Except they can't do the equivalent for art yet either, and I am fairly familiar with the state of image diffusion today.

I've commissioned tens of thousands of dollars in art, and spent many hundreds of hours working with Stable Diffusion, Midjourney, and Flux. What all the generators are missing is intentionality in art.

They can generate something that looks great at surface level, but doesn't make sense when you look at the details. Why is a particular character wearing a certain bracelet? Why do the windows on that cottage look a certain way? What does a certain engraving mean? Which direction is a character looking, and why?

The diffusers do not understand what they are generating, so they just generates what "looks right." Often this results in art that looks pretty but has no deeper logic, world building, meaning, etc.

And of course, image generators cannot handle the client-artist relationship as well (even LLMs cannot), because it requires an understanding of what the customer wants and what emotion they want to convey with the piece they're commissioning.

So - I rely on artists for art I care about (art I will hang on my walls), and image generators for throwaway work (such as weekly D&D campaign images.)

Of course the "art" art -- the part that is all about human creativity -- will always be there.

But lots of people in the art business aren't doing that. If you didn't have midjourney etc, what would you be doing for the throwaway work? Learn to design the stuff yourself, hire someone to do it on Upwork, or just not do it all? Some money likely will exchange hands there.

The throwaway work is worth pennies per piece to me at most. So I probably wouldn't do it at all if it wasn't for the generators.

And even when it comes to the generators, I typically just use the free options like open-source diffusion models, as opposed to something paid like Midjourney.

Have you seen https://www.swebench.com/ ?

Once you engage agentic behaviour, it can take you way further than just the chats. We're already in the "resolving JIRA tickets" area - it's just hard to setup, not very well known, and may be expensive.

> We're already in the "resolving JIRA tickets" area

For very simple tasks maybe, but not for the kinds of things I get paid to do.

I don't think it will be able to get to the level of reliably doing difficult programming tasks that require understanding and inferring requirements without having AGI, in which case society has other things to worry about than programmers losing their jobs.

Looks like the definition of "resolving a ticket" here is "come up with a patch that ensures all tests pass", which does not necessarily include "add a new test", "make sure the patch is actually doing something meaningful", "communicate how this is fixed". Based on my experience and what I saw in the reports in the logs, a solution could be just hallucinating completely useless code -- as long as it doesn't fail a test.

Of course, it is still impressive, and definitely would help with the small bugs that require small fixes, especially for open source projects that have thousands of open issues. But is it going to make a big difference? Probably not yet.

Also, good luck doing that on our poorly written, poorly documented and under tested codebase. By any standard django is a much better codebase than the one I work on every day.

Some are happy with creating tests as well, but you probably want to mostly write them yourself. I mean, only you know the real world context - if the ticket didn't explain it well enough, LLMs can't do magic.

Actually the poorly documented and poorly written is not a huge issue in my experience. The under tested is way more important if you want to automate that work.

But that’s not that far. Like sure, currently it’s not. But "reading a ticket with a description, find the relevant code, understand the code (often better than human), test it, return the result" is totally doable with some more iterations. It’s already doable for smaller projects, see GitHub workspaces etc.