There has always been a lot of contention between developers and management, they seem to fight with each other for position and leverage like a wrestling match.

Its usually IT / Dev management and business management, and the devs get a lot of collateral damage.

But AI has introduced something new to this struggle, its removed the fun of coding and the accomplishment of craft. Now both sides feels like they can use AI to replace the other, where managers are taking up coding and coders are becoming their own companies. And while that adds more grist for the mill, the customers are thinking they’ll replace both and just code and manage their own applications.

That is a lot of uncertainty, and the promise of being able to make a killer app is democratized but that means the ability to make lots of money at it is much more improbable.

Uncertainty and how the game has changed from sporting contest to win or lose high stakes, just makes this not fun anymore.

I’ve been thinking of all the places computers have democratized industries. Music is produced by someone on a laptop now more than a collective group of practicing and talented performers. 3d printing produces objects of great sophistication without really any craft skills at all. Chess is a bigger industry now than it was, and no one can beat a computer.

But even then, sports have been something that anyone can participate in to various degrees, yet we still admire people who reach the pinnacle of performance.

Before starting my own aquarium, a wise person said “Aquariums aren’t about keeping fish, they are a hobby for people who like to keep water, and the fish are just enjoying that”. Every craft, every sport, every performance has practice and maintenance that itself has to bring the enjoyment, the puzzle, and the promise.

I see that for programming. It will be for someone who desires the craft of computing more than the outcome of the application, and they will achieve things that are simply beautiful. Because they love the craft.

Nice article, thanks. I like how the writer came up with an economic metric for understanding code review in terms of dollars in proportion to the volume of code.

That is the right way to discuss this with upper management.

The other barrier is the illusion of objectivity. In the other comments, and in many programmers experience with AI, there are code short cuts and issues that are objective in that no one would disagree with their value and importance, but they are subjective in that they cannot be described so cleanly that an LLM or human can’t misunderstand them. That it can be described so perfectly as to be findable 100% with no false positives or missed positives.

And then on top of that are the purely subjective goals like ‘simplicity’. Give programmers the goal of simplicity and they wind up simply pushing the complexity onto someone else’s desk. LLMs (subagents, etc…) are even worse at that.

And it goes all the way up and down, the more you elevate or granulate to architectural decisions or algorithmic decisions, different illusions appear.

Code Review has never really been 100% successful, nor has Quality Control/assurance, Testing, or any other measure. At best it just forces people to look at code with another perspective to hopefully distill myth from reality. And that is itself valuable, if not for being able to show due diligence and effort.

Which brings us back to the article’s equation of value. Given production, liability, are calculated in business terms from the real dollars spent or projected to be spent holds up, its a good start, no?