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[return to "Measuring the impact of AI on experienced open-source developer productivity"]
1. noisy_+g5[view] [source] 2025-07-10 17:04:56
>>dheera+(OP)
It is 80/20 again - it gets you 80% of the way in 20% of the time and then you spend 80% of the time to get the rest of the 20% done. And since it always feels like it is almost there, sunk-cost fallacy comes into play as well and you just don't want to give up.

I think an approach that I tried recently is to use it as a friction remover instead of a solution provider. I do the programming but use it to remove pebbles such as that small bit of syntax I forgot, basically to keep up the velocity. However, I don't look at the wholesale code it offers. I think keeping the active thinking cap on results in code I actually understand while avoiding skill atrophy.

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2. emoden+l7[view] [source] 2025-07-10 17:17:55
>>noisy_+g5
I think it’s most useful when you basically need Stack Overflow on steroids: I basically know what I want to do but I’m not sure how to achieve it using this environment. It can also be helpful for debugging and rubber ducking generally.
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3. some-g+Ia[view] [source] 2025-07-10 17:35:25
>>emoden+l7
All those things are true, but it's such a small part of my workflow at this point that the savings, while nice, aren't nearly as life-changing to my job as my CEO is forcing us to think it is.

Once AI can actually untangle our 14 year old codebase full of hosh-posh code, read every commit message, JIRA ticket, and Slack conversation related to the changes in full context, it's not going to solve a lot of the hard problems at my job.

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