Podcast

Today we're talking about Deep Research. It is the AI God's gift to accountants. I'm so bullish on the applications that there are for Deep Research. Also because it's a Q and A Friday, we got a new AI enabled accounting ledger that just launched. We're going to be talking about digits and what they're doing now and what it's how it's different than what they were doing before. A story about how accounting softwares part of their growth strategy is to now look at acquiring accounting firms. What? And Ryan Lazanus, fellow accounting think person just launched Ryan Bot, a paid chatbot that gives you access to his expertise. How do we feel about this? Have influencers gone too far? Come on in, let's talk about it. Okie dokie. Let's start out with Deep Research. It's been out for maybe a couple months now. If you're not familiar. Deep Research, it's exactly what it sounds like. It's a ChatGPT feature that will work on a problem for upwards of 10 minutes and write like up to a 10 page paper about whatever you want it to go on research. So inside of Chat GPT, if you're on a paid plan, any paid plan now I believe you'll see a little button that says Deep Research. It's got a little cute little picture of a telescope and when you click that button it means it's going to work for work on something for a really long time. One actually interesting note here. If you've played with it yet, pay attention to the model that you have selected at the top because that will impact your Deep Research results. I always use O3 mini high, the reasoning model anytime I'm using Deep Research. Just a note there to think about. But anyways, why do I want an AI to go off and take 10 minutes to work on something for me and 10 pages of results? Do I really want that? Like at its worst it can feel like you're grading AI's papers and that's just a waste of time generating something just so that I can grade it. Here's the thing, here's what I'm realizing about Deep Research is calling it Deep Research is, is awful, awful branding. It is the wrong packaging for what that thing is. Because what it is is the beginning of longer time horizon AI's cutting AI's loose to work on a problem for you. It's like the very beginning of this chatgpt. Like to date it has been these quick ephemeral conversations where I want an answer as quickly As I can. It's a single stream of conversation. I'm talking with one AI having a back and forth the same way that you would with a human. But kind of the wild thing about where AI is headed is AI is not limited to this sort of single stream of consciousness that you and I are limited to. And I didn't totally get my head around this until I started seeing more examples of like 80 AI agents working on a problem at the same time. And it's like to see it visualized like on screen of all these agents interacting with different sites and, and kind of trying to do something together. It wasn't until I saw that that I was like, okay, that's actually what I'm competing with in the future. If I have this like survivalist me versus AI mindset right now of like, it's never going to replace me. Because ChatGPT and AI assistants in general right now, they are very smart, but they are not smarter than domain experts in general at whatever you're an expert in. So it's, it's why right now we go to chat GPT. Honestly, for all the things that we're not an expert in, usually that's where it's going to be most helpful. I would say in the last three months, for the first time, it's really gotten very useful for even the things that you're a domain expert in. But I'm still not threatened by it. For, for the stuff that like, I'm an expert in. And that may change, but at least right now I'm not threatened by it. But when I saw like 50 to 100 AI agents working on something simultaneously, like working with each other on it, I was like, okay, I kind of get that now. Because there is no theoretical limit on how many agents can go off and work on something simultaneously. They call these swarms is kind of the, the, the vernacular that they're using for this. And so they're, they're working collaboratively to like get to the bottom of a problem. And, and to be clear, a dumb AI, it doesn't matter how many dumb AIs you have. If it's a dumb AI, it's not going to achieve anything meaningful. Actually, I had a, a joke about this in an upcoming video that I'm so proud of. It's something along the lines of talking about like dumb AIs and whether they're smart enough to actually do something if there's a bunch of them. I'm, I'm not afraid of fruit flies. So by extension I'M not afraid of a hundred fruit flies, but bees, I don't like bees. I can still physically dominate a bee, but if there's 100 bees, that's going to hurt like a mother. So. So even if a b. Even like I could still beat a bee in a fight, but if there's a hundred bees, that's going to create some problems for me. And I kind of think that's where AI is right now. Like it's not as smart as me, unlike the things that I'm an expert on, but still pretty smart and can probably be helpful. So to bring this back to Deep Research behind the scenes, Deep Research uses an unreleased O3 model that is very powerful. And what it's actually doing behind the scenes is cutting a number of agents loose and at the same time to kind of work on this problem for you. Another example of this, if you're plugged into the AI nerdosphere out there, a platform called Manus M A N U S it's gotten a ton of hype this last week. It's a Chinese company that released. It's an AI agent basically and kind of looks like the next step, kind of an even more powerful AI agent than we've seen yet. It's only available in private beta. It is a Chinese company, so it's not super relevant to us. You know, even if you look at something like Deep Seek, which was a really, really big deal when they launched Deep Sea GR1 because it was a super powerful open source model. Unless you're going to run that model yourself, which you have to have massive server architecture to be able to do that. Deep Seek didn't impact how anybody in the Western world worked because you can't bolt a Chinese model into your Western company with how things are structured today. So similarly, this Manus AI agent, very, very cool. Not something you're going to be using in the near term, but what I hope it does, much like deep seq R1 did serve as a kick in the pants to Western companies to be like, keep shipping cool agent stuff. And Deep Research at its core it is a, it's a research agent. But that research framing it, it makes us think that it, it is limited to just do. Doing sort of like academic things or say tax research when it can do so so much more because it can work on anything that you give it. So that can be spreadsheets, that can be work paper files, it can be anything. And you know, recently I did a, a ch. A video about how to do tax research with ChatGPT. We also did like a big feature roundup for ChatGPT maybe a month ago. And in those videos I stuck to, I don't think deep research is worth buying the $200 a month pro plan for because for a while the only way that you could get this deep research feature was on the $200 a month ChatGPT plan. Well, the amazing news is the biggest AI headline of the last 30 days is that anybody on any paid plan gets limited research to deep research. Now I think for most plans you get 10 queries per month that may go up over time. They've already increased how many you get access to on the pro plan from 100 to 120. So I'm hoping over time on those paid plans you get access to more and more of those queries because man, if you use it like I do, they go really, really, really fast. But my justification for not leaning into deep research further in those videos is for basic tax research. It, it's too much. I don't, I don't like it. In fact, if all you're doing is basic tax research, I would say the best approach right now is just using the O3 mini high model in your paid chat GPT, enabling browsing and then telling it where to go find the answers. So this is, you know, 2024, IRS rules only use information from the IRS website. And while that's not like deep diving into the code section and all that, like that's not 95% of tax research, it, it is just like I can't remember that thing or I gotta put a couple ideas together. Like that's what most tax research is, not taking a different position to the irs. So for work like that, deep research, it's, it's not worthwhile. And so if, if all that I think that this feature is for, is for research things. And I'm like, most of the time the research I'm doing is not that sweaty to justify me then having to read through this 10 page paper. Now in practice, the outputs that it usually gives me, it's not 10 pages, it's like maybe two pages worth of text. But the way, way, way better way to use this stuff is for larger meteor tasks that have to be grounded in a very, in a very specific thing. So I'll give you an example. I've got loads of transcripts from podcasts, from YouTube videos and all that stuff. And oftentimes I will do a little write up based on what I said on a podcast. So we could take this Podcast episode. I, I can take the transcript from YouTube, I can give it to Deep Research, and I will say, give me a 500 word LinkedIn post and usually I'll give it an outline structure to follow. That is a more engaging structure for a LinkedIn post. Like, it needs to have a juicy hook at the beginning and it needs to have three points that each lead into each other and like encourage the reader to read till the end. It's something honestly that we've used ChatGPT for a lot. But the quality of what you get from Deep Research now is so much better and the adherence to the source materials you provide it is much, much, much better. And so honestly, for me, for the very first time ever, really, I'm actually starting to use AI for writing. And so most of the time Deep Research is actually my first draft and then I take it from there. I change it a ton sometimes, sometimes I kind of get on a roll and I just like rewrite it from scratch practically. But that first draft is what gets me started, which is oftentimes the hardest part. And for anyone that has like that backing authoritative thing that you need it to stick to, that's where it's really, really valuable. And for you, what that probably looks like. Meeting Transcripts, the level of depth of work that it can do with Meeting transcripts is now like on a whole other level. Like if you're trying to pull content ideas out of a meeting transcript, if you want to throw 10 meeting transcripts into it and say something like, I'm trying to get like synthesize the way that I advise into more of a framework, like pull out the common themes from these different transcripts and help me to start developing that framework. That's a really big lift job that just a normal chat GPT conversation can't handle, the O3 mini model can't handle. But Deep Research, it does that stuff really, really well. Even scripting YouTube videos now, I'm using it on every single YouTube video I will pull in an initial outline. Because the way I script my YouTube videos is basically here's the intro, which is, which is kind of the hook, and then each of those beats there, there may be like kind of three sections to that video and every single one of them needs to create an open loop in the viewer's mind. So they're like, oh, I got, I have to stick around because I, I want that resolution of that loop being closed. But before you close the first loop, you've opened another one. So you give closure on that first loop, but by the time you do, you've opened some other interesting thing that they're going to want to stick around for. And so when I plan out a video, I have to be able to think about what is what does the title and thumbnail look like? Is that because it only matters if somebody will click on it? And then I think what are those juicy loops? And then I cut deep research loose with a whole bunch of source material. Even past videos, even past podcasts and third party stuff. I give it a whole bunch of source material and I say develop this outline further and it will, you know, 4x the length of the outline by adding a whole bunch of relevant beats within the outline that I've already defined. It does that stuff really, really well. This episode is brought to you in part by the fine folks at Cloud Accountant Staffing who help you find talented accountants in the Philippines. One of the fastest growing trends in small firm running. Honestly, Ask around. Ask in the comments. Ask folks you meet on social media. A huge number of people have started doing this in the past year or two. Not just accounting firms, tax firms as well. Yes, I understand with US tax you got 7216 disclosures and that's not a reason to not offshore, it's a reason to disclose totally manageable ways to navigate that thousands of firms are doing. So world's getting smaller. Honestly, it's never been harder to find folks in are excited about doing accountants on short. Now does this change how you build your org chart out a little bit? It does, but I was. Let's see, I was on a meeting with 22 other sub million dollar firms, tax firms specifically, and the prompt was what's the best thing you've done this year? A couple different people called out hiring in the Philippines for the first time and they were super happy with the people that they'd found. Cloud Account Staffing's background. They were an accounting firm. They started hiring themselves. Folks in the Philippines, hired some recruiters over there to do that directly and now they help other firms do the same thing. Simple as that. So that's something you want to explore. Have a conversation with me. You got nothing to lose. Learn more about cloud account staffing down in the show Notes. This episode is sponsored in part by Makers Hub. Hey, quick, quick win opportunity for your clients that do any sort of accounts payable even if you don't do bill pay. Send them to this podcast sponsor, Makers Hub. You've heard me talk about Makers Hub before. Before. We've run several Demos on the YouTube channel. Ooh. In fact, bonus points if you send your client one of my YouTube videos. Okay, this isn't your ad read, Jason. Makers Hub, they are leaning into AI vision models and large language models to enable a entirely different level of accounts payable automation. I've talked about this before. The single most disrupted part of the accounting profession right now, courtesy of AI, is accounts payable. And Makers Hub is a great snapshot of that done really well, really smartly. It's not one more platform to manage. It pushes all the data back into the QuickBooks file. So you still got a single source of truth. I have clients who this would have saved an unbelievable amount of time for. And this is when we were running Best of Breed tech three or four years ago for them. This would have taken that automation so much further. If you do bill pay as a service, you need to be looking at this because this totally changes your business model. But even, even if you don't, if you have clients that struggle with this and, and a lot of them do haven't, check out Mega Sub super smart folks behind that. You're going to see him out at a lot of accounting conferences this year. Learn more Check out the link down in the show notes now. Another wildly powerful thing here is you can upload spreadsheets, do deep research. Spreadsheet. Spreadsheets. Spreadsheets. And that opens like a whole can of worms of a tremendous number of things you can do with it. And to be clear, you could also do this with regular old ChatGPT. You can upload a spreadsheet and be like, hey, give me your insights on this or that. And the progression of that has been GPT4, which was the model we got in March of 2023. At that point, I think shortly after that model came out, you were able to upload Excel files to ChatGPT for the first time. And if I would have a conversation with it about the Excel file, oftentimes it would be like, can you actually see the Excel file? Like what you're giving me? It is not very intelligent. The next model 4O, it was a little better, but there was still a lot of gaps and it was not particularly impressive. A really big step with this actually was reasoning models. And so, you know, last fall, late fall, on the podcast O1 Preview first came out, we used O1 Preview to review a set of financial statements. And we're like, wow, this is really novel. This would be tremendously useful for juniors to do a first set of review, something I still recommend you do. This is A great justification for having chat GBT with every single member of your team is you can chuck a balance sheet, a pound, a profit and loss in there and and with a, a reusable prompt that you ought to define for your team. Have chatgpt to a do a technical review of the balance sheet and the profit and loss and you will see it catch a whole bunch of issues that go across the desk of seniors every single day. And if we can get the preparer to use that as a self review, that's super helpful. And 0101 preview that was the very first quote reasoning model we got in ChatGPT. Reasoning models basically they spend, you know, 30 seconds to a minute thinking through a problem and processing it much more, having kind of this internal dialogue before giving you a response. The net effect of that is the response is much more intelligent and much more thoughtful when it comes to materials that you give it. So when we got those reasoning models it was really the first time where I could give it a spreadsheet and it would give me actually a pretty darn intelligent response back. Now the biggest thing to look out for here is still giving it more information than it needs. So going back to that last example, if I give it a balance sheet and a P and L and then the full general ledger detail, it's going to spend a whole bunch of time getting tripped up on the general ledger and being like I'm not sure that this transaction is actually reflected on the balance sheet. Me I like because I know how the accounting underlying accounting system works. I don't have any doubts about the GL report not matching the balance sheet report and so I don't want it to waste time on that. So most of the time I don't give it the general ledger report unless I want it to look into specific, specific transactions and then I'll give it part of the GL report. So you still have to navigate the issue of not giving it too much information or irrelevant information. The more irrelevant info I get it, the more distracted it will be and the more it will take away from the points I actually want it to dig into. This took another step with the O3 mini model which we got in the new year. Now O3 mini high, which is what the model is called in chat GPT, just awful naming conventions. But O3 mini high is now the best way to do this in your chat GPT. Upload a spreadsheet, have an interaction with it and my accounting friends. Let me tell you just how massive of a step further Deep research is down that path of getting something useful out of it. When you provide a spreadsheet, it is a huge, huge step. I did a video a couple of weeks ago around just a whole roundup of a whole bunch of really, really cool stuff you can do with ChatGPT and Excel now. In fact, we'll put that down in the show notes. You may not have seen this video because it's on a new YouTube channel. I'll link that in the show Notes. We do everything from like using operator, which is the agents that will go out and use a web browser for you. Like we, we use that to like have AI agents go and work in a spreadsheet for us and you can actually see them working live like just as if it were another human. Using a spreadsheet is really cool. But one of the things that we did in there is I had a spreadsheet with two tables of data and I asked it to do some analysis and it came back with really, really smart stuff of like, well, here's these are your highest traffic locations. And I actually rounded up a bunch of different details to determine that that wasn't a, an obvious thing. It would have required like hustling some pivot tables and some like real thinking. But it came back with a long list of insights that were really, really good. And there's a world here where I mean, if you're doing any sort of advisory around financial statements, this almost now for me has risen to the level of like, it's almost irresponsible not to use this if you're doing advisory on the performance of a company. Like it's that juicy. Like there's absolutely a world where every month, once the month end close is complete, this goes into deep research and you give it specific instructions on how you want it to pull insights from all of this information. Now there's like a very basic version of this where you're just raw dogging it, chucking it in deep research and just say, tell me what you know. There's a upgraded version of this. We're actually doing a whole video on this right now. There's an upgraded version of this where you have your own advising framework and you say, here is my advising framework. Apply it to this. And so then it's like through your own lens and the results of what it gives back is structured probably in a more helpful way to you. And then there's an even bigger brain version of this where you give it those two things and you give it the last three months transcripts from when you meet with the client to discuss their results, then it's putting it through, like, through the context of the actual conversations you've had with the client. And like Deep Research is just something you need to try to believe how, how powerful it is. And so if you haven't played with it yet, like this is going to be, this is going to sound like hyperbole and it's, I'll be honest, like, it's pretty rare that I'm as excited about an AI thing as I am about this right now. Combining those three things, actual specific client data. By the way, another argument for only using the team plan. Unfortunately, the team plan is still limited to 10 deep research queries a month. But it's the only plan where your prompts don't train the model. So use the team plan for this. That being said, actually, if your whole team is on the team plan, everybody gets 10 queries. So maybe think about how you distribute those. Anyways, if you think about how powerful that is putting in their actual financial results, your advising framework and actual meeting transcripts from when you talked with the client, the output, it gives you a two page, like research summary that'll, it'll take five to 15 minutes on that is an unbelievably powerful starting point for how I'm going to advise the client that month. In fact, if it's me, that's how every single advising, like if, if I'm, if I'm blocking out an hour or two to kind of put together some insights for an upcoming meeting with a client, that's how it starts every single time right now. Like it is that good. And that's coming from me, who would fall into the bucket of, you know, one of those advising unicorns who can just sit back and shoot from the hip and do it ad nauseam in a way, in a way that's good enough for clients and many of you, that is you, whatever combination of experience and riz and like, whatever that combination of factors is, that makes you a great advisor and you can just do it. But then you look at everybody else in your team and you're like, why can't they do it? Well, it's because you haven't like created a framework and they don't have that experience. They may not have like, you know, like kind of the X factor that it takes to make that stuff useful. I'm saying this about Deep research as one of those people that can do the shoot from the hip advising. And so if you then transplant the quality of the deep research output and put it in front of your team. The people who are not those unicorns and have to advise more to a framework because maybe at this point they aren't able to shoot from the hip. If it's useful for me, it is 10 times as useful for those people. What kind of blew my mind with all this was the moment I realized, oh, deep research isn't just about going out and doing quote unquote research and pulling 100 sources from the web. Deep research can also just be working through the pile of information that I just gave it and nothing else. And after doing a few tests, I was like, because we've had ChatGPT experiences before where you give it the spreadsheet and you're like, are you even looking at the spreadsheet? I don't believe you. But having a few really positive tests with it, that was like, holy smokes. Like, how deep does this rabbit hole go? I now do probably, probably three to five deep research queries a day. And of those results, two or three of them I probably read through from beginning to end, like they're juicy enough and helpful enough for me. Super, super recommend you give that a try. It's the biggest AI development we've had this year and it's not even close. Very, very interesting, honestly. It will make you, it will challenge your thinking on just how good direct to consumer, direct to entrepreneur advisors will be. Just because like you can like out of the box. If I just give it the financial statements and say, you know, give me some advice, it's pretty good. Paired with your advising framework that's, it's like 2x, it's very, very good. And so somebody standing up a, a service that is like, just give me your financial statements, connect your QuickBooks file, whatever it is. The level of advice they can get from a service like that now just, just went way up. Which is what makes your framework so important. And we, we talk about this a lot. Like, what is the relevance of my accounting firm in a timeline where AI does get really, really powerful, it's taste, it's like your perspective of here is the right way to do this. If I go to ChatGPT and I ask it for copy for a website, by definition it will be the most average copy you could imagine because it is a probabilistic system that is the average of all the data that it's been trained on. The same will apply for how it advises people. And so what gives us value long term, regardless of how AI gets is our taste. Is our perspective and the framework that we channel AI through. Like that is our value. And this is a great example right now of how out of the box it's going to do. Advising. Pretty, pretty good. But paired with your framework, it's 5x as helpful for a specific type of entrepreneur and like gang like it's here. Like it's it just landed. Like go give it a play. Drop a comment here. I would love to hear your experience with it, what it does well today, what it doesn't do well today. Equally important, it's very rare that I am truly as excited about as a development as I am about this. Also go check out that ChatGPT Excel video. I'm pretty proud of that one. This episode is sponsored in part by Team up, who helps you directly hire talented accountants in the Philippines. Why do you hear so much about the Philippines specifically? Used to be like India, right? Why is the Philippines caught on A few things that I'm stealing from this excellent salary guy Team up put together. You can swipe that down in the show notes four reasons for why the Philippines has caught on 1. They've got a critical mass of talent, loads of people there with decades of experience and also just coming out of school. It was the only time in my firm running journey where I knew I could start the hiring process and have somebody within 30 days. In fact, I just talked with someone who did that like within 14 days. So the talent is there. 2. English fluency Very good English speakers will have an accent usually, but very, very common to have strong English speakers in the Philippines. Cultural compatibility Very strong Western influences in the Philippines. So generally easy from a work culture standpoint to get connected with and then a work ethic. So Filipinos pride themselves on bringing energy and optimism to work, which isn't always the case when you're hiring somebody, right? So to have that enthusiasm on your team to provide an opportunity to these folks, an awesome career, a better path, opportunities for their families like they turn up to work with just an entirely different level of excitement. And that was my experience. Anyways, Team Ups put together a great guide for how to get started with this stuff. Swipe that one down in the show notes. This episode is sponsored in part by the folks at Canopy Canopy, the practice management system. I've spent a lot of time digging through PMs trying to filter through the 43PMs now that I believe are marketing to North American firms. As you probably know, Canopy is on my short list of recommended practice management systems and nobody likes having any more tools than you absolutely need to have. Right? That's why you start building your tech stack with, with the practice management system to let that do as many things as possible. And when it comes to all in 1ers, it's pretty hard to beat Canopy. In fact, a couple years ago when we did this giant roundup of feature comparison of all the PMs on the market, Canopy may have actually had the most complete feature set of any PM out there. Now that's not always the answer, right? Just more, more, more. But I can tell you we're also pretty burned out of just like having to build these ridiculously big stacks. So having a, having a PM behind your firm who has the mindset of we want to try to pull everything that we can into one platform for you and to know they're going to keep investing in that in the future. I can get behind that. Hey, I'm a big time tech nerd, but I also don't like playing software night janitor. So if I can get all that stuff in one place as much as possible, I want to do that. That's Canopy. To learn more about Canopy, check out the link down in the show notes. That's not, we're not done. There's more because it's a Q A Friday. Digits Digits has been around for a while. Digits had a big announcement video this last week saying they're launching the first, you know, kind of AI first accounting ledger. And I love it. It's super cool. It's, it's very exciting. I mean, I love that they're doing this. I don't know enough about the platform to know that I'm in love with the platform. Digits has been around for a while. They've done a bunch of things. They've got bill pay, they've got like quality assurance, they've got uncategorized expenses. They were this thing that kind of sits on top of your QuickBooks file and it's, it's pretty good. Like, especially, I would say the strongest part of their product was probably the quality assurance product. They would like identify outliers and help you with classifications and that sort of thing. That doesn't necessarily mean you're going to be good at, at building an accounting ledger because, because what they've built to date, I know people that use it, but it definitely was far from like getting a whole ton of adoption from accounting firms. If you've used the Digits ledger stuff yet, man, drop a comment like, let us know how it's going. I think the thing that we can all agree is the ledger space just needs more competition. Like it's, it's a lot of sort of legacy players and it's a place where it's really easy. Like you've got some players with really big moats like QuickBooks moat in North America or especially in the US is that quote QuickBooks is synonymous, synonymous with an accounting file. There's a lot of people that just if they need to spin up an accounting file, they go to QuickBooks and they don't even realize there's anything else. They also have the advantage of the ecosystem. And so if I'm in love with some tools that work with QuickBooks, then I'm only going to use QuickBooks because they only work with those tools. Like if you're in love with Keeper right now and somebody says come do this, like you get a bookkeeping client that uses FreshBooks or something like that, you're going to be like, it is going to hurt you more to serve that client because Keeper doesn't integrate with it right now. That could change, that could change down the road. But that is like that stickiness is a big advantage for QuickBooks and for zero. So to overcome that ecosystem advantage, it takes something truly different and truly like novelly better. And AI might be that step change that was required. Like the thing that can make it way better. An AI first ledger to where it's better enough to like. Even without having an ecosystem at all, it's still worth it for me to switch to that platform AI. My hope honestly is AI is the thing that gets us over that hump so that we've got some new ledger options. So I don't, I don't know. I know the digits guys very well. I've known them for years. They're super, super smart guys. Like from a technical engineering standpoint, time will tell if this sticks for accountants, but I can like, I think we can all root them on because the ledger space just needs more competition. Right. This was an interesting one. Somebody shared it with me via dm so I won't, I won't share who shared it with me. A Wall Street Journal article that I'll link in the show notes about how like venture capital is excited about investing in not just accounting software, but in accounting firms. And so there's, there's some, some VCs whose sort of investment strategy right now is to invest in technology companies that are supporting accounting firms with the ultimate goal of then rolling up the accounting firms themselves, which. Woo. How to feel about that. I was Actually talking with somebody that runs a software company in the accounting space one time that said there were users that had fears them stealing those firms, clients that like the software company stealing those firms clients. I'd never heard that before and I'd never even thought of that being a thing. The notion that you would be afraid of a software company stealing your clients. I'm realizing now this almost sounds like a joke because it's kind of what Intuit has done. The context of this other software company. The software company is run by an accounting firm and they had people coming in who would find out that this company also ran an accounting firm and then they were afraid that they were going to like swoop their clients if they put them on their software platform. It's interesting, I like a lot of feelings from this one. Never been a better time than now to be an accounting firm owner. Like they're just, you're everything about what you're building. People want PE super interested. I still have major struggles with any sort of third party exit. Like maybe I'm too connected to the people or not thinking capitalist enough or something like that. But even in my accounting firm, a 40 person firm, like I brought it, I brought, I guess not every one of those team members in, but I brought a lot of them in, brought a lot of those clients in for me, the business owner to be like, I'm going to cash out, I'm going to get whatever X for selling this firm and then peace. We've all seen so many versions of that where the people that get hosed are the clients and the team. So like I just have a lot of struggles with me getting all of these people to buy into me for my plan to ultimately bail on them. Right. Which is ironic in a lot of ways because in my case that's exactly what I did. I bailed on my firm to go and like focus on creating content for accounting firm owners. It was all done in as, you know, smooth and tactful of a way as possible. But at the end of the day, a lot of my most fervent followers came to work for me at my firm. And then I left my firm because I'm like, gang, I'm really sorry, but running a firm, like it's not the thing that's going to let me help the most people. So like I, I, I still struggle with any sort of like third party sale. I get the upside to it. Like, I mean you can do that all day and make a crap ton of money. It just burns some people in the process and it may stand to, I don't know, complicate your relationship with your software vendors a little bit. Right. Like, if you knew that was on the horizon, would that change how you interacted? Let's just, I mean, I don't know this, that this is a thing, but you know, we've got so many practice management systems out there right now. What if there was a practice management system who was like very into acquisition if this pm, because it has all the data about how profitable your firm is, if it has like three KPIs that says if your firm is this size, running at this level of efficiency and, and has, you know, this sort of client profile, we will make an offer to you at X multiple. Like if there was a practice management system where that was part of kind of the underlying premise of that platform, would it cause people to go to that PM instead of other PMs? That's actually fascinating because like, there's a world where like, when I'm in my sweatiest kind of like business boy mindset, which is usually when I'm just got out of bed and then a couple hours later I'm old and tired. But when I am in my most like, sweaty entrepreneurial mindset, I'm like, would it be fun to like launch and sell a firm every three years or something like that? Because right now, like, I could line up buyers, like, I could say like, what's the firm that you would buy at a premium multiple in three years? We could, I could literally probably lock them down to buy that firm at a pre like agreed to multiple if the firm meets these certain metrics. That's a thing that I could do right now. That's a thing that you can do right now too, if you have the network for it. And so I'm thinking in my head, I'm like, okay, how big of a firm in three years, how big of a firm could we, could we do without killing ourselves? Like there's, I mean, you could. In that time, I think I could pretty comfortably build to, you know, a one to $3 million practice, like without killing myself. You get a premium multiple on that. Let's say you're going to sell that for 2 or 3x. That's a, you know, a 3 to $5 million sale every three years. That's not a bad gig. And then I'm back just running accounting firm stuff. I could probably still do content, just not at the same volume. I. The reality is I still have that struggle of like hosing people in that process. I guess maybe the advantage here is like they're probably going to a much better home. Like it's another very modern firm runner that I, that I respect who's doing some roll ups. That's a much better destination than going to some random regional firm. Right. There's a part of me that that's appealing to and there's a lot of folks that are just building to to exit and that's what they want to do. For those folks, a practice management system like that, you're absolutely going to go there, right? Maybe you can't get the best multiple from them as opposed to having a good network of other folks who will give you a better premium. But there's definitely an archetype of firm runner out there who that would be attractive to. So seeing the software and like the M and A stuff kind of starting to overlap will be very interesting to watch. Last one, Ryan Lazanus. Ryan, Ryan. Ryan Lazanus. In many ways like in my mind that he was like the first the OG modern accounting firm influencer. Accounting has had thought leaders back to the beginning of time. But to me Ryan was the first guy who's like I'm an influencer and that's my business. And I who was running an online first accounting firm like in a very progressive way. It was a Canadian accounting firm but those are accounting firms too. What is was sick Burn rival rivals ass Launches Ryan Bot Get 247 personalized coaching to scale your firm and reduce your workload for just $14 a month from my AI clone. Ryan, bless your heart, you are a, you are a more brave man than I. So this is a real thing. You can go buy it right now. We'll put a link in the show notes. In fact go buy it like kick the tires on. I'm fascinated to see what you think what's interesting about this and what's interesting about the medium in general. I think specifically what's interesting about Ryan Bot is it is built on his own framework, his playbooks for how to run a firm. So Ryan like myself runs an online community called Future Firm Accelerate. And I always tell people who are thinking about joining joining an accounting community. If you want the template for how to run an accounting firm like a framework, like if you're like can somebody just tell me how to do this? Ryan. Ryan's community is the place to go. That's what Ryan does. That's not what I do. I my community. What I do is more like a peer networking community where you're going to Meet a whole bunch of other people like yourselves. You're going to make all these connections, and it is going to make it easier to find people to fire clients, to. To, you know, find a recruiter to work with. Like, just everything about running accounting firm to me, gets infinitely easier when you have an abundance of people, you can just ask, like, hey, who should I use for marketing? Who should I use for recruiting? And just always having those people on tap. That's what my community does. Ryan is like the framework guy to me, and that framework sits behind Ryan Bot and that. So that's really cool. Like, he's got something tremendously valuable that you get access to via that chat bot. It's the same. He's using the same platform behind the scenes that we've used with the bot that we've used on this podcast that's trained on all the podcast episodes, if you're interested. The platform is called Delphi. Delphi AI. You can. It's not hard to build the hard thing, and the valuable thing is the underlying context. So, like, it's something that absolutely you could develop for yourself, for your accounting firm, for your team to use, even. What's interesting to me is just this medium of getting access to somebody or to expertise. The medium itself hasn't been normalized. Like, that's almost the weirdest thing right now, is the tech is good enough for this to actually be really useful. So, like, you know, the bot that we've got, that. That has all of the. All the podcast episodes, like, you can get some really valuable information out of that. Also, what's really useful is, at least in my case, it points to the context it points to. This is in this part of a podcast episode. And we like, to be clear, I haven't really shared this bot publicly so much. I've shared it in a few places because it actually kind of gets expensive to run. And there's been a part of me that's actually thought about, am I going to. Would I do this one day? Like, exactly what Ryan's doing. I'm. Honestly, I'm. I'm afraid to, because. Because it hasn't been normalized. Right. But, you know, if you look at this through your lens and your expertise, there's a tremendous number of things you could put behind a bot that would be really, really useful to clients. And you could see that because you're like, man, I get this question every single day. This would be valuable for folks. But the people on the other side of it, like, people. I. I don't know how excited they are to talk to a bot. And maybe it's because I've only talked with chat cbt, which doesn't have a person behind it that I respect. And so maybe that's a different calculation. But I'm super fascinated. What is your gut reaction to this? If you, if you don't know how to feel about, like, go out and try. I mean, it's all 14 bucks a month. What do you got to lose? I'm. I'm very curious to see what you think about this. Is it icky? Is it interesting? Is it the future? Is it something in between? Drop a comment. I would love to hear from what from you what you think about it. I'm not gonna do the same thing anytime soon, but I actually love that Ryan has done this because it is a step to normalizing it and it's also going to be really useful for a lot of people, like it genuinely is. Again, I put a link to it down in the show notes. It's something that he shared on his his LinkedIn, but I'm going to be really interested to see how that develops. Gang, thanks for being here. It is a great week to be an accountant. Never been a better time than now to run an accounting firm. Honestly, it is wild. You got any questions? Pop down in the comments. Love doing these Q and A episodes every every Friday. And thanks for coming and hanging.