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0 pointstim-tday1mo ago0 comments

This is wild. I’m on the other end.

I’ve probably prompted 10,000 lines of working code in the last two months. I started with terraform which I know backwards and forwards. Works perfectly 95% of the time and I know where it will go wrong so I watch for that. (Working both green field, in other existing repos and with other collaborators)

Moved on to a big data processing project, works great, needed a senior engineer to diagnose one small index problem which he identified in 30s. (But I’d bonked on for a week because in some cases I just don’t know what I don’t know)

Meanwhile a colleague wanted a sample of the data. Vibe coded that. (Extract from zip without decompressing) He wanted randomized. One shot. Done. Then he wanted randomized across 5 categories. Then he wanted 10x the sample size. Data request completed before the conversion was over. I would have worked on that for three hours before and bonked if I hit the limit of my technical knowledge.

Built a monitoring stack. Configured servers, used it to troubleshoot dozens of problems.

For stuff I can’t do, now I can do. For stuff I could do with difficulty now I can do with ease. For stuff I could do easily now I can do fast and easy.

Your vastly different experience is baffling and alien to me. (So thank you for opening my eyes)

0 comments

ua7091mo ago

I don’t find it baffling at all and both your experiences perfectly match mine.

Asking AI to solve a problem for you is hugely non-linear. Sometimes I win the AI lottery and its output is a reasonable representation of what I want. But mostly I loose the AI lottery and I get something that is hopeless. Now I have a conundrum.

Do I continue to futz with the prompt and hope if I wiggle the input then maybe I get a better output, or have I hit a limit and AI will never solve this problem? And because of the non linear nature I just never know. So these days I basically throw one dart. If it hits, great. If I miss I give up and do it the old fashioned way.

My work is in c++ primarily on what is basically fancy algorithms on graphs. If it matters.

enceladus061mo ago

What I've found Claude really helpful for is filling in the gaps. When you know vaguely how do to something like interpret data, but what other packages exist in xyz random technical domain? That is how I found for expample https://cran.r-project.org/web/packages/gggenes/vignettes/in... and Orthofinder when trying to teaching myself computational biology.

But sometimes even Claude gets stuck e.g. when I was trying to set up micropython via platformio running inside wsl2 on a windows 11 it got stuck setting up my ESP32 board.

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