Categories
Computers FORTH IBM Programming

The Architecture of the Stack

Back in the early 1980’s when I worked for IBM, I was able to acquire my own IBM PC and experience my own form digital frontierism. Today I really wish I had a logbook at hand with a record of everything I did as my ability to recall those details has faded with age. A couple of those memories that still do remain with me involve two obscure languages: APL and FORTH. And then there was Borland Turbo Pascal.

In those early days of the 1980’s, memory wasn’t an infinite field; it was a precious, finite resource. While most of us were content living with the structured guardrails of BASIC, there was a subset of us drawn to the elegant, stripped-back world of FORTH.

Learning FORTH felt less like coding and more like learning a new way to breathe. It was lean. It was efficient. It stripped away the overhead of high-level syntax until it was just you, the dictionary, and the stack. There was an honesty to it—no hidden abstractions, just a direct conversation with the hardware.

Then, of course, there was the hurdle of Reverse Polish Notation (RPN). Grokking the stack meant rewiring your brain. You couldn’t just state an operation; you had to prepare the world for it first. You pushed your data onto the stack, one piece at a time, and only then did you call the action. It was a rhythmic, almost percussive way of thinking: Input, input, act.

“In FORTH, you don’t just write programs; you build a language to solve the problem.”

This “bottom-up” philosophy changed the relationship between the creator and the machine. You weren’t just a user; you were an architect of your own vocabulary. To define a new “word” in FORTH was to permanently expand the capabilities of your environment. It was a recursive journey where every small success became a building block for the next complexity.

Looking back, those days with the IBM PC and the stack weren’t just about efficiency. They were about the discipline of clarity. When resources are limited, your thinking must be precise. The difficulty of RPN wasn’t a bug—it was a feature that forced you to understand the flow of data at its most fundamental level.

Categories
AI

The Ghost in the Spreadsheet

There is a specific kind of quiet that descends when a tool finally disappears into the task. We saw it with the cloud—once a radical, debated concept of “someone else’s computer,” now merely the invisible oxygen of the internet. We saw it with Uber, moving from the existential dread of entering a stranger’s car to the thoughtless tap of a screen.

In a recent reflection, Om Malik captures this shift happening again, this time with the loud, often overbearing presence of Artificial Intelligence. For years, we have treated AI like a digital parlor trick or a demanding new guest that requires “prompt engineering” and constant supervision. But as Om notes, the real revolution isn’t found in the chatbots; it’s found in the spreadsheet.

“I wasn’t spending my time crafting elaborate prompts. I was just working. The intelligence was just hovering to help me. Right there, inside the workflow, simply augmenting what I was doing.”

This is the transition from “Frontier AI” to “Embedded Intelligence.” It is the moment technology stops being a destination and starts being a lens. When Om describes using Claude within Excel to model his spending, he isn’t “using AI”—he is just “doing his taxes,” only with a sharper set of eyes.

There is a profound humility in this shift. We are moving away from the “God-in-a-box” phase of AI and into the “Amanuensis” phase. It reminds me of the old craftsmanship of photography, another area Om touches upon. We used to carry a bag full of glass lenses to compensate for the limitations of light and distance. Now, a fixed lens and a bit of intelligent upscaling do the work. The “work” hasn’t changed—the vision of the photographer remains the soul of the image—but the friction has evaporated.

However, as the friction disappears, a new, more haunting question emerges. If the “grunt work” was actually our training ground, what happens when we skip the practice?

“The grunt work was the training. If the grunt work goes away, how do young people learn? They were learning how everything worked… The reliance on automation makes people lose their instincts.”

This is the philosopher’s dilemma in the age of efficiency. When we no longer have to struggle with the cells of a spreadsheet or the blemishes in a darkroom, we save time, but we might lose the “feel” of the fabric. Purpose, after all, is often found in the doing, not just the result.

As AI becomes invisible, we must be careful not to become invisible along with it. The goal of augmented intelligence should not be to replace the human at the center, but to clear the debris so that the human can finally see the horizon. We are entering the era of the “invisible assistant,” and our challenge now is to ensure we still know how to lead.

Categories
Books Half Moon Bay Living Photography Photography - Fujifilm X-T1 Quotations

Less but better.

Less But Better

I’ve been enjoying reading Greg McKeown‘s new book “Essentialism” – and, after listening to the beginning, put together this image suitable for desktop or screen saver use. It’s a shot made in the kitchen at the James Johnston House in Half Moon Bay – and was one that seemed to focus on the essential!

Here’s a link to Greg’s book and perhaps an easier to download version of my image on Flickr.