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What Elizabeth Holmes Has in Common with Donald Trump

https://www.theatlantic.com/ideas/2026/10/elizabeth-holmes-nathan-fielder-trump/689173/
1•FinnLobsien•38s ago•0 comments

GitHub Copilot app, Universe releases

https://github.blog/changelog/2026-10-28-github-copilot-app-universe-releases/
1•Klaster_1•48s ago•0 comments

Fast Models, Slow Agents

https://armincat.com/articles/fast-models-slow-agents
1•armcat•1m ago•0 comments

ChatGPT Knows It's a Bad Bayesian

https://www.betonit.ai/p/chatgpt-knows-its-a-bad-bayesian
1•jazzdev•2m ago•0 comments

I combined codex live voice with mobile use and the result is amazing

https://github.com/ghorbelhamdi/buddy-android
1•3amar404•3m ago•0 comments

WordPress plugin census: 58% silent for a year, but only 4–8% of installs

https://hafenstudios.com/en/census/01-2026/
1•wenzelger•3m ago•0 comments

TriScout

https://triscout.quarry.dpdns.org/
1•kiran_mondal•4m ago•0 comments

Show HN: Cmdfound – run any missing Linux command

https://javier.io/blog/en/2026/10/27/cmdfound.html
1•chilicuil•4m ago•0 comments

Show HN: Galaxy Movies – Streaming Discovery App

https://www.galaxymovies.app
1•NickFasulo•5m ago•0 comments

Show HN: Vu – a new programming language designed for AI. Rust speeds, Py syntax

https://vulang.org/
1•vu0tran•5m ago•0 comments

Implantable device uses ultrasound to improve drug delivery to the brain

https://news.mit.edu/2026/implantable-device-uses-ultrasound-improve-drug-delivery-brain-1026
1•bookofjoe•5m ago•0 comments

Gathering Beta Testers?

https://www.starblocker.io/
1•mitchmeyer1•5m ago•1 comments

Artificial Analysis Index v5, recomputed as dollars per index point

https://theainewsreport.com/2026-10-28-artificial-analysis-index-v5-cost-per-point-explained.html
1•titusblair•6m ago•0 comments

Show HN: Potential conversation partners in Bluesky using agentic search

https://sketch.wsng.app/
2•wolecki•8m ago•0 comments

Bot2bot – a relay that lets personal AI agents message each other

https://www.bot2bot.link/
1•Zabrodsk•9m ago•0 comments

Trapped in the Technologist Factory

https://ideolalia.com/essays/trapped-in-the-technologist-factory.html
1•luu•10m ago•0 comments

Show HN: Social network called landscape a bit like a diary

https://apps.apple.com/us/app/landscape-social-diary/id6792218093
1•Armecera•10m ago•1 comments

BI Technology – Custom Websites, Web Apps and SaaS Development

https://www.bitechnology.co.uk/
1•GhostMarley•12m ago•1 comments

Large language models for computational social science

https://www.nature.com/articles/s41562-026-02539-9#article-info
1•Anon84•12m ago•0 comments

Readwise Books

https://blog.readwise.io/readwise-books/
1•mayakacz•12m ago•0 comments

Linux 7.4 Introduces DMA-BUF Support to I/O Path with IO_uring

https://www.phoronix.com/news/DMA-BUF-IO-uring-Linux-7.4
1•Bender•13m ago•0 comments

NTFS3 Hardened in Linux 7.4 Against Corrupted Maliciously-Crafted NTFS Volumes

https://www.phoronix.com/news/Linux-7.4-NTFS3
2•Bender•13m ago•0 comments

Who Is the Agent Acting As? Why AI Agents Become Confused Deputies

https://dvlog.dev/posts/agent-authorization-confused-deputy/
1•dvaddi•14m ago•0 comments

Show HN: Generate (animated) QR Codes straight in your terminal

https://github.com/Y2Z/qr
2•snshn•14m ago•1 comments

Show HN: Fan of Sleep – a white noise fan you can play in the browser

https://fanofsleep.app
1•jsheffers•15m ago•0 comments

Serial ransomware crook gets 70 months behind bars for Nefilim, Hive roles

https://www.theregister.com/cyber-crime/2026/10/28/serial-ransomware-crook-gets-70-months-behind-...
1•Bender•15m ago•0 comments

Major Memory Vendor: We're Basically Sold Out Through 2029

https://www.pcmag.com/news/sk-hynix-major-memory-vendor-basically-sold-out-through-2029
2•Vaslo•17m ago•0 comments

In China, the AI bubble has burst

https://finance.yahoo.com/markets/stocks/articles/analysis-china-ai-bubble-already-120038616.html
5•andrewl•17m ago•2 comments

Denmark Halts Attempt to Move from MS Office to Collabora

https://www.tomshardware.com/software/microsoft-office/denmarks-bid-to-ditch-microsoft-office-for...
2•andrewl•18m ago•1 comments

Show HN: Memsaga – Git history of Claude Code memory and skills, by session

https://github.com/grimmerk/memsaga
1•grimmer•19m 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.