Automatic Programming, Again

Embracing the next phase of programming

Time is a flat circle.

I read Grace Hopper and The Invention of the Information Age a few years ago. In the 1950s she introduced the first compiler—a program to translate human-friendly, English-like code into machine code. It was a paradigm shift, one that provoked immediate negative reaction:

Reflecting on the negative reactions of some of her fellow programmers, Hopper expressed the belief that arguments focusing on “efficiency” and “creativity” covered far baser motivations: “Well, you see, someone learns a skill and works hard to learn that skill, and then if you come along and say, ‘you don’t need that, here’s something else that’s better,’ they are going to be quite indignant.” In fact, Hopper felt that by the mid 1950s many programmers viewed themselves as “high priests,” for only they could communicate with such sophisticated machines. They served as the intermediaries between user and computer, and automatic programming jeopardized their exclusive position.

These days, no one bats an eye at using compiled languages. We’ve been using Dr. Hopper’s invention to more efficiently write code for decades. Much like the days before her invention of the compiler, writing code today is deep knowledge work. Still, software engineers act as “intermediaries between user and computer.”

Time is a flat circle.

We find ourselves, again, at a clear paradigm shift. By the late 1950s, I bet you could have said the same about compilers as we now say about AI. And much in the same way as those PhD mathematicians writing machine code ultimately had to think more abstractly, we’ll have to shift our thinking. We’ll have to step back from hand-typing every single line of code (minus handy command-line generators) to engaging with AI agents at a more abstracted level.

Time is a flat circle.

Why, now, should we keep building the same old directory structures, tweak migrations, or fiddle with broad-strokes of data models? Let the agents do that, so our deep knowledge work can focus on the trickiest of the tricky—let’s say the 5% of a project where reasoning and creativity matter most.

The LLM is the new compiler.

The agent, the new high-level language.

And we’re about to see a new degree of productivity echoing the gains brought on by Dr. Hopper.

Time is a flat circle.