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I6P: An IPv6-only P2P transport layer in Go (QUIC and ratchet)

https://github.com/TheusHen/I6P
1•TheusHen•1m ago•1 comments

Plaza.one

https://plaza.one/
1•indigodaddy•2m ago•0 comments

Show HN: ApiTap – Stream APIs to any Data Warehouse with SQL (Rust + DataFusion)

https://apitap.dev/
1•kotekaman•2m ago•0 comments

Slopware.wtf – Roasting AI-Generated Garbage Software

https://slopware.wtf/
1•airhangerf15•3m ago•0 comments

Cchistory: Track Claude Code system prompts over time

https://cchistory.mariozechner.at/
1•handfuloflight•3m ago•0 comments

Show HN: I built an AI that calls you until you wake up

https://wakecall.online/
1•rahma_tm•13m ago•1 comments

SHP: 700x faster context recall by treating memory as network

https://github.com/silentnoisehun/Silent-Hope-Protocol
1•Hope_Genom•15m ago•1 comments

A Year of Typing: My NumPy Fellowship Retrospective

https://blog.scientific-python.org/numpy/fellowship-program-2025-retrospective/
1•todsacerdoti•16m ago•0 comments

Anthropic bans use of API in OpenCode CLI tool

https://github.com/anomalyco/opencode/issues/7410
2•sergiotapia•17m ago•0 comments

We just open sourced the code-simplifier agent we use on the Claude Code team

https://twitter.com/bcherny/status/2009450715081789767
1•cleanexit0•17m ago•0 comments

SFC vs. VIZIO: who can enforce the GPL?

https://lwn.net/SubscriberLink/1052734/5903e175673caeef/
2•pabs3•19m ago•0 comments

GPLv2 and Installation Requirements

https://lwn.net/SubscriberLink/1052842/52c45fb8bcc3fade/
1•pabs3•20m ago•0 comments

Show HN: Open-source multimodal AI that runs in the browser

https://johnjboren.github.io/ai-assistant.html
1•EschatonCometh•21m ago•0 comments

Show HN: Layoffstoday – Open database tracking for 10k Companies

https://layoffstoday.io/
1•doremon0902•22m ago•0 comments

Pituffik Space Base

https://en.wikipedia.org/wiki/Pituffik_Space_Base
2•CGMthrowaway•23m ago•0 comments

From old English to modern American English in one monologue

https://www.youtube.com/watch?v=842OX2_vCic
1•gk1•23m ago•0 comments

Financial Hardship Shows Up in Baby Brains

https://nautil.us/how-financial-hardship-shows-up-in-baby-brains-1260476/
1•fleahunter•25m ago•0 comments

Testing 2 open-weight models across coding tasks: GLM 4.7 and MiniMax M2.1

https://blog.kilo.ai/p/open-weight-models-are-getting-serious
1•heymax054•25m ago•0 comments

When AI writes almost all code, what happens to software engineering?

https://newsletter.pragmaticengineer.com/p/when-ai-writes-almost-all-code-what
3•Brajeshwar•29m ago•0 comments

Show HN: A commitment model for usage billing

https://twitter.com/tryflexprice/status/2009226683849773430
1•sudeepsd__•29m ago•0 comments

Trump Lays Out a Vision of Power Restrained Only by 'My Own Morality'

https://www.nytimes.com/2026/01/08/us/politics/trump-interview-power-morality.html
8•Stevvo•30m ago•0 comments

Ask AI via Lightning payments (no accounts, no API keys, no stored history)

https://satsforai.com/
1•LightProx•32m ago•1 comments

The most popular Go dependency is

https://blog.thibaut-rousseau.com/blog/the-most-popular-go-dependency-is/
1•bzGoRust•36m ago•0 comments

Ralph Wiggum Experiment – Can AI meaningfully improve through iterative loops?

https://github.com/UtpalJayNadiger/ralphwiggumexperiment
1•iacguy•36m ago•0 comments

Implementing a web server in a single printf() call (2014)

https://tinyhack.com/2014/03/12/implementing-a-web-server-in-a-single-printf-call/
1•nateb2022•37m ago•1 comments

Kelly Evans: Goodbye, Google

https://www.cnbc.com/2026/01/07/kelly-evans-goodbye-google.html
1•cebert•40m ago•1 comments

Spirit Cave Resilience: How Do We Explain a 10k-Year Continuity

https://www.cambridge.org/core/journals/american-antiquity/article/spirit-cave-resilience-how-do-...
1•1659447091•43m ago•0 comments

Show HN: LSP Skill – IntelliSense for Coding Agents That Works

https://lsp-client.github.io/
1•observerw•49m ago•0 comments

Against the 'METR Graph'

https://arachnemag.substack.com/p/the-metr-graph-is-hot-garbage
1•zygmunt417•49m ago•0 comments

Cellular Landscape

https://gaelmcgill.artstation.com/projects/Pm0JL1
2•o4c•49m ago•0 comments
Open in hackernews

The End of Programming

https://cacm.acm.org/opinion/the-end-of-programming/
14•cumo•8mo ago

Comments

kartik_malik•8mo ago
This era is for vibe coders
cumo•8mo ago
At the end, AI can replace coders ...
zombiwoof•8mo ago
Interesting the last decade of interviews has been leetcode bullshit which is utterly obsolete now given AI can do all that

So what is a software engineer? An SRE?

smallnix•8mo ago
Someone who can translate an ambiguous business need into a computer system that solves it.
Supermancho•8mo ago
Just assign an eng manager to the AI to handle that and be responsible, is the thinking. It's juvenile.
sathomasga•8mo ago
I think Cory Doctorow described said eng manager as a "human crumple zone" that serves to absorb the blame for failures.
goatlover•8mo ago
I guess we're still in the peak of inflated expectations.
smallnix•8mo ago
> Posted Jan 1 2023
voidfunc•8mo ago
Looking forward to rise of artisinal programming where we only use 100% AI free software. I can finally be a hipster of something!

I'm not sold on the demise of software engineering. But if it's truly going to die I'll still be programming but just for my hobby purposes.

thdhhghgbhy•8mo ago
Unconvinced. I believe we'll go the other way, further into the theoretical aspects, in particular program verification.
aquafox•8mo ago
> most software, as we know it, will be replaced by AI systems that are trained rather than programmed

The problem with this are all the edge cases. There are more ways unforseen circumstances can arise as you can train for. That's why you should do a lot of input checks in production.

yalok•8mo ago
Last 1 year I’ve been working full time on an integration layer between an end-user service and a few realtime LLM models that are part of that service.

The amount of code needed to achieve stability/predictability and address all kinds of edge cases is huge, and I have yet to see at least 1 use case where we can rely on LLMs answer 100% if it concerns any fixed state machine implementation etc.

Yes, these models are really good (just amazing!) at what classical CS approach can’t do around media and text processing, but they have such a hard time playing by specific strict rules…

So, CS focus will change, but it’s not going away… it’s more like we will end up with a better abstraction layer - like in 50-60s it was all in pure machine codes, then assembly, then C/etc, OOP, etc - here we will probably figure out even more elegant way to express unambiguous algorithm in a very succinct and very readable/maintainable way - and let LLM-based compilers convert it deterministically into some c++ code… (and those compiler may end up still having tons of classical code for speed/reliability/etc)

01100011•8mo ago
I'm pretty skeptical based on my experiences so far but still believe we'll get there eventually. AI seems to work fine for folks who hate programming and prefer describing their problem in imprecise english in an iterative fashion as long as their problem can ultimately be implemented with high level libraries written by competent programmers.

At some point AI will have some conceptual model of software and that's when I think things start to change. How we get there is anyone's guess. I think we're heading in the right direction by using the AST and not simply tokenizing source code. I'm not an AI engineer though. I just help those sorts of things run faster.

justinnk•8mo ago
Reminds me a bit of Isaac Asimov‘s novel „I, Robot“ where they rely on positronic brains to do things. In the story, mathematics seems to have caught up and developed a framework to analyse the behavior of an AI system. I wonder if something similar will happen if CS becomes an empirical science, i.e., will we try to infer laws from empirical AI behavior measurements so that we can reason about it more effectively? This would then turn CS into Physics somewhat, but based on an artificial system. Very strange times.

> these AI systems will be flying our airplanes, running our power grids, and possibly even governing entire countries.

I guess we should figure out how to include the three laws of robotics in connectionist models asap…

rich_sasha•8mo ago
It's a bit like the efficient market hypothesis and the rise of passive funds. The EMH says, if there is any inefficiency in the market, a well-resourced arbitrageur can close it and make a lot of money, so all such inefficiencies are closed before they even arise, so actually there are no inefficiencies. But if there are truly no inefficiencies, then there are no arbitrageurs, as they cannot support themselves! And thus no one to keep the markets efficient.

Passive investment management works really well, but also sort of depends on someone actually reading annual reports and firing incompetent management. Without it, if everyone just invests passively and thinks not one bit what they are doing, management will pay themselves stupid money and run their businesses to the ground.

So... Sure, LLMs learned a lot on from humans, and will eat a lot, maybe 90%+ of programming jobs - which in itself is a little scary. But I'm not sure what a 100% LLM software world looks like. I can imagine, rather, where a lot of mundane stuff that now requires the skills will be shifted to LLMs - like, dunno, a neighbourhood making its own parking app from a prompt. But is the field of software going to stop in its current shape?

TFA makes the point that most SEs these days have no idea how CPUs actually work. There was a time where this was all crucial knowledge, and you could say high level languages like Java make SEs redundant. Well they didn't, and employment in software has only been going up in the long run.

pragmatic•8mo ago
Needs a 2023 tag in title.