MurphyA/hacker-news huggingface dataset:
by Rochus | 2026-01-13 23:50:31+00:00
That was deliberately just a simple example to give people an impression how the "code" looks which the LLM generates. There is no doubt that you can implement a traffic light with a "traditional" programming approach. The question is rather, why an LLM should produce something which was mostly invented to overcome human weakness, instead of using the much higher potential of this technology. As a programming language author myself I'm interested in the role of programming languages in the age of LLMs; the article represents my conclusions so far.
by el_benhameen | 2026-01-13 23:50:39+00:00
I find the opposite to be true. Once you know the problem you’re trying to solve (which admittedly can be the biggest lift), writing the fist cut of the code is fun, and you can design the system and set precedent however you want. Once it’s in the wild, you have to work within the consequences of your initial decisions, including bad ones.
by functionmouse | 2026-01-13 23:51:03+00:00
Two schools of thinking I flip flop between to rationalize however I'm currently behaving:

a.) Ideas not meaningfully capitalized on are no more useful than delusions. Force yourself to focus with tools.

b.) Don't worry about it; you should be able to think and imagine freely in and about the environment the world has presented you with. When you have The One Right Idea™, you'll know, and it'll be like it's putting itself together in front of you. Allow yourself kindness, understanding, and leniency; only then will your output be pure. Or something.

Maybe it's good to have some of both of these. Maybe I should plan for them in advance.
by duendefm | 2026-01-13 23:51:07+00:00
It's different this time. You can see that at the same time, they are finally, definitely solving hard mathematical problems. They passed the phase of just being like good search engines to being actual generators of new data from their generalizations. I can give you a simple example. Any code they generated before brought frustration and they would loop with feedback. Now they actually produce "human level" code.
by zahlman | 2026-01-13 23:51:09+00:00
Please explain what you think the word "murder" means, first.

Then please explain your understanding of the law, with regards to the circumstances under which LEO are permitted to use their weapons.

Then please watch https://www.youtube.com/watch?v=bDda-L_ZOE8 and cite at least one point of disagreement with the legal argument presented, on any objective grounds (factual or legal).
by bdhe | 2026-01-13 23:51:11+00:00
> A cyberattack targeting an oncology journal has taken it offline that published a peer-reviewed study from Tufts and Brown University exploring links of COVID injections to newly diagnosed or rapidly worsened cancer shortly after COVID injections. Did this have anything to do with your cancer? It doesn't seem like this kind of question is allowed to be entertained either.

We had billions of COVID shots. Even if there was a weak correlation with 1% of the people going on to get rapidly worsening cancer we'd be seeing cancer spikes everywhere. Do we have anything remotely close to that in real life?

Why'd you call him Clott Adams?
by somethingsome | 2026-01-13 23:51:23+00:00
I'm only a data point, but some years ago I spent a whole year learning a mathematical book above my level at the time. It was painful and I only grasped parts of it.

I did again the same book this year, this time spending much time questioning an llm about concepts that I couldn't grasp, copy pasting sections of the book and ask to rewrite for my understanding, asking for fast visualization scripts for concepts, ask to give me corrected examples, concrete examples, to link several chapters together, etc..

It was still painful, but in 2 months (~8h-10h a day) I covered the book in many more details that what I ever could do some years ago.

Of course I still got some memories of the content from that time, and I'm better prepared as I have studied other things in the meantime. Also the model sometimes give bad explanations and bad links, so you must stay really critic about the output. (same goes for plots code)

But I missed a lot of deep insights years ago, and now, everything is perfectly clear in two months.

The ability to create instant plots for concepts that I try to learn was invaluable, then asking the model to twist the plot, change the data, use some other method, compare methods, etc..

Note: for every part, when I finally grasped it, I rewrited it in my own notes and style, and asked the model often to critic my notes and improve a bit. But all the concepts that I wrote down, I truly understand them deeply.

Of course, this is not coding, but for learning at least, LLMs were extremely helpful for me.

By this experiments I would say at least 6x speedup.
by wouldbecouldbe | 2026-01-13 23:51:23+00:00
Developers that can’t see the change are blind.

Just this week, sun-tue. I added a fully functional subscription model to an existing platform, build out a bulk async elasticjs indexing for a huge database and migrated a very large Wordpress website to NextJS. 2.5 days, would have cost me at least a month 2 years ago.
by 19-84 | 2026-01-13 23:51:33+00:00
the data from 2025-12 has been released already, it is usually released every month, it just needs to be split and reprocessed for 2025 by watchful1. i will probably eventually add support for importing data from the monthly arctic shift dumps so that archives can be updated monthly.

https://github.com/ArthurHeitmann/arctic_shift/releases

Arctic Shift
https://academictorrents.com/browse.php?search=RaiderBDev

Watchful1
https://academictorrents.com/browse.php?search=Watchful1
by itishappy | 2026-01-13 23:51:34+00:00
> Shouldn't we reject these people entirely?

Probably, but humanity doesn't seem to have the luxury of rejecting anything in total, and I'm not convinced the attempts are working.

When Scott was rejected he was immediately given a platform by Fox news. Our current regime was rejected quite thoroughly across a number of platforms (the Republican primary, Twitter, Congress, etc.) but here we stand.
by wild_egg | 2026-01-13 23:51:35+00:00
After a certain experience level though, I think most of us get to the point of knowing what that difference in quality actually matters.

Some seniors love to bikeshed PRs all day because they can do it better but generally that activity has zero actual value. Sometimes it matters, often it doesn't.

Stop with the "I could do this better by hand" and ask "is it worth the extra 4 hours to do this by hand, or is this actually good enough to meet the goals?"
by fsflover | 2026-01-13 23:51:49+00:00
GPU acceleration is coming: https://github.com/QubesOS/qubes-issues/issues/8552

> Do you hate using most hardware?

Nobody uses "most hardware". You may be unlucky with your hardware, then it's a problem. Or you can specifically buy hardware working with the OS you want.

> Do you like using Xorg?

What's wrong with Xorg?
by simonw | 2026-01-13 23:51:58+00:00
I'm currently sounding the alarm, because I sincerely believe that the the "it doesn't work, and even if it did you can catch up easily" message is no longer credible as of November 2025.

If I didn't sincerely believe that I wouldn't say it.

It true that you will always be able to tech up - the industry has newbies entering it all the time
and I believe they will continue to make it to point where they can contribute effectively.

But if I'm right and it does take 6-12 months for most developers to get proficient there's a real career risk involved now in listening to people who say it's all hype and no substance.
by plutodev | 2026-01-13 23:52:32+00:00
You’re not alone a lot of founders and builders experience this ADHD-like pattern: intense curiosity, deep focus, then idea overload. Your brain is optimized for exploration, not maintenance, which is why vision comes easy and follow-through feels hard. What helps is having one place to dump ideas, time-boxing deep work, offloading admin, and keeping tools minimal. Switching off is still tough, but physical activity, hard stop routines, and accepting rest as part of productivity make a real difference.
by 9JollyOtter | 2026-01-13 23:52:36+00:00
There is simply no-incentive to. Generally there are many incentives to increase the number of laws, as they can be seen as doing something about a some recent issue. Many of the recent online safety laws (even before OSA) are good examples of this.

Additionally Britain generally has a problem with politicians believing that the only solution to a problem is banning/regulating things, regardless what the root cause might be. Banning/regulating something requires new legal powers. So more laws.

This been true as far back as I can remember with them talking about banning the Lotus Carlton back in the early 90s because one vehicle the infamous 40RR was used in a spate of ram raids which embarrassed the police. I remember this on the news when I was about 9-10 years old.
by onlyrealcuzzo | 2026-01-13 23:52:43+00:00
> Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving.

I think the big problem is that the pace of improvement was UNBELIEVABLE for about 4 years, and it appears to have plateaued to almost nothing.

ChatGPT has barely improved in, what, 6 months or so.

They are driving costs down incredibly, which is not nothing.

But, here's the thing, they're not cutting costs because they have to. Google has deep enough pockets.

They're cutting costs because - at least with the current known paradigm - the cost is not worth it to make material improvements.

So unless there's a paradigm shift, we're not seeing MASSIVE improvements in output like we did in the previous years.

You could see costs go down to 1/100th over 3 years, seriously.

But they need to make money, so it's possible non of that will be passed on.
by jordwest | 2026-01-13 23:52:49+00:00
For me the biggest gaps in LLM code are:

- it adds superfluous logic that is assumed but isn’t necessary

- as a result the code is more complex, verbose, harder to follow

- it doesn’t quite match the domain because it makes a bunch of assumptions that aren’t true in this particular domain

They’re things that can often be missed in a first pass look at the code but end up adding a lot of accidental complexity that bites you later.
Ask HN: How are you preventing LLM hallucinations in production systems?
by kundan_s__r | 2026-01-13 23:52:50+00:00
Hi HN,

For those running LLMs in real production environments (especially agentic or tool-using systems): what’s actually worked for you to prevent confident but incorrect outputs?

Prompt engineering and basic filters help, but we’ve still seen cases where responses look fluent, structured, and reasonable — yet violate business rules, domain boundaries, or downstream assumptions.

I’m curious:

Do you rely on strict schemas or typed outputs?

Secondary validation models or rule engines?

Human-in-the-loop for certain classes of actions?

Hard constraints before execution (e.g., allow/deny lists)?

What approaches failed for you, and what held up under scale and real user behavior?

Interested in practical lessons and post-mortems rather than theory.
by epolanski | 2026-01-13 23:53:04+00:00
Honestly I feel I have never learned as much as I do now.

LLMs remove quite a lot of fatigue from my job. I am a consultant/freelancer, but even as an employee large parts of my job was not writing the code, but taking notes and jumping from file to file to connect the dots. Or trying to figure out the business logic of some odd feature. Or the endless googling for responses lying deep inside some github issue or figuring out some advances regex or unix tool pattern. Or writing plans around the business logic and implementation changes.

LLMs removed the need for most of it which means that I'm less fatigued when it comes to reading code, focusing on architectural and product stuff. I can experiment more, and I have the mental strength to do some leetcode/codewars exercise where incidentally I'll also learn stuff by comparing my solution to others that can then apply back to my code. I am less bored and fatigued by the details to take some time more focusing on the design.

If I want to learn about some new tool or database I'm less concerned with the details of setting it up or exploring its features or reading outdated poorly written docs, when I can clone the entire project in a git subtree and give the source code to the LLM which can answer me by reading the signature, implementation and tests.

Honestly, LLMs remove so much mental fatigue that I've been learning a lot more than I've ever done. Yet naysayers will conflate LLMs as a tool with some lovable crap vibecoding, I don't get it.
by xp84 | 2026-01-13 23:53:27+00:00
Perfectly fair point! Although when I've seen OF stats published the median model makes like $1,000 a year or something. So I think if you took even the top 5,000 models out of the computation, most of them are not earning enough to pay for a nice lifestyle in the moment, let alone funding retirement by the time their beauty declines.

What I think is more likely to happen though with an immigrant OF model (who isn't in that elite earning tier) is that she meets a partner in the US, which affords her an exit strategy if she doesn't want to (or can't) keep doing OF forever.
by jhullse | 2026-01-13 23:53:32+00:00
Location: Brazil

Remote: Yes

Willing to relocate: No

Technologies: Python, FastAPI, TypeScript, Node, React, Next.js, Tailwind, Go, Java, Spring Boot, AWS, Terraform

Résumé/CV: https://docs.google.com/document/d/1WLzFsXfIlFZDn0o-V04Giipp...

Email: jhonatan.hulse@gmail.com

Software engineer with more than 10 years of experience, working remotely for US startups for the past 5 years. I've owned projects end to end with a product mindset that has allowed me to design impactful solutions that brought great value. Here are some of my achievements: At Moskit CRM, I helped the team scale the product and increase its MRR by more than 15 times in less than 3 years. At Jobble, I proposed and led the implementation of an EDA that improved payment reliability and reduced the time spent on payment reconciliation by over 90%. It also improved the efficiency of the engineering team, as the same EDA was used to implement other features. At COVU, I developed a new ETL system that enabled the company to perform complex data analyses that were not possible before, improving the decision-making process.
by observationist | 2026-01-13 23:54:08+00:00
Some sort of hashing and incremental serial versioning type standards with http servers would allow hitting a server up for incremental udpates, allow clean access to content, with rate limits, and even keep up with live feeds and chats and so on.

Something like this in practice breaks a lot of the adtech surveillance and telemetry, and makes use of local storage, and incidentally empowers p2p sharing with a verifiable source of truth, which incentivizes things like IPFS and big p2p networks.

The biggest reason we don't already have this is the exploitation of user data for monetization and intrusive modeling.

It's easy to build proof of concept instances of things like that and there are other technologies that make use of it, but we'd need widespread adoption and implementation across the web. It solves the coordination problem, allows for useful throttling to shut out bad traffic while still enabling public and open access to content.

The technical side to this is already done. Merkle trees and hashing and crypto verification are solid, proven tech with standard implementations and documentation, implementing the features into most web servers would be simple, and it would reduce load on infrastructure by a huge amount. It'd also result in IPFS and offsite sharing and distributed content - blazing fast, efficient, local focused browsers.

It would force opt in telemetry and adtech surveillance, but would also increase the difference in appearance between human/user traffic and automated bots and scrapers.

We can't have nice things because the powers that be decided that adtech money was worth far more than efficiency, interoperability, and things like user privacy and autonomy.
by Cornbilly | 2026-01-13 23:54:12+00:00
I share your fear.

We have a hard enough time finding juniors (hell, non-juniors) that know how to program and design effectively.

The industry jerking itself off over Leetcode practice already stunted the growth of many by having them focus on rote memorization and gaming interviews.

With ubiquitous AI and all of these “very smart people” pushing LLMs as an alternative to coding, I fear we’re heading into an era where people don’t understand how anything works and have never been pushed to find out.

Then again, the ability of LLMs to write boilerplate may be the reset that we need to cut out all of the people that never really had an interest in CS that have flocked to the industry over the last decade or so looking for an easy big paycheck.
by deadbabe | 2026-01-13 23:54:13+00:00
“You’ll get left behind if you don’t learn AI”

Left behind where? We all live in the same world, anyone can pick up AI at any moment, it’s not hard, an idiot can do it (and they do).

If you’re not willing to risk being “left behind”, you won’t be able to spot the next rising trend quickly enough and jump on it, you’ll be too distracted by the current shiny thing.
by TeMPOraL | 2026-01-13 23:54:25+00:00
Yup. The problem was never with the technology replacing work, it was always with the social aspect of deploying it, that ends up pulling the rug under people whose livelihood depend on exchanging labor for money.

The luddites didn't destroy automatic looms because they hated technology; they did it because losing their jobs and seeing their whole occupation disappear ruined their lives and lives of their families.

The problem to fix isn't automation, but preventing it from destroying people's lives at scale.
by perfmode | 2026-01-13 23:54:26+00:00
This is a fun piece to dissect because it's self-aware about being uncharitable, yet still commits the very sin it's criticizing.

The author's central complaint is that LLM evangelists dismiss skeptics with psychological speculation ("you're afraid of being irrelevant"). Their response? Psychological speculation ("you're projecting insecurity about your coding skills").

This is tu quoque dressed up as insight. Fighting unfounded psychoanalysis with unfounded psychoanalysis doesn't refute anything. It just levels the playing field of bad arguments.

The author gestures at this with "I am still willing to admit I am wrong" but the bulk of the piece is vibes-based counter-psychoanalysis, not engagement with evidence.

It's a well-written "no u" that mistakes self-awareness ("I know this isn't charitable") for self-correction.
by bob001 | 2026-01-13 23:54:45+00:00
Having talked to Occupy Wall Street people at the time I don't think many on the ground differentiated as much as you think they did. I used a generic word because from my experience that is how they saw the world. I got told I deserved to have everything I own set on fire for saying I spent $100 on a nice dinner once. That was on the more extreme side but the sentiment seemed to not differentiate.
by woah | 2026-01-13 23:55:03+00:00
The anti-LLM side seems much more insecure. Pro-LLM influencers are sometimes corny, but it's sort of like any other influencer, they are incentivized to make everything sound exciting to get clicks. Nobody was complaining about 3d printer influencers raving about how printing replacement dishwasher parts was going to change everything.

LLMs have also become kind of a political issue, except only the "anti" side even really cares about it. Given that using and prompting them is very much a garbage in/garbage out scenario, people let their social and political biases cloud their usage, and instead of helping it succeed, they try to collect "gotcha" moments, which doesn't reflect the workflow of someone using an LLM productively.
by arnabgho | 2026-01-13 23:55:10+00:00
"LLM evangelists - are you willing to admit that you just might not be that good at programming computers?"

The people who were the best at something don't necessarily be the best at a new paradigm. Unlearning some principles and learning new ones might be painful exercise for some masters.

Military history has shown that the masters of the new wave are not necessarily the masters of the previous wave we see the rise and downfall of several civilizations from Roman to Greek for being too sure of their old methods and old military equipments and strategy.
by stouset | 2026-01-13 23:55:35+00:00
The comments sections in git posts vs. jj posts are always hysterical to me.

If there’s a jj post on HN, people come out of the woodworks to say that git is easy and it’s crazy to suggest that anyone finds it difficult or confusing. Also people saying they’ve figured out git is super usable if you only ever use commit, merge, pull.

Then you have git posts where everyone talks about how hard some basic things are, how easy it is to mess up your repo, how frustrating rebase is, etc.

It’s fun to watch.
by Arch-TK | 2026-01-13 23:55:55+00:00
"actually good enough to meet the goals?"

There's "okay for now" and then there's "this is so crap that if we set our bar this low we'll be knee deep in tech debt in a month".

A lot of LLM output in the specific areas _I_ work in is firmly in that latter category and many times just doesn't work.
by hu3 | 2026-01-13 23:56:09+00:00
This is also bad evangelism, but on opposite side.

Just because LLMs don't work for you outside of vibe-coding, doesn't mean it's the same for everyone.

> LLM evangelists - are you willing to admit that you just might not be that good at programming computers?

Productive usage of LLMs in large scale projects become viable with excellent engineering (tests, patterns, documentation, clean code) so perhaps that question should also be asked to yourself.
by chadcmulligan | 2026-01-13 23:56:24+00:00
I have been through this before (wherever/whenever the money seems to flow) - databases are bad, you should use couchbase etc, I was a db expert, the people advocating weren't, but they were very loud. The many, many evangelistic web development alternatives that come and go, all very loud. Now the latest - LLM's, like couchbase et al they have their place but the evangelists are not having any of it.

I work a lot with doctors (writing software for them), I am very envious of their system of specialisation, eg this dude did is such and such a specialist - he knows about it, listen to him. IT seems to be anyone who talks the loudest has a podium, separating the wheat from the chaff is difficult. One day we will have a system of qualifications I hope, but it seems a long way off.
by robotresearcher | 2026-01-13 23:56:31+00:00
Adams seemed to me to have made a career out of a 'smartest guy in the room' schtick. Someone is always too smart to go along with the norms, such as Dogbert. They see through to what the normies can not. In 'The Religion Wars' there's explicitly 'The Smartest Guy In the World'. It's a version of a Mary Sue.

The problems come when the author believes this about themselves. They probably are smart, and Adams' work is enjoyed because he recognizes and points out stuff that resonates with people. When this is strongly reinforced, too much, too long, I think it's really unhealthy for some people. Adams seemed to need to show that his thought could not be constrained by convention. He got strong, addictive attention for this. He wanted to be thought of as smart, rather than good.

Just my armchair psychology.

I wonder what would have happened to Douglas Adams if he had lived a long life. I wonder what will happen to Scott Galloway. We are watching what's happening to Elon Musk.