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The rise of async AI programming

(www.braintrust.dev)
123 points mooreds | 2 comments | 11 Sep 25 12:20 UTC | HN request time: 0s | source
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ankrgyl ◴[11 Sep 25 17:19 UTC] No.45213946[source]▶
(Author here)

Hi everyone, thanks for the spirited debate! I think there are some great points in the discussion so far. Some thoughts:

* "This didn't work for offshoring, why will it work all of a sudden?" I think there are good lessons to draw from offshoring around problem definition and what-not but the key difference is the iteration speed. Agents allow you to review stuff much faster, and you can look at smaller pieces of incremental work.

* "I thought this would be about async primitives in python, etc" Whoops sorry, I can understand how the name is confusing/ambiguous! The use of "async" here refers to the fact that I'm not synchronously looking at an IDE while writing code all the time.

* "You can only do this because you used to handwrite code". I don't think this workflow is a replacement for handwriting code. I still love doing that. This workflow just helps me do more.

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1. datadrivenangel ◴[11 Sep 25 18:17 UTC] No.45214512[source]▶
I do think that AI will work well compared to the low end of offshoring, where to get good results you need people who could do the work themselves tightly involved. AI will give you slop code faster and cheaper, and that is sometimes enough.

The question is how it compares to the medium level of offshoring. Near term I think that at comparable cost ($100s of dollars per week), it'll give faster results at an acceptable tradeoff in quality for most uses. I don't think most companies want to spend thousands of dollars a month on developer tools per developer though... even though they often do.

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2. ankrgyl ◴[11 Sep 25 19:06 UTC] No.45215027[source]▶
It's just a different workflow IMO. AI is effectively real-time, whereas offshoring, no matter the quality, is something you have to do in batches.