Makes perfect sense to anyone good at using these models. What doesn't make sense is that analogy. Typing prompts isn't even close to as difficult to baking bread.
Makes perfect sense to anyone good at using these models. What doesn't make sense is that analogy. Typing prompts isn't even close to as difficult to baking bread.
Depending on how good you are at this task. If typing prompts was that easy, there won't be so many tutorials, blog posts, and framework (Act as ... etc)
But there is a difference though. You can ask LLM for "how to write a prompt for ... to prompt you". You can't do that with bread.
It doesn't really, because whenever I ask them what did they actually create, its always a shitty dashboard or a finance tracker or something derivative and worse than what is out there
They've implemented only the parts they need, and removed all the crap that just complicates the system for them. They've made it do exactly what they need, exactly how they need it. It's something that you couldn't afford to do previously, sometimes even as a programmer. Now, it's often quick and easy, up to a certain complexity.
…until it breaks, or the bot goes off and does something ridiculous that you can’t understand without domain expertise. Which always happens.
I’m sympathetic to your argument, but I also strongly believe that most of these so-called “exactly what I need” projects will be abandoned within a fairly short time. That’s totally fine, but it’s not where most of the effort in professional software lies.
I vibe-coded a semantic parser for Lojban.
A friend of mine is using it to work on dev tooling.
Another friend, a mathematician, has recently used it to prove a conjecture he published 15 years ago.
Typing prompts would be like measuring ingredients.