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1•otrebladih•23s ago•0 comments

FSD helped save my father's life during a heart attack

https://twitter.com/JJackBrandt/status/2019852423980875794
1•blacktulip•3m ago•0 comments

Show HN: Writtte – Draft and publish articles without reformatting, anywhere

https://writtte.xyz
1•lasgawe•5m ago•0 comments

Portuguese icon (FROM A CAN) makes a simple meal (Canned Fish Files) [video]

https://www.youtube.com/watch?v=e9FUdOfp8ME
1•zeristor•6m ago•0 comments

Brookhaven Lab's RHIC Concludes 25-Year Run with Final Collisions

https://www.hpcwire.com/off-the-wire/brookhaven-labs-rhic-concludes-25-year-run-with-final-collis...
2•gnufx•8m ago•0 comments

Transcribe your aunts post cards with Gemini 3 Pro

https://leserli.ch/ocr/
1•nielstron•12m ago•0 comments

.72% Variance Lance

1•mav5431•13m ago•0 comments

ReKindle – web-based operating system designed specifically for E-ink devices

https://rekindle.ink
1•JSLegendDev•15m ago•0 comments

Encrypt It

https://encryptitalready.org/
1•u1hcw9nx•15m ago•1 comments

NextMatch – 5-minute video speed dating to reduce ghosting

https://nextmatchdating.netlify.app/
1•Halinani8•16m ago•1 comments

Personalizing esketamine treatment in TRD and TRBD

https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1736114
1•PaulHoule•17m ago•0 comments

SpaceKit.xyz – a browser‑native VM for decentralized compute

https://spacekit.xyz
1•astorrivera•18m ago•1 comments

NotebookLM: The AI that only learns from you

https://byandrev.dev/en/blog/what-is-notebooklm
1•byandrev•18m ago•1 comments

Show HN: An open-source starter kit for developing with Postgres and ClickHouse

https://github.com/ClickHouse/postgres-clickhouse-stack
1•saisrirampur•19m ago•0 comments

Game Boy Advance d-pad capacitor measurements

https://gekkio.fi/blog/2026/game-boy-advance-d-pad-capacitor-measurements/
1•todsacerdoti•19m ago•0 comments

South Korean crypto firm accidentally sends $44B in bitcoins to users

https://www.reuters.com/world/asia-pacific/crypto-firm-accidentally-sends-44-billion-bitcoins-use...
2•layer8•20m ago•0 comments

Apache Poison Fountain

https://gist.github.com/jwakely/a511a5cab5eb36d088ecd1659fcee1d5
1•atomic128•22m ago•2 comments

Web.whatsapp.com appears to be having issues syncing and sending messages

http://web.whatsapp.com
1•sabujp•22m ago•2 comments

Google in Your Terminal

https://gogcli.sh/
1•johlo•24m ago•0 comments

Shannon: Claude Code for Pen Testing: #1 on Github today

https://github.com/KeygraphHQ/shannon
1•hendler•24m ago•0 comments

Anthropic: Latest Claude model finds more than 500 vulnerabilities

https://www.scworld.com/news/anthropic-latest-claude-model-finds-more-than-500-vulnerabilities
2•Bender•29m ago•0 comments

Brooklyn cemetery plans human composting option, stirring interest and debate

https://www.cbsnews.com/newyork/news/brooklyn-green-wood-cemetery-human-composting/
1•geox•29m ago•0 comments

Why the 'Strivers' Are Right

https://greyenlightenment.com/2026/02/03/the-strivers-were-right-all-along/
1•paulpauper•30m ago•0 comments

Brain Dumps as a Literary Form

https://davegriffith.substack.com/p/brain-dumps-as-a-literary-form
1•gmays•30m ago•0 comments

Agentic Coding and the Problem of Oracles

https://epkconsulting.substack.com/p/agentic-coding-and-the-problem-of
1•qingsworkshop•31m ago•0 comments

Malicious packages for dYdX cryptocurrency exchange empties user wallets

https://arstechnica.com/security/2026/02/malicious-packages-for-dydx-cryptocurrency-exchange-empt...
1•Bender•31m ago•0 comments

Show HN: I built a <400ms latency voice agent that runs on a 4gb vram GTX 1650"

https://github.com/pheonix-delta/axiom-voice-agent
1•shubham-coder•32m ago•0 comments

Penisgate erupts at Olympics; scandal exposes risks of bulking your bulge

https://arstechnica.com/health/2026/02/penisgate-erupts-at-olympics-scandal-exposes-risks-of-bulk...
4•Bender•32m ago•0 comments

Arcan Explained: A browser for different webs

https://arcan-fe.com/2026/01/26/arcan-explained-a-browser-for-different-webs/
1•fanf2•34m ago•0 comments

What did we learn from the AI Village in 2025?

https://theaidigest.org/village/blog/what-we-learned-2025
1•mrkO99•34m ago•0 comments
Open in hackernews

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

2•mbm•9mo ago
As a rough estimate...

Comments

90s_dev•9mo 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•9mo 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•9mo ago
Zero
latexr•9mo 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•9mo 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•9mo 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•9mo 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•9mo ago
Partly. Mostly I write it myself, and only ask the LLM when I encounter problems.
apothegm•9mo 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•9mo 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.