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AI Can Help Plan a Bioweapon

https://secondthoughts.ai/p/ai-can-help-plan-a-bioweapon-building
1•soltanov•2m ago•0 comments

WithExe: In-process EXE host for Windows x64

https://github.com/IgorTebelev/WithExe
1•AngryIgor•6m ago•0 comments

How viable is LLM-assisted 3D modeling in Blender?

https://twitter.com/louszbd/status/2093047548550525165
1•HyperAI•9m ago•0 comments

New York City Bans AI from Elementary Schools

https://gizmodo.com/new-york-city-bans-ai-from-elementary-schools-2000806172
1•the-mitr•10m ago•1 comments

Quasi-Bialgebra

https://en.wikipedia.org/wiki/Quasi-bialgebra
1•blizow•15m ago•0 comments

Trump's Lake Ontario push forces tech to pick a side

https://www.politico.com/news/2026/09/02/tech-lake-ontario-01062631
1•JumpCrisscross•17m ago•2 comments

Show HN: Free app for offline image search and smart file renaming

https://ringlochid.me/imagesage/index.html
1•ringlochid•22m ago•0 comments

Ask HN: A tool to share my data

1•roromainmain•27m ago•0 comments

Update on RISC-V Standards and Adoption at Hot Chips 2026

https://www.servethehome.com/update-on-risc-v-standards-and-adoption-at-hot-chips-2026/
2•lumpa•28m ago•0 comments

PromptSonar – Execution path analyzer for AI agents and MCP servers

https://github.com/meghal86/promptsonar
1•meghal86•29m ago•0 comments

Show HN: Vanity Domain Generator

https://vanitydomain.net
2•i3oi3•30m ago•1 comments

Who Survived the Great Dying – and Why, from PBS

https://www.pbs.org/video/who-survived-the-great-dying-and-why-life-and-death-on-pangea-pzs3ev/
1•blizow•30m ago•0 comments

SF's Tech Right Debates the Ideal Dictator

https://bayareacurrent.com/sfs-tech-caesar/
3•hliyan•33m ago•3 comments

What do you think about elastic workload?

https://xflops.io/blog/flame-v0-6/
1•k82cn•34m ago•0 comments

Dutch central bank moves 86 tonnes of gold from US citing 'geopolitical unrest'

https://www.theguardian.com/world/2026/sep/03/netherlands-gold-dutch-central-bank-uk-us-and-canad...
11•Jimmc414•36m ago•7 comments

Show HN: Review-to-rule – Turn accepted review feedback into durable repo rules

https://github.com/vamgan/review-to-rule
1•vamgan•43m ago•0 comments

The Loose: The Coming of Useless Agents

https://twitter.com/deanwball/status/2094794694572015854
1•jjwiseman•44m ago•0 comments

Toxic haze from Indonesia spreads to Malaysia and Philippines as wildfires rage

https://www.bbc.com/news/live/cqevw9y34y34t
1•blondie9x•45m ago•0 comments

We analyzed the code published by 29 frontier AI labs. Here's the data

https://opsera.ai/blog/frontier-ai-software-readiness-benchmark/
1•nassirkhan•46m ago•0 comments

Phased Behaviour in Wrapture

https://grahamdumpleton.me/posts/2026/09/phased-behaviour-in-wrapture/
1•lumpa•47m ago•0 comments

The mission to reach Nepal's underground 'Goldilocks zones'

https://www.abc.net.au/news/2026-09-03/nepal-hydroelectric-tunnels-rescue-interactive/107101108
2•CHB0403085482•47m ago•0 comments

Literate Programming with LLMs? – A Study on Rosetta Code and CodeNet

https://research.chalmers.se/en/publication/549267
1•gurjeet•51m ago•0 comments

Load-Bearing People

https://mikefisher.substack.com/p/load-bearing-people
2•Garbage•57m ago•0 comments

Frontier Act – Federal oversight of the development of frontier AI

https://www.congress.gov/bill/119th-congress/house-bill/9925/text
4•cco•1h ago•1 comments

Show HN: Indicate: Transliterate Indic Languages with PyTorch and LLMs

https://github.com/in-rolls/indicate
2•neehao•1h ago•0 comments

Reactor Live

https://live.reactor.inc/
1•willemhelmet•1h ago•0 comments

An Inflection Point for Prediction Markets

https://www.theatlantic.com/newsletters/2026/09/kalshi-polymarket-insider-trading-santos/688505/
1•paulpauper•1h ago•0 comments

How to Evaluate Diet Gurus

https://www.exfatloss.com/p/how-to-evaluate-diet-gurus
2•paulpauper•1h ago•0 comments

Rootnet: Exponentially Accelerate Advancing the Frontier

https://twitter.com/onrootnet/status/2095349077542342858
1•koopuluri•1h ago•0 comments

Wk. 6 of Vibecoding an MMO

https://eldermyr.com/
12•josiahturnq•1h ago•24 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.