Q1 2026 Cadence Design Systems Inc Earnings Call

April 27, 2026

Richard: Q4 2026 Earnings Conference Call. I'm joined today by Anirudh 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 be available on our website, cadence.com. Today's discussion will contain forward-looking statements, including our 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 10-K and 10-Q, 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.

Richard Gu: Q4 2026 Earnings Conference Call. I'm joined today by Anirudh 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 be available on our website, cadence.com. Today's discussion will contain forward-looking statements, including our 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.

Speaker #1: Of the 2026 earnings conference call. I'm joined today by Anirudh Devgan, President and Chief Executive Officer, and John Wall, Senior Vice President and Chief Financial Officer.

Speaker #1: The webcast of this call and a copy of today's prepared remarks will be available on our website, cadence.com. Today's discussion will contain forward-looking statements, including our outlook on future business and operating results.

Speaker #1: 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.

Richard Gu: For information on factors that could cause actual results to differ, please refer to our SEC filings, including our most recent Forms 10-K and 10-Q, 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.

Speaker #1: Including our most recent Forms 10-K and 10-Q, 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.

Speaker #1: 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.

Richard: 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&A session today, we would ask that you observe a limit of one question only. If time permits, you can requeue with additional questions. Now I turn the call over to Anirudh.

Richard Gu: 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&A session today, we would ask that you observe a limit of one question only. If time permits, you can requeue with additional questions. Now I turn the call over to Anirudh.

Speaker #1: Reconciliations of GAAP to non-GAAP measures are included in today's earnings release. For the Q&A session today, we would ask that you observe a limit of one question only.

Speaker #1: If time permits, you can re-queue with additional questions. Now, I'll turn the call over to Anirudh.

Speaker #2: Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. I'm pleased to report that Cadence had a strong start to 2026.

Anirudh Devgan: Thank you, Richard. Good afternoon, everyone, and thank you for joining us today. I'm 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 the 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 sixty for the first time. John will provide more details in a moment. The agentic AI era is here, and Cadence is leading the transformation of semiconductor and system design.

Speaker #2: With accelerating AI demand and disciplined execution, we delivered one of the best Q1s in the company's history. Our record backlog of $8 billion was ahead of plan, reflecting strong customer confidence in our AI-driven portfolio and a pivotal role in enabling delivery of their increasingly complex chip and system design roadmaps.

Speaker #2: 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.

Speaker #2: John will provide more details in a moment. Agendic AI era is here. And Cadence is leading the transformation of semiconductor and system design. At CadenceLIVE Silicon Valley 2026, we took a major step towards fully autonomous chip design.

Anirudh Devgan: At CadenceLIVE 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 AI Super Agent, which enables knowledge sharing across the design flow and extend autonomous designs from chips to 3D IC to systems. Building on our revolutionary ChipStack AI Super Agent for RTL design and verification, we introduced two new breakthrough AI Super Agents, ViraStack 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.

Speaker #2: Pioneering the industry's most advanced and comprehensive Agendic full-flow platform. We introduced AgentStack, the head agent framework for our AI super knowledge sharing across the design flow and extends autonomous designs from chips to 3D IC to systems.

Speaker #2: Building on our revolutionary ChipStack AI super agent for RTL design and verification, we introduced two new breakthrough AI super agents: VeraStack for analog and custom design, and InnoStack for digital implementation and sign-off.

Speaker #2: 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 Agendic AI, the need for physically accurate and highly mathematical EDA solutions becomes even more critical.

Speaker #2: Our Agendic AI solutions are built on decades of domain expertise, proprietary data, and tightly integrated, physically accurate engines, delivering high-fidelity results. We continue to 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 Agendic AI as the top layer.

Anirudh Devgan: 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 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 ChipStack 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.

Speaker #2: 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.

Speaker #2: 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.

Speaker #2: We announced a strategic collaboration with Google to optimize the ChipStack 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.

Speaker #2: In Q1, we furthered our long-standing partnership with MediaTek through a wide-ranging expansion across our new Agendic AI offerings, and core EDA, 3D IC, and system analysis solutions.

Anirudh Devgan: In Q1, we furthered our long-standing partnership with MediaTek through a wide-ranging expansion across our new agentic AI offerings and core EDA 3D IC 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. Cadence is uniquely positioned to lead this transition. The addition of Hexagon's D&E leading structural and multi-body 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-to-real gap. At CadenceLIVE 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.

Speaker #2: 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.

Speaker #2: 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-to-real gap.

Speaker #2: At CADENCE Live Silicon Valley, we announced an expanded partnership on AI and robotics with NVIDIA. By combining our Agendic 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.

Speaker #2: 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.

Anirudh Devgan: 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. Growing complexity of advanced node designs and chiplet-based architectures is driving strong demands of our 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 record deal 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.

Speaker #2: The growing complexity of advanced node designs and chiplet-based architectures is driving strong demand for our differentiated star IP portfolio across interface, memory, and foundation IP.

Speaker #2: 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.

Speaker #2: We closed a record deal with a leading global foundry, marking our largest IP engagement with this customer to date, and reinforcing our leadership at the most advanced nodes.

Speaker #2: 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.

Anirudh Devgan: 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 displacement. Momentum on verification software grew, particularly in Xcelium and Verisium SimAI, and ChipStack generated tremendous customer interest with a large number of evaluations underway. Led by AI-driven Cadence Cerebrus 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.

Anirudh Devgan: 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 displacement. Momentum on verification software grew, particularly in Xcelium and Verisium SimAI, and ChipStack generated tremendous customer interest with a large number of evaluations underway. Led by AI-driven Cadence Cerebrus 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.

Speaker #2: Our AI-driven solutions, and increasingly our Agendic 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.

Speaker #2: Palladium Z3 continues to be the gold standard for emulation and drove multiple competitive displacements. Momentum on verification software grew, particularly in Excelium and Verisium SIM AI, and ChipStack generated tremendous customer interest, with a large number of evaluations underway.

Speaker #2: Led by our AI-driven Cadence Cerebrus solution, our digital platform continues to gain share, especially at the most advanced nodes. A global semiconductor design leader significantly increased their in-house usage and adopted our digital sign-off solutions.

Speaker #2: And a marquee AI infrastructure company expanded their usage of 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.

Anirudh Devgan: A marquee AI infrastructure company expanded their usage of 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 and 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 3D IC, 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 Sigrity and Clarity, with multiple memory and advanced IC packaging customers expanding their deployments as they move to higher speed interfaces.

Speaker #2: 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 3D IC, where our unified multi-die integrated design-to-analysis flow is helping customers address their rising chiplet and advanced packaging complexities.

Speaker #2: We also saw strong momentum in Segrity and Clarity, with multiple memory and advanced IC packaging customers expanding their deployments as they move to higher-speed interfaces.

Speaker #2: 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 pleased with our strong execution, and the broad-based momentum of our business.

Anirudh Devgan: 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 pleased with our strong execution and the broad-based momentum of our business. As the agentic AI era 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 differentiated solutions and expanding agentic 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 #2: As the Agendic AI era unfolds, Cadence is leading the charge to realizing much higher design productivity. Increasing design complexity and the growing need for productivity are creating a compelling long-term opportunity for Cadence.

Speaker #2: With our differentiated solutions, and expanding Agendic AI portfolio, I believe we are very well positioned to lead this transition and continue delivering meaningful innovation and value to our customers.

Speaker #2: Now, I will turn it over to John to provide more details on the Q1 results and our updated 2026 outlook.

Speaker #1: Thanks, Anirudh. 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.

John Wall: Thanks, Anirudh, and good afternoon, everyone. I'm pleased to report that Cadence delivered excellent results for Q1 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&L. Total revenue was $1.474 billion. 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.

John Wall: Thanks, Anirudh, and good afternoon, everyone. I'm pleased to report that Cadence delivered excellent results for Q1 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. Q1 bookings were ahead of expectations, resulting in record backlog of $8 billion. Here are some of the financial highlights from the Q1, starting with the P&L. Total revenue was $1.474 billion. 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.

Speaker #1: Robust design activity, coupled with our solid execution, drove 19% year-over-year revenue growth and a 45% operating margin for Q1. First quarter bookings were ahead of expectations, resulting in a record backlog of $8 billion.

Speaker #1: Here are some of the financial highlights from the first quarter, starting with the P&L. Total revenue was $1.474 billion. GAAP operating margin was 29.3%.

Speaker #1: 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 billion and $407 million.

John Wall: Our cash balance was $1.407 billion, while the principal value of debt outstanding was $2.925 billion. Operating cash flow was $356 million. DSOs were 67 days, and we used $200 million 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 to 6.225 billion. 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%.

Speaker #1: While the principal value of debt outstanding was $2 billion and $925 million, operating cash flow was $356 million. DSOs were 67 days, and we used $200 million to repurchase Cadence shares.

Speaker #1: 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.

Speaker #1: For our updated outlook for 2026, we expect revenue in the range of $6 billion and $125 million. To $6 billion and $225 million. Gap operating margin in the range of $27.5 to $28.5%.

Speaker #1: 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.

John Wall: 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. 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 billion to $1.595 billion. GAAP operating margin in the range of 28.5% to 29.5%. Non-GAAP operating margin in the range of 44.5% to 45.5%.

Speaker #1: 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.

Speaker #1: With that in mind, for Q2, we expect revenue in the range of $1 billion and $555 million, to $1 billion and $595 million. Gap operating margin in the range of $28.5 to $29.5%.

Speaker #1: 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.

John Wall: GAAP EPS in the range of $1.07 to $1.13. Non-GAAP EPS in the range of $2.02 to $2.08. 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 in 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. With that, operator, we will now take questions.

Speaker #1: 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.

Speaker #1: 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.

Speaker #1: And with that, operator, we will now take questions.

Speaker #2: 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.

Operator: 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&A roster. Our first question comes from the line of Charles Shi with Needham. Your line is open.

Speaker #2: 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&A roster.

Speaker #2: And our first question comes from the line of Charles. She with Needham. Your line is open.

Speaker #3: Hi, yeah. Good afternoon. Thanks for taking my question. Anirudh, I think I have a pretty high-level question, but this is probably top of mind for a lot of investors.

Charles Shi: Hi. Good afternoon. Thanks for taking my question. Anirudh, I think I have a pretty high-level question, but this is probably top of mind for a lot of investors. We obviously learned agentic AI is probably good for EDA, good for license consumption, et cetera. But we're still hearing some concerns around AI's ability to actually write the software. There are some doubts around whether AI can actually write better EDA-based tools like based tool. I mean, Virtuoso, those kind of tools. Obviously, there are always many EDA startups happening at the same time. The question is AI's ability to write software worries you about the dispensability of the EDA-based tool business?

Speaker #3: We obviously learned Agendic AI is probably good for EDA, good for licensed consumption, etc. But we're still hearing some concerns around AI's ability to actually write the software, and there are some doubts around whether AI can actually write better, EDA-based tools like, based to, I mean, virtual—so in a verse, those kind of tools.

Speaker #3: So, obviously, there are always many EDA startups happening at the same time. And so the question is, does software worry you about the defensibility of the EDA-based tool business?

Charles Shi: Obviously, once again, we understand that agentic AI is good for consumption of the base tool business, but want to get your thoughts. Thank you.

Speaker #3: Obviously, once again, we understand that Agendic AI is good for consumption of the base tool business, but we want to get your thoughts. Thank you.

Charles Shi: Obviously, once again, we understand that agentic AI is good for consumption of the base tool business, but want to get your thoughts. Thank you.

Speaker #1: 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.

Anirudh Devgan: Yeah. Hi, Charles. Thanks for the question. I mean, there are multiple parts to this. Of course, I'm super excited about agentic AI applied to chip design and EDA. Your question is more specific to the base tool and whether AI can write those base tools. First of all, you know, I'm very confident in our position in the base tool and our competitive advantage. Okay. Just to remind everyone, I mean, we have 15,000 people now in Cadence, about 10,000 of them are in R&D. You know, we have more than half of them have advanced degrees. I think more than 1,000 of them have PhDs from the top universities. We will anyway deploy AI internally like we are to, you know, write our software better.

Speaker #1: 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 I'm very confident in our position in the base tool and our competitive advantage.

Speaker #1: Okay. And just to remind everyone, I mean, we have about 15,000 people now in CADENCE. About 10,000 are in R&D. We have more than half of them have advanced degrees.

Speaker #1: I think more than 1,000 of them have PhDs from the top universities. So we will, anyway, deploy AI internally, like we are, to write our software better.

Speaker #1: 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.

John Wall: I'm not worried that, you know, some other party will be able to write any better base tools, so. Our competitor of the base tool is anyway best in class.

Anirudh Devgan: I'm not worried that, you know, some other party will be able to write any better base tools, so. Our competitor of the base tool is anyway best in class.

Speaker #1: And I don't see any reason that will change going forward. Okay. Now, what I'm super excited that we launched in CADENCE Live is the Agendic part.

Anirudh Devgan: I don't see any reason that will change going forward. Okay. Now, what I'm super excited that we launched in CadenceLIVE is the agentic part, you know, and the interplay of the agentic tools with the base tools, you know. The AI orchestration combined with physically accurate base tool. That creates new opportunities for us, you know, both in terms of TAM expansion, because what agentic AI allows us is to sell products in spaces we didn't have products before, you know, like RTL generation, you know, verification plan generation. Those products, I think, will be consumed more on a subscription plus consumption model. This is entirely a new category for Cadence. Then in turn, like you said, agentic AI will drive more of our base tools.

Speaker #1: And the interplay of the agendic tools with the base tools, the AI orchestration combined with physically accurate base tools—and that creates new opportunities for us.

Speaker #1: Both in terms of TAM expansion, because what Agendic AI allows us is to sell products in spaces we didn't have products before—like RTL generation and verification plan generation.

Speaker #1: And those products I think will be consumed more on a subscription plus consumption model. So this is entirely a new category for CADENCE. And then in turn, like you said, Agendic AI will drive more of our base tools so I feel pretty good about this kind of three-layer framework we have talked about.

Anirudh Devgan: I feel pretty good about this kind of three-layer framework we have talked about, and confident going forward.

Speaker #1: And confident going forward.

Operator: Our next question comes from the line of Jason Celino with KeyBanc Capital Markets. Your line is open.

Speaker #2: And our next question comes from the line of Jason Salino with KeyBanc Capital Markets. Your line is open.

Operator: Our next question comes from the line of Jason Celino with KeyBanc Capital Markets. Your line is open.

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

Speaker #3: Great. Thank you so much. Maybe just to clarifying question. So I noticed that the operating margin guide is coming down by a little bit.

Speaker #3: Curious if what are the main drivers of that, John? And I know we're layering in kind of the hexagon acquisition, but on an absolute basis, it's relatively small layering in that OPEX.

Speaker #3: So maybe you can just help us understand the guide on the margin. Thank you.

Speaker #1: 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.

John Wall: Yeah, sure, Jason. Thanks for the question. Yeah. What you're seeing there is primarily the impact of including the Hexagon Design & Engineering business in the current outlook. The strategic opportunity there is very large, but the 2026 P&L reflects the timing of integration that we announced in the press release when we closed the deal that we expect $160 million of revenue this year. That's in the guide now. We expect it to be dilutive to the tune of about $0.28. The margin impact on the $160 million is kind of in the 5% to 10% range. The dilution comes from 'cause we paid 30% of the acquisition price in shares and 70% in cash.

Speaker #1: The strategic opportunity there is very large, but the 2026 P&L reflects the timing of integration that we announced in the press release when we closed the deal, that we expect $160 million of revenue this year.

Speaker #1: That's in the guide now. We expect it to be diluted to the tune of about 28 cents. The margin impact on the 160 million is kind of in the 5 to 10 percent range.

Speaker #1: But the dilution comes from because we paid 30% of the acquisition price in shares and 70% in cash. So the interest component, or the lost interest income on the cash.

John Wall: The lost interest income on the cash causes a lot of the dilution impact in the short term. We'd expect it to be accretive in 2027. I think the way to think about it is financially, 2026 is an integration year. The guide includes the acquired cost base, the financing impact, the acquisition-related integration costs, and kind of near-term dilution. That's why revenue moves higher while EPS and operating margin are lower than the February guide. It's $160 million. I think in Q1, the impact was slightly less on the EPS that we had about $20 million of revenue from Q1 from Hexagon.

Speaker #1: It causes a lot of the dilution impact in the short term. We'd expect it to be accretive in 2027. Yeah. So I think the way to think about it is, financially, 2026 is an integration year.

Speaker #1: And the guide includes the 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 EPS and operating margin are lower than the February guys.

Speaker #1: So yeah. So 160 million. And I think in Q1, the impact was slightly less on the EPS that we had about 20 million of revenue from Q1 from Hexagon.

John Wall: Only about $0.01 kind of dilution impact. EPS would have been, like, $0.01 higher if we didn't have Hexagon.

Speaker #1: So only about 1 cent kind of dilution impact. So EPS would have been like 1 cent higher if we didn't have Hexagon.

John Wall: Only about $0.01 kind of dilution impact. EPS would have been, like, $0.01 higher if we didn't have Hexagon.

Operator: Our next question comes from the line of Vivek Arya with Bank of America Securities. Your line is open.

Speaker #2: And our next question comes from the line of Vivek Arya with Bank of America Securities. Your line is open.

Operator: Our next question comes from the line of Vivek Arya with Bank of America Securities. Your line is open.

Speaker #3: Thanks for taking my question, Anirudh. In the last year, all we have been hearing nonstop are different news about chip shortages, and the growing kind of price of chips, and just the pricing power that many of your customers have.

Vivek Arya: Thanks for taking my question. You know, Anirudh, in the last year, all we have been hearing nonstop are, you know, different news about chip shortages, and growing kind of price of chips and just, you know, the pricing power that many of your customers have. My question is, what effect do shortages and the fact your customers have more pricing power, what effect does that have on their engagement with Cadence? You know, does it restrict chip starts? Does it shift them towards higher ASP products? Just what impact do semiconductor shortages have on your growth and engagement trajectory? What has changed, and what are you observing in your customer behavior? Thank you.

Speaker #3: And my question is, what effect do shortages and the fact your customers have more pricing power—what effect does that have on their engagement with Cadence?

Speaker #3: Does it restrict chip starts? Does it shift them towards higher ASP products? Just what impact do semiconductor shortages have on your growth and engagement trajectory?

Speaker #3: What has changed and what are you observing in your customer behavior? Thank you.

Speaker #4: Thank you.

Speaker #1: 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.

Anirudh Devgan: Yeah, thanks, Vivek, for the question. I would say a few things. First of all, I mean, the environment is pretty healthy, you know, both for the system companies and semi companies. That's always good. You know, 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 mixed companies are doing well. We, of course, wanna see our customers doing well, and that creates a positive environment for engaging, especially with these new solutions we have. That's actually a pretty market improvement over the last 3 to 6 months. That's number one. Number two, the shortages, you know, it doesn't directly...

Speaker #1: So that's always good. Like you know, I mean, some of the hyperscalers and AI semi-companies were already doing well last year. But now the memory companies are doing well.

Speaker #1: Even analog big companies are doing well. So of course, we want to see our customers doing well. And that creates a positive environment for engaging, especially with these new solutions we have.

Speaker #1: So that's actually a pretty marked improvement over the last three to six months. So that's number one. Number two, the shortages—it doesn't directly, I mean, the customers are still committed to long-term R&D roadmaps.

Anirudh Devgan: I mean, the customer is still committed to long-term R&D roadmaps, and sometimes they may, like, I've seen in a 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. That would directly lead to more design activity for us. 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.

Speaker #1: And sometimes they may do—like I've seen in a few cases—the customers, for example, may use multiple foundries or nodes to make sure there is capacity at a particular node or foundry.

Speaker #1: So that would directly lead to more design activity for us. So in general, if the customer is healthy because their revenue is going up, they will do not only more in the current designs to accelerate them, but also may start new designs.

Speaker #1: I think that's the second thing, I would say. And the third thing, which is more exciting for us, is as we have these agentic solutions, it can give more productivity for our customers.

Anirudh Devgan: Third thing, which is more exciting for us, is, you know, as we have these agentic solutions, it can, you know, give more productivity for our customers, and we can deliver more value ourselves, and the more value we deliver, you know, the more opportunity we have to capture part of that value. The customers are very open to those discussions, you know, as there is more automation. We are actually, like I mentioned, there's a lot of engagement with ChipStack and also the new, you know, AgentStack, you know, InnoStack, ViraStack. There is no pushback at all. If we can deliver productivity, the customer is more than willing to engage. That's, I would say, Vivek, are the, at least the three broad areas I see in the current environment. Yeah.

Speaker #1: 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.

Speaker #1: As there is more automation, so we are actually, like I mentioned, there's a lot of engagement with ChipStack and also the new AgentStack and NoStack VeraStack.

Speaker #1: 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 #1: Yeah.

Speaker #2: And our next question comes from the line of Jim Schneider with Goldman Sachs. Your line is open.

Operator: Our next question comes from the line of James Schneider with Goldman Sachs. Your line is open.

Speaker #5: Good afternoon. Thanks for taking my question. I was wondering if you could maybe unpack your commentary on the agentic solutions, specifically around your indication they would drive increased consumption for base tools.

James Schneider: Good afternoon. Thanks for taking my question. I was wondering if you could maybe unpack your commentary on the agentic solutions, specifically around your indication they would drive increased consumption for base tools. Can you maybe talk a little bit about the pricing for those tools, how the agentic solutions are being priced specifically, and then on net, if you could frame for us maybe how you might be able to capture more revenue value overall on net between agentic and conventional licenses. Thank you.

Jim Schneider: Good afternoon. Thanks for taking my question. I was wondering if you could maybe unpack your commentary on the agentic solutions, specifically around your indication they would drive increased consumption for base tools. Can you maybe talk a little bit about the pricing for those tools, how the agentic solutions are being priced specifically, and then on net, if you could frame for us maybe how you might be able to capture more revenue value overall on net between agentic and conventional licenses. Thank you.

Speaker #5: Can you maybe talk a little bit about the pricing for those tools? How the agentic solutions are being priced specifically? And then on net, if you could frame for us maybe how you might be able to capture more revenue value overall on net between agentic and conventional licenses.

Speaker #5: Thank you.

Speaker #1: Yeah. Thanks for the question. So I think the opportunity is significant, I believe, and especially with agentic because what this and this happened over the last, let's say, 6 to 12 months, in my opinion, and more so in 6 months, is not only the agentic tools have evolved, but agentic tools are able to we can embed skills in them so they can do a lot more automation.

Anirudh Devgan: Yeah, thanks for the question. 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, 6 to 12 months, in my opinion, and more so in 6 months, is not only the agentic tools have evolved, but agentic tools are able to we can embed skills in them, so they can do a lot more automation. You know, for example, we launched you know, AgentStack, 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. What does that mean in terms of pricing or how these things are consumed, so consumed? First of all, like I said, this kind of automation was not possible before.

Speaker #1: For example, we launched VeraStack, 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.

Speaker #1: 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.

Speaker #1: So all this work used to be done by the customers themselves, right? 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 an unrealizable headcount growth because they can't hire 2X more engineers.

Anirudh Devgan: All this work used to be done by the customers themselves, right? 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. Anyway, it's like unrealizable headcount growth because they can't hire 2x more engineers every time. 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, you know, which is more like this was manually done by customers, you know, like doing analog design or doing, you know, RTL. That will be priced as a subscription plus consumption model. You know, very similar to other kind of leading AI tools. That's a completely new category for Cadence.

Speaker #1: 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 a customer.

Speaker #1: Like doing analog design or doing RTL. So that will be priced as a subscription plus consumption model, very similar to other leading AI tools.

Speaker #1: 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.

Anirudh Devgan: That will kind of bend the headcount curve for our customers, but the expected headcount curve was never realizable anyway. This is the history of automation, as you know, in EDA. You know, we always need to do that. This way this time, we can do that with the agentic kind of AI flow. Then once the agent runs, you know, like when a user designs a chip, and this is pretty common, right? Like let's say that chip has 100 blocks just to keep it simple, and there are 100 engineers. You know, one engineer is running one block. One engineer will run like one or two experiments, you know, he or she to see, you know, which settings or which design is better.

Speaker #1: So this is the history of automation as you know in EDA. We always need to do that. But this time, we can do that with the agentic kind of AI flow.

Speaker #1: And then once the agent runs, like when a user designs a chip—and this is pretty common, right? Like, let's say their chip has 100 blocks.

Speaker #1: And just to keep it simple, there are 100 engineers. One engineer is running one block, so one engineer will run like one or two experiments—he or she—to see which settings or which design is better.

Speaker #1: But when the agent runs those blocks, they may try 10 or 100 variations of those things. And anyway, AI does a lot more exploration than a human would do.

Anirudh Devgan: When the agent runs those blocks, they may try 10 or 100 variations of those things. Anyway, AI does a lot more exploration than a human would do. Not only agent can give more productivity, it by nature runs more of the base tools. That's why if you look at our usage of base tool, it's going up pretty significantly in this kind of environment. This is the 2 ways. In those environments are the traditional business model, but in the base tools, there'll be more demand for it. Then the new business model, which is more, you know, automating what was manual with agentic flows.

Speaker #1: So not only can agents give more productivity, but by nature, they run more of the base tools. So that's why, if you look at our usage of base tools, it's going up pretty significantly in this kind of environment.

Speaker #1: 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.

Speaker #1: And then the new business model, which is more automating what was manual with agentic flows. Yeah.

John Wall: Yeah. I would just add, Jim, that, you know, what we saw from Q1 was, I mean, the overall pricing environment has improved. Pricing obviously remains value-based with us. We provide tremendous value to our customers, especially with our agentic flow. We stand to benefit from our customers' success in that area. That 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 #3: Yeah. And I would just add, Jim, that what we saw from Q1 was—I mean, the overall pricing environment has improved. Pricing, obviously, remains value-based with us.

Speaker #3: We provide tremendous value to our customers, especially with our agentic flow. 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.

Speaker #3: And likely to accelerate over time.

Speaker #2: And our next question comes from the line of CT Panigrahi with Mizuho, your line is open.

Operator: Our next question comes from the line of Siti Panigrahi with Mizuho. Your line is open.

Speaker #1: It was great. Thank you. I want to switch to the IP business. Anirudh, you talked about IP entering now a third year of strong growth.

Siti Panigrahi: Great. Thank you. I want to switch to the IP business. Anirudh, you talked about IP, entering now third year of strong growth. Could you give an update like what you saw in Q1, and are those HBM, LP, DDR6, and all that remaining still the key drivers or, and the new foundry like Rapidus, Intel Foundry, are they contributing meaningfully to the IP demand yet? And, Jim, just to clarify also on your EPS guidance, you said $0.28 dilution, but you lowered only $0.20. Just want to clarify that your organic basis, you raised by $0.08 EPS. Thank you.

Speaker #1: Could you give an update like what you saw in Q1? And are HBM, LP, DDR6, and all that remaining still the key drivers?

Speaker #1: Or in the newer foundries like Rapidus and Intel Foundry, are they contributing meaningfully to the IP demand yet? And Jim, just to clarify also on your EPS guidance—you said $0.28 dilution, but you lowered only $0.20. I just want to clarify: on an organic basis, you raised by $0.08 EPS.

Speaker #1: Thank you.

John Wall: I'll take the last part first. Yes, we did. We raised by $0.08.

Speaker #3: I'll take the last part first. Yes, yes, we did. We raised by 8 cents.

John Wall: I'll take the last part first. Yes, we did. We raised by $0.08.

Speaker #1: And it is a great start to the year, 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.

Anirudh Devgan: It is a great start to the year, okay? Not just in IP, across the board. 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. Two months later, I think this is one of the strongest raises we have had. All the businesses are doing well, and especially IP is off to a great start, okay? I think it will do well, going forward from what I think I see. There are at least three big reasons in my mind for IP growth. Like I said, it's the third year now, so we don't like to talk about things too early.

Speaker #1: 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.

Speaker #1: And especially, IP is off to a great start, okay? And I think it will do well going forward from what I think I see.

Speaker #1: 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.

Anirudh Devgan: After three years of strong growth, I think that is a good trend, you know. The first thing is our IP quality and performance is just better. You know, we have a new team, you know, the performance, you know, because these things are standard-based IPs, right? Like DDR or PCIe. The most promising thing to me is because the strength of our R&D team, our PPA is better, and that is leading to a lot of competitive wins at pretty significant major customers. I highlighted some of them in CadenceLIVE. These are like really big kind of marquee names. That gives me strength that the team is operating well.

Speaker #1: So the first thing is our IP quality and performance is just better. We have a new team. Just the performance, just because these things are standard-based IPs, right?

Speaker #1: Like DDR or PCIe. So the spec is same. But if our power area is better, then the competitor or what the customer can do, then they will buy our IP.

Speaker #1: So the most promising thing to me is, because of the strength of our R&D team, our PPA is better. And that is leading to a lot of competitive wins at pretty significant major customers.

Speaker #1: 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.

Anirudh Devgan: That's number one. Number two, our portfolio is expanding, you know, like we have highlighted, with like HBM and some of it is organic, some of it is acquired, like HBM we acquired from Rambus and then we improved it. UCIE, which is a critical chip-to-chip technology, was all developed organically. Okay. The second reason is that our portfolio is expanding. The third reason is these new foundries, okay? 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. Now there are at least three other major foundries, as you know, Samsung, Intel, and Rapidus at advanced nodes, and then GlobalFoundries and others at, you know, mainstream nodes. The amount of, you know, design activity with AI and number of increasing foundries requires more IP.

Speaker #1: So that's number one. Number two, our portfolio is expanding, like we have highlighted, with HBM. And some of it is organic, some of it is acquired.

Speaker #1: Like HBM, which we acquired from Rambus, and then we improved it. But UCIe, which is a critical chip-to-chip technology, was all developed organically, okay? So the second reason is that our portfolio is expanding.

Speaker #1: 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.

Speaker #1: 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.

Speaker #1: So the amount of design activity with AI, and the number of increasing foundries, requires more IP. So that's why I'm actually pleased to note today in the prepared remarks that we had a pretty significant IP deal, one of the largest ones, at a leading global foundry, okay?

Anirudh Devgan: that's why I'm actually pleased to note today, like in the prepared remarks, that we had a pretty significant IP deal, one of the largest ones at a leading global foundry. Okay. And just to clarify, you know, that is not Intel. Okay? We are actually pleased with our discussions with Intel, you know, with Libo 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, you know, because availability of IP and EDA solutions as 14A is critical as they go talk to their customers. We are making very good progress with Intel, and we'll have, you know, soon we'll have more to say on our engagement with Intel.

Speaker #1: And just to clarify, that is not Intel, okay? We have actually pleased with our discussions with Intel. With Libu and team. On 18A and especially on 14A.

Speaker #1: I think Intel realizes they need to invest more in 14A. And this time, be more ready because availability of IP and EDA solutions at 14A is critical as they go talk to their customers.

Speaker #1: So, we are making very good progress with Intel. And 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.

Anirudh Devgan: I'm also pleased with this engagement with the other global foundry. Overall, you know, IP growth seems robust, and I'm very pleased where we are. We're already, we're always very strong in EDA, but historically, last few years, you know, we have not done as well in IP. Right now, I think we are very well positioned and also well positioned in SDA.

Speaker #1: So overall, 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, we have not done as well in IP.

Speaker #1: But right now, I think we are very well positioned, and also well positioned in SDA.

Operator: Our next question comes from the line of Joe Quatrochi with Wells Fargo. Your line is open.

Speaker #2: Our next question comes from the line of Joe Quatracchi with Wells Fargo. Your line is open.

Joe Quatrochi: Yeah, thanks for taking the question. Maybe just to kind of focus 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&D expense, and clearly we're seeing an acceleration of R&D expense across a number of different companies. How should we think about, you know, EDA's contribution to that or percent of that? Where could that go given the value maybe you're providing from AI? Because we're also seeing, right, memory costs are increasing, things like that also need to flow through that R&D line.

Speaker #4: Yeah. Thanks for taking the question. Maybe just to kind of focus on the discussion earlier on EDA. I mean, I guess when you take a step back and you think about EDA's share of R&D expense, and clearly we're seeing an acceleration of R&D expense across a number of different companies.

Speaker #4: How should we think about EDA's contribution to that, or the percent of that? And where could that go, given the value, maybe, you're providing from AI?

Speaker #4: Because we're also seeing, right, memory costs are increasing, things like that, that also need to flow through that R&D line.

Anirudh Devgan: Yeah, good question. We have to, you know, observe it closely, right? You know, as we rather like print things than kind of predict what will happen because it's better to show than to predict. You know, as you know, historically, we have said, you know, EDA used to be 7% of R&D, and now it's more like 11% of R&D, so it has gone up. R&D spend itself will go up significantly. I think there is a real potential, especially with agentic AI, for that 11% to go up. All the, you know, big CEOs I talk to, they're more, not only willing, they want to see that happen. You know, 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.

Speaker #1: Yeah, good question. And we have to observe it closely, right? You know, as we rather print things than kind of predict what will happen.

Speaker #1: Because it's better to show than to, but as you know, historically, we have said EDA used to be 7% of R&D, and now it's more like 11% of R&D.

Speaker #1: So it has gone up. And R&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.

Speaker #1: And all the big CEOs I talked to, they're not only willing, they want to see that happen. They want to invest in more automation and compute to make it happen.

Speaker #1: So I'm pretty sure right now, I think it will go up. Now, how much it will go up, we will see, right? But I think there is a meaningful opportunity for automation to be a higher percentage of R&D.

Anirudh Devgan: Now, how much it'll go up, we will see, right? I think there's a meaningful opportunity for automation to be a higher percentage of R&D, plus R&D itself to go up.

Speaker #1: Plus R&D itself to go up.

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

Speaker #2: Our next question comes from the line of Ruben Roy with Stifel. Your line is open.

Ruben Roy: Yeah. Thank you. John, I want to go back to the operating margin discussion. It's great to see that you guys are targeting Rule of 60 by the end of the year here. Just thinking about that though, it's driven on revenue acceleration. Obviously, we've got the Hexagon integration costs here. But how are you thinking about the operating model relative to operating margin, you know, 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 a 43% to 45%, you know, range how we should be thinking about the operating margins or? And I ask that because obviously you're investing in agentic AI and other, you know, sort of new product areas.

Speaker #3: Yeah, thank you. John, I want to go back to the operating margin discussions. It's great to see that you guys are targeting a rule of 60 by the end of the year here.

Speaker #3: Just thinking about that, though, it's driven on revenue acceleration. Obviously, we've got the Hexagon integration costs here. But how are you thinking about the operating model relative to operating margin as you get over $6 billion in revenue?

Speaker #3: Does the operating model look a lot different than it did at $5.3 billion? Is this sort of a 43 to 45 percent range how we should be thinking about the operating margins?

Speaker #3: Or, and I ask that because obviously you're investing in agentic 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 the operating margin structure at this revenue run rate longer term, as you integrate Hexagon.

Ruben Roy: Just wondering if you can give us a little bit of an idea of how you're thinking about the operating margin structure at this revenue run rate, you know, longer term as you integrate Hexagon. Thank you.

Speaker #3: Thank you.

John Wall: Yep. Sure, Ruben. Thanks for the question. Yeah, I think when we look at our, like, organic incremental margin is closer to 60% these days than 50%. You know, as we get our arms around these acquisitions, it typically takes us 12 to 18 months to improve the profitability up to kind of something close to our expectations at Cadence. I would liken the profile to the way Beta. In 2024 and 2025, you kinda had an operating margin profile where we had the dilutive impact of the Beta acquisition in 2024, but then, you know, margins improved dramatically in 2025 as we got the synergies and we got the benefits of making that more profitable.

Speaker #1: Yeah, sure, Ruben. Thanks for the question. Yeah, I think when we look at our organic incremental margin, it's closer to 60% these days than 50%.

Speaker #1: And as we get our arms around these acquisitions, it typically takes us 12 to 18 months to improve the profitability up to kind of something close to our expectations that CADENCE that 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.

Speaker #1: But then 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.

John Wall: I would expect a similar pattern for 2026 and 2027 when it comes to Hexagon. We have a slight headwind in the short term, but there's plenty of opportunities to improve the profitability there. Also with the benefits that we're seeing in terms of customer engagement, accelerating on the agentic AI front, I think there's even more opportunities to stretch that incremental operating margin going forward.

Speaker #1: We have a slight headwind in the short term, but there are 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 agentic AI front, I think there's even more opportunities to stretch that incremental operating margin going forward.

Operator: Our next question comes from the line of Harlan Sur with J.P. Morgan. Your line is open.

Speaker #2: Our next question comes from the line of Harlan Sir with JP Morgan. Your line is open.

Harlan Sur: Yeah, good afternoon. Thanks for taking my question. If I take your Q2 guidance and look at your implied H2 guidance, the average quarterly revenue run rate in the H2 is actually both slightly below the Q2 level. Is there some lumpiness in the Hexagon business in the H2, maybe moving customers to multi-year license agreements? Or is it due to some lumpiness in the core business, maybe a more H1-weighted hardware or IP shipment profile?

Speaker #5: Yeah, good afternoon. Thanks for taking my question. If I take your Q2 guidance and look at your implied second-half guidance, the average quarterly revenue run rate in the second half is actually both slightly below the Q2 level.

Speaker #5: 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, maybe a more first-half weighted hardware?

Speaker #5: Or IP shipment profile?

John Wall: Yeah, thanks for the question, Harlan. Yes, sure. Look, H1 is very strong and H2 I describe as containing appropriate prudence. Your comment on Hexagon's D&E business is correct. They are more kind of H1-weighted, in terms of their profile. When I looked at last year's revenue for Hexagon, I think Q3 and Q4 were their worst two quarters of the year. They tend to have a lot of early year kind of dated contracts. But overall, I think H2. I mean, Hexagon doesn't impact H1, H2 that much.

Speaker #1: Yeah, thanks for the question, Harlan. Yeah, surely. Look, the first half is very strong, and the second half I describe as containing appropriate prudence.

Speaker #1: Your comment on Hexagon's D&E business is correct. They are more kind of first-half weighted. In terms of their profile, when I looked at last year's revenue for Hexagon, I think Q3 and Q4 were their worst two quarters of the year.

Speaker #1: They tend to have a lot of early-year kind of dated contracts. But overall, I think the second half really I mean, it doesn't the hexagon doesn't impact the first-half, second-half that much.

John Wall: It's really, I think—as Andrew said—the Q1 guide represents one of the highest raises we've had at this time of the year, and we normally like to wait until, you know, we have two quarters under our belt to raise the guides. We couldn't help but raise the guide given the strength of Q1 bookings and the strength we saw across the board. We just wanted to wait until July to update the H2.

Speaker #1: It's really, I think, we had—such as Anirudh said—Q1 guide represents one of the highest raises we've had at this time of the year.

Speaker #1: And we normally like to wait until we have two quarters under our belt to raise the guides. We couldn't help but raise the guide given the strength of Q1 bookings and the strength we saw across the board.

Speaker #1: So, we just wanted to wait until July to update the second half.

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

Speaker #2: Our next question comes from the line of Lee Simpson with Morgan Stanley. Your line is open.

Lee Simpson: Great. Thanks for squeezing me in. I just wanted to ask about physical AI. I mean, you've made some pretty good acquisitions. You've now announced collaborations, especially with NVIDIA. I'm just trying to get a sense for the momentum here and what really is still the early years in this breakout. 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 gonna really lead to an outsized value capture for Cadence. When do we actually see this in the numbers as well? Thanks.

Speaker #5: Great, thanks for squeezing me in. I just wanted to ask about physical AI. I mean, you've made some pretty good acquisitions. You've now announced collaborations, especially with NVIDIA.

Speaker #5: 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, the takeup of your emulation tools, especially as it relates to closing the SIM to real gap and robotics and probably even self-driving chips as well.

Speaker #5: Whether or not that's going to really lead to an outsized value capture for Cadence. And when—when do we actually see this in the numbers as well?

Speaker #5: Thanks.

Anirudh Devgan: Yeah, thanks for the question, Lee. I mean, you know, like I talked about it forever now that we look at this thing as a three-layer cake, right? There are multiple slices of the cake, and the first slice was data center AI or infrastructure AI, and the second big slice is physical AI. Of course, I've said this for five years now, but I believe physical AI will be bigger than data center AI by a long shot, because you're talking about like trillions of dollars of product opportunity. It will reconfirm the data center layer with the data center slice. Because to deploy, for example, the AI model in the car, you need to train it on the data center anyway. I think it will even help the data center slice.

Speaker #1: Yeah, thanks for the question, Lee. So, I mean, I've talked about it forever now that we look at this thing as a three-layer cake, right?

Speaker #1: And there are multiple slices of the cake. The first slice was data center AI, or infrastructure AI. And the second big slice is physical AI.

Speaker #1: And of course, I've said this for five years now, but I believe physical AI will be bigger than data center AI by a long shot, because you're talking about trillions of dollars of product opportunity.

Speaker #1: And it will reconfirm the data center layer. Data center slice because to deploy, for example, an AI model in the car, you need to train it on the data center anyway.

Speaker #1: 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 it.

Anirudh Devgan: Now for our portion, yes, we made this acquisition we are super excited about, and we have this now training flow for world models and also more complete simulation environment. What is exciting about Hexagon is with combination of our previous technologies like Millennium and Cascade and Beta, we do have finally a complete solution for physical AI in the middle layer, kind of principal simulation and optimization layer. Then that can be used to do these world models, which will be different in the top layer. Another thing I want to emphasize, apart from the SDA and the AI part, that physical AI itself will drive a lot of silicon design.

Speaker #1: And we have this now training flow for word models. And also a more complete simulation environment. So what is exciting about Hexagon is, with the combination of our previous technologies like Millennium and Cascade and Beta, we do have, finally, a complete solution for physical AI in the middle layer—kind of principle simulation and optimization layer.

Speaker #1: And then that can be used to do these word models, which will be different in the top layer. But the other thing I want to emphasize, apart from the SDNA and the AI part, is that physical AI itself will drive a lot of silicon design.

Anirudh Devgan: It is also good for EDA and IP, and this is, we are 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. Physical AI not only is good for SDA and AI, it is also really good for silicon. It also is the sweet spot of Cadence, because Cadence always had both analog and digital in our solutions. That's why we are always good with all the major semiconductor companies for automotive and now with all the system and OEM companies for automotive. As that translates to drone and robots, it'll also turbocharge the silicon business. That's why I have always been excited about physical AI, not just for the AI and SDA part, but also for EDA and IP.

Speaker #1: So it is also good for EDA, NIP. And this is—you're starting to see that, of course—companies like Tesla mentioning that they don't have enough silicon because of physical AI.

Speaker #1: So, physical AI not only is good for SDNA AI, it is also really good for silicon. And it also is the sweet spot of Cadence.

Speaker #1: Because Cadence always had both analog and digital solutions, 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.

Speaker #1: And as that translates to drones and robots, it will also turbocharge the silicon business. That's why I have always been excited about physical AI.

Speaker #1: Not just for the AI and SDA part, but also for EDA and IP.

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

Speaker #2: Our next question comes from the line of John Marco Conti with Deutsche Bank. Your line is open.

Gianmarco Conti: Afternoon. Yeah, thanks for squeezing me in too. Perhaps on hardware, another strong quarter of course, but as we think about the next refresh cycle for Palladium and Protium, historically you've roughly been on a two-year cadence. Should we expect Z4 and X4 within the next 12 to 18 months? Or is the bar to upgrade higher now given how recently customers absorbed the first generation? 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 #6: Afternoon. Yeah, thanks for squeezing me in, too. Perhaps on hardware, another strong force, of course. But as we think about the next refresh cycle for Palladium and Proteon—historically, you've roughly been on a two-year cadence.

Speaker #6: Should we expect Z4, X4 within the next 12 to 18 months? Whereas the bars upgrade higher. Now, given how recently customers absorbed the first generation.

Speaker #6: 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?

Speaker #6: Thank you.

Anirudh Devgan: Yeah, absolutely. Great question. First of all, you know, like I said, we have a very, you know, most of our headcount is engineering, right? Whether it's R&D or customer support. We always want to use our own product in both our hardware groups, which is a significant design team. You know, we do both software, hardware, and all the system design in Palladium and Protium. Also, just to remind you, in our IP team, you know. It's a great. You know, we'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 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.

Speaker #1: Yeah, absolutely. Great question. So, first of all, like I said, most of our headcount is engineering, right? Whether it's R&D or customer support.

Speaker #1: So we always want to use our own product in both our hardware groups, which is the significant design team. We do both software, hardware, and all the system design in Palladium.

Speaker #1: And Proteon. And also, just to remind you, in our IP team, they're working very well together—our IP team and EDA teams.

Speaker #1: Because IP, we have so much demand, and instead of, again, increasing headcount—we're always sensitive about how much headcount we'll increase. And we are increasing headcount in all areas, including IP.

Speaker #1: But we can make them a lot more productive with agentic AI. Now, on the hardware part—yeah, I'm very pleased. I mean, it's a remarkable start to the year.

Anirudh Devgan: Now on the hardware part, yeah, we have. I'm very pleased. I mean, it's a remarkable start to the year. 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. Then Protium also is doing now, in which we use the FPGA solution. Now just to be clear, we always design next generation systems, you know. 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. You know, FPGA companies will also do next generation FPGA designs, but because we are our own chip, you know, we do our own design, it will be much faster than FPGA.

Speaker #1: 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.

Speaker #1: And then Proteon 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.

Speaker #1: FPGA companies will also do next-generation FPGA designs. But because we are our own chip, we do our own design, it will be much faster than FPGA.

Anirudh Devgan: What that means is the lead of Palladium over FPGA systems will only continue to increase as we introduce new products, okay? I'm not gonna get into, like, when we're gonna introduce new products because the current products are doing amazingly well. Of course, we are designing, you know, Z4 and Z5. What you have to remember is the current Z3 system has the capability to design, you know, 1 trillion transistor systems, okay? Right now the biggest systems in the world are 100 to 200 billion transistor. We have a lot of leeway. You know, the industry is supposed to reach 1 trillion transistor by 2030. One thing I'll assure you is we'll have a Z4 system before 2030. There is no issue of whether Z3 can handle the capacity and requirements.

Speaker #1: So what that means is the lead of Palladium over FPGA systems will only continue to increase as we introduce new products. Okay. But I'm not going to get into when we're going to introduce new products because the current products are doing amazingly well.

Speaker #1: Of course, we are designing Z4 and Z5. But what you have to remember is the current Z3 system has the capability to design 1 trillion transistor systems.

Speaker #1: Okay. And right now, the biggest 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.

Speaker #1: 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.

Anirudh Devgan: We're just happy to work with our customers. At the same time, we want to assure our investors and customers we have a very, very good roadmap on hardware systems.

Speaker #1: So we're just happy to work with our customers. At the same time, we want to assure our investors and customers we have a very, very good roadmap on hardware systems.

Operator: Our next question comes from the line of Jay Vleeschhouwer with Griffin Securities. Your line is open.

Speaker #2: Our next question comes from the line of Jay Fleehour with Griffin Securities. Your line is open.

Jay Vleeschhouwer: Thank you. Good evening. Anirudh, now that you've completed Hexagon MSC acquisition, it would appear that you are the fourth largest non-EDA simulation company. Let's call it industrial simulation with multiphysics. Your share is perhaps one-tenth of that total market, again, aside from EDA simulation. The question is, now that you've assembled all these pieces, invested over $5 billion over the last five or six years, could you speak in some detail about what your principal technical and/or go-to-market objectives or executables are going to be for the next year or so? Synopsys talked about what they're doing with Ansys. Perhaps you could do the same for your pieces. It also seems you're becoming a little bit more vertically integrated in go-to-market with the acquisition of a longtime channel partner.

Speaker #5: Thank you. Good evening. Anirudh, now that you've completed the Hexagon MSC acquisition, it would appear that you are the fourth largest non-EDA simulation company. Let's call it industrial simulation with multi-physics.

Speaker #5: Your share is perhaps one-tenth of that total market—again, aside from EDA simulation. So the question is, now that you've assembled all these pieces, invested over $5 billion over the last five or six years, can you speak in some detail about what your principal technical and/or go-to-market objectives or executables are going to be for the next year or so? Synopsys talked about what they're doing with Ansys.

Speaker #5: Perhaps you could do the same for your pieces. It also seems you're becoming a little bit more vertically integrated in go-to-market with the acquisition of a longtime channel partner.

Jay Vleeschhouwer: Maybe talk about some of those critical elements here to grow your revenues and share in that business.

Speaker #5: So maybe talk about some of those critical elements here to grow your revenues and share in that business.

Anirudh Devgan: Yes, Jay, that's a lot there, right? There's a lot there. 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. First of all, you know, we are satisfied with the scope of our SDA business now after this acquisition. I mean, this is rough numbers, so, you know, I think it will be roughly $1 billion of run rate. 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?

Speaker #1: Yes, Jay. That's a lot there, right? There's a lot there. So let me try to unpack some of it. And I'm sure we can talk more if I don't get to all the pieces there.

Speaker #1: But first of all, we are satisfied with the scope of our SDA business now after this acquisition. So, I mean, this is a rough number.

Speaker #1: So 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.

Speaker #1: I'm a fan of SDA for a while now. I don't know, maybe eight years now. But not all SDA is graded equal. Okay. To me, we want to do the part of SDA that is either growing well or is closely related to EDA.

Anirudh Devgan: To me, you know, we want to do the part of SDA that is either growing well or is closely related to EDA. The part of SDA that is closely related to EDA is of course 3D IC, okay? We have an available position in 3D IC, with Allegro being the leading packaging platform, and then we completed that with, you know, Clarity, Sigrity and Celsius, so all the thermal electromagnetics. I'm pretty happy with the 3D IC 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 with Hexagon is all this physical AI and, you know, for design of cars and robots.

Speaker #1: So the part of SDA that is closely related to EDA is, of course, 3DIC. Okay. So we have an inevitable position in 3DIC with Allegro being the leading packaging platform.

Speaker #1: And then we completed that with Clarity and Integrity and Celsius—so all the thermal, electromagnetics—so, and Integrity. So I'm pretty happy with the 3DIC portion, which is like the closest to chip design.

Speaker #1: 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.

Anirudh Devgan: That, with this acquisition, is complete, and we can do a much better integration of that part of SDA. There are multiple things happening there, okay? There are at least, you know, two, three key things. First thing is, we will integrate the whole solution. You know, this. You know, we, I know you asked me this before, you know, when will you integrate? 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 structural, we have multi-body dynamics, we have pre and post, okay? We have a lot of effort to make a full flow solution, integrate them, and you know, I kind of hinted at that at CadenceLIVE.

Speaker #1: So, with this acquisition complete, we can do a much better integration of the part of SDA. And there are multiple things happening there.

Speaker #1: Okay. There are at least two, three key things. So, first thing is we will integrate the whole solution. I know you asked me this before.

Speaker #1: 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.

Speaker #1: We have structural. We have multi-body dynamics. We have pre and post. Okay. So we have a lot of effort to make a full-flow solution, integrate them.

Speaker #1: 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 the agentic flow.

Anirudh Devgan: The other thing, the way to integrate these solutions, which is true for EDA, what will be true in this area is the agentic flow. You will see from us a agentic flow to do system design, and that part of the market has not seen that much. It's even worse automation than you know, chip design that had a lot of automation. 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, and especially in our history of improving the base solvers, you know, adding GPU acceleration, adding a you know, physics AI or AI surrogate models.

Speaker #1: So you will see from us an agentic flow to do system design. And that part of the market has not seen that much; it is even worse automation than chip design, which had a lot of automation.

Speaker #1: 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.

Speaker #1: Adding GPU acceleration, adding physics AI or AI surrogate models. So, for example, there's a potential for at least an order of magnitude improvement of performance with these new solvers.

Anirudh Devgan: For example, there is a potential for at least an order of magnitude improvement of performance of these new solvers. That's the second thing we'll do in terms of R&D. Third thing, you know, what I'm also pleased with Hexagon is we did get like a good go-to-market team. You know, that's one area we have not been as strong because we were most of the others was mostly organic. We did move some of our, you know, people into go-to-market. With Hexagon D&E business, we get a much stronger go-to-market team. Then, as we mentioned, we also acquired some resellers to strengthen go-to-market. Okay. At this point, I'm very confident of our R&D solution, and it will get improved by agentic solutions. It will get improved by, you know, speeding of the solvers.

Speaker #1: So that's the second thing we'll do in terms of R&D. And the third thing, what I'm also pleased with Hexagon is we did get a good go-to-market team.

Speaker #1: That's one area we have not been as strong because most of the others were mostly organic. And we did move some of our people into go-to-market.

Speaker #1: But with Hexagon, D&E business, we get a much stronger go-to-market team. And then, as we mentioned, we also acquired some resellers to strengthen go-to-market.

Speaker #1: Okay. At this point, I'm very confident in our R&D solution, and it will get improved by agentic solutions. It will get improved by speeding up the solvers.

Anirudh Devgan: We also need to invest in go-to-market, and Hexagon gives us a good start. You will see that too. These are the three kind of focus areas of improvement of SDA.

Speaker #1: But we also need to invest in 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.

Operator: Our next question comes from the line of Kelsey Chia with Citigroup. Your line is open.

Speaker #2: Our next question comes from the line of Kelsey Chia with Citigroup. Your line is open.

Kelsey Chia: Hi. Thank you and good afternoon. Anirudh, you mentioned that the agent stack helped address talent gaps for chip designers. It sounds like the agent stack adoption is just accelerating from here. Based on your conversation, is that the case, or are you seeing cases where customers prefer to build or use their own agentic stack versus adopting Cadence's? If so, is Cadence able to sort of charge for agent stack or the increased base licenses as an incremental add-on within an existing via contract, or is that monetization tied to renewals?

Speaker #6: Hi. Thank you, and good afternoon. Anirudh, you mentioned that the agent stack helped address talent gaps for chip designers. It sounds like the agent stack adoption is just accelerating from here.

Speaker #6: Based on your conversation, is that the case? Or are you seeing cases where customers prefer to build or use their own agentic stack versus adopting Cadence's?

Speaker #6: And if so, is Cadence able to sort of charge for agent stack or the increased base licenses as an incremental add-on within an existing CA contract?

Speaker #6: Or is that monetization tied to renewals?

Anirudh Devgan: Oh, yeah. Thank you. There's a lot of good questions there. Okay. I'll start, and John can add to that. 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, you know, we would have give a lot of flexibilities to our customers. You know, we had a TCL or a Python interface to our tools, and they would always have their own flows. I mean, this is natural for big customers. I mean, these are who's who of tech companies, so they always want to have some differentiation from one flow to the other. That will happen in the agent world itself.

Speaker #1: Oh, yeah. Thank you. There are a lot of good questions there. Okay, so I'll make sure I start, and John can add to that.

Speaker #1: 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.

Speaker #1: Even in our pre-agentic flow, we would have given a lot of flexibilities to our customers. We had a Tcl or a Python interface to our tools.

Speaker #1: And they would always have their own flows. I mean, this is natural for big customers. I mean, these are who's who of tech companies.

Speaker #1: So they always want to have some differentiation from one flow 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.

Anirudh Devgan: I think most of our customers are writing some of their own agents. 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 physical design, these are like super categories. 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, these API calls, which is not possible for customers to do. What has happened, as an example, as we showed InnoStack or ViraStack and ChipStack to our customers, they realized, "Oh, there's no point writing these kind of agents." Okay?

Speaker #1: 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 Physical Design—these are like super categories.

Speaker #1: 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.

Speaker #1: 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 VeraStack and ChipStack to our customers, they realized, "Oh, there's no point writing these kind of agents." Okay.

Anirudh Devgan: 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 base tools. Now, they will still write some agents to customize things which are specific to them, and we naturally welcome that. And an AgentStack allows the environment to, for the customer to write its own agent, but also the customer to write its own skills. You know? We want the customers to write their own skills in InnoStack, which may be specific for a part of design. This has always been our strategy to be more open to customer, kind of, customizing their own environment. Okay. I think the second question is on renewals versus new. I mean, it's a combination of that always. John, maybe you wanna comment on that.

Speaker #1: So they would rather use the super agents we have, because not only are we good in agentic flow, we are good in the coupling to the base tools.

Speaker #1: Now, they will still write some agents to customize things which are specific to them, and we naturally welcome that. An agent stack allows the environment for the customer to write his own agent, but also the customer to write its own skills.

Speaker #1: 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 customers kind of customizing their own environment.

Speaker #1: 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 on that.

John Wall: Yes. Yeah. Thanks, Anirudh, and thanks, Kelsey. Our subscription model remains the anchor arrangement with our customers. The 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 Cadence 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. The monetization opportunity is twofold really. You've got like the new agentic 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.

Speaker #5: Yes. Yeah. Thanks, Anirudh. And thanks, Kelsey. Our subscription model remains the anchor arrangement with our customers. The 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.

Speaker #5: What's different about agentic AI is that it doesn't replace the core EDA engines. It causes them more often, and it causes them intelligently. So the monetization opportunity is twofold, really.

Speaker #5: So you've got the new agentic 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.

Speaker #5: Now, that said, we're obviously being disciplined in our 2026 outlook. We're not assuming a sudden step function in AI monetization in the guide. But we do believe agentic AI expands the long-term growth opportunity for Cadence.

John Wall: We're not assuming a sudden step function in AI monetization in the guide, but we do believe agentic AI expands the long-term growth opportunity for Cadence.

Operator: Our next question comes from the line of Andrew DeGasperi with BNP Paribas. Your line is open.

Speaker #2: Our next question comes from the line of Andrew DiGasperi with BNP Paribas. Your line is open.

Andrew DeGasperi: Thanks for fitting me in. I just had a two-part question. One is Marquee. I think you called out in prepared remarks that a Marquee AI infrastructure company expanded the use of signoff solutions. I just want to clarify, was this a cloud provider? And then second, at CadenceLIVE, you discussed about physical AI in terms of the timeline of adoption being around two years, but yet, you called out that automotive and robotics companies have adopted hardware. I'm 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 benefiting from that? Thank you. Yeah.

Speaker #1: Thanks for fitting me in. I just had a two-part question. One is, Markey—I think you called out in prepared remarks that a marquee AI infrastructure company expanded the use of signoff solutions.

Speaker #1: I just want to clarify, was this a cloud provider? And then second, at CADENCE Live, you discussed physical AI in terms of the timeline of adoption being around two years.

Speaker #1: But yet, you called out that automotive and robotics companies have adopted hardware. I was just wondering, does this mean that the physical AI timeline has been brought forward?

Speaker #1: Or is this just a natural evolution of how these new markets will adopt EDA? And if so, when would we see that kind of software benefiting from that?

Speaker #1: Thank you.

Anirudh Devgan: I think, you know, with physical AI and also agentic AI in general, I mean, yes, I've said for a long time, 2 contract cycles, and that is generally true. Though I think because of this new category of data center 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 2 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 there are more opportunities there because of all the shortages, because all the build outs, because of physical AI. 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.

Speaker #3: Yeah, I think 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.

Speaker #3: Though I think, because of this new category of time 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.

Speaker #3: Okay. I don't want to predict too much. And like John said, we are not putting it in our guide. But I think definitely there are more opportunities there because of all the shortages, because of all the build-outs, because of physical AI.

Speaker #3: So, we are, and like the previous question, we can always add in the renewal. But we always have the capability to do add-ons, which we have already seen.

Anirudh Devgan: That's what I would like to say. On the sign-off, you know, we are very happy. You know, Innovus has been the leading solution for implementation, especially at TSMC and now increasingly with Samsung, Intel, and Rapidus. Sign-off is coming on strong at TSMC and other customers. We are working with all the leading AI players. I think the one we mentioned specifically is a major kind of AI infrastructure/ASIC company, and we are glad to see that adoption. Yeah.

Speaker #3: Okay. So that's what I would like to say. On the sign-off, we are very happy. InnoVerse has been the leading solution for implementation.

Speaker #3: Especially at TSMC, and now increasingly with Samsung, Intel, and Rapidus. But sign-off is really coming on strong at TSMC and other customers, and we are working with all the leading AI players.

Speaker #3: And I think the one we mentioned specifically is a major kind of AI infrastructure/ASIC company, and we are glad to see that adoption. Yeah.

Operator: Our next question comes from the line of Gary Mobley with Loop Capital. Your line is open.

Speaker #2: Our next question comes from the line of Gary Mobley with Loop Capital. Your line is open.

Gary Mobley: Hi, guys. Thanks so much for fitting my question in. John, I think if I'm not mistaken, 2026 is gonna be a low renewal period. By that I mean existing long-time customers scheduled to renew this year, kind of like 2022 was. Was the strong bookings in Q1 a reflection of some add-on sales as salespeople are trying to meet their quota, and do we expect that type of behavior to last through the balance of the year?

Speaker #4: Hi, guys. Thanks so much for fitting my question in. John, I think, if I'm not mistaken, 2026 is going to be a low renewal period.

Speaker #4: By that, I mean existing long-time customers scheduled to renew this year—kind of like 2022 was. And so, with strong bookings in the first quarter, a reflection of some add-on sales as salespeople are trying to meet their quota, do we expect that type of behavior to last through the balance of the year?

John Wall: Hey, thanks for the question, Gary. Yes, I mean, the 2026 is kind of lighter than 2025 for actual renewals on an annual value basis. But what we often see is that those are some of the strongest growth years for us, because of all the add-on activity. Yeah, we were really pleased with the Q1 booking strength, and it was right across the board, across all lines of business. Yeah. Gary, I mean, it bodes well for the year, 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 H2.

Speaker #5: And thanks for the question, Gary. Yes, I mean, 2026 is kind of lighter than 2025 for actual renewals on an annual value basis.

Speaker #5: But what we often see is that those are some of the strongest growth years for us, because of all the add-on activity.

Speaker #5: Yeah, we were really, really pleased with the Q1 booking strength. And it was right across the board, across all lines of business. So, yeah.

Speaker #5: So Gary, I mean, it bodes well for the year. 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.

John Wall: 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 #5: 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.

Operator: Our next question comes from the line of Clarke Jeffries with Piper Sandler. Your line is open.

Speaker #2: Our next question comes from the line of Clark Jeffries with Piper Sandler. Your line is open.

Clarke Jeffries: Hello. Thank you for taking the question. I just wanted to ask about the largest IP arrangement today with the GlobalFoundries foundry. Was it 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 #6: Hello. Thank you for taking the question. I just wanted to ask about the largest IP arrangement today with GlobalFoundries. Was it 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 make this the largest arrangement you've ever seen?

Anirudh Devgan: Yeah. That's a particularly IP contract, so that one particular is focused on IP. The two things that drove it is that it is a new node, new advanced node, more specifically 2-nanometer, and more content in IP because we have much broader portfolio. Yeah.

Speaker #3: Yeah, that's a particular IP contract. So that one in particular is focused on IP. And the two things that drove it are that it is a new node, a new advanced node—more specifically, 2 nanometer.

Speaker #3: And more content in IP, because we have a much broader portfolio. Yeah.

Operator: Our next question comes from the line of Joshua Tilton with Wolfe Research. Your line is open.

Speaker #2: Our next question comes from the line of Joshua Tilton with Wolfe Research. Your line is open.

Joshua Tilton: Hey, guys. Thanks for sneaking me in here. Maybe just a two-parter, a little unrelated, so I apologize. Anything to call out on what drove such a strong quarter for China? Then maybe just a second part to that, can you help us just bridge what is driving such a great 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, 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 for H2. Any help there would be greatly appreciated. Thanks, guys.

Speaker #1: Hey, guys. Thanks for sneaking me in here. Maybe just a two-parter—a little unrelated, so I apologize. But anything to call out on what drove such a strong quarter for China?

Speaker #1: And then maybe just a second part to that. Can you help us just bridge what is driving such a great organic raise to the full year relative to the organic beat in the quarter?

Speaker #1: I know you mentioned the record backlog, but is there anything one level deeper you can give us, especially in the context of—it sounds like you’re trying to tell us that, even though you raised by a pretty solid amount, there still seems to be some conservatism in the guide for the second half?

Speaker #1: So any help there would be greatly appreciated. Thanks, guys.

John Wall: Sure. Josh, thanks for the question. I'll take this one. Josh, yeah, China, it was 13% of Q1 revenue. That was just kind of broadly consistent with what we were expecting. Yeah, we'd still expect China to be about 13% for the year. I think it can be lumpy from quarter to quarter. I think the year-over-year comps probably look generous 'cause Q1 in 2025 wasn't that good in China. It being 13% revenue in Q1, probably the growth rate looks strong. It's just, it's a really important region for us, yeah. We were very, very pleased with the 13%.

Speaker #5: Sure, Josh. Thanks for the question. I'll take this one. So, Josh, yeah. China, it was 13% of Q1 revenue, and that was just kind of broadly consistent with what we were expecting.

Speaker #5: Yeah, we still expect China to be about 13% for the year. I think it can be lumpy from quarter to quarter, so the year-over-year comps probably look generous because Q1 in 2025 wasn't that good in China.

Speaker #5: So, with it being 13% of revenue in Q1, the growth rate looks strong. It's a really important region for us. Yeah, we were very, very pleased with the 13%.

John Wall: In relation to the guide, I mean, the Q1 was a very strong start to the year. We exceeded all our metrics. I guess when we back out the Hexagon, the $160 million of Hexagon and the $0.28, we're basically raising the year by $65 million at the midpoint for revenue and about $0.08 for EPS. Also on the cash flow front, that operating cash, the way we paid for Hexagon, the reported guide includes approximately $180 million of pre-close 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.

Speaker #5: In relation to the guide, yeah, I mean, look, Q1 was a very strong start to the year. We exceeded all our metrics. And I guess when we back out the Hexagon, the $160 million of Hexagon and the $0.28, we're basically raising the year by $65 million, at the midpoint, for revenue.

Speaker #5: And about $0.08 for EPS. Also on the cash flow front, that operating cash—the way we paid for 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.

Speaker #5: 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 operating cash flow outlook is approximately $2.1 billion, which would be about $100 million above our original guide.

John Wall: If you adjust our operating cash guide for that underlying, the, for that pre-close Hexagon tax liability that we're paying, the operating cash flow outlook is approximately $2.1 billion, which would be about $100 million above our original guide. There's a lot of strength we saw across the businesses. The $65 million, you know, is what we took revenue up by, but we're seeing $100 million extra in cash that.

Speaker #5: So there's a lot of strength we saw across the businesses. So, the $65 million is what we took revenue up by. But we're seeing $100 million extra in cash, that there's potentially strength in the second half.

John Wall: There's potentially strength in H2, but we thought it was too early to raise H2 right now.

Speaker #5: But we thought it was too early to raise the second half right now.

Operator: Our final question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is open.

Speaker #2: And our final question comes from the line of Blair Abernethy with Rosenblatt Securities. Your line is open.

Blair Abernethy: Thanks very much for squeezing me in, guys. Just, I want to ask about the Millennium platform. How's the adoption going there, Anirudh? You know, just in general, the health in some of your non-semi verticals like automotive, aerospace, industrial equipment, so forth. Just any commentary around that would be great.

Speaker #3: Thanks very much for squeezing me in, guys. Just want to ask about the Millennium platform. How's the adoption going there on AWR? And just in general, the health in some of your non-semi verticals, like automotive, aerospace, industrial equipment, and so forth.

Speaker #3: Just any commentary around that would be great.

Anirudh Devgan: Yes, absolutely. Yeah, Millennium is doing great. I don't know if you saw, you know, Jensen was there at CadenceLIVE and did a nice autograph on a Millennium box. We are pleased with the partnership with NVIDIA there. I mean, there are two kind of high-level applications. You know, 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? You know what Cascade acquisition we made is very good at very high accuracy CFD, which also applies to aerospace and defense. There is autos, but also A&D is Millennium uptake. We have several customers. Some we can talk about, some we can't, okay? That's in the traditional Millennium.

Speaker #5: Yes, absolutely. So, yeah, Millennium is doing great. I don't know if you saw, Jensen was there at CadenceLIVE and did a nice autograph on a Millennium box.

Speaker #5: So we are pleased with the partnership with NVIDIA there. And I mean, there are two ways—two kind of high-level applications. We are working on this kind of CFD or SDA application for a while.

Speaker #5: And that's going well, especially in auto and also in drones. Okay? There's a lot of, you know, what—the Cascade acquisition we made is very good at very high-accuracy CFD.

Speaker #5: Which also applies to aerospace and defense. So there is autos, but also A&D is a millennium uptake. And we have several customers—some we can talk about.

Speaker #5: Some we can't. Okay? So that's in the traditional Millennium. And the other part this year, like I mentioned in CadenceLIVE, we have all kinds of EDA applications now on Millennium.

Anirudh Devgan: The other part this year, like I mentioned in CadenceLIVE, we have all kinds of EDA applications now on Millennium. It's super exciting. The most exciting part of EDA applications on Millennium is 3D IC sign-off. Because right now the biggest issue is the complexity of these 3D IC systems, not just to design them, which we can do in Integrity and Innovus, but to sign them off. There's this huge system that needs to do thermal simulation, you know, electromagnetic simulation, power delivery simulation, and they are more naturally like a matrix without getting too technical. They are closer to a matrix multiplier numerical solver, which is great for GPU acceleration. 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 3D IC sign-off.

Speaker #5: It's super exciting. And the most exciting part of EDA application on Millennium is 3D IC sign-off, because right now, the biggest issue is the complexity of these 3D IC systems.

Speaker #5: Not just to design them, which we can do in integrity and innovative, but to sign them off. So there's this huge system that needs to do thermal simulation, electromagnetic simulation, power delivery simulation.

Speaker #5: And they are more naturally like a matrix, without getting too technical. They are closer to a matrix-multiplying numerical solver, which is great for GPU acceleration.

Speaker #5: 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 3D IC sign-off.

Anirudh Devgan: We are super excited about the Millennium opportunity along with our traditional hardware systems.

Speaker #5: So, we are super excited about the Millennium opportunity along with our traditional hardware systems.

Operator: I will now turn the call back to Anirudh Devgan for closing remarks.

Speaker #2: And I want to turn the call back to Anirudh Devgan for closing remarks.

Anirudh Devgan: 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. 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 #5: 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.

Speaker #5: 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.

Operator: Ladies and gentlemen, thank you for participating in today's Cadence Q1 2026 Earnings Conference Call. This concludes today's call, and you may now disconnect. Goodbye.

Speaker #2: 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.

Q1 2026 Cadence Design Systems Inc Earnings Call

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