Why AI initiatives stall in government organizations—and how to fix it

You're accountable for outcomes you don't fully control. You're expected to modernize faster with the same constraints, the same procurement cycles, the same leadership rotation. You've sat through the AI briefings. You've approved the pilots. And you're still not sure it's actually moving the mission.

That's not a reflection of your effort. It's a reflection of a system that wasn't designed for this pace of change.

In this Mission O/S Live, Rise8 Founder & CEO Bryon Kroger sits down with Barry O'Reilly—author of Artificial Organizations and Lean Enterprise, and advisor to executive teams across the globe—to get specific about what it actually takes to lead effectively in the AI era.

The research is blunt: 95% of AI initiatives fail to deliver measurable value. Inside government, where programs are already under pressure to justify investment, that's not a statistic. It's a warning.

They'll cover:

• Why AI initiatives stall at the system level — and what leaders can do about it from where they sit
• How to make better decisions faster when rotation cycles are short and the mission can't afford to start over
• What decision velocity actually looks like when you're operating inside complex, constrained systems
• How to build a leadership operating system that makes you more effective now

Bryon Kroger (00:31):

Hello everyone. Welcome to the Mission OS Livestream. I'm your host, Brian Kroeger. And for those that don't know me, I spent 10 years at Duty Air Force. The first seven is a targeting officer using really terrible software to conduct very critical missions. I got the privilege to fix that in the Air Force acquisitions where I co-founded a very successful transformation project called Kestle Run. And I got out and started RISE eight to help others do the same. And now we've launched Mission OS to share all of our lessons alongside this live stream where we extend the conversation with government and tech leaders and explore what it really takes to ship across people, process, and technology. So today I am super excited to have Barry O'Reilly joining us live this morning. When I read The Lean Enterprise, it was one of the turning points in my own journey in how to transform large organizations.

(01:19)
But Barry spent over a decade in the rooms where the hardest leadership decisions get made, advising CEOs, executive teams, and boards across the globe, not just in the United States, on how to redesign the way their organizations perform, decide, and innovate at scale. So he's the co-founder of Nobody Studios, a global top 10 AI venture studio, faculty at Singularity University, and bestselling author of Lean Enterprise, which I mentioned. Highly recommend picking up that book. Unlearn, another great one, and his brand new book, Artificial Organizations, which I have been sending to everybody on my team and telling them, "You must read this right now and we need to talk about it. " So we'll be digging into that today, but his work cuts through the AI hype, in my opinion, and gets at what actually matters for senior leaders. It's like the book that I have been waiting to read, not the tools, but the judgment, not automation, but decision advantage.

(02:09)
So thank you for being here, Barry.

Barry O'Reilly (02:11):

I'll listen here. That's the nicest intro I think I've had in a while. So yeah, look, it's a pleasure to be with you all.

Bryon Kroger (02:17):

Thank you. So one of the stats right off the bat in the book, and the opening salvo of the book is just a ton of unbelievable stats and survey data, but 95% of GenAI initiatives are failing to deliver measurable ROI in the enterprise. It's not a technology problem. So you've been in rooms where some of the most ambitious AI initiatives have been put out. What's the pattern that you keep seeing in the ones that aren't working?

Barry O'Reilly (02:45):

Yeah, so there's a couple of factors that come up straight away. And that report you just mentioned, 95% of GenAI failing, that was done by MIT. So these are super rigorous reports. This is not just five people in a room you're asking. They're really deep researched. And what they're seeing is even the programs that are successful, they're seeing a less than 5% increase in EBITDA. So that's basically profit after you've paid all the bills. So we're not seeing massive returns from people investing in this, and that's an issue. A couple of the key ones to stand out. The first one is when people see AI adoption as a tools initiative rather than a personal transformation, there's just failure written all over that. And I think this is one of the challenges we're facing in the market. These businesses, I'm here in San Francisco right now.

(03:40)
We had the book launch last night, and there's businesses here with millions of dollars in marketing spend that are on your Instagram feed. They're on your LinkedIn feed, they're on your Twitter feed, and they're telling you, you need to use our tool, you're too slow, you're falling behind. They're creating this sort of fear selling, but it's all about tools, tools, tools, tools, tools, tools. And that is, again, the worst place to start when you're trying to adopt this new way of working. So one of the quotes that everyone loves in the book is, if you're just adopting AI and you're not having any behavior change, it's just decoration. And it really is. So for me personally, my experience to come into this world was about six years ago. It was just as we were starting our venture studio, Nobody Studios. We had a two-year-old, our first, second baby was just born.

(04:35)
I was trying to launch the venture studio. I had more work on my plate than I could imagine. My wife had gone to bed, my dinner was cold. I was working on some-

Bryon Kroger (04:44):

This sounds familiar.

Barry O'Reilly (04:45):

Yeah, right. And I was sitting there going, "There's got to be a better way. I cannot keep working the same way and expect to go after these opportunities that are in front of us." And that was a big aha for moment for me where I fundamentally had to change the way I worked. And that involved me starting to experiment. First of all, understanding myself though, how I did my best work. And again, this is one of the models that's very helpful for a lot of people in the book. It's called a 3T model.

Bryon Kroger (05:17):

Yeah, I was going to ask you about this.

Barry O'Reilly (05:19):

Great. Yeah, your traits, your tasks and your tools. So for most people, and you're probably familiar with this from doing transformation programs before, most people start with tools thinking, "Oh yeah, if I just use this tool because the market has told me Claude is the coolest tool or GBT is the coolest tool." Most people just start using a tool and try to apply it to a task that they have, never even thinking about the way they do their best work. So they try these tools, there's a lot of friction and they struggle with it, and they sort of give up and go, "Oh, AI's not there yet," or, "This tool isn't for me, " or, "I'm just going to go back and do it the way I always have. " But that's the wrong approach. You actually have to start with yourself. How do you do your best work?

(06:09)
And for me, and I'm sure folks, a lot of the leaders on this live stream, I spend a lot of my time talking. I'm in meetings, I'm in problem solving sessions. So the way I generate my best information is in productive debate with people. It's almost a Socratic back and forth.

(06:33)
And I'm also dyslexic as well. So typing is actually a friction for me because I'm trying to spell ... How do I spell simultaneously? Oh, now I've lost my thought because I've got to figure out how to spell that word.

(06:49)
So when I became very attuned to how I do my best work, and talking being a huge part of it, then I was like, well, for my tasks, what are my highest leverage tasks? And for me, they're often one-on-one calls with coaching founders or execs, they're team calls, like weekly business reviews with some of the startups in our portfolio, but that's where I have my most leverage in those sessions. So as I started then to go, well, my trade is talking. The highest leveraged tasks are meetings with high stakes meetings. And then the tools then is obvious then where I should start to experiment with. So for me, having a meeting Copilot was basically an obvious thing to start doing because one, I could fully dial in to the conversations with people, be fully present. I knew I was creating essentially an audit trail of the conversation so I could go back to it.

(07:52)
And also I was creating a data asset. And probably this is one of the things, a big mindset shift I would say for people is in the manual world, our human only world, I'm relying on notes, post-it notes, stuff on the back of bubblegum packets, trying to remember

(08:11)
What conversation did we have. But then suddenly I got to this world where I could be a hundred percent focused on the conversation knowing that I have a real-time data feed I'm creating that I can go back, I can recall, I can challenge it, I can compound that data over time. So every conversation for me started becoming an information asset that I can use it. So my recall at the end of the day, I literally just started going, right, put all the transcripts into my LLM, what are all the meetings I had? What were all the actions? What's all the follow-ups? Who do I need to farm things out to? That would've taken me two or three hours. That went to 15 minutes.

(08:56)
And then the way I started preparing for meetings ... So when folks met with me, I would be sending them emails three minutes later with a full breakdown of key discussion points, key decision, key information, decision to be made next week. They actually started getting freaked out. They were like, "How did you do this? " We were just talking three minutes ago. So again, this tempo and the quality and ultimately expectation of working together, people started going to me, "This is great. I have great clarity about what we expect from each other." And they knew if they were meeting with me, we weren't meeting to try and remember what we talked about last time. We were meeting to make decisions. So it was like, let's show up with the information we need to make the decisions to help us move forward. And if that meeting's booked for an hour, if we make the decision in 15 minutes, we're done

Barry O'Reilly (09:53):

The next thing. So you start getting all these second order effects of not only productivity because that's table stakes, but you get performance or even better as an exec, you get presence. You start showing up to these things calmer. Your head is not as full of information from the last meeting wondering the five actions I just got, how do I remember those and then be present in the next meeting and then be thinking about the problem I got to solve next week. So it just became a totally different world of operating and that is really what the book is about. It's about showing people this leadership operating system that can give them their life back in a way. And that's exciting.

Bryon Kroger (10:39):

Yeah. It's interesting you say that, right? I'm coming off the heels of Impact Labs Ship Summit that we did where we taught people to vibe code at all levels. I had a 06 senior material leader, acquisitions officer, Vibe coding and app, some really young people who are new to their careers and everybody in between. My head of HR or people ops, we call it here, on the flight home vibe coded an app to integrate with Greenhouse and do all sorts of stuff that we've just not been able to do. And so that was on my mind. And then I pick up your book and I'm sitting here thinking like, "Oh, I got to start vibe coding more." And then it really pointed me to like, "That's probably not my highest leverage task." If I'm vibe coding for the organization, that's fun and it's cool. And it's also very addictive by the way.

(11:27)
But your book I just found was full of so many practical tips on how to make me a more high leverage leader. And they seem very obvious. And all of the things that you talk about are things that are being talked about in the community about decision, advantage and velocity, but you had very practical tips for actually doing it. So you mentioned traits, tasks, and tools. I thought that was a big one because like you, I've been wanting to write the Kessel Run story for a long time. I'm not a bad writer, but for me to sit down and write like you, it's not when I'm at my best. I write my best things after long conversations, but it's not something that ever really dawned on me until you were like, "Hey, I'm like a verbal person.This is the way I process all my information.

(12:08)
And if I can take that, turn it into writing based on high leverage tasks that I need to do, then choose the tools that match that. " And I was totally reversing that, I think, like most people. But for the next part, you say, you've already talked about capture and transcription, but you have the CTSA, which is like the new plan do check act loop for you. So capture and transcribe, but synthesis and action, besides ... I mean, you said in a lot of one-on-ones with your CEOs initially, it's like, "Hey, easiest thing you can do is just start transcribing all of your meetings with AI and capturing and transcribing." For synthesis, what are you finding? I think some folks struggle with synthesis actually because AI will not necessarily give you the right results. You have some practical tips for prompts and things you can do, but is there anything that you think folks might be missing when it comes to like maybe they've already started transcribing everything, but they're having trouble turning that into good synthesis and action?

Barry O'Reilly (13:06):

Yeah, no, great question. Right. So as you said, one of the models in the book is this idea of capture, transcribe, synthesize, and act. And it's four steps, but three of those, the machines are best at, and one of those the humans are best at. So machine capturing, you're getting atomic binary information. Let the machine capture everything. It's good at that. Transcribing, again, it's good at that. You can use markdown files. You can download things out of whatever tools you use, Copilot auto into a Word file. But Synthesis is actually a really interesting activity because most leaders struggle, right? When you know this yourself as a CEO, it's a pretty lonely job. It's hard sometimes to turn around to people when you've got a half baked idea or a hunch or a strategy or something that you want to really test out. Sometimes when you turn to your team and go, "I'm thinking about opening an office in a new region." Suddenly people start extrapolating like, "Oh my God, we're all moving to ... " And you're like, "No, I just want to add out an idea and see what I'm thinking here." And so that is a tough space for leaders is to have this sort of experimentation space where you can really push your thinking.

(14:26)
And that's the power of synthesis with these LLMs, I argue. So for me, what I would be doing is I would download, say in the venture studio, right? We've a portfolio of 14 companies moving at any one time. That's 14 potential meetings I could have in a week with the leadership groups there. So what I would do is download all of these calls and I would put them into my LLM and I'd start asking challenging questions of myself, but all focused around decisions. So what decisions need to get made across the portfolio and what blind spots could I potentially have? What are some of the implicit assumptions that I should be aware of that keep coming up in these conversations? So I'm not asking that synthesis is not summarize the meeting and tell me the actions. Synthesis is pressure testing your thinking. It's actually asking disconfirming questions about what potentially happened in these meetings and getting feedback.

(15:26)
So for me, that's a huge part of what helps make my thinking more resilient.

Bryon Kroger (15:36):

Because we started this by saying a lot of these initiatives don't have ROI, but you had stories of several CEOs and VPs, but there was a, I want to say it was a SVP or VP at American Airlines.

Barry O'Reilly (15:47):

Yeah, Misty.

Bryon Kroger (15:47):

Yeah. Misty. Yeah, that was the story. That one or any other, are there any that really stick out in your mind? I just remember that one because she was doing this and she actually had some really great things that turned into ROI for the company.

Barry O'Reilly (16:01):

Yeah. So Misty is basically the VP of commercial for American Airlines. So largest airline in the world, she's responsible for revenue generation. You don't get more of a more pressure job in the airline industry with the fuel prices right now. So she is in the thick of it, but her natural style of working is, she thinks out loud. She externalizes a lot of her thoughts and she's also a huge fan of Bernay Brown. Bernie Brown has this great expression like to rumble. And a rumble is basically this sort of back and forth, productive descent conversations that you want to have with peers. So Misty, again, she doesn't have her best ideas sitting in innovation workshops. She has them when she's walking around talking to customers, when she's spending time with the ops crew and sees a problem. So in what we were started working on is she was aware her trait was, I think out loud, I'm a talker.

(17:04)
Her highest leveraged innovation tasks is like looking for these revenue opportunities or commercial opportunities. So she started just talking a lot of these ideas out as soon as she had them. So she was down in the hangar working with the operations team and saw a problem. She'd literally just start transcribing into her voice note going, "Okay, here's one of the challenges I see. We probably need to optimize this part of the production system or the supply chain. I need to think about three or four other things that we need to do here." So she never was ... These are ideas that most people have and lose where she built a natural habit to capture them. So then at the end of the day, when she's got her half hour to herself, that's where she would start to use Synthesis to start pressure testing these ideas.

(17:54)
So she'd be like, "Give me all the revenue reports for the East Coast of America in spring when we're flying with these types of conditions around it. What would be potential revenue uplift if we were able to do four flights instead of three flights? Or what if we could turn around the crew in 27 minutes instead of 28?" So literally, she's pressure testing all of these half baked ideas in her mind. And again, half of them would lead to a dead end where she'd be like, "Okay, I can put that one to rest." But literally over 30, 40% of them started to have massive impacts and revenue opportunities for their business. And for a company like an airline where you're on margin thin, that's how you make your money. It's literally in one per 2% margins. You find those little innovations and they have a huge systemic effect across the entire business.

(18:53)
So we just did a podcast with her too as well last week. Highly recommend everyone check it out. But this is really turning these behaviors into bottom line impact, saving millions of dollars for this company, especially at a moment where, again, airline industry is sensitive to price fluctuations in Petroleum. So she's still making progress. And yeah, I'm there actually on Wednesday for they're celebrating a hundred years as an airline and I'm giving a keynote to a couple of thousand people around this. So super exciting. And yeah, Misty is just a star, how she's adopted these things and had a massive success.

Bryon Kroger (19:32):

Love it. And like I said at the top, some of these things seem fairly obvious. And if you're listening, it's like, well, duh. But then I would ask you, how many of you are doing this? As I was going through this book, it was like a bunch of thoughts that I've had but just haven't done. And honestly, it feels overwhelming to start doing even as simple as something as simple as recording myself when I'm marking around talking to people. It's like an easy step, but something I haven't done. So one plug I'll just say, people that have listened to me for a long time, I always advocate for coaching. Ever since I read Trillion Dollar Coach and I was like, "If Eric Schmidt and Steve Jobs need a coach, then I need a coach." It would be one, a book can be your coach. So I do highly, by the way, interviewing out of this book right now, it's so good.

(20:12)
I have it all marked up, but a book can be a really great coach. And then I highly recommend taking some of these prompts and easy steps and working on them with your coach. And if you don't have a coach, you should get one. Barry does one-on-one and group coaching, but really fantastic thing. So what I have pulled up right now that I wanted to ask you about, because it came up several times, and I want to come back to leaders, but in the kind of moving to an artificial organization, as you call it, one of the first steps is just, I love how you framed this, capture work as data. We've talked about doing that as a leader a bunch here and capturing meetings and conversations and ideas, but I think there's often a lot of pushback. And when you talk about Lean Enterprise, which primarily focus about how to organize teams across the enterprise, there's all kinds of data that you can capture and measure, but it's always like, "Oh, but we should only do the stuff that's really important because it's costly to capture it.

(21:06)
It's costly to analyze it. " And sometimes if you're looking at the wrong things, it actually leads to the wrong behaviors. But I think some of that has changed in this new world in a way where I feel like I should be capturing not only all of my meetings, but the whole company's meetings and every commit and all the way down to the lowest level of everything that's going on because of the power of the synthesis here. Is that something you think organizations should start thinking about or is it still a bit dangerous and costly?

Barry O'Reilly (21:36):

Yeah. So I think this, as you say, we have these moments where the fundamentals change, right? If you asked me that five years ago, building all these, you're building a data center just to record every single team meeting, it seems a bit much. But now, not that the cost has gone to zero, but to manage terabytes of data is not as expensive as it was. For individual operators and companies, you give them a 30 buck a month license and then they can actually start processing relatively sophisticated data sets. Or as their day job feels like, five spreadsheets that they use to manage something, two Word docs and a PowerPoint presentation and maybe the corporate strategy, you can load that all in to your workspace and start asking challenging questions. And I think this is one of the behaviors, again, I'll keep underlining. The point of these tools is not to summarize or sometimes I think when people hear synthesis, they're just like, "Oh, tell me what these documents say." That is not the point of these tools.

(22:39)
The point is to keep pressure testing your thinking, is to ask it, what decision needs to be made here? What are the assumptions that have been made? What am I not thinking about? Give me four scenarios about how this plays out, pros, cons, options, cost, returns.

(22:56)
So you're really like, in essence, like game theorying, everything that is in front of you. And I think that is where the real cost has come down. Before, it would take you a long time to do scenario planning. It's costly, you might have to engage many people in different parts of the organization to get the information that you want. Now as a leader, you can get early leading indicators, you can get documents that you're working with day-to-day as the inputs to help you start formulating and pressure testing these ideas. And that is really powerful. And I'll tell you one thing that execs and senior leaders love. It's people who come to them, not to say, "Hey, I need you to think about this and come up with a decision." It's people who say, "I'm recommending we take this path. Let me explain the rationale. Here's what I've looked at.

(23:49)
These are the options I've considered. Option A, pros and cons, B, pros and cons, C, pros and cons. I think we do C, here's why, and here's the impact if we get it wrong." What a dream conversation to have with someone. And these tools allow both sides of that story to be prepared to actually maybe the IC or the individual contributor to do that mental arithmetic, like pressure test their thinking.

(24:16)
And this is another, again, just all these things just keep giving a little bit back. Before for an operator to do that, they might have to build a spreadsheet, find all the data, pull all this administrative work, and then they only get maybe 20% of their work time on creative problem solving. Now we're in a world where, no, no, your admin work is actually getting smaller and your creative problem solving time is getting bigger, which means you actually, rather than worrying about doing more, you have things like time to think, time to actually really consider thoughtfully these high stakes decisions. And that's what people make the big books for. It's like you're paid to make judgment calls in high stake situation under pressure.That's what leadership is. And these tools, and I call that decision velocity, so the ability to make high quality decisions at pace supported with decision advantage, which is an advantage being the information that you're able to source to support that information.

(25:25)
So when you're a high functioning organization, you have velocity and you have advantage because you're making good decisions that you have confidence in because you've great information to support them and it leads to a lower reversal rate in decisions. It means to hire tempo and that keeps companies fast even when they're big. And again, if you ever listen to the Lex Friedman podcast with Jeff Bezos, one of the things he talks a lot about that he's probably most proud is that Amazon has stayed fast with one and a half million employees because they make decisions at high velocity that they're confident in. And that is the magic. And I think, again, most of the book is really talking about, one, how you build your judgment system. So the method you use to make tough calls supported by a judgment infrastructure, which is the platforms, the tools that get you the information you need to make those high stakes decisions.

(26:28)
And I think the companies and the people who adopt that philosophy of human plus machine for better judgment, they're just winning. It's not even debate, right? And again, more research in the book shows that if you're someone, an individual using AI efficiently, you're as productive as a team. And even better, if you're a team using AI, you're three times more productive than the sort of baseline. And that was done by Proctor and Gamble, another Harvard Business Review. So massive indicators about this is the stuff you should be doing.

Bryon Kroger (27:03):

Yeah. I want to get to at least maybe two questions here that we got a lot of questions submitted actually.

Barry O'Reilly (27:10):

Love it. I see the feed here. I love it. Thank you

Bryon Kroger (27:13):

Everyone. There were two things I wanted to footstomp that I had planned to ask you about. One was just the AI slop thing, but I'll just suffice to say throughout the book, you do footstomp that slop is real and it's a problem. People get fired for it, as they should sometimes, and you have to be very careful about it. So you advocate for, I would say, a much more nuanced use of AI. And then the other thing was, we kind of touched around, but I just want to make it very explicit. You have a line in the book where you say that you as the leader have to be the first one to do this change. Transformation isn't something you do to your team. It's something that starts with you. And so that is the huge theme of the book and has been of this conversation.

(27:51)
But going into ... One of the first questions that I liked here was, what does measurable value actually look like for internal process automation in large enterprise or in our case government, and how do you prove ROI?

Barry O'Reilly (28:06):

Yeah. So for most people, again, you've got to start with your leading indicators. So this idea of decision velocity, this is something you can actually start tracking relatively easily and show progress. So how many decisions have we made this week? How long is it taking us to make decisions when we're in meetings? Does it take us four meetings to make a decision or can we actually get it done in one? Do we book an hour and sit in for an hour and not make a decision? Or do we book an hour, bring the information we need, and then make the decision in 20 minutes? So that's some very easy things people can start thinking about for decision velocity. Decision advantage, very simple thing. On a scale of one to 10, do we have the information we need to make this decision with confidence? Most people can score that straight away in a meeting.

(28:54)
If they score three, you're like, right, well, what do we need to fix it? They score eight. You're like, okay, cool. We have confidence here. Let's go. Reversal rates. So when you make decisions, how often are you going back and them going, "That was wrong." Okay? Now this isn't like a testing if you failed or not. Sure, you're going to make decisions that don't turn out as you want, but the more confidence and more information you have to make good decisions, you should be doing less reversals. You should be moving on to the next order effective problem. So these are just some very simple things I get people started with where they're measuring outcomes because you're doing speed, right? We're making decisions more frequently. Our information quality is higher. There's less reversals about how we're making those decisions. Awesome. And then you can do, if you want, your vanity and sort of metrics where you're just counting time.

(29:45)
Well, how long does it take me to do synthesis at the end of the week? How long does it take me to do a board preparation, a quarterly business review, weekly business review? But if you want to get to outcomes again, it's starting out Asking your teams almost like an NPS. How good is it working with me at the moment? What does it feel like to be prepared for meetings with me? Are they good meetings? Do you enjoy them? Can you score them one out of 10? So these are other ways where you can really quantify. Is the work you're doing making it better for people? Because to your AI slot question, every time I meet people, they're like, "Oh, I've got a thousand agents running on this problem." And they're talking about volume, volume of output. And that's exciting, but what's really exciting is volume of output with business outcome as well.

(30:44)
So I think that's where I try to get people to ... I call it productivity flex. So when people just rock up and go, and we saw this in our studio. In our venture studio, founders would show up with a full suite of every document you could imagine. Go to market, customer profiles. They even had data rooms and investment thesis, financials. If you were a VC, you'd be like, "This is amazing." But once you scratch the surface of the documents, you realize that they're just generic. There was no real thought. So people were outsourcing the thinking to me. They were just creating the output, looking great, but the thinking was really shallow. And you need both if you're going to see some real return. And they're all your leading indicators that ultimately roll up to revenue and Epita impact and saving the business money and time.

Bryon Kroger (31:42):

Love it. All right. Well, I think that's a great note to end on. Barry, I want to thank you for joining us today. Folks want to follow you. They should follow you on LinkedIn, check out your website. Yeah, LinkedIn.

Barry O'Reilly (31:54):

Go to theartificialorganizations.com. Let's give it a wave. Thank you so much for reading the book. Yeah, and I just want to give a big shout out to you and your team. It's great to spend time with you. Prodlicity last year is a great conference. Highly recommend everyone checks that out. And yeah, look, it's always ... I'm in DC as well with your team this week. Really looking forward to spending some time with them as well. Yeah, it's always great to spend time with you, and I love the work that you're doing.

Bryon Kroger (32:21):

Thank you. Appreciate it. And Prodacity, by the way, that Barry mentioned is coming up. So August 25th through 27th in Nashville, Tennessee. Hope to see you all there. Thanks again, Barry. I really appreciate you. Everybody go pick up that book.

Barry O'Reilly (32:34):

Thanks very much.

‍