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Lines of Code as a Productivity Metric in the AI Era

https://keegan.codes/blog/lines-of-code-as-a-productivity-metric-ai-era
1•keegandonley•1m ago•0 comments

Stop renting AI – run AI workers on your own dedicated node

https://ainode.sh
1•rzessski•3m ago•1 comments

Northstar CUA Fast, open source 4B CUA model

https://www.tzafon.ai/blog/northstar-cua-fast
1•publius_•4m ago•0 comments

How Tenaciously Palantir Courted Switzerland

https://www.republik.ch/2026/02/18/how-tenaciously-palantir-courted-switzerland
1•sschueller•6m ago•0 comments

Beside

https://aplwiki.com/wiki/Beside
1•tosh•6m ago•0 comments

2 Days to Ship: Codex-Authored Metal Compute Shaders in Draw Things

https://engineering.drawthings.ai/p/2-days-to-ship-codex-authored-metal
1•liuliu•7m ago•0 comments

Open Decision-Making (2021)

https://web.stanford.edu/~ouster/cgi-bin/decisions.php
1•otoolep•7m ago•0 comments

Show HN: Tic-Tac-Word – Can you beat yourself in this tic-tac-toe word game?

https://www.tictacword.com
2•onion92•8m ago•1 comments

Autoresearch for SAT Solvers

https://github.com/iliazintchenko/agent-sat
2•chaisan•8m ago•1 comments

Agents are not thinking: a behavioral study of pwning sonnet

https://technoyoda.github.io/pwning-claude.html
1•sci-genie•8m ago•0 comments

Embedding TeX Hyphenation Patterns for 30 Languages in a 1.1 MB Rust Automaton

https://laurmaedje.github.io/posts/hypher/
2•PaulHoule•9m ago•0 comments

MacBook Neo can be modded to run faster, but you probably shouldn't

https://appleinsider.com/articles/26/03/16/macbook-neo-can-be-modded-to-run-faster-but-you-probab...
3•gslin•10m ago•0 comments

Show HN: Smart glasses that tell me when to stop pouring

https://github.com/RealComputer/GlassKit/tree/main/examples/rokid-overshoot-openai-realtime
3•tash_2s•11m ago•0 comments

All Linus rants from 2012 to 2015

https://github.com/corollari/linusrants
2•stmw•11m ago•0 comments

Pure Functions in APL and J

https://dl.acm.org/doi/10.1145/114054.114065
2•tosh•13m ago•0 comments

Anthropic requires your phone number

https://support.claude.com/en/articles/8287232-verifying-your-phone-number
2•dataspun•13m ago•0 comments

AI campus gender wars ahead

https://hollisrobbinsanecdotal.substack.com/p/the-ai-campus-gender-wars-ahead
1•HR01•14m ago•1 comments

Neal.Fun Constellation Draw

https://neal.fun/constellation-draw/
1•memalign•14m ago•0 comments

Combinatory Logic

https://en.wikipedia.org/wiki/Combinatory_logic
2•tosh•15m ago•0 comments

Chemical safety API – Free for public

https://aletheia.holisticquality.io/
1•Phractal•15m ago•0 comments

Show HN: Mnemosphere – AI chat for the intellectually ambitious

https://www.mnemosphere.ai
1•jntucehyd•17m ago•0 comments

Show HN: GhostVM – macOS containers on Apple Silicon

https://ghostvm.org/
3•CarolineWang•18m ago•0 comments

COBOL Is the Asbestos of Programming Languages

https://www.wired.com/story/cobol-is-the-asbestos-of-programming-languages/
2•chrisaycock•20m ago•0 comments

Show HN: AgentPen – macOS dashboard for managing OpenClaw AI agents

https://agentpen.io
2•sara_builds•22m ago•0 comments

Show HN: Open-source agent first AEO monitoring platform

https://github.com/AINYC/canonry
1•arberx•22m ago•0 comments

Upgrading Hex security – Gleam v1.15.0 released

https://gleam.run/news/upgrading-hex-security/
1•iruoy•23m ago•0 comments

Living Human Brain Cells Play Doom [video]

https://corticallabs.com/doom.html
1•smartmic•25m ago•0 comments

Metrify – open-source annotation-driven Micrometer metrics for Spring Boot

https://github.com/wtk-ns/metrify-spring-boot-starter
2•wotkins•26m ago•1 comments

Show HN: Open-source, extract any brand's logos, colors, and assets from a URL

https://openbrand.sh/
3•hitchyhocker•27m ago•0 comments

Try ZeroTrain

https://www.zerotrain.ai/
1•WalterStjones•29m ago•1 comments
Open in hackernews

The End of Programming

https://cacm.acm.org/opinion/the-end-of-programming/
14•cumo•10mo ago

Comments

kartik_malik•10mo ago
This era is for vibe coders
cumo•10mo ago
At the end, AI can replace coders ...
zombiwoof•10mo 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•10mo ago
Someone who can translate an ambiguous business need into a computer system that solves it.
Supermancho•10mo ago
Just assign an eng manager to the AI to handle that and be responsible, is the thinking. It's juvenile.
sathomasga•10mo ago
I think Cory Doctorow described said eng manager as a "human crumple zone" that serves to absorb the blame for failures.
goatlover•10mo ago
I guess we're still in the peak of inflated expectations.
smallnix•10mo ago
> Posted Jan 1 2023
voidfunc•10mo 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•10mo ago
Unconvinced. I believe we'll go the other way, further into the theoretical aspects, in particular program verification.
aquafox•10mo 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•10mo 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•10mo 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•10mo 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•10mo 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•10mo ago
Needs a 2023 tag in title.