You can instantly get whatever you want, only it’s made from 100% technical debt
Programmer Humor
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That estimate seems a little low to me. It's at least 115%.
even more. The first 100% of the tech debt is just understanding "your own" code.
And then 12 hours spent debugging and pulling it apart.
And if you need anything else, you have to use a new prompt which will generate a brand new application, it's fun!
Not to be that guy, but the image with all the traintracks might just be doing it's job perfectly.
The one on the right prints “hello world” to the terminal
And takes 5 seconds to do it
Engineers love moving parts, known for their reliability and vigor
Vigor killed me
Might is the important here
It gives you the right picture when you asked for a single straight track on the prompt. Now you have to spend 10 hours debugging code and fixing hallucinations of functions that don't exist on libraries it doesn't even neet to import.
While being more complex and costly to maintain
Depends on the usecase. It's most likely at a trainyard or trainstation.
The image implies that the track on the left meets the use case criteria
Im looking forward in the next 2 years when AI apps are in the wild and I get to fix them lol.
As a SR dev, the wheel just keeps turning.
I'm being pretty resistant about AI code Gen. I assume we're not too far away from "Our software product is a handcrafted bespoke solution to your B2B needs that will enable synergies without exposing your entire database to the open web".
It has its uses. For templeting and/or getting a small project off the ground its useful. It can get you 90% of the way there.
But the meme is SOOO correct. AI does not understand what it is doing, even with context. The things JR devs are giving me really make me laugh. I legit asked why they were throwing a very old version of react on the front end of a new project and they stated they "just did what chatgpt told them" and that it "works". Thats just last month or so.
The AI that is out there is all based on old posts and isnt keeping up with new stuff. So you get a lot of the same-ish looking projects that have some very strange/old decisions to get around limitations that no longer exist.
Holdup! You've got actual, employed, working, graduated juniors who are handing in code that they don't even understand?
Yeah, I think personally LLMs are fine for like writing a single function, or to rubber duck with for debugging or thinking through some details of your implementation, but I'd never use one to write a whole file or project. They have their uses, and I do occasionally use something like ollama to talk through a problem and get some code snippets as a starting point for something. Trying to do too much more than that is asking for problems though. It makes it way harder to debug because it becomes reading code you haven't written, it can make the code style inconsistent, and a non-insignifigant amount of the time even in short code segments it will hallucinate a non existent function or implement something incorrectly, so using it to write massive amounts of code makes that way more likely.
without exposing your entire database to the open web until well after your payment to us has cleared, so it's fine.
Lol.
Offtopic: But when I was a kid, I was obsessed with the complex subway rail system in NYC, I keep trying to draw and map it out.
God, seriously. Recently I was iterating with copilot for like 15 minutes before I realized that it's complicated code changes could be reduced to an if
statement.
I personally find copilot is very good at rigging up test scripts based on usings and a comment or two. Babysit it closely and tune the first few tests and then it can bang out a full unit test suite for your class which allows me to focus on creative work rather than toil.
It can come up with some total shit in the actual meat and potatoes of the code, but boilerplate stuff like tests it seems pretty spot on.
The key is identifying how to use these tools and when.
Local models like Qwen are a good example of how these can be used, privately, to automate a bunch of repetitive non-determistic tasks. However, they can spot out some crap when used mindlessly.
They are great for skett hing out software ideas though, ie try a 20 prompts for 4 versions, get some ideas and then move over to implementation.
And of course the ai put rail signals in the middle.
Chain in, rail out. Always
!Factorio/Create mod reference if anyone is interested !<
I think I would more picture planes taking off those railroads when it comes to AI. It tends to hallucinate API calls that don't exist. if you don't go check the docs yourself you will have a hard time debugging what went wrong.
It depends. AI can help writing good code. Or it can write bad code. It depends on the developer's goals.
LLMs can be great for translating pseudo code into real code or creating boiler plate or automating tedious stuff, but ChatGPT is terrible at actual software engineering.
I don't understand how build times magically decrease with AI. Or did they mean built?
They mean time to write the code, not compile time. Let's be honest, the AI will write it in Python or Javascript anyway