MurphyA/hacker-news huggingface dataset:
by Rendello | 2026-02-19 00:53:33+00:00
I appreciate the discussion. I'm always looking for ways to look better, although you wouldn't know it because I'm unkempt and wear old clothes. But fantasy me dresses really well.

> and keep some of the sun off you!

This has become really important to me in the last few years after I realized the impact sunlight has on people's skin (I always think of this [1] or just generally the people I know who don't care about sun exposure). I'm not sure what my ideal summer look will be since I look best in sporty clothing, but don't intend to spend long periods of time with large parts of my skin exposed to direct summer sunlight any longer. The face and back of the neck is the hardest part to fashionably keep safe.

https://www.cbsnews.com/news/trucker-accumulates-skin-damage...
Brain file format for AI agents – one file, any LLM, sub-millisecond queries
by morshola | 2026-02-19 00:54:56+00:00
Every AI agent has amnesia. Claude doesn't remember your last conversation. GPT doesn't know
what you decided last week. The current solutions — vector databases, markdown files, key-value
stores — lose structure, can't track reasoning chains, and lock you to one provider.

I built AgenticMemory: a binary graph format where every cognitive event (facts, decisions,
inferences, corrections) is a node with typed edges (caused_by, supports, supersedes).
One .amem file holds your agent's entire knowledge graph. Works with any LLM.

Key numbers:
• 276ns to add a node
• 3.4ms to traverse 5 levels deep in a 100K-node graph
• 9ms similarity search across 100K nodes
• ~24 MB for a year of daily use
• A lifetime of memory fits in under 1 GB

Built in Rust. Zero dependencies. Python SDK: pip install agentic-brain.
Rust CLI: cargo install agentic-memory.

https://github.com/agentic-revolution/agentic-memory
by marcus_holmes | 2026-02-19 00:55:03+00:00
Did we lose something when we invented the calculator and stopped teaching the times table in schools? There have been millions of words discussing this, and the general consensus amongst us crusty old folks was that yes, the times table was useful and losing the ability to do mental arithmetic easily would be bad.

Turns out we were wrong. Everyone carries a calculator now on their phone, even me. Doing simple maths is a matter of moments on the calculator app, and it's rare that I find myself doing the mental arithmetic that used to be common.

I can't remember phone numbers any more. I used to have a good 50+ memorised, now I can barely remember my own. But the point is that I don't need to any more. We have machines for that.

Do we need to be able to write an essay? I have never written one outside of an educational context. And no, this post does not count as an essay.

I was expelled from two kindergartens as a kid. I was finally moved to a Montessori school where they taught individually by following our interests, where I thrived. Later, I moved back into a more conventional educational environment and I fucking hated every minute of it. I definitely learned despite my education not because if it. So if LLMs are about to completely disrupt education then I celebrate that. This is a good thing. Giving every kid a personal tutor that can follow their interests and teach them things that they actually want to learn, at the pace they want to learn them, is fucking awesome.
by bunderbunder | 2026-02-19 00:55:06+00:00
For what it’s worth, ObjC is not Apple’s brainchild. It just came along for the ride when they chose NEXTSTEP as the basis for Mac OS X.

I haven’t used it in a couple decades, but I do remember it fondly. I also suspect I’d hate it nowadays. Its roots are in a language that seemed revolutionary in the 80s and 90s - Smalltalk - and the melding of it with C also seemed revolutionary at the time. But the very same features that made it great then probably (just speculating - again I haven’t used it in a couple decades) aren’t so great now because a different evolutionary tree leapfrogged ahead of it. So most investment went into developing different solutions to the same problems, and ObjC, like Smalltalk, ends up being a weird anachronism that doesn’t play so nicely with modern tooling.
by nojs | 2026-02-19 00:55:13+00:00
A bit ironic to publish an AI slop piece about how “AI Slop Is Drowning Maintainers”

> Agents don’t think in sprints. They don’t think about any of these features. They only think about writing code as effectively as possible.

> These aren’t incremental improvements to git, they’re rethinking what version control means

AI slop is also drowning us unsuspecting HN readers.
by JonathanAquino | 2026-02-19 00:55:21+00:00
A developer shares what an AI agent called Chloe has built for him over a few weeks using the OpenClaw platform: a set of personal tools (bookmarks, a key-value tracker, voice chat, a photo gallery) plus a daily “web lab” where the agent reads his blog posts, infers his interests, and autonomously builds something new each day. The unsolicited creations – a saints match game, a hypercube explorer, a task manager – are what make it interesting.
Show HN: SalaryScript – The FAANG Negotiation Playbook
by corefiredrill | 2026-02-19 00:56:03+00:00
Hey HN,

I’m the founder of SalaryScript, and I wanted to share a project I’ve been working on for over a year: a comprehensive negotiation playbook tailored specifically for big tech roles.

I’ve navigated the FAANG hiring gauntlet multiple times myself, with stints at FAANG companies, so I know firsthand how opaque and high-stakes these negotiations can be. I wrote SalaryScript based on my experience, insights from a dozen FAANG-alumni colleagues, and lessons from recruiters I’ve worked with over the years. We’ve pooled perspectives from engineers, PMs, and execs who’ve collectively negotiated millions in total compensation.

Think of it as a “golden rule” book for tech negotiations. It covers everything from decoding offer letters and leveraging competing offers to scripting responses for common recruiter tactics, handling equity cliffs, and navigating relocation packages. No fluff — just battle-tested scripts, templates, and strategies that have helped people increase their total comp by 30–50% on average.

One contributor, a former Meta engineering manager, shared how he turned a $300K offer into $550K by reframing the RSU vesting conversation. Another, an ex-Apple product lead, broke down the psychology of why “total comp” framing often beats focusing on base salary alone.

Since launching last year at an introductory price of $19, we’ve crossed 1,000+ downloads and sales. Demand has been strong, and as word has spread, we’ve gradually raised the price.

If you’re prepping for interviews or staring at an offer right now, this might be the edge you need.

If you’re interested, you can check it out at salaryscript.com.

Would love your thoughts, war stories, or questions like what’s the biggest negotiation win (or fail) you’ve had in tech?

Cheers
by shadowgovt | 2026-02-19 00:56:27+00:00
Reviewing docs is a lower bar than reviewing code because it's a lower bar than reviewing code.

I have never even heard of a software company that acts otherwise (except IBM, and much of the world of Silicon Valley software engineering is reactionary to IBM's glacial pace).

I'm not saying docs == code for importance is a bad way to be, just that if you can name firms that treat them that way other than IBM (or aerospace), I'd be interested to learn more.
by devanampiya | 2026-02-19 00:56:49+00:00
NO, It is no INSULT to India at all. Present regime even has problem using the term "INDIA" for the country, if you observe they are representing it in political / non-political spaces as "Bharat" at least inside India.
They don't have guts doing the same in international platform. For Indians living outside a very Rosy picture of India is portrayed. People living in India know that, instead of REAL WORK that is supposed to happen for prosperity of country & it's people, they are just managing the show with propoganda machine & media. India will go into deep pits ( Paathaalam ) as long as this regime continues.
by gh2k | 2026-02-19 00:57:23+00:00
The article doesn't say if the confidentiality labels were created with encryption. I've been using the latter (with Preview DLP) to prevent emails leaking out to _external_ integrations, which can't access the keys. With MS internal tooling, it's feasible that it access to the key, in which case that would be even worse. Does anyone know if this happened?
by refulgentis | 2026-02-19 00:57:35+00:00
> Swift is strictly better in OO support and C++ interop

Fascinating.

They've shown the idea it is better on C++ interop is wrong.

I don't know enough to say Rust has OO support, but I'm pretty sure it does.

i.e. as an observer over the years, that's the rationale it says on the tin, but the real motivation was is "its cooler!" i.e. informed by what Apple said about C++ interop, and liked some esoteria about Swift's type system, not OO. i.e. not a mature engineering decision.
by streetfighter64 | 2026-02-19 00:57:50+00:00
Again, what does government enforcement of a certain belief about nature, have to do with government enforcement of property rights?

Ownership of physical property is also an artificial grant from the state. (Or if you will, a recognition by the state of what people in general believe) Perhaps not a table or a knife, but a farm or a factory, have in many countries been suddenly disqualified as legitimate property of their (former) owner, as a result of e.g. a communist revolution. There's nothing more "natural" to owning a piece of land, than to owning a song.

I'm pretty sure physical possession was not generally considered ownership before the 1970s, that's an absurd statement. Shareholders of the East India Company in the 1600s weren't in physical possession of the ships, yet they were considered owners. Even purely intellectual property, such as patents, have existed in laws since at least 1474.
by ribbitapp | 2026-02-19 00:58:01+00:00
Two months ago I started building a small social network as an experiment.

Some parts were built quickly, and I used AI to help when I got stuck on JavaScript implementation details. The goal wasn’t architectural perfection — it was to test an idea.

The constraints:

No algorithm

No engagement optimization

No infinite scroll

Posts are strictly chronological

Right now it has ~180 users.

The motivation wasn’t to compete with existing platforms. I was curious about something more specific:

If you remove algorithmic amplification entirely, does social media become healthier — or just quieter?

Most major platforms optimize for engagement. That usually means ranking systems, recommendation engines, and constant novelty. I wanted to see what happens if you strip that away and let posts exist purely in time order.

Some observations so far:

Without amplification, there are no engineered dopamine spikes.

But there’s also less constant stimulation.

When activity is low, it feels visibly low.

When a few people are active, it feels surprisingly human.

Growth has been small and mostly organic (campus QR codes and word of mouth). Some days it feels alive. Some days it feels empty.

One thing I didn’t anticipate fully: algorithms don’t just drive addiction — they also solve the “empty room” problem. Chronological feeds don’t.

I’m still unsure whether that’s a feature or a structural limitation.

For those who’ve worked on social platforms or ranking systems:

Is algorithmic ranking necessary for social networks at scale? Or could a platform without amplification sustain meaningful activity long-term?

I’m currently a college student, and this started as a way to explore these ideas more concretely. It may remain an experiment, but I’m curious whether a model like this could ever sustain meaningful activity at scale.

I’m open to technical, product, or philosophical critique.
by idoubtit | 2026-02-19 00:58:16+00:00
Wikidata is a FRBR-compatible public database of books. I don't know if it's good enough for the kind of books the author wants, but in recent years the quality of wikidata greatly increased for the books that deal with (about 1000 items).

BTW, they misunderstood their own example of "Hotel Iris" by Yoko Ogawa when they wrote "the same work is duplicated four times." In fact, those four entries in the list point to distinct works.

One of these is a French publication by the publisher Actes Sud. Translations are not the same work as the original. They are derived works.

But it's true this list is a mess. Another entriy has 3 editions, one in English and two in Spanish, so it's obviously an error that mixes two distinct works.
by a1ff00 | 2026-02-19 00:59:10+00:00
I’m over 40. Barely. But, over 40 nonetheless.

I grew up in front of a PC as early as 6. I used it for everything. I grew up with it, on the internet as it was blossoming, and escaped through it as a means to escape reality, bullying, abusive household… you name it, from early Heat.net/mplay.net days, early mIRC CS alpha/beta/1.6 days, ICQ, MSN, VBasic coding, learning C/C++, to just about doing everything on a computer.

I escaped and escaped hard. If I couldn’t access it at home, I’d bike to the library and access it, or joined the computer club in HS just so I had another one I could easily hop on.

I remember over the years comments like, “you look like you watch too much TV”, or “why are your shoulders always raised?”, or “what’s wrong with your right neck?”, or “why are you corkscrewing to the left”.

As the years went on, my jaw started to hurt, my right rotator cuff would crack all the time, my right-abs snapped, my obliques weakened, my right hips started to fail, I don’t think I have a right scapula at this point, my molars no longer touched, my head jetted forward, my breathing worsened, my right-diaphragm hurt to inhale… I always blamed it on poor genetics, or something else.

It wasn’t until I hit 39 when it all kind of clicked.

It’s years of using a god damn mouse. Forward, right, back, left, circle motions, rinse and repeat, 12+ hours a day.

I’m unable to sleep more than 4 hours a day without waking up with excruciating pain down my right shoulder and neck, unable to feel a large part of my right side, and the pain is getting worse by the day.

Ive done PT, chiro, acupuncture, personal trainer, THOUSANDS of dollars to no avail.

Where’m I going with this?

Log off people. Stretch. Do exercise. Something before it’s too late.

I’m pretty sure we’re going to see more and more of “millennial” style abuse and neglect rear its ugly head.
by jurgsieg | 2026-02-19 00:59:24+00:00
I built RustyClaw, a system for running multiple AI coding agents as persistent daemons that collaborate in teams.

The idea started from OpenClaw's approach to multi-agent coordination, but I wanted something faster, more reliable, and fully open source — so I rebuilt it from scratch in Rust.

How it works: you define agents with different roles (@coder, @review, etc.), group them into teams, and the system handles routing and handoffs automatically. When @coder finishes implementing something, it mentions @review in its response, and the queue processor detects it and routes the message. No central orchestrator LLM — agents coordinate through a simple file-based queue.

Key design decisions:

Provider-agnostic — works with Claude Code, OpenAI Codex CLI, and OpenCode. Mix and match models per agent

tmux daemon — everything runs in a persistent tmux session. Attach, detach, check logs, no web UI required (though there's an optional WASM visualizer)

Identity files — each agent has SOUL.md, IDENTITY.md, MEMORY.md in its working directory. The agent's personality and role are defined in plain markdown, not prompt engineering hidden in code
Supports Discord and Telegram as input channels, or just use the CLI directly.
by gdwatson | 2026-02-19 00:59:27+00:00
Years ago I wrote a toy Lisp implementation in Objective-C, ignoring Apple’s standard library and implementing my own class hierarchy. At that point it was basically standard C plus Smalltalk object dispatch, and it was a very cool language for that type of project.

I haven’t used it in Apple’s ecosystem, so maybe I am way off base here. But it seems to me that it was Apple’s effort to evolve the language away from its systems roots into a more suitable applications language that caused all the ugliness.
by UltraSane | 2026-02-19 00:59:50+00:00
I use AWS Route53 and you can get incredibly granular with API permissions

Key condition keys for this purpose include:

route53:ChangeResourceRecordSetsActions: Limits actions to CREATE, UPDATE, or DELETE.

route53:ChangeResourceRecordSetsRecordTypes: Limits actions to specific DNS record types (e.g., A, CNAME, TXT).

route53:ChangeResourceRecordSetsRecordValues: Limits actions based on the specific value of the DNS record.

route53:ChangeResourceRecordSetsResourceRecords: For more complex scenarios, this can be used to control access based on the full record set details.
by rvz | 2026-02-19 01:00:13+00:00
> It doesn't have a "browser", it has a testing shell.

So, yes it is still pre-historic.

> Once it gets embedding stabilized that will be the time for a full blown browser developement.

Servo development began in 2012. [0] 14 years later we get a v0.0.1.

At this point, Ladybird will likely reach 1.0 faster than Servo could, and the latter is not even remotely close to being usable even in 14 years of waiting.

[0] https://en.wikipedia.org/wiki/Servo_(software)
Show HN: Analytics that tells AI product teams where their AI fails user
by Lindadao | 2026-02-19 01:02:00+00:00
Traditional analytics tracks clicks. For AI products, you need to know: what was the user trying to do, did the AI help, and did they succeed?

I built a demo of this. It ingests AI conversations and runs 3 workers (GPT-4o-mini): intent classifier, quality scorer (LLM-as-judge), and task completion detector. Results show up in a dashboard designed for PMs, not engineers.

Stack: Python SDK (zero deps, async) → FastAPI → Supabase → GPT-4o-mini workers → Next.js dashboard.

Demo with sample data (not live product, validating the concept): https://dashboard-xi-taupe-75.vercel.app

The sample data models an AI app builder. Interesting patterns: scaffolding works great (78% success), but API integrations fail 75% of the time, and users who enter bug-fix loops almost always churn.

Key design question: is the "insights layer" (auto-generated recommendations, revenue-at-risk estimates, root cause identification) valuable enough to differentiate from Langfuse/Helicone adding product analytics to their existing tracing tools?

Looking for honest feedback, especially from AI product builders.
by altairprime | 2026-02-19 01:02:17+00:00
To provide context for those still using BMI as the sole 'fat or not' discriminator — the CDC published an n=9894 longitudinal study* about ten years ago; generally summarizing figure 1, the median starts around 0.53 +/- gender variance at 20-29, peaks at 0.62 +/- at 70-79, and then begins decreasing from there; however, they found that BMI fails to represent the 'fat' levels improperly (to our detriment) for people in their 40s (figure 2), as older human bodies tend to lose fat in areas (i.e. arms) that have no significant bearing on overall health, but gain fat in the abdomen (which other studies have shown does correspond to increasing cardiovascular issues). They show median waist-to-height-ratio data as 'monotonically increasing abdominal adipose tissue throughout the years of adulthood but decreasing mass in non-abdominal regions', which bodes very poorly for clothing manufacturers — because not only do you have to account for nine body shapes in women, but you also have to account for age skewing the waist-to-length ratios of the body shape further.

It would be particularly interesting to repeat this sizing study using the garment length to identify where it falls in 'height' median for women, and then identifying what 'age' median the garment's waistline is calibrated for. I can certainly guess what the results will be from personal experience on a per-retailer basis, and it would be a useful way to mathematically identify 'underserved niches' in today's market to target with appropriately-fit clothing (without a body scan).

* doi:10.1371/journal.pone.0172245 (2017) https://stacks.cdc.gov/view/cdc/44820
by alexgarden | 2026-02-19 01:02:20+00:00
The short version: instructions tell the model what to do. An Alignment Card declares what the agent committed to do — and then a separate system verifies it actually did.

Most intent/instruction work (system prompts, Model Spec, tool-use policies) is input-side. You're shaping behavior by telling the model "here are your rules." That's important and necessary. But it's unverifiable — you have no way to confirm the model followed the instructions, partially followed them, or quietly ignored them.

AAP is an output-side verification infrastructure. The Alignment Card is a schema-validated behavioral contract: permitted actions, forbidden actions, escalation triggers, values. Machine-readable, not just LLM-readable. Then AIP reads the agent's reasoning between every action and compares it to that contract. Different system, different model, independent judgment.

Bonus: if you run through our gateway (smoltbot), it can nudge the agent back on course in real time — not just detect the drift, but correct it.

So they're complementary. Use whatever instruction framework you want to shape the agent's behavior. AAP/AIP sits alongside and answers the question instructions can't: "did it actually comply?"
by huey77 | 2026-02-19 01:02:29+00:00
I just stumbled upon a recent repo for playwright via the CLI. I use OpenCode w/ Opus 4.6. After installing the skill in my repo Claude navigated my local running frontend and has grasped some UI/UX refactors I was struggling to convey.

Thought I would share this for anyone running a similar set up doing frontend/full-stack work. I know playwright MCP is nothing new, but the CLI + skill is much lighter on token usage. So far so good.
by niyikiza | 2026-02-19 01:02:29+00:00
Right on. Human-in-the-loop doesn't scale at agent speed. Sandboxing constrains tool execution environments, but says nothing about which actions an agent is authorized to take. That gets even worse once agents start delegating to other agents.I've been building a capability-based authz solution: task-scoped permissions that can only narrow through delegation, cryptographically enforced, offline verification. MIT/Apache2.0, Rust Core.
https://github.com/tenuo-ai/tenuo
by chlorion | 2026-02-19 01:03:06+00:00
The statistics we have on real world security exploits proves that most security exploits are not coming from supply chain attacks though.

Memory safety related security exploits happen in a steady stream in basically all non-trivial C projects, but supply chain attacks, while possible, are much more rare.

I'm not saying we shouldn't care about both issues, but the idea is to fix the low hanging fruit and common cases before optimizing for things that aren't in practice that big of a deal.

Also, C is not inherently invulnerable to supply chain attacks either!
by wongarsu | 2026-02-19 01:04:26+00:00
Just because it says "CC0" does not make it CC0. If you upload a dataset you don't have the rights to, any license declaration you make is null and void, and anyone using it as if it had that license is violating copyright

Even if MS could claim that they were acting in good faith there really isn't much legal wiggle room for that. But it doesn't even come to that because I don't think anyone would buy that they really thought that the Harry Potter books were under the CC0
by dylan604 | 2026-02-19 01:04:47+00:00
One of the early DAWs (long forgot the name of it) had an interface that recreated the look of a flatbed with animated reels. It ran on an old monochrome green/black monitor. I saw this in the mid-90s and was already used to seeing a waveform in timelines, so this thing really felt ancient. Apparently, the makers felt sound editors would be unable to grasp a new interface???