I freelance too and I have been struggling personally for a while for other reasons but I absolutely recognise this. I have only about eighty lines of code in production that I fully did not write (thanks Muse Glimmer).

The difference between corporate salaried programming and freelance programming is who is on the hook in a direct sense for the bug the LLM introduced, or for maintaining the massive pile of code or the cognitive burden of ownership.

My experience of freelancing is that most of the people I am competing against for the work care less about the code (and things like quality, security, appropriateness, user burden), are faster, are happy to nickle-and-dime the bill, will charge more to fix their own bugs, churn out meaningless requirements specs that they cannot stick to, and rely on lack of client knowledge to get through.

So there has always been a problem of competing against the slapdash; they always win the quote. I care about longer-term maintainability, cost control and quality, and I lose out because of it. (I'm often asked to maintain or finish the work of people who beat me to the quote and then failed; nowadays I say no.)

The problem is, those people now use LLMs. For the immediate future, LLMs may actually be improving their output, certainly at the prototype stage, and they will now be including one-shot, vibe-coded demos with their quotes.

So what is a freelancer who still has a sense of ethics to do?

The long bet is that those people who do not care for quality will still be disappointing their clients, but how do you avoid using LLMs while still getting, at least, back to where you were in competing with them?

I love it, although in my experience, one needs very strict agent rules that tightly define how the AI should develop. The problem is that 1) these rules take a lot of effort to build and 2) AIs always overengineer, complicate, overstructure, overdesign… ;)