https://www.listennotes.com/e/9cddfc1b5ada46928bbcad2224a3ff55

This is a big one. There's a type of AI that is especially relevant to those of us who have like a specific type of expertise or advice through sort of our own proprietary frameworks. And so I'm thinking, you know, accountants, attorneys, consultants. For most of us, we rock up to an AI tool and the first thing that we do is we chuck the hardest thing we know into it just to see what it says. And we're usually left unimpressed. But that's like vanilla default AI. The AI that's gonna have the biggest impact on the ways that we work. It is the AI that encapsulates our expertise, the stuff that's proprietary to us. That's what we're talking about today. I've got kind of a new mental model for how to think about this, and I think it's pretty wild. All right, if you're an accountant, you know what an accounting ledger is. A ledger It is supposed to be like a complete picture of all of the transactions that run through a business, right? Every single thing that ever happens, it is like the encapsulation of all of that stuff. And most of the time, you don't really need to go back and like get a very specific thing out of there. Sometimes you do, but you have that record in the event that you need it. So we all understand how that works. It's fairly straightforward. It's a collection of transactions, could be small, could be massive. Let me introduce to you the concept of the mind ledger. Mind ledger, M-I-N-D, the mind ledger. What if you had a way to capture the things that you said, the advice that you gave to clients, the stuff that you posted on social media, in a format that was very similar to an accounting ledger, where you have a collection of transactions, what if you had a ledger Of all of the expertise that you dispensed, all of the value that you put out into the world, you actually captured that. And longtime listeners of the podcast, you are already rolling your eyes and identifying that this is just another podcast of Jason yelling at me telling me to use meeting recorders. And I kind of am, but also it goes deeper than that. Because when we think about AI, oftentimes, I would say actually the vast majority of people, and not the folks who listen to this podcast, but the vast majority of people, Their AI strategy is to hope that it doesn't get good enough to do their job. And many of them, they will say like, well, AI can never do X, Y, or Z, when in reality they are not AI experts. In fact, they use these statements to justify not learning AI and not experimenting with it. And so they're kind of like the last people that should be offering opinions on what AI could ever do. and usually those things that they point to to say that I could never do, it's from just a self-preservation standpoint, it is the things that we hold most precious or the things that we're capable of doing or we know or we think that other people don't. But my brothers and sisters in accounting, I think the most impactful AI applications, it's actually the opposite. It's exactly that. It's using AI for the things that only you know, and the expertise that you wield that is not general because we all have access to the same AI tools right now. And that's the big change of the generative AI era is pre-generative AI. The scary thing was the world's best AI models were controlled by the folks that had all of the data and the millions of dollars that they could invest into developing those models. And so in the accounting space, that was, you know, Intuit or zero, like who are the folks that have the most data? and big old checkbooks so that they can train these big old models and they're proprietary to them. These days, you have OpenAI, you have Google, you have Facebook, you have companies sinking hundreds of millions of dollars into training a single model, but these are all now public models. That is, we can all use them. Now, public model does not mean insecure. It does not mean it's training itself on everything that hits it. All it means is that that was not a model that was developed in-house behind the scenes by someone. So if Intuit right now goes out and they train their own model, they can keep that private so nobody knows about it and only they use it. But everyone today is using public models, Intuit included. And it's actually very funny in the marketing you see from companies these days. You look at big software companies like Notion or ClickUp or something like that. The way they talk about it is like we are using the best AI models available today to do X, Y, or Z and make our product bigger. But you'll see little itty bitty startups, and this is so common in the accounting space, and I hope people see through it. You will see little itty bitty startups say things like, We've trained our own models to do X, Y, or Z. How likely do we think that is? That this company has trained a model that is more performant than the models that big companies are investing hundreds of millions of dollars into training. They're not training their own models. They are most often doing retrievals with public models. That is, the documentation that they give to the model to do a job is proprietary to them. And so, you know, a good example is aicpa or cpa.com right now has their own AI assistant. They're kind of taking their own swing at doing like ChatGPT for accountants. And there's a lot of, I mean, there's some problematic wording in there where they're saying some things like training your own models or being more secure or something like that. The only thing in reality that is unique about these solutions is how they prompt the models and the information that they give it as part of the prompt. So for example, I could take the transcript of this podcast. and say, build out an AI strategy for my team according to this information. And it will follow all the stuff that I'm saying here and build that out accordingly. Now, if that transcript is something that is proprietary to you, that's a cool opportunity. That's not training your own models. That's using the same public models as everybody else, but doing a specific job with them. And these small startups that are saying this, that is all that they're doing behind the scenes. Now, think of yourself as one of these software companies. What do you have that's proprietary to you, unique to you, that you could use to put AI to work? It's your expertise. It's the mind ledger. We're seeing like the very, very beginnings of this with AI meeting recorders, where we're capturing the meetings and the conversations that we're having with clients. And you think of, if you think about this across the entirety of an accounting firm or any service business, professional services firm for sure. All of these meetings that are happening every single day, the transcripts from those meetings are the greatest, most realistic representation you have of the collective expertise of the firm. And that is the only thing that is unique to your firm. Firms all run on the same software. Like we're not building our own tech by and large. We will have different processes. We will position ourselves to serve clients differently, but the expertise of the firm, the greatest snapshot we have of that is all of our meetings. And the thing that AI is best at right now, like while it's impressive at just like summoning up general stuff without giving it any context, I would argue the thing that it's very best at is applying specific concepts from information that you give it to a particular problem or, you know, write up this thing using these six bits of information that I'm giving you. And so if you've got a hundred meetings of how you advise around a very specific thing and the next person comes up and has a question that AI, it's gonna be pretty darn good. Just think across like all of the work that you do in your firm. When's the last time you got a question that was like truly novel, truly unique, you hadn't, experienced it before. That's very, very rare. In fact, from the first episode of this podcast, we've had an AI assistant that you can interact with. We're now 470 episodes into this podcast or something like that, and that AI assistant has gotten pretty darn good. And it's smart enough to not answer questions around things that I've never discussed. But after 470 episodes of the podcast, we've discussed a lot of things firm running. It's actually kind of funny 'cause I can see on the back end, I'll put a link to this AI assistant in the show notes if you wanna play with it. And I get an email notification anytime somebody asks the assistant a question that it can't answer. It says, I need more information, it comes and sends me an email. And usually the stuff that it stumbles over is, what was that cool palm tree shirt Jason was wearing? What is Jason's favorite ice cream? Sometimes stuff that's even more weird than that. Just know I can see that, okay? I see the weird stuff that you're putting into my chat assistant. and the tool I use for this, it's called Delphi, D-E-L-P-H-I.ai. There's some pretty cool stuff built into this around even like on some of the higher tiered plans, you can give it to like plug, you know, some of your company resources. So like me and my business, I've got a number of lead magnets, basically really useful things that you can have for free, you just have to provide your email address. And if you've got 10 of these things, you can tell Delphi the tool that you have these resources and anytime a question comes up that's related to it, It'll kind of give them an answer, but say like, hey, you can do a deeper dive here with this free resource and it'll pass them off to it. It'll actually give them the link. So this thing is like working for you, doing your bidding around the clock 24/7. And right now, using these assistants, it's kind of weird. Like it hasn't been normalized. In fact, I would argue that the usefulness of them right now is like outpacing our comfort with using them. Maybe we'll get more comfortable with using them over time than we are now, or maybe we'll just, oh, we always want to hear from the human directly and we just won't trust what that assistant will say. I will say one thing that Delphi does really good is it doesn't just give answers. Like it's, I mean, it's pretty amazing. You can answer a pretty complex, like multi-sentence or you can ask a fairly complex question and pretty much instantly across 470 episodes, which is, you know, over 200 hours of audio, it will pretty much instantly give you the answers. but with citations deep linked into the timestamp of like when I said that inside of a podcast. And it'll pull together like a page to two pages of text across all sorts of different episodes and synthesize that into an answer. It is really good. Honestly, the worst part about that assistant right now is that its tone of voice is the tone of voice that I use when I'm speaking, which is very different than the tone of voice I use when I'm writing. When I write, it's like very, short, very direct, like try to keep it at a fifth grade level. Like it's very, very simplified. When I talk, it's much more like over the top. And so the assistant will be like, Hey, guy, how's it going? And it's like, just cool it, okay? But I would argue that AI is already good enough to retrieve across huge amounts of information very, very, very accurately, which means the only thing stopping you from having a tremendously useful assistant is your documentation of thought. Like how like you have a job, so you don't have 470 episodes of you railing on about running accounting firms or, you know, supporting taxidermy businesses or whatever it is that you do. But you do in the course of running your business. And this is really wild for folks running bigger teams who are having these meetings every day. You do have a huge volume of meetings. And so you can see If we're not there already, you can see a very near-term scenario where you have a mind ledger, a library of the things that you've said and the ways that you've advised people that's tremendously valuable. That is the single greatest representation of your expertise in the things that you know. Not unlike an accounting ledger, where it's a perfect record of all the transactions that have happened, the mind ledger is a record of the transactions that you've had with your clients, the stuff you posted on your social media accounts. It is a record of your expertise. And this is the most profound change that AI will enable for professional services firms. What do we do with it? Because it's very, very good at sounding just like you and answering the way that you would answer a question and even not answering a question if it hasn't seen from you an answer that is close enough to be able to confidently provide that answer. So it is a very good simulation, facsimile of your expertise. But as we've also seen out in the wild, increasingly, AI can create speech like voice, like talking that sounds very, very similar to you. For most people, it's good enough to pass as like you not even realizing that it is AI. If you've listened to a ton of this podcast, you know much more about my tone than the average person does. So you would be able to pick up something that 99.9% of people would not. My wife similarly, like she is another level where she could be like, no, like that's not his tone. That's not how he would say that thing. But that's not normal. That's like, that's not 99.9% of people. So we have a facsimile of what you know. We have a facsimile of what you sound like. And as you've probably seen, we also have facsimiles of what you look like that are very, very convincing talking head. like AI avatars, like a person sitting at a desk. I would say they're also to the point where the vast majority of folks can't delineate between what's real and what's not real. This episode is brought to you in part by Cloud Accountant Staffing, who helps you hire staff, come work for your accounting firm, but they live in the Philippines. I did my firm, my last four hires were in the Philippines. If you listen to the podcast, you know this by now, but when you're getting inundated with like all sorts of offshore options every single day. How do you know what the right one is, huh? Well, I can tell you for one, cloud accountant staffing, we partnered with them because I actually know a bunch of firms that have had a very good experience with them, but they also used to be an accounting firm. So they get it, man. Now another reason we're heading into conference season, cloud accountant staffing, they're actually gonna be out at a whole bunch of the big accounting conferences, same ones that I'm gonna be at, which means Man, they're part of the zeitgeist. They're out there jamming with accountants hanging out. They get what's going on. They know about the new tax bill. They're in the thick of it, man. And I want that with the people that I partner with, not that random weirdo that just sends me a LinkedIn DM. Okay, that's not the move. If you never hired in the Philippines before, you're gonna have a bunch of embarrassing questions. They can answer them for you. You got nothing to lose. To learn more, check out a link down in the show notes. This episode is sponsored in part by Mercury, which I am oh so happy about because I am actually a big Mercury fan, a user myself. So Mercury is a fintech that over 200,000 companies trust for banking and running their finances because the traditional way of getting this done, those platforms, big hot pile of new sponsor. There they go, walking right back out the door. Like I said, I'm a happy user myself. It is a modern platform. We liked it so much we actually moved all of my businesses to it. Now Mercury for accountants. It's a referral partner program that allows firms to give their clients VIP access to the Mercury product and unlock special perks. Tell me more. Dedicated onboarding and support for firms and clients. Thousand dollar referral bonus for every new what? Okay, per eligible client. An advisor portal for easy team and client management. Mercury Pro for the firm. Nice. Check out the link down in the show notes to sign up and learn more. Disclaimer. Disclaimer. Disclaimer voice. Mercury is a fintech company, not a bank. Terms apply for bonus eligibility, see show notes for details. If you want to get real sci-fi, we've crossed the threshold where you can have very true to life interactions with avatars of a person, which means my kids, long after I'm gone, will be able to interact with a 35 year old version of me, a 45 year old version of me, a 60 year old version of me, well after I'm gone. And unfortunately, the 35 year old version of me is gonna give a lot of answers that sound like they're for an accounting firm owner. But if you think about all the different ways that we are documented these days, from your emails, to your teams and your Slack messages, to more on the personal side, your text messages, your WhatsApp messages, all the ways that we're documented now, like we are, this is the least documented that we will ever be right now. And so this is like the lowest resolution that these facsimiles of you will ever be today. But already, they're very, very good. I love doing Q&As on the podcast, and I go around the world and do Q&As about all sorts of things at conferences. The reality is 98% of those questions can be answered by this AI assistant. And when I see those answers myself, I'm like, I don't know if it's right, but that's what I would say. It's very, very accurate. So how do we use this inside of a firm? And does it even create some problematic situations? We all get bent out of shape when software companies say that they have the right to train their models on our data. Well, what about somebody who comes to work for you? And over the course of working a couple of years, you have, you know, 500 meeting recordings of theirs. And that informs sort of this hive mind assistant that you have inside of your firm. and then that person leaves. Like, do you still have the rights to all those meeting transcripts? I think probably most people on the employer side would say, like, I employed that person to come and hold those meetings and all that. Like, yes, those are my property. But there's a line, there's a version of this where it's like such a real representation of that person where it probably is going to feel like crossing a line. So maybe we can leverage that person's expertise what about their voice? What about what they look like? That's much more creepy, right? That's a lot more weird. But should the visual and the audio really be any different than what they would actually say, which is the vastly more important thing, you know? So that stuff gets a little bit more spooky. But once we have sort of this record that's a very accurate snapshot of how we advise, it's going to be really, really dicey to identify the right ways to put this in front of people and the wrong ways to put this in front of people. So low stakes ways to use this right now. And this is something that you can do, and I would encourage you to do internally with your team, just using like a custom GPT where you just upload the files or point the custom GPT to, you know, a folder in your SharePoint or your Google workspace or something like that. A really low stakes use case here is for your juniors to have access to an assistant or maybe multiple assistants that are more contextual. So maybe there's an assistant that's like, we run these monthly meetings with our clients every single month when we deliver the financial statements. This assistant just has the recordings for all those monthly meetings. Maybe there's one that just has all of the recordings for a specific client. Maybe there's one that's more like HR oriented. Maybe there's one for kind of your training documentations and documentations, documentation and recordings of sort of past internal meetings you've had on that topic. any version of this is immensely helpful to the juniors in your firm as a first line of defense before coming to you for the answer. And it shouldn't ultimately replace you having real interactions and connections with these people. But the fear of it replacing those connections, that's not a reason to not use this stuff because most people need a lot more help than we have the bandwidth to give them. So that's an example of a good, really low stakes way to use this stuff. A higher stakes way to use this stuff is externally with your clients. But it feels inevitable because all else being equal, if you have two accountants that are serving clients largely the same way, but one accountant gives the client access to an AI assistant that works 24/7 and has, you know, access kind of to your expertise and how you advise. That's just a better client experience because there's going to be a day where the client sits up in bed at two in the morning and is like, crap. Was I supposed to make that payment in June or in May? And they can ask this thing a question, and if they can get an instant answer, that's really, really valuable. So it's useful for your staff, it's useful for your clients. But the next stage here, and this is a big one, is it's going to be useful for AI agents that are working autonomously. So zoom out a bit. AI agents just to kind of level set, AI agents are like a thing that can navigate the web, navigate your desktop, navigate. APIs of software on their own to get a job done. So you give it kind of a more open ended task and it figures out how to do it. It fills in the blanks, goes out and looks kind of all the different places that it needs to get that job done. The best example we have of a AI agent in the wild right now is ChatGPT operator available on the $200 a month Pro plan. It's like a ChatGPT chat interface. but it has a built-in web browser. So I can tell it, go out to this conference and pull all the AI talks. I'm into AI stuff. And it will go out and it will find that conference website, it will find the agenda, we'll go through all the talks, see the ones that look like they're AI related, and then return to you with like a short list of these are the things that you should catch. Now, logistical problems with these AI agents today, how do you handle like authentication, logging into things? Because what I really want to do is send it to QBO and say, go reconcile the bank with this PDF bank statement. Already ChatGPT operator, it will remember logins. So you can log in in once and it will stay authenticated within reason, depending on how long that software platform will allow you to, or will recognize that as like a remembered device. But some headaches around that stuff. But these agents, like there really isn't any limitation to what they can do. Besides right now, they're not super smart and they're pretty slow. But all things AI right now is improving very, very quickly. And this is a really important realization. There's no limit to the number of agents that can be working for you at a time. And 100 things being cut loose that kind of suck is not useful. In fact, probably just makes a mess. But if they can do anything marginally useful for you, that becomes really, really powerful. And so if you think about ChatGPT operator, just rocking up and asking it to do a task today, That's just like going to ChatGPT and raw dogging it for a, you know, technical answer. If I didn't give it any of my own context, it's giving me the default vanilla answer. Similarly, when you cut an AI agent loose to do a task for you and we all have access to the same tool, what firm's agent will be most performant? It'll be the one that has access to your SOPs and to your expertise. The old mind ledger. How you navigate a problem can be informed by the things that you say, by the ways that you train your team, by how turnkey that system is inside your firm, or isn't super reliant upon like this sort of black box, you know, unicorn wizardry, where somebody just kind of makes a decision based on experience or something like that. The folks who have the best, most informative context that they can feed that agent will have the most productive agents. and you know what that sounds like? Sounds like working with humans, right? Like the people with the best processes, the best documentation, they set the clearest expectations. They also have the most productive humans. The difference now is leverage, is the fact that there is no limit on the number of agents you could have working for you at once. And even as we cling to, well, it can never talk like me, it can never sound like me, it'll never think like me, that might just be the thing that it's very best at. like that might be the most useful application of AI. Now, it's gonna be really easy to get this wrong. And AI avatars are a great example where like this copy of you that visually looks like you talking and saying this thing, that's very impressive. It's kind of this razzle dazzle cool AI thing right now, right? Like just kind of a party trick. And if you deploy that in a situation where before there was like no human answer or no interaction or something like that, that might feel novel. So, you know, it may be impractical to record a video for 2500 of your tax clients every single year, and maybe you've never done that. And so using AI to create that, maybe that's cool. But if right now you send a video delivery with every set of monthly financial statements and you switch that to being AI, I could tell you if that's me, I'm probably just gonna feel insulted. if I'm on the other side of it, because it really means that you couldn't be bothered to take the time to make that yourself, even though you used to. So deploying this stuff where before there was no version of it at all, or there was no level of human connection, I think that's pretty cool. That's an opportunity. That is the AI assistant that will give you instant answers, but you're still allowed to ask me. But the AI that replaces what was once a human thing that's trickier. Oftentimes I think that's gonna feel insulting. There will probably be some situations where that's still useful because clients will come to us, frankly, oftentimes with very low quality questions. And so an example in, you know, like help desk support scenarios, you've probably bumped into this where you email support@whateverthecompanyis.com, normally you get the auto response saying, here's your ticket number, we'll get back to you as soon as we can. Now oftentimes what you'll get in that auto response is your ticket number, but what it thinks is probably the answer according to its help docs as written by an AI. And you can click a button in that response to say, thanks, this answered my question. So AI takes an initial stab at trying to solve your problem for you. And if that did resolve the problem, then you can acknowledge that and be like, I don't actually need the human to help me now. But by default, that that inquiry stays open. So I think there's probably a version of that that becomes pretty compelling and maybe looks more like how we support clients when they send you a message. Can AI give them an auto response that might resolve 50% of those inquiries? If it can, I think that's a win for everybody, right? It's getting the client a faster answer. It's saving you having to hop in there yourself. Today's episode is sponsored in part by ClientHub. the practice management system that delivers wow seasons year round, not busy seasons, seasons that will dazzle your clients for two reasons. One, client hub, just drop that simple man. If you're too tired of a practice management system that just feels like you gotta have a PhD and learning something new, client hub, you hop in, the vibes are great. It just all makes sense. But two, remember there's a second reason client hub offers a game changing client experience. That is you can actually get to like collaborate with you and be helpful on the platform. Cause the portal wasn't this like afterthought bolt on now very cool. Uh, recent development in client hub magic books review twinkle sounds. So client hub sinks in the transactions from your QuickBooks file. You can run an AI analysis on it like from inside of client hub. It'll highlight any potential issues you can mark like on the balance sheet and the P&L, you mark each account one by one, whether or not it's been reviewed. But if you want to troubleshoot, it'll pull you straight back into QuickBooks, like so you don't have to learn like a whole new troubleshooting tool if you'd rather sort that stuff out in QuickBooks. Other cool stuff it'll identify automatically, expense inconsistencies, purchases without a payee, purchases in parent accounts. Why is, why can we not disable that in QuickBooks? Large transactions, new accounts, new vendors, new customers. It's Magic Books review inside a client hub. I think you might like it. Learn more about client hub. Check out the link down in the show notes. TeamUp is a recruiting firm that helps you hire direct in the Philippines. Talented accountants. That's different from the outsourcing or offshoring companies you most commonly hear about where you're actually hiring the company. With TeamUp, you're just hiring a person. Because you can just hire people in the Philippines. Same way that I may hire somebody in Reno, Nevada. Actually, a great example. That's a pretty, pretty suspicious place. I'd say the Florida of the west side of the United States. How do I trust them? How do I train them? How do I do XYZ? Well, how do you do it for like your own short people? But you really are just working with them. They're an extension of your team. That's what Team Up specializes in. So with Team Up, you do a flat one-time price to recruit that person. Most hires are about four grand, this one-time fee. Team Up, no ongoing costs. most offshoring groups about half of what you're paying is actually going to the company, not to the person. Teamup even has a guarantee. If that hire wasn't a fit for the role that you put them into in the first six months, Teamup will find you a replacement at no cost. Does Indeed do that? They don't do that. Hiring in the Philippines is simpler and easier than you think. My last four hires in my firm, this was like three, three and a half years ago, they were all in the Philippines. If you want to learn more, check out a link down in the show notes to schedule a call with Timo. And just to acknowledge what's uncomfortable about this, the notion of something sounding like you or replacing you in terms of the answer that you would have given. There's a very real comfort level and trust sort of thing here where we have to disclose this is an AI and the answers won't always be totally accurate. But boy, have they gotten better? Boy, have they gotten more accurate? And boy, is it useful more often than it's problematic, generally? And obviously devil's in the details in how you deploy this. It's like, you know, Wikipedia, early days Wikipedia, everybody made fun of it where they're like, this is how is this authoritative? This isn't an encyclopedia. It wasn't put together by, you know, experts. And now people rely on Wikipedia's a lot, Wikipedia a lot. And when's the last time you saw Encyclopedia Britannica in the wild? It's getting better every day, so it's going to be part of how we serve clients day over day. But the devil's gonna be in the details of how we do it, and it will only ever be as good as your mind ledger. Something about that framing of it being like kind of like an accounting ledger, but for the things that you said and the expertise that you've given, that was really helpful for me. And now because AI is really good at synthesizing answers out of context like that, It means like your expertise is kind of infinitely accessible now, right? To the degree that it's documented. Like, there's no limit to the number of people that could talk to the AI assistant for this podcast. We are all on this same path. Like, I know you don't have an AI assistant trained on 470 episodes of a podcast, but we're all on this path and you will very soon have that. And so while that mind ledger gets better every day with every single meeting that you take, and alongside that AI models continue to just get more and more powerful. The result is the marriage of those two things is you is something that is very, very close to you. Now, it can't replicate like the vibes of meeting with somebody live, being in person and like hanging out and riffing on ideas. But let's be real. What percentage of your clients did you do that with last month versus what percentage were you just emailing? We're just chatting back and forth. And so on the other side of this, I think it means a higher level of service, greater access to answers for our clients, and probably a greater focus on what's left. And that is more connection. That is like making time for connection for connection's sake, because that stuff still does matter. There's no shortage of education online about how to run accounting firms, but we're here hanging out, right? We still go to conferences, we meet in person, that stuff still has value. And I think the value of that goes up even more when our expertise is as accessible as it's ever been. What do you think? Speaking of meeting in person, upcoming events. I sure hope these AI events we've got coming up are available for you to sign up to by the time this podcast goes out. Keeps getting pushed out. But we've got an events page@jasononfirms.com now coming up June 24th in Orlando, Florida. I've got a meetup going on on the expo hall floor at Scaling New Heights. July 14th. I'm in Los Angeles, California, for a one day AI conference. We're running that same conference July 16th in Denver, July 22nd in Chicago, and July 25th in Atlanta. We thought we'd have tickets and like signing up up by now. It's out of my hands. There's been some issues. Hopefully by the time this comes out, it will be up. But either way, if you're in one of those cities and you go and check right now and it's not available on a future podcast, I will let you know it's live now. You can hop out so you don't Miss out. Got a bunch more live events kind of in the works too that'll be coming up later in the year. I'm gonna try to bookend these podcast episodes, always saying upcoming events at the end so that you don't miss out. Honestly, my favorite thing is hanging out, meeting you in person. Met a whole bunch of folks at Engage last week. We did a meetup on the expo hall floor when it opened that over a hundred people came to. And that's cool from the standpoint of me getting to meet you. But what's even cooler is you're standing around with a whole bunch of other people that listen to the podcast that are into the content and like everybody left that meet up with some new friends. Like that's that's kind of the coolest thing about it. We'd love to see you there. You got any thoughts on on kind of the Mind Ledger, like the ways that we use AI to amplify our expertise expertise. Drop that stuff down in the comments. I'll see you in the next one.