TechFlowPost, citing Wall Street News, reported on Intel CEO Lip-Bu Tan’s first long-form podcast interview on No Priors, where the hosts and Allad asked him about rebuilding Intel, the role of the U.S. government as a major shareholder, the feasibility of manufacturing chips in the United States, semiconductor investing, and the way AI is reshaping the global supply chain. Tan framed his mandate in venture-capital terms: as someone who still thinks like a VC, he said his goal is to pursue a 10x return for Intel over five to ten years.
Tan said Intel has generated roughly a 6x return for shareholders over the past 14 months, but he described that as only the beginning. His operating framework is “crawl, walk, run.” The first stage is to stabilize the balance sheet, change the culture, establish accountability, simplify decision-making, and listen directly to customers. He also said that, from day one, he had all engineering teams report directly to him because he wanted to know personally where problems were and what needed to be corrected. At age 66, he said he accepted the Intel role because the company is iconic and deeply important to both the semiconductor ecosystem and the United States, and because after Cadence he wanted to do one more major thing.
Balance sheet repair and a renewed CPU cycle
Tan recounted that one of the most surprising moments of the past year came when President Trump asked him to resign early one morning, citing conflicts of interest. Tan said he first set aside personal emotion and reminded himself that he did not need the job and was doing it to save Intel. He later secured a meeting, explained that he was born in Malaysia, grew up in Singapore, graduated from MIT, and had lived in the United States ever since. According to Tan, Trump listened and gave him the chance to continue. Inside Intel, Tan said he found multiple layers of meetings and bureaucracy, which he is trying to replace with a pace closer to that of a startup.
On the balance sheet, Tan said he was pleased that the U.S. government became a major shareholder, arguing that infrastructure-level projects deserve government support and pointing to Japan and Singapore as examples. He also thanked Nvidia CEO Jensen Huang for investing $5 billion in Intel, saying that stake has grown to $25 billion or more. SoftBank’s Masayoshi Son, with whom Tan had worked through SoftBank’s board, also helped. With the balance sheet strengthened, Tan said Intel’s next priority is to focus the product portfolio, simplify the product line, listen to customers, and launch next-generation leading products.
Tan described agentic AI and inference as a favorable timing factor for Intel’s CPU business. During the training era, he said the CPU-to-GPU ratio was roughly one to eight. He now sees that ratio moving to one to four, and even lower. Conversations with AI model developers led him to conclude that CPUs perform better in reinforcement learning and in the orchestration and scheduling of agents. After establishing the data-center server product line, Tan wants Intel to move toward full-stack offerings: not only silicon, but also software and system-level solutions. He said some customers have directly asked him to provide an entire rack.
Foundry discipline and the Terafab collaboration
Intel’s foundry business has faced skepticism, but Tan said he decided to keep investing in it because advanced manufacturing in the United States is strategically important for supply-chain resilience and for the broader industry. No major semiconductor company, he argued, should depend entirely on one or two geographically concentrated suppliers. In execution, Tan is focused on yield, defect density and cycle time. Foundry work, in his words, is a service business and a trust business: customers must trust Intel before they hand over wafers, and if yield is not good enough, customers can lose revenue and leave.
Tan also emphasized that Intel respects TSMC and sees it as a strong partner, not merely a competitor. He said the industry needs more capacity to serve customers. On advanced process technology, Tan referred to Intel’s 18A node, describing it as a 1.4-nanometer-class process, and said Intel is planning 1 nanometer and 0.7 nanometer. As nodes shrink, manufacturing becomes more complex, and a single mistake can undermine the whole process. That level of required precision, he said, is increasingly becoming a bottleneck.
The interview also covered the Terafab project with Elon Musk. Tan said he and Musk share the view that semiconductor infrastructure has not kept pace with AI growth in capacity, production efficiency or power efficiency. Under the collaboration, Musk decided to build his own fab, while Intel will contribute technology and process support to help accelerate production. Tan said he meets with Musk’s team every week and enjoys the collaboration because Musk constantly asks why things have to be done in the traditional way. He mentioned one unconventional discussion about allowing smoking in certain cleanroom areas; Tan said he would not go that far, but the broader point is to keep an open mind and evaluate ideas seriously.
Advanced packaging, glass substrates and synthetic diamond
When asked about physical limits in chip scaling, Tan said Intel already has 18A, is pushing 14A into mass production, and can see a path to 10 nanometers and 7 nanometers. But that path, he said, will become more expensive and more difficult. As traditional scaling approaches bottlenecks, he is turning to materials science, substrates and advanced packaging. TSMC has CoWoS, while Intel is advancing its next-generation EMIB packaging approach. Tan’s responsibility is to make sure EMIB reaches customer-required yield levels in mass production.
Tan said he has invested in gallium nitride, silicon carbide and indium phosphide, and that some of those portfolio companies have already been acquired by large semiconductor companies including ADI. In packaging materials, he has focused on glass and invested in 3DGS because he sees glass as an effective heat-dissipating 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 collaboration projects in India and New Mexico. In addition, Tan has invested in a synthetic diamond wafer company, viewing diamond as another strong insulating material for chip packaging. As he put it, the engineer’s spirit is to keep encountering bottlenecks and then find a way to cross them or go around them.
Tan also discussed how Moore’s Law is changing. The core idea, he said, is transistor-density doubling, but power and cost do not fall at the same rate. Performance can double, but area and cost do not necessarily decline proportionally unless new materials and new design methods are found. That is why he is hiring more materials-science talent. He recalled that 15 to 20 years ago many top VCs had little interest in semiconductors, apart from institutions such as Samsung, ARM and SoftBank. Today, Nvidia under Jensen Huang is valued at $5.3 trillion, Broadcom and TSMC are each around $2 trillion, AMD under his friend Lisa Su is close to $800 billion, and Intel is close to $600 billion. Semiconductors, in his view, have again become a foundational field.
How Tan invests across the semiconductor stack
Tan spoke as both an operator and a long-time investor. He said his record includes 159 IPOs and 126 M&A exits, with more than 200 semiconductor investments, 38% of them in the United States. His investment method begins with one question: where is the bottleneck, and what problem is being solved? He cited Cradle Semiconductor as an investment related to interconnect bottlenecks, and Celestial AI as an investment tied to the growing importance of optical interconnect inside clusters. He also noted that Jensen Huang has invested in almost every photonics-related company, saying this is not a coincidence.
At the design layer, Tan sees major opportunities in using AI and machine learning to reduce complexity and improve design quality, especially in EDA. In materials, gallium nitride, silicon carbide and indium phosphide remain his investment areas. In power management, he highlighted the significant loss involved in converting from 40V to 1V. His framework is to test whether the problem is real, whether customers are truly struggling with it, and who the first target customer is. He prefers companies that can win hyperscale customers, because those customers have the ability and willingness to pay millions over several years, and their backing can help a startup scale after one major win.
Talent is another central part of the framework. Tan named the United States, Silicon Valley, Austin and Israel as areas he watches closely. He praised Israeli entrepreneurs for disruptive innovation and resilience, including their willingness to keep meetings going during wartime, even if they must move to a basement during an alert and switch to voice because the internet connection is weak. He also said that, beyond agentic AI, physical AI is the next major frontier, and that he remains deeply involved in investments connected to frontier models and open-source technology for physical AI.
Tan tied this back to his Cadence experience. He spent nearly 15 years at Cadence and said one of the achievements he is proudest of is choosing and training his successor, who is now actively bringing agentic AI into Cadence tools to improve efficiency. Synopsys CEO Sassine is doing similar work, supported by a $2 billion investment from Nvidia, and Synopsys has expanded toward full-system design through its acquisition of Ansys. Tan said large companies are moving quickly, but startups still have room to do more disruptive work, whether their path leads to IPOs or acquisitions by larger players.
Capital, organization and Intel after 2030
Looking at the next decade, Tan said AI will change Intel and future semiconductor companies. Because semiconductor investing is capital-intensive, cyclical and hard to predict, he likes to enter early, help build teams, find investors willing to stay through difficult periods, and bring in strategic investors who can add value in manufacturing, memory, interconnect or other parts of the stack. He said that in his own portfolio, nine out of ten companies changed their business plan midway because the market changed. That is why he prefers teams over single founders, and founders who can listen, absorb feedback and still form their own judgment.
For Intel, Tan’s desired role is to combine XPU, advanced packaging and foundry capability into customized chips for different workloads. He compared this platform approach to Nvidia’s focus on CUDA, while also noting that startups such as Anthropic and OpenAI can move at light speed and change the game in elegant ways. Future winners, he said, will focus on specific niches, find the right partners, scale effectively and offer full-stack solutions.
On organizational change, Tan returned to the “crawl, walk, run” framework. In the crawl stage, he has recruited top semiconductor talent. He is also thinking about the software talent needed to build full-stack capability. Intel’s team is often in its 40s and 50s, and he wants to bring in younger people who understand workloads and frontier open-source models. He joked that his son has become his teacher on AI and machine learning; when he visits to play with his grandchildren, he asks his son questions and tries to convert what he learns into investment judgment and hiring decisions. Tan said Intel had been an old-school, spreadsheet-heavy company, and he is trying to make it AI-enabled across the entire organization, not only in design but also in sales, marketing and operations.
Capital access was another major theme. Tan said capital-intensive businesses and infrastructure projects must seek support from government funding, sovereign wealth funds and large infrastructure funds. Some VCs now invest $1 billion into a single company, which he said was previously unimaginable, while Series A valuations have already exceeded $1 billion in some cases. As a public-company CEO, he is also seeking investors with long-term growth orientation rather than only short-term holders focused on quarterly buybacks, while acknowledging that shareholder return is a reasonable concern.
When asked about the biggest investor misunderstanding around Intel, Tan said many people expect the company to run before it has finished crawling. On products, PC client remains Intel’s base, but performance must improve substantially, and he is quietly building CPU architecture, GPU architecture and software architecture teams to prepare for leapfrogging. On foundry, Intel still has a large gap with TSMC and must remain humble while building the foundations: IP, yield, defect density and cycle time. He believes that by 2030 to 2032, people will begin to see Intel’s true potential, extending from PCs and servers into edge computing, physical AI and agentic AI.
Tan closed by discussing where computing power will live. He supports the current buildout of large-scale AI infrastructure and said he sees constraints coming from supply, not demand. But he is more focused on what applications will run on that infrastructure once it is built. He compared the process to the internet era, when Amazon and Netflix emerged as real applications while others disappeared or were acquired. In AI, he expects major growth to be followed by consolidation, with one or two real winners emerging in some categories. Robotics and defense, he said, are examples of workloads where edge or client-side computing matters, because assumptions about connectivity and device capability determine what can be done. Returning to his personal target, Tan noted that at Cadence the share price went from $2.40 to a roughly 76x return for shareholders, and about 85x by the end of his executive-chairman tenure. Intel is larger and harder, but his stated aim remains 10x over five to ten years.