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by xeromal
28 days ago
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No, we did a actual test using our existing testing framework. We have shitloads of metrics to know when a user gets stuck, when they give up, which login path they took, etc. This wasn't a half assed test but a legitimate effort to improve something that we never prioritized We had a legitimate 25% reduction in users giving up logging in in a system that has millions of users. We ran a 50-50 AB test for several weeks to confirm the data and then turned it on completely edit: If you haven't already read my post, I'd also like to say that the benefit AI gives us is that I worked on something I never get to work on, the analyst got to try a hunch he always had, and we got to see it go live in a day. If it didn't' work out, we were out a day of work which beats the few weeks of an effort prior to AI that we would spend on something just to find out it didn't work. |
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This is why LLMs are really great 'knocking off the todo/wishlist' of things you always meant to do. The problem, as far as broader discussions of 'productivity multipliers' or 'total factor productivity' go is that there's a certain perverse diminishing returns to such wishlist items (if each item was all that important, why didn't it get done before?), they generally only apply to a small part of a large complicated whole (what % of your ecosystem/business/community as a whole is the login page, as pleasing and profitable as that fix is relative to the investment? Probably not a big %), and they are also finite (what happens when you have worked through your backlog of lowhanging fruit?).