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Steam Client Adds HDR Streaming on Steam Deck OLED, AV1 Video Streaming

https://www.phoronix.com/news/Steam-Beta-Video-Streaming
1•DemiGuru•1m ago•0 comments

EU Icons for labelling AI-generated content

https://digital-strategy.ec.europa.eu/en/policies/eu-icons-labelling-ai-generated-content
1•pekko•2m ago•0 comments

design of Plan 9 and how I use it (2022)

https://hackerpublicradio.org/eps.php?id=3675
1•bmacho•3m ago•1 comments

Collusion with Competitive Marginals: Price-Level Audits Are Blind

https://arxiv.org/abs/2607.26385
1•sbulaev•5m ago•0 comments

UK on track for record heat-related deaths this year, UKHSA estimates

https://www.bbc.co.uk/news/articles/c0m78g01r8jo
2•ljf•7m ago•0 comments

Show HN: HuPow – Proof-of-Work to stop AI bots in your inbox

https://hupow.app
2•cmbza•7m ago•0 comments

The Cities That Said Yes to Drugs

https://www.theatlantic.com/magazine/2026/09/city-drug-addiction-harm-reduction-policy/687967/
3•SanjayMehta•7m ago•0 comments

Self-Hosting Agent-Built Apps on a Mac Mini: My Personal Software Journey

https://metedata.substack.com/p/016-my-personal-software-journey
1•young_mete•8m ago•0 comments

Show HN: Formae 0.88.0 Released

https://docs.formae.io/documentation/reference/release-notes
1•discountelf•8m ago•0 comments

Sandboxing Claude CLI with Tart on Apple Silicon

https://www.mrafayaleem.com/blog/sandboxing-claude-cli-with-tart-on-apple-silicon
1•iamspoilt•8m ago•0 comments

Postgres rewritten in Rust v0.2, now faster than Postgres and ClickHouse

https://pgrust.com/
1•booksock•10m ago•0 comments

Copyright Was Never Your Friend

https://mkultra.monster/copyright/2026/07/23/copyright-bad/
1•surprisetalk•10m ago•0 comments

Show HN: Tinbase – OSS Supabase-compatible back end in TypeScript

https://www.tinbase.dev/
7•sanketsahu•10m ago•3 comments

Who's suing AI, and who's signing

https://pressgazette.co.uk/platforms/news-publisher-ai-deals-lawsuits-openai-google/
2•thm•11m ago•0 comments

Email in the Tranco Top-1M: 10 years of DNS measurements

https://labs.ripe.net/author/artem-berezin/two-providers-a-stubborn-plateau-and-a-very-long-tail-...
1•ArtemBerzin•11m ago•0 comments

Meta's AI spending reduces quarterly free cash flow by 91%

https://www.reuters.com/business/retail-consumer/metas-ai-splurge-lays-bare-its-compute-conundrum...
2•johnbarron•12m ago•0 comments

I measured what SmartScreen costs an indie developer. It's about 4x

https://senticmoney.com/blog/smartscreen-cost-indie-developer
2•fdcampbell•12m ago•1 comments

AI coding agents should optimize for less owned code

https://www.openenergytransition.org/posts/ai-coding-agents-should-optimize-for-less-owned-code
1•lyoncy•13m ago•0 comments

Octane JavaScript

https://octanejs.dev
1•haburka•14m ago•0 comments

Mandelbrot-2: C++ visualizer with perturbation theory up to 1e-308

https://github.com/Divetoxx/Mandelbrot-2
1•Divetoxx•15m ago•0 comments

SpaceX Looks to Compete with the Carriers

https://www.semafor.com/article/07/29/2026/spacex-looks-to-compete-with-the-carriers
1•TMWNN•15m ago•0 comments

Openinterpreter: Terminal coding agent built for low-cost models

https://www.openinterpreter.com
1•nateb2022•15m ago•0 comments

I built a free deepfake detector that works directly from social media URLs

https://kweliai.com/
1•ProlificVA•16m ago•0 comments

Taking Extreme Measures to Avoid New Car Technology

https://www.wsj.com/lifestyle/cars/driver-assistance-technology-dashboard-ead96bd2
1•ike_usawa•17m ago•0 comments

Go LLM SDK for streaming, tool-calling AI backends (plus frontend React lib)

https://github.com/grafana/ai-sdk
8•matryer•17m ago•0 comments

Leadership Lessons from the Odyssey

https://danielmangum.com/posts/odyssey-leadership-lessons/
1•hasheddan•17m ago•0 comments

AI and the Enshittification Era W Cory Doctorow – Weekly Show with Jon Stewart [video]

https://www.youtube.com/watch?v=-dAIJRjb-Bw
1•nekusar•17m ago•0 comments

Æsh, Another Extensible SHell

http://aeshell.github.io/
1•ankitg12•18m ago•0 comments

HSIP – a self-hosted identity and audit trail for AI agents

https://github.com/rewired89/HSIP-1PHASE
1•Rewired89•19m ago•0 comments

Blankie – Ambient sounds for your flow state

https://blankie.rest/
1•ai2027•20m 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.