I think this is the clearest example of: exceptions don't make the rules.

Author might be a vibe coder, designer or someone who does not do really heavy and complicated development, maybe some api here and there.

But it is pretty obvious that a very concerned engineer would not allow any of that, for critical systems.

I have two years of copy pasta from Reddit pre-AI. Does that count?

Completely agree with your first paragraph and a point I've made repeatedly here is that I want agents to work more like pair programming and less like code review. I want to delegate typing, not thinking.

But what I've noticed is that lots of people don't want that. They're happy to delegate both typing and thinking.

There are folks who still want to think for themselves of course, but model providers are incentivised to maximise token spend over all else, so the "official" harnesses are not aligned with their needs. My message to those folks is: _go and build your own harnesses_.

I built one, it wasn't a huge lift and it completely changed how I work with LLMs. One consequence is that I choose smaller, cheaper models now because latency is more important with shorter feedback loops. I don't want a super-intelligent model that disappears for ages and provides a final answer, my own brain thinks and guides the process instead.

I'm deliberately not linking to my harness here because that's not the point. Think about what modes of work you want from a coding harness, then build one that works exactly like that. Immense happiness and satisfaction is just a couple of weekends away.

Are you following more of an “aider” type approach, or something different?

I did everything by hand for so long and miss it, now I just read thousands of lines day in day out. But there are interesting gains such as lowered barrier to quickly run adhoc perf tests, do some formal verification, you can just add more guardrails for the thing that gets shipped. The thing I hate though is when managers sell their generated code and you are left shoehorning it to production, they take away the interesting part of the job.