Reasoning model prompting is relevant here. OpenAI in their docs state that giving detailed, step-by-step instructions often hinders reasoning models. It's better to clearly define the outcome along with what you're working with. Then let the mode interpolate.
Do you have any of those examples handy by chance? Curious to check them out. And agreed! While coding has become a commodity - programming is still as alive as ever.
I haven't fully stress tested it, but from brief use their proprietary context engine just feels like a gimmick to draw in VC investments. You can't convince me you get better end performance using an older model. Especially as most AI coding tools draw closer to enshitification with opaque context compression to save on costs
Adding to the conversation, Cursor is really genuinely good. Their agentic system has solid system prompts, better than Roo imo.
Their UX is absolutely the best as well. Excluding maybe Claude Code (completely different tho). You can argue what's better, what deserves to stand as a standalone product, but Cursor is easily the most mature 'vibe coding' tool imo.
Yes. It's definitely noticeable. Though, I try to console myself by remembering that my architectural design is definitely hypertrophied. My code is ultimately better. I think my LLM-assisted problem solving is definitely more efficient as well. My code literacy is better.
Hopefully LLMs won't vanish away... I'd be at a net negative.