> 75% of my workflow is generating documentation, at ever lower levels of abstraction, until it’s just code

Some might hate that writing code (which they enjoy) is turning into that, others might doubt the efficacy of doing that and the claims about it working so well.

Personally, I’d say that docs help as long as they’re meaningful and not too long (even AI tools have limited context), but you probably also want to codify what you can into code.

For example I wrote a tool in Go and goja called ProjectLint (not public yet but anyone can do that in a week) where you write custom rules in regular ECMAScript that can check whatever you want - code conventions across languages, project structure and architecture and all the stuff that goes under “In this project, we do X but don’t do Y” that just telling an LLM about (or colleagues) will be worth nothing (even memories and focus are limited), instead CI gates that.

I guess I reinvented a simplified and stack-agnostic version of ArchUnit but whatever, it works for me and I can use the same tool in Python and Java projects and elsewhere as well as parallelize all the read only checks and run sequentially the potential-write ones that might auto-fix stuff.

I’m sure it depends on the project, stack, and dev. I know loc is a terrible metric, but …

For me, my human only productivity in the firmware work I do is usually around 100-500 loc a day on good days. Obviously more when clean-slating the initial work on a project , but that’s typically a day or two and the same ratios apply.

With ai tools, I roughly 4x that with the same effort, or 2x it working lazily from my phone playing with my 2 year old.

The code is typically also more compact so the LOC metric is strong here IMHO.

Overall I have about the same number of bad-unproductive days, far less bugs (but worse bug hunts) and 10x better documentation lol.

Coding is definitely a different job though.