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Hildegard of Bingen The 12th-century mystic who saw the Earth as a living whole

https://blue-continuum.com/hildegard-of-bingen
1•dnetesn•48s ago•0 comments

US proposes $100k charge for international students to do post-graduate work

https://www.nature.com/articles/d41586-026-02921-7
1•bluenose69•1m ago•0 comments

I Pointed AI at 400 Years of Archives. It Found a Forgotten Meteorites and More

https://jessewaites.com/blog/post/i-pointed-ai-at-400-years-of-archives/
1•piratebroadcast•5m ago•1 comments

HarnessTax: How Much Does the Harness Matter for Coding Agents?

https://arena.ai/blog/coding-agents-harness-tax
1•jfaat•7m ago•0 comments

Comparing Chromium Development at Google and Igalia

https://lwn.net/Articles/1094721/
1•sohkamyung•7m ago•0 comments

Show HN: 10M synthetic corporate emails and calendar files in 29 languages

https://huggingface.co/datasets/sinabis-group/sinabis-10m-synthetic-emails
1•sinabis_1•7m ago•0 comments

2nd Yandex Cloud Data Center Was Attacked

https://twitter.com/yandex/status/2108482115155169544
1•defly•13m ago•0 comments

Show HN: Pigeon – email API for the mail your app sends

https://pigeonfs.com/
1•oivoodoo_•13m ago•0 comments

Plumbers, chains, and famous painters: The history of the pipe operator in R

http://adolfoalvarez.cl/blog/2021-09-16-plumbers-chains-and-famous-painters-the-history-of-the-pi...
1•sinnsro•20m ago•0 comments

Michelangelus, the Story of the Font – Microsoft

https://matiasmobilia.substack.com/p/how-do-you-keep-500-years-of-heritage
1•matiasmobilia•21m ago•0 comments

Ask HN: How do you turn videos into searchable text without uploading them?

1•flounderXM•22m ago•2 comments

Notes on how glibc and musl handle math errors

https://sebsite.pw/w/20261004-math_errhandling.html
1•sinnsro•23m ago•0 comments

A US charity plans to use AI to monitor its Gaza schools

https://apnews.com/article/gaza-children-village-ai-speech-schools-7a41b3986524877b3e7ade7985853c53
1•CrypticShift•24m ago•0 comments

Maybe humans are just bad at math

https://trotro.mataroa.blog/blog/maybe-humans-are-just-bad-at-math/
2•trotro•24m ago•0 comments

ChatGPT work is down: Could not resolve host: github.com

2•itvision•25m ago•0 comments

Ask HN: Difference Between Astro and Next.js?

1•zsnkhnyt•26m ago•0 comments

Show HN: All Things Banana – banana news, prices, and a daily Wikipedia game

https://allthingsbanana.com/
2•nicknnamsa•28m ago•0 comments

You can now run Googlebook OS on your Mac, unofficially of course

https://www.androidauthority.com/googlebook-os-apple-silicon-mac-gbos-vm-3720744/
1•GaryBluto•33m ago•0 comments

Ask HN: What was the last task about that you abandoned

1•Haeuserschlucht•33m ago•1 comments

I Use AI to Learn Things [video]

https://www.youtube.com/watch?v=kzcI5F4tGiU
2•ssernikk•37m ago•2 comments

Show HN: I let Claude refactor my old game

https://github.com/victorqribeiro/aimAndShoot
1•atum47•37m ago•0 comments

Let your AI agents paint big arrows, boxes and text on your screen

https://github.com/franzenzenhofer/big-arrow-on-the-screen
37•franze•37m ago•12 comments

We're putting too much faith in AI's ability to say no

https://www.technologyreview.com/2026/10/09/1145728/we-are-putting-too-much-faith-in-ai-to-say-no/
2•joozio•39m ago•0 comments

Show HN: Client-side image cropping for any file input, without coding

https://cropguide.io/#demo
2•rikschennink•39m ago•0 comments

Show HN: Gh-reponark – audit settings across every repo in a GitHub org

https://github.com/admcpr/gh-reponark
1•sequence7•40m ago•0 comments

Pure ARM64 assembly implementation of the ED homophonic codebook cipher

https://gitlab.com/here_forawhile/edasm
2•Bluestein•41m ago•0 comments

An Open Letter to Scott Alexander

https://quillette.substack.com/p/an-open-letter-to-scott-alexander
1•GTP•42m ago•0 comments

AI Assistants Transform Nuclear Power Plant Work

https://spectrum.ieee.org/ai-assistants-nuclear-power-plant
1•rbanffy•43m ago•0 comments

Windows Media Player skin museum

https://wmp-skin-museum.mitpit.com/
1•MitPitt•43m ago•0 comments

A GTA-like vibe coding game that's currently taking Taiwan by storm

https://www.taipei-rush.app/
1•haebom•44m ago•0 comments
Open in hackernews

Ask HN: What percentage of your coding is now vibe coding?

2•mbm•1y ago
As a rough estimate...

Comments

90s_dev•1y ago
Proudly zero. I just wrote and posted an article explaining why. The short version: genuine engineering is an abandoned skill I want to revive.
leakycap•1y ago
Zero.

But there wasn't this much hate for people who copied random Javascript off whatever site LYCOS linked you to back in the day. Vibe coding for non-critical applications doesn't seem all that different to me.

JohnFen•1y ago
Zero
latexr•1y ago
Zero. I care about the code I write and value doing things well and building knowledge through deep understanding. Over the years I’ve proven to myself (and others) that approach improves both speed and accuracy, as well as reduce the need for rewrites because experience increases the chance I’ll get it right early on and design in a way that I don’t paint myself into corners.

I’ve noticed that coding with an LLM leads to severely diminished knowledge retention and learning (not to mention it’s less fun), and I suspect overuse would lead to a degree of dependency I don’t wish for myself.

joeismailyan•1y ago
Depends on the task. I use AI for planning/figuring out how to implement stuff. Probably 80% is with AI to bounce ideas off and figure things out.

Writing the code, probably 30% is with AI. Our product requires a lot of context for AI to get stuff right so it's challenging to get it to write good, working code. If it's a small thing that doesn't require a lot of context then I use AI.

I use various tools for this, let me know your needs and I can provide recommendations.

chrisrickard•1y ago
Vibe coding in the traditional sense (coined by Karpathy back in Feb): 20%

Vibe coding using detailed, structured requirements (from tools like Userdoc): 65%

khedoros1•1y ago
Very little. It's directly forbidden for my day job, and if I'm programming anything in my off hours, it's for my own enjoyment.

All of the code that I've generated by LLM has backed itself into a corner very early on, so I tend to use that as a starting point, then fix and refactor. I've made some toy-sized programs that way (but hours quicker than I would've looking up library documentation on my own).

I've had good luck refining my understanding of some concepts, talking through design of pieces of code, and basically generating snippets of example code on demand. Even in those limited cases, I end up relying on my own experience to determine what's helpful and what's crap. They're usually intertwined.

codeqihan•1y ago
Partly. Mostly I write it myself, and only ask the LLM when I encounter problems.
apothegm•1y ago
I almost never tell it to just write me a thing (what I think of as vibe coding). (2%)

I sometimes write a pretty detailed doc or spec; have the AI draft an implementation; then review and fix it myself. I try to keep this to “reasonable PR” size, a few hundred lines (a module or two) max, and will do a few rounds per hour. (~25%)

I will often stub out modules or classes (sometimes with docstrings) and tab-complete big chunks of them. (And then turn tab completion off and rage-code the rest by hand because the AI is so far off base.) (~25%)

I will often tell the AI to write tests for stubbed methods prior to implementation. I then double check the tests before moving on to manual or AI-assisted implementation. This is usually in increments of a single AI request/response. (~35%)

I will occasionally ask the AI to change existing code and tests, usually in a single request/response. I’ve had very mixed results with this. (~10%)

I have been finding myself writing code in smaller standalone libraries and then assembling those into larger and larger composites so that each library is a size a model can more realistically reason about; and for the layers on top of it the AI wont fill its context up reading all that source instead of just the public API docs.

rstuart4133•1y ago
Zero.

I've now convinced myself current LLM's are much closer to a "stochastic parrot" than an AGI in all areas other than natural language processing. In natural language they are super-human, meaning they can wordsmith better than most humans and are far faster at it than all humans.

That means it you are writing something it's seen a lot of before in it's training data in a language that's somewhat forgiving (so, not C), vibe coding might have 1/2 a chance. I don't do that. But if you're building UI's in javascript using a common framework it might work for you.