MurphyA/hacker-news huggingface dataset:
by solarwindy | 2025-06-06 00:03:37+00:00
My comment was admittedly a little inflammatory, so I’ll try to elaborate on what I find so exasperating about the whole experience of using LLMs for coding (in any form, chat, agent, etc.): at root, it’s their total lack of a model of computation.

This leads to mistakes that are difficult to catch, because while I know the kinds of mistakes another human might make, having been through the process of learning not to make them myself, LLMs produce whole classes of bizarre mistakes that I have no interest in learning to catch. There is no discernible flawed mental model behind these errors—which with a human could be discussed and corrected—just an opaque stochastic process which I can tediously try to set on a better course with ‘incantations’, attempting to dial in to a better part of the training data that avoids the relevant class of error.

It’s honestly amusing how much of ‘prompt engineering’ (if it can be dignified with that term) amounts to a modern-day kind of mysticism. What better can we really do though when these models’ structure and operation is utterly opaque, on the one hand through deliberate, commercially-oriented obfuscation, and on the other because we still just cannot explain how a multi-billion parameter model works.

It’s rewarding to work with human juniors because people actually learn and improve. My learning how to coax these models into producing better than trash just is not, especially on anything either remotely novel, or in a legacy codebase that requires genuine understanding of how an existing system functions at runtime.

Once those two ends of the spectrum are ruled out, I find there’s little left that an LLM can accomplish, without necessitating a loop of prompt refinement that leaves me feeling like a worse developer for not just having thought through the problem myself, and resentful of the time wasted.

Edit: this entire thread about coercing Gemini into behaving is exactly the kind of crap I have zero interest in: https://news.ycombinator.com/item?id=44194061
by sidgarimella | 2025-06-06 00:03:44+00:00
I myself run five IDE's in parallel with ~ 6 terminal sessions all on Claude Code. There's a time and place for each tool. Also, thanks to my Neuralink, I have Linear and Azure MCP's wired directly into my frontal cortex at all times. This makes it really easy to keep our docs up to date without lifting a finger.
by david-gpu | 2025-06-06 00:04:05+00:00
For folks who comment before reading, the article uses "multiple invention" as follows:

"In “How Common is Independent Discovery?,” Matt Clancy catalogues several attempts to estimate the frequency of multiple discovery, and tentatively comes up with a frequency of around 2-3% for simultaneous scientific discoveries, and perhaps an 8% chance that a given invention will be reinvented in the next decade"

I.e. they are not talking about multiple people working together on an invention, but rather parallel discoveries.
by lxgr | 2025-06-06 00:04:29+00:00
> Blaming consumers for choosing the many conveniences of cloud data when the incentive structure has been carefully tailored to funnel our data into their possession and control is truly a superficial take.

Couldn't have said it better.

Just consider Apple as an example: Some time ago, they used to sell the Time Capsule, a local-first NAS built for wireless Time Machine backups. Today, not only has the Time Capsule been discontinued, but it's outright impossible to make local backups of iOS devices (many people's primary computing devices!) without a computer and a USB cable.

Considering Apple's resources, it would take negligible effort to add a NAS backup feature to iOS with polished UX ("simply tap your phone on your Time Capsule 2.0 to pair it, P2P Wi-Fi faster than your old USB cable" etc.) – but they won't, because now it's all about "services": Why sell a Gigabyte once if you can lease it out and collect rent for it every month instead?
by bayindirh | 2025-06-06 00:04:59+00:00
> Is it enough to do an informed decision?

With my layman hat, yes it is. I'll think about a trade-off between site's importance in my life, trustworthiness of the body behind the site, and my privacy.

> You do care, whether you mistyped or the network is down.

No I don't. Because it's easy to check for a typo, and then it's easy enough to investigate like layman. e.g.: Try going to Google, check for your (wireless) connection from your taskbar, every OS shows a "!" when internet is unreachable, and so on...

> but that information was already there and was thrown away.

Sometimes starting with a truncated but accurate info allows a way faster start. Precision and accuracy are different things, and accuracy is more important than precision.
by fazlerocks | 2025-06-06 00:05:21+00:00
Been messing around with the different memory files and honestly it's pretty useful once you get the hang of it.

I mostly use:

Project ./claude.md - team stuff like our weird API naming conventions, how we structure components, deployment steps that always trip people up

Local ./claude.local.md - my dev URLs, test accounts, personal shortcuts. Stuff I don't want to commit to the team file

User ~/.claude/claude.md - code style preferences, how I like explanations (brief vs detailed), tools I always use

The recursive thing is neat - it picks up memories from parent folders so you don't have to duplicate everything.

That # shortcut is way faster than editing files manually. Still forget about /memory command half the time tho.

Main thing I learned is being specific helps a lot. 'Use our error handling pattern' vs actually showing the pattern makes a big difference.
by SalariedSlave | 2025-06-06 00:05:24+00:00
Behavioural patterns are heavily influenced by hormonal balance and as such, success-rates of different self-help strategies (diets, fasting, resistance and/or endurance training) are highly individual. This also extends to addictive behaviours.

"Hormon-typical" individuals have an easier time shaping their behavior because they don't face imbalances that complicate adherence. For them, sticking to a program is trivial. Combine that with lack of reflection, and many of these individuals delude themselves into thinking their success of following simple programs (which are simple in design, and only difficult in adherence) is somehow an accomplishment worthy of note. Low-empathy individuals, in particular, often interpret this as evidence of their own superiority, while dismissing others as mediocre.

So you see such comments a lot, because many people are "hormon-typical" and also low empathy. See any discussion about diet, fitness, Ozempic, etc.
by rvz | 2025-06-06 00:06:33+00:00
We both already know it's very obvious that the layoffs are due to them getting away with actually doing more with less using AI.

Evidently:

1. After the layoffs that happned at Meta, it is reported that they are building (and using) AI coding agents to become even more efficient, same with Google. [0] 2. Duolingo went all in and replaced their contract workers with AI. [1] 3. Microsoft CEO says "up to 30% of the company’s code was written by AI" [0] then laid off 3% of workers (6K employees), including engineers. [2] 4. Business Insider went "AI first" with 70% of employees using ChatGPT and then lays off 21% of their workers. [4] 5. After Salesforce laid off 1,000 their workers in Feburary 2025, they now said that "the use of artificial intelligence tools internally has allowed it to hire fewer workers" and additionally said: "We view these as assistants, but they are going to allow us to have to hire less and hopefully make our existing folks more productive." [5]

The list goes on and on in 2025 alone and this further strengthens my whole point that companies will be doing more with less knowledge workers and these workers still have a lot more to lose, rather than gain if they don't use AI.

[0] https://www.entrepreneur.com/business-news/ai-is-taking-over...

[1] https://www.entrepreneur.com/business-news/duolingo-will-rep...

[2] https://www.forbes.com/sites/chriswestfall/2025/05/13/micros...

[3] https://www.forbes.com/sites/jackkelly/2024/11/01/ai-code-an...

[4] https://www.businessinsider.com/a-note-from-business-insider...

[5] https://finance.yahoo.com/news/salesforce-says-ai-reduced-hi...
by sfRattan | 2025-06-06 00:06:42+00:00
> The projects security requirements don't need to be that stringent.

GrapheneOS security requirements very much do need to be that stringent. That's the whole reason for the project. Have something that is maximally secure within the most aggressive limits of what is possible today.

It targets end users who either have an acute threat model (e.g. journalists, dissidents) or are willing to tolerate some level of inconvenience (compared to stock Android) to gain the security advantages. Not everyone is willing to make that trade-off, and that's okay. I don't want my daily use phone OS to adopt a more permissive security model to appeal to a broader audience. I suspect most GrapheneOS users share that stance.

There are other AOSP custom distributions that benefit from the security improvements GrapheneOS is able to get accepted upstream (though Google is making this more difficult than it used to be). I think, for people who aren't willing to make the trade-off, a better path is to use another AOSP distribution on the hardware they prefer, or to establish a separate project to build a downstream version of GrapheneOS (under a clearly distinct name) for other, less secure hardware... Trying to shadow each release as closely as possible and make best use of Graphene's generally excellent software customizations (e.g. storage scopes, deny network permission, etc) without pursuing a hard fork.

I'd certainly like something similar for NVIDIA Shield Devices, for example. But I know that's not what Graphene's mission is.

The GrapheneOS devs absolutely will not listen to anyone asking them to loosen their security model. And thank goodness they don't! That's why I use GrapheneOS. It's why many do.
by abtinf | 2025-06-06 00:07:39+00:00
Yes, we have been gated.

In the book Guns, Germs, and Steel, Jared Diamond develops a theory for why Europe and Asia developed vast, powerful civilizations, but Africa and the Americas did not.

In Africa, the co-evolution of primates/humans and other life resulted in that other life becoming extremely dangerous to humans. My impression is that if Africa were the only continent, humans would still be living in caves, because nature had enough time to adapt. Even today, we do not have the technology to tame the wildlife and diseases of Africa, nor will most crops grow there. So the ability to escape the continent would have been the first “external gate”.

In the Americas, the geography and north-south orientation of the continents, as well as the lack of work animals and crops suitable for agriculture, gated development until much later than Europe and Asia. Corn took a very long time to go from being an itty bitty little thing to a crop capable of supporting civilization.
by trunci | 2025-06-06 00:09:20+00:00
Hey y'all! We are Fabric Chat, an AI assistant built for multi-user collaboration.

We noticed that a lot of people take screenshots of ChatGPT conversations, add the responses into a shared GDocs or Notion documents or even just send the prompt to a coworker for them to run it on their own.

But that constant sharing, mismatching and people getting different answers made us think: why don't we build a multiuser AI chat? The biggest issue: it would be very annoying for the chat to answer every single message.

So we built the Smart Mode - the assistant will only jump in when it's contextually relevant or when they have something to add - such as a datapoint that was wrong, or showing info from a web search. We plan on adding this agent into video conferences too - as if you had an analyst not only taking notes, but actively contributing to the conversation.

We also added a shared notepad (Notion style) for live collab and are currently implementing its connection to the chat.

Would love to hear feedback! We only have a free trial plan now, but our waitlist for the full product is open.
by consumer451 | 2025-06-06 00:10:06+00:00
Yeah, true.. but I just meant for users/user growth. Even if not completely warranted, users in their subreddit are upset that they don't have access to Sonnet 4.

With the Claude Max development, non-vibing users seem to be going to Claude Code. This makes me think that maybe Cursor should have taken an exit, cause Claude Code is gonna eat everyone's lunch?
by JCattheATM | 2025-06-06 00:10:12+00:00
> GrapheneOS security requirements very much do need to be that stringent. That's the whole reason for the project.

They don't though, that's just a nonsense claim.

Remove the parts dependent on the Pixel security hardware, and you still have a MUCH stronger android OS than anything else available.

> And thank goodness they don't!

Your reasoning does not support your conclusion.
by crazygringo | 2025-06-06 00:10:31+00:00
The point is, it doesn't matter if your ketchup is made with sugar or HFCS. If it weren't HFCS, it would be sugar, because ketchup is supposed to be sweet, and they have the same nutritional effect.

Similarly, it's not suprising when pasta sauce has some sweetness added -- grandma also likely added a bit of sugar if she found tomatoes too acidic, which many do.

The only thing that matters is that it's sugar. HFCS isn't somehow worse. If you're trying to eliminate sugar overall then sure, of course avoid HFCS. But if you're fine with a certain moderate amount of sugar per day, then the relatively small amounts of HFCS in things like pasta sauce and peanut butter are fine. The same way the sugar or honey in teriyaki sauces is. They count towards your daily allotment of sugar. For people trying to eat relatively healthily, avoid the soda but there's no reason to worry about the HFCS in ketchup or normal amounts of tomato sauce, for goodness' sake. The only reason to avoid HFCS entirely is if you're truly cutting sugar out of your diet entirely. Otherwise they're just substitutes for practical nutritional purposes.
by valcron1000 | 2025-06-06 00:10:40+00:00
Thanks! I didn't actually build it myself but a professor and other student were also involved. When I joined the project the decision was already made: the professor wanted to use APL and we were using an old CPU architecture book as reference that used APL (Gerritt A. Blaauw, Frederick P. Brooks Jr. Frend, Computer Architecture: Concepts and Evolution 1st Edition).

We almost got the PDP-11 working albeit some extensions like floating point arithmetic.
by sfRattan | 2025-06-06 00:15:47+00:00
>Remove the parts dependent on the Pixel security hardware, and you still have a MUCH stronger android OS than anything else available.

Yes.

And the correct course of action is a separate, downstream project with a different name doing exactly that and shadowing the GrapheneOS releases. Not a weakening of the GrapheneOS security model. If you don't want a maximally secure build of AOSP, you don't want GrapheneOS: you want something else. Maybe something substantially similar, but not GrapheneOS.

>They don't though, that's just a nonsense claim.

I don't know what is nonsensical about claiming that a project whose principal goal is to be maximally secure shouldn't weaken its hardware security requirements. The statement is closer to tautological than it is to nonsensical.
by kmb5vs | 2025-06-06 00:16:50+00:00
Title: Full-Stack Engineer | Contract | Remote (US-based)

Company: Audio-First Test Prep Platform

Duration: ~10–12 weeks for MVP

Compensation: Paid contract – competitive rate (no equity)

Experience Level: Mid to Senior preferred (3 years +)

Funding: Final stages of mobilizing resources to begin the MVP build. The project timeline reflects this progression.

We’re building an adaptive, audio-driven test prep platform designed for nurses, pre-med students, law students, and other high-intensity learners balancing work, family, and study. Think voice-based Duolingo meets real-time spaced repetition.

We’ve already built the front-end and now need a self-directed, back-end/full-stack engineer to help us finish the MVP by late summer, early fall.

Ideal Stack (flexible):

* Node.js / Python / Firebase / Postgres / Supabase

* Open to suggestions if justified and lightweight

You might be a fit if:

* You’ve built and launched real tools or platforms before (not just internal dashboards)

* You like fast execution but also appreciate mission-driven projects

* You value clarity, minimal meetings, and aligned momentum

* You have the capacity for solo execution but are open to scaling

* We’re not offering equity or co-founder status. This is paid contract work with possibility for long-term relationship once MVP proves value.

More info + how to apply: (https://hail-peridot-e09.notion.site/Hiring-Full-Stack-Softw...)

*This is a time-sensitive build that requires steady focus. Please only apply if you're able to be fully present during this phase.*
by photonthug | 2025-06-06 00:17:06+00:00
Interesting article about this: https://en.wikipedia.org/wiki/History_of_cannons

The oldest bell foundries do seem to happen at around the same time as the emergence of what we'd call a cannon, but before that there were indeed bamboo tubed contrivances and similar. If the Romans did have gunpowder earlier though, I bet they'd find a way.. I mean you don't hear about stone cannons and they'd be heavy AF but why not? These people basically invented fracking in BC, and literally tore down mountains to shake out all the gold. https://en.wikipedia.org/wiki/Las_M%C3%A9dulas
by glyph | 2025-06-06 00:20:55+00:00
I appreciate your commitment to being open to the possibility of being surprised. And I do wish I _could_ find a context in which I could be comfortable doing this type of personal experiment. But, I do remain confident in my own particular course of action chosen in the face of incomplete information.

Again, it's tough to talk about this while constantly emphasizing that the CVE at best a tiny little data point, not anywhere close to a confirmation bullseye, but my model of this process would account for it. And the way it accounts for it is in what I guess I need to coin a term for, "vigilance decay". Sort of like alert fatigue, except there are no alerts, or hedonic adaptation, for when you're not actually happy. You need to keep doing the same kinds of checks, over and over, at the same level of intensity forever to use one of these tools, and humans are super bad at that; so, at some point in your list, you developed the learned behavior "hey, this thing is actually getting most of this stuff right, I am going to be a little less careful". Resisting this is nigh impossible. The reason it's less of a problem with human code review is that as the human seems to be getting better at not making the mistakes you've spotted before, they actually are getting better at not making those mistakes, so your relaxed vigilance is warranted.
by Anthony-G | 2025-06-06 00:22:15+00:00
Thanks for the response. I think you’re right that, “if something truly does make no sense, that doesn't make it unrealistic.” I’ve watched documentaries or dramatisations of events that happened in real life (my wife is a also true-crime aficionado) and thought that if this plot or character was a work of fiction, I wouldn’t buy it. My memory isn’t that good either so I can’t think of any recent examples from TV/film.

However, the first time I heard about the CIA’s MKUltra project, I assumed that it was a 70s’ conspiracy theory but was shocked to then discover that it’s true. Dosing non-consenting victims with hallucinogenic drugs outside of a controlled clinical test made as much sense as the US military’s psychic spies and “men who stare at goats” program. I was similarly shocked to learn about the Tuskegee Syphilis Study (though less surprised, given US history), particularly that it continued right up until 1972 – this really made no sense as antibiotics had already been proven to be an effective treatment back in the 40s. More recently, when I first heard of the systemic sexual abuse and rape of thousands of mostly white English under-age girls by gangs of mostly Pakistani men in places like Rotherham, Rochdale, Oxford and Peterborough, it sounded like a far-right racist fantasy. I still find it hard to wrap my head around that one; I still see – and want to see – people as being essentially good/moral and this conflicts with that narrative.

Sorry for going off on such a disturbing tangent. I want to start reading more books and will add the Silo series to my list.
by gsf_emergency | 2025-06-06 00:22:17+00:00
More specifically:

https://news.ycombinator.com/item?id=21535498

(The HN just for completeness; didn't see any remarkable dismissals there.. ntheless some (schizoid?) comments seemed worthy of being kept in my background eg https://news.ycombinator.com/item?id=21548795 )

https://archive.is/latest/www.nybooks.com/articles/2019/12/0...

>After such a catastrophic embarrassment, orthodox economists fell back on their strong suit—academic politics and institutional power.
by paulorlando | 2025-06-06 00:23:43+00:00
I love the execution on this. It's powerful because it overlaps with different approaches (adjacent possible, inflection points, dominant design, creative destruction, opportunity curves, the multigenium, hype cycles, Cambrian explosions, tech leapfrogging...) and also just lets you click around to explore.

I've been interested in the timing of new inventions and how they sometimes go on to become successful innovations. This visual tree is a great resource.
by CuriouslyC | 2025-06-06 00:23:48+00:00
Regarding architecture considerations:

AI likes modular function grammars with consistent syntax and interfaces. In practice this means you want a monolithic service architecture or a thin function-as-a-service architecture with a monolithic imported function library. Microservices should be avoided if at all possible.

The goal there is to enable straightforward static analysis and dependency extraction. With all relevant functions and dependencies defined in a single codebase or importable module, you can reliably parse the code and determine exactly which parts need to be included in context for reasoning or code generation. LLMs are bad at reasoning across service boundaries, and even if you have OpenAPI definitions the language shift tends to confuse them (and I think they're just less well trained on OpenAPI specs than other common languages).

Additionally, to use LLMs for debugging you want to have access to a single logging stream, where they can see the original sources of the logging statements in context. If engineers have to collect logs from multiple locations and load them into context manually, and go repo hopping to find the places in the code emitting those logging statements, it kills iteration speed.

Finally, LLMs _LOVE_ good documentation even more than humans, because the humans usually have the advantage of having business/domain context from real world interactions and can use that to sort of contextually fumble their way through to an understanding of code, but AI doesn't have that, so that stuff needs to be made as explicit in the code as possible.

The largest individual repo under my purview currently is around 250k LoC, my experience (with Gemini at least) is that you can load up to about 10k LoC functionally into a model at a time, which should _USUALLY_ be enough to let you work even in huge repos, as long as you pre-summarize the various folders across the repo (I like to put a README.md in every non-trivial folder in a repo for this purpose). If you're writing pure, functional code as much as possible you can use signatures and summary docs for large swathes of the repo, combined with parsed code dependencies for stuff actively being worked on, and instruct the model to request to get full source for modules as needed, and it's actually pretty good about it.