Tag: scaling

Categories
AI IBM

From Picnic to Workforce: The New Scaling

In 1977, Charles and Ray Eames released a short film for IBM called Powers of Ten.

The film opens with a couple picnicking on a blanket in Chicago and zooms out—every ten seconds, the field of view increases by a factor of ten.

We move from the intimacy of a lakeside lunch to the edge of the observable universe, then plunge back down through the skin of a hand into the subatomic architecture of a carbon atom.

The subtitle was “A Film Dealing with the Relative Size of Things and the Effect of Adding a Zero.”

It was a meditation on scale, suggesting that as we add zeros to our perspective, the very nature of what we are looking at transforms.

Today, with AI, we are living through a new kind of “Powers of Ten” journey, but the zeros aren’t being added to meters; they are being added to tokens.

I recently read a reflection by Azeem Azhar where he chronicled his shift from using 1,000 AI tokens a day to nearly 100 million. In the Eames’ film, adding a zero moved you from a park bench to a city, then to a continent. In the world of Large Language Models, adding a zero moves the AI from a novelty to a tool, then to a collaborator, and eventually—at the scale of 100 million—to something resembling a “workforce.”

“At 100,000 [tokens], a collaborator. At 1 million, I was building workflows. At 10 million, processes. At nearly 100 million – something closer to a workforce.”

This shift is more than just “more of the same.” It is a phase change.

When the Eames’ camera zoomed out to $10^{24}$ meters, the Earth didn’t just look smaller; it disappeared into a texture of galaxies.

When we scale our interaction with intelligence by several orders of magnitude, the “picnic” of human cognition—the way we think, draft, and create—is no longer the center of the frame.

At the 100-million-token-day scale, we aren’t just “using” AI. We are orchestrating vast, invisible ecosystems of thought. We are seeing companies like Spotify where top developers reportedly haven’t written a line of code in months, instead directing systems that ship features while the humans review the output from their phones.

We have added so many zeros that the “relative size” of human effort has changed.

The chilling yet beautiful thing about Powers of Ten was the realization of our own insignificance in the face of the cosmos, balanced by the intricate complexity found within our own cells.

As we zoom out into the “Token-Verse,” we face a similar existential pivot. If an AI can process a hundred million tokens of “thought” in a day—a volume no human could read in a lifetime—what does it mean to be the “author” of our lives?

The answer, I suspect, lies back on the picnic blanket.

The Eameses knew that while the scale of the universe is staggering, the meaning is found in the connection between the two people on the grass.

As we add zeros to our digital capabilities, our value shifts from the production of tokens to the intention behind them.

We are no longer the builders of the cathedral; we are the ones deciding why the cathedral needs to exist at all.

We are moving from the era of the “Worker” to the era of the “Architect” or maybe just the “Witness.”

Categories
Business

The Geometry of Focus: Finding the Limiting Factor

In the modern landscape of high-stakes management, there is a recurring temptation to solve everything at once. We are taught to optimize across the board—to improve efficiency by 2% here, 5% there—until the entire machine hums. But in a recent conversation with John Collison and Dwarkesh Patel, Elon Musk repeatedly returned to a single, almost obsessive mantra: the “limiting factor.”

It is a deceptively simple phrase. It suggests that at any given moment, there is one specific bottleneck that dictates the speed of the entire enterprise. If you aren’t working on that, you aren’t really moving the needle. You are merely polishing stuff.

“I think people are going to have real trouble turning on like the chip output will exceed the ability to turn chips on… the current limiting factor that I see… in the one-year time frame it’s energy power production.”

Musk’s management technique is not about broad oversight; it is about a radical, almost violent prioritization. He looks at the timeline—one year, three years, ten years—and asks: What is the wall we are about to hit? Right now, it might be the availability of GPUs. In twelve months, it might be the physical gigawatts of electricity required to plug them in. In thirty-six months, it might be the thermal constraints of Earth’s atmosphere, necessitating a move to space.

This approach requires a high “pain threshold.” To solve a limiting factor, you often have to lean into acute, short-term struggle to avoid the chronic, slow death of stagnation. John Collison noted this during the interview:

“Most people are willing to endure any amount of chronic pain to avoid acute pain… it feels like a lot of the cases we’re talking about are just leaning into the acute pain… to actually solve the bottleneck.”

For many leaders, the “limiting factor” is often something they aren’t even looking at because it lies outside their perceived domain. A software CEO might think their limit is talent, when it’s actually the speed of their internal decision-making. A manufacturer might think it’s raw materials, when it’s actually the morale of the factory floor.

To manage by the limiting factor is to admit that 90% of what you could be doing is a distraction. It is a philosophy of subtraction and focus. It demands that we stop asking “What can we improve?” and start asking “What is stopping us from being ten times larger?” Once you identify that wall, you throw every resource you have at it until it crumbles. And then—and this is the part that requires true stamina—you immediately go looking for the next wall.

By focusing on the one thing that matters, we stop being busy and start being effective. We stop managing the status quo and start engineering what may feel like the impossible.

Categories
AI Leadership

The Power of Two

I recently watched and thoroughly enjoyed Harry Stebbings’ interview with OpenAI’s Sam Altman (CEO) and Brad Lightcap (COO). In addition to gaining new insights into OpenAI’s evolution, their conversation covered a wide range of topics regarding the future of AI and its implications for society and new ventures.

One of the most fascinating aspects was the dynamic between Altman and Lightcap — hearing them discuss their respective strengths, weaknesses, and how those translate into their roles at OpenAI. It’s uncommon to witness a dual interview like this, with two colleagues who have clearly worked together for years and have complete confidence and trust in each other’s judgment and insights.

Throughout my involvement with various small companies, I wish I could have experienced such a powerful duo! In my experience, it’s not uncommon for the CEO to dominate the senior management team’s dynamics. While this sometimes works well, I’ve also seen it lead to reduced performance or frustration among senior managers due to the CEO’s actions.

Altman and Lightcap (and OpenAI by extension) appear to have a much more synergistic working relationship — effectively amounting to a co-equal division of responsibilities. I highly recommend watching this conversation for anyone involved in a startup aiming to scale quickly and effectively! Congratulations to Harry Stebbings for his hosting this excellent conversation with two key individuals leading the evolution of AI!