Define “prompt” [LWN.net]

Define “prompt”

Posted Oct 15, 2025 20:39 UTC (Wed) by SLi (subscriber, #53131)
In reply to: Define “prompt” by Baughn
Parent article: The FSF considers large language models

> Unless you’ve only ever used ChatGPT, you will know that LLM-produced code is not the result of a single prompt, not even a conversation, but rather a workflow that often goes as such:

Even with ChatGPT this should be the case.

I've come to suspect that the usual difference between people who insist LLMs are absolutely useless and those who get a lot of good out of them is likely exactly that: Take a human who's likely not even very good at communicating textually (few of us are; technical writing is a discipline for a reason), have him write a single sloppy prompt and dismiss the results when the LLM was not able to read his mind.

to post comments

Define “prompt”

Posted Oct 15, 2025 20:54 UTC (Wed) by Wol (subscriber, #4433) [Link] (1 responses)

Except every time I've tried to make it clearer, the AI just digs itself deeper into the same hole.

Okay, the only AI I've (knowingly) used is Google search. And at least it has the decency to rephrase my query into the query it's going to answer (which it then answers pretty well). It's just that the question it's answering bears precious little resemblance to the question I asked it.

Cheers,
Wol

Define “prompt”

Posted Oct 15, 2025 21:19 UTC (Wed) by SLi (subscriber, #53131) [Link]

Yes, Google search is very hilarious, especially if you mean the "people also ask" results :)

Define “prompt”

Posted Oct 16, 2025 8:17 UTC (Thu) by taladar (subscriber, #68407) [Link]

Oddly enough none of the people who "get a lot of good out of them" have ever made a video showing that off on Youtube or anywhere else that had a convincing result in terms of the ratio of effort to output quality.

Define “prompt”

Posted Oct 20, 2025 8:35 UTC (Mon) by ssmith32 (subscriber, #72404) [Link] (3 responses)

That's a bit of a straw man argument. There are plenty of people who, like me, find it useful for simple transformations or generating boilerplate that, unfortunately, continues to persist in the codebase, for various and sundry reasons. But also recognize it can fail hilariously at simple tasks.

I asked my claude-powered assistant to:

- upgrade a library to a specific version. Instead, it updated an unrelated config value that had a similar name to the library to be the name of the library. The config file was most emphatically _not_ part of the build system. If LLMs truly understood "context" like people claim, it should have ruled out touching that file completely.

- generate a bunch of boilerplate for writing out new objects to a datastore that still needs boilerplate. Mostly got it right.

- generate a dockerfile for me. It saved time and worked, but added an unusual amount of completely useless cruft. Still faster to quickly remove it then make it myself from scratch.

- how to install a particular java version on my mac. Utterly failed. Kept on insisting on using a cask that no longer exists, on downloading it from locations that no longer hosted that particular version, etc. It was clearly just barfing up the suggestions from a bunch of outdated blogs.

For something that has similar patterns in your codebase, or has plenty of (correct) examples in documentation and random websites, it can do great.

For something novel or unique, even if it is something as banal as updating a library version by understanding it's pulled in transitively, and another library must be updated - or something both unique and genuinely interesting, LLMs fail miserably.

Which is not surprising. They are useful tools, once you know how they work. And a remarkable amout of code is not really doing anything that novel or unique.

For conversations about design, a co-worker or rubber duck is still much better for me.

Define “prompt”

Posted Oct 20, 2025 12:36 UTC (Mon) by pizza (subscriber, #46) [Link] (2 responses)

> Which is not surprising. They are useful tools, once you know how they work. And a remarkable amout of code is not really doing anything that novel or unique.

In other words, where LLMs are most useful is are twofold:

* A successor to the boilerplate-generating development environment "Wizards" [1]
* Fancy autocomplete.

[1] Referring to interactive prompt-guided templating engines popularized by Microsoft in Visual<whatever> development environments in the early 90s.

Define “prompt”

Posted Oct 22, 2025 17:25 UTC (Wed) by raven667 (subscriber, #5198) [Link] (1 responses)

That seems about right, I might also add that very simple usage of existing comprehensive frameworks seems like something LLMs should be able to cough up, like boilerplate describing how to make a simple CRUD app should have plenty of examples in the training data, so telling it what field names you want it should be possible to spit out a Django app, but I haven't tested that theory as I haven't touched LLMs, not even once. Maybe a freeform text frontend to ffmpeg invocations ;-)

Define “prompt”

Posted Oct 23, 2025 7:32 UTC (Thu) by taladar (subscriber, #68407) [Link]

If you just want a CRUD app auto-generated LLMs seem like overkill, it is probably easy to do that with a regular template engine, possibly even with the simple ones in project template tools (e.g. cargo-generate, not sure about a Python equivalent)