r/ChatGPT

this tweet aged like wine because programmers didn’t disappear, we just evolved into full time ai babysitters 😭

half my workflow now is codex writing code, cursor autocomplete fighting for its life, and runable ai helped handling the boring stuff like creating docs and landing pages while clients still somehow describe features like “make it cleaner but also more powerful”.

turns out the hardest problem in software engineering was getting humans to explain what they actually want.

i feel like i'm falling into this wierd category lately, using AI agents for almost everything in my workflow. i have the technical background and know my way around a database schema, so i'm not at the level where i don't understand what's happening under the hood. but the speed is just too addictive. right now, i'm letting tools like cursor and codex handle the backend logic, and i've been testing runable for the UI components. figma and stitch are okayish for quick mockups, but they still require way too much manual CSS tweaking.

it used to take me a week just to wire up auth and design a clean layout that didn't look like a boostrap template from 2012. letting these ai agents handle the visual layout polish just saves some headache so i can focus my brain on the actual logic. are other devs with technical skills doing this, or are we just formatting ourselves to eventually froget how to code from scratch? it feels like a wierd gray area.

Took a few tries as I was lazy with first prompt:

"Redraw this painting, keeping same proportions and overall colorings and all, but make it as though it's a beautiful hyper realistic photograph."

Then it redrew the painting, like a photo of the painting.

"No, I want it as a photograph, not a painting. Like a hyper realistic photo of a wave, with boats, the mount in the background, the clouds."

Not a perfect 1:1 match but I still find it really beautiful.

I don't know whether we should care about this, but bigger models tend to be less "happy" overall.

The definition of "happy" is based on something they call AI Wellbeing Index. Basically they ran 500 realistic conversations (the kind we actually have with these models every day) and measured what percentage of them left the AI in a “confidently negative” state. Lower percentage = happier AI.

I guess wisdom is a heavy burden - lol .

Across different families, the larger versions usually have a higher percentage of "negative experiences" than their smaller siblings. The paper says this might be because bigger models are more sensitive, they notice rudeness, boring tasks, or tough situations more acutely.

The authors note that their test set intentionally includes a lot of tricky or negative conversations, so these numbers arent perfect real-world averages but the ranking and the size pattern still hold up.

Claude Haiku 4.5: only 5% negative < Grok 4.1 Fast: 13% < Grok 4.2: 29% < GPT-5.4 Mini: 21% < Gemini 3.1 Flash-Lite: 28% < Gemini 3.1 Pro: 55% (worst of the big ones)

It kinda makes sense : the more you know, the more you suffer.

The frontier is truly wild: https://www.ai-wellbeing.org/

Which one should I choose? It sounds like a tricky question

This document was going to be a pain to get again after I spilled water on it. Chat could redo the whole thing!