devrimozcay

5 ms·

1.
by devrimozcay 6mo ago
This looks useful. One pattern we've been seeing internally is that once teams standardize API interactions through a single interface (or agent layer), debugging becomes both easier and harder. Easier because there's a central ab
2.
by devrimozcay 6mo ago
One thing I'm curious about here is the operational impact. In production systems we often see Python services scaling horizontally because of the GIL limitations. If true parallelism becomes common, it might actually reduce the number
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by devrimozcay 6mo ago
Interesting direction. One thing we've been seeing with production AI agents is that the real risk isn't just filesystem access, but the chain of actions agents can take once they have tool access. Even a simple log-reading capabi
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by devrimozcay 7mo ago
what do you think about that?
5.
Show HN: ProdRescue AI – Turn Slack war-rooms and raw logs into incident reports(prodrescueai.com)
4 points by devrimozcay 7mo ago|1 comments
6.
by devrimozcay 7mo ago
’ve spent way too many nights at 3 AM trying to piece together what happened during a P1 incident. The hardest part isn't usually fixing the bug—it's writing the post-mortem report for the leadership 2 hours later while you'r
7.
I built an AI that turns 3 AM messy logs into board-ready incident reports(prodrescueai.com)
2 points by devrimozcay 7mo ago|1 comments
8.
by devrimozcay 1y ago
Thanks
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by devrimozcay 1y ago
Python is Dying in 2025: Why Rust and Other Alternatives Are Taking Over
10.
by devrimozcay 1y ago
what is this