Intel CEO Lip-Bu Tan used his first detailed podcast interview on No Priors to lay out a broad plan for reshaping Intel. His stated goal is direct: achieve a 10x return over five to ten years. Tan said Intel has already created roughly a 6x return for shareholders over the past 14 months, but described that as only the beginning. In his view, Intel’s next phase is not limited to the traditional PC client base. The company must combine its XPU portfolio, advanced packaging and foundry capabilities to deliver custom silicon solutions for different workloads.
The interview covered why Tan accepted the role, how he is dealing with Intel’s balance sheet and product portfolio, how AI is changing CPU demand and global semiconductor supply chains, and why he is putting emphasis on materials science, EDA, advanced packaging and manufacturing infrastructure. Tan, now 66, said he took the job because Intel is an iconic company that is highly important to both the semiconductor ecosystem and the United States. After Cadence, he said, he decided to do one more major thing.
From balance sheet repair to a crawl-walk-run operating model
Tan repeatedly framed Intel’s transformation with the phrase “crawl, walk, run.” In the crawling phase, he said the company has had to change its culture, clarify accountability and speed up decision-making. Coming from an engineering background, he put all engineering teams under direct reporting to him so he could personally understand what was wrong and what needed correction. He also emphasized customer listening, customer satisfaction, product simplification and a clear five-to-ten-year roadmap.
On the balance sheet, Tan said he was pleased that the U.S. government became a major shareholder. He said he explained to President Trump that, as seen in Japan and Singapore, semiconductor manufacturing sits at an infrastructure level and deserves government support. He also mentioned Jensen Huang’s $5 billion investment in Intel, saying that the investment has now grown to $25 billion or more. SoftBank’s Masayoshi Son, with whom Tan had worked through SoftBank’s board, also helped. Tan recalled that President Trump once asked him early in the morning to resign because of an alleged conflict of interest. Tan later secured meetings, explained that he was born in Malaysia, raised in Singapore, graduated from MIT and had lived in the United States ever since, and was ultimately given the opportunity to continue.
On the product side, Tan said agentic AI and inference workloads are bringing CPU demand back strongly. In past training workloads, the CPU-to-GPU ratio was roughly one to eight. He said he now sees that moving toward one to four, and even lower. Conversations with AI model developers led him to the view that CPUs perform better in reinforcement learning and in coordinating and scheduling large numbers of agents. That shift makes the data center server product line important again, while Intel Foundry remains a separate capital-intensive business that requires the right IP portfolio, reliable execution and trust from customers.
Advanced packaging, glass substrates and synthetic diamond
Tan identified materials science and advanced packaging as key answers to the limits of traditional process scaling. He said Intel has 18A, is moving 14A into production, and can see paths toward 10 nanometers and 7 nanometers, but that road will become more expensive and more difficult. This is why he said Intel must work closely with substrate suppliers and equipment vendors to improve yield and performance.
Advanced packaging was one of the clearest themes in the interview. TSMC has CoWoS, while Intel is pushing its next-generation EMIB approach. Tan said he must make sure EMIB reaches the customer-required yield level in mass production. He also invested in 3DGS, a glass substrate company, because he sees glass as a strong thermal and insulating material. Intel has about 1,000 patents in modules, and Tan described the integration of substrates and modules as an important engineering challenge. Intel has also announced advanced packaging manufacturing cooperation projects in India and New Mexico in the United States.
In semiconductor materials, Tan named gallium nitride, silicon carbide and indium phosphide as areas where he has invested. Some of the companies in those areas have been acquired by major semiconductor companies including ADI. He also invested in a synthetic diamond wafer company, citing diamond as another excellent insulating material for chip packaging. “That is the spirit of engineers,” he said in the interview. Engineers keep running into bottlenecks and then find ways to go over them or around them.
Foundry execution and Terafab with Elon Musk
Intel’s foundry business has faced doubts over cost and feasibility, but Tan said he chose to stay with it. His reasoning is that advanced domestic manufacturing in the United States is important for supply chain security and for the broader industry. Large semiconductor companies, he said, cannot concentrate their supply chains too heavily in one or two geographic areas. He acknowledged that Intel still has a large gap with TSMC, while also describing TSMC as a partner rather than a simple competitor. The industry, in his view, needs more capacity to serve customers.
For foundry execution, Tan focused on yield, defect density and cycle time. Foundry, he said, is a service business and a trust business: customers must trust Intel before they hand over wafers. If yield fails to meet requirements, customers can lose revenue and leave, and that loss is hard to reverse. Tan said Intel must build the foundation first, including IP, yield, defect density and cycle time, before the market can fully see the foundry business. He pointed to the 2030 to 2032 period as the time when Intel’s true potential should become clearer.
Tan also discussed Terafab, the project being pursued with Elon Musk. He said both sides agree that semiconductor infrastructure has not kept up with AI growth in capacity, production efficiency or power efficiency. Under the cooperation, Musk decided to build his own wafer fab, while Intel will provide technology and process support to help accelerate production. Tan said he meets with Musk’s team every week and enjoys working with them because they challenge conventional approaches. He also mentioned Musk raising unconventional operational questions, such as whether smoking could be allowed in certain areas of a cleanroom. Tan said he would not go that far, but that keeping an open mind and evaluating ideas seriously matters.
AI supply chains, investment lessons and Cadence experience
Looking at AI’s effect on the global semiconductor supply chain, Tan said its impact will be greater and deeper than the internet. AI can improve efficiency in semiconductor design, including timing optimization and time to market, while lowering cost. At the same time, he listed several bottlenecks: electricity limits in some countries, the impact of helium on the semiconductor industry, and memory shortages. Even if capacity is expanded now, new supply takes years to come online, while CPUs and GPUs are also in short supply and higher costs eventually flow through to clients.
Tan also drew on his record as a long-term investor. He said he has been involved with 159 IPOs and 126 M&A exits, and has made more than 200 semiconductor investments, 38% of them in the United States. His investment method begins with a bottleneck: what problem is real, and what pain are customers actually experiencing? He cited Cradle Semiconductor because interconnect became a bottleneck, and Celestial AI because optical interconnect is becoming more important inside clusters. He also pointed to opportunities in EDA where AI and machine learning can reduce design complexity and improve quality, as well as power management where the conversion from 40V to 1V involves major losses.
Talent and geography were also part of his investment discussion. Tan named the United States, Silicon Valley, Austin and Israel as key areas of focus. He praised Israeli entrepreneurs for disruptive innovation and resilience, describing founders who continue meetings during wartime, sometimes moving to a basement during an alarm and switching to audio when the connection is weak. Beyond agentic AI, he called physical AI the next major frontier and said he remains deeply involved in investments around frontier models and open-source frontier technologies for physical AI.
Tan’s Cadence experience served as another reference point. He spent nearly 15 years at Cadence and said one of the things he is most proud of was finding and training his successor, who is now embracing AI and bringing agentic AI into tools to improve efficiency. He also mentioned Synopsys CEO Sassine doing similar work, supported by Nvidia’s $2 billion investment, and Synopsys’ acquisition of Ansys to expand into full-system design. Tan noted that semiconductor investing was once unpopular among many venture capitalists, but the field has returned to the center: he cited Jensen Huang’s Nvidia at $5.3 trillion in market value, Broadcom and TSMC at about $2 trillion each, Lisa Su’s AMD near $800 billion, and Intel near $600 billion.
What investors misunderstand about Intel
Asked about the biggest investor misconception around Intel, Tan returned to the crawl-walk-run framework. He said the company is still in the crawling stage, even though people have begun to see the potential. The PC client business remains Intel’s base, but performance must improve significantly. He said he is quietly building CPU architecture, GPU architecture and software architecture teams so Intel can move with the speed of a large startup and prepare for leapfrog innovation.
In foundry, he said Intel must remain humble because the gap with TSMC is still large. The company must first focus on IP, yield, defect density and cycle time so the foundry business becomes more efficient and reliable. Trust takes time. Tan said customers must trust Intel before they give Intel their wafers. He expects the 2030 to 2032 period to reveal how large Intel’s real potential is.
Tan sees Intel extending from the PC base into edge computing, physical AI and agentic AI. In the past, servers and PCs served human users, but agentic AI creates another dimension: millions of agents need access to compute and software stacks. Physical AI also changes the role of device-side computing, especially in robotics and defense. On where compute will live, Tan said large-scale AI infrastructure buildout remains appropriate and he sees no reason for a slowdown, because workloads continue to grow and current constraints are mostly on the supply side rather than the demand side. Still, he said the important question is what applications will actually run at scale on that infrastructure, comparing the future AI application landscape with the internet era in which Amazon and Netflix emerged while other applications disappeared or were acquired.
Tan closed the investment discussion by comparing Intel with his Cadence record. At Cadence, he said the stock rose from $2.40 to a level that created about 76x returns for shareholders from his time as acting CEO to retirement, and about 85x by the end of his term as executive chairman. Intel is larger and harder to replicate, he acknowledged. But as someone who says venture capital is in his DNA, his stated target for Intel remains a 10x return over five to ten years.