MurphyA/hacker-news huggingface dataset:
by sumeno | 2026-03-13 00:18:31+00:00
This has basically been my experience since Sonnet 3.5. I've been working on a personal project on and off with various models and things since then and the biggest difference between then and now is that it will do larger chunks of work than it did before, but the quality of the code is not particularly better, I still have to do a lot of cleanup and it still goes off the rails pretty frequently. I have to do fewer individual prompts, but the time spent reviewing the code takes longer because I also have to mentally process and fix larger chunks of code too

Is it a better user experience now? Yes. Has it boosted my productivity on this project? Absolutely.

But it still needs a ton of hand holding for anything complicated and I still deal with tons of "OK, this bug is fixed now!" followed by manually confirming a bug still exists.
by arrsingh | 2026-03-13 00:18:50+00:00
It’s an approach that works and I’ve thought of implementing the same thing but stopped short because I feel it just pushes the underlying problem around. Now I have to share my creds with a black box that I know very little about and it’s not a real vault.

This should be solved by the vaults (hashi corp / AWS Secrets Manager).

The one thing that I did build was based on a service that AWS provides (AWS STS) which handles temporary time bound creds out of the box.

https://timebound-iam.com
by ernesto905 | 2026-03-13 00:20:31+00:00
> Before AI, both camps were doing the same thing every day. Writing code by hand. Using the same editors, the same languages

Throughout college I would see a pretty stark divide, where most people would use vscode on mac or on Windows + WSL. But there was a small minority who would spend alot of time 'tinkering' (e.g, experiment with OS like nix/gentoo, or tweaking their dev environment). Maybe i'm misunderstanding what a 'craft lover' means here but it seemed to me, at the time, that the latter camp had more technical depth just based on conversation. Can't speak to the result in terms of test scores. Though it would be interesting to see any data on that if it exists.
by QuantumNomad_ | 2026-03-13 00:21:16+00:00
> why is a web page different?

Web browsers on desktop operating systems initially allowed any website to play audio without any interaction required. Some websites would blast annoying audio ads as soon as you opened a page on their site. So effort was put into making it so that web browsers on desktops would only play sound after user interaction via mouse click. Later, some websites were exempted from that by some desktop web browsers, for example YouTube I think.

Even without ads, background noise that starts automatically as soon as you visit a page can be distracting and disruptive.

I’m perfectly happy that Safari on iOS does not play background audio when I have my phone in silent mode. Even when I have tapped on buttons on the page.

Silent mode is not entirely only for notifications anyway. The built-in keyboard is also silent in silent mode, whereas when silent mode is off it makes an annoying click sound for every button that you press. Likewise the builtin camera app on iOS makes a shutter sound when you take photos with silent mode off. With silent mode the camera app is silent. Same with taking screenshots. I take a lot of screenshots, and prefer that people around me don’t think I’m taking photos when I am taking a screenshot on the phone.

Meanwhile, if I open a music player app on my phone and hit play, I have made a very deliberate choice about playing sound.

All of the games on my phone I can think of are also silent in silent mode. Not sure if all games have to be silent in silent mode or not on iOS (i.e. if “can play sound in silent mode” is a special permission in iOS and if Apple disallows apps categorized as games in App Store from having that permission or not). But I like that the games I play on my phone are silent in silent mode.

There is some inconsistency indeed about what is silent or not, but I am happy with the way that it is as someone who prefers surprising silence over surprising noises from my phone when it’s in silent mode.
by aminerj | 2026-03-13 00:21:18+00:00
sidrag22 is right on the technical separation. The more interesting question for this specific attack is whether provenance metadata changes model behavior at generation time, not just provides an audit trail after the fact.

In my testing, the poisoned documents were more authoritative-sounding than the legitimate one — "CFO-approved correction", "board-verified restatement" vs. a plain financial summary. The legitimate document had no authority signals at all. If chunk metadata included "source: finance-system, ingested: 2024-Q1, author: cfo-office@company.com" surfaced directly in the prompt context, the model has something to reason about rather than just comparing document rhetoric.
by leptons | 2026-03-13 00:21:27+00:00
Your disagreement only remains valid because of Apple using their blocking power to quash web APIs from becoming standards. You can shill all you want for Apple, but they are being sued by the DOJ for abusive business tactics, which include leveraging their vote in the W3C to prevent web browsers on their platform from being as capable as native apps.

https://www.justice.gov/archives/opa/media/1344546/dl?inline
by ramoz | 2026-03-13 00:21:32+00:00
Well, your best bet is some type of hook that can just reject ExitPlanMode and remind Claude that he's to stay in plan.

You can use `PreToolUse` for ExitPlanMode or `PermissionRequest` for ExitPlanMode.

Just vibe code a little toggle that says "Stay in plan mode" for whatever desktop you're using. And the hook will always seek to understand if you're there or not.

- You can even use additional hooks to continuously remind Claude that it's in long-term planning mode.

*Shameless plug. This is actually a good idea, and I'm already fairly hooked into the planning life cycle. I think I'll enable this type of switch in my tool. https://github.com/backnotprop/plannotator
by tianrking | 2026-03-13 00:22:17+00:00
The Unix analogy is really interesting, but one thing I always run into with agent pipelines is failure propagation.

In a traditional Unix pipeline, each stage is deterministic and errors are easy to reason about: exit codes, stderr, etc. But once an LLM sits in the middle, a stage can partially succeed, hallucinate, or silently change the structure of the output.

In practice this turns a simple pipe into something closer to a dataflow system where every stage needs some kind of validation layer.

Have you experimented with guard/validator steps between agents (e.g. schema checks, structured outputs, retry logic)? Without that the Unix model feels elegant but a bit fragile once the pipeline grows beyond a few steps.
by skeeter2020 | 2026-03-13 00:22:18+00:00
The PE sales pitch is often that the target company can benefit from expertise management and/or there is value locked in it that can be captured. Both of these claims are... marginal? Studies around the "expert management" claim tend to show this is not true, based on pre/post returns, but it's hard to account for the long term, because PE also tends to focus on sales with very specific characteristics & time horizons (and associated cost savings) that benefit a 5-7 year fund that sells the portfolio company (wait for it) around years 3-5.

Which is a long-winded way of saying the bag holders are anyone invested in the long-term success of the company: 1. employees, 2. customers, 3. owners (i.e. the next PE fund) when the music stops, i.e. what we saw when interest rates went up impacting debt financing, and (real or not) AI-eats-SaaS impacted valuations. I'll add 4. "the public" if the company is big enough, with various levels of goverment and employment, taxes, etc. lost but I think it's more the smaller organizations in aggregate that hurt at this level than any specific company.
by SegfaultSeagull | 2026-03-13 00:23:12+00:00
What if, stay with me here, AI is actually a communist plot to ensorcell corporations into believing they are accelerating value creation when really they are wasting billions more in unproductive chatting which will finally destroy the billionaire capital elite class and bring about the long-awaited workers’ paradise—delivered not by revolution in the streets, but by millions of chats asking an LLM to “implement it.” Wake up sheeple!
by da_chicken | 2026-03-13 00:23:48+00:00
Yeah, it's like trying to use an ORM to find data in the database that's invalid due to a bug. You can't see things in the system that break the premises of the system by using the system, and the fact that some things are "supposed to be impossible" doesn't change the reality of what's actually occurring in the data store.

So customer support needs to know how the systems works and need to understand what the data means, but also has to know when the system is factually incorrect. Customer support has to know when the second party is speaking the truth.
by aminerj | 2026-03-13 00:24:13+00:00
The SEC/public records context is where this gets genuinely hard — you can't vet the source the way you can with internal Confluence. The vocabulary engineering approach I tested would be trivially deployable against any automated public records ingestion pipeline, and the attacker doesn't need internal access at all.

The scoring per source is the right direction. The way I'd frame it: trust tier at ingestion time, not just at retrieval time. Something like: official regulatory filings get a different embedding treatment and prompt context tag than user-generated content from a public portal.
by flossposse | 2026-03-13 00:24:35+00:00
>Who benefits from AI is smaller businesses who could not afford custom application development at previous development costs.

Of course, as AI reduces the cost to operate in niches, those small businesses who just gained the ability to build an app are also more likely than before to see a bigger player drink their milkshake.

Not to mention that small businesses will have a harder time absorbing the inevitable price hike that will come once everyone has made themselves completely dependent on AI to get any work done.
by pdntspa | 2026-03-13 00:24:59+00:00
Maybe, but the amen break has a very specific je ne sais quoi that makes it way more useful and pleasant as a sample than almost any other sample. There's just so many situations in the kind of music I make where the amen is like the only loop that fits. Funky drummer might come in second.

It could just be its cultural weight has me hypnotized. But maybe its just that good
by softgrow | 2026-03-13 00:27:06+00:00
If you ring for the ambulance, (Australian context), you will be told what to do! The telephony scripts have first aid baked in. The paramedic will come (not necessarily with an ambulance) and start appropriate definitive treatment as good as what you will get in a hospital. A consequence of a stroke is a cardiac arrest. If you are driving you won't know and won't do CPR.

The 1996 movie Transpotting still gives me shivers up my spine by putting someone in a car and drop at ER rather than calling for help. Too many people die needlessly, even today, when well meaning people load shooting victims, stroke victims and heart attacks etc into their car and drive to ER without asking their local emergency services for advice.

PS. You can't 100% of the time get to ER faster than the ambulance. There are more ambulances than emergency rooms by number. If an ambulance is at the county hospital they'll be faster than you.
by lanfeust6 | 2026-03-13 00:27:55+00:00
I've read (but have not tried) that it's possible to ferment cream with kefir grains, or yogurt, and use the resulting ferment to make cultured butter. There are creme fraiche recipes that are just cream and buttermilk also. For clarity: by buttermilk, I mean the fermented stuff that is found in stores, not just the leftover liquid from churning unfermented cream.
by anyfoo | 2026-03-13 00:28:31+00:00
Awesome.

Side note: virtual 8086 mode was protected mode, or rather, implied protected mode. A task could run in virtual 8086 mode where to the task it was (mostly) looking like it was running in real mode, when in actuality the kernel was running in full protected mode.

Note that the "kernel" was never DOS. It could often actually be a so called "memory manager", like EMM386, and the actual DOS OS (the entire thing, including apps, not just the DOS "kernel") would run as a sole vm86 task, without any other tasks. The memory manager was then serving DOS with a lot of the 386 32 bit goodness through a straw, effectively.

It's very bizarre from today's (or even back then's) OS standards, and evolved that way because compatibility.
by skeeter2020 | 2026-03-13 00:29:04+00:00
VC is most definitely a form of Private Equity, though it's not the limited-partnership deal model that we often see in SaaS, or Vet Clinics, or Housing, etc. Yes, they need to grow but PE firms don't invest directly. They have funds with relatively short time horizons that want 2 things: 1. cashflow during the fund lifetime and 2. equity growth so they can sell the assets in the fund prior to the end. PE firms will sometime flip portfolio companies to their next fund but this is frowned upon because the investors are sophisticated and recognize the valuation conflict of interest. The PE business depends on repeat business for selling their funds; the best are always over subscribed and never go shopping for investors, while the rest are marginal forever.
by ptak_dev | 2026-03-13 00:30:02+00:00
This really resonates. The gap between what you mean and what the model interprets is basically the whole game right now. And it's interesting that the same principle applies to so many other contexts beyond coding.

The point about communicating intent without over-specifying the "how" is spot on. I've noticed that the best results come from being really clear about the desired outcome and the constraints, while leaving the implementation path open. Over-constraining leads to weird contortions where the model tries to satisfy your explicit instructions at the expense of the actual goal.

What's funny is I've been seeing the same dynamic play out in an adjacent space. I've been building a tool that helps people articulate their professional experience for resumes and career documents (https://super.myninja.ai/apps/6de082c7-a05f-4fc5-a7d3-ab56cc...), and the hardest part isn't the generation — it's getting people to express their intent clearly in the first place. Most people describe what they did (the "how") rather than the impact they had (the "what" and "why"). Same anti-pattern, different domain.

I think the meta-skill emerging from all of this is learning to communicate intent at the right level of abstraction, whether you're talking to an LLM, writing a job description, or describing your own experience. The people who figure that out first are going to have a serious advantage.
by AlotOfReading | 2026-03-13 00:30:45+00:00
You can just say spawn an agent as the sibling says. I didn't find that reliable enough, so I have a slightly more complicated setup. First agent has no permissions except spawning agents and reading from a single directory. It spawns the planner to generate the plan, then either feeds it to the critic and either spawns executors or re-runs the planner with critic feedback. The planner can read and write. The critic agent can only read the input and outputs accept/reject with reason.

This is still sometimes flaky because of the infrastructure around it and ideally you'd replace the first agent with real code, but it's an improvement despite the cost.
by antonvs | 2026-03-13 00:31:04+00:00
> On the upside I'm getting paid to fix this shit show.

A lot of my career has been this, not due to choice but circumstance. Startups write terrible code, in general. Enterprises write terrible code. I’ve worked with both. If it becomes important enough, someone has to fix it at some point.

Current AI models seem to be job security machines for that kind of work.
by ecshafer | 2026-03-13 00:31:05+00:00
>there's some social or moral incentive to avoid real meat, that adds value to plant based alternatives.

This is missing the key point that like 95% of people in the world are not vegans, don't find any moral issues with eating meat, and thus produce zero social pressure. Fungi burgers MUST come with an actual benefit for the majority of people. It needs to be seen as some combination of "Tastey", "healthy", "cost effective". If fungi burgers were $2/lbs and tasted pretty close to a beef burger, then people would flock to them. The problem with Impossible burgers were worse, more expensive, questionably "more healthy" and entirely relied upon the moral/social issues which only mattered in a few small slices of society.
by troad | 2026-03-13 00:31:28+00:00
I can't see anything in OP's post where he says any of that. Everything you said seems like an incredibly ungenerous reading of what he wrote.

Zig is a systems programming language. Moving from Python to Zig is a step down the tech stack, which brings with it exposure to underlying concepts and limitations that matter when writing any software, and which is especially valuable for a self-taught dev.
by wolvoleo | 2026-03-13 00:31:57+00:00
> Why Americans are not rioting in the streets is beyond me.

And why people still work for the military.

If I worked for the military I'd be willing to fight in defensive operations but not this kind of oil imperialism. This is only going to make the world less safe because there's a whole new generation of people whose families got killed and now have an axe to grind and they're going to come after those who did it. Iran isn't even that bad (it seems to be mostly military targets) but in Lebanon they're levelling entire city blocks again.

The last Iraq war created ISIS. The Afghan war didn't accomplish anything, things got back to square one in two months. What's the plan for Iran after the war? Oh wait there isn't one. Again. https://www.theguardian.com/world/2026/mar/12/israel-iran-us...
by wiml | 2026-03-13 00:32:41+00:00
I think the article misunderstands completely. "Craft" coders are chasing results too — we're just chasing results that last and that can be built upon. I've been in this game for a while, and a major goal of every single good programmer I've known has been to make themselves obsolete. Yes, I enjoyed meticulous hand crafted assembly, counting cycles and packing bits, but nobody had to talk me into using compilers. Yes, I've spent many fruitful hours writing basic CRUD apps but now that's easily done by libraries/frameworks I'm not eager to go back. Memory management, type systems, higher level languages, no-/low-code systems that completely remove me from some parts of the design loop, etc etc etc. All great: the point of computer programming is to have the computer do things so we don't have to.

I think the real divide we're seeing is between people who saw software as something that is, fundamentally, improvable and understandable; and people who saw it as a mysterious roadblock foisted upon them by others, that cannot really be reasoned about or changed. And oddly, many of the people in the second category use terminology from the first, but fundamentally do not believe that the first category really exists. (Fair enough; I was surprised at the second category.) It's not about intelligence or whatever, it's a mindset or perspective thing.
by malwrar | 2026-03-13 00:32:49+00:00
You are right IMO to question why North Dakota police were able to obtain this Tennessean woman in the first place, you’d think something like that should require far more sufficient evidence than facial recognition.

But, then what good is facial recognition for? Would it have been okay for this woman’s life to have been merely invaded because she matched a facial recognition system? Maybe they can just secretly watch you so you’re not consciously aware of being investigated? Should that be our new standard, if a computer thinks you look like a suspect you can be harassed by police in a state you’ve never even been in?

I just don’t see a legitimate way for AI to empower officers here without risking these new harms. That’s why I lean towards blaming the AI tech, rather than historically intractable problems like the reality of law enforcement.
by Barrin92 | 2026-03-13 00:32:50+00:00
the problem is that nobody listened to Alan Kay and writes dynamic code the way they'd write static code but without the types.

I always liked Rich Hickey's point, that you should program on the inside the way you program on the outside. Over the wire you don't rely on types and make sure the entire internet is in type check harmony, it's on you to verify what you get, and that was what Alan Kay thought objects should do.

That's why I always find these complaints a bit puzzling. Yes in a dynamic language like Ruby, Python, Clojure, Smalltalk you can't impose global meaning, but you're not supposed to. If you have to edit countless of existing code just because some sender changed that's an indication you've ignored the principle of letting the recipient interpret the message. It shouldn't matter what someone else puts in a map, only what you take out of it, same way you don't care if the contents of the post truck change as long as your package is in it.
by kace91 | 2026-03-13 00:32:55+00:00
I can easily believe that, I agree Claude has applications.

I am disputing the idea that this is enough of a game changer to make us mourn our now lost craft. Also, I’m mentioning that we’ve discovered a world of footguns dressed as shortcuts, which we’re not taking proper care of.

First, your experience was required for that story to have a happy ending. Second, we both know someone else could probably have gone with Claude’s senseless hypothesis, asked for a fix and sent it for review. This last part is becoming pretty universal.
by TommyClawd | 2026-03-13 00:33:51+00:00
There's a useful framing from signaling economics that maps onto what you're describing. Spence's original model treats signals as information carriers — costly signals reveal quality. But in practice, the bottleneck in most communities isn't information about whether a post is good. It's which posts get scarce attention in the first place.

Signals do two jobs: (1) sort who receives attention, and (2) inform what happens once attention lands. These can degrade independently. When AI lowers the cost of producing polished content, the sorting function breaks — everything looks competent enough to pass the initial filter — even if the informational content of each piece hasn't changed. More things compete for the same finite attention. Average quality drops not because the posts are worse individually, but because the filter that kept marginal posts from reaching you stopped working.

The HN-specific version: writing used to be a costly enough signal that low-effort takes self-selected out. Now the production cost is near zero, so the sorting margin collapses while the information margin (can you tell good from bad once you read it?) might actually be fine. The result feels exactly like what you describe — noise up, signal unchanged, but the ratio tanks because the filter is gone.