I'm Vivek Arya. I cover semiconductor, semi cap equipment at BofA Securities. Really delighted to have the team from Cadence join us this morning. John Wall, CFO, and Richard Gu, VP of Investor Relations. I'll go through a list of my, but actually I will pass it off to Richard to read the disclaimer first, but then I'll have some of my questions. If you have any question at any time during the Q&A, please feel free to raise your hand. There's a mic that we can hand to you so people on the webcast can listen to your question also. But with that, warm welcome, John and Richard.
Hey, thanks, Vivek. Thanks for having us.
Richard, in the-
Yeah, I'll quickly. Just today's meeting, today's discussion will contain forward-looking statements, and Cadence will disclaim any obligation to update that. Yeah. I was just telling people that there's some seats here if you want.
Excellent.
Thank you.
Thank you, Richard.
Yeah.
Appreciate it. So maybe, John, let's start at the top. Over the last, you know, decade or so, we have seen the semiconductor industry, you know, essentially grow at this 6%-8% kind of pace. But during that time frame, we have seen your electronic design automation, EDA, industry consistently accelerate, you know, from 7%-8% towards double-digit, and over the last few years, mid-teens. So maybe walk us through what helped that acceleration, and then more importantly, are these kind of growth rates sustainable, right? What are the key drivers of that?
Yeah, look, I think the trends has been pretty consistent for the last kind of couple of decades. Essentially, when you're doing chip design, the companies that are doing chip design, their R&D budget is you could bifurcate it into their spend on the tools that they use for the design. And I think over time, tools are doing more and more of the heavy lifting. I mean, there's just... But you can see the pace in increase in chips, and clearly, population growth is not keeping up with that. So you can't do it manually. More and more, chip design has become automated.
It's like 99% auto- you, you can't do it physically and I think if you look at our share of, like, if you take the semi customers, if you look at our share of their R&D budgets, it's probably right now maybe 80% on people and only 12% of the budget on tools. But with AI and everything, I think AI can do more heavy lifting for customers. And we've seen that. I mean, that's... Like, if I go back, take your trends, like a decade ago, maybe it was 500 engineers taking 5 years, where engineers can do it in half a year or 6 months, maybe even a year.
That's, that's huge productivity improvement that we're providing through tools, and I think we're extracting more value for that, and I think it's the value proposition. But, and there really isn't huge alternatives. But, so I think the productivity gains are there. It's easy to sell the value to the semis consistently. And, and I do think that 88/12 will naturally have to become a 75/25 and maybe even 50/50 over time, but, because I expect the growth and complexity to continue.
What are you seeing in terms of design starts? You know, what are you seeing in terms of computing complexity? You know, going up, data's telling you right now about the next 2-5 years.
Oh, well, I firmly believe that history will record this period in our time as, like, the design engineers that use our renaissance artists of their time. We pretty much just provide the paintbrushes, right? But our customers will paint masterpieces. Some of them are
Amazing.
Well, they do. I mean, I'm always careful with our group at Cadence that we have to always remember we're the paintbrush. But, you know, it's like, it's great to see Jensen in the spotlight and, and what this- they, it's true, they can't do what they, they do without our technology, though. So there is a dependence on that. But I, I do think, I mean, Jensen probably painted a masterpiece of the... So but I do think we provide tremendous value, and, and we cover off on, in terms of trends, we cover off on, like we're, we're involved in everything. There's, like to tell everybody that, you know, that a lot of the technology just wouldn't exist without... There's always some element of Cadence design in any technology product. Yeah.
Describe the different eras and the masterpieces. So every era has a lot of skeptics also. So let me, you know, give you a skeptical point of view-
Yeah
... which is, the EDA industry definitely benefits from AI, but we've seen a lot of those benefits because a number of the product, whether it was Hopper or Blackwell or the product at AMD or Broadcom, you know, the design of these products started several years ago.
Mm-hmm.
Right? Already seen that big first phase of product design and growth could, you know, mature for some time before accelerating as these, you know, product and the monetization. But how do you look at just the semiconductor industry is developing AI versus when you see the benefits of this come through for Cadence?
Oh, well, we'll see, we'll see multiple benefits in terms of design phases in the industry. Do you want to talk through that one, just the-
Sure
... infrastructure being the first piece?
Sure.
Yeah.
Overall, I think to your question, Vivek, we definitely foresee that it's a big wave one is always the infrastructure kind of build-out. You know, right now you're seeing all kinds of companies try to design their own custom silicon, right? AI chips. I think you heard about like, like, NVIDIA and AMD, they're all coming to be a one-year kind of cadence already. So I think the proliferation of design activity is not only their own AI chip design, but it's also semi companies doing the designs and all kinds of various types of chips designs. So I think overall, if you look at the abilities companies on those, so we're a beneficiary.
The second wave is obviously we're applying AI to our own product set, right? So we have five different AI products, riding on one common big data platform, large language model, to really help with the sort of like spec-to-RTL conversion, which is a great use case.
... and the third way, longer term, will be new vertical molecular bioscience kind of simulation. So yeah, we definitely see this as a big long-term tailwind for our industry.
Yeah, there's new applications all the time. But when Cadence does, I know we sell some hardware and we computational software, engineering software, but and when you look at chip design, like 99% of that's automated already. When you go to system analysis, the silicon is EDA. When you apply computational software to things like cars or phones or buildings, that's system analysis. And then when you apply it to data, it's AI. But and when you look at applying, you know, Cadence capability and simulation capability in, like, the medical space, that's probably only 1% automated. But so I think there's to grow for many decades, I would say. But and I think it's just a natural progression. I mean, we've all seen the progression of this.
Like, you go back a day, smartphones, and now we've seen cars become smart cars, buildings are becoming smart buildings, and that's the kind of transition. What our customers really are looking for. The biggest problems that they're trying to solve is they want to have one unified platform, verification, packaging and board, and system analysis, kind of all at once. So that if you're changing something in place and route, that you can see what it does to your electromagnetic dynamic time. And I do think Cadence is probably the best position to provide that platform.
Got it.
Yeah.
Well, I'm sure, discuss more about AI. The one question, John, that we always grapple with from the outside is-
Okay
... Cadence has the double digit. Now, you know, double digit is a very, very wide spectrum.
Yeah.
So as CFO, what informs you whether it's gonna be 10% or 15%, or 20%, like, for 3, 4, 5 years? What are the leading indicators you're—what is on your dashboard to say-
Right
... where you will be in that growth curve?
That's a great question. Yeah, so, I mean, we say double digits, we mean 10%, not 99%. But so when we say double digits, we're really. I always find that we try to take pressure off the team. You know, I mean, if you listen to us, if you follow us for any length of time, you'll find we're very. Because the opportunity for Cadence is long-term. We want people focused on long-term and designing the best technology and solving the biggest problems for humanity, essentially. I mean, that's, I mean, when people inside, the core tools, you're using them to optimize for power, performance, and area. You know, we're gonna need Cadence tools more and more to optimize for power. Otherwise, with AI in backyard to run all these things.
But, so when we're kind of looking at growth rates, typically what I tell the team is, I mean, I'd love all product lines. I know it's impossible, but if I can't get the growth, I want more profitability. So if it's a more mature product, then you want more profitability, and then I take the profitability, and I'll give it to the opportunities for growth. And what's important to me is how it all fits together. The model is we're trying to aim for double-digit revenue growth, right? But with increased incremental margin, it's hugely important to me in terms of the model. But we started seven years ago when it was like mid-20s.
But we've been delivering every $1 of revenue growth since, was it, 2016—every $1 of revenue growth since 2016. More than $0.50 of that revenue growth has dropped through to the bottom line. And as a result, of course, operating leverage has increased from [2] to 42 last year. So with double-digit revenue growth and improving operating leverage, double-digit revenue growth can give you, you know, kind of mid-teens operating income. And by using our free cash flow, 'cause we spin off a lot of free cash flow, so we use half of our free cash flow to buy back stock and reduce the share count over time, and that can turn that into growth or even in a low 20% range.
If I look at our average over the last seven years, it's been 23%-24% EPS growth. And that's the way the model works. Now, like I say, some of them, they're guidance tools into interactive tools and kind of multi-license user tools. But. So for example, Virtuoso is a great franchise. Virtuoso license needs a driver, so if you're, if you're a 100-person analog engineer design house, that we're probably selling you 100 licenses of Virtuoso, and growth there is gonna come from price increases be contained until you hire 10 more engineers. On the simulation side, one engineer could use 100 licenses, and if one engineer could use 100 licenses for simulation, one engineer could use 1,000 licenses to be able to use, get them access to compute power to do that.
So growth on the growth on simulation technology is hugely profitable, hugely profitable, 'cause revenue can go nonlinear in comparison to your expense base because one engineer can use so many licenses. So what we tend to find is, over time, price per unit, but the volume more than makes up for it. And then from a forecasting perspective, or actually the AI tools, where those are really helpful, you take like Cerebrus, which is probably the more advanced three years ago. But Cerebrus allows a digital design engineer who previously, one digital design engineer used one license of Cerebrus, now uses licenses of Cerebrus. So it's converting what was previously an interactive tool into a multi-license tool.
When we give metrics about our AI tools are now, there's three times the amount of revenue this year from the five year. That's not including the pull-through of the extra Cerebrus licenses. That's just the sale of Cerebrus. But, so, so when it comes to forecasting, where business is recurring, that's, I mean, even this year, what is it? We're expecting about 82.5% at the midpoint of our, of our revenue to be recurring. It's from that huge, substantial base of customers that you know us. It's coming out of backlog. You know it's in there. It's very easy to forecast. The stuff that's more difficult to forecast is the upfront revenue, 'cause it's ba- like our hardware is a pipeline business. You really only have visibility in the pipeline, maybe two quarters out.
For IP, you have more visibility. That's like IP, we're expecting twin milestones, where if we're to execute properly, it will naturally trigger the revenue from bookings that are already in backlog. And it's kinda easy, but what's there, and as long as we don't have execution issues, it'll deliver that much revenue. And generally, our style is we try to de-risk anything we see. So last year we saw Oppo, one of our customers in China, just decided to cancel a design project. So when the renewal came around for that, we went from selling 3,000 licenses to zero. And now, what tends to happen is that will come back to us.
It'll come, 'cause those 3,000 engineers will end up somewhere else, and whenever they end up somewhere else, those customers that they go to will have to buy licenses for them. So that eventually comes back. But that's, that happening last year, that's why we were guiding that, "Hey, we expect China to dip this year," because of that phenomenon. We know it'll come back, but I'm always conservative about the timing of when it comes back in the long term.
One of the topic that I wanted to touch on is your competitor has announced a fairly large acquisition, right?
Yeah.
And kinda conceptually understand silicon and systems or electrical and mechanical, right? These designs are coming together. How does that impact Cadence's growth opportunity? Does the fact companies getting together, does that foreclose your growth in any way? Does that keep you out of, you know, markets? And then how does Cadence respond? Like, will you have to consider large M&A also, or medium M&A?
Let me take the last bit first, 'cause the answer to that is no. We won't have to consider a large M&A. So what we typically do is talking M&A. Cadence, they're innovators, but the 11,000 people, maybe 11,500 people right now, but over 10,000 of those are engineers. But it's always been an R&D innovation machine.
They're creators.
Leaders. Imitators tend to follow. But what I see in terms of what our competitors are doing is I think they've seen the value of what we're doing. This is typically what happens when someone wants to come in and do the same thing. It's very hard for them to do the same thing, though. But what we've built with our own organic innovation, plus I think in terms of talking M&A, including BETA CAE, which is the recent one that we announced, and that was $1.24 billion. I think we've— That's probably doubled our M&A spend. But we have a— we feel we have a complete solution there. Synopsys has had to pay, what was it? $35 billion? $35 billion-
Hundred.
Yeah, but, so it's, it's a big expense on their part to do that, and we just—I, I do think they want to look more like us. But Cadence are, are innovators. They tend to... I mean, and like I say, we're, we're leading. But, vision, Anirudh's vision with Intelligent System Design strategy was this. He knew, you know, that core business is really important and, and core design, chip design is, is largely automated. But, system analysis, it's 20% automated. The medical field is probably 1% automated. We're heading down that path. We did OpenEye. I think we're, even with Synopsys acquiring Ansys, we're still some digital biology companies to, to keep up with us, and maybe they'll see that in a few years' time. But, but we don't have to do big M&A.
I think, we prefer to make-
You think equivalent to that combination? Is it, is it different?
I think it's better.
Both benefit.
I think it's better 'cause, it's kinda like—I mean, it's old technology versus new technology, for a start. But, I mean, products for electromagnetic solver. That was our first kinda foray into system analysis, was Anirudh wanted to make his own electromagnetic solver. Using our simulation capability, he created Clarity. The capability of simulation tools is based on how powerful your matrix multiplier is. Matrix multiplier is the number of variables it can handle. But, and it's by 50 million variables, which is impressive, and it was the leading product at the time. But, our product handles 50 billion by 50 billion. But, and it's so far ahead. Now, unfortunately, the market didn't need anything like... But you get to a point with some complex designs that you have to break up the design to use HFSS.
You don't have to break up the design for, for Cadence, and it's brute force. So the market's kinda coming to us capability. The other thing is, when you have that strength of simulation capability, you're able to simulate moving targets. And that's why we thought, well, molecules are moving targets. That's why we thought entering in memory was a good science project for us, and we bought OpenEye to, to test that out, and that definitely has legs. So I do think when you compare, like, Netflix and Synopsys just bought Blockbuster, it's like, great. I mean, if you, if you're, if you're looking at the capability and the potential through the rear view mirror-
DVD or the...
Well, I just think that, like, our stuff is new, right?
Right.
That, it's new, it's new innovation, and that's typically what Cadence is all about.
Yes.
We're committed to making versus buying.
If I look at the next, let's say, five years, right?
Yeah.
What scenarios would make your growth diverge from your...? Not worry too much about, like, they're both, you know, good companies in a good space.
Yeah.
Right? Because one has a different mix of IP versus EDA, and now, right, this inorganically organic focus, but a different mix of IP.
Yeah.
One has more digital than analog. So how are investors supposed to sort which company will do better over the next, you know, five years? How does that landscape shake out?
No, perfect. But you can't, you can't design this new technology. You can't design chips without one or both of us, and typically it's both of us. I think, though, that there's been a. Our advantage in making and being early is that we've only had to spend $2-$2.5 billion putting the pieces together inorganic, to get the Cadence machine operating and being able to solve the customers' problems. But when you're paying as much as $35 billion, I think that will suck some dollars away from R&D and into. So I would expect that this is an opportunity for us in the short term to take advantage of that. I do think that we've been more profitable.
There's a lot of business in some—I mean, in some areas of IP, for example. There's a lot of companies are happy to give you business, just to take the, take some design. And it's like, we've avoided what we call the, you know, selling $20 bills for $15. But, you can, you can print any revenue growth you want, but if you're prepared to do loss-making business. But, so we're, we're very thoughtful and data-driven in terms of how we price our business. And that, and that's why we say... That's why we're always cautious about double-digit growth. We're not. What we want is profitable and sustainable revenue growth, and ideally, I'd like to see that EPS growing 20%+ every year.
Got it. Are customers willing to pay extra for AI? You know-
Yeah
... that and enabling, as you mentioned, you know, greater productivity. Are customers willing to pay incrementally for that, or you think they're still in a trial stage of-
No, they're definitely-
I think it's like 10%.
No, you-
You can always ask-
Yeah
... what is the AI incremental benefit, right? From a-
Yeah, that's-
-value and pricing-
Yeah
perspective, how much is it roughly?
That's harder to determine. I mean, we've announced, like, a specific about... We're not reclassifying revenue when we give you metrics about the five AI tools are now three times the revenue it was, and three times the bookings it was last year.
Of the business?
But it's not $100 million yet.
Okay.
But, from those. But those will not be the only AI tools. I mean, there'll be more AI copilots and everything that will come out over time. I mean, that's, I, I think that's just an inevitable. Customers are willing to, definitely willing to pay for it, and the more they, the more value they see from it, the more they'll pay. The, but it's a process in terms of extracting that value. We transformation. So you remember that, right?
Right.
So Anirudh joined us about 10 years ago. We were way behind Synopsys in digital. And Anirudh made the brave choice to scrap a whole bunch of our digital tools and redo some blank page, kinda using all the latest in AI and machine learning techniques. And a lot of our simulation capability came out of that. But this 50 billion variables by 50 billion variable, more than a decade's experience of doing that transformation, Synopsys never really had to do that.
Right.
But, so what we found when we did that digital transformation, eventually, that, hey, we're really competitive now. And I think if you take out maybe 1 or 2 of the large customers, that we're probably already 50/50, we're certainly more than 50% at TSMC. And, but that whole transition in terms of digital and getting pricing right for digital took about 6 years, about 2 contract cycles to get that right. Initially, we probably underpriced this, using it, and then once they saw the value, it was benchmarking effectively. I mean, most customers, they'll look at benchmarking our tool against the competitor's tool for their specific design, performance, and area metrics. That's the one to use.
Right.
Pricing doesn't matter a huge amount because the economics of it is that if you're designing a chip a million times or so, it's you know, a small fraction of improvement in PPA, more than offsets whatever you're paying for the tools. But like I say, that was to figure out the pricing for digital, and I think it's gonna take us two contract cycles to figure out the pricing for these initial AI apps, but we will launch new AI apps as we go as well. But
How are you looking, John, the rest of the year into early year? Because, you know-
Yeah
... last year was tough for the semiconductor industry.
Yeah.
That especially a lot of your-
Yeah
... you know, analog customers. So as they are just from the downturn with all the inventory adjustments over-
Yeah
... do you think you would start to see that in, in your bookings improvement in the back half, or is that more a 25 factor for, for-
Well, I think that weakness from last year is already... Because recurring revenue dipped from, like, 13% growth for the last number of years, down to 9% in the first half. Second half, it's already recovering. It's like it's on track for 11%-
Right
... year over year. The odds in that, you know, most of the other CFOs I meet on our network would be like tell me that, you know, it's very hard to forecast 'cause you're trying to figure out, you're looking at pipeline— More than 80% of the business, you know, when the renewal is coming around, you know the... 'Cause the licenses expire at a particular date, you know the customers have to renew by that date, and often you're discussing the configuration with. So it's relatively easy to forecast, but also the timing of renewals impacts bookings. That's like if all of your bookings happened in one quarter and add-ons for the next 11 quarters, you would have a huge explosion in backlog-
Right
... and then you'd burn backlog for 11 quarters, and then you'd have a huge explosion to backlog again. But they're typically spaced out. When I look at, Q2 was the lowest, like the lowest quarter for expiring annual contract value. So there's not a huge amount of renewals and dips slightly in Q2 as a result.
Right.
But, now the second half is strong, though. But, I would expect to finish the year higher than we did last year. I think we were more than $6 billion.
Six billion.
Yeah. So I think it'll be higher than $6 billion, but dip. And it was $6 billion at the end of Q1, but it might dip in Q2 just by virtue of the fact that there's less contracts expiring in Q2, so the quarter of that backlog until the,
Right
... until the contract renewal comes around.
Got it. And then just the last question in the two minutes we have.
Uh.
So, you're at the start of the upgrade cycle for your Dynamic Duo.
Yeah.
When does that start to show up in numbers, and how much of a content or ASP lift do you think versus a Z2 X2?
Oh, that's, that's a great question. It's gates of capacity, right? So the gates of capacity, emulation capacity that a Z3 has is double. Isn't it double?
Yeah.
Yeah. What Z2 is?... but, so the gate price per gate will come down, but the price of a Z3 is almost double the price of a Z2. So profitability should, revenue will improve. The challenge with it is that it takes time to build the Z3s. But I'm quite happy if people want to keep purchasing the Z2s. Launch, and Jensen said such nice things about it. Everyone's very interested in it.
Blackwell was-
Yeah.
Design on Z2.
That's right. But and, and I think, well, sell more Z2s. But of course, there's any customer that Z3 is available, some of them are willing to wait for the Z3, which kind of creates a bit of an air pocket for Q2, to be honest, on the, on the verification side. So we, and, and I think that got lost in the noise a little bit, and it's just our style. We're prudent. We try to de-risk the guide, essentially. So we de-risk Q2, and with the big launch for the hardware systems, the big launch of, of,
But does it create-
Z3
... some above trend potential for next year?
Oh, I think so. I think so. I mean, it, it sets us up really, really well. I mean, it's, it's a showcase product for us. It's Cadence on Cadence. The momentum on that is tremendous. I mean, we've used all Cadence IP and all Cadence tools to create our own product. But, we've done it in half the production cycle of the previous system using our productivity benefits there. And I think it sets us up with the demand for the next... I mean, we, we couldn't keep Z2 on the shelf, so it was selling out all the time.
Any supply constraints?
With our guide, right? Our guide is conservative.
Over the next several-
We basically need 7%-8% revenue growth in the verification group to hit our guide for the year.
I see.
But, so it's 7%-8% because they had a tremendous year last year, the Palladium ramps. But, I mean, if it doubles in demand, we could run into some supply constraints. Previous system, it took a... We ended up having, like, a 6-7-month backlog at one point.
Mm-hmm.
And then we managed to clear through that. We also have huge customers that want access to that emulation capacity, but they can't afford it. They can't afford to—it's like purchasing an emulation system is like buying a Ferrari, and if you only have a use case to use it for a weekend, you don't wanna buy the car. But we think there's an opportunity for us to use the existing inventory in the cloud to service those customers. But what it does from an accounting perspective, boringly, cloud revenue is daily. But so it'll—that piece of it will become, will become ratable. But we're delighted with the capability of the product and everything that Jensen said about it, and just the feedback we're getting from them.
But I think it sets us up for multiple years. I think we're clearly leading in that space. Yeah.
Terrific. Thank you so much, John. Thank you, Richard.
Thanks.
Really appreciate your time.
Thank you.
Thanks so much.