Part 3 of 4 of The Narrow Part Is Moving. Each part has its own short video.

Cheaper code means more work, not less

In 1865 an economist named William Stanley Jevons noticed something that annoyed the efficiency optimists of his day. Steam engines had become much more efficient with coal. Britain’s coal consumption had gone up, not down. Cheaper work made more uses worth doing.

Code is now on the same curve. When a feature costs a day instead of a month, a whole class of software suddenly becomes worth building: software for problems that never justified a team. A tournament companion for parents. A research agent for one person’s accounting questions. A keeper for a machine that runs a dozen projects. None of these would have existed five years ago, because nobody would have staffed them.

And every one of them arrived with its own deciding, checking and adopting. More software means more specifications, more verification, more organisations deciding whether to trust something new. The work doesn’t disappear. It moves to a different place.

That’s how I read the fear about jobs. The fear assumes a fixed amount of work to be shared out between people and machines. That assumption has been wrong for every general-purpose technology I know of. It will be wrong again, though, as I’ll come to, “wrong on the total” is not the same as “harmless”.

No one gets to stand still

There’s a companion to Jevons that takes the comfort out of it. In 1973 the evolutionary biologist Leigh Van Valen proposed what became known as the Red Queen hypothesis, after Lewis Carroll’s line in Through the Looking-Glass: “it takes all the running you can do, to keep in the same place.” Species don’t get safer by surviving longer, because their competitors keep evolving too.

Everyone is getting the faster engine. The advantage it gives you is real and temporary. What doesn’t equalise is the part that isn’t being commoditised.

Here is my bet, and I’d rather name it as a bet than dress it up as a forecast. Writing code is drifting from craft towards commodity, the way electricity and compute did before it. Models that compete only on getting better at writing code are racing into that commodity. The gains that matter next will come from the stages around the code: specialists that go deep in one domain and check their own work against sources, and generalists that orchestrate, keep the instructions straight, and know when to ask a human.

The research agent I mentioned is the first kind. The keeper on my machine, and the shared improvement flow my projects now run on, are the second kind. Neither is impressive because it writes code quickly. Both are useful because they make the slow parts less slow.

What would prove me wrong? If, a year from now, the teams pulling ahead are the ones with the fastest code generation, and specification and verification have stayed exactly as hard as they are today. I’ll be watching.

← Part 2 · The full article · Part 4 →

Sources

  • William Stanley Jevons, The Coal Question (1865).
  • Leigh Van Valen, “A New Evolutionary Law”, Evolutionary Theory (1973); Lewis Carroll, Through the Looking-Glass (1871).

The panel that argued this series, and who inspired it: the full article.