DevOps enthusiast and Golang/observability hacker changing the world @typesafeai. alum @docker @honeycombio @Bauplan_labs. i like barbells, EDM and Aeropress
@echantech1@shrav_10 I feel the dread but I also I feel like this, which is the bright side. I can express myself fluidly, focus more on systems thinking and cover more ground in areas I’m not a direct expert.
@EricLevitz rlhf strikes again, whenever you see a quirk like this the answer is always the reviewers preferred this style, i think because it’s a bit snappy and hits with kind of a one-two punch
@NotASithLord@Suhail it is. you don’t have to baby a rack of servers anymore, just spin up a vm with a few button clicks, if you need a different provider, you just switch, no different than caring who you get your potatoes from. with kubernetes even more so
engineers who are high IQ but low EQ continue to report terrible results from coding models, while CTOs with people skills rip ahead because the AI likes them
@JustinAlexP Apparently the median user *really* prefers the way AIs write now, where the text is constantly broken up with bulleted lists and blockquotes, and this is why it's so hard to get AIs to stop doing it.
every coding agent looks like a senior dev until you ask it to use an ORM. a new paper shows that adding a real database and architecture rules drops agent pass rates by 30%, with cross-file consistency hitting a brutal 8%. we didn't build autonomous engineers, we built a machine that writes single-file flask apps and panics the second it touches a data layer.
@ibuildthecloud probably. k8s and glue on top. if you writing your own inference system, you need e k/v store, efficient networking/proxying, node autoscale… might as well just ship into kube. i bet a lot of deployments look like aibrix or llmd
@dotpem The post discusses one case of a couple selecting largely on the basis of predicted IQ, but most of what we offer is screening against common, highly heritable diseases.
Here's an earlier example of T1D screening: https://t.co/FE6xHk1v2G.
Vibecoding is when you let LLMs generate code and you accept it as long as the end result appears to be working. You don't even review the code, you don't care.
When you rigorously ensure that generated code is up to a standard, it's not vibecoding anymore. It's programming.