frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

Tell HN: Happy Thanksgiving

1•LorenDB•1m ago•0 comments

OpenAI says dead teen violated TOS when he used ChatGPT to plan suicide

https://arstechnica.com/tech-policy/2025/11/openai-says-dead-teen-violated-tos-when-he-used-chatg...
2•chha•7m ago•0 comments

Why does Redis run out of memory when you still have free space?

https://velieroglu.substack.com/p/why-memory-defragmantation-occurs
1•velieroglu•10m ago•0 comments

Aluminum Sphere Pencil Makes You Draw Like a Caveman

https://www.yankodesign.com/2025/11/20/this-aluminum-sphere-pencil-makes-you-draw-like-a-caveman/
1•MortyDev•10m ago•0 comments

In 1982, a physics joke gone wrong sparked the invention of the emoticon

https://arstechnica.com/gadgets/2025/11/in-1982-a-physics-joke-gone-wrong-sparked-the-invention-o...
1•miltava•13m ago•0 comments

Ask HN: TCP/IP Illustrated, v2 2e?

2•mayureshkathe•14m ago•0 comments

US breach reinforces need to plug third-party security weaknesses

https://www.computerweekly.com/news/366634992/US-breach-reinforces-need-to-plug-third-party-secur...
1•latein•18m ago•0 comments

Plan beautiful, twisty Routes with Kurviger

https://kurviger.com/en
2•robin_reala•19m ago•0 comments

AI-First Web:Practical guidelines for making your site readable by AI assistants

2•kure256•21m ago•1 comments

Show HN: Logry – A low-dopamine social diary for close friends using Gemini

https://logry.app/
1•TytoMan•22m ago•0 comments

All-optical visualization of specific molecules in brain ultrastructure

https://www.nature.com/articles/s41587-025-02905-4
1•bookofjoe•23m ago•0 comments

Show HN: MkSlides – Markdown to slides with a similar workflow to MkDocs

https://github.com/MartenBE/mkslides
3•MartenBE•25m ago•0 comments

Proof – Court-admissible cloud evidence acquisition (free 1GB tier)

https://proof-data.com/
1•kierandeeptrace•34m ago•1 comments

The State of GPL Propagation to AI Models

https://shujisado.org/2025/11/27/gpl-propagates-to-ai-models-trained-on-gpl-code/
4•jonymo•37m ago•0 comments

Who's Next? Pete Townshend and Roger Daltrey at Odds over AI Music

https://www.thetimes.com/uk/technology-uk/article/pete-townshend-the-who-ai-music-f3kmh5tt0
1•ilamont•38m ago•0 comments

Cloudflare's November 18 Outage – A Continuous Delivery Perspective

https://markoanastasov.com/signals/cloudflare-november-18-outage-continuous-delivery-perspective/
1•markoa•43m ago•0 comments

Solving the Partridge square packing problem using MiniZinc

https://zayenz.se/blog/post/partridge-packing/
3•fanf2•43m ago•1 comments

AGI is not possible even in 10 years

https://medium.com/@anwarzaid76/agi-is-not-possible-even-in-10-years-013a1aec0d9c
4•MindBreaker2605•46m ago•0 comments

Apple's 1976 formation papers could fetch $4M at auction

https://appleinsider.com/articles/25/11/26/apples-1976-formation-papers-could-fetch-4-million-at-...
1•giuliomagnifico•48m ago•0 comments

Hachi: An (Image) Search Engine

https://eagledot.xyz/hachi.md.html
1•warangal•50m ago•0 comments

What to Buy That Improves Quality of Life

https://www.developing.dev/p/what-to-buy-that-improves-quality
1•skadamat•52m ago•0 comments

Can Vibe Coding Beat Graduate CS Students? An LLM vs. Human Coding Tournament

https://arxiv.org/abs/2511.20613
2•geox•52m ago•0 comments

Haskell Weekly – Issue 500

https://haskellweekly.news/issue/500.html
2•amalinovic•53m ago•0 comments

Shahed-107 UAV Components

https://war-sanctions.gur.gov.ua/en/page-shahed-107
1•IndrekR•56m ago•0 comments

Ask HN: How to Find Investors?

3•karanveer•1h ago•0 comments

Tiny tweak for Pi OS, big makeover for the Imager

https://www.theregister.com/2025/11/27/new_raspberry_pi_imager/
1•rbanffy•1h ago•0 comments

Can you share how your team handles FinOps and cloud cost optimization?

https://qualtricsxm6y7fnpxlk.qualtrics.com/jfe/form/SV_3t9duUd1bWwJrn0
1•avinashgaurav_•1h ago•1 comments

CIA Menu Collection

http://ciadigitalcollections.culinary.edu/digital/collection/p16940coll1/search
3•pseudolus•1h ago•0 comments

Ask HN: Would you use a fast/cheap "prior art" service instead of a patent?

1•shaheeniquebal•1h ago•1 comments

R.O.B. Robotic Operating Buddy

https://en.wikipedia.org/wiki/R.O.B.
2•debo_•1h ago•0 comments
Open in hackernews

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

2•mbm•6mo ago
As a rough estimate...

Comments

90s_dev•6mo 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•6mo 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•6mo ago
Zero
latexr•6mo 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•6mo 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•6mo 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•6mo 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•6mo ago
Partly. Mostly I write it myself, and only ask the LLM when I encounter problems.
apothegm•6mo 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•6mo 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.