know Christian Martinez has shown many ways you can use AI and Python to enhance your analysis. Seen people use AI with vba. I've used it in my work. Oh, I need a quick script to do this or do that. I ask AI to write that vba have it help you write that formula, analyze data. Another great one from Jim o' Neill in a prior episode is he talked about how it can be the contrarian ask it for all the risks and all the reasons you shouldn't do something, all the counter reasons. So the more specific you can get with AI, the better the answers you can get from it. But the reality is you need to learn how to start using it so you can be more effective. Many people do not impact that AI will take away a lot of jobs in finance, but one thing it could definitely do is companies will start looking for a productivity tax, almost an efficiency. Like hey, we're not going to give you this many employees because we expect you to be 10 or 15% more efficient. You may delay hiring. You may have to justify every headcount and say why can't AI do it? The better you are at using AI, the more efficient you are, the easier it is to maintain your role because you're being very productive. So this week the focus is on being better with AI, not talking about the shortcomings of AI. Welcome to another episode of Future Finance. I am your co host Paul Barnhurst and this week we have with us Glenn Hopper and Christian Martinez. I'm going to give a little bit of an introduction for Christian and then we'll welcome to the show here. Christian comes to us from the Netherlands. He currently works as a finance transformation senior manager at Kraft Heinz. He has worked on several different continents during his career including Europe, Australia and South America. He's well traveled and and he's quite the expert. He loves teaching finance and FPA people how to use AI and data analytics. He has several courses he has developed on those subjects helping people be better with AI. He has his own newsletter that he recently launched called AI for FPA and Finance. Christian, welcome to the show.

Info right. About to be there.

Yeah, excited to have you. I know we had the opportunity to chat previously on FP&A today several months back. But we're really looking forward to having a little bit of a different conversation today. So again, very excited for this. Let's jump into our first question we have for you. You recently started your newsletter, as I mentioned in the intro there, to help FPA people Learn AI. What made you decide to start a newsletter and what's, you know, what's going to be in those newsletters? Talk a little bit about that.

Definitely. So I think that artificial intelligence can be very utilized and leveraged in fpa and I started to have a lot of different articles like all over the place in my medium, in different blogs and so on. So I decided to put everything in one place in the newsletter and try to communicate on the things I'm most passionate about. That it's artificial intelligence in finance and FNA in a constant basis.

Got it. And so you kind of put everything together so they can see it. And what's really the, the focus? I know it's AI, but is there the certain technical skills? Is it prompting a little bit of everything? What are you hoping to people kind of take away from your newsletter? What will they get if they read it?

Yeah, definitely. So the main focus is that after they read every, let's say like er newsletter they will have something very practical that they can fully utilize. For example, last couple of weeks ago I put this profit algorithm. There is an algorithm developed by Facebook and I put the full code, the full data set and a couple of like videos and prompts so that they, if they want they can utilize their sales data in that algorithm in like 10 minutes. So that's the, the main aim and the main focus.

That's amazing to think, I mean think two, three years ago trying to get somebody to use an algorithm like that in 10 minutes on their data. I'm gonna have to go check that one out because I've had it on my list to play with profit with some data and I, you know, I know a little bit about it and I've talked to people. I know someone that helped develop that algorithm, worked a little bit, worked in finance at the time it was developed at Facebook. And so that, that's really cool. That's, that's just amazing.

Yeah.

And I love Glenn's face. I can tell he's geeking out over this one.

I am. And I, you know, I always love talking to Christian because Christian, I feel like you and I, you know, early on in this, your coding chops are way better than mine. But I've always been a kind of a half assed coder out there, you know, just doing the citizen development and stuff. But I feel like, you know, we've been connected a while and you and I in the, you know, pre generative AI, we were out there espousing how great, you know, machine learning is to be used in finance and the power of big data and all these correlations you could find in building models. And then as generative AI was coming along, I feel like you and I paddled out on our surfboards, you know, out way ahead of everyone else, looking around for all the great whites and everything. And then, you know, the generative AI waves started coming and you and I turned and started paddling along the wave.

And as, as we Australia and South America. He's well traveled and he's quite the expert. He loves teaching finance and FPA people how to use AI and data analytics. He has several courses he has developed on those subjects, helping people be better with AI. He has his own newsletter that he recently launched called AI for FPA and Finance. Christian, welcome to the show.

Thankful. Very glad to be here.

Yeah, excited to have you. I know we had the opportunity to chat previously on FP&A today several months back, but we're really looking forward to having a little bit of a different conversation today. So again, very excited for this. Let's jump into our first question we have for you. You recently started your newsletter, as I mentioned in the intro there, to help FPA people learn AI. What made you decide to start a newsletter and what's, you know, what's going to be in those newsletters? Talk a little bit about that, definitely.

So I think that artificial intelligence can be very utilized and leveraged in FP&A. And I started to have a lot of different articles like all over the place in my medium, in different blogs and so on. So I decided to put everything in one place in the newsletter and try to communicate on the things that are most passionate about that. It's artificial intelligence in finance and FNA in a constant basis.

Got it. And so you kind of put everything together so they could see it. And what's really the focus? I know it's AI, but is there the certain technical skills? Is it prompting a little bit of everything? What are you hoping to people kind of take away from your newsletter? What will they get if they read it?

Yeah, definitely. So the main focus is that after they read every, let's say like every newsletter, they will have something very practical that they can fully utilize. For example, last couple of weeks ago, I put this profit algorithm that is an algorithm developed by Facebook and I put the full code, the full data set and a couple of like videos and prompts so that they, if they want, they can utilize their sales data in that algorithm in like 10 minutes. So that's the main aim and the main focus.

That's amazing to think, I mean, think two, three years ago trying to get somebody to use an algorithm like that in 10 minutes on their data. I'm gonna have to go check that one out because I've had it on my list to play with profit with some data. And I, you know, I know a little bit about it and I've talked to people. I know someone that helped develop that algorithm, worked a little bit, worked in finance at the time it was developed at Facebook. And so that, that's really cool. That's just amazing.

Yeah.

And I love Glenn's face. I can tell he's geeking out over this one.

I am. And I, you know, I always love talking to Christian because, Christian, I feel like you and I, you know, early on in this, your coding chops are way better than mine. But I've always been a kind of a half assed coder out there, you know, just doing the citizen development and stuff. But I feel like, you know, we've been connected a while and you and I in the, you know, pre generative AI, we were out there espousing how great, you know, machine learning is to be used in finance and the power of big data and all these correlations you could find in building models. And then as generative AI was coming along, I feel like you and I paddled out on our surfboards, you know, out way ahead of everyone else, looking around for all the great whites and everything. And then, you know, the generative AI waves started coming and you and I turned and started paddling along the wave. And as, as we go along our path, I feel like every now and then I'm looking over and saying, oh, there's Christian right there doing very similar things to what I am. And you're usually surfing just a bit ahead of me, but I really appreciate the work you're doing. And as something, one of the questions that I get a lot that I thought would be great to pose to you because we've talked about, let's call it traditional machine learning for a while, traditional AI using machine learning algorithms to supercharge our forecasts. But now generative AI has come along and I remember the early days, probably, you know, ChatGPT 3.5, where, you know, significantly better than 3, but still, you know, far behind where we are today. And I remember some of the first stuff I tried to do. Paul, you and I talked about it when I tried to build it.

I tried to get back when I hosted your show.

That's right, yeah. It's a, it's a strange family world here where we have a lot of crossover. Yeah. But I, you know, I tried to get 3.5 to write some Python code for me and it was pretty good, but it wasn't good at QC in the code back then. And it was, you know, you had to kind of know Python a little bit to be able to execute the code. But it's gotten so much better so fast. And outside of the coding, or maybe it is just the coding, but as you work in and teach how to use generative AI with finance, I mean, what has surprised you the most about the capabilities of generative AI and how and how it's being used or could be applied in fpa?

Yeah, very good question. So I think the main one to be first is the code because as you were mentioning before, like finance professionals needed to have like six months, one year of training to be able to know everything about Python, even downloaded Python, their computers and so on, and then start using it allow with genius like generative AI. I have seen a lot of different people in our courses that in matter of like 10, 15 minutes, 30 minutes, they're already coding their machine learning algorithms, but using like generative AI, which is like fantastic. I feel it's like really democratizing the access of all of these bigger technologies for every FPNA person.

Now, are you hearing feedback from people like after they take one of your courses and after you talk to them, are, are you getting feedback, are you getting good stories of how they're actually using what they learned from you in production?

Yeah, because one of the very good things that we do in our course, like both Nicholas and I, is that at the end of the course we also tell our people on how to continue like the next steps. Right. So either they can message us or email us and so on. And then that's where I get a little bit of how they are using it. Or also Nicholas has this great cop, the AI finance club and a lot of people from the courses, they join the club and then I'm interacting with them afterwards, like on a constant basis and really knowing how they have been exploring and utilizing everything that we teach. And because one of the other things is that as you're mentioning then like this environment, it changes very, very quickly. Right. So what we were teaching on the first cohort, it's very different to what we can teach now. And, and obviously we cannot go with everyone and say like, okay, now all of this happens, so this is like the new thing and so on, but with These type of communities, we can really share the knowledge of everything that is like constantly changing.

Love that.

Very exciting. And I want to step back. Right. We talked a little bit about Python machine learning. Obviously it feels like any conversation around technology today has to include generative AI. But a lot of the work you do is in the data analytics field. Not just finance, but data analytics. So what are some of the other technologies that have you excited that we should be talking about? Obviously, AI is the big one we all hear about, but what else is out there that you're like, you know, this is really exciting and I wish more people knew about it.

Yeah. So I have to say that I think that these days, most people in FBA know about it, but one of the things that I really think is very useful, it's a good dashboard that can tell a financial story. So either if people decide to use Tableau or Power BI these dashboarding tools, I feel that they can improve the way we do FP and A work a lot. And that's because the typical FP and A type of work, it's either monthly closing and then you're preparing a couple of reports, sending to them, and then analyzing the data and then exploring like the whys that data, the that, and so on, the various analysis and so on. And with a good dashboard, you can do all of that very, very quickly so that then you can focus more of your time on business partnering and talking to the business ongoing, really either if you are, let's say manufacturing finance, go to a factory you're in sales finance, go to the stores, and so on and so on. So it's, I think, one of the things that again, many people know these days, but I'm still very passionate about.

Love it. I'm curious, you have a favorite analytics tool? Do like, do you prefer Power bi, Tableau looker Domo? Do you have one that, if you could pick that you like to use.

So I have to say that both Power BI and Tableau, those are my favorite ones. I do think that they can do very good job both of the tool. They have a little bit of pros and cons in both environments, but yeah, those are my favorite ones for BI intelligence, like business intelligence.

And those are the two biggest out there. Right. And so that doesn't surprise me. And you would expect them to do a lot of similar things. Some of it comes down to preference.

Yeah, you know, I. Years ago, when I really started getting into analytics, I had to. I felt like I had a choice. I guess I could have done both. But I, I picked Tableau over Power BI because I felt like it. The entry cost was lower, it was easier to do stuff in Tableau. But as the years have gone by and especially now as Microsoft is really ramping up its AI presence with its partnership with OpenAI and everything they're doing with Copilot and some of the built in functionality of Power bi. I wish I'd spent more time when I was actually more hands on learning Power bi. But who would have seen how far Microsoft would have come since then? But I know this is a question for both of you and it's going to lead into my, my next prepared question here. Maybe not for management, you know, knowing how to get into the guts of things, but as far as frontline FP and A people right now, what percentage of FP and A professionals do you think have either Tableau or Power BI or whatever it is, have that sort of dashboarding and storytelling and experience beyond Excel and able to create is that most Frontline people have that skill set Now?

I would guess that, let's say if you are talking more about the finance analysis, like the people actually doing analysis and so on, I would say right now either from 50 to 60% they would have that skill or their list, they're trying to get that skill that makes sense. I don't know if you have a similar viewer.

Yeah, I was gonna go a little lower, but I wasn't that different. I, the number that just popped my head is probably 30, 40% have it. If you're saying who's trying to get it? There's probably another 10, 15 that are starting to develop it which gets to a similar place that Christian's at. I, I'm, I guess I'm a little more pessimistic maybe, but it's, it's somewhere in that probably 30 to a little over 50 plus. I think some of it also depends on company size. Right. Big, huge companies have an entire team that's managing bi. So a lot of times the FPA person never has to get into it. So if you only work for big companies, you may have only pulled reports and learned, you know, basically nothing. Where if you work for a mid sized company, you may have the BI team reporting to you, you may have chose the BI team, you know, a small to midsize company and been involved in the entire process. So I would think it's much higher in small to midsize company is than it is enterprise people that have spent their career in enterprise. So I think there's a little bit of industry segmentation. Would you agree we work at a big company at craft. Would you say the numbers are really high there on strong BI skills or you say most the FPA people probably a little lower because they have people who can do a lot of it for them. Ever feel like your go to market teams and finance speak different languages? This misalignment is a breeding ground for failure, impairing the predictive power of forecasts and delaying decisions that drive efficient growth. It's not for lack of trying, but getting all the data in one place doesn't mean you've gotten everyone on the same page. Meet Qflow30AI, the strategic finance platform. Purpose built to solve the toughest part of Planning an analysis. B2B Revenue QFLO quickly integrates key data from your go to market stack and accounting platform, then handles all the data prep and normalization under the hood. It automatically assembles your go to market stats, makes segmented scenario planning a breeze and closes the planning loop. Create airtight alignment, improve decision latency and ensure accountability across the teams.

So one of the things that are really about working cloud finds is let's say that learning and development, ecosystem and environment. So back when I started around six years ago, there was this huge wave of everyone learning data literacy, a little bit of Power bi, dashboarding things, a little automation and so on. So I think we have way more people than the average, let's say big company people that know how to use dashboard intros.

That's great. I mean that's fabulous to have at a big company. I think think that's awesome that you have that kind of investment to, you.

Know, to me and it's to my mind in a leadership position that you understand, you know, enough data science to be dangerous enough about kind of what goes on under the hood with Power BI or Tableau or any of the other tools out there and then a little bit more about what the BI people are doing. Because if you're trying to organize the chessboard and know how to have your teams work together, like understanding how all the components fit together, it helps you sort of allocate resources and know what you can get and what you can't. And I think I've been my whole career has been with SMB companies and to my mind and maybe because I didn't have the luxury of resources, to my mind it's always been very important for the FPA folks to have that BI skill set. And you know, if you think about Tableau and Power bi, there's sort of a drag and drop component to it. So you may not, you know, you can just learn the drag and drop without really understanding, without really understanding what's going on under the hood.

You don't have to learn a data model to build a basic report as an example.

Right.

You can drag and drop the report and have some of the DAX built for you if it's basic enough without having to know anything about the actual underlying Star schema model. That's going.

Yeah, exactly. And I, but to my mind, and I get a lot of pushback on this, so maybe I'm wrong, but it's not going to stop me from keeping an answer this question. So Christian had this is a really important question for you because I know how deep your skills are here. So I've long believed that FPA professionals, they need to expand their skill set to include some basic programming. And I think to your earlier point, that's easier now because you can, you know, if you don't know anything about Python or anything about coding, it's going to be hard for you to even get a generative AI to write code for you that you can run in any kind of environment. So. And maybe, you know, I would say at a bare minimum, I think we should be able to write SQL queries, but that's probably that, that maybe is table stakes now. I could even make the argument for learning Python as well because you can, you get so much more flexibility if you actually have a coding language and you're not sort of restricted by the drag and drop and by one environment and you can really dig deeper into the data when you can fine tune the programming and whether you're setting parameters or whatever it is that you're doing, you know, you have that flexibility to really customize what you're doing. So Christian, with your skill set and knowing what it took for you to kind of develop that, I mean, what are your thoughts on this? Should all finance folks be able to code?

So I definitely believe that all finance professionals need to have that analytic skills. I do think that the majority of people would be very like, will have a lot of benefits if they know how to code either SQL or either Python. And I also believe that many professionals would have a lot of value if they know, let's say, how to build a dashboard, like from scratch. But I think in general it's more like data analytics skills because it really depends as well on your level, if you're an analyst, if you're a manager, if you are the cfo. And so on but having those right type of data analytics skills for your position, that that is key. So maybe not everyone needs to to learn how to code. I do, let's say suggest many people to learn how to code, but again it really depends on their level as well the organization. But that analytic skills, that one for sure, yes.

Do you think that the job, the marketplace for hiring, if you have those skills, I mean it, it would have to put you at a premium, right? Have you seen any indication of that?

Yeah, so I have seen it for maybe like six years now and so on that people with those skills on top of other very important skills in finance then as you mentioned, like they are in on a premium.

And I'll share a little bit of my thoughts here because I think I'm similar to both of you, maybe a little different. I've always said fpa, not maybe all finance should at least learn SQL being able to pull the data. I did report writing for two years. I did a Master of Science and Information Management. It worked on a software thing. So I learned a lot on the data side. Never learned to code. Yes, I could do some M code, sure. Can I do a little bit of vba? I've always wanted to learn Python but never done it. And I'm still going one of these days I'm going to get there even though I don't use it in what I do for business today. So I think at a minimum you need to be really dating data literate as we were talking about. I think books like this are great. Jordan Goldmeier Becoming a Data Head where the whole book is to help you be able to speak the data language without being a technical person. At a minimum, as a finance professional, you have to understand that data language and be able to have those conversations. Do you have to know how to do it all? No. But will it benefit you? I think without a doubt. I think we're all on the same page that it's when you have an employee that knows how to do that stuff, can you trust them with more things? For sure. And is AI making that easier? Of course it is. But I would argue, and I'd love your thoughts on this, Christian, I'd say anyone who knows some basics, knows a little bit of coding, knows SQL, knows Excel, really whatever it may be, the more technical skills they have, the more they can get out of AI than someone who doesn't know anything. Would you agree, Christian?

Yep, totally. And I have one very good example as well. So it's not with AI per se. It's actually with dashboards. But back on the day when I was working in Australia, I had a manager that I was telling him, like, oh, look, there's this thing called tablom. We can build dashboards, we can do this, we can do that. And then he's starting slowly to trust me and told me like, okay, yeah, try it on. Okay, bring me the things and then see if we can add value to our company and so on. I feel like maybe like six months to one year passed and then at one stage he had to take one of these courses of tableau, but let's say more for managers. So as you mentioned, well, not to build a dashboard, but to learn everything behind the score. And I thought it was already quite late, but he called me and I was still available and he was telling me like, okay, Christian, now I really understand what I can ask you to do. And my mind go like, super, super quickly. It's like, now we can really build up very, very interesting things. And I did admire, like two weeks after that. We built up so many more things than the previous six months wherever he was still not trusting me 100% on, okay, this is a very good technology. So I think it's exactly the same thing now with AI. So, like, if people understand this part of, like, more like data literacy, data analytics, how that behaves, they will be so much better and really getting the most out of any type of AI.

All right, so we've talked quite a bit about Python. I'm still going to go ahead and ask a little bit. You just released a course, Python for finance professionals. What. What was the thinking behind that course? We've talked about how AI can do some, they can learn more. But why Python? Why not R or SQL or what was the reasoning for choosing Python as your kind of next finance course for people?

Yeah, so actually the full name of that course is Python in Excel for Finance.

Oh, it is in Excel.

Okay. And that's the main reason because Microsoft news last year that they were going to be integrating Python completely natively in Excel. So Microsoft Also, like owning LinkedIn and then LinkedIn reach out to me to basically create this course of combining like, let's say final skills of DNA, but also Python and then also Excel. So that the first course that I have already released in the platform and I'm already working on a second one which is a little bit more deeper and advanced and actually it's about using more machine learning still in Python in Excel.

I'm going to have to take those. I didn't realize it was LinkedIn. I know George Mount's done some as well. He's another Python in Excel. I finally got it in my beta version of Excel Excel and played with it the other day. It's fun.

It's really good. It's really good. And then one of the, I think, most beneficial things is that it's in Excel. Right. So a lot of finance people are of FNA people, they love Excel. So then Python, instead of, like, taking them out of Excel and going somewhere else, now they can leverage the power of this program language natively in the solution that they like to use.

No, I. I've played with a little bit. Have you had the opportunity yet, Glenn? Have you played with Python and Excel at all?

Really haven't. And I'm. I mean, I. I saw, and it's been out long enough that I don't even have an excuse at this point other than I just have to sort of pick my paths to go down, so.

Oh, I get it.

I'm excited to see that course, though. And the. Did you go on site to do the recording?

No. So this one, they sent me the. The recording kit.

If you get an opportunity to go out there. It's a beautiful part of the country right there. Just, you know, just south of San Jose, I guess that.

Is that Santa Clara. Yeah. I've heard it's a really good campus to go to.

I'll definitely go. It's a bit farther from me over there. From the Netherlands.

Yeah, yeah, yeah.

I'll be kin to both.

Yeah, we've talked. We've really geeked out and gone way deeper in Python probably than we have in. In previous courses or in previous interviews, rather. But I want to get back to something that a lot of people can relate to. And this is my other hot take. So, Christian, I'm really curious to hear your response on this. So, like, you, like, like all of us, I'm out talking about AI all the time, and one of the most common questions I get is, well, could you just give me a prompt library? Could you just give me some prompts that I can use to interact with generative AI? And that always drives me crazy because to me, people, it means people are not thinking of generative AI the right way. It's not like a software where you push a button and, you know, pull a lever and get a result. It's rather than prompt engineering. And I do think I've said it. I probably did one of my monologues on this. I think in a few years, prompt Engineering, if it's not already, is going to be like saying, I'm really good at Googling stuff. I mean, it's just going to be, it's not going to matter. But what does matter is understanding what these tools can do and how to interact with them and how to be specific in your questions and all that. So I'm, I'm sure, Christian, you get it all the, all the time. But what are your thoughts on prompt engineering and if somebody's asking you for guidance or for you to make some canned prompts for them to use, I mean, what are your thoughts on it and how do you sort of handle it from your perspective?

Yeah, no, definitely. Very good question. So I have two points on that. Well, first one is that one of the, I think the second slide that we show in our course of advanced activity with the class, it's a picture of someone fishing and we do the whole metaphor of teaching you how to fish instead of like giving you fish. Right. And I think that's one of the things I most like about the course. Like that, let's say, structure that we don't give people exactly, just this prompt and then that will work and that's it, that we have 100 prompts, but instead we do give them a bit of guidance at first, like, okay, needs to be the structure of the prompt. You need to add this. If you don't add this, then this happens. If you add this, this happens, and so on. But essentially we try to teach them how to think differently about handling these tools. And that's I think the most important because even though we put a lot of different finance use cases, like cohort analysis, like heat maps, PPM analysis, different automations and so on, we teach all of that. But on top, we really teach them on how with their own data after the course, they can really utilize the framework and then build the prompt by themselves.

That's great.

Yeah. First thing, the second thing is that even though we do that in the course, which is obviously the more comprehensive one that we have, and we spend a lot of time with the people in there, we also have some documentation on like prompt libraries. And I started not like a prompt library itself, but More like in ChatGPT, you can share the link of an entire conversation. So I started building these full conversations of like, I don't know, 10 different questions back and forth and so on, but for specific use cases on fpa, on controllership, on tax and so on so that people that don't want that further to either take a full course or go very deep into a rabbit hole or something like that. They can go in there and more or less see what is available and what is possible.

That makes sense. And it's almost. I feel like, you know, you're almost structuring that, like a chain of thought prompting that. It's like, look, you can't ask. You can't eat the whole elephant in one bite. Let me just show you. These are the sequential prompts that you do, and maybe after somebody does that a couple times, it clicks with them and they can, you know, take off the training wheels and go off and do it on their own.

I think it's very similar to learning Excel or other things. And what I mean by that is, like, later today I'm doing a Excel webinar where I'm talking about lookup methods in Excel. How many people just learn Vlookup and never go any further? But we all know if you understand the why and the different methods, you can get a lot more analysis out of your data. You can often be quicker, do it in better ways. And I think it's the same with AI. If all you do is say, give me the prompts, you might get to the third grade level. But if you start to understand the why behind it and experiment, and all of a sudden you're sixth, your eighth, your college, whatever, you're becoming advanced because you're getting the why behind it. Not just, you know, oh, I do it this way because, well, that's what I learned. And it always makes sense.

Definitely.

All right, well, we should move on into our last section here. This is where we get to know a little bit about you. So I'll lay out the ground rules and how this will work. We have a list of questions. The list they believe this week came from Haiku Claude. We asked it 25 questions to come up with to ask a podcast guest to get to know them. So we have two ways for my question. Then Glenn will walk you through how he's going to do it. I have two ways. You can pick a number between 1 and 25, or the random number generator can pick a number between 1 and 25. And that's the question we'll ask you. Do you have a preference?

Yep. Maybe. Let's do the random number generator.

All right, here we go. Let me generate 23. Let's see what 23 has to say. All right, this is a pretty good one. What's your hidden talent or something unique about you that we don't know?

That's a very Good one for sure. Trying to think more on things that I think many people don't know. It's not a hidden talent, but I would go with that part. So I was actually doing a presentation on it earlier today. But one of the things about me is that right now I live with my girlfriend and my two pets. So one cat called Simba and one dog called Nala. And then I have always loved dogs, but until I met my girlfriend around like eight years ago, I had never even touched a cat. And then since then I started like slowly interacting more with cats. Until last year we decided to get one and then now the family bitter because we just got a dog. So again, not for sure, but things that.

No, that's a unique. I like it. That qualifies. We'll give you that one.

So with these questions, my idea, I'm waiting for the full Movie Multimodal Chat GPT4O, the voice and everything. And we're just going to have chat GPT or maybe a advanced Siri after the Apple partnership. We're just going to have the bots ask you the questions and that way we can't be held accountable for asking stupid questions at this point. But until then we've been bouncing around. Gemini is the worst. I'm, I'm just, I'm dog cussing. I'm not a Google stock owner so. But I've been dog cussing Gemini for a while. We'll see. You know, maybe they'll, they'll catch back up. But for a while, chatgpt4o I thought was doing the best job at, at coming up with the questions and now we're using Claude Haiku here. But the, the new, you know, the, the 3.5 from anthropic is really, really good and then I'm getting my model names mixed up, but the version three is that sonnet, I guess does an incredible job writing. But anyway, long story short, we're, we're still doing a bake off between the, the different large language models and we've got Haiku this week and instead of doing the random number generator, what I do, I don't know what it's going to take in context out of this and I've not seen any rhyme or reason, but we'll load, we'll have it come up with the questions and then I'll load your bio and the questions that we asked you and then I'll have it come up with the random questions here. So the what I'm going to come up with or what Haiku is going to come up with for you is what is. And this one's kind of boring. I just talked it up. It's fine, it's fine. We're going to learn something new. What is your favorite way to start the day? Perfect. Whether it's a work day, weekend day, you get up, how are you greeting the day? If you can do everything right, I.

Would say I'm very structured person. So if you had asked me that question, I think one month ago, I would say just like, wake up and then start my coffee, like in my espresso machine and put me on my laptop and starting looking at different things. I have a few different websites, like, I look every. Every morning and so on. But nowadays, since my dog is like, I just got her, so she's a puppy, I start my day with her. So basically doing all of these puppy needs, then I do the coffee and then I start my computer.

I think puppies are a good way that calms you down, releases the. The chemicals and everything is probably a great way to start the day and put you in a calm space. If the puppies behave, if the puppies behaved otherwise, if it's chewed up something overnight, you have a whole other list of problems.

And speaking of puppies, that's probably a good spot to end on, right? A nice calm. Everybody can think about their pet that they love and how it can help calm them down. So, Christian, we really appreciate you joining us. We enjoyed chatting. You know, we got to get deep a little bit in Python, just all the amazing things you're doing. And I just want to close by saying thank you for all you're doing for the finance community. I think the work you do is great. We need people out there like you that can help lead the way and help us realize that there's a lot more we can do with technology if we're just willing to invest a little bit of time for. So thanks for coming on the show, Christian.

Yeah, thanks, Christian.

Thanks so much for having me.

Thanks for listening to the future finance show and thanks to our sponsor, qflow.AI if you enjoyed this episode, please leave a rating and review on your podcast platform of choice. And may your robot overlords be with you. Sam.