Your experiences must be much different from mine.

Three years ago, AI was barely able to provide sort-of reliable command completion.

Two years ago, it could extrapolate a single function from a docstring - but the docstring had to be so verbose that it wasn't practical to use in that way.

A year ago, I was tinkering with Devin to try to find a way to get it to reliably implement small, isolated features from verbose Jira tickets.

Six months ago, I started using AI to generate the majority of my code output. Most of my time was spent reviewing, and I was ecstatic to reach ~2x output because I could run the next task while reviewing the last.

Now, at work I'm managing a half dozen Claude Code instances, Devin sessions, and orchestrating a review loop between Claude, Devin, and CodeRabbit. It's not uncommon for me to be working on four or more discrete features at once. My output is approximately 15x my pre-AI baseline - and I've not sat down and written a line of code directly in six months.

At home I'm managing a Hermes agent that can spin up a whole fleet of purpose-tuned agents for whatever purpose I'd like. I've implemented spec-driven development a'la Acai, and extended it to the point that my agent creates specs from text or voice conversation, I review them, and it handles implementation end-to-end. The code itself is an almost disposable artifact - useful primarily to ensure no regressions have been introduced between rounds.

... I simply don't understand how you can assert that "it's been basically the same for 3 years". It absolutely has not.