That's just not true, and if it is in your case, then you're not great at writing prompts yet.
> Take the todo_items table in Postgres and build a Micronaut API based around it. The base URL should be /v1/todo_items. You can connect to Postgres with pguser:pgpass@1.2.3.4
That's about all it takes these days. Less lines of code than your average controller.
And every day I do something else where the LLM output is off enough that I end up spending the same amount of time on it as if I'd done it by hand. It wrote a nice race condition bug in a race I was trying to fix today, but it was pretty easy for me to spot at least.
And once a week or so I ask for something really ambitious that would save days or even weeks, but 90% of the time it's half-baked or goes in weird directions early and would leave the codebase a mess in a way that would make future changes trickier. These generally suggest that I don't understand the problem well enough yet.
But the interesting things are:
1) many of the things it saves 90% of the time on are saving 5+ hours
2) many of the things I have to rework only cost me 2+ hours
3) even the things that I throw away make it way faster to discover that 'oh, we don't understand this problem well enough yet to make the right decisions here yet' conclusion that it would be just starting out on that project without assistance
so I'm generally coming out well ahead.
Now that ratio is swinging way over towards the LLMs favor.
How do you reconcile that with your example prompt, which demonstrates no skill requirement whatsoever. It’s the first thing any developer would think of.
Your comment exemplifies what a lot of people complain about vibe coding: it works great for greenfielding CRUD apps, but it’s a bitch to use in a real code base.
"But we have documentati..." then give the Agent access to the same docs as humans and it'll use them.
Some version of that happens in every big company or every long running app. Claude isn’t AGI and that prompt isn’t nearly specific enough for anything outside of greenfield.
I actually believe it just surfaces them, humans will tolerate ambiguity like that and deal with it. AI Agents either won't work properly or will just fail to do anything useful.
Communicating, in words, is extremely hard. I don't think this should be as controversial as it's seems in the prompt era.
VS: someone has mastered one of the myriad openAPI generators, and it's shipped.
"I'll go in the other direction and say that if you're spending a lot of your time learning to [program] better then you're wasting it because [computer]s are only going to get better at [computing] regardless of "[software] engineering". The JSON API example to wire up a database can be [run] pretty easily by the latest [computer]s without much [design] and without setting up any [optimizations]. The more time you spend perfecting your [program], the more time you would have wasted when the next [computer] comes out to make it obsolete."
I think 3.5 would probably need more frequent intervention than a lot of harnesses give. But I bet 4 could do a simple JSON API one-shot with the right harness. Just back then I had to manually be the harness.
Letting the tool figure out your assumed intent on those things is a double-edged sword. Better than you never even thinking of them. But potentially either subtle broken contracts that test coverage missed (since nobody has full combinatoric coverage, or the patience to run it) or just further steps into a messy codebase that will cost ever-more tokens to change safely.
Time-wise, it's easy-mode vs easy-mode at that point.
The human is more likely to make copypasta errors, though!
I started as a skeptic and have similarly drank the kool-aid. The reality is AI can read code faster than I can, including following code paths. It can build and keep more context than I can, and do it faster as well. And it can write code faster than I can type. So the effort to learn how to tell it what to do is worthwhile.
> That's just not true, and if it is in your case, then you're not great at writing prompts yet.
That's just not true, and if it is in your case, then you're not great at writing code yet.
You know what we call adequately specifying the system such that the computer can run it as a viable system.
Coding. We call it coding.
> provides not great prompt