Hasta la vista, minutiae;

The way it should have always been

It’s not new for a piece of technology to emerge and threaten an entire sector of the economy. The Industrial Revolution did it. Robotics did it. History is full of similar moments.

What feels different about this GenAI-driven threat, though, is that this time we are the ones potentially being displaced. Knowledge workers. People who have contributed greatly to the demise of many other industries. Now our own livelihoods may be at risk because much of the work we’ve been doing could soon be handled almost entirely by machines.

Or could it?

Jensen Huang, the CEO of Nvidia (which, yes, is one of the companies benefiting from the current AI hype cycle), put it well in Davos earlier this year: we need to distinguish between a job’s purpose and its tasks. He used radiologists and nurses as examples, but the idea applies just as strongly to my people: engineers (software, quality, platform, data, you name it, but let’s use software engineers as a short-hand).

Even though historically our work has not been just about programming computers, i.e. writing instructions in a language a machine can execute, that specific aspect of software engineering has often become the center of attention because the process was so difficult.

It’s no surprise, then, that many engineers are nervous about GenAI’s ability to write most, if not all, of our code.

But writing code was never the purpose. Or at least, it shouldn’t have been.

I’ve worked with plenty of engineers who believed their primary value was the act of writing code itself. They were mistaken then, and they’re mistaken now. Our real purpose is to analyze problems, generate possible solutions, evaluate those options, implement one or more of them (this is where programming comes in), and then determine which one (if any) solves the problem best.

Implementation should never have been the centerpiece. It should have always been a detail, something mechanical that a machine could handle.

How many late nights have we all spent discovering that a bug was caused by a missing semicolon (damn you, JavaScript;), or that version 1.4.5 of Library A doesn’t work with version 2.8.7 of Library B? Is any of that fundamentally important to the people using the product we were building?

Of course not.

The painstaking act of assembling exactly the right characters, in exactly the right order, with exactly the right spacing was never the point. It was a necessity, a means to an end, a way to communicate intent to a machine.

We should celebrate that GenAI is finally freeing us from that minutiae. There are real pitfalls, and there’s still plenty of progress to be made, but the promise of GenAI for software engineering is undeniable. GenAI understands patterns. It understands syntax. And it’s increasingly good at understanding intent.

The GenAI era will be a golden age for true problem solvers: people who want to engage deeply with customers, who are curious about their domains, and who can articulate intent clearly enough to leave the implementation details to the machines.