Jun 18, 2026 · 44m · no-priors
Re-engineering the Semiconductor Supply Chain with Intel CEO Lip Bu Tan
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In this episode of No Priors, Intel CEO and veteran investor Lip-Bu Tan details his multi-year turnaround strategy for Intel, examining domestic manufacturing, advanced packaging, and the evolving capital and architectural demands of the AI era.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. The hosts hold 22.5% of the talking time here. How this is scored →
The hosts as informed peer 4.8 Guest teaching 4.2 Guest disagreement 1.1 The hosts pushing back 1.6
speaking balance: gold is the hosts, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 13:56 Tan rejects market consensus on abandoning foundry operations
Tan directly counters widespread industry skepticism declaring that Intel foundry cannot work, arguing that domestic sub-1nm capacity is existential for the United States.
Hardest push from the hosts ▶ 13:08 Sarah challenges the feasibility of domestic foundry economicsSarah presses Tan on the high cost of domestic manufacturing and labor constraints, questioning the core premise of Intel Foundry and TerraFab.
Biggest teaching moment ▶ 16:48 Tan teaches alternative substrate physics and packagingTan provides a masterclass on overcoming CMOS scaling limits by detailing his specific technical bets across gallium nitride, silicon carbide, indium phosphide, glass, and artificial diamond.
The host holds their own ▶ 20:39 Sarah breaks down structural venture risks in semiconductorsSarah displays deep venture expertise by articulating a comprehensive taxonomy of semiconductor risk factors including capex intensity, tapeout failure, cyclicality, and switching friction.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The hosts as informed peer | Guest teaching | Guest disagreement | The hosts pushing back | Why |
|---|---|---|---|---|---|---|
| Episode Preview and Core Philosophies | 3 | 2 | 1 | 1 | Sarah introduces Lip-Bu Tan and asks why he took on the daunting task of running Intel at age 66. Tan explains his motivation to save an iconic American company and details his meeting with Donald Trump regarding conflict-of-interest allegations. | |
| Restructuring Intel: Culture, Balance Sheet, and CPU Demand | 4 | 5 | 1 | 1 | Tan outlines his crawl-walk-run turnaround strategy, including direct engineering reporting, securing capital from Jensen Huang and SoftBank, and explaining how CPU demand is surging for agentic AI and reinforcement learning orchestration. | |
| Collaborating with Elon Musk on TerraFab | 5 | 5 | 1 | 1 | Elad frames a broad question about global semiconductor supply chain impacts across different nations. Tan discusses his weekly collaboration with Elon Musk on TerraFab and identifies critical supply bottlenecks such as helium, power, and memory shortages. | |
| Domestic Foundry Viability and Sub-1nm Nodes | 5 | 4 | 2 | 4 | Sarah pushes back with the common market critique that domestic foundry manufacturing faces insurmountable labor and cost hurdles. Tan firmly rejects the idea of abandoning foundries, citing national security and Intel's roadmap toward 1nm and 0.7nm nodes. | |
| Physical Miniaturization Limits and Material Science | 5 | 6 | 1 | 1 | Elad asks when physical semiconductor miniaturization will reach an absolute physical barrier. Tan educates on post-CMOS frontiers, discussing his venture investments in gallium nitride, silicon carbide, indium phosphide, glass substrates, and artificial diamond. | |
| The Resurgence of Semiconductor Venture Capital | 4 | 4 | 1 | 1 | Elad asks about performance normalization across foundries as physical limits approach. Tan reflects on the historical shift in venture capital, noting how partners used to walk out of meetings when he pitched semiconductors two decades ago. | |
| Semiconductor Investment Strategy and Key Bottlenecks | 6 | 5 | 1 | 2 | Sarah articulates the core structural risks of semiconductor venture investing including capex, tapeout risk, and switching friction. Tan responds by laying out his playbook of investing directly in interconnect and power management bottlenecks with hyperscaler design partners. | |
| AI Innovation in EDA and Chip Design | 5 | 4 | 1 | 1 | Sarah and Elad inquire about AI-driven automation in EDA and chip design. Tan discusses the competitive dynamic between Cadence and Synopsys, noting that nine out of ten portfolio startups must pivot and that winning companies will provide full-stack purpose-built silicon. | |
| Modernizing Intel from Legacy Systems to AI-Native Teams | 6 | 4 | 1 | 1 | Elad draws an analogy between software engineering team shifts and semiconductor operations. Tan acknowledges Intel's historical weakness as an aging spreadsheet-driven organization and describes modernizing the company into an AI-native design shop. | |
| Industrial Policy, Sovereign Capital, and Scaling Infrastructure | 5 | 4 | 1 | 1 | Sarah asks about the acceptance of state industrial policy in modern venture capital and infrastructure. Tan explains how building advanced fabs requires a blend of sovereign capital, long-term mutual funds, and government backing over short-term buyback demands. | |
| Investor Misperceptions and Intel's 10x Long-Term Roadmap | 4 | 4 | 1 | 1 | Sarah asks what public investors fundamentally misunderstand about Intel. Tan explains that while the foundry turnaround is targeted for the 2031-2032 timeframe, Intel's edge, physical AI, and agentic computing expansion position it for a long-term 10x return. | |
| Centralized Data Centers vs. Edge AI and Application Focus | 6 | 3 | 1 | 4 | Sarah pushes Tan on his assumption that AI compute will decentralize to edge and client devices rather than consolidating into centralized gigawatt data centers. Sarah demonstrates domain expertise in robotics and defense hardware constraints. |
Statements from this episode (23)
Tan: President Trump asked him to resign over conflicts of interest
“Well, the most surprising that I don't learn from my previous job or even training is one day early morning, President Trump asking me to resign and a conflict of interest, and there's no exceptions.”
Tan: All Intel engineers report directly to the CEO
“And also the other part, from day one, I decided all the engineers report to me.”
Tan: Jensen Huang's $5B Intel investment is now worth $25B+
“Secondly, very happy that Jensen Huang, my old time friend, he also put five billion in investing and support me. And I'm glad I at least do some good work. It's five billion become twenty five billion now and or more.”
Tan: AI inference is shifting CPU-to-GPU ratios toward 1:4 or 1:1
“Right now, the authentic AI and inference, CPU become, you know, highly in demand. And so, you know, versus one to eight in the training CPU to GPU, now I can see one to four, maybe one to one, and I'm delighted CPU become important.”
Tan: Intel CEO personally handles all recruitment without search firms
“By the way, all the recruitment, I do it myself. No search firm helping.”
Gil: Layoffs Attributed to AI Are Overstated and Driven by COVID Over-Hiring
“When I look at the layoffs that are claimed from AI, for example most of them I think are overstated right now. You know, most of the layoffs are actually just over hiring during the COVID period.”
Tan: Memory is the biggest AI bottleneck and takes years to fix
“Everybody know right now, memory is the biggest shortage. And everybody tried to scramble for memory. And then even though you want to build a fab to capacity increase, it would take a couple of years to do that.”
Tan: Intel is already planning for 1nm and 0.7nm nodes
“And then the most advanced process, like for example, we have the, you know, the is like 1.4 nanometer.
And we are already starting to plan for one nanometer and 0.7 nanometer.”
Tan: Chip manufacturing will reach 10A and 7A nodes despite escalating costs
“So I think I can see, you know, right now we have A and then now going to production of A, I can see 10 and seven. And so I think that path, I think we can get there, but couldn't it be more and more expensive and more difficult to do?”
Tan: Invested in 3D Glass Solutions for advanced glass packaging
“And then in terms of packaging, I started to invest into glass. Glass is a very good heat Insulator. So we, I even invest in a venture site called three DGS.”
Tan: Invested in Diamond Foundry for semiconductor packaging applications
“I also starting to look at artificial diamond. And that's another very good, you know, insulator. So I also invest into, you know, diamond foundry.”
Lip-Bu Tan reports 159 IPOs, 126 M&A exits across his investment career
“You know, I still have 159 IPO, one 126 you know, M&A. And that's include semiconductor. Just break down to semiconductor. I invest over the years 200, and 38% is in US.”
Tan: Jensen Huang invests in almost every photonics-related company
“Look at Jensen. He invests in almost every company is photonic related.”
Tan: Chip startups should target hyperscalers on day one, even granting warrants
“The next thing is look at, it's very important from day one, you'd have to target the first customer. And usually I like the customer is hyperscale. They have the scale. If they like what you have, they're willing to pay millions of dollars next few years. And…”
Lip-Bu Tan: Open-source physical AI technology is a goldmine
“And right now, beside the agentic AI, now you're looking at physical AI, it's a mixed big frontier, and then you have to really look at a full stack. That's why I'm still involved with a lot of this frontier model that we very familiar, and some of the investm…”
Tan: Nine in Ten Portfolio Startups Pivot Midstream
“Nine of the 10 companies I invest, halfway they change their business plan because market have changed.”
Gil: Team management experience transfers directly to managing AI agents
“Many people now that I know are hiring people more in their thirties, forties, fifties, because they're used to managing teams. And I think that transfers directly over to managing agents in terms of understanding the complexity of what to set up and the QA an…”
Tan: Venture Capital Firms Are Now Putting $1B Checks Into Startups
“And some of the venture firm willing to put one billion into some company is very unheard of in the VC business. Now it's happening.”
Tan: AI Factories and Semiconductor Foundries Require Sovereign and Government Capital
“And then in terms of the capital intensive, like AI in a factory and also the foundry, and then you really need to tap either government funding or some sovereign fund, and also some very big capital. You know, there's some big fund that doing that, and they'r…”
Tan: Intel Foundry is very distant from TSMC on performance and yields
“And the Foundry side, we are very distant from TSMC. And then in terms of their performance, so that's we have to be humble looking at building the building block, like I mentioned earlier, the IP, the yield, the defect density, and the cycle time to make it m…”
Tan: Intel Foundry turnaround will begin surfacing around 2031 or 2032
“So those are the things will take longer time, but I think by 32,032, 31, 32, I think I was starting to surface up.”
Tan: Cadence delivered an ~85x shareholder return under his leadership
“You know, at Cadence, when I stepped down as a CEO, I think we make about close to 76 times, you know, starting from interim CEO, two dollar 42 cents. And then when I retired as security chairman, about 85 times return to the shareholder.”
Tan: Setting goal of 10x shareholder return at Intel within a decade
“So it's hard to do that at Intel because the base is bigger. So I kind of said, okay, let's do it at 10 X, you know, and then, and five years, 10 years, we can Do Xx. I think it's a good return. Being a venture capital at heart. That's kind of my goal.”