Well probably we'd want a person who really gets the AI, as they'll have a talent for prompting it well.

Meaning: knows how to talk to computers better than other people.

So a programmer then...

I think it's not that people are stupid. I think there's actually a glee behind the claims AI will put devs out of work - like they feel good about the idea of hurting them, rather than being driven by dispassionate logic.

Maybe it's the ancient jocks vs nerds thing.

Speaking of tools, that style of writing rings a bell.. Ben Affleck made a similar point about the evolving use of computers and AI in filmmaking, wielded with creativity by humans with lived experiences, https://www.youtube.com/watch?v=O-2OsvVJC0s. Faster visual effects production enables more creative options.

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The pattern repeats because the market incentivizes it. AI has been pushed as an omnipotent, all-powerful job-killer by these companies because shareholder value depends on enough people believing in it, not whether the tooling is actually capable. It's telling that folks like Jensen Huang talk about people's negativity towards AI being one of the biggest barriers to advancement, as if they should be immune from scrutiny.

They'd rather try to discredit the naysayers than actually work towards making these products function the way they're being marketed, and once the market wakes up to this reality, it's gonna get really ugly.

The first electronic computers were programmed by manually re-wiring their circuits. Going from that to being able to encode machine instructions on punchcards did not replace developers. Nor did going from raw machine instructions to assembly code. Nor did going from hand-written assembly to compiled low-level languages like C/FORTRAN. Nor did going from low-level languages to higher-level languages like Java, C++, or Python. Nor did relying on libraries/frameworks for implementing functionality that previously had to be written from scratch each time. Each of these steps freed developers from having to worry about low-level problems and instead focus on higher-level problems. Mel's intellect is freed from having to optimize the position of the memory drum [0] to allow him to focus on optimizing the higher-level logic/algorithms of the problem he's solving. As a result, software has become both more complex but also much more capable.

(The thing that distinguishes gen-AI from all the previous examples of increasing abstraction is that those examples are deterministic and often formally verifiable mappings from higher abstraction -> lower abstraction. Gen-AI is neither.)

[0] http://catb.org/jargon/html/story-of-mel.html

If educators use AI to write/update the lectures and the assignments, students use AI to do the assignments, then AI evaluates the student's submissions, what is the point?

I'm worried about some major software engineering fields experiencing the same problem. If design and requirements are written by AI, code is mostly written by AI, and users are mostly AI agents. What is the point?

But less thinking is essential, or at least that’s what it’s like using the tools.

I’ve been vibing code almost 100% of the time since Claude 4.5 Opus came out. I use it to review itself multiple times, and my team does the same, then we use AI to review each others’ code.

Previously, we whiteboarded and had discussions more than we do now. We definitely coded and reviewed more ourselves than we do now.

I don’t believe that AI is incapable of making mistakes, nor do I think that multiple AI reviews are enough to understand and solve problems, yet. Some incredibly huge problems are probably on the horizon. But for now, the general “AI will not replace developers” is false; our roles have changed- we are managers now, and for how long?

Here's an archived link: https://archive.is/y9SyQ