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Index/Engineering & DevTools/Cadence Design Systems Inc Earnings Call Podcast
Cadence Design Systems Inc Earnings Call Podcast artwork

Cadence Design Systems Inc ($CDNS) Q1 2026 Earnings Call

Cadence Design Systems Inc Earnings Call Podcast · 2026-04-27

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Key moments - from our scoring

Substance score

56 / 100

Five dimensions, 20 points each

Insight Density11 / 20
Originality8 / 20
Guest Caliber13 / 20
Specificity & Evidence14 / 20
Conversational Craft10 / 20

Cadence's Q1 2026 earnings call showcases the semiconductor EDA company firing on all cylinders as agentic AI adoption accelerates across the industry. CEO Anirudh Devgan announced the launch of AgentStack - a framework spanning three new AI super agents (ChipStack for RTL design, VitaStack for analog design, InnoStack for digital implementation) - that promise to automate previously manual design work while driving increased consumption of Cadence's base tools. The $8 billion record backlog reflects strong customer confidence in these solutions. On the financial side, Q1 revenue hit $1.474 billion with 45% operating margin and 19% YoY growth. The Hexagon DNE acquisition (contributing $20 million in Q1) adds physical AI and multibody dynamics capabilities for autonomous systems and robotics applications. Management emphasized a three-layer strategy: accelerated compute/data, simulation/optimization engines, and agentic AI orchestration. Key customer wins include a record IP engagement with a leading foundry, expanded deployments with MediaTek and Nvidia, and strong adoption of Palladium Z3 emulation hardware. The pricing model is evolving: new agentic capabilities will use subscription-plus-consumption models on workflows previously done manually, while base tool consumption increases as agents run more iterations and experiments than human engineers. Partnerships with Google (Gemini integration on GCP) and Nvidia (AI/robotics collaboration) extend Cadence's reach into hyperscale AI infrastructure and autonomous systems.

Key takeaways

  • →Agentic AI solutions are driving a new subscription-plus-consumption revenue model for previously manual workflows (analog design, RTL generation, verification) while simultaneously increasing base tool usage as agents perform more design iterations than human engineers.
  • →Cadence achieved record $8 billion backlog and is raising 2026 revenue growth guidance to 17% while expecting to hit the rule of 60 for the first time, despite Hexagon acquisition diluting 2026 EPS by ~$0.28 due to financing structure.
  • →The IP business grew 22% YoY with competitive wins at advanced nodes and marquee accounts, while core EDA achieved 18% growth, driven by proliferation at market-shaping customers and strong demand for hardware accelerators (Palladium Z3) among AI and HPC customers.
  • →Physical AI is becoming a strategic growth vector through the Hexagon DNE acquisition, enabling structural and multibody dynamics simulation for autonomous systems, drones, and robotics applications where narrowing the sim-to-real gap is critical.
  • →Strategic partnerships with Google (ChipStack optimization with Gemini on GCP) and Nvidia (combining agentic AI with accelerated compute) are positioning Cadence as the platform layer for next-generation chip development and hyperscale AI infrastructure.

Topics in this episode

Agentic AIPhysical AIChipStackVitaStackInnoStackAgentStackHexagon DNERule of 60Palladium Z3Virtuoso Studio

Questions this episode answers

How is Cadence planning to monetize agentic AI solutions given they automate work previously done manually?

Cadence plans a two-pronged approach: new agentic tools automating previously manual workflows (analog design, RTL generation) will be priced on a subscription-plus-consumption model similar to leading AI tools, while base tool consumption increases because agents run far more design iterations and experiments than human engineers, driving higher usage of simulation and verification engines.

What is the rule of 60 that Cadence expects to achieve in 2026?

The rule of 60 combines revenue growth rate (17% expected for 2026) and free cash flow margin to reach a target of 60; achieving it for the first time demonstrates Cadence is balancing strong growth with profitability and cash generation.

Why is the Hexagon DNE acquisition dilutive to 2026 EPS despite driving long-term value?

Hexagon's $160 million revenue contribution is dilutive by approximately $0.28 per share in 2026 because 30% of the $1.45 billion acquisition price was paid in stock and 70% in cash; the cash portion creates interest expense that outweighs the operating profit from the business in the short term, though it is expected to be accretive in 2027.

What competitive advantages does Cadence cite against AI-based EDA tool development by competitors?

Cadence emphasizes its 15,000-person workforce with 10,000 in R&D (over half with advanced degrees, more than 1,000 with PhDs), plus decades of domain expertise, proprietary data, and physically accurate simulation engines; management is confident this competitive moat cannot be replicated by other parties writing EDA tools with AI.

How are chip shortages and customer pricing power affecting Cadence's engagement and revenue opportunity?

Shortages are actually benefiting Cadence because healthy semiconductor customers are increasing R&D spending, expanding to multiple foundries/nodes for capacity assurance (driving more design activity), and showing strong openness to agentic AI solutions that boost productivity and allow them to tackle the unrealizable headcount growth required for next-gen designs.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

11 / 20

The call contains a meaningful number of specific, operationally relevant claims - EDA as a rising share of R&D, agentic agents running 10-100x more tool invocations than humans, and the unrealizability of 2x engineer headcount growth - but is padded with standard earnings call promotional language and repeated framework recitations that dilute density.

EDA used to be 7% of R&D and now it's more like 11% of R& D. So it has gone up And R and D spend itself will go up significantly
every new Design they require 2x more engineers. And anyway it's like unrealizable uh, headcount growth because they can't hire 2x more engineers every time

Originality

8 / 20

The physical-AI-bigger-than-data-center-AI thesis and the irreversibility-of-automation-spend point are moderately contrarian, but most content is standard earnings narrative - recycled 'three layer cake' framing, agentic-AI-drives-consumption logic repeated across multiple answers, and familiar TAM-expansion rhetoric.

I believe physically it will be bigger than data center AI by a long shot because you're talking about like trillions of dollars of product opportunity
any shift that you see from customers labor spend to automation that's likely to be irreversible and likely to accelerate over time

Guest Caliber

13 / 20

Anirudh Devgan is a genuine practitioner running a $6B+ EDA company at the frontier of semiconductor design automation, and he demonstrates real technical depth on tool architecture, foundry dynamics, and hardware roadmaps; John Wall adds credible CFO-level financial specificity. However, it is a formatted earnings call with IR boilerplate, which constrains candor.

we have um, about 15,000 people now in cadence, about 10,000 are in R and D. You know, we have more than half uh, of them have advanced degrees. I think more than thousand of them have PhDs
we always design next generation systems. And because we control the whole stack including the system design and silicon design, one thing to remember is we will do it much faster than what the FPGA cadence will be

Specificity & Evidence

14 / 20

The transcript is rich with concrete numbers - $8B backlog, 22%/18%/18% segment growth rates, Hexagon $160M revenue / 28-cent dilution / 5-10% margin impact / accretive 2027, $180M pre-close tax liability reclassification, 1 trillion transistor Z3 capacity ceiling, 2nm node IP deal - though customer names are anonymised ('marquee AI infrastructure company') and some product adoption claims lack external validation.

operating cash flow approximately 2.1 billion, which would be about 100 million above our original guide
that particular is focused on IP and the two things that drove it is that it is uh, a new node, new advanced node, more specifically 2 nanometer

Conversational Craft

10 / 20

Analysts ask targeted, informed questions - pushing on Z4 refresh timing, agentic pricing models, second-half conservatism, and Hexagon go-to-market - but the one-question rule prevents substantive follow-ups, and executives frequently pivot to prepared talking points without being pressed back on vague claims like 'agentic AI could happen sooner than two contract cycles.'

historically you've roughly been ON uh, a two year cadence. Um, should we expect Z4X4 within the next 12 to 18 months or is the bar to upgrade higher now
the largest IP arrangement uh today with the Global Foundry was really the extension of that agreement to additional nodes, the scope of more content or the addition of agent ready AI flows that made the biggest difference

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Share of words spoken

  • Speaker C56%
  • Speaker D19%
  • Speaker B19%
  • Speaker A6%

Most-used words

question50design41agentic38customers38cadence37line35first26operating26thank25strong25thanks25flow24chip23revenue23hexagon23part21

Full transcript

0

Transcribed and scored by The B2B Podcast Index.

Speaker A: Ladies and gentlemen, good afternoon. My name is Abby and I will be your conference operator today. At this time I would like to welcome everyone to the cadence first quarter 2026 earnings conference call. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, simply press star and then the number one on your telephone keypad. Thank you. And I will now turn the call over to Richard Goo, Vice President of Investor Relations for Cadence. Please go ahead.

Speaker B: Thank you, operator. I'd like to welcome everyone to our first quarter of 2026 earnings conference call. I'm joined today by Anur Devgan, President and Chief Executive Officer and John Wall, Senior Vice President and Chief Financial Officer. The webcast of this call and a copy of today's prepared remarks will will be available on our website, cadence.com today's discussion will contain forward looking statements including our uh, outlook on future business and operating results. Due to risks and uncertainties, actual results may differ materially from those projected 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, 10K and 10Q, CFO commentary and today's earnings release. All forward looking statements during this call are based on estimates and information available to us as of today and we disclaim any obligation to update them. In addition, all financial measures discussed on this call are non GAAP unless otherwise specified. The non GAAP measures should not be considered in isolation from or as a substitute for GAAP results. Reconciliations of GAAP to non GAAP measures are included in today's earnings release. For the Q and A session today, we would ask that you observe a limit of one question only. If time permits, you can re queue with additional questions now. I'll turn the call over to Anirud.

Speaker C: Thank you, Richard. Good afternoon everyone and thank you for joining us today. I'm uh, pleased to report that Cadence had a strong start to 2026 with accelerating AI demand and disciplined execution delivering one of the best Q1s in company's history. Our record backlog of $8 billion was ahead of plan, reflecting strong customer confidence in our AI driven portfolio and its pivotal role in enabling delivery of their increasingly complex chip and system design roadmaps. Given the accelerating momentum of our business, we are raising our 2026 revenue growth outlook to 17% and expect to achieve the rule of 60 for the first time. John will provide more details in A moment Agendiq Ah AI Era is here and Cadence is leading the transformation of semiconductor and system design. At Cadence live Silicon Valley 2026, we took a major step towards fully autonomous chip design, pioneering the industry's most advanced and comprehensive agentic full flow platform. We introduced AgentStack, the head agent framework for our uh AI super agents which enables knowledge sharing across the design flow and extend autonomous designs from chips to three DIC to systems. Building on our UH revolutionary chip stack AI Super Agent for RTL design and verification, we introduced two new breakthrough AI super agents, Vita Stack for analog and custom design and Innostack for digital implementation and sign off. Together, these solutions span the entire chip design flow, creating a connected continuous learning platform that brings the industry closer to comprehensive automation. As the industry begins transitioning to agentic AI, the need for physically accurate and highly mathematical EDA solutions become even more critical. Our agentic AI solutions are built on decades of domain expertise, proprietary data and tightly integrated physically accurate engines delivering high fidelity results. We continue to uh, view our platform as a three layer cake with accelerated compute and data as the base layer, principal simulation and optimization as the critical middle layer and agentic AI as the top layer. As I've said before, we believe the greatest value comes from the tight coupling of these layers reinforcing each other to deliver much better results. As these super agents invoke our simulation, verification and implementation engines at scale, we expect them to materially expand EDA consumption and drive higher usage across our platforms. We announced a strategic collaboration with Google to optimize the chip stack AI Super Agent with Gemini on Google Cloud by combining LLM Reasoning with GCP Scalable Compute. This collaboration delivers a cloud native platform for next generation chip development. In Q1, we furthered our long standard partnership with MediaTek through a wide ranging expansion across our new agentic AI offerings and core EDA3 DIC and system analysis solutions. Physical AI is emerging as the next big wave of intelligence as AI moves into autonomous systems, autos, drones and robotics, and Cadence is uniquely positioned to lead this transition. The addition of Hexagon's DNE leading structural and multibody dynamics technologies transforms our system analysis portfolio to a leadership position in physical AI, enabling customers to build and train fundamentally new AI world models by narrowing the critical Sim 2 real gap. At cadence Live Silicon Valley, we announced an expanded partnership on AI and robotics with Nvidia. By combining our agentic AI driven solutions with Nvidia's advanced technologies, we are accelerating engineering workflows and boosting productivity across chip design. Physical AI systems and hyperscale AI factories. Now let me provide an update on our businesses. Our IP business continued its strong momentum with 22% year over year revenue growth driven by accelerating demand of AI, HPC and automotive workloads. UH growing complexity of advanced node designs and chiplet based architectures is driving strong demands of our UH differentiated star IP portfolio. Across interface, memory and foundation IP we achieved meaningful competitive wins and customer expansions at marquee accounts reflecting the breadth of our portfolio and more importantly the differentiated performance of our solutions. We closed a UH record deal with with a leading global foundry marking our largest IP engagement with this customer to date and reinforcing our leadership at the most advanced nodes. With strong market tailwinds, focused strategy and expanding customer proliferation, we remain very well positioned for continued growth in ip. Our core EDA business delivered another strong quarter with revenue growing 18% year over year driven by increasing proliferation of our solutions at market shaping customers. Our AI driven solutions and increasingly our agentic offerings are becoming an important part of customer renewals and expansions. Demand for our hardware accelerated in Q1 resulting in our best quarter ever led by AI, HPC customers and increasing demand in automotive and robotics. Palladium Z3 continues to be the gold standard for emulation and drove multiple competitive displacements. Momentum on verification software grew particularly Nexelium and Verisim sim AI and chip stack generated tremendous customer interest with a large number of evaluations underway led by AI driven cadence Cerebris solution, our digital platform continues to gain share especially at the most advanced nodes. A global semiconductor design leader significantly increased their innovus usage and adopted our digital sign off solutions and a marquee AI infrastructure company expanded their usage of uh, our sign off solutions and their leading edge ASIC designs in custom and analog. Our AI driven virtuoso studio continued its strong momentum in design migration and layout automation as it gets increasingly deployed by analog and mixed signal leaders seeking greater productivity. Our system design analysis business delivered 18% year over year revenue growth as AI driven multiphysics simulation and 3D IC become essential to addressing growing system challenges. We have strong momentum in 3Dic where our unified multi die integrated design to analysis flow is helping customers address their rising chiplet and advanced packaging complexities. We also saw strong momentum in Syncret and Clarity with multiple memory and advanced IC packaging. Customers expanding their deployments as they move to higher speed interfaces. Customer adoption is increasing as they look to address signal integrity, power integrity and thermal challenges earlier in the design flow through deployment of a full cadence sign off flow in Closing I'm, uh, pleased with our strong execution and the broad based momentum of our business. As the agentic AI era UH unfolds. Cadence is leading the charge to realizing much higher design productivity. Increasing design complexity and the growing need for productivity is creating a compelling long term opportunity for Cadence. With our AH, differentiated solutions and expanding agentiq AI portfolio, I believe we are very well positioned to lead this transition and continue delivering meaningful innovation and value to our customers. Now I will turn it over to John to provide more details on the Q1 results and our updated 2026 outlook.

Speaker D: Thanks Anilud and good afternoon everyone. I'm pleased to report that Cadence delivered excellent Results for the first quarter of 2026 with accelerating momentum and broad based strength across all our businesses. Robust design activity coupled with our Solid execution drove 19% year over year revenue growth and 45% operating margin for Q1. First quarter bookings were ahead of expectations resulting in record backlog of $8 billion. Here are some of the financial highlights from the first quarter, starting with the P and L total revenue was $1,474,000,000. GAAP operating margin was 29.3% non GAAP operating margin was 44.7% GAAP EPS was $1.23 and non GAAP EPS was $1.96. Next, turning to the balance sheet and cash flow. Our cash balance was $1,407,000,000, while the principal value of debt outstanding was 2,000,000, uh, $925,000,000. Operating cash flow was $356,000,000. DSOs were 67 days and we used $200,000,000 to repurchase cadence shares. Before I provide our updated outlook, I'd like to highlight that it contains the usual assumption that export control regulations that exist today remain substantially similar for the remainder of the year. For our updated outlook for 2026, we expect revenue in the range of $6,125,000,000 to $6,225,000,000 GAAP operating margin in the range of 27.5 to 28.5% non GAAP operating margin in the range Of 43.5 to 44.5% GAAP EPS in the range of $4.39 to $4.49 non GAAP EPS in the range of$7.85 to $7.95 operating cash flow in the range of 1.875 to $1.975 billion and we expect to use approximately 50% of our free cash flow to repurchase cadence shares in 2026. With that in mind, for Q2, we expect revenue in the range of $1,555,000,000 to $1,595,000,000, GAAP operating margin in the range of 28.5 to to 29.5%, non GAAP operating margin in the range Of 44.5 to 45.5%, GAAP EPS in the range Of $1.07 to $1.13 and non GAAP EPS in the range of $2.02 to $2.08. And as usual, we published a CFO commentary document on our investor relations website which includes our outlook for additional items as well as further analysis and GAAP to non GAAP reconciliations. In conclusion, Cadence is off to a strong start for the year. We are raising our 2026 revenue outlook to approximately 17% year over year growth. As always, I'd like to thank our customers, partners and our employees for their continued support. And with that operator, we will now take questions.

Speaker A: Thank you. At this time I would like to remind everyone who wants to ask a question to please press STAR and then the number one on your telephone keypad. As a courtesy to all participants, we ask that you please limit yourself to one question. We will pause for just a moment to compile the Q and A roster. And our first question comes from the line of Charles she with Needham. Your line is open.

Speaker B: Hi, good afternoon. Thanks for taking my question. Um, Anirudh, I think I have a pretty high level question but uh, this is probably top of the mind uh, for a lot of investors. Uh, we obviously learned agentic AI, uh, is probably good for EDA, good for license, consumption, etc. But uh, we're still hearing some concerns around AI's ability to actually write the software. And um, there are some doubts around whether AI can actually write better EDA based tools like uh, based tool, I mean uh, virtuoso universe, those kind of tools. Um, obviously there are always many EDA startups happening at the same time and so the question is AI's ability to write software, uh, worries you about ah, the defensibility of the uh, EDA based tool? Uh, obviously once again we understand that gentake AI is good for consumption of

Speaker C: the base tool business.

Speaker B: But uh, want to get your thoughts? Thank you.

Speaker C: Yeah, hi Charles, thanks for the question. So I mean there are multiple parts to this of course. I'm super excited about agentic AI applied to chip design and eda. And your question is more specific to the base tool and whether AI can write those base tools. So first of all, I have to, you know, I'm very confident in our position in the base tool and our competitive advantage.

Speaker B: Okay.

Speaker C: And just to remind everyone, I mean we have um, about 15,000 people now in cadence, about 10,000 are in R and D. You know, we have more than half uh, of them have advanced degrees. I think more than thousand of them have PhDs from, from the top universities. So we will anyway deploy AI internally like we are to write our software better. But I'm not worried that some other party will be able to write any better base tools. And our competitor of the base tool is anyway best in class. And I don't see any reason that will change going forward. Okay, now what I'm super excited that we launched, uh, in Cadence Live is the agentic part and the interplay of the agentic tools with the base tools, the AI orchestration combined with physical accurate based tools. And that creates new opportunities for us both in terms of um, TAM expansion. Because what agentic AI allows us is to sell products in spaces we didn't have products before, like RTL generation, verification, plan generation. And those products I think, uh, will be consumed more on a subscription plus consumption, uh, model. So this is entirely a new category for Cadence. And then in turn, like you said, agentic AI will drive more of our base tools. So I feel pretty good about this kind of three layer framework we have talked about and confident going forward.

Speaker A: And our next question comes from the line of Jason Salino with Keybanc Capital Markets. Your line is open.

Speaker B: Great. You know, thank you so much. Um, maybe just a clarifying question. Um, so I noticed that the operating margin guide, you know, is coming down, you know, by a little bit. Um, curious if, like what are the main drivers of that, John? And I know we're layering in kind of the Hexagon acquisition, but on like an absolute basis it's relatively small entering in that opex. So maybe you can just help, help us understand the guide on the margin. Thank you.

Speaker D: Yeah, sure, Jason, thanks for the question. Yeah, what you're seeing there is primarily the impact of including the hexagon design and engineering business in the current outlook. Um, the strategic opportunity there is very large. But the 2026 P&L reflects the timing of integration that um, we announced in the press release when we um, when we closed the deal that we expect 160 million of revenue this year. That's, that's in the guide now. Um, uh, we expect it to be dilutive to the tune of about 28 cents. Uh, the margin impact on 160 million is kind of in the 5 to 10% range. Um, but the dilution comes from um, because we paid 30% of the acquisition price in shares and 70% in cash or the interest component on the, or the lost interest income on the cash, um causes a lot of the dilution impact in the short term. We'd uh, expect it to be accretive in um, in 20, uh, 27. The um. Yeah, so, so I think the way to think about it is financially 2026 is an integration year and the guide includes the, the uh, acquired cost base, the financing impact, the acquisition related integration costs and kind of near term dilution. And that's why revenue moves higher while, while EPS and operating margin are lower than the February guys. Um, uh, so yeah it's 160 million and I think in Q1 the impact was slightly uh, less on the, on the EPS that uh, we had about 20 million of revenue from Q1 from Hexagon, um, so only about $0.01 kind of dilution impact. Um, so EPS would have been like $0.01 higher if we didn't have uh, Hexagon.

Speaker A: And our next question comes from the line of Vivek Arya with Bank of America securities. Your line is open.

Speaker B: Thanks for taking my question. Um, you know Aniruddh, in the last year all we have been hearing nonstop are uh, different news about chip shortages, um, and uh, growing kind of price of chips and just the pricing power that many of your uh, customers have. And my question is what effect new shortages and the fact your customers have more pricing power, what effect does that have on their engagement with cadence? Um, you know, does it restrict chip starts, does it shift them towards higher um, asp, uh products? Just what impact do semiconductor shortages have on your growth and engagement, uh, trajectory? What, what has changed and what are you observing in your customer behavior? Thank you. Thank you.

Speaker C: Yeah, thanks Vivek for the question. So I would say a few things. So first of all, I mean the environment is pretty healthy both for the system companies and semi companies. So that's always good. Like you know, I mean some of the hyperscalers and AI semi companies were all already doing well last year but now you know, the memory companies are doing well. Even you know, analog big semic companies are doing well. So we uh, of course want to see our customers doing well and that creates a positive environment for, for engaging especially with these new solutions we have. So that's actually a pretty uh, marked improvement over the last three to six months. So that's number one Number two, the shortages, you know, it doesn't directly, I mean the customer is still committed to long term R and D roadmaps. And sometimes they may like do um, like I've seen in few cases the customers for example may do, you know, multiple foundries or nodes, you know, to make sure there is capacity at a particular node or foundry. So that would directly lead to more design activity for us. So in general if the customer is healthy because the revenue is going up, they will do not only more in the current designs to accelerate them but also may start new designs. You know, I think that's the second thing I would say. And third thing which is more exciting for us is you know, as we have these agentic solutions, it can give more productivity for our customers and we can deliver more value ourselves. And the more value we deliver, the more opportunity we have to capture part of that value. And the customers are very open to those discussions as there is more automation. So we are actually like I mentioned, there's a lot of engagement with Chip, uh, Stack and also the new Agent Stack, Endostack Beta Stack. There is no pushback at all. If we can deliver productivity, the customer is more than willing to engage. So that's, I would say Vivek, are at least the three broad areas I see in the current environment.

Speaker A: Our uh, next question comes from the line of Jim Schneider with Goldman Sachs. Your line is open.

Speaker C: Good afternoon, thanks for taking my question. I was wondering if you could maybe unpack your commentary on the Agentix solutions

Speaker B: specifically around uh, your indication they would drive increased consumption for base tools.

Speaker C: Can you maybe talk a little bit

Speaker B: about the pricing uh, for those tools,

Speaker C: um, how the Agentix solutions are being

Speaker B: priced specifically and then on net, uh,

Speaker C: if you could frame for us maybe how you might be able to capture more revenue value overall on net, uh, between agentic and conventional licenses.

Speaker B: Thank you.

Speaker C: Yeah, thanks for the question. So I think the opportunity is significant I believe and especially with Agentic because what, you know this, and this happened over the last, let's say six to 12 months in my opinion and more so in six months is not only the agentic tools have evolved but agentic tools are able. We can embed skills in them so they can do a lot more automation. You know, for example we launched uh, you know, Vita Stack, uh, which is analog automation. Analog has been a long problem to automate. Right. Very difficult to automate. But now with these agentic flows and skills we can automate that. So what does that mean in terms of pricing or how these things are consumed. So first of all, like I said, this kind of automation was not possible before. So all this work used to be done by the customers themselves.

Speaker B: Right.

Speaker C: And in that case also I talked to one big customer. Like for example they said for analog or even for digital, every new Design they require 2x more engineers. And anyway it's like unrealizable uh, headcount growth because they can't hire 2x more engineers every time. So the way we plan to monetize and the early signs are positive is that first of all we'll sell new tools that we never sold which is more like this was manually done by customers like doing analog design or doing so that will be priced as a subscription plus consumption model, very similar to other kind of leading AI tools. So that's a completely new category for cadence and that will kind of bend the headcount curve for our customers. But the expected headcount curve was never realizable anyway. So this is the history of automation. As you know in EDA we always need to uh, do that, but this time we can do that with the agentic kind of AI flow. And then once the agent runs when a user designs a chip, and this is pretty common, uh, let's say that chip has 100 blocks just to keep it simple. And there are 100 engineers, one engineer is running one block, one engineer will run one or two experiments. He or she to see which settings or which uh, design is better. But when the agent runs those blog they may try 10 or 100 variations of those things. And anyway AI does a lot more exploration than a human would do. So not only agent can give more productivity if by nature runs more of the base tools. So that's why if you look at um, our uh, usage of base tool, it's going up pretty significantly in this kind of environment. So this is the two ways and in those environments as a traditional business model, but in the base tools, but there'll be more demand for it. And then the new business model which is more automating which was manual with agentic flows.

Speaker D: I would just add Jim that what we saw from Q1 was the overall pricing environment has improved. Um, uh, pricing obviously remains value based with us we provide tremendous value to our customers especially with our uh, agentic flow. Um, and we stand to benefit from our customer success in that area. Also any shift that you see from customers labor spend to automation that's likely to be irreversible and likely to accelerate over time.

Speaker A: And our next question comes from the line of CT panigrahi with Mizuho. Your line is open.

Speaker B: Great. Uh, thank you. I want to switch to the IP business. Uh aniruddh you talked about IP uh entering now third year of strong growth. Uh, could you give an update like what you saw in Q1 and are uh, there's HBM, LP, DDR6 and all that remaining still the key drivers or uh, and the new foundry like Rapidus Intel Foundry are uh, they contributing meaningfully to the IP demand yet?

Speaker D: And John, just to clarify also on

Speaker B: your EPS guidance you said 28 cents dilution but you lowered only 20 cents. Just want to clarify that your organic basis you raised by 8 cents EPS. Thank you.

Speaker D: I'll take the last part first. Yes, yes we did. We raised by 8 cents

Speaker C: and it is a great start to the year. Uh okay. And not just in IP across the board and I was looking at with our team, I think this is one of the strongest raises we have had in Q1. You know we only gave you guidance in February, so two months later I think this is one of the strongest raises we have had. Now all the businesses are doing well and especially IP is off to a great start and I think it will do well uh going forward from what I think I see. And there are at least three big reasons in my mind for IP growth. And like I said it's the third year now so we don't like to talk about things too early but after three years of strong growth I think that is a good trend. So the first thing is our IP quality and performance is just better. We have a new team, just the performance because these things are standard based IPs like DDR or PCIe so the spec is same but if our power area is better than the competitor or what the customer can do then they will buy our ip. So the most promising thing to me is because the strength of our R and D team, our PPA is better and that is leading to a lot of competitive wins at pretty significant major customers. And I highlighted some of them in Cadence Live. So these are really big kind of marquee names. So that gives me strength that the team is operating well. So that's number one. Number two, our portfolio is expanding like we have highlighted uh with hbm. And some of it is organic, some of it is uh acquired like HBM we acquired from Rambus and then we improved it. But ucie which is a critical chip to chip technology was all developed organically.

Speaker B: Okay.

Speaker C: So the second reason is that our portfolio is expanding. The third reason is these new Foundries. Okay. And it's very encouraging to see. Of course we want to make sure we are best in class in tsmc, which is the leading foundry. But now there are at least three other major foundries, as you know, Samsung, intel and rapidus at advanced nodes and then Global and others at mainstream nodes. So the amount of design activity with AI and number of increasing foundries requires more ip. So that's why I'm actually pleased to note today in the prepared remark that, uh, we had a pretty significant, um, IP deal, one of the largest ones at a leading global foundry. Uh, and just to clarify, that is not Intel. We are actually pleased with our discussions with intel, with Libbu and team on 18A and especially on 14A. I think intel realizes they need to invest more in 14A and this time be more ready because availability of IP and EDA solutions as 14A is critical as they go talk to their customers. So we are making very good progress with Intel. And, uh, we'll have, um, you know, soon we'll have more to say on our engagement with intel, but I'm also pleased with this engagement with the other global foundry. So overall, you know, IP growth seems robust and I'm very pleased where we are. And we're already always very strong in eda. But historically, last few years, you know, we have not done as well in ip. But right now I think we are very well positioned and also well positioned in sda.

Speaker A: Uh, our next question comes from the line of Joe Quatrocchi with Wells Fargo. Your line is open.

Speaker B: Yeah, thanks for taking the question. Maybe just to kind of follow up on the discussion earlier on eda. I mean, I guess when you take a step back and you think about, you know, EDA's share of R and D expense, um, and clearly we're seeing an acceleration of R and D expense across a number of different companies. How should we think about, you know, EDA's contribution to that or percent of that and where could that go, given the value maybe you're providing from AI? Um, because we're also seeing. Right. Memory costs are increasing, things like that that also need to flow through that R and D line.

Speaker C: Yeah, good question. And we have to, you know, observe it closely. Right. You know, you know, as we rather like print things than kind of predict what will happen, because it's better to show than to. But as historically we have said EDA used to be 7% of R&D and now it's more like 11% of R& D. So it has gone up And R and D spend itself will go up significantly. But I think there is a real potential, especially with agentic AI, for that 11% to go up. All the big CEOs I talked to, they are not only willing, they want to see that happen. They want to invest in more automation and compute to make it happen. I'm pretty sure right now I think it will go up. It will go up. We will see, right? But I think there's a meaningful, uh, opportunity for automation to be a higher percentage of R&D R&D itself to go up.

Speaker A: Our next question comes from the line of Ruben Roy with Stifel. Your line is open.

Speaker D: Yeah.

Speaker B: Uh, thank you, John. I want to go back to the operating margin discussion. Uh, it's great to see that, uh, you guys are targeting rule of 60 by the end of the year here. Um, just thinking about that, though. It's driven revenue acceleration. Obviously we've got the hexagon integration costs here, but are you thinking about the operating model relative to operating margin? As you get over 6 billion in revenue, does the operating model look a lot different than it did at 5.3 billion? Is this sort of 43 to 45% range how we should be thinking about the operating margins? And I asked that because obviously you're investing in the gentic AI and other sort of new product areas. Just wondering if you can give us a little bit of an idea of how you're thinking about, uh, the operating margin structure at this revenue run rate, uh, you know, longer term, as you integrate hexagon. Thank you.

Speaker D: Yeah, sure, Reuben. Thanks for the question. Yeah, I think when we look at our, um, like organic incremental margin is closer to 60% these days than 50%. Um, and you know, as we get our arms around these, uh, acquisitions, it typically takes us 12 to 18 months to, to improve the profitability up to kind of something close to, uh, two to our expectations, that cadence that, uh, and I would liken the profile to the way beta. So. So in 24 and 25, you kind of had an operating margin profile where we had the dilutive impact of the beta acquisition in 24. But then, you know, margins improved dramatically in 25 as we got the synergies and we got the benefits of making that more profitable. I would expect a similar pattern for 26 and 27. When it comes to Hexagon, we have a slight headwind, um, in the short term, um, but, uh, there's plenty of opportunities to improve the profitability there. And also with the benefits that we're seeing in terms of customer engagement accelerating on the agent I front, I think there's, there's um, even more opportunities to stretch that um, incremental uh, operating margin going forward.

Speaker A: Our next question comes from the line of Harlan sir, with JP Morgan. Your line is open.

Speaker D: Yeah, Good afternoon. Uh, thanks for taking my question. If I take your 2Q guidance and look at your implied second half guidance, the average quarterly revenue run rate in the second half is actually slightly below the 2Q level. Is there some lumpiness in the Hexagon business in the second half? Maybe moving customers to multi year license agreements? Or is it due to some lumpiness in the core business?

Speaker B: Maybe a more first half weighted hardware

Speaker D: or IP shipment profile? Yeah, thanks for the question, Harlan. Yes, surely. Look, the first half is very strong and the second half I describe as containing appropriate prudence. The um, your comment on uh, Hexagon's D and E business is correct. They are more kind of first half weighted um, in terms of their profile. Uh, when I looked at last uh, year's revenue for Hexagon, I um, think Q3 and Q4 were their worst 2/4 of the year. They tend to have a lot of um, uh, early year kind of dated contracts. Um, but, but overall I think the second half, I mean it doesn't, Hexagon doesn't impact the first half, second half that much. It's uh, it's really uh, I think we had such as Andrew said, Q1 guide represents one of the highest raises we've had at this time of the year. And we normally like to wait until um, you know, know we had two quarters under our belt to raise the guide. We couldn't help but raise the guide given the strength of Q1 bookings and the strength we saw across the board. Um, so uh, we just wanted to wait until July to update the second half.

Speaker A: Our next question comes from the line of Lee Simpson with Morgan Stanley. Your line is open.

Speaker B: Great. Uh, thanks for squeezing me in. Uh, I just wanted to ask about physical AI. I mean you've made some pretty good acquisitions. You're now announced collaborations m especially with Nvidia. So I'm just trying to get a sense for the momentum here and what really is still the early years in this breakout and I think in particular you know, the take up of your emulation tools, especially as it relates to closing the sim to real gap in robotics and probably even self driving chips as well. Whether or not that's going to really lead to an outsized value capture for cadence and when ah, do we actually see this in the numbers as well. Thanks.

Speaker C: Yeah, thanks for the question, Lee. So I mean, you know, like I talked about it forever. Now that we look at this thing as a three layer cake, right? And there are multiple slices of the cake. And the first slice was data center AI or infrastructure AI. And the second big slice is physically AI. And of course I've said this for five years now, but I believe physically it will be bigger than data center AI by a long shot because you're talking about like trillions of dollars of product opportunity. And it will reconfirm the data center layer. Data center slice because to Deploy e.g. aI model in the car, you need to train it on the data center anyway. So I think it will even help the data center slice. Now for our portion, yes, we made this acquisition, we are super excited about and we have this um, uh, now training flow forward models and also more complete simulation environment. So what is exciting about Hexagon is with combination of our previous technologies like Millennium and Cascade and um, Beta, we do have finally a complete solution for physical AI, uh, in the middle layer kind of uh, principle simulation and optimization layer. And then that can be used to, to do these word models which will be different in the top layer. But uh, other thing I want to emphasize apart from the SDNA and the AI part that physical AI itself will drive lot of silicon design. So it is also good for EDA and ip. And this is, you're starting to see that, you know, of course companies like Tesla mentioning that they don't have enough silicon, you know, because of physical AI. So physical AI not only is good for SDN AI, it is also really good for silicon and it also is the sweet spot of Cadence because Cadence always had both analog and digital solutions. And that's why we're always good with all the major semiconductor companies for automotive and now with all the system and OEM companies for automotive. And as that translates to drone and robots, it will also turbocharge, uh, the silicon business. That's why I have always been excited about physically not just for the AI and SDA part, but also for EDA and ip.

Speaker A: Our next question comes from the line of Gianmarco Conti with Deutsche Bank. Your line is open

Speaker C: afternoon.

Speaker B: Yeah, thanks for squeezing me into um, perhaps on hardware, uh, another strong cause of course. But um, as we think about the next refresh cycle for Palladium and Proteom, historically you've roughly been ON uh, a two year cadence. Um, should we expect Z4X4 within the next 12 to 18 months or is the bar to upgrade higher now, given how recently customers absorbed the first generation and perhaps related, are you seeing any of your own agentic AI tooling materially compress the internal hardware development timelines to the same extent that customers are reporting that same 10x productivity on RTL? Thank you.

Speaker C: Yeah, absolutely. Great question. So first of all, you know, like I said, we have uh, most of our headcount is engineering, right? Whether it's R and D or customer support. So we always want to use our own M products in both our hardware groups, which is a significant um, design team. We do both software, hardware and all the system design in Palladium and Proteome. And also just to remind you in our IP team, you know, it's a great, you know, they're working very well together, our IP team and EDS teams because ip, you know, we have so much demand and you know, instead of again, uh, increasing headcount, we're always sensitive about how much headcount we'll increase. And we are increasing headcount in all areas including ip. But we can make them a lot more productive with agentic AI. Now on the hardware, um, part, yeah, we have, I'm very pleased. I mean it's a remarkable start to the year. Uh, our competitive position is amazing. We are the only company that does its own chip. As you know, we have at least a 10 year lead in that in Palladium. And then Protium also is doing now in which we use the FPGA solution. Now just to be clear, we always design next generation systems. And because we control the whole stack including the system design and silicon design, one thing to remember is we will do it much faster than what the FPGA cadence will be. FPGA companies will also do next generation FPGA designs. But because we are own chip, we do our own design, it will be much faster than fpga. So what that means is the lead of Palladium over FPGA systems will only continue to increase as we introduce new products. But I'm not going to get into like when we're going to introduce new products because the current products are doing amazingly well. Of course we are designing Z4 and Z5. Uh, but what you have to remember is the current Z3 system has a capability to design 1 trillion transistor systems. And right now the biggest uh, systems in the world are 100 to 200 billion transistors. So we have a lot of leeway. The industry is supposed to reach 1 trillion transistors by 2030. One thing I'll assure you is we'll have a Z4 system before 2030. So there is no issue of whether Z3 can handle the capacity and requirements. So we're just happy to work with our customers. At the same time, we want to assure our investor and customers we have a very, very good roadmap on hardware systems.

Speaker A: Our next question comes from the line of Jay Fleeshauer with Griffin Securities. Your line is open.

Speaker B: Thank you. Good evening. Um, Anirud, now that you've completed um, Hexagon MSC acquisition, um, it would appear that you are uh, the fourth largest, um, non eda um, simulation company, let's call it Industrial Simulation with Multi Physics. Uh, your share is perhaps one tenth of that total market. Again, aside from um, uh, EDA simulation. So the question is, now that you've assembled all these pieces, um, invested over 5 billion over the last, uh, five or six years, can you um, speak in some detail about what your principal, uh, technical and or go to market, um, objectives or executables are going to be for the next year or so? Um, Synopsys talked about what they're doing with Ansys. Perhaps you could do the same for your uh, pieces. Uh, it also seems you're becoming a little bit more vertically integrated and go to market with the acquisition of a longtime channel partner. So maybe talk about some of those critical elements here to uh, grow your revenues and share in that business.

Speaker C: Yes, Jay, that's a lot there. Right? There's a lot there. So let me try to unpack some of it. I'm sure we can talk more if I don't get to all the pieces there. Uh, well, first of all, we are satisfied with the scope of our uh, SDA business now after this acquisition. So, I mean, this is rough numbers. So, you know, I think it will be roughly a billion dollars of run rate. And what is more exciting to me is that it is focused in the two important areas of sda. You know, I'm a fan of SDA for a while now. I don't know, maybe eight years now. But not all SDA is created equal. Okay. To me, you know, we want to do the part of SDA that is either growing well or is closely related to eda. So the part of SDA that is closely related to EDA is of course 3DIC. So we have an inevitable position in 3DIC, with Allegro being the leading packaging platform. And then we completed that with clarity and security and Celsius, so all the thermal electromagnetics and integrity. So I'm pretty happy with the 3DIC portion, which is like the closest to chip design, the part of SDA that is closest to chip design and the part that is growing the most because of AI. Now the other part now with Hexagon is all this physical AI and for design of cars and robots. So that with this acquisition is complete and we can do a much better integration of that part of sda. And there are multiple things happening there. Okay. There are at least, you know, two, three key things. So first thing is, um, we will integrate the whole solution. You know, this, you know, I know you asked me this before, you know, when will you integrate? So I think now that we have all the pieces of critical mass, this is the right time to integrate because we have CFD now, we have uh, structural, we have multibody dynamics, we have pre and post. Okay. So we have a lot of effort to make a full flow solution, integrate them. And I kind of hinted at that at Cadence Live. The other thing, the way to integrate these solutions, which is true for eda, but will be true in this area, is agentic flow. So you will see from us agentic flow to do system design and that M part of the market has not seen that much is even worse automation than chip design that had a lot of automation. But there will be agentic flow which will integrate all these things in a better way. The second thing we will do is that there is a lot of room for improvement of these solvers. Especially in our history of improving the base solvers, adding GPU acceleration, adding phys, uh, AI or AI surrogate models. For example, there is a potential for at least the order of magnitude improvement of performance of these new solvers. So that's the second thing we'll do in terms of R and D. And third thing, you know what I'm also pleased with Hexagon is we did get like a good go to market team. That's one area we have not been as strong because we were. Most of the others was mostly organic. And we did move uh, some of our people into go to market. But with Hexagon D and E business we get a much stronger go to market team. And then as we mentioned, we also acquired some, some resellers, uh, to strengthen go to market. At this point I'm very confident of our R and D solution and it will get improved by Gentex solutions. It will get improved by speeding up the solvers. But we also need to invest and go to market and Hexagon gives us a good start. So you will see that too. So these are the three kind of focus areas of improvement of sda.

Speaker A: Our next question comes from the line of Kelsecia with Citigroup. Your line is open. Hi, thank you and good afternoon. Um, Anirudh, um, you mentioned that the Agent Stack helps address talent gaps for chip designers. It sounds like the agent stack adoption just accelerating from here. Based on your conversation, is that the case, um, or are you seeing cases where customers prefer to build or use their own agentic stack versus adopting cadences? And so um, is cadence able to sort of charge for Agent Stack or the increased base licenses as an incremental add on within an existing three year contract or is that monetization type to renewals?

Speaker C: Oh yeah, thank you. There's a lot of good questions there. Okay, so make sure I and I'll start and John, John can add to that.

Speaker B: Um,

Speaker C: now first of all, I think just to be clear, the customers will always write their own agents as well. If I understand the first part of your question. Even in our pre agentic flow we would have given a lot of flexibilities to our customers. We had a tickle or a Python interface to our tools and they would always have their own flows. I mean this is natural for big customers. These are who's who of tech companies. So they always want to have some differentiation, uh, from one floor to the other. And that will happen in the agent word itself. So I think most of our customers are writing some of their own agents. But the key thing is that the critical agents, okay, like these big super agents we talked about like RTL design and verification, analog design and um, physical design, these are like super categories. And also the value of the agentic flow is not just in the agent itself. It's always the coupling of the agent with the base tools because we operate the agent at a much lower level of interaction. This API call which is not possible for customers to do. So what has happened? As an example, as we showed Innostack or Vera Stack and Chip Stack to our customers, they realized, oh, there's no point writing these kind of agents, okay? So they would rather use the super agents we have because not only we are good in agentic flow, we are good in the coupling to the. Now they will still write some agents to customize things which are specific to them and we naturally welcome that. And the agent stack allows the environment for the customer to write its own agent, but also the customer to write its own skills. We want the customers to write their own skills in innostack which may be specific for a part of design. So this has always been our strategy to be more open to customer, uh, kind of uh, customizing their own environment. Okay. And I think the second question is on renewals versus new. I mean it's a combination of that always. John, maybe you want to comment?

Speaker D: Yes. Yeah, thanks Anirud. And thanks Kelsey. Um, our subscription model remains the anchor arrangement with our customers. The um, add on monetization then comes incrementally through agentic workflow products that are kind of usage based or consumption based for capacity and through our token and card models. What's different about agentic AI is that it doesn't replace the core EDA engines. It calls them more often and it calls them intelligently. So sort of monetization opportunity is twofold really. So you've got like the new agent workflow products and then you've got the increased usage of the underlying base tools through more exploration, more verification, more optimization and more compute. Now that said, we're obviously being disciplined in our 2026 outlook. We're not assuming a sudden step function in monetization in the guide. But we do believe agentic AI expands the long term growth opportunity for Cadence.

Speaker A: Uh, our next question comes from the line of Andrew d' Agospiry with BNP Paribas. Your line is open.

Speaker B: Thanks for fitting uh me in. I just had a two part question. One is Marquis, I think you called out in prepared remarks that a marquee AI infrastructure company expanded the use of sign off solutions. I just want to clarify, was this a cloud provider and then second, um, a Cadence live. Um, you discussed about physical AI in terms of the timeline of adoption being around 2 years but yet um, you called out that automotive and robotics companies have adopted hardware. I was just wondering, does this mean that that physical AI timeline has been brought forward or is this just a natural evolution of how these new markets will adopt eda? And if so, when do we see that kind of software um, benefiting from that? Thank you.

Speaker C: Yeah, I think you know, with physical AI and also agentic AI in general, I mean, yes, I've said for a long time, two contract cycles. And that is generally true though I think because of this new category of DAM expansion which is more labor productivity related along with the base tools, I think there is a potential that the monetization of agentic AI could happen sooner than two contract cycles. Okay. I don't want to you know, predict too much and like John said, we are not putting it in our guide. But I think Definitely the more opportunity is there because of all the shortages, because all the build outs because of physical AI. So we are, and like the previous question, you know we always can add in the renewal but we always have capability to do add ons which we have already seen. Okay, so uh, that's what I would like to say on the sign off. You know we are very happy. You know innovation has been the leading solution for implementation especially at TSMC and now increasingly with the Samsung, intel and Rapidus. But sign off is where is coming on strong at TSMC and other uh, customers and we are working with all the leading AI players and I think the one we mentioned specifically is a major kind of AI infrastructure, uh, ASIC company. And we are glad to see that adoption. Uh,

Speaker A: our next question comes from the line of Gary Mobley with Loop Capital. Your line is open.

Speaker B: Hi guys. Thanks so much for fitting my question in. Um, John, I think if I'm not mistaken, 2026 is going to be a low renewal period. By that I mean existing longtime customers scheduled to renew this year. Kind of like 2022 was. And so was the strong bookings in the first quarter reflection of some add on sales as salespeople are trying to meet their quota. And do we expect that type of

Speaker D: behavior to last through the balance of the year? Uh, thanks for the question, Gary. Yes, I mean the uh, 2026 is kind of lighter than 2025 for actual uh, renewals on an annual um, value basis. But what we often see that that's the, that those are some of the strongest growth years for us um, because of all the add on activity. Yeah, we were really, really pleased with the um, with the Q1 booking strength and it was right across the board, across all lines of business. Um, so yeah, so Gary, I mean it bodes well for the year but uh, but look, it's just one quarter. As you know we like to wait for a couple of quarters before taking up the guide in the second half. And although the last few years Q1 has been strong and this one has been very, very strong, so we had to take up the guide at the end of Q1.

Speaker A: Our next question comes from the line of Clark Jeffries with Piper Sandler. Your line is open.

Speaker B: Hello. Thank you for taking the question. Um, I just wanted to ask around. The largest IP arrangement uh today with the Global Foundry was really the extension of that agreement to additional nodes, the scope of more content or the addition of agent ready AI flows that made the biggest difference. To get that to the largest arrangement, you've ever seen.

Speaker C: Yeah, that's a particularly IP contract. So that one particular is focused on IP and the two things that drove it is that it is uh, a new node, new advanced node, more specifically 2 nanometer and uh, and more content in IP because we have a much broader portfolio.

Speaker A: Our next question comes from the line of Joshua Tilton with Wolf Research. Your line is open.

Speaker B: Hey guys, thanks for ah sneaking me in here. Um, maybe just a two parter, uh, a little unrelated so I apologize. But uh, anything to call out on what drove such a strong quarter uh, for China and then maybe just a second part to that. Um, can you help us just bridge what is driving such a great uh, organic raise to the full year relative to the organic beat in the quarter. I know you mentioned, you know the record backlog, but is there anything one level deeper you can give us? Uh, especially in the context of. It sounds like you're trying to tell us that even though you raised by a pretty solid amount that there still seems to be some conservatism in the guide, uh, for the second half. So any help there would be greatly appreciated. Thanks guys.

Speaker D: Sure Josh. Thanks for the question. I'll take this one, Josh. Yeah, China, it was 13% of Q1 revenue.

Speaker B: Um,

Speaker D: uh, and that was just kind of broadly consistent with what we were expecting.

Speaker B: Um.

Speaker D: Yeah, we still expect China to be about 13% for the year. Um, I think it can be lumpy from quarter to quarter. So I think the year over year comps um, probably look generous because Q1 in 2025 wasn't that good in China. So the uh, 18% revenue in Q1 probably the growth rate looks strong but um, but it's just, it's a really important region for us that um.

Speaker B: Um.

Speaker D: Yeah, and we were very, very pleased with um, with the 13%. The. In relation to the guide. Um, Yeah, I mean we're look the Q1 was a very strong start to the year. We exceeded all our metrics. Um, and, and I guess when we, when we back out the hexagon, the 160 million of hexagon and the 28 cents, we're basically raising the year by 65 million uh at the midpoint for revenue and about 8 cents for um, uh, EPS. Also on the cash flow front, that uh, operating cash, the uh, way we paid for um, hexagon, the reported guide includes approximately 180 million of pre closed hexagon tax liabilities that are economically part of the acquisition consideration but are classified in operating cash flow. I think just the geography and the Accounting forces us to put it through operating cash. If you adjust our operating cash guide for that underlying, for that pre closed hexagon tax liability that we're paying, the um, operating cash flow outlook is approximately 2.1 billion, which would be about 100 million above our original guide. Um, so, so there's, there's a lot of strength we saw across the businesses. So the 65 million, you know, is what we took revenue up by. But we're seeing 100 million extra in cash. But um, there's potentially strength in the second half, but we thought it was too early to raise the second half right now.

Speaker A: And our final question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is open.

Speaker B: Thanks very much for squeezing me in guys. Um, just want to ask about the Millennium platform. Um, how's the adoption going there on arud? And uh, just in general the uh, health in some of your non semi verticals like automotive, aerospace, industrial equipment, so forth. Uh, just any commentary around that would be great.

Speaker C: Yes, absolutely. So yeah, Melina is doing great. I don't know if you saw, you know, Jensen was there at Cadence Live and did a nice autograph on Millennium box. So we are pleased with partnership with Nvidia there. And I mean there are two ways to two kind of high level applications. And we are working on this kind of CFD or SDA application for a while and that's going well, especially in auto and also in drones. Okay. There's a lot of, you know what? Cascade acquisition we made is very good at very high accuracy CFD which also applies to aerospace, uh, and defense. So, so there is autos, but also A and D is Millennium uptake. And we have several customers. Some we can talk about, some we can't. Okay, so that's in the traditional Millennium. And the other part this year, like I mentioned in Cadence Live, we have all kinds of EDA application now on Millennium. It's super exciting. And the most exciting part of EDA application in Millennium is three DIC sign off. Because right now the biggest issue is the complexity of these three DIC systems. Not just to design them in integrity and innovas, but to sign them off. So there's this huge system that need to do thermal simulation, electromagnetic simulation, power delivery simulation. And they are more naturally like a uh, matrix without getting too technical. They're closer to a matrix multiply numerical solver, which is great for GPU acceleration. So right now I see Millennium as applying to more traditional areas like autos and then new areas like aerospace and drones and then applying to three DIC sign off. So we are super excited about the Millennium opportunity along with our traditional hardware systems.

Speaker A: And I will now turn the call back to Anaru Devgan for closing remarks.

Speaker C: Thank you all for joining us this afternoon. It's an exciting time for Cadence as we begin 2026 with product leadership and strong business momentum. And on behalf of our employees and our board of Directors, we thank our customers, partners and investors for their continued trust and confidence in Cadence.

Speaker A: And ladies and gentlemen, thank you for participating in today's cadence first quarter 2026 earnings conference call. This concludes today's call and you may now disconnect. Goodbye.

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