@eric@social.ericwbailey.website
Post #4288432
2026-06-15 15:23 UTC
Replies (3)
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@prism@infosec.exchange 2026-06-15 15:36
@eric@social.ericwbailey.website @mark@mastodon.fixermark.com Very much this--I can get pretty good results out of it, because I (not to toot my own horn,) am a genius. I know precisely how it must function and test it riggorously before submitting If you just say, "here's a thing, fix it" it usually doesn't work the first time. But if you stick with it you'll either get it to a good place or realize your problems were deeper than you thought, which is still useful.
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@gerardkcohen@front-end.social 2026-06-15 18:03
@eric@social.ericwbailey.website @mark@mastodon.fixermark.com #Facts The amount of manual effort to get AI to do what everyone thinks it can do is severely understated. And even after all the setup, my experience was that it did not accelerate anything. Output was barely equal, but mostly lagging behind humans. (yes, this was actually measured) And the reality is, thats "ok?" if everyone agrees and understands the effort and output. It's not magic. It's more artificial than it is intelligent. It's definitely not cheaper.
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@mark@mastodon.fixermark.com 2026-06-15 18:08
@eric@social.ericwbailey.website The approach I've seen work best is AI as an automated reviewer in the pull request workflow. It can false positive and false negative, but in practice the false-pos rate I'm seeing is like 1-5% (and much of that corner case stuff, like "yes you're right but that is autogen code that cannot be fixed at this layer"). It needs human in the loop, but it doesn't get bored in the same way humans do.