[frankc]

I think we really need to have a serious think of what is "good quality" in the age of coding agents. A lot of the effort we put into maintaining quality has to do with maintainability, readability etc. But is it relevant if the code isn't for humans? What is good for a human is not what is good for an AI necessarily (not to say there is no overlap). I think there are clearly measurable things we can agree still apply around bugs, security etc, but I think there are also going to be some things we need to just let go of.

[Thanemate]

>But is it relevant if the code isn't for humans?

The implications to your statement seems to me that is: "you'll never have to directly care about it yourself, so why do you care about it?". Unless you were talking about the codebase in a user-application relationship which in this case feel free to ignore the rest of my post.

I don't believe that the code will become an implementation detail, ever. When all you do is ship an MVP to demonstrate what you're building then no one cares, before or after LLM assistance. But any codebase that lives more than a year and serves real users while generating revenue deserves to have engineers who knows what's happening beyond authoring markdown instructions to multiple agents.

Your claim seems to push us towards a territory where externalizing out thought processes to a third party is the best possible outcome for all parties, because the models will only get better and stay just as affordable.

I will respond to that by pointing out that, models that will ultimately be flawless in code generation will worth a fortune in terms of adding value, and any corporation that will win the arms race will be actually killing themselves by not raising the cost of access to their services by a metric ton. This is because there will be few LLM providers that actually worth it by then, and because oligopoly is a thing.

So no. I don't expect that we'll ever reach a point where the average person will be "speaking forth" software the same way they post on Reddit, without paying cancer treatment levels of money.

But even if it's actually affordable... Why would I ever want to use your app instead of just asking an LLM to make me one from scratch? No one seems to think about that.

[tiny-automates]

i've been building agent tooling for a while and this is the question i keep coming back to. the actual failure mode isn't messy code, agents produce reasonably clean, well-typed output these days. it's that the code confidently solves a different problem than what you intended. i've had an agent refactor an auth flow that passed every test but silently dropped a token refresh check because it "simplified" the logic. clean code, good types, tests green, security hole. so for me "quality" has shifted from cyclomatic complexity and readability scores to "does the output behaviour match the specification across edge cases, including the ones i didn't enumerate." that's fundamentally an evaluation problem, not a linting problem.

[mlaretallack]

This is where I think its going, it feels that in the end we will end up with an "llm" language, one that is more suited to how an llm works and less human.

[skydhash]

You can’t drop anything as long as a programmer is expected to edit the source code directly. Good luck investigating a bug when the code is unclear semantically, or updating a piece correctly when you’re not really sure it’s the only instance.

[tjr]

I think that's the question. Is a programmer expected to ever touch the source code? Or will AI -- and AI alone -- update the code that it generated?

Not entirely unlike other code generation mechanisms, such as tools for generating HTML based on a graphical design. A human could edit that, but it may not have been the intent. The intent was that, if you want a change, go back to the GUI editor and regenerate the HTML.