4 ms·

They should also share their prompts and discuss exactly how much effort went into checking the output and re-prompting to get the desired result. The post hint

They should also share their prompts and discuss exactly how much effort went into checking the output and re-prompting to get the desired result. The post hints at how much work it takes for the human, "If you are able to describe problems in a clear way and, if you are able to accept the back and forth needed in order to work with LLMs ... you need to provide extensive information to the LLM: papers, big parts of the target code base ... And a brain dump of all your understanding of what should be done. Such braindump must contain especially the following:" and more. After all the effort getting to the point where the generated code is acceptable, one has to wonder, why not just write it yourself? The time spent typing is trivial to all the cognitive effort involved in describing the problem, and describing the problem in a rigorous way is the essence of programming.

tines 1y ago
I would assume the argument is that you only need to provide the braindump and extensive information one time (or at least, collect it once, if not upload once) and then you can take your bed of ease as the LLM uses that for many tasks.
- skydhash 1y ago
  The thing is no one writes that much code, at least anyone that cares about code reuse. Mostly the times is spent collecting the information (especially communication with stakeholder), and verifying that the code you wrote didn't break anything.
deleted 1y ago
[deleted]
UncleEntity 1y ago
> After all the effort getting to the point where the generated code is acceptable, one has to wonder, why not just write it yourself? You know, I would often ask myself that very question... Then I discovered the stupid robots are good at designing a project, you ask them to produce a design document, argue over it with them for a while, make revision and changes, explore new ideas, then, finally, ask them to produce the code. It's like being able to interact with the yaks you're trying to shave, what's not to love about that?
datastoat 1y ago
> They should also share their prompts Here's a recent ShowHN post (a map view for OneDrive photos), which documents all the LLM prompting that went into it: https://news.ycombinator.com/item?id=44584335 https://news.ycombinator.com/item?id=44584335
keeda 1y ago
> After all the effort getting to the point where the generated code is acceptable, one has to wonder, why not just write it yourself? Because it is still way, way, way faster and easier. You're absolutely right that the hard part is figuring out the solution. But the time spent typing is in no way trivial or cognitively simple, especially for more complex tasks. A single prompt can easily generate 5 - 10x the amount of code in a few seconds, with the added bonus that it: a) figures out almost all the intermediate data structures, classes, algorithms and database queries; b) takes care of all the boilerplate and documentation; c) frequently accounts for edge cases I hadn't considered, saving unquantifiable amounts of future debugging time; d) and can include tests if I simply ask it to. In fact, these days once I have the solution figured out I find it frustrating that I can't get the design in my head into the code fast enough manually. It is very satisfying to have the AI churn out reams of code, and immediately run it (or the tests) to see the expected result. Of course, I review the diff closely before committing, but then I do that for any code in any case, even my own.
- cratermoon 1y ago
  > A single prompt can easily generate 5 - 10x the amount of code in a few seconds That doesn't sound like a great outcome. Every line of code is a potential bug and a liability. The least important skill in programming is typing speed.
- gf000 1y ago
  > frequently accounts for edge cases I hadn't considered, saving unquantifiable amounts of future debugging time; And creates new ones you wouldn't even consider before, creating just as much, if not more future debugging :D
  - keeda 1y ago
    That's what the code review is for :-) But to echo the sibling comments, I've not caught a subtle edge case or bug in the generated code in more than a year and half. There are mistakes and failure modes for sure, but they are very glaring, to the extent that I simply throw that code away and try again. That said, I've adopted a specific way of working with AI that is very effective for my situation (mentioned in my comment history, but echoes a lot of what TFA advises.)
spaceman_2020 1y ago
As someone who just used AI to create a very comprehensive creative visual marketing campaign, there is absolutely a massive gap in output depending on your prompting skills You can get images that can go straight to print or end up with pure slop based on your prompt

tines 1y ago

I would assume the argument is that you only need to provide the braindump and extensive information one time (or at least, collect it once, if not upload once) and then you can take your bed of ease as the LLM uses that for many tasks.

skydhash 1y ago
The thing is no one writes that much code, at least anyone that cares about code reuse. Mostly the times is spent collecting the information (especially communication with stakeholder), and verifying that the code you wrote didn't break anything.

deleted 1y ago

[deleted]

UncleEntity 1y ago

> After all the effort getting to the point where the generated code is acceptable, one has to wonder, why not just write it yourself? You know, I would often ask myself that very question... Then I discovered the stupid robots are good at designing a project, you ask them to produce a design document, argue over it with them for a while, make revision and changes, explore new ideas, then, finally, ask them to produce the code. It's like being able to interact with the yaks you're trying to shave, what's not to love about that?

datastoat 1y ago

> They should also share their prompts Here's a recent ShowHN post (a map view for OneDrive photos), which documents all the LLM prompting that went into it: https://news.ycombinator.com/item?id=44584335 https://news.ycombinator.com/item?id=44584335

keeda 1y ago

> After all the effort getting to the point where the generated code is acceptable, one has to wonder, why not just write it yourself? Because it is still way, way, way faster and easier. You're absolutely right that the hard part is figuring out the solution. But the time spent typing is in no way trivial or cognitively simple, especially for more complex tasks. A single prompt can easily generate 5 - 10x the amount of code in a few seconds, with the added bonus that it: a) figures out almost all the intermediate data structures, classes, algorithms and database queries; b) takes care of all the boilerplate and documentation; c) frequently accounts for edge cases I hadn't considered, saving unquantifiable amounts of future debugging time; d) and can include tests if I simply ask it to. In fact, these days once I have the solution figured out I find it frustrating that I can't get the design in my head into the code fast enough manually. It is very satisfying to have the AI churn out reams of code, and immediately run it (or the tests) to see the expected result. Of course, I review the diff closely before committing, but then I do that for any code in any case, even my own.

cratermoon 1y ago
> A single prompt can easily generate 5 - 10x the amount of code in a few seconds That doesn't sound like a great outcome. Every line of code is a potential bug and a liability. The least important skill in programming is typing speed.
gf000 1y ago
> frequently accounts for edge cases I hadn't considered, saving unquantifiable amounts of future debugging time; And creates new ones you wouldn't even consider before, creating just as much, if not more future debugging :D
- keeda 1y ago
  That's what the code review is for :-) But to echo the sibling comments, I've not caught a subtle edge case or bug in the generated code in more than a year and half. There are mistakes and failure modes for sure, but they are very glaring, to the extent that I simply throw that code away and try again. That said, I've adopted a specific way of working with AI that is very effective for my situation (mentioned in my comment history, but echoes a lot of what TFA advises.)

spaceman_2020 1y ago

As someone who just used AI to create a very comprehensive creative visual marketing campaign, there is absolutely a massive gap in output depending on your prompting skills You can get images that can go straight to print or end up with pure slop based on your prompt