[montfort]

The profession has already changed. For the past eight months, AI has been competent enough to code like the best human programmer, but strangely, the software isn't any better yet. Everyone has lost sight of what the profession truly is. It's not just about coding; it's about software engineering. Our role is no longer that of programmers, AI has taken over that role. Our role is that of engineers who manage programming agents. Every attempt to have AI develop a medium-to-large project fails because the goal is to solve everything with a magic four-line prompt. We're forgetting the structural aspect, the engineering side. We must treat the tool as just that: a tool. The direction and responsibility remain in our hands. It's not about reviewing the code line by line; it's about ensuring that the product faithfully represents a well-planned engineering intent. That's why the concept of AI-augmented Software Engineering is so important.

[jdlshore]

> AI has been competent enough to code like the best human programmer

It’s really not. Opus 4.8 can’t produce good software design and it still makes straightforward implementation mistakes. Two errors it made in one day for me recently: it built the Cookie class I asked for without a name field—cookies have a name and a value—and it neglected to handle a case where a database could have multiple rows with the same id, just returning whatever came back first.

The “best human programmers” absolutely would not have made those mistakes. At worst, they would have asked if I really meant what they thought I meant.

[montfort]

I understand your point, but what you're describing is exactly the kind of mistake even the best human programmer could make in a poorly managed environment. I'm concerned that since AI emerged, we've overestimated our programming abilities. The comparisons we make between our own work and AI are based on an assumption of absolute perfection that doesn't exist in reality. Bugs aren't an invention of AI; they're ours. All modern software engineering, testing systems, version control systems, and so on, were developed through years of dealing with our own mistakes. We don't make systems fault-tolerant by understanding that failures are external to our work. These failures are our doing, and now they're AI's doing too. We have to deal with applying to those agents the management that we previously applied among ourselves. The example you provide is very good, because you yourself, with your human mind that solves problems, suspect that the origin of the problem was poor communication, and you are very likely right, but just as if it were a human error, the programmer is responsible for their faulty code, but you are responsible for poor process management, and yes, the same applies to working with AI agents.