frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

War Department Cuts Ties with Harvard University

https://www.war.gov/News/News-Stories/Article/Article/4399812/war-department-cuts-ties-with-harva...
1•geox•1m ago•0 comments

Show HN: LocalGPT – A local-first AI assistant in Rust with persistent memory

https://github.com/localgpt-app/localgpt
1•yi_wang•2m ago•0 comments

A Bid-Based NFT Advertising Grid

https://bidsabillion.com/
1•chainbuilder•5m ago•1 comments

AI readability score for your documentation

https://docsalot.dev/tools/docsagent-score
1•fazkan•13m ago•0 comments

NASA Study: Non-Biologic Processes Don't Explain Mars Organics

https://science.nasa.gov/blogs/science-news/2026/02/06/nasa-study-non-biologic-processes-dont-ful...
2•bediger4000•16m ago•2 comments

I inhaled traffic fumes to find out where air pollution goes in my body

https://www.bbc.com/news/articles/c74w48d8epgo
2•dabinat•16m ago•0 comments

X said it would give $1M to a user who had previously shared racist posts

https://www.nbcnews.com/tech/internet/x-pays-1-million-prize-creator-history-racist-posts-rcna257768
3•doener•19m ago•0 comments

155M US land parcel boundaries

https://www.kaggle.com/datasets/landrecordsus/us-parcel-layer
2•tjwebbnorfolk•23m ago•0 comments

Private Inference

https://confer.to/blog/2026/01/private-inference/
2•jbegley•27m ago•1 comments

Font Rendering from First Principles

https://mccloskeybr.com/articles/font_rendering.html
1•krapp•30m ago•0 comments

Show HN: Seedance 2.0 AI video generator for creators and ecommerce

https://seedance-2.net
1•dallen97•34m ago•0 comments

Wally: A fun, reliable voice assistant in the shape of a penguin

https://github.com/JLW-7/Wally
2•PaulHoule•35m ago•0 comments

Rewriting Pycparser with the Help of an LLM

https://eli.thegreenplace.net/2026/rewriting-pycparser-with-the-help-of-an-llm/
2•y1n0•37m ago•0 comments

Lobsters Vibecoding Challenge

https://gist.github.com/MostAwesomeDude/bb8cbfd005a33f5dd262d1f20a63a693
2•tolerance•37m ago•0 comments

E-Commerce vs. Social Commerce

https://moondala.one/
1•HamoodBahzar•38m ago•1 comments

Avoiding Modern C++ – Anton Mikhailov [video]

https://www.youtube.com/watch?v=ShSGHb65f3M
2•linkdd•39m ago•0 comments

Show HN: AegisMind–AI system with 12 brain regions modeled on human neuroscience

https://www.aegismind.app
2•aegismind_app•43m ago•1 comments

Zig – Package Management Workflow Enhancements

https://ziglang.org/devlog/2026/#2026-02-06
1•Retro_Dev•44m ago•0 comments

AI-powered text correction for macOS

https://taipo.app/
1•neuling•48m ago•1 comments

AppSecMaster – Learn Application Security with hands on challenges

https://www.appsecmaster.net/en
1•aqeisi•49m ago•1 comments

Fibonacci Number Certificates

https://www.johndcook.com/blog/2026/02/05/fibonacci-certificate/
2•y1n0•51m ago•0 comments

AI Overviews are killing the web search, and there's nothing we can do about it

https://www.neowin.net/editorials/ai-overviews-are-killing-the-web-search-and-theres-nothing-we-c...
5•bundie•56m ago•1 comments

City skylines need an upgrade in the face of climate stress

https://theconversation.com/city-skylines-need-an-upgrade-in-the-face-of-climate-stress-267763
3•gnabgib•56m ago•0 comments

1979: The Model World of Robert Symes [video]

https://www.youtube.com/watch?v=HmDxmxhrGDc
1•xqcgrek2•1h ago•0 comments

Satellites Have a Lot of Room

https://www.johndcook.com/blog/2026/02/02/satellites-have-a-lot-of-room/
3•y1n0•1h ago•0 comments

1980s Farm Crisis

https://en.wikipedia.org/wiki/1980s_farm_crisis
4•calebhwin•1h ago•1 comments

Show HN: FSID - Identifier for files and directories (like ISBN for Books)

https://github.com/skorotkiewicz/fsid
1•modinfo•1h ago•0 comments

Show HN: Holy Grail: Open-Source Autonomous Development Agent

https://github.com/dakotalock/holygrailopensource
1•Moriarty2026•1h ago•1 comments

Show HN: Minecraft Creeper meets 90s Tamagotchi

https://github.com/danielbrendel/krepagotchi-game
1•foxiel•1h ago•1 comments

Show HN: Termiteam – Control center for multiple AI agent terminals

https://github.com/NetanelBaruch/termiteam
1•Netanelbaruch•1h 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.