MurphyA/hacker-news huggingface dataset:
by brazzy | 2026-02-18 13:52:46+00:00
My observation is about what your assumptions say about you, and that's not a miss.

Nobody really understands a job they haven't done themselves, and "arguing" that 90% of them are "bullshit" has no other possible explanation than a combination of ignorance (you don't understand the jobs well enough to judge whether they are useful) and arrogance (you think you can make that judgement better than the 90% of people doing those jobs).
by evolve2k | 2026-02-18 13:53:05+00:00
A key critique

The article is well argued and well written, as far as I’m concerned.

What’s needed if you really want adoption is to define a term; something like 256-ex for extended. Or whatever.
But folks and apps need to be able to say; we’ve implemented or we support 256-ex. Without this label is hard to drive adoption.

The heartbleed thing from a few years back best taught me this.

Good luck I hope to see broad adoption it’s a great idea.

Give it a name, better yet move the copy onto a website with the same name also and a little icon folks can add to their website if they implement this k to their terminal app.
by gus_massa | 2026-02-18 13:53:28+00:00
I agree.

@OP: There are official threads for jobs, https://news.ycombinator.com/newsfaq.html

Latest edition https://news.ycombinator.com/submitted?id=whoishiring

They are closed now. Wait until March 2nd for next month edition, take a look and repost in the correct one.

g
by Zigurd | 2026-02-18 13:54:01+00:00
To be maximally reductive, FSD will never work because the sensor suite is deficient. There are other reasons but that one's enough.

Same for a rocket that's ridiculously large for orbital missions but can't go beyond orbit without 15 to 25 refueling flights of the same enormous rocket.

The reasons for both these failing are going to be manyfold and complex, but there are enough simple reasons that everyone should understand.
by SilverBirch | 2026-02-18 13:54:08+00:00
Ah I see, so the misaligned agent was unsurprisingly directed by a misaligned human. Good grief, the guy doesn't seem to realise that starting your soul.md by telling your AI bot that it's a very important God might be a bad idea.

"Social experiment" you might as well run around shouting "is jus a prank bro!".
by elyonox | 2026-02-18 13:54:23+00:00
I built TypeDock - a collection of 52 developer tools that run 100% client-side in your browser.

Tools include:
- JSON to TypeScript/Zod converters
- RegEx tester with live highlighting
- Base64, URL, hash generators
- Color converter, QR generator
- SQL/XML/JSON formatters
- Password generator, JWT decoder
- And 40+ more

Everything runs locally - your data never leaves your browser. No sign-up, no tracking (optional analytics with consent), open source.

Built with Next.js 16, React 19, TypeScript, and Monaco Editor.

GitHub: https://github.com/yoni-crypto/typedock

Would love feedback on the UX and which tools you find most useful.
by lqstuart | 2026-02-18 13:54:29+00:00
We just haven’t figured out how to use it. You wouldn’t try to create an entire project out of IDE templates, but how many “low code” attempts were there to do just that at some point?

I think there are phases in a project’s lifecycle where it’s more appropriate, at the very beginning and very late. I do not think junior developers should be using it, because it is much much harder to learn and it kills productivity having senior developers review 3000 lines of slop. Just stuff like that needs to be figured out.
by ethbr1 | 2026-02-18 13:55:49+00:00
> "enterprise OS", some kind of Salesforce / ERP-like platform where all the data about a business is kept

I read this, turn it to "person", and see Google/Android (maybe Microsoft/Windows/Office to a lesser degree) shooting off if they design their data APIs to be gen AI usable. Which they mostly already are.

If individuals can vibe code personal apps easily because their personal/relevant data is already in one place, that's going to be a major tailwind.

Sadly, I think Apple is too institutionally cathedral (over bazaar) to keep up with them.
by elicash | 2026-02-18 13:56:03+00:00
> Like, imagine if I owned a toll road and started putting up road signs to "convince" Waymo cars to go to that road.

I think a clearer parallel with self-driving cars would be the attempts at having road signs with barcodes or white lights on traffic signals.

There's nothing about any of these examples I find creepy. I think the best argument against the original post would be that it's an attempt at prompt injection or something. But at the end of the day, it reads to me as innocent and helpful, and the only question is if it were actually successful whether the approach could be abused by others.
by YetAnotherNick | 2026-02-18 13:56:39+00:00
I don't think I can make TNT but I can understand the steps without chemistry background. I believe I will likely injure myself but more detailed steps is unlikely to help.

> So you think helping a terrorist plan how to kill people somehow makes things safer?

They just need to run a bus into some crowded space or something. They don't need ChatGPT for this. With more education, the chances of becoming terrorist reduces even if you can plan better.
by zamadatix | 2026-02-18 13:56:49+00:00
Hmm, not sure I agree it ever only meant "running at a loss to capture the market" - even after having gone back and re-read Doctorow's early postings. It's certainly a common way for the situation to start (getting a large mass of users to abuse is a difficult task), but it's never specified as the only way. I could be very wrong of course, but if so I must have missed some very explicit language in the early coinage.

The original post https://pluralistic.net/2022/11/28/enshittification/ about it makes no mentions of running at a loss, just what happens when a two-sided platform gains a bunch of users.

Later in "The ‘Enshittification’ of TikTok" https://www.wired.com/story/tiktok-platforms-cory-doctorow/ Doctorow does explicitly mention Amazon operated as a loss leader to gain it's initial users but when they get around to the subject of the article they explicitly note it was the recommendation system which made it grow the early audience:

> Which brings me to TikTok. TikTok is many different things, including “a free Adobe Premiere for teenagers that live on their phones.” But what made it such a success early on was the power of its recommendation system. From the start, TikTok was really, really good at recommending things to its users. Eerily good.

> By making good-faith recommendations of things it thought its users would like, TikTok built a mass audience, larger than many thought possible, given the death grip of its competitors, like YouTube and Instagram. Now that TikTok has the audience, it is consolidating its gains and seeking to lure away the media companies and creators who are still stubbornly attached to YouTube and Insta.

And, in the very same, he opens up with this generic definition of enshittification that it's "good to users" then "abuse users for profit" but not an explicit "how" of either:

> Here is how platforms die: first, they are good to their users; then they abuse their users to make things better for their business customers; finally, they abuse those business customers to claw back all the value for themselves. Then, they die. I call this enshittification, and it is a seemingly inevitable consequence arising from the combination of the ease of changing how a platform allocates value, combined with the nature of a "two-sided market", where a platform sits between buyers and sellers, hold each hostage to the other, raking off an ever-larger share of the value that passes between them.
by johncoltrane | 2026-02-18 13:57:40+00:00
My latest, "zaibatsu" is bundled with Vim.

- Apprentice, a low-contrast colorscheme I made years ago and used for a long time: https://github.com/romainl/Apprentice.

- Malotru, my curent colorscheme, more contrasted: https://github.com/romainl/vim-malotru.

- Dichromatic, for colorblind users: https://github.com/romainl/vim-dichromatic.

- Bruin, which only uses typography: https://git.sr.ht/~romainl/vim-bruin
by tremon | 2026-02-18 13:58:04+00:00
Exactly. As soon as you're working with multiple active releases, the branching model becomes a distinction without a difference. You will always be working with multiple (tagged) release branches, a default branch where developers base their new work on, and an integration branch where development work is gathered and tested to cut the next release. Whether the default and integration branch are identical or separate is mostly immaterial to the developer workflow.

The only actually different model is when you have a continuously-releasable trunk and never do fixes on older releases.
by Kim_Bruning | 2026-02-18 13:58:07+00:00
I think this commentor (Boxo McFoxo) did better work than almost everybody:

https://pivot-to-ai.com/2026/02/16/the-obnoxious-github-open...

"No, I'm not convinced: [...] I think MJ Rathbun really is a case of someone giving their OpenClaw stack a vague instruction, sitting back and letting it run with little intervention..." and then lays it out in detail. (I'm a little suspicious of some of the terminology, but it does lay out the story at least)
by ElectricalUnion | 2026-02-18 13:59:11+00:00
Ideally you want to run all those trusted (read: security critical, if compromised entire system is no longer trustworthy) processes on separated and audited machines, but instead busy people end up running them all together because they happen to be packaged together (like FreeIPA or Active Directory), and that makes it even harder to secure them correctly.
Show HN: Keychains – Prevent LLM/OpenClaw agents from leaking API credentials
by severin | 2026-02-18 13:59:29+00:00
Hi HN — I’m a heavy OpenClaw user and, like many others, I’ve been thinking about how to give these new “unleashed” agents secure access to my accounts.

Agents need API access to be useful.
But API keys are long-lived secrets.
And agents are not secure environments.

So I built something for myself that quickly turned into a product: keychains.dev.

The idea is simple: agents never see raw credentials.

With Keychains.dev:

• Agents make API calls via a drop-in replacement for curl or JavaScript’s fetch()
• They use template variable names instead of embedding credentials
• The request is proxied through keychains.dev
• The proxy analyzes the target endpoint and determines the minimal OAuth scopes required
• It attempts to fulfill the request using credentials stored server-side
• If credentials are missing — or the agent isn’t approved for that action — it returns an approval link
• The agent forwards that link to its human for authorization

This creates a user-in-the-loop escalation model instead of blind credential injection.

Security-wise:

• Agents can make requests without ever touching credentials (protects against prompt-injection exfiltration)
• Credentials cannot be replayed to arbitrary endpoints — they’re bound to the issuing provider
• Each agent machine is authenticated via SSH keypair + stateful fingerprinting (keys can’t be reused elsewhere, instant revocation)
• Agents can delegate scoped credentials to sandboxed sub-agents if needed
• Users approve new permissions via FaceID/TouchID in the browser
• Full audit trail of every request, with granular revocation at the agent, sub-agent, or scope level

Even if a private key is stolen, permissions can be revoked immediately and tokens are short-lived.

I currently support delegation across 6,754 APIs, but the core idea isn’t the number — it’s controlled delegation with human approval on escalation (+ any API you can reach with curl is compatible).

WDYT?

I’d really appreciate feedback on:
– Whether this matches your threat model for agents
– If user-in-the-loop escalation feels practical
– How you're handling credential security today

Happy to answer technical questions.
by indiekitai | 2026-02-18 13:59:39+00:00
This highlights a fundamental challenge with AI assistants: they need broad access to be useful, but that access is hard to scope correctly.

The bug is fixable, but the underlying tension—giving AI tools enough permissions to help while respecting confidentiality boundaries—will keep surfacing in different forms as these tools become more capable.

We're essentially retrofitting permission models designed for human users onto AI agents that operate very differently.
by squeefers | 2026-02-18 13:59:56+00:00
> Back then it took a lot of effort over an extended period to do what can now be had for a few dollars of LLM tokens,

we are just prone to hysteria id say, predating the invention of internet, phones or even print media (though they certainly exasperate the issue)

https://en.wikipedia.org/wiki/Day-care_sex-abuse_hysteria
remember the US daycare/satanism scare... it made its way to england via TV, no mechanical turks required.

https://en.wikipedia.org/wiki/Yellow_journalism
the common person manipulated by lies in print. old as print itself
by lobsterthief | 2026-02-18 14:00:01+00:00
Just because ChatGPT says it sounds negative doesn’t mean it is. I didn’t think of it negatively either.

Who knows how ChatGPT made that suggestion [this time around]. Maybe 30% of the English-speaking population thinks it’s negative, or 60%, or perhaps someone simply wrote a high-profile negative op-ed that included the phrase in its title.

Anyways, not that you did this, but we need to be careful not to use LLMs as the deciding factor in how to feel about things. :) It gives too much power in swaying our thought to those who build the models.
by saezbaldo | 2026-02-18 14:00:06+00:00
The fundamental issue here isn't the specific vulnerabilities — it's that these agent frameworks have no authorization layer at all. They validate outputs but never ask "does this agent have the authority to take this action?" Output filtering ≠ authority control. Every framework I've audited (LangChain, AutoGen, CrewAI, Anthropic Tool Use) makes the same assumption: the agent is trusted. None implement threshold authorization or consumable budgets.
by red-iron-pine | 2026-02-18 14:00:20+00:00
they are not happy, they are distracted and vaguely know it's not going well.

the "russian firehose" approach and vryanyo (institutional lying) means they're bombarded with info but also know most of it is BS, but not necessarily how or why.

they know it's not going well but at this point much of the economy is on war-footing and if they're not drafted they're probably getting paid okay. STFU and keep your head down and you won't get drafted.
by saezbaldo | 2026-02-18 14:00:41+00:00
One underexplored reason: companies can't give AI agents real authority. The moment an agent needs to do anything beyond summarizing text — update a CRM, transfer funds, modify infrastructure — the security question kills it. No one wants an agent that can take irreversible actions with no approval chain. Until the trust architecture problem is solved, AI stays in read-only mode for most enterprises.
by notepad0x90 | 2026-02-18 14:01:23+00:00
it's not a waste of your time if you're getting paid for it, that's why you are there. You're not there to be otherwise "productive" you're there to do what the company wants you to do. you might say they're inefficient, but are things like company outings efficient? b.s. townhall calls? half the time it's just managers trying to hear their own voice in front of everyone. You're not there to write code or fix things, you're there to make those pay-check signers happy. placate to their ego if that's what they want.

That said, often, meetings are much more efficient means of syncing information than slack/chat or emails. call it "real-time active communication with rich context" if it sounds more technical. you can communicate in voice tones, body language, timing,etc.. what you can't using other means. and communicate doesn't mean just talk or listen for the sake of it, it can me brainstorm, understand requirements and expectations better, prevent misunderstandings and other wasted effort.

In my experience, things that exist as patterns like this in systems are always important, but it's also important to use them as intended, and not abuse them excessively.

Simply extracting the most value out of individual contributors isn't typically the goal of white collar management. as in my earlier example, you won't see order pickers at amazon warehouses attend meetings all day. their time at work is valued differently than a white collar workers'.
by oogali | 2026-02-18 14:01:34+00:00
> I've always advocated for having a read only database connection to be available for your customers to make their own visualisations.

Roughly three decades ago, that *was* the norm. One of the more popular tools for achieving that was Crystal Reports[1].

In the late 90s, it was almost routine for software vendors to bundle Crystal Reports with their software (very similar to how the MSSQL installer gets invoked by products), then configure an ODBC data source which connected to the appropriate database.

In my opinion, the primary stumbling block of this approach was the lack of a shared SQL query repository. So if you weren’t intimately aware with the data model you wanted to work with, you’d lose hours trying to figure it out on your own or rely on your colleagues sharing it via sneakernet or email.

Crystal Reports has since been acquired by SAP, and I haven’t touched it since the early ‘00s so I don’t know what it looks or functions like today.

1: https://en.wikipedia.org/wiki/Crystal_Reports
Show HN: Owoa – Image watermarking resistant to camera capture
by wodoshio | 2026-02-18 14:01:40+00:00
My friends and I built Owoa to solve a specific problem in digital rights management: the "analog hole."

Traditional steganography and watermarking usually rely on LSB (Least Significant Bit) modifications or fragile metadata. These methods are instantly defeated the moment a user takes a physical photo of their monitor with a smartphone. The moiré patterns, sensor noise, and lens distortion destroy the digital signal.

Instead of hiding data in pixels, Owoa uses generative AI to create unique variants of an image by subtly modifying background elements (textures, foliage, unstructured patterns).

Because the "data" is now part of the actual visual composition of the image, it is much more robust. In our testing, the attribution survives:

Heavy JPEG compression and resizing.

Aggressive cropping.

Physical photos of 1080p/4K screens taken with mid-range smartphones.

We've just launched a Owoa Playground and are looking for technical feedback on the robustness of this approach compared to traditional robust watermarking.

We're giving 10 free credits to anyone who joins the waitlist to test the engine. I'd love to hear how you'd try to break this.

Link: https://owoa.app/
by trentm6 | 2026-02-18 14:01:51+00:00
I built an AI workflow system for my own product work, refined it across client engagements, and decided to open-source the whole thing.

Baseline Core is a complete AI system for product work. It loads your business context into whatever AI tool you use so the output is actually specific to your company.

What's in it:
- 12 skills covering research, PRDs, sprint planning, UX design, prototyping, positioning, docs, analytics, and more
- 14 reusable frameworks (RICE, PAS, AIDA, research synthesis, etc.)
- Context file scaffolding for your business identity, voice, users, competitors
- Works with Claude Code, Cursor, Windsurf, ChatGPT, Gemini, Copilot

Install: npx @baseline-studio/cli init

MIT licensed. No SaaS. No API calls. Files live in your repo.

10 years in product. The gap isn't the AI tools -- it's having a system around them.

Also launched on Product Hunt today if anyone wants to check it out there: producthunt.com/posts/baseline-core

Feedback welcome. What would you actually use? What's missing?
by apignotti | 2026-02-18 14:02:35+00:00
We test performance internally constantly, and we plan to soon publish a benchmarking repository.

Depending on the workload the performance is actually very close to native, I'll give a few highlights.

* Node.js C++ code is compiled to WebAssembly and as such is very close to native speed
* Node.js JavaScript payloads are executed directly by the browser engine. There is some additional overhead in some scenarios, but it's not large and we expect to further improve this down the line.
* There is proper multi-process support via WebWorkers. Multiple node processes can actually run in parallel on top of the same WebAssembly kernel.

There are a few areas that we need to improve still, to make an example we are hitting some of the limitations of IndexedDB for data persistent and we are experimenting with the OPFS API to squeeze some more performance. This is tricky since performance with OPFS is very dependent on the browser at this tie.

Our kernel itself still need some work, as concurrency in some scenarios is limited by overly extensive locking. We expect to make significant progress on these problems as well over the next weeks and months.

Moreover, the most direct alternative to BrowserPod is not a local sandbox, but a cloud provisioned one. Of course cloud performance depends on how much the platform owner is willing to spend, but we expect BrowserPod to be actually _much_ faster than common cloud options especially on the cheaper tiers.

We plan to publish benchmark against the main cloud sandbox providers as well in the future.

[Edited to mention the comparison against cloud VMs]
by grayhatter | 2026-02-18 14:02:35+00:00
> In short, we should focus on what works, not what you feel is righteously good.

These are not mutually exclusive. But i'm glad you're considering shareholder value!

> I’m guessing you have absolutely no empathy for people who run small single person or small team business and our overwhelmed by all the regulatory traps they can fall into at any point in time.

Sigh... yeah, lack of empathy is the core problem here.

> The general thrust of the underlying messagr is not dishonest just because you say so.

Comparing suicide of an individual to administrative fines on a corporation for needlessly destroying textiles is rhetorically dishonest. There's so many disparities and meaningful differences that trying to equate them without discussing any of them is counter productive to a beneficial conversation. It's a cheap impotent shot trying to stir up an emotional reaction where one doesn't belong. Or given how strongly you seem to feel, a completely different reaction is deserved. Making a misleading or inappropriate comparison is dishonest, not because I say it is, but because being misleading, even carelessly, lacks rhetorical integrity, or honesty.

Four more examples, of rhetorical dishonesty suggesting I'm acting in bad faith, and lack empathy, or sympathy for the balance of weight for smaller companies (without cause)

Saying again without argument or evidence that my position is a self righteous one devoid of pragmatic function.

Mischaracterizating my opposition to your comments as shallow or opinionated rather than a different core issue you've been unable to identify or reply to.

And then my top reply to yours, suggesting that all you care about is shareholder value. But at least I'm only saying so because it's become a common joke, but also because your first comment feels irreverent towards S/SI, or humans. And the sum total of your next reply ignores the core point of my objections, and drones on about the financial cost towards companies. So maybe it's not that dishonest.