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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.”

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AI Work

Why IBM is Hiring Beginners

There is a pervasive anxiety humming beneath the surface of the modern workplace—a quiet, collective fear that the bottom rungs of the corporate ladder are being systematically sawed off by artificial intelligence.

The common wisdom, echoed in countless op-eds and boardroom whisperings, is that entry-level jobs are the natural prey of the Large Language Model.

The tasks of summarizing, drafting, formatting, and basic coding are easily consumed by algorithms. If a machine can execute the rote labor of a junior analyst in three seconds, why hire the junior analyst at all?

It is a seductive, mathematically appealing logic, especially in an era of tightening belts and efficiency mandates.

Consequently, we are witnessing a landscape where many tech companies are quietly, or sometimes loudly, slashing their junior roles to lean on AI.

But amidst this trend, an alternative approach emerges that feels almost rebellious in its long-term optimism.

IBM, a legacy titan that has weathered every technological revolution of the past century and where I started my career, is leaning entirely the other way. Rather than cutting, they are reportedly tripling their entry-level hiring.

Reflecting on this strategy, IBM’s chief HR officer noted:

“The companies three to five years from now that are going to be the most successful are those companies that doubled down on entry-level hiring in this environment.”

This perspective is profound because it challenges the very premise of what an entry-level employee actually is.

The prevailing, perhaps cynical, view treats a junior worker merely as a unit of basic output. If you view a beginner only as a spreadsheet compiler or a draft-writer, then yes, they appear redundant in the face of AI.

But what if we view the entry-level role not as a terminal function, but as an apprenticeship?

When we hire a beginner, we aren’t just buying their immediate, unpolished labor. We are investing in a trajectory.

We are bringing them into the fold so they can absorb the tacit knowledge of the organization—the unwritten rules, the cultural nuances, the complex, human art of navigating institutional friction.

An AI cannot learn the subtle interpersonal dynamics of a specific team, nor can it develop the intuition that comes from failing, recovering, and being mentored by a seasoned veteran.

If we automate away the entry-level, we effectively destroy the incubator for our future mid-level and senior leaders. Where will the experienced managers of 2030 come from if no one is allowed to be a beginner in 2026? You cannot suddenly parachute someone into a senior role and expect them to possess the deep, intuitive judgment that is only forged in the crucible of early-career trial and error.

The institutional memory breaks down.

IBM’s strategy recognizes a crucial reality: AI shouldn’t replace the beginner; it should accelerate them.

Imagine a junior employee who isn’t bogged down by mindless grunt work, but instead is handed the tools to instantly bypass the mundane. They can spend their foundational years analyzing, questioning, and engaging in higher-order problem-solving alongside their mentors. They transition from data-gatherers to hyper-learners.

By doubling down on human potential in an age of artificial intelligence, companies are making a strategic bet on the one asset that cannot be replicated by a server farm: the evolving, adapting, and deeply creative human mind.

The most successful organizations of the near future won’t be the ones with the fewest employees and the most algorithms; they will be the ones that used algorithms to cultivate the most formidable, deeply experienced human talent.

The ladder hasn’t been dismantled. It has merely been redesigned.

The only question is whether we have the foresight to keep inviting people to climb it.

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Uncategorized

The Power of the Handwritten Note

In an era dominated by digital communication, the handwritten note stands out as a powerful and increasingly rare form of expression. The simple act of putting pen to paper carries a weight and significance that makes it a potent tool for both personal and professional communication. We can all appreciate their enduring charm and delightfulness.

During my tenure at IBM years ago, one of the most delightful aspects of being a manager was the provision of personal stationery. This wasn’t just any paper; it was a statement of elegance and personal touch. Smaller in size, cream-colored, and boasting a luxurious texture, each sheet bore my name engraved on the letterhead, conspicuously lacking any IBM logo. This stationery was designed for a specific purpose: to maintain the long-held company tradition of writing personal notes to colleagues and associates.

The power of a handwritten note lies in its inherent personal touch. When someone takes the time to write by hand, they invest a part of themselves into the message. The unique curves and strokes of their handwriting, the choice of words, and even the occasional crossed-out phrase all contribute to a sense of authenticity and intimacy that cannot be replicated by typed text. This personal investment communicates to the recipient that they are truly valued and special.

Receiving such a note was always a delight. Many of us kept these notes in special file folders, occasionally taking a few minutes to flip through them, reliving important moments and feeling a renewed sense of appreciation. These tangible and physical mementos have a quality that digital messages simply cannot match.

As the years have passed, the custom of sending personal notes has faded, replaced by the convenience of digital communications. This shift has only served to enhance the impact of handwritten notes. Receiving a handwritten note today feels like discovering a treasure. Such a note stands out precisely because it isn’t instant, digital communication.

The act of writing by hand also benefits the sender. The slower pace of handwriting compared to typing allows for more thoughtful composition. It encourages the writer to choose their words carefully and reflect on their message.

As we’ve been grappling with the impact of AI tools on various aspects of our lives, handwritten notes also serve as a bastion of genuine human expression. The act of writing by hand removes the temptation to rely on AI-generated text for our most personal communications. When we put pen to paper, we directly confront our own thoughts and emotions, as we find our own words to express what we truly feel.

Moreover, handwritten notes also provide a level of privacy and intimacy. Unlike emails or text messages, which can be easily forwarded or shared, a handwritten note is meant for the eyes of the recipient alone. This exclusivity adds to the special and personal nature of the communication.

Whether expressing gratitude, offering condolences, or simply saying “hello”, the act of putting pen to paper creates a moment of pause in our hectic lives for both the sender and and recipient providing a moment to reflect, to connect, and to affect another person’s life in a delightful and meaningful way. Special creations for special people in our lives!

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Fujifilm X-T1 Living Photography Photography - Fujifilm X-T1

Memories of My Early Days at IBM

IBM System 360 Model 30 - Computer History Museum - 2014

Yesterday we taught a Bitcoin payments workshop at the Computer History Museum in Mountain View. It was fun talking about the future of payments and virtual currencies in such a setting – with rooms full of vintage hardware on the floor below! It also reminded me that we need to be thinking about creating a “Payments History Museum” someplace on the planet!

The new Revolution exhibit at the Computer History Museum is stunning – beautifully laid out and thematically organized. One of the areas is devoted to “Mainframes” – and, as I came into that area, this IBM System/360 Model 30 was on display.

I have many fond memories of the Model 30 – I probably logged more hands-on datacenter time on the Model 30 than any other mainframe. While it was primarily a DOS machine, I’d also put together a trimmed down version of OS/360 which I could also run in the limited memory of the Model 30.

Seeing this “beauty” brought back lots of memories!…

Both of these images were quickly grabbed with a Fujifilm X-T1.

Think - Computer History Museum - 2014