# Intel's process team makes decisions before data is complete

Markdown copy of https://realalpha.app/s/intels-process-team-makes-decisions-before-data-is-complete/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Kevin Fisher](https://realalpha.app/people/kevin-fisher/)
- Host: [Dwarkesh Patel](https://realalpha.app/people/dwarkesh-patel/) · Host, Dwarkesh Podcast · Co-wrote The Scaling Era, an oral history of AI; named to TIME100 AI.
- Show: Dwarkesh Podcast
- Episode: [What will computer chips look like in 2045?](https://realalpha.app/v/frYSOKvNiiE/), Oct 22, 2026
- Moment: 23:42 to 26:39 of the episode (3 min), playing on https://realalpha.app/s/intels-process-team-makes-decisions-before-data-is-complete/; the episode from there: https://realalpha.app/v/frYSOKvNiiE/?t=1422

## Quote

> “If you want to wait for a complete data set, **you've waited too long**. It's already too late.”
> — [Kevin Fisher](https://realalpha.app/people/kevin-fisher/) at [25:05](https://realalpha.app/v/frYSOKvNiiE/?t=1505) · Dwarkesh Podcast

## Takeaways

1. The meeting directs resources to urgent node problems.
2. Waiting for complete data can be too late.
3. Epitaxy nodules can short adjacent regions and disable transistors.

## About this segment

Kevin Fisher describes how Intel's Hot Topics meeting directs resources to urgent process problems. He says waiting for complete data can mean missing the production window.

From “What will computer chips look like in 2045?”, Oct 22, 2026. [Watch the full episode](https://realalpha.app/v/frYSOKvNiiE/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[23:44](https://realalpha.app/v/frYSOKvNiiE/?t=1424) I sat in on one of Intel's Hot Topics meetings, where those decisions get made. Okay, I'm here with Kevin Fisher, who was laying down the law this morning at the Hot Topics meeting where you guys were discussing how you're improving 18A and 18AP technologies. And people would come to you with these different... Experiments they were running, different ideas they had for improving yield and for improving performance.

[24:04](https://realalpha.app/v/frYSOKvNiiE/?t=1444) And then you and your integration engineers would tell them what data you needed, tell them how they should proceed, tell them how you think you can move things faster. I want people to have a sense of the culture at these meetings. So one thing that I found striking is just that there's, you know, this is bottlenecking your most advanced node. You want to practice what happens fast. And so you kind of lay down the hammer.

[24:26](https://realalpha.app/v/frYSOKvNiiE/?t=1466) I would say the average engineer doesn't understand the stakes or the urgency of how this is going to impact, you know, Intel's bottom line, how it's going to impact our customer. They just have no visibility to those issues, right? So they will typically have a certain set of criteria that they want to go capture. they'll hit boundaries of, you know, I asked for something and someone said no. And, you know, I'm done. I can't, I can't, I guess I can't have this thing that I asked for. One thing you learn in this industry is that you will never have a complete data set. If you want to wait for a complete data set, you've waited too long. It's already too late. So a lot of what I end up doing in those meetings is I decide how much risk we're going to take on a certain decision or not take on a certain decision and you need to say, look, do we go now? Do we start risking production?

[25:27](https://realalpha.app/v/frYSOKvNiiE/?t=1527) Because you're risking, you know, the bottom line, you're risking revenue. I'm worried you're going to put me in the light of being an ogre because I'm putting the hammer down on you. That's a great reputation to have. It's really conveying urgency. Yes. Every day counts. Yeah. Can you walk me through a particular issue that might come up? Well, one of the examples you saw this morning, which is epi nodules.

[25:50](https://realalpha.app/v/frYSOKvNiiE/?t=1550) Epi is short for epitaxy, which means growing new material on top of an existing one. Chipmakers flow gases over a heated wafer, and the gases leave atoms on its surface. The crystal structure of the material underneath acts as a template. Each new atom lines up with the atoms below it, and the new layer continues the same crystal. Chipmakers use epitaxy at several stages of making a chip. In the step Kevin describes, they use it to grow the source and the drain as small crystals on either side of the gate.

[26:20](https://realalpha.app/v/frYSOKvNiiE/?t=1580) So during the deposition of our epitaxy, we get abnormal growth, like a tumor, right? It's going super fast. And that causes problems because one epi will short to the wrong epi, and you get transistors not working. And then you've got to narrow it down to how are you going to fix it.