So I built this whole kind of client context engine, where it's pulling in your emails with a client, it's pulling in meeting nodes, if you're managing tasks, all that kind of stuff. So in addition to hey, the model can see a real-time PNL, can also see your interactions with the clients. So hey, I'm like, worrying on the model, I as a human forget a lot of stuff. I forgot I had this conversation with the CEO two months ago and he mentioned this was happening. You know, that's going to have an impact on cash flow or revenue or whatever else. That's really like the next layer for me is and for my users is, okay, how do I pull really everything about that relationship into whatever the current issue or conversation is? Welcome to another episode of FPNA Unlocked. Are you tired of being seen as just a spreadsheet person while others get a seat at the table? Well, then welcome to FPNA Unlock, we're finance meets strategy. I'm your host Paul Barnhurst, the FPNA guide. Each week we bring you conversations and practical advice from thought leaders, industry experts and practitioners who are reshaping the role of FPNA in today's business world. Together, we'll uncover the strategies and experiences that separate good FPNA professionals from great ones, helping you elevate your career and drive strategic impact. Today's guest is Brian Vigallan. Brian, welcome to the show. Next fall, good to see you. Yeah, excited to see you. So we can a little bit of background about Brian and then we'll jump into things. Brian Vigallan is the rare CFO who can read a balance sheet and builds an API integration. After a decade running finance and tech, he founded Alpine in 2021 to solve a problem he'd lived. Great CFOs were drowning in manual work instead of doing strategic thinking. Finance might be in his blood. His grandfather was commissioner of the IRS. I don't know if I should congratulate him or feel sorry for him. IRS is one of your days I guess. Yeah, you know, but his approach is decidedly modern with degrees in electrical engineering and an MBA from Cornell plus four years at Intel. He combines financial rigor with technical chops in the AI era. That means building platforms that handle the repetitive work. So CFOs can focus on what matters. Love the background and welcome again to the show excited to get to chat with you. Yeah, likewise. So we start pretty much every episode with this question. I always love to see how different people answer it. From your view, what does great FPNA look like? How would you define it? So I don't know who this quote is actually attributed to. I've seen it associated with different people, but there's a there's a mantra that I like to live by which is that models are never right, but sometimes they're useful. And it's something that I try to apply across the board whether in technology or CFO work. It basically what that means to me is I see the CFOs role or an FPNA person's role as providing an analytical framework for the entire organization. It's not just with CEO. It can be sales leaders, marketing leaders, operations, etc. And so if you are, if you can create a structure, if you can provide a framework that allows for support's effective decision making across the organization, I feel like you're doing your job like that. So kind of providing that framework can support across the org. And you know, the quote, the least one I always think of, there's one that was by George Box, who was a physicist. You said, all models are wrong. Some are useful. That's probably some genesis of that. I've seen different versions of that float around, but that's one that's always, I've always kind of like I joke. It's like the same thing. All data is messy. Some actually, you know, has value. Yes. If you can, if you can lie around the notion that you're not trying to predict the future, you're trying to imagine versions of the future. And is there a way to feed that back into contemporary decision making? That's the job. Yeah. When we don't predict the future, you're not a sous-sayer? Not yet. I mean, there's all this news about anthropics new model. We'll see what that can do. When does that drop? Well, they're saying they're not going to release it because it's too powerful. And it's going to hack into government systems. And so they're trying to put together this consortium of companies to figure out how to regulate this thing, which how much of that is marketing hype. But I don't really know. Interesting. I only saw one link that article about data security concerns with the new model. But either way, it's amazing how quick it's all moving. And that's what we're going to talk quite a bit about today. So our audience, now we're going to dive into AI and talk about some of the things that Brian's doing in that front. And what I'd love to know, just kind of start off, what's the number one thing in your job you're using AI for today? My job is a lot of different things. So it's software development, continuing to build and iterate platform. And that was my path in AI. It was kind of a natural first application for language models. And so I've been using various models and tools software development for 18 months now, going back to the original cursor release. So that's how the house a ton. And then over the last 69 months, I've started to embed integrations throughout platform that I use daily as a fraction of CFO and that other CFOs use. And so I have really tried to do at a ground level around a lot of different finance operational functions. Got it. So obviously you're using cursor a lot on the development side for your software. Not anymore. So like to start with cursor, that was kind of really the first master option tool on the development side. I started using cloud code maybe a year ago. And it really took a step function at the end of last year. Really incredible what you can do with cloud code simply. I haven't tried some of the other tools. That's kind of my primary driver day to day terms software development. Yeah, I know four six took a hugely a few months back. It definitely feels like all we've heard now is cloud the last few months. Everywhere I turn is something about cloud. Yeah. Yeah, it's amazing what Androborus made well to do just in the in the last six months. I've always liked Anthropic. It's always been one of the models I've used the most, but I can see the change or last few months. So yep. So everything in my platform that necessitates an AI integration, whether it's analytics, transaction, classification, driving actions within the platform, that's all the backend is an integration with Anthropic over their API. Sure. No, I know a lot of people definitely use their their API. So I'm curious. Kind of step back before we get a little deeper in AI, you start your career in engineering before going back to school and getting an MBA and switching to finance. So what motivated the switch? I was a Lego kid, math and science, and I started my career at Intel, which you know, recent struggles now standing was a really fascinating company to be at in the early 2000s. I got really interested in their history. You know, if you read Andy Groes' biography, there's a couple other books we're in about Intel. They were obviously one of the original Silicon Valley companies that carry on of American innovation, manufacturing, and they made some really interesting strategic decisions in the 80s, get out of memory and focus on microprocessors and the whole initial eight, but Intel and Side Campaign was one of the most brilliant campaigns of all time. And I remember those Super Bowl commercials with dancing and the buddy seats and everything. I just remember staying every computer slapped on Intel inside. I mean, when you're just a part inside something and you can get them to slap that on every single one somebody's buying, you've done something right. Yeah. And so I got really interested in kind of the intersection of of technology and strategy and decided that's kind of where I wanted to be. Not even necessarily finance, just how to position technology, how to grow technology businesses. So went back and did an MBA after working for Intel. Really some of my favorite classes of this school are accounting, like you mentioned, and must be in Medellin somewhere. And I ended up after business school working for a number of, I'm from the New England area, I was living in Boston, worked for a number of companies that come out of MIT and Harvard. And it was sort of organic, it was kind of well, you know, you're the only person in the company with an MBA. You can run the books too and and you know, build the forecast, our investors and our board and everything. And so it's kind of how I how I fell into it. So you basically got ball and told because you had an MBA and most sense for you to do the finance stuff. And fortunately, I ended up enjoying it quite a bit and have spent the last 15 hours at CFO and various capacities. Well, that's a good thing you enjoyed it. Obviously, and you can see how it's shaped your career. But it's funny sometimes how we get into things. I've told this before, I got into FPNA basically because I gave me a promotion. Now you're going to pay me more. It's a finance role. Okay, I'll take it. You have a technical degree. I know you like to code. So how is coding helped you kind of in your finance career? So not so much in the software platform, but just as a CFO, either being able to code from a thinking standpoint or in work. How have you seen that help you? Yeah. So even though back to those days, with kind of startups back in Boston, you know, I've always been building automations and API integrations and trying to make my job a little bit easier. And that's evolved a lot over the last 10 years. Like API is where we're relatively new thing 10 years ago. And you know, various of the accounting platforms have supported them to differing decrees. Say what you want about into it, like they've really supported the kind of open ecosystem. And so I've always kind of played around the edges and specific workflows make my job easier, getting data in and out more efficiently, building custom integrations, things of that nature. And but honestly, like the one of the biggest advantages has been understanding the back ends of accounting systems. I'm in other kind of business systems. As you may amount now, accounting was and then did in the 13th century.
century in Italy and it's what was kind of laid out at that time that it's driven the sort of object models and schema behind QuickBooks and NetSuite and Intax and so they're not really conventional softwares in a lot of ways and understanding kind of how they operate under the hood has really helped me as a CFO. Got it. Yeah, I can see we're definitely helping with getting at data and understanding how the data flows and things like that because yeah, like you said, double entry bookkeeping and recording that is not typically how you would see most databases record transactions and most software. Correct. And it's really exciting what's happening now with some of the new entrants in that space and how they're they're reconceiving of how an accounting system can and should be structured. No, we're seeing a ton of activity. I have I've been tracking some of it and I think I'm up to the tools about a list of about 10 newer tools, kind of ERPs, accounting software and between all of them they've raised I don't know 750, 800 million. It's a big opportunity. You don't need a huge amount of market share when ERPs and accounting software are not cheap. Oh yeah, when you address the market as the entire world. Yeah, there's it's a big sample. Every business in the world needs it and it's a core software. Not a bad business if you can get a little percent. And a few years ago you started Alpine, you know, your your fractional CFO platform. So all really motivated you to start the platform. Was it kind of to meet your own needs? You felt like the market needed it or kind of how did that journey happen? It was very explicitly to solve my own problem. That's kind of what I figured. I mean, that's not how it works. Even initially with a notion that kind of offer it to other CFOs. It's really just I was a practicing practicing fractional CFO. You know, you've got somewhere between six and 12 clients and given time and inevitably they're all on some combination of back office systems. You know, we're principally interested in the ledger, but CFOs, we want to know it's going out of the CRM and in stripe and they've got an AP system and what you have you. And so in part, just kind of out of my own laziness, like I just got tired of I do not want to log in and export another trial balance and paste it into a model and make sure that I'm so cracking and I just is not how I want to be spending my time. And so, you know, at the time, most of these systems had APIs some better than others, like I mentioned. And so I kind of started there. Kind of started just building integrations, building kind of youth one day of warehouse across my client portfolio and then just sort of different widgets and applications on top of that. And you know, it's eventually churn into this, you can think of it as kind of an operating system for fractional CFOs and really accelerated in the last few months with my ability to develop quicker all of these new interesting integrations and plugins and everything. But you know, when it comes down to it, I had I still like being a fractional CFO, working with entrepreneurs and business owners and understanding it in business models. And I'm always going to be the first customer. I love that. And you know, some of the best products are ones that we developed the solver own needs and then it's just scaled from there. We understand the pain point and we see the benefit. Otherwise, you wouldn't have built it. I've been involved with projects where you're trying to solve something where you're not the user and you're just sitting in a room with a laptop and a whiteboard and trying to imagine what people's issues are and it's it's a lot less fun. It's fun when you're solving your own problems. I imagine the first time you had the APIs out working, you get the report, okay, that was just all automated. Now all I got to do is this, this and this instead of you know, 20 steps, it now becomes five or whatever. Yeah, if you quit honest, like, you know, if you're whether you're a fractional CFO, you're in house, you know, your your real value is strategic partner. Do you have it in two to sense of business and finance accounting and the more time you're spending moving data around and manipulating it, the less you're spending in those other areas. Well, that's just when I was a director of FPNA, I worked at a company that, you know, we had systems that were very dated when I'm a director of FPNA roles and I spent a ton of time cleaning up data because it was the only way I could get to decent analysis and it was just it was painful. I mean, I spent a ton of time, you know, in power query more than I'd ever want to admit. We made a ton of progress, but it's like I'd much rather be figuring out this commission plan or the strategy for this customer or talking with the salesperson and you know, seeing how we can grow this. Instead, I'm trying to figure out why we have 10 different versions of the same product with different names that, you know, don't match. I think every FPNA professional has been there and that's some of the exciting stuff of how AI can help with that. You still got to have a decent data foundation, but it can help you with cleaning and matching data. You know, I'd love to a little bit of your AI journey. I'd love to kind of talk a little bit about that and more how you're using it in your fractional CFO, you know, business versus decoding side. I know you've done a lot of coding and may ask a question there, but would love a little bit of kind of your journey, how you started and what you're doing today. Yeah, there's a lot there quite with there, you know, I mentioned starting on the technology side, but you know, with respect to finance and accounting, my approach has been pretty organic. You know, it's as of middle of last year, I had a pretty good sense of kind of what AI couldn't do in limitations, hallucinations and all of that just from having green and ton of development side. I'm like, all right, so how do we, how do I start integrating this both as a as a user platform in a scalable way? And you know, I things like analyzes data and give me Trent, like that's table stakes. Like I was much more interested in what are processes, procedures, workflows, things like that, where I'm spending time. It's not really creating value to be your by client and I'll give you an example. So when I get involved with a client, one of the first things I do is get the chart organized. And as I'm sure you know, like you'll you'll come into a business, maybe they started with the default chart of accounts and QuickBooks and there's been kind of chart creep over the years and it's not well organized and maybe they use account numbers, maybe they use other kind of dimensions, but it's never the same as always challenge. If you're going to stand up a budget, you want a degree of an organization, right? And the traditional way of doing this is you have a lookup table in your model workbook where you say, I'm going to group, you know, these six accounts into a teeny line. I'm going to set a budget at group rather than I don't want to set a budget against airfare and cars and hotels and maybe you two in most cases, I don't have professional services or you know, there's some convention to this. And so that's always the first thing that I do. And like this is something that AI is quite good at is it can it can parse natural language, it can figure out kind of groupings and organizations and things like that. So like one of the first AI tools I built into my application was a kind of a chart of accounts mapping an organizer. And as with most AI tools, it's not perfect, but it'll get you 90% of the way there. Like all right, it did a pretty good job. I've got these kind of nominal logical account groupings of that tweak a few things. And now I have this foundation for the company. I can go and do my reporting, do my model, everything else. And I'm not having to manage the Z lookup table and inevitably somebody adds an account didn't tell me and oh crap, I've got to fix that. So I've tried to find kind of like point areas in the sort of natural progression of a CFO engagement where I can start hooking things in. So I'm hearing it's kind of the workflows. And the first one is obviously every company you go in the chart of accounts is typically a mess. How can I organize that and it consistent way that makes it easier for customer after customer take the 90% of take the common, you know, the standard chart of accounts from QuickBooks and say, okay, all that's going to get mapped here. Here's some other ones. I see a lot map them here use AI to make assumptions for that that it can't map and then you read you the final table. And that's process that maybe used to take me three or four hours. And I only do it once, but you know, if you're onboarding a new I in once a month or whatever it might be. Now I can do that in three or four minutes and then I'm on to the next task. What are some of the other kind of workflow things? You mentioned that one. Where'd you go from there on the on the workflow front? What are the other areas you're looking at for AI? One of the things I've been working on lately and hoping to have production next week is so you know, the genesis of Alpine was was wrangling data, right? Is you have all of these different systems. It's not conformed. And so like my initial task with platform was like, let's let's get everything kind of structured in uniform such that I can see that into whatever kind of workflows that I want to build. The other challenge I have is the fresh to see if those like you're managing all of these relationships, you know, maybe maybe have six or eight or 10 clients and different personalities, different needs, different schedules, different requirements, typically you're managing communications across a lot of different platforms, email, Slack, texts, you know, in-person meetings, virtual meetings, meeting notes. If all of these channels of interaction with your client and you know, the problem with using through AI point solutions is they don't have all of that context. Like you can see the snapshot of a P&L into plot Excel, it'll build a really nice looking model for you, but it's it's not getting the data updates, but it's also not really getting all of that client context. So I built this whole kind of client context engine, whether it's it's pulling in your emails with a client, it's pulling in meeting nodes, if you're managing tasks, all that kind of stuff. So in addition to hey, the model can see a real-time P&L, it can also see your interactions with the client.
So, hey, I'm like, "Worrying on the model, I as a human, forget a lot of stuff." I forgot I had this conversation with the CEO two months ago and he mentioned this was happening and that's going to have an impact on cash flow or revenue or whatever else. That's really like the next layer for me is and for my users is, "Okay, how do I, how do I pull really everything about that relationship into whatever the current issue or conversation is?" Incredibly handy, right? The more context you can give AI, the more time it saves you, but even more important than the time is the better the answer you get. Yes, what's all about. And like, I mean, this is one of the limitations of language models is it will very confidently tell you something. You don't have a great sense of confidence level and so the more that you can layer onto it and give it structure and give it background, the better the result is going to be. One of my favorite when you talk about confidently with the answers is we had an LLM that try to get the balance sheet to balance. It wouldn't balance. We're testing in Excel and Excel agent. We asked it to keep looking and I found this and it got a little closer, got a little closer. And it was like, I don't know, 1.3 million off on a billion dollars and it said, "That's only a 0.3% variance. That's not how a balance sheet works." You know what the word balance means? So I have a whole kind of system prompt layer that's very finance and accounting specific. And you literally have to include things like a balance sheet must balance, like provide the source whenever you're quoting a number. Yeah, we were talking, well, a good example of that is on a webinar yesterday and Glenn Hopper shared, right? If you ask an LLM to build an amortization table, not use code, but just build it. It will build it. And at first glance, it will make sense. The problem is it's just building it off probabilities. It's not doing any math. It's taking, it's been trained on 50 amortization tables. So it's just trying to make them look right as you start looking at the numbers. You're like, "Oh, wait. That one doesn't make sense in every single one F. That's all things a mess." How do you manage that kind of the, with AI? I know you're doing a lot of coding. So imagine anything that needs to be deterministic. Are you writing kind of your own Python code? You're having the AI generate some code? Because I know there's a balance, right? There's certain things probabilistic as fine. Like that chart of accounts, make an assumption. Yeah, you're monthly commentary, whatever. There's lots of areas where I don't care what word they used. I get the context. If the math is wrong, you got a problem. I learned in the pre-AI world as a CFO that I'll say, like, "I don't need help from AI to make a balance sheet that doesn't balance." I can mess that on my own quite easily. And so, you know, I really got into the habit of building parity checks into these workflows of this output. So very simple example is you've got a three-statement model. You know, is the cash flow statement footing to the balance sheet, right? My building cash flow statement and does the change in cash match the actual difference on the balance sheet. And so, you know, in spreadsheet world, the way to do that is you just put in a line with a check in some conditional formatting and it turned credit, it doesn't. And so, I mean, I still do this. Like I have my agents building a model, but it's still putting the parity checks visually into the workbook or into the dashboard. So when I'm looking at it, I know it's something strong. But there's something analogous going on in the back end as well. If it's building a balance sheet, there is a literal parity check in the code to make sure things like balance sheets, balance. Or we have the right balance based on account type, debit credit, etc. So CFOs and accountants have these analogs kind of on the technical side that I think are really important to develop trust in these systems. You know, I know quad really skills some of those things. How is that helped? Now that it's much easier to give instructions, to give detailed, even to code some of the references, all those things. How is that helped in the work you're doing with AI? Maybe this is a politically incorrect analogy. It's kind of like I have three kids. It can be like working with toddlers. You got to go to Mondries and then rules and kids feel safer when they have boundaries. And I think the AI does as well. And so whether it's on the valedance side or the finance side, and anytime it messes something up, which is still a lot better, but it still does. You can create a rule. You can put that into the context. And on the finance side. That's kind of like the tuning element of this is as me as a user and as other users are getting into it, you know, we are stuff is going to happen. It still does hallucinate. It still does. You're just incrementing these these kind of guardrails around the agent and the model. Yeah. I mean, it's a good way to look at it. I like the toddler analogy. We'll call it politically incorrect, but that's okay. We'll go with it. What's the thing you're most proud of that you've kind of automated a workflow with AI? I think you're most proud of that you've done so far. I mean, I had a project just a few weeks ago, you brought up an organization. So it's a different kind of an organization, but it was a real estate investment firm that was managing 50 or 60 properties. And they needed the issue K1, which is a couple weeks ago. And nothing about what was coming out of their account. It's almost correct. And so and very tight timeline. So like, I think I got engaged, you know, business taxes do more 15th. Business one K ones week head of that. Like I think I got engaged on March 1st, something like that. We eat PNLs by proper because we don't know how to do. Yeah, locations like we're basically a square one here. And so what I was able to do is first get connected to their account system. So also I have all of the data in my warehouse. It's structured. So I know what's actually in there. I know it's wrong. You know, like I'm looking at the sort of principal interest on these properties. Like, huh, why is the interest same every month or why are they book here? Meaning a principal with property or, you know, all the mortgages were standard and were stationed, but the accounting was just completely wrong. And then I could feed in the PDFs of all of the mortgage grants. And like you were saying, it generated kind of the principal and interest tables so that I could match that against what was actually in the accounting system, generate all a pro former PNLs and then feed the adjustments back into the ledger. I was like, that was highly spoke kind of project, but it involved, you know, some heavy duty finance, a lot of custom code. You know, like I could spin up custom interfaces so they could see these kind of bridge PNLs by property. And it's pretty cool. I felt pretty good about that. How much time do you think you saved, you know, being able to use AI, being able to code so you had to do that all yourself? Would you have hit your deadline? Oh, no way. In a free AI world, that would have taken without kind of my existing foundation of a platform. That would have taken multiple people weeks to months to do. Pretty amazing. And that's the thing. Sometimes people don't realize, yes, AI gets things wrong. That doesn't mean it still can't be really helpful in finance. And that's kind of part of the why I want to bring, you know, people like you and others that are seeing those huge time savings on is to help people realize that there is big opportunity here. How much would you analysis work you do now? How much would you say runs through cloud? Yeah, I don't think of it as kind of a replacement. I think of it as support. You know, my philosophy is in an increasingly AI based world, things like business acumen and strategic expertise and experience are more and more important. And so if I can build systems and workflows that support my ability to be more focused on that, then when you say analysis, it can mean what was the top line. That's a very loose. Let's say this. How much time do you think in a month on average, you're now saving with AI? I mean, again, for me, it's two sides of the house, like on the development side. Let's talk diffraction. Let's ignore the software for a minute. I know you're getting huge benefit on the coding side. But let's just talk kind of that FPNA, fractional CFO, the finance work. I think in terms of fractional CFOs, like the amount of time. So if you're spending 30 hours a month on a given client previously with AI and data normalization and integrations and all of that, I'm probably cutting half of that. You have some not having to do model updates and producing analysis and particularly kind of any initial part of an engagement when you're doing all of that setup. So and that's not just AI. That's also just the whole platform, the whole substrate. Sure. There's other automations behind that and technology. Sometimes I think we think everything's AI and sometimes good power query or a good API or just a good rule based process is all you need. Across all those things, it's maybe half of the time that I would formally spend on a given client. So material. I mean, it's it's a substantial savings, obviously. So let's talk. I mean, obviously you know coding. You do a lot of coding. You have your own platform. Let's take a minute and talk a little bit about the average FP&A person or kind of average finance. As soon as someone who has never coded before, you know, they might they know Excel. They might know a little less QL or power query, but they don't consider themselves a coder at all. What advice would you give them as they're kind of trying to figure out this whole AI journey? I would say the first thing to kind of develop some intuition around is the limitations and that it had personality and this doesn't even necessarily have to be finance specific, you know, like.
I use AI in a ton of different ways. And so pick one of the models, get a $20 a month subscription, and just start engaging with it in, I mean, it can be every day from the aspects of your life and your work. And what you'll start to get a sense of is, what do people mean by context? Right, so if you have a long running conversation with ChatGbT or Cloud or Gemini, what you'll notice is it's gone better, but it still degrades over time. And so you'll start to develop an intuition of how and why that happens and what the implication is. And then also other kinds of limitations, whether it's hallucinations or kind of like you were saying with composing emails or jumping in or just filling in gaps that you didn't really want to fill in. And so you'll start to develop this kind of intuition before you can get into kind of finance workflows and things like that. And then beyond that, if you want to start getting more specific, I know you've posted a lot about Call of FriXcel and Millie models and things like that. Like, get practical, right? Like that's always a solution for me. Is it a problem in your client or if you're in in-house somewhere, like a thing that you're trying to solve and make sure it's not mission critical? And I just find it's always more realistic if I'm working with real data with a real problem, the real world. And so pick one of these tools and try to solve one thing. And then there's a very meta element to it. Like AI can be very helpful in helping you understand how to use AI. Yes, I definitely have noticed that. I know I'm talking about it on the whole. And, you know, like not to be an anthropocomer, but like they're, they have a really good documentation that there's so many tutorials and stuff out there. I see anthropocostosis is a great job of supporting the community and the ecosystem. Yeah, and you're totally fine. You feel free to be a homeer, I think right now. Everybody sees anthropic in the lead. If they're using other tools, I mean, at least the majority, right? They've done a really good job the last few months. I'm like you, I've jumped more and more on anthropics. Even two years ago, I liked the best mostly for writing, for writing posts, summarizing my podcasts. And now I like them for a lot more of everything. Yeah. And I'd add, like it's, you know, you don't have a background in software development. Like it's, it can still be incredibly helpful to have basic intuition understanding around data structures. So, and you can do this with the chat. Yeah, like you just talk to it about SQL. And like if you can get access to a database somewhere and just start getting your head around how data is structured, how tabled relate to each other, basic object schema, I think that's really critical kind of foundational knowledge. Like you don't need to have, you know what need to be a right code, but having this sort of just data facility can be really helpful. So I'll speak to that a little bit, 'cause I 100% agree with you. I did my master of science and information management, you know, so there were some data table type classes in there. And I did report writing for about a year and a half out of grad school before I moved into a more traditional FPNA role. So a lot of SQL and reporting out of, you know, complex Excel files and things. But learning that data and, okay, when do I write code? When do I build a table to do something? It's helped incredibly, whether it's Excel formulas, whether it's using Power Query, whether it's just being able to think about how the data needs to connect to get good input out of it. And so I'm 100% with you. I found that kind of that base invaluable for me. And I don't consider myself a coder. Yes, I know some SQL, yes, I know some Power Query, but I don't write Python. I've never been one of those people that wants to code. I find the data side invaluable. So I'm a big believer in that. I agree with you there. What do you think is kind of limiting most people from getting more out of AI? What do you think that kind of the big problem we need to overcome in finances? Yeah, so I say one element of it is kind of the limitations that we've talked about. There are still hallucinations. There are limitations in how it gets applied. But something that I sell that might resonate with people is just kind of a generalized anxiety around it, especially the last nine months, it feels like things have changed so quickly. And in the Brings world, even just the last two to three months, I mean, it's just, I just feel like it's exploded in 2026 so far. And I totally understand how like that can be overwhelming and disheartening in a way. Like, shit, am I keeping up? Am I just coming for my job? You know, like I feel that on a daily basis. And so I can understand kind of the anxiety and the resistance. And what I'd say is all of these people who are posting hype on LinkedIn or I've created a one person, $100 million come back, like, no, these people are any smarter than you are. And a lot of what they're saying probably it's not grounded in reality. And so don't be intimidated by a lot of what you see on social media or other types of media. Like a lot of that is not really the real world. And with finance professionals in particular, like in this increasingly automated AI world, there's going to be more and more of a premium on experience and expertise and, you know, the ability to have insight. And if you can figure out tools and processes to deal with everything else and you can focus on that part of what you offer, you know, that's that. I don't think that's going to go away any time soon. Great advice. I particularly like the whole reminder look. Social media is curated. Take it all of it with the green assault. Some more than others for sure. But yeah, the LinkedIn stuff, use my prompts and save half a million dollars or whatever. Yes. I replace my entire finance team with, you know, Claude and Zapier. All right. So I want to move on. We have a FPNA section where I ask some pretty standard questions. Then we have a little bit of a get to know you some fun questions and then we'll wrap up here. So if I ask you, what's the number one technical still that FPNA professionals should master, what would you say? I'm going to sound sold saying this, but like fundamentals and accounting. Honestly, I had a financial statements relate to each other. Davidson credit, you know, like just the logic that buffs straight behind everything that we do. And maybe you would consider that technical, I don't know. But anything you do on top of that is going to ultimately relate to that. And so if you're using an AI tool to build a financial model, like you need to be able to explain how balance sheet relates to the PNL, relates to cash flow. Appreciate that answer. What about software human skill? I think the best thing you can do, whether you're a fractional CFO or you're just, you know, you're doing FPNA in a larger company, can you inhabit the mindset of the entrepreneur and the business owner or whoever the principles of the business are? You know, what are they trying to optimize for? What are they worried about? What are they thinking about? What do they want visibility into? How do they like to consume information? You know, some people like visual. Some people like numbers. To what extent can you just sort of empathize with who your customer is, whether it's a plan or a boss or a colleague or anything like that? And if you can use that to inform your processes, your work outputs, I think that's what's going to make you successful. Which Excel mistake that you've made over your career has taught you the most? I have definitely put balance sheets in front of boards that don't balance. If you're looking at something that a finance professionals put together and you see that, you can't trust anything else that person, instead of front of you, right? Then you're checking everything. And so for me, it's been an in-out that it I regard to a state of perfection on this, but it's what are the simple checks and balances and quality control that into my processes that I'm not degrading that trust? And I'm curious when that balance sheet doesn't balance, how often was it a formula mistake versus not understanding financials? For me, it was typically somebody added an account that I didn't catch. It's typically processed stuff and having multiple cooks in the kitchen. That's why that was one of the first features I built. It was like, I needed better handle on the chart of accounts and I need to know something changes or something thoughts. All right. So we're going to move into the get to know you section. I have a few questions. I just want to ask, what's your favorite hobby or passion? What are you doing in your free time? Yeah. So I'm a musician. So this is a small part of the collection. So I'm typically playing in a band at any given time. And then I let down the road from you in Utah. And so I really enjoy all the kind of recreation that is offered here, backcountry skiing. There's no snow this year, not biking, any of those kinds of things. Yeah, I was going to say skiing this year was lousy a few years here. All right. I'm curious to see how you answer this one. If you had to listen to one song and only one song for the rest of your life, what are you picking and why? My favorite artist is a guy named Jason. He's been around for 10 or 15 years. I kind of like the Americana somewhat Foki genre. He's one of the few Grammys. He's got a ton of incredible albums and songs. We wrote one when he was-- he went into teenager when he wrote this. It's called Decoration Day. And it's like a rock-n-er album. I mean, it's just like legacy of the Civil War and family dynamics and the South. And it's just a banger of a song. And he played it. I saw him in Salt Lake here last year at a front row. And he played it. It was awesome. Nice. So that's going to be your song. I appreciate that one. What's your favorite food? I really like Mexican food. In Mexico, a bunch of times, first on the list. So what's your favorite Mexican restaurant for those listening?
in Utah or might visit here. - Redigwant or Redigwant or two. I mean, you really can't go wrong. And they're around corn from each other. - That's mine as well. So we just put a plug in for Redigwant. If you're listening, come sponsor an episode. All right. What's one business belief you hold that you think most people would disagree with? - Probably less disagreement on this than there used to be, just because of how things are evolving. But I think there's so many paths to building a business. You know, like it's very easy if you're living in LinkedIn or Twitter or in certain parts of the country, you think that like the only way to build a business is to go raise much of capital money and kind of get on this treadmill. And like that's such a small slice of the world. Right. And so I really support the notion of just different, different paths to being successful as an entrepreneur. And you know, I've tried to live this. Like I'm not VC-funded. You know, I still have a services offering that is just kind of keep me going. And I think there's so many ways to be creative and to inject your personality and to building business. - I'm not sure how controversial that is now. But definitely you do. A lot of people have the idea you have to go that VC or raise capital or out or you can't build. And I've never bought into that. Do I think it makes sense in certain situations? Sure. But for the vast majority of businesses, there's not, you don't need it to be successful, I think. All right. So as we wrap up here kind of last question I want to ask, what advice would you offer to our audience to be a better business partner? - I just rewatched Ted Lasso. Have you ever watched that show? - I'm familiar with it, but I haven't watched it. I know a little bit of the premise of the show. - It's one of my favorite shows. And I think it's a great study in leadership and teamwork and it's also really funny and heartwarming. But there's key scene. I think it's the first season where he's trying to impart a message which is be curious. He meant it in terms of just interpersonal relationships and not being judgmental with people or what might be going on in their lives. But I think that applies here, whether it's adopting new tools, maybe you're initially intimidated by whether it's getting to know a new client or a new colleague or new, I think the most important thing when you're trying to drive the direction or you're having a role in driving the direction that this is, is to be curious is to what am I not thinking about? What am I avoiding? What am I, what question should I be asking? You know, how can I be? It's much of a sponge, just possible so that I can do my job, the highest level. That's an answer I get a lot. I love that answer because I think it's critical to F/P&A. You got to understand what's going on around you and being genuinely curious is the best way to do that. All right, last thing. If somebody wants to get in touch with you or maybe learn more about, you know, Alpine or the things you're doing, how should they do that? Got a website. It's getalpine.com So Alpine with a Y. You can email me,
[email protected],
[email protected], I'll find one with a Y. I'm trying to represent Tom LinkedIn. I'm not nearly where you are, Paul, but you can find me on there. I mentioned one quick other thing. I just launched another business with my brother in the mental health and recovery world. It's kind of space. It's pretty important to us, my brother is an executive, that a recovery center in Connecticut. So we built a payments, patient management platform for those kinds of residential facilities. It solves a real problem in that world. And that business is called care ledger. So you're interested in that space as well, be having some more content around that. Cool. Well, congratulations on starting that. I mean, that's a very important area to have good resources for. We need more of that. All right. Well, thank you for joining me today, Brian. I appreciate you taking some time and getting to chat and enjoy hearing a little bit more of, you know, how you're thinking about AI, how you're incorporating it and the work you're doing. Yeah, absolutely. Thanks very much, Paul. That's it for today's episode of F-P-N-A Unlocked. If you enjoy F-P-N-A Unlocked, please take a moment to leave a five-star rating and review. It's the best way to support the F-P-N-A guy and help more F-P-N-A professionals discover the show. Remember, you can earn CPE credit for this episode by visiting earmarkcpe.com, downloading the app and completing the quiz. If you need continuing education credits for the F-PAC certification, complete the quiz and reach out to me directly. Thanks for listening. I'm Paul Barnhurst, the F-P-N-A guy, and I'll see you next time.
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