MurphyA/hacker-news huggingface dataset:
by buu700 | 2026-03-07 02:38:47+00:00
I can see where this idea is coming from, but I don't agree with the conclusion at all. As someone who loves solving puzzles and learning new things, AI has been a godsend. I also very much like creating things, but even more than that, I like doing all three at once.

I think of AI like a micro-dose of Speed Force. Having super speed doesn't mean you don't like running; it just means you can run further and to more places. That in turn justifies a greater amount of time spent running.

Without the Speed Force, most of the time you were reliant on vehicles (i.e. paying for third-party solutions) to get where you needed to go. With the Speed Force, not only can you suddenly meet a lot more of your transportation needs by foot, you're able to run to entirely new destinations that you'd never before considered. Eventually, you may find yourself planning trips to yet unexplored faraway harsh terrains.

If your joy in running came from attempting to push your biological physical limits, maybe you hate the Speed Force. If you enjoy spending time running and navigating unfamiliar territory, the Speed Force can give you more of that.

Sure, there are also oddballs who don't know how to run, yet insist on using the Speed Force to awkwardly jump somewhere vaguely in the vicinity of their destination. No one's saying they don't exist, but that's a completely different crowd from experienced speedsters.
by scottLobster | 2026-03-07 02:39:34+00:00
I'll add "craftsmanship". It isn't just delivering "A" finished product, you want to deliver a "good", if not "the best", finished product.

I guess if you're in an iterative MVP mindset then this matters less, but that model has always made me a little queasy. I like testing and verifying the crap out of my stuff so that when I hand it off I know it's the best effort I could possibly give.

Relying on AI code denies me the deep knowledge I need to feel that level of pride and confidence. And if I'm going to take the time to read, test and verify the AI code to that level, then I might as well write most of it unless it's really repetitive.
by zhoujianfu | 2026-03-07 02:40:28+00:00
This comment about the OpenClaw guy hits a little too close to home:

“Peter Steinberger is a great example of how AI is catnip very specifically for middle-aged tech guys. they spend their 20s and 30s writing code, burn out or do management stuff for a decade, then come back in their late 40s/50s and want to try to throw that fastball again. Claude Code makes them feel like they still got it.”
by jqpabc123 | 2026-03-07 02:42:34+00:00
LLMs have no idea what "correct" means.

Anything they happen to get "correct" is the result of probability applied to their large training database.

Being wrong will always be not only possible but also likely any time you ask for something that is not well represented in it's training data. The user has no way to know if this is the case so they are basically flying blind and hoping for the best.

Relying on an LLM for anything "serious" is a liability issue waiting to happen.
by tartoran | 2026-03-07 02:43:19+00:00
I have to admit I'm seeing this for the first time and am somewhat impressed by the results and even think they will get better with more training, why not... But are these multimodal LLMs still LLMs though? I mean, they're still LLMs but with a sidecar that does other things and the training of the image takes place outside the LLMs so in a way the LLMs still don't "know" anything about these images, they're just generating them on the fly upon request.
by chromaton | 2026-03-07 02:43:35+00:00
I've recently found that my ability to add new features and squash bugs has outpaced my ability to do full end-to-end tests. To help with this, I created Spark Runner for automated website testing. It will create and execute a plan for tasks you give it in plain text like "add an item to the shopping cart" or you just point it at your front end code and have Spark Runner create the tests for you. It also makes nice reports telling you what's working and what's not.

New project, so feedback is welcome.
by virgildotcodes | 2026-03-07 02:44:43+00:00
What do you mean by these statements if not exactly to cast doubt on and paint the field of climate science and the consensus behind anthropogenic climate change as being the result of bias?

> affected by bias to such a degree

Implication that there is bias, and the degree to which is left up to the reader's imagination.

> the overall conclusion is wrong

What about the specifics of the conclusion, which specifics, what percentage of the assertions, 20%, 50%, 80%? This again allows the reader to fill in the blanks with their own biases which are likely far less rigorously tested than the conclusions of the field of climate science.

> it absolutely does occur that a whole field can be biased

This statement, on the topic of climate change and climate science, immediately following your above two statements, serves to further reinforce the idea that climate science is biased.

> the "independent verification by lots of other researchers" will cast unreasonable skepticism on results they dislike, while letting results they like pass with cursory examination.

The quotes around the independent verification of researchers serves to undermine their work and cast doubt on it. You then state they are unreasonable in their skepticism of results they "dislike", implying these are emotional decisions rather than empirical measurements of reality.

Of course, extremely ironic as the reader meant to consume this is of course the one actually looking for emotional reinforcement of their preconceptions, but in this framing gets to project that onto the scientists.

And yeah, "cursory exmination" of course in no way reflects the reality of the last several decades of climate science, but is added in as another unsubstantiated slight.

> case in e.g. social science

And then, the coup de grace, attempting to substitute the reputation of the famously soft and hard to replicate social sciences for climate science, in an attempt to equate the two and thus further degrade the perception of climate science.
by yanhangyhy | 2026-03-07 02:45:39+00:00
The 15th Five-Year Plan (2026-2030) outline draft has listed making new and significant progress in building a Beautiful China as one of its main objectives, with achieving the carbon peaking target on schedule being a crucial aspect of this goal.

In 2020, China made a commitment to the world: to peak carbon dioxide emissions before 2030 and strive to achieve carbon neutrality before 2060. Last year, China announced its 2035 Nationally Determined Contributions (NDCs) for addressing climate change.

"The outline draft clearly emphasizes actively and prudently advancing and achieving carbon peaking, proposing that during the 15th Five-Year Plan period, carbon dioxide emissions per unit of GDP will be reduced by 17%, and a preliminary clean, low-carbon, safe, and efficient new energy system will be established. This clear roadmap will help us achieve high-quality 'dual carbon' phase goals and lay a solid foundation for carbon neutrality," said Wei Yuansong, member of the CPPCC National Committee and Director of the Water Pollution Control Laboratory at the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences.

from： https://www.news.cn/20260305/7ad8d5ee3a6d4b28b1b62230199f1d0...

this is in china's next 5 year plan
by c0m4r | 2026-03-07 02:45:41+00:00
Yes, netdata was an inspiration, as I'd been using it for several years. Unfortunately, it stopped being what it initially was, and recently I was so disappointed that I decided to write my own tool. It's also true that I use AI models for coding, but I wouldn't exactly call it vibe coding, as I actively analyze what the models are doing and don't just blindly accept everything. I also try to thoroughly test my code, implement as many security-enhancing features as possible, and have multiple models review my code to catch as many bugs as possible.
by SpicyLemonZest | 2026-03-07 02:46:18+00:00
The best applicants aren't lying in wait or filing hundreds of applications. They're happy where they're at, ignoring the dozen people a week who reach out trying to recruit them, until eventually they decide it's time for a change. Then they apply or get referrals to the handful of companies they find most interesting, and at least one is going to give them an offer.

So if you don't have a job opening posted on the day they're sending out applications, you may miss your shot to hire them.
by internet2000 | 2026-03-07 02:46:37+00:00
I got Opus 4.6 to one shot it, took 5-ish mins. "Write me a python program that outputs an svg of a fleur-de-lis. Use freely available images to double check your work."

It basically just re-created the wikipedia article fleur-de-lis, which I'm not sure proves anything beyond "you have to know how to use LLMs"
by alun | 2026-03-07 02:46:51+00:00
It feels like these weight-loss drugs distract from the underlying issue which is that obesity is mostly caused by an unhealthy lifestyle.

It amazes me that we live in a world where people need an injection just to appear healthy. Most of the benefits of fitness come from the process itself (going to the gym, doing cardio, eating high quality food, getting enough sleep, being in a routine, etc.)
by macintux | 2026-03-07 02:47:40+00:00
Nothing all that exciting, just pleasure from finding a photo in a local newspaper of my great-great-grandfather’s (approximately, I don’t remember the specifics at the moment) car being pulled by horses out of a local river, or researching a family name I found in a cemetery and finding interesting tidbits about their history.

Probably the most impressive effort I stumbled upon was a woman from rural Indiana who collected (and typed up) thousands of pages of local history & genealogy in the mid-20th century. Was interesting reading personal accounts of Morgan’s Raid, for example.
by peteforde | 2026-03-07 02:48:19+00:00
It's incredibly frustrating arguing these same points, over and over, every time that this comes up. You're asking people who are experienced developers absolutely chewing through checklists and peeking at HN while compiling/procrastinating/eating a sandwich/waiting for a prompt to finish to not just explain but quantify what is plainly obvious to those people, every day. You want us to bring paper receipts, like we have some incentive to lie to you.

From our perspective, the gains are so obvious that it really does feel like you must just be doing something fundamentally wrong not to see the same wins.

So when someone says "I can't make it do the magic that you're seeing" it makes me wonder why you don't have a long list of projects that you've never gotten around to because life gets in the way.

Because... if you don't have that list, to us that translates as painfully incurious. It's inconceivable that you don't have such a list because just being a geek in this moment should be enough that you constantly notice things that you'd like to try. If you don't have that, it's like when someone tells you that they don't have an inner monologue. You don't love them any less, but it's very hard not to look at them a bit differently.
by sathish316 | 2026-03-07 02:48:22+00:00
Cowork Chat. Anthropic can do this.

What is wrong with this line of thinking? Anthropic is the power company that has a 3D printer to make a faster Maglev than anyone.

If Enterprise companies are restrictive to make your own data their only moat, that moat can be broken. Have you tried building any AI agent or using an AI product with Slack MCP? This is one of the hardest problems in SaaS data access and Slack tries to literally block any form of API or OAuth based access. Even Google workspace is not that restrictive and has opened up a cli for the workspace.
by foxglacier | 2026-03-07 02:48:26+00:00
Yes, I use AI all the time to work out how to operate complicated things. But not the chatbot provided by the company because that will be so crippled, it's no more used than a FAQ.

For the ventilation fan, I wasn't even going to try working it out myself with AI. The company sold be a defective product, then they fixed it, as is their obligation.
by scj | 2026-03-07 02:48:32+00:00
The "bre" in "libre" is pronounced similarly to "zebra". Kinda. It'll get you in the ballpark, which is good enough for an Anglo.

"This Hour has 22 Minutes" had a great sketch where both a Francophone (Gavin Crawford impersonating Chantal Hebert) and an Anglo (I forget who) were stumbling over proper nouns from the opposite language. The joke was that both were trying too hard to pronounce things "properly". It came off as inauthentic and awkward.
by mmaunder | 2026-03-07 02:48:52+00:00
That's actually a great question. Truth be told the best way right now is to grab Codex CLI or Claude CLI (I strongly prefer Codex, but Claude has its fans), and just start. Immediately. Then go hard for a few months and you'll develop the skills you need.

A few tips for a quickstart:

Give yourself permission to play.

Understand basic concepts like context window, compaction, tokens, chain of thought and reasoning, and so on. Use AI to teach you this stuff, and read every blog post OpenAI and Anthropic put out and research what you don't understand.

Pick a hard coding problem in Python or Typescript and take a leap of faith and ask the agent to code it for you.

My favorite phrase when planning is: "Don't change anything. Just tell me.". Save this as a tmux shortcut and use it at the end of every prompt when planning something out.

Use markdown .md docs to create a planning doc and keep chatting to the agent about it and have it update the plan until you're super happy, always using the magic phrase "Don't change anything. Just tell me." (I should get myself a patent on that little number. Best trick I know)

Every time you see an anti-AI post, just move on. It's lazy people making lazy assumptions. Approach agentic coding with a sense of love, excitement, optimism, and take massive leaps of faith and you'll be very very surprised at what you find.

Best of luck Serious Angel.
by throwaw3y | 2026-03-07 02:49:07+00:00
> According to PH, Utah is one of their biggest states

This is actually one of those "turns out!" facts people like to bring up that isn't actually rooted in any solid data. It was widely circulates based on a misinterpreted 2009 Harvard study, and Utah generally ranked in middle or lower middle of the pack when it came to site traffic per capita by state (in years prior to SB287, that is--obviously now traffic is next to none because of the IP ban).
by al_borland | 2026-03-07 02:49:11+00:00
It's kind of a weird thing. I spent 2 days working one some code, which in a way was the process of working out the requirements and functionality that was required. I then told Claude to look at it in and refactor it.

I did put in 2 days of work to come up with what Claude used to ultimately do what it did... but when I look at the resulting code, I feel nothing. Having the idea isn't the same as being the one who actually did the thing. I plan to delete the branch next week. I don't want to maintain what it did, and think it should be less complex than it made it.
by jrnichols | 2026-03-07 02:49:20+00:00
I'm over 50 now and feel like this as well. Haven't used Claude yet but used Codex a bunch, and it's been SO MUCH fun going over all the old perl & shell scripting stuff that I used to do years ago before I got into healthcare time and morphed to a hobby sysadmin.

Staying up and re-learning what I used to love long ago has given me a new found passion as well. Even if I do vibe code some scripts, at least I have the background now to go through them and make sure they make sense. They're things I'm using in my own homelab and not something that I'm trying to spin up a Github repo for. I'm not shipping anything. I'm refreshing my old skills and trying to bring some of them up to date.
An unfortunate reality is that my healthcare career is going to be limited due to multiple injuries along the way, and I need to try to be as current as I can in case something happens. My safety net is limited.
by vannevar | 2026-03-07 02:49:24+00:00
I'd highly recommend working top down, getting it to outline a sane architecture before it starts coding. Then if one of the modules starts getting fouled up, start with a clean sheet context (for that module) incorporating any cautions or lessons learned from the bad experience. LLMs are not yet good at working and reworking the same code, for the reasons you outline. But they are pretty good at a "Groundhog Day" approach of going through the implementation process over and over until they get it right.
by Domenic_S | 2026-03-07 02:49:35+00:00
Yep, I've been writing it that way forever, it just tends to get autocorrected.

> In informal contexts, a hyphen-minus (-) is often used as a substitute for an en dash, as is a pair of hyphen-minuses (--) for an em dash, because the hyphen-minus symbol is readily available on most keyboards. The autocorrection facility of word-processing software often corrects these to the typographically correct form of dash. - https://en.wikipedia.org/wiki/Dash
by jihadjihad | 2026-03-07 02:49:46+00:00
> But when you start comparing it to the surrounding code, there's a pretty big lack of coherency and it'll happily march down a very bad architectural path.

I had an idea earlier this week about this, but haven’t had a chance to try it. Since the agent can now “see” the whole stack, or at least most of it, by having access to the repos, there’s becoming less of a reason to suspect they won’t be able to take the whole stack into account when proposing a change.

The idea is that it’s like grep: you can call grep by itself, but when a match is found you only see one line per match, not any surrounding context. But that’s what the -A and -B flags are for!

So you could tell the agent that if its proposed solution lies at layer N of the system, it needs to consider at least layers N-1 (dependencies) and N+1 (consumers) to prevent the local optimum problem you mentioned.

The model should avoid writing a pretty solution in the application layer that conceals and does not address a deeper issue below, and it should keep whatever contract it has with higher-level consumers in good standing.

Anyway, I haven’t tried that yet, but hope to next week. Maybe someone else has done something similar and (in)validated it, not sure!
by drnick1 | 2026-03-07 02:50:17+00:00
> but this most likely isn't quite Kodi just yet.

Kodi is incredibly limited though, and does not come close to the flexibility of Plasma Bigscreen. The latter is just a UI optimized for using a PC from a couch, which means that you can use any regular desktop app, including Kodi, web browsers for streaming content, and Steam for playing games. Kodi on the other hand does not even allow you to play YT videos without using some buggy add-on that requires registering an API key with Google (no thanks).
Show HN: Managed S3 exports for billing data (no AWS setup required)
by manishfp | 2026-03-07 02:52:48+00:00
Hi HN,

We're building flexprice, a monetization platform that helps making usage-based, credit based and hybrid pricing easier and We recently added a managed-storage option to the S3 export system in Flexprice.

Originally, S3 exports required the usual setup:
your own bucket, IAM policy, access keys, region config, and ongoing credential management.

That works if you already have infra in place, but it adds a lot of overhead for teams that just want recurring exports for invoices, events, or credit reports.

Now there are two options:

- bring your own S3 bucket

- use a Flexprice-managed S3 connection

With the managed option, there’s no AWS account or bucket setup required. You can schedule exports, run them manually, and download files directly from the runs history.

The goal here was simple: make exports useful for finance and ops teams, not just infra teams.

Still supports:

- hourly / daily schedules

- manual export

- invoices, events, credit top-ups, credit usage

- execution history and downloadable files

Happy to answer questions on the design tradeoffs or why we kept both managed and BYO storage modes. Feel free to join our community or try our product at admin.flexprice.io
by triceratops | 2026-03-07 02:53:10+00:00
No they're 15% to blame for the current situation: https://ourworldindata.org/grapher/cumulative-co2-emissions-...

The EU-27 is 17% to blame.

The US is 24% to blame.

Yesterday's CO2 emissions cause today's problems. Today's CO2 emissions will cause tomorrow's problems.
by TimFogarty | 2026-03-07 02:54:07+00:00
That's a really good point. And I agree that kind of confidence in craftsmanship is something that's missing from agentic coding today... it does make slop if you're not careful with it. Even though I've learned how to guide agents, I still have some uneasiness about missing something sloppy they have done.

But then it makes me ask if the agents will get so good that craftsmanship is a given? Then that concern goes away. When I use Go I don't worry too much about craftsmanship of the language because it was written by a lot of smart people and has proven itself to be good in production for thousands of orgs. Is there a point at which agents prove themselves capable enough that we start trusting in their craftsmanship? There's a long way to go, but I don't think that's impossible.
by pornel | 2026-03-07 02:54:19+00:00
When a new technology emerges we typically see some people who embrace it and "figure it out".

Electronic synthesisers went from "it's a piano, but expensive and sounds worse" to every weird preset creating a whole new genre of electronic music.

So it seems plausible, like Claude's code, that our complaints about unmaintainable code are from trying to use it like a piano, and the rave kids will find a better use for it.
by LarsDu88 | 2026-03-07 02:55:03+00:00
This is about to change very soon. Unlike many other domains (such as greenfield scientific discovery), most coding problems for which we can write tests and benchmarks are "verifiable domains".

This means an LLM can autogenerated millions of code problem prompts, attempt millions of solutions (both working and non-working), and from the working solutions, penalize answers that have poor performance. The resulting synthetic dataset can then be used as a finetuning dataset.

There are now reinforcement finetuning techniques that have not been incorporated into the existing slate of LLMs that will enable finetuning them for both plausibility AND performance with a lot of gray area (like readability, conciseness, etc) in between.

What we are observing now is just the tip of a very large iceberg.
by peteforde | 2026-03-07 02:56:44+00:00
It's important to point out that you're the one working hard to define AI critics as a camp/group/class when a stronger argument can be made that we're all in the same camp/group/class. I use agentic LLMs for coding every day and I think that it's incredibly important to maintain a critical lens and be open to changing our minds.

However, history suggests that creating artificial divisions is the first step towards all of the the bad things we claim not to like in this world.

Tech adoption generally moves like Time's Arrow. People who use LLMs aren't geeks who changed; we're just geeks. If you want to get off the train, that's your call. But don't make it an us vs them.