I'm going to try and be honest with you because I'm where you were at 3 months ago
I honestly don't think there's anything I can say to convince you because from my perspective that's a fools errand and the reason for that has nothing to do with the kind of person either of us are, but what kind of work we're doing and what we're trying to accomplish
The value I've personally been getting which I've been valuing is that it improves my productivity in the specific areas where it's average quality of response as one shot output is better than what I would do myself because it is equivalent to me Googling an answer, reading 2 to 20 posts, consolidating that information together and synthesising an output
And that's not to say that the output is good, that's to say that the cost of trying things as a result is much cheaper
It's still my job to refine, reflect, define and correct the problem, the approach etc
I can say this because it's painfully evident to me when I try and do something in areas where it really is weak and I honestly doubt that the foundation model creators presently know how to improve it
My personal evidence for this is that after several years of tilting those windmills, I'm successfully creating things that I have on and off spent the last decade trying to create successfully and have had difficulty with not because I couldn't do it, but because the cost of change and iteration was so high that after trying a few things and failing, I invariably move to simplifying the problem because solving it is too expensive, I'm now solving a category of those problems now, this for me is different and I really feel it because that sting of persistent failure and dread of trying is absent now
That's my personal perspective on it, sorry it's so anecdotal :)
No I agree with you, there are area's where AI is helping amazingly. Every now and then it helps me with some issue as well, which would have cost me hours earlier and now it's done in minutes. E.g. some framework that I'm not that familiar with, or doing the scaffolding for some unit test.
However this is only a small portion of my daily dev work. For most of my work, AI helps me little or not at all. E.g. adding a new feature to a large codebase: forget it. Debugging some production issue: maybe it helps me a little bit to find some code, but that's about it.
And this is what my post was referring to: not that AI doesn't help at all, but to the crazy claims (10x speedup in daily work) that you see all over social media.
Example for me: I am primarily a web dev today. I needed some kuberntes stuff setup. Usually that’s 4 hours of google and guess and check. Claude did it better in 15 minutes.
Even if all it does is speed up the stuff i suck at, that’s plenty. Oh boy docker builds, saves my bacon there too.
you haven't contributed much to GitHub since 2022?
*edit unless your commits are elsewhere?
>The value I've personally been getting which I've been valuing is that it improves my productivity in the specific areas where it's average quality of response as one shot output is better than what I would do myself because it is equivalent to me Googling an answer, reading 2 to 20 posts, consolidating that information together and synthesising an output
>And that's not to say that the output is good, that's to say that the cost of trying things as a result is much cheaper
But there's a hidden cost here -- by not doing the reading and reasoning out the result, you have learned nothing and your value has not increased. Perhaps you extended a bit less energy producing this output, but you've taken one more step down the road to atrophy.