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Ticket-In Ticket-Out

https://en.wikipedia.org/wiki/Ticket-in,_ticket-out
1•suopspaces•46s ago•0 comments

Show HN: An honest comparison of the Agent Harness vs. six alternatives

https://time2magic.com/agent-harness
1•bishopz•5m ago•0 comments

Before and After Photos Show Data Centers Furiously Popping Up Across America

https://petapixel.com/2026/09/19/before-and-after-photos-show-data-centers-furiously-popping-up-a...
1•andsoitis•6m ago•0 comments

Breaking a four year hiatus to talk about the export keyword (PEPs 842 and 843)

https://aroberge.blogspot.com/2026/09/breaking-four-year-hiatus-to-talk-about.html
1•lumpa•6m ago•0 comments

Show HN: Primescript – Academic Markdown editor with vector search and LaTeX

https://primescript.com
1•mac-r•6m ago•0 comments

Show HN: A Mondrian-style puzzle block game

https://game.wdamao.com/mondrian-blocks/
1•wdamao•8m ago•1 comments

A Calendar of Smells

https://worldsensorium.com/a-calendar-of-smells/
1•dnetesn•8m ago•0 comments

A space war played in SQL

https://schemaverse.com/
1•thunderbong•9m ago•0 comments

Solitaire Alone Together

https://eieio.games/blog/solitaire-alone-together/
1•anitil•10m ago•1 comments

An Ocean Planet in Space

https://blue-continuum.com/an-ocean-planet-in-space
2•dnetesn•11m ago•0 comments

EZ4: A reflection-driven alternative to AWS CDK for serverless apps

https://github.com/sbalmt/ez4
2•sbalmt•15m ago•0 comments

Ask HN: How do you sell a small bootstrapped SaaS?

2•hpsilab•17m ago•0 comments

A 7B fact-checker beat 30B LLM reviewers and deleted no true claims

https://openteams.com/llm-review-reliability/
3•khuyentran1401•17m ago•0 comments

The World After Capital (2024)

https://worldaftercapital.org/
2•measurablefunc•18m ago•0 comments

How Your Internet Traffic Gets There: IXPs and Peering

https://community.ipinfo.io/t/how-your-internet-traffic-actually-gets-there-ixps-peering-and-why-...
2•shubhamjain•21m ago•0 comments

A Programming Mentality

https://www.natemeyvis.com/a-programming-mentality/
1•meetpateltech•23m ago•0 comments

Vibes vs. Evidence: What delivers AI code review quality

https://dsifry.github.io/harnesseval/
2•pjf•23m ago•0 comments

What Makes Jev Different from Other LLMs? A Simple Explanation

https://medium.com/@dolevietthang/what-makes-jev-different-from-chatgpt-and-claude-a-simple-expla...
1•vietthangif•23m ago•0 comments

Silicon Valley Saw the iPhone Coming 13 Yrs Before Apple [video]

https://www.youtube.com/watch?v=34dAyDUglrI
1•Teever•25m ago•0 comments

Something bugs me about AGI AI LLM, what if we back paddled 1000 year

https://shatteringtheabyss.substack.com/p/llm-agi-god-congratulations-humanity
1•vseedstriker•26m ago•1 comments

Context compaction, measured: FutureOS vs. Codex vs. OpenCode

https://future-os-blog.github.io/posts/context-compaction-measured.html
1•thetechlead•31m ago•0 comments

Major air traffic controller outage triggers flight chaos [video]

https://www.youtube.com/watch?v=gHUZ9W025lA
2•shinryudbz•33m ago•0 comments

Meta's Muse Is Better at Surveilling Than Helping Me

https://www.wired.com/story/metas-muse-is-better-at-surveilling-than-helping-me/
2•the-mitr•36m ago•0 comments

Android Bench 2.0 – Long Horizon Android Development Benchmark

https://developer.android.com/bench
1•bentrengrove•38m ago•0 comments

FloatLib: Verified Floating-Point Arithmetic in Lean

https://leandojo.org/floatlib.html
1•matt_d•44m ago•0 comments

Driscoll's Gave China Its Blueberries–Then China Swiped the Secret to Growing Th

https://www.wsj.com/business/driscolls-berry-farms-china-competition-b0b49f04
4•harry_nutsachs•46m ago•0 comments

Open-Sourcing Rebalancer: High-Performance Assignment Problem Solver

https://engineering.fb.com/2026/09/21/open-source/rebalancer-generic-high-performance-library-ass...
1•iamsyr•48m ago•0 comments

Lifestreams: A storage model for personal data (1996)

https://dl.acm.org/doi/10.1145/381854.381893
1•dgudkov•49m ago•0 comments

A zero-day has been released for Meta's Muse

https://github.com/pwardle/not-a-mused
2•momentmaker•50m ago•0 comments

I built an autonomous accounting tool to let AI do my taxes

https://github.com/CodeGameDev29/KFAutonomousAccounting
4•7eleven2007•50m ago•1 comments
Open in hackernews

The End of Programming

https://cacm.acm.org/opinion/the-end-of-programming/
14•cumo•1y ago

Comments

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