The Problem With the AI Layoff Narrative

Block, the company behind Square, Cash App, and Afterpay, is cutting almost half its staff, and far too many articles about it claim that it's due to AI efficiencies. It's not. It's about reckless overhiring during the pandemic, and correcting for it.

The common narrative is outwardly compelling: If a company needed X employees and, thanks to AI, those employees are now twice as effective, then it only needs X/2 employees to achieve the same outcome. Therefore, it can now save money by firing half its workforce.

Except that makes no economic sense. It requires us to accept that there's only a fixed amount of software engineering to be done, no new ideas, no unfinished business, nothing in the backlog of things to get around to eventually if only resources weren't so tight.

Well, now, with AI, resources aren't so tight. The ROI of each engineer is (or at least should be, if we believe the headlines), is through the roof. If anything, you want more engineers now:

Imagine listing all the ideas for features and products. They have a projected value and a projected cost, the ratio of which gives you the projected return on investment (ROI). Sorting by ROI from highest to lowest, as we go down the list, eventually we'll reach a crossover point, below which it makes no economic sense to build the feature.

Now, imagine cutting the cost in half. What happens to the crossover point? It moves much further down the list. Suddenly, it makes sense to build a lot more features than before. Features that had marginal ROI are now no-brainers. At the very least, you'll want to hold on to your existing team and reap the benefits of their increased value. Maybe you should even look into hiring additional ones!

A company's value-creating workforce is its most important investment. When that investment achieves a higher yield, you don't let it go; you double down on it.