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0 pointswilliamcotton1d ago0 comments

I agree 100%. Boring old software skills are part of what it took to "write" this DSL, complete with a fully featured LSP:

https://github.com/williamcotton/webpipe

https://github.com/williamcotton/webpipe-lsp

(lots of animated GIFs to show off the LSP and debugger!)

While I barely typed any of this myself I sure as heck read most of the generated code. But not all of it!

Of course you have to consider my blog to be "in production":

https://github.com/williamcotton/williamcotton.com/blob/main...

The reason I'm mentioning this project is because the article questions where all the AI apps are. Take a look at the git history of these projects and question if this would have been possible to accomplish in such a relatively short timeframe! Or maybe it's totally doable? I'm not sure. I knew nothing about quite a bit of the subsystems, eg, the Debug Adapter Protocol, before their implementation.

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dalenw1d ago

I recently "vibe coded" a long term background job runner service... thing. It's rather specific to my job and a pre-existing solution didn't exist. I already knew what I wanted the code to be, so it was just a matter of explaining explicitly what I wanted to the AI. Software engineering concepts, patterns, al that stuff. And at the end of the day(s) it took about the same amount of time to code it with AI than it would've taken by hand.

It was a lot of reviewing and proofreading and just verifying everything by hand. The only thing that saved me time was writing the test suite for it.

Would I do it again? Maybe. It was kinda fun programming by explaining an idea in plain english than just writing the code itself. But I heavily relied on software engineering skills, especially those theory classes from university to best explain how it should be structured and written. And of course being able to understand what it outputs. I do not think that someone with no prior software engineering knowledge could do the same thing that I did.

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