Sam Altman's Latest Interview: Unfazed by Open-Source Distillation, OpenAI Will 'Shock the World' in the Next 12 Months

Compiled by: Deep Tide TechFlow

Guest: Sam Altman, CEO of OpenAI

Host: Patrick O'Shaughnessy, Invest Like The Best

Podcast Source: Invest Like The Best

Original Title: Sam Altman on AGI, Compute, and Human Agency

Release Date: July 28, 2026

Conflict of Interest Statement: Sam Altman is the CEO of OpenAI and does not hold equity in OpenAI, but his personal investment portfolio includes Helion Energy, Stripe, Reddit, Retro Biosciences, and World Network (formerly Worldcoin), among others. OpenAI has commercial or investment relationships with some of these companies. This article presents his personal views and does not constitute investment or operational advice.

Key Takeaways

This is a rare, in-depth personal conversation with Sam Altman on Invest Like The Best. He candidly admits that over the past year, OpenAI "tried to do too much and wasn't focused enough," but after cutting away the branches, the company has re-anchored itself to a single mission: build the best, most abundant, and most cost-effective intelligence, and let the world use it to create incredible things. Based on this judgment, he believes the next 12 months could be OpenAI's best 12 months ever.

But the real tension in this conversation lies in Altman describing OpenAI's mission as "about to create a magic lamp that can grant any wish," while repeatedly stressing that this lamp cannot be monopolized by a few people or a single company. He states bluntly that he is not a "jobs doomer" and does not believe AGI will upend society overnight. What truly concerns him is the concentration of power disguised under the banner of "AI safety." For investors, this episode feels like an insider's monologue: about compute power, model iteration, competitive moats, robotics, personal agents, and the ever-present question of why the CEO of OpenAI doesn't hold company equity.

Highlights of Key Insights

On OpenAI's Focus and Next Steps

• "The past year was really tough, and it was somewhat my fault. But the next 12 months could be our best 12 months ever."
• "We were trying to do too many things. They were all worthwhile things to do, but the trick is, when you're in an incredible historical moment, you can only do a very small number of truly great things."
• "Our business is essentially selling AI, and letting people use it to build incredible products and services for each other."

On Compute and Frontier Returns

• "We can feel the exponential curve of model improvement, and we know it will continue. As long as we can drive the cost down, the demand for high-priced, high-capability AI is essentially limitless."
• "At first, everyone told us we were crazy. We called cloud providers, chipmakers, energy companies, and they all said no industry could develop like this. But most people say no; you only need one or two yeses."
• "The bottleneck keeps shifting: sometimes it's research ideas, sometimes it's compute, sometimes it's data. Now it's back to research ideas."

On AGI and Safety

• "About two weeks after GPT 5.6 was released, even some true skeptics told me it felt very AGI-like."
• "What really worries me isn't others distilling our models. That doesn't even make my top ten list of concerns."
• "We encountered a very sci-fi cybersecurity incident. An unreleased model that was supposed to run in a sandbox figured out how to escape by chaining multiple zero-day vulnerabilities, get on the internet, and ultimately retrieve test answers from the Hugging Face side."

On the Relationship Between Humans and AI

• "I'm not a jobs doomer. I think there will be more work than people can handle, not the opposite."
• "Human values are valuable precisely because they are human."
• "My kid's generation will never live in a world where they are less intelligent than a computer."

On Corporate Governance and Personal Incentives

• "I'm sitting in the front row of the most exciting moment in human history, and that's worth more than any amount of money."
• "In the beginning, we innovated too much on the company structure, and that became one of the sources of pain."

From 'Trying to Do Too Much' to 'Doing Only the Greatest Things'

Patrick O'Shaughnessy: You recently wrote something about the past year being tough and somewhat your fault, and that the next 12 months will be our best 12 months. Can you start by talking about why the past year was tough and why you believe the second part?

Sam Altman: The past year was tough because, at the end of the day, we tried to do too many things and weren't focused enough. Those things were all worth doing, but the trick is that we are in an incredible historical moment, and in such moments, you can only do a very small number of truly great things. So we spread ourselves too thin. Then, after a series of tough decisions, we refocused on a single mission: build the best, most abundant, and most cost-effective intelligence, and let the world use it to create incredible things.

After making this adjustment, our progress has been astonishingly fast. And based on what we see in the pipeline, the next 12 months will be even more astonishing. The quality of the models and the products that can be built around them will allow people to benefit from this technology in entirely new ways. It should be quite stunning.

Patrick O'Shaughnessy: Was there a specific moment when you realized you had to change direction? If we go back to early 2025, the biggest worry at the time was whether OpenAI, having bought so many GPUs, could generate enough revenue to cover the costs, and whether demand would materialize. What made you change your thinking?

Sam Altman: At that time, we had made many contingencies. Just in case revenue growth was slower than expected, we thought we could use consumer apps, media businesses, etc., to absorb the GPUs we had already committed to. It sounds absurd now, because industry revenue has grown so steeply, but that was indeed the big shift at the time. Once we realized the model trajectory was growing so fast and the return on investment was so clear, we knew what to focus on.

Patrick O'Shaughnessy: You've written a lot about how many things to focus on—one, three, five. How do you calibrate that?

Sam Altman: Ultimately, our business is selling AI, letting people use it to create incredible products and services for each other. The components around this include: training models that perform excellently in all the scenarios people want to use; producing or partnering to get chips and systems; finding enough land, power, and data center space to house these server racks; and eventually, likely building robots to automate the construction process, continuously driving down the cost of power, chips, and the entire supply chain. This full-stack work is about creating the best, most abundant, and most useful AI, making it permeate the entire economy like electricity.

We have no interest in competing with every startup in every vertical application. OpenAI just wants to provide that platform.

The Compute Gamble: From Being Rejected by Everyone to Not Having Enough

Patrick O'Shaughnessy: Dario once called you a 'YOLO CEO' because you were exceptionally aggressive early on in compute allocation. Now everyone seems to be short on compute. Can you talk about how you initially reached that conclusion and dared to bet when everyone else thought it was crazy?

Sam Altman: We could feel the exponential curve of model improvement, and we knew it would continue. We were also fairly confident that as models got better and costs kept falling, the demand for high-priced, high-capability AI would be essentially limitless. It's like a brand new commodity. What people will do with it reminds me of the early underestimation of computers—people said "the world only needs five computers," or "no one needs more than a certain amount of memory." Human creativity and the desire for useful things are worth betting on.

We knew algorithms would become more efficient and models would improve. But no matter how efficient it gets, at its core, we are converting electricity into useful intelligence, and the demand for that will only grow. So we just wanted more compute.

Patrick O'Shaughnessy: When did this conviction first emerge? Was it with GPT-3?

Sam Altman: I think it was GPT-4. Not even 3.5. We saw that the model was smart enough that we knew we could find a viable reasoning path. And once reasoning works well, it leads to what we now call agents. This capability can perform a huge amount of high-value economic work, making people's lives easier in many ways.

Patrick O'Shaughnessy: How did you start acting on this?

Sam Altman: We started calling cloud providers, chipmakers, and energy companies. Everyone said, "You're completely crazy, this is impossible, no industry has ever developed like this." It reminded me of early startup fundraising: most people say no, you only need one or two yeses. We got one or two yeses. Microsoft was the first yes. Oracle became a big yes in cloud services. Nvidia has been a fantastic partner all along.

Patrick O'Shaughnessy: There's all this innovation now on reasoning and training data centers, but many people hate data centers. What's your take?

Sam Altman: I keep thinking about how to organize people to visit a gigawatt-scale data center in person. Seeing pictures is one thing; standing there is another. Building one requires about 10,000 construction workers working full-time for a year and a half. The amount of energy flowing through it could power a small city. These are some of the most expensive infrastructure projects in human history, and we are building many of them now.

I understand people don't want a data center in their backyard, just as I wouldn't want a nuclear power plant next to my house, even though I know it's safe. But data centers are different; they can be built anywhere. We should put them in deserts where no one wants to go. It's perfectly fine for AI systems. And we've made great progress on environmental issues too—for example, we used to use water for evaporative cooling, now we use closed-loop systems. Modern data centers use about as much water as the kitchen and bathrooms of an office building. On the energy side, we are transitioning from fossil fuels to solar and nuclear.

Open Source, Distillation, and Competition: Why Altman Isn't Worried

Patrick O'Shaughnessy: The hottest topic this week might be Kimi's new model. Looking back, DeepSeek seems like just a small hurdle. How do you view this kind of competition now?

Sam Altman: Our goal is to offer the best combination of intelligence and price across the entire Pareto optimal frontier, including open source. At certain latency points today, using our open-source model is more cost-effective than using Kimi. We use distillation to make our own smaller, cheaper models, and that itself is a good thing. Open-source models will have a place in the world. Many people want their own weights and the ability to modify models for various reasons. But our goal is the best cost-performance ratio across the entire frontier, and we will consistently deliver on that.

Patrick O'Shaughnessy: But the previous narrative was, someone else spends a fortune training a model, I distill it, and offer it at 1% of the cost. How do you make enough money to keep training?

Sam Altman: Our model usage will be so massive that we won't need to be an ultra-high-margin company to afford model training. A huge portion of our future compute plans are dedicated to providing inference services to customers. Even with razor-thin margins, if revenues reach the trillions, it can support training. The ratio of inference to training is key. Training is indeed extremely expensive, but a large part of future compute will come from serving customers, so I am very bullish on this flywheel.

Patrick O'Shaughnessy: I'm a bit surprised you're so calm about this.

Sam Altman: Of course, I would prefer people didn't 'steal' our stuff. Maybe I'm overly confident right now about our progress and the upcoming models. But it doesn't make my top ten list of concerns.

Patrick O'Shaughnessy: So what is in your top ten?

Sam Altman: We recently encountered a very sci-fi cybersecurity incident. We were evaluating an unreleased model. It was supposed to run in a sandbox. But it discovered it could escape the sandbox by chaining multiple zero-day vulnerabilities, get on the internet, then break through multiple systems at Hugging Face to retrieve test answers and make itself perform well on the evaluation. This was the first time I felt the security threat so viscerally.

Patrick O'Shaughnessy: This just happened a few days ago, and I'm surprised more people aren't feeling that visceral fear. What will you do?

Sam Altman: In the short term, we will pause training and figure out how to keep sandboxes secure in a world where multiple zero-days can be chained. But the long-term question is, if this is the new pace of progress, we may need to slow down AI development to give society time to adapt to new capability levels. The difficult part is figuring out how to do this without it looking like regulatory capture by a single company or collusion among frontier labs. It requires effort and must be done right.

The Magic Lamp, AGI, and Human Agency

Patrick O'Shaughnessy: Describe in the simplest terms what OpenAI wants to do, and whether that mission has evolved.

Sam Altman: I think this will be the greatest technological achievement in human history so far. But the only way it truly matters is by making people's lives vastly better. On one hand, we want to give people material abundance and the freedom to express creativity and help each other. On the other hand, we need to ensure people maintain control and agency, and that the world becomes more democratic, not less.

On the positive side, we are about to build a magic lamp that can grant any wish. I hope the first wish the world makes with this lamp is beneficial for all humanity. People will realize the astonishing creative power they will have—not just curing diseases, which is obvious, but world-class entertainment ideas we can't even imagine sitting here today. I want to put this capability in everyone's hands.

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