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Comment by austinjp | Hacker News Reader

In climate terms, or even simply in terms of $cost, this very much feels like throwing failing on a bonfire.

Should we really advocate for using AI to both create and then destroy huge amounts of data that will never be used?

I don't think it is a long term solution. More like training wheels. Ideally the engineers learn to use AI to produce better code the first time. You just have a quality gate.

Edit: Do I advocate for this? 1000%. This isn't crypto burning electricity to make a ledger. This objectively will make the life of the craftsmanship focused engineer easier. Sloppy execution oriented engineers are not a new phenomenon, just magnified with the fire hose that an agentic AI can be.

Who said anything about advocating for it.

What can keep up with the scale of it?

We know that AI is more capable by what's input into it for the prompt side so chances are code review might be a little more sensible.

Maybe this comment/idea will be a breakthrough in improving AI coding. :p

The environmental cost of AI is mostly in training afaik. The inference energy cost is similar to the google searches and reddit etc loads you might do during handwritten dev last I checked. This might be completely wrong though

I hear this argument a lot, but it doesn’t hold water for me. Obviously the use of the AI is the thing that makes it worthwhile to do the training, so you obviously need to amortize the training cost over the inference. I don’t know whether or not doing so makes the environmental cost substantially higher, though.

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