Programming Deflation

The genies are out of the bottle. Let’s take as a given that augmented coding is steadily reducing the cost, skill barriers, and time needed to develop software. (Interesting debate to be had—another day.)

Will this lead to fewer programmers or more programmers?

Economics gives us two contradictory answers simultaneously.

• Substitution. The substitution effect says we'll need fewer programmers—machines are replacing human labor.

• Jevons’. Jevons’ paradox predicts that when something becomes cheaper, demand increases as the cheaper good is economically viable in a wider variety of cases.

Both can't be right. Or can they?

Another way of looking at the contradiction—if programs are cheaper to write today than they were yesterday, then we should be more likely to write them today. But, if programs are going to be cheaper to write tomorrow, then why not just wait until the cost goes to zero? This is the deflationary spiral, the urge to defer investment leading to less economic activity leading to lower prices leading to the urge to defer investment.

What’s a software executive to do? A programmer? What we’d like is a strategy that:

• Let’s us act today.

• Doesn’t rely on information that just not available.

• Leads to reasonable outcomes regardless of which way the rock tumbles.

But Wait, This Feels Different

Traditional deflation is destructive because it reflects economic weakness—falling demand, broken confidence, shrinking money supply. Programming deflation is different. It's driven by genuine productivity gains. AI isn't just redistributing the same pie; it's making the pie-making process fundamentally cheaper.

This creates some interesting paradoxes:

Delay vs. Experiment: Yes, you might wait for better tools. But when experimentation costs approach zero, the urge to try something right now often wins. How many of us have spun up a quick prototype just because we could?

Quality Bifurcation: Cheap code floods the market. Most of it is terrible. But the gap between commodity code and carefully crafted software widens. The middle disappears.

Value Migration: Writing code becomes like typing—a basic skill, not a career. Value moves to understanding what to build, how systems fit together, and navigating the complexity of infinite cheap software pieces.

The Acceleration Effect

Here's where programming deflation breaks the traditional model entirely. In economic deflation, the spiral is self-reinforcing and destructive. In programming deflation, cheaper tools might actually accelerate innovation—when programming accelerates programming. Better tools. Better models. The reinforcing loop kicks in.

Every small business becomes a software company. Every individual becomes a developer. The cost of "what if we tried..." approaches zero.

Publishing was expensive in 1995, exclusive. Then it became free. Did we get less publishing? Quite the opposite. We got an explosion of content, most of it terrible, some of it revolutionary.

Living in the Spiral

So what do we do while we're in this deflation? A few thoughts:

Embrace the Commodity: Use the cheap tools. Build the obvious stuff with AI. Save your energy for the hard problems.

Focus on Integration: The bottleneck isn't writing code anymore. It's making all these cheap software pieces work together coherently.

Develop Taste: When anyone can build anything, knowing what's worth building becomes the skill.

Think in Systems: Individual programs are commoditized. Complex, adaptive systems are not.

The New Scarcity

In a world of abundant cheap code, what becomes scarce? Understanding. Judgment. The ability to see how pieces fit together. The wisdom to know what not to build.

We're not just experiencing technological change. We're watching the basic economics of software development transform in real time. The question isn't whether programming deflation will happen—it's already happening. The question is how we adapt to abundance.

Hedging Our Bets

Here's the beautiful thing about focusing on understanding, integration, and judgment: these skills matter whether we end up with fewer programmers or more programmers. If automation replaces routine coding, these human skills become the differentiator. If cheap tools create an explosion of new programmers, these skills separate signal from noise even more than they did a year ago.

Cultivating judgement also improves one’s competitive position vis a vis those who use the tools simply to churn out the same features faster.

Don’t bother predicting which future we'll get. Build capabilities that thrive in either scenario.

Interested in a private, custom talk for your organization on the effects of AI on software development & how y’all can navigate them? Contact me! I still have some slots open in the last quarter of the year.

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