You both raise good arguments that I don't disagree with. I have always favored LLM's for less intensive tasks than development, though agentic VScode is the beginning of agentic architectural development. Manus seems to be spinning off in the "less architectural, more functional analytics" use-case as to revitalize what I believe is best about LLM.

I would argue nostr:nprofile1qqsyeqqz27jc32pgf8gynqtu90d2mxztykj94k0kmttxu37nk3lrktcprdmhxue69uhhg6r9vehhyetnwshxummnw3erztnrdakj7qg3waehxw309ahx7um5wghxcctwvshsz9thwden5te0w3jhxapwd4kx26m49ejx2a30j09tjd's statistic with hallucinations regarding code or development versus simple data analytics or otherwise.

For image generation there is a lot of simple and complex processes that can improve outputs significantly, but the cost (time) is the limitation. How complex of a workflow is necessary to achieve the finished result? How many similar images or themes will be recycled, and how many times? In simple projects you can use public models and LORAs to achieve plenty of good results.

With LLM we are just breaking into MCP workflows which will continue to enable other apps with less demand on the models themselves. GenAI is growing in efficiency while simultaneously blowing its load to fundraise.

All of this is to say, yes developing with AI is slop and garbage, and yes it's getting better, and no it's not going to take over the world but ultimately does come down to your goals and the cost vs. complexity of workflows. There is a time and place for all forms of AI, but it only shines when the conditions are satisfactory.

Well, it'll keep getting better at the pictures, but always double-check anything it does because it guesses and makes up stuff. Calls functions from libraries that don't have that library, or finds bugs that don't even exist and then adds 20 lines of code and 10 debugging logs to "correct" it.

Mine tried to add a monospace font that looks exactly like the standard ones and bloated up the size of the app.

That's the sort of stuff that vibe-coders can't see and just "approve". That's why they're actually quite slow developing with AI, as it's faster to hit the brakes and redirect to something more promising, but then you have to be able to code and think algorithmically.

Another example, it tried to make up wanton links to the pages to scrape, by taking a selection of pages like https://divineoffice.org/easter-w02-thu-mp/?date=20250501 and just randomly making up shit for the middle section.

I had to explain that it should do a first-pass on the main date for the page (as dates are a standard calendar object and not a fluctuating liturgical object) https://divineoffice.org/?date=20250502 or whatever, record the sub-page links (they change from year to year and season to season), and then do a second pass and scrape those links. Then you only scrape pages that exist and only with accurate links. That also gets around the fact that they change the content on the fly to introduce special mourning days for the Pope and stuff.

Then I can just rescrape the links and update whichever ones break, in my thrice-daily Jenkins routine, so that the 30040 hour content for the time frame selected. That way my stuff is always accurate and the links don't break. Don't have to look at the content, for that, just the links, as major changes to the content result in differnt links.

But, like, the AI couldn't figure that out. Seems completely obvious to me and it was so tedious writing it out that it's like, I coulda coded that faster.

And then the regex would have been right. How the heck do you try to use "psalm" for "Psalm 20" and "psalm-prayer". Those are obviously two completely different things. It couldn't even find all of the headers, when I told it precisely what the html tags look like for the divisions.

Just fighting stuff like that, all over, and so irritated.