You’re right, but I also use codex at work to create Chrome extensions from scratch that automate processes.
I see the limitations and have encoutered them trying to develop more complex programs for work.
It’s great for creating chrome extensions or scripts that help me tremendously at work. It’s still not good enough to let me, a complete beginner, create an app for work that would replace a service my boss pays 100€ a month for. (For now at least, I haven’t given up).
I’m also trying to develop a Deltarune like game on Godot using Codex, to see how far the tools currently go, I don’t intend to publish o montetize it of course it’s just a passion project among friends.
One year ago trying to use AI to setup Plex completely wrecked my mini-PC and I had to reset it, now it does everything by itself and I just supervise.
I wouldn’t bet against it is all I’m saying.



A calculator lets people get useful results without understanding how arithmetic is implemented internally. That doesn’t make calculators bad; it means the required expertise depends on the stakes. I wouldn’t want someone designing a bridge who doesn’t understand engineering. But I also wouldn’t tell someone calculating a grocery discount to learn numerical methods first. That’s how I see AI coding: if I can make a small tool that solves my problem, test it, and verify it works, “you don’t understand the implementation deeply enough” isn’t automatically an argument against the tool. Otherwise you can make the same argument against basically every abstraction in computing.
I see your argument and I think there’s value in the concern. AI absolutely can let people build things they don’t understand, and that can become a problem when the stakes are high.
Where I disagree is treating that as a reason to oppose the abstraction itself. I think you’re focusing entirely on what gets lost when the barrier to entry drops, while ignoring what becomes possible for people who previously couldn’t participate at all.