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413 points martinald | 1 comments | | HN request time: 0s | source
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tangotaylor ◴[] No.46204312[source]
> Engineers need to really lean in to the change in my opinion.

I tried leaning in. I really tried. I'm not a web developer or game developer (more robotics, embedded systems). I tried vibe coding web apps and games. They were pretty boring. I got frustrated that I couldn't change little things. I remember getting frustrated that my game character kept getting stuck on imaginary walls and kept asking Cursor to fix it and it just made more and more of a mess. I remember making a simple front-end + backend with a database app to analyze thousands of pull request comments and it got massively slow and I didn't know why. Cursor wasn't very helpful in fixing it. I felt dumber after the whole process.

The next time I made a web app I just taught myself Flask and some basic JS and I found myself moving way more quickly. Not in the initial development, but later on when I had to tweak things.

The AI helped me a ton with looking things up: documentation, error messages, etc. It's essentially a supercharged Google search and Stack Overflow replacement, but I did not find it useful letting it take the wheel.

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r_lee ◴[] No.46204550[source]
These posts like the one OP made is why I'm losing my mind.

Like, is there truly an agentic way to go 10x or is there some catch? At this point while I'm not thrilled about the idea of just "vibe coding" all the time, I'm fine with facing reality.

But I keep having the same experience as you, or rather leaning more on that supercharged Google/SO replacement

or just a "can you quickly make this boring func here that does xyz" "also add this" or for bash scripts etc.

And that's only when I've done most of the plumbing myself.

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1. bonzini ◴[] No.46204843[source]
I did find some benefit in lowering the cost of exploratory work, but that's it—certainly worth 20€/month, but not the price of any of the "ultimate" plans.

For example today I had to write a simple state machine (for a parser that I was rewriting so I had all the testcases already). I asked Claude Code to write the state machine for me and stopped it before it tried compiling and testing.

Some of the code (of course including all the boilerplate) worked, some made no sense. It saved a few minutes and overall the code it produced was a decent first approximation, but waiting for it to "reason" through the fixes would have made no sense, at least to me. The time savings mostly came from avoiding the initial "type the boilerplate and make it compile" part.

When completing the refactoring there were a few other steps like where using AI was useful. But overall the LLM did maybe 10% of the work and saved optimistically 20-30 minutes over a morning.

Assuming I have similar savings once a week, which is again very optimistic... That's a 2% reduction or less.