Analyst who covers the EDA software sector, which includes Cadence. And up on stage with me is the management team from part of the management team from Cadence, including John Wall, the CFO, and Richard Gu, to my far left, who heads up investor relations. Guys, I really appreciate you joining us today, and I don't say this to all my management teams, but you're one of my favorite. And so really glad to have you guys here. And so, John, for the purpose of the audience here in the room and online, I was hoping that you could just give us an overview of Cadence, and give us a sense of the breakdown between your different products and exactly it is, you know, what it is that Cadence does. Yeah, sure, absolutely. Just before we start, though, can I have Richard do our disclaimer? Of course. Yeah. Yeah. It keeps us clean- Yes. Yeah. So today's discussion will contain forward-looking statements, including Cadence's outlook in future business and operating results. Due to risks and uncertainties, actual results may differ materially from those projected in or implied in today's discussion. For information on factors that could cause actual results to differ, please refer to our SEC filings, including our most recent Forms 10-K and 10-Q. All forward-looking statements during this meeting are based on estimates and information available as of today, and Cadence disclaims any obligation to update them. With that out of the way, back to you. Great, thanks, Richard. That keeps us clean with all our legal folks. Our legal folks at Cadence are very conservative. They make sure we do this all the time. Thank you, Gary. I'm sure Gary says that about all the people he's interviewing. I know Gary knows this team. We've had a long relationship with Wells Fargo and with Gary, and he understands the space really, really well. For those of you that don't know Cadence, it was formed back in the late 1980s, and basically a company that was created by engineers for engineers as when people realized that you're gonna need other engineers to create tools that engineers need as they move down the process nodes and chase Moore's Law. The biggest and maybe the best way to describe Cadence now is, I mean, we're always customer-focused in solving the biggest customer problems. And what customers have been looking for, for the last five years or so is they want, ideally, one unified platform that takes you from chip design, chip verification, packaging, and board through to electronic system analysis. But and ideally, they want to do all of that concurrently. It traditionally, it's been done in a chronological order, but they want to do this all at the same time so that if they tweak a design, they want to see what the electromagnetic impact of that is at the same time. But before that section, people generally, when they're trying to design an electronic system, they'll choose some IP off the shelf and then focus their efforts on where they want to differentiate when they start their own chip design. But in Cadence's business, we have some IP. We focus on differentiated IP, because the important thing there for us is just to have a seat at the table. It's the least profitable business to Cadence, and it's about 10%, about 10% of the business. But like I say, once customers have selected the IP, then the real work starts in terms of that chip design, verification, packaging, board, and system analysis. On the chip design part, we have generally, there's analog, digital, and mixed-signal design. That's where you have the mix of both. Cadence was born as like the analog EDA company, but we started off in analog Synopsys. Our competitor was a digital version of Cadence. They focused on digital. And over the early kind of decades, both of us converged in each other's space and kind of soaked up a bunch of the other smaller EDA players so that we're down to really two big EDA players, and Siemens plays with Mentor Graphics in some of the higher process nodes. The, so there we have custom IC is our analog piece, and digital is our, our digital business. We, we feel our destiny is always going—was always going to be the largest company in core EDA, so that's why we focus on this particular area. And, and the reason for that is that we started off maybe about 70-80% of the analog market. We're probably higher now. But, and then we always felt it was only a matter of time before we got to 50/50 on digital, and we think we're there, with the exception of maybe one large customer in North America, who's, who's a particularly big spender with, with our competitor. But, but extracting that customer, we're kind of, we're at 50/50 already, I think, in the market with, with everybody else. The... So that's the core piece in terms of EDA. Then you go to packaging and board. In packaging, we have a product called Allegro, which is really, really popular. We think Allegro is probably 80% of the market in packaging. And then that's a useful bridge from chip design into system analysis. On the system analysis side, it's where our customers are basically running all their system analysis. They're checking the electromagnetic dynamics and things like that, and thermal analysis. It's. There's two elements, really. It's finite element analysis, which are physical things, and then there's thermal analysis. 'Cause when you start stacking chips, you create kind of heat around that, and it causes kind of thermal issues, and you need to be able to model those. But, I... So that's the kind of the overall business. I think about 50% of the business is the core EDA piece, the chip design piece. Like I say, 10% is IP. System analysis is probably twelve- Correct. -and growing. And then, of course, you've got verification in the middle of that, too, of chip design and verification. Verification has been really strong for us. When our customers use our chip design tools, what they're trying to do is optimize for power, performance, and area, but then they want to verify all of that. The other thing is that we have emulation and prototyping hardware systems. We have software simulation as well for verification. But for hardware, we have some extremely popular products, particularly the emulation system. The emulation system at Cadence is called Palladium, and it's Cadence on Cadence. So it's a Cadence custom chip in a hardware system that's designed to allow you to bring up your chip so that software developers can design the apps to put on the chip before there's a physical version of the chip. And that's really disrupted the order with which people have designed. In the past, you would do the chip, software guys would create the apps for that chip, and it's a long process. But we have some customers, they're on, like, if you forgive the pun, they're like on an annual cadence of product release. And to do that, you can't do that without bringing up a virtual version of the chip and letting your software guys design the apps to go on that. The reason I say it's disruptive is that we think some of the popularity for those hardware systems is coming from the software engineers. Because the software engineers are able to collaborate more with the chip design teams and influence the chip design. Because the beauty of the emulation system is that when you bring up the chip, it doesn't need to be finished, it doesn't need to be final and locked in. The software guys can influence the chip design before it's hardened, if you like. So that's been a really popular piece for us. And I think if you look at the overarching, I suppose, if I were to simplify this, Cadence is really a computational software company. We do a little bit of hardware, but, we do a little bit of IP, but it's a computational software company. And when you apply computational software to silicon, that's EDA, that's the front part of the design process. When you apply computational software to, like, a car or a building, that's system analysis or FEA, you know, so that's, that's the system analysis side of things. And then when you apply, when you apply computational software to data, that's overarching the entire process, that's AI. But, and, and, I guess that's probably the best way to describe this. Thank you for that comprehensive overview, John. I wanted to talk about the growth that you've been able to put in, solid growth, year in and year out. Mm-hmm. Per your most recent guidance, you're expected to grow at a mid-teens% this year, which is consistent with, you know, your CAGR over the last few years. And I know you're not gonna give us any sort of a preview into next year, but as we think about next year- Mm-hmm. You know, how do you think about the different puts and takes? I know you've had a heavier mix of revenue coming from upfront sources in 2023. Maybe that's not quite as repeatable for next year, but that repeatable, recurring portion of your revenue has been growing at a 13% rate, and then also we have to consider some recent acquisitions. So how do you put all those pieces together? No, fair enough. Gary always asks me questions to help him model. But, the... So we're very transparent. I'd encourage you all to go to our investor relations website, Richard does a great job there. We're very transparent. You'll see all kinds of interactive financials going back to 2012 because that, it's— we're farmers, not hunters. It's, you know, we're planting now, we're generating R&D now for future benefit, for revenue in the, in the future. The, often the investment timeline is you're investing a whole bunch of effort into R&D now, and it may not pay off for revenue for two to three years. The, in terms of the model, we have a mix of upfront and ratable business. The software is mainly ratable. I mean, that core EDA side, that's all ratable. We get revenue on a daily basis from our customers, and that's probably 70-75% of the revenue. Then there's other things where there's kind of bonus elements in contracts, and there's ones where there's consumption-based, where they draw down over time, and it's recurring in nature. There's royalty on the IP side, that's kind of recurring. All in all, our recurring has generally been kind of 85%-90% of revenue over the last kind of seven years since I became CFO in 2017. But over that period of time, it's been, like, 85%-90%. But which means 10-15% is upfront. Now, the 10-15% upfront can be cyclical because that... You get upfront revenue on the hardware piece, you get upfront revenue on IP, and they're the main components of upfront. You get a little bit on software from time to time on what we call license compliance, if someone's pirating the software, we have call home technology in the software, so we know who's using the software. And then occasionally, the triggering event for a license compliance catch-up is that customer might wanna purchase hardware to do the verification side. We'll know it's the same IP addresses, and but. And then we'll say, "Look, well, we can't sell you hardware. It's our policy not to sell you the hardware unless you're compliant on the software side." And then we catch them up on the software, do a new three-year deal with them or something like that. But, most of our customers on the software side do three-year baseline contracts, and then over the course of 12 quarters, they'll come back between four and seven times to purchase kind of add-on technology. When they purchase an add-on. And they'll purchase add-ons either because new technology we've released that they didn't have access to in the underlying agreements, in the baseline agreements, or, you know, headcount growth, that they've hired more engineers than they were planning, than they had planned in the original, baseline contract. And, most of the time, they have visibility into what they need for the first year, less visibility second year, less visibility third year. So the baseline contract is, the first three-year contract. The annual value of that is probably bigger than the total contract divided by three. If that makes sense, because they'll have maybe it's 100%. What they commit to is 100%, 80%, and maybe 60% in year 3, so it kind of averages 80% of their requirements, and then they come back and purchase add-ons, which adds the other 20% or so. And when we sell those add-ons, we always try to co-terminate. I actually say it that way because I'm not aware of ever selling an add-on where we didn't co-terminate, but we sell so many, it's possible that one exists. But generally, everybody does an add-on that co-terminates then with the baseline contract, and by the time you get to the baseline contract renewal, you kind of start the dance all over again. Everything gets rolled into a new baseline contract. We've drifted kind of higher on upfront revenue, partly because of the success of this hardware system. I mean, it's been so successful. Our previous hardware iterations, they've come in— It's been like the... I think in my time, the last, so between Palladium XP2, or sorry, Z2 and Z1, I think it was six years. But the Palladium version before that was five and a half years, I think. They're kind of long cycles. You know, I always complain to the engineers, "Why so long? How come it takes, like, six years?" And they say it's the paradox of long cycles, that by the time you get to year three or four and you're ready to launch something, someone will come out of the woodwork and say, "If you can wait four more months, I'll have it for two... I'll have it ready for, I'll have something for two nanometer." And then you're faced with a choice of, do I wait four months for that, knowing that if I don't wait, it could be another four or five years? But so it tends to take a bit longer. But they've been really successful. We launched the latest ones, oh, was it March 2021? I think it was March 2021. But so we're coming up on three years. The demand has just, like, outstripped our ability to supply. We had to get more production lines back last January just to keep up. Our lead times are typically around about 8 weeks, and at the end of last year, we had about 28-week lead time with all the orders that we had. It's just really, really, really popular. It's, I think it's just, it's such a big investment for our customers to, when they're doing design work, not to verify it, 'cause nobody wants to be right first time. They want their silicon right first time. If you don't invest in verification and the systems that come with that, you run a much higher risk of not having your silicon right when it comes back from the foundry. But on your question in terms of modeling, though, generally, the recurring revenue is the farming piece, right? That's where you have a much more stable kind of revenue recognition. It's averaged 13% growth the last three years. But then I think we're on track for 13% growth this year, so it's pretty consistent. You know, and that's up from double digits. We generally aim to do double digits. I mean, that's our model. And you know us, we always like to underpromise or overdeliver, right? But our model is basically every year, we aim to do double-digit revenue growth and 50% incremental margin, 'cause it's the EDA business is tremendously profitable. It's very sticky. Our customers can't operate without us. And when it comes to renewals, it's like it's practically a 100% renewal rate. The only people that don't renew have either been acquired, in which case the renewal has been done by someone else, or they've expired. But there's very, very little. I think we might have had one or two startups that were desperate for cash that went and designed us out because they just wanted cheaper tools or something like that. But they don't last very long. If they don't expire, if they haven't expired by the time they haven't renewed, they'll expire shortly after. So we're very, very sticky customer base on the EDA side. And then, like I said, because all these customers want, they want this unified platform, they wanna be able to do everything concurrently, I think that's put us in a position where our strategy has been to expand across that platform from chip design through to system analysis. And it makes everything more sticky, because the more you adopt from Cadence and the more you have the full flow on everything with Cadence, the better your AI results or your analysis of data, 'cause you're using the same tools for everything. So that's been really helpful. On the upfront side, the IP, that's like services, it's like milestone contract. Most IP is customized to a certain extent. I mean, you'll buy IP off the shelf, but there's always some element of customization. And depending on how much customization, you either have... Revenue tends to trigger when you hand over the IP or when you hit certain milestones, like a, so that can be, that's upfront. We treat that as upfront. We take, we include the royalty piece as recurring because it's, it's quite predictable. On the hardware side, because you hand over a system, you're, I mean, you, you've delivered most of the value as soon as the system's installed and the customer's using it. There's a piece of hardware that we've assigned to maintenance that gets taken over time, like software, but that has grown from the kind of the low double digits to about 15. It could be 16. This would be the first time in my time, where we're outside of the 85, we're under 85% for recurring revenue. But, and I think, like, your focus is really on, so what does this mean for next year, I presume, right? Yeah. Like, when we think about that, recurring revenue is, I mean, we don't guide next year until we complete Q4, 'cause Q4 is always a huge bookings quarter for us. Now, that's probably consistent over a number of years. Now, this year was a bit odd in that two-thirds of renewals, like the software renewal base that was coming up for renewal in. So like if you look at all of our software contracts that were expiring in 2023, I mean, we're spoiled for predictability because you know when those customers' licenses expire, they have to renew. They have to renew. When we get hedge fund people coming and telling us sometimes, "You could 5x the price on this, and your customers would have to pay it," that is absolutely true. Because if your customer's in the middle of, of, like, multiple project designs, there's just no way by the time your contract comes around for renewal, that they can't renew with you. Now, the trouble is, though, that we, we adopt the farming, the kind of long-term strategy, that, we partner with our customers. We would never do that to them, and that's why they're comfortable partnering with us. But, but I-- But I think the trade-off for that is we do want a predictable kind of rate of return, and we do want to get some return on the investment that we make. 'Cause we, we spend about 30% of our revenue on, R&D every year, and that 30% is sunk upfront. That, about two-thirds of that doesn't contribute anything to revenue in the year that it's spent. But, the... So although we have high margins, that if we had to match the expense timing with the revenue timing, we'd probably have higher margins again. But generally, the way we start each year is we aim for double-digit revenue growth, and then what we like to do is, it scales really, really well. So, we want to try and drive more than 50 cents of every dollar of revenue growth to operating income, which would mean that double-digit revenue growth turns into kind of low to mid-teen operating income growth. And then on top of that, we use about 50% of our free cash flow, 'cause we generate consistent free cash flow from our customers. But, we use about 50% of the free cash flow to repurchase shares, which has the share count declining gradually over time, which means the kind of low- to mid-teen operating income generally turns into high-teen EPS growth. We've averaged from 2017 periods to. If I just take the midpoint of guidance, I think we've averaged about 22% EPS growth, but that was helped partly by tax benefits. It's probably high-teen is what we've done if you had a consistent tax rate. But taxes are lower now than they were back in 2017. Okay, let me stop you there. Sorry. Sorry. Okay. So, if I wanna double-click on something you said in there, and that is- Yeah. It sounds like this year's fourth quarter has a disproportionately high amount of license renewals. How is that going? Oh, it's so busy. So busy. I think, since we started Q4, I don't think there's been a day that I haven't been talking to the sales force on something. It's, it's tricky out there, though. I mean, in comparison to other Q4s, Q4 is always busy. I think people are a bit cautious. They always. I think they see that their spend with us as an opportunity to save. 'Cause the more you spend with us, the more you potentially save because you're, if you can leverage the tools more, yeah, and particularly with the AI capabilities that are there, maybe you can throttle your headcount growth in your model. That when you're doing some of your long-term planning. That's been a challenge, though, from a pricing perspective that, I mean, Anirudh is super proud, and he should be. The R&D teams have created such tremendous AI tools. I mean, he gave me an example of, there was one customer who was getting 75% benefit. While he's rejoicing, and the R&D guys are rejoicing with that, it gives me shivers 'cause I'm thinking, "We didn't price that right if it's 75% benefit." And it's like, "It's okay. We'll get them next time." But... And we'll make sure we factor that into pricing for those tools that, with all the customers going forward, 'cause we're all kind of learning through that. But Q4 is always a super busy quarter. Like I said, this year was a bit unusual. I think it was the most back-end loaded half, first half versus second half, than that I've seen in a long time. It was about one-third of our renewals came up in the first half, two-thirds of the. So like I say, if you look at your software base and which contracts are expiring, you look at the annual value of those, about a third of the annual value that was expiring in the year was expiring in the first half, two-thirds in the second half, which meant you're gonna have a much bigger second half bookings. Next year is about 40, 60, Gary. 40 first half, 60 second half, right now. But it's hard to kind of tell what it's going to be because it's such... There's still a lot to do between now and the end of December. It's yeah, there's huge demand. The two things I wanna point you to, though, is that I think on the earnings call, you all wanted us to talk about our AI tools and how much growth we were getting from AI tools. And we did. We gave you a metric. We said, "Look, it's 3x." Basically, the revenue we're generating. We have five AI apps that we're selling, and they're generating about 3x the bookings and revenue value this year than they did last year. That now that's all ratable revenue 'cause it's all on the software side. What I wanna point you to, though, is that recurring revenue is still 13%, right? So that's part of the recurring revenue. And what I'm seeing on a bunch of contracts is that customers are adopting the AI tools, but if they had 100 licenses of this, you know, ex- product X before, they're trying to make do with 85 or 90 in the baseline renewal to make room to buy the AI tools. And we saw that with... When we proliferated digital tools, 'cause there was a time when we were probably, you know, 20%, 25% of the digital market. We're up to 50% now, we think. But back then, when we launched new tools that were very popular with customers, they did it the same way, and it proved to be a fairly false economy. But, in that they shave back their baseline configuration, then discover within six months that they just can't manage without the extra licenses, and they just do more add-ons later. But, so I think the recurring revenue piece is pretty consistent. I mean, that will go in line with the economy to a certain degree as well. I mean, we always say that we're very resilient, but we're not immune to recession. I mean, if there's a recession and a whole bunch of people are laid off, that will hurt us. But, but not so much as most other companies. On the upfront side, though, what tends to happen, like, I mean, I know when I'm doing budgeting and everything, I'll cut back on CapEx and things like that. That would, that could hurt your hardware. But, and we're up against tough comps for next year. So the upfront piece, I mean, last year was very cautious 'cause upfront revenue grew, like, 50% almost, I think, from 2021 to 2022 on the, because of the popularity of those hardware systems. And I thought, "Oh, really, really tough comps." And I think I was, I was trying to get you all to calm down this time last year because I was worried we had tough comps, and we've beaten that again this year. But, and it's, I think upfront is probably up 20% again, isn't it? But, again, I would just caution, it's tough comps for next year. You know, you don't—I mean, again, if there's, if there's any slowdown in the economy, people might slow down their, their purchasing. Okay. Can I talk a little bit about pricing, just for a second? Yeah. Just in terms of how people approach things. Yeah. 'Cause most of the stuff I'm going through right now in Q4 is I'm dealing with the sales force. 'Cause we do extensive pricing analysis. We look at what's the average selling price that we're getting from all our customers for each product at different volume levels. But and we compare what we're getting on an individual contract against that, and we call it a deal quality metric. So let's say I'm looking at the average selling price for what's in your configuration, and you're looking for $10 million worth of software annually. But but you're coming off a contract where you were paying $8 million, and you just have the budget. You're telling us you have the budget for $8.5 million. Nobody capitulates and gives us $10 million. But what happens is that we shave the configuration down to try and match their wallet. But... And you might end up, if they have the budget for $8.5, you might end up getting them to $8.7, $8.8. They might be stuck at $8.5, but they'll end up with a smaller configuration, and then that creates the add-on opportunities later. And I think that's playing in somewhat into... You're seeing some AI revenue show up, but it's not really raising the overall top-line number yet. I think that will come, though, with add-ons. I just wanted to- Okay. Make that point. I appreciate that. Sure. And that's probably a good pivot point to talk about what these five different AI tools from Cadence, you know, bring to customers from an efficiency standpoint, right? And so the way I view the opportunity, there's about $90 billion a year spent on chip design R&D activity. And if you just simply divide that into the size of the EDA market and the semiconductor IP market, you can come to the conclusion that you're grabbing only a high teens% of the chip design R&D wallet share. Yeah. And so if you can bring more efficiency to the chip design process, you can capture a greater percentage of that wallet share. Maybe you can just give us a sense of how, you know, that high level shift alters the core growth rate of the EDA market and your growth rate. But that's a great question, Gary. That... So let me start it, but I wanna bring Richard in a little bit, and I'll let him talk about... Would you talk about the AI tools- Sure. Maybe that in a minute. But overall, most of our customers, if you look on the EDA side, the tool spend is only about 10% of their total spend on R&D. One of the reasons we're resilient in a recession is because our revenue line is our customer's R&D line. You know, in a recession environment, the last thing I'm going near is cutting R&D, because R&D is for the future. But, you know, we'll cut back on G&A, we'll cut back on some sales and marketing efforts or... But from an R&D perspective, we might even double down on R&D, but to design our way out of that recession, the... So we're quite resilient that way. But when you look at our customers' R&D spend, they spend 90% on people and 10% on tools, particularly on the semi side. You know, we've talked to some customers that are adopting AI tools, and the whole pitch about, you know, the more you spend, the more you save, is based around, let's say, for every $10 million a year you're spending on R&D, right now, you're spending $9 million on people, $1 million on tools. And without adopting any different approach or different methods, at some point you'll double, and then when you double, you're gonna be spending $18 million on people, $2 million on tools, if on the assumption you can find the people. 'Cause that engineering talent is really hard to come by. But what we explain to them on the AI side is that if you adopt more of our, our AI tools, you might need less people. And what you could achieve for $20 million, you might be able to do for $16 million if you're spending $4 million of that on tools. But so the logic there is that we don't necessarily want them to cut back on people, we just we wanna try and capture more of the, a kind of an outsized portion of the increase in their R&D spend, because I think that will be helpful for them. I think they will, they will save more by, by adopting more tools. And what we should see over time is the, the 90/10 split of their budget between people and tools will start to gradually work towards 75/25, and 50/50. I mean, if you extrapolate long enough, there's just not enough growth in the human population to keep up with the growth and complexity of design. You're just gonna have to need more and more AI to... The tools are gonna have to do more of the heavy lifting, and, and I think we're, we're in the right spot for that. But we have like, we have five, five AI apps. So do you wanna talk about some of those? Sure, sure. I'll just touch on that quickly. So five AI products cutting across the entire EDA and system design analysis, kind of, you know, life cycle. And these AI tools bring dramatic, tremendous benefit in threefold. First off, it helps the designers to design a better chip, okay, from a power, performance, and area standpoint. I'll give you an example. We have a chip design project with Renesas on one of the automotive chips. It has 17 variables. For the longest history of EDA, it's all a single-run process. You do one round, you split the different blocks amongst a lot of different engineers, and they'll use intuition to keep doing iteration and make it better. But with 17 variables, it'll involve almost four million kind of runs, you know, and every run takes one to two days. So humanly, it's impossible to explore the entire design space. With the Cerebrus, one of our AI tools, that could be shrink down to weeks and, you know, 200 runs, we get the much better results. So the benefit of PPA is to the tune of anywhere from 5%-20%, depending on where your starting point is or how good your design team is. So the second benefit for the AI tools is you have much better control for the destiny, right? And, you know, you, you're not dependent on the other, you know, semiconductor companies to help you do that. And dramatically, importantly, is, as John pointed out, the from a productivity standpoint, it helps companies and design companies and EDA company and chip companies to have much more design activities with much less engineering resources. So these are really at the starting point of, you know, a big AI revolution for us. Thanks, Richard. Actually, can I add one more point? Sure. Sorry. So the in that whole model of double-digit revenue growth and 50% incremental margin, you know, people often ask, "Yeah, 50% incremental margin, how long can you keep that up for?" 'Cause we've done that for, like, seven years in a row now, and I think it's averaged 55, isn't it? But we start generally with 50. We like to go out with, go low and then try and overachieve with that. We're really holding it down to 50 in that 50-55% range, because that's our budget for R&D. We're trying to do more R&D 'cause revenue growth tends to go in line with new product releases, and we want to release more and more new products over time. But, it's also giving us some funding for plugging some gaps on the M&A side. And you might have noticed that we bought Intrinsix, and we bought a piece of the Rambus business. And those are kind of long-term plays. We changed the IP leader at Cadence at the start of the year, and Anirudh spent a bit of time with him, wanted to know, you know, "What did you want?" And we went and bought those. I don't think they provide a huge amount of revenue in the short term because the way we did the—I think we got those cheap 'cause we allowed them to sell out into the future, take it for a low price, and then we'll eventually get the renewals on those when they come around. But there's that. We've got that. We're also investing in the system analysis space. EDA is pretty, I mean, it's down to two and a half players, really. But we did some IP because we have a new IP leader, and they've got to digest that. I would say in terms of, from an R&D standpoint, a lot of effort's going into system analysis, 'cause I think that's where there's system analysis and verification, because I think that's where there we have kind of an out above average opportunity for growth. Okay. Well, I think we're actually up against our timeline. Oh. I wish we had more time- Yeah. But we don't. So, John and Richard, I really appreciate you joining us up here on stage. I appreciate the people in the audience who joined, and as well, people online. So again, thank you, guys. Excellent. Thanks, Gary, to you. Thank you.