The AI Coding Rorschach Test

01 Nov 2025

“Today, more than a quarter of all new code at Google is generated by AI, then reviewed and accepted by engineers. This helps our engineers do more and move faster.”

— Sundar Pichai, Forbes

If you work as a software engineer, you’ve probably seen many statements like this recently. They’re vague enough to be interpreted in a hundred different ways, and may even be saying nothing at all. But I’ve noticed that reactions to these statements tend to fall into two broad categories.

Two Perspectives

This diagram is an oversimplification, but it illustrates two ways to interpret this kind of statement.

Perspective 1 reflects a zero-sum mindset that views coding as a static block of “work” to be done. It imagines the job of software engineering as shoveling a pile of dirt. If AI is shoveling 25% of the dirt, then you now need only 75% of the engineering capacity.

This is an uninformed view, but it’s understandable to feel this way, especially if you’re inexperienced or struggling to find a job. The media amplifies this narrative because executives want to communicate it to investors. Massive layoffs can then be spun as “embracing AI” rather than as the result of overhiring during ZIRP or shrinking profit margins.

Perspective 2 is closer to how companies actually operate. It’s important to understand that code itself has no inherent value; it’s an enabling input. It’s a resource that produces value only once it’s compiled, deployed, and integrated into real systems. Economically, code has similar properties to other enabling inputs like energy.

First, it exhibits a property of non-satiation. Even at the company level, there is a nearly infinite demand for code. The amount of code a company writes is proportional to its capacity to produce code, not its demand to consume that code. We know this is true because we’ve been making coding more efficient for decades, yet demand continues to grow. This likely reflects a form of Jevons Paradox and will continue on into the future.

Second, the efficiency of code, kind of like energy, is highly elastic. A lightbulb at the turn of the century required far more watts to produce the same light output. Code is even more dynamic. As a thought experiment, imagine writing millions of lines of code that accomplish the same thing as a single line. It’s so easy to write wasteful code. The amount of code you have says nothing about the value it creates.

Conclusion

If you’re new to the industry or an outsider, you should resist all the market forces that want you to doom spiral into a zero sum mindset. We’ve seen this play out for decades: a world in which coding is easier and more abundant creates more value for the world; and being a software engineer allows you to capture that value. Even if your slice may be proportionally smaller, it will still grow as the pie becomes much bigger.