MurphyA/hacker-news huggingface dataset:
by Aditya_kachhawa | 2026-01-21 16:07:36+00:00
Sorry for the late reply, I missed the notification earlier.
What I'm really curious about is how modern AI systems work end-to-end in production. I can code and understand the basics, but I want to get into the real-world implementation details. Like, how do companies actually structure their training pipelines? What's the data collection process like at scale? How do they handle data quality issues? What are the actual trade-offs teams face when choosing between different approaches?
I'm also interested in where these systems break down in practice and what that means for developers building with them.

I started a small blog about tech and marketing. Honestly, I got into this thinking about marketing, but I realized quickly that if you don't have an audience that trusts you, marketing doesn't work. The only way to build that is by creating genuinely valuable content. So now I'm focused on learning properly and sharing what I figure out.

Since I just wrote about ambient AI, I want to go deeper into how these systems actually get built in practice. I know "how AI works" is massive, so I'm thinking of starting with the data pipeline how training data gets collected, cleaned, and prepared at that scale. Feels like that's foundational but doesn't get nearly as much attention as model architectures.

Your question really helped me think about this more clearly. I honestly wasn't expecting anyone to respond, so I really appreciate you taking the time. Thank you sir!
by kstrauser | 2026-01-21 16:07:47+00:00
Or more likely, network engineers who’ve been subpoenaed to collect the information?

Your scenario is plausible for high value targets. Like, what country wouldn’t want to have a friendly tech working at the ISP most politicians use in DC? That doesn’t seem improbable.

For the regular Joe Schmoe, I’d be more concerned with court-ordered monitoring.
by pixl97 | 2026-01-21 16:07:49+00:00
>Not to say that coding doesn't have those two, but I'd argue developers have been caring less and less for it over the years.

I think this is both hindsight bias and survivorship bias.

There has always been massive buckets of buggy shit code out there. Now, one thing we had in the past was very tight computing limitations that worked as a decent evolutionary death function. As computing resources grew, the selection function became less effective and we get to see these hulking crap monsters lumber around our CPUs.
by grayhatter | 2026-01-21 16:07:59+00:00
Best I can do is t'ree fiddy.

I can definitely be bought for much much less. But only because I'm pretty sure I could rave about some AI platform while still being honest about it. Why do you draw such a hard ethical line? I agree with your sentiment, AI is currently a net negative on the world that I care about. But I also believe people when they say it helps them. Despite their inability to articulate anything useful to me, or that I can understand.
by convolvatron | 2026-01-21 16:08:00+00:00
we do. being a machinist in the US means being able to convert between decimal inches, mm, fractional inches, and things like feet all the time. not to mention other completely arbitrary units like sheet gauge, fastener number and inverse thread spacing. there are also decimal feet for carpenters.

this for me is the real appeal of metric, not that somehow a meter is magical, but at least there is one system, with a consistent set of rules, that allows us to do some magic things like tell the approximate volume of water given a weight.

edit: omg I forgot about nominal wood sizes. the underlying system actually has different units based on the material and the usage. copper gauge is not the same as steel gauge. thats pretty hopeless. for precious metals we also have the pennyweight
by MarkusQ | 2026-01-21 16:08:29+00:00
> But it's not really a question of style if you misspell certain words.

Sure it is. Flagging vernacular, phonetic spelling for accents, punning, signalling a character's use of a word they are unfamiliar with, and so on and so forth. Intentionally misspelling words can definitely be a stylistic choice.
by jcranmer | 2026-01-21 16:08:37+00:00
I really shouldn't be so gobsmacked by people's ignorance of history, but it is astounding to me the number of replies here that seem to believe that the press really was well-behaved in this time period. When learning about the Spanish-American War, pretty much the most important bullet point covered in history class is the role of the press in essentially inventing the cause of the war, as exemplified by the infamous quote from a newspaper baron: "You furnish the pictures and I'll furnish the war."

The general term to look up is "yellow journalism."
by pratikdeoghare | 2026-01-21 16:08:45+00:00
I faced this problem when designing my own notation [1].

Solved it by surrounding code with more ticks than maximum number of consecutive ticks inside its text. This allows arbitrary nesting.

Postgres solves it by using `$something$ whatever $something$` [2].

[1] https://github.com/PratikDeoghare/brashtag
[2] https://www.postgresql.org/docs/current/sql-syntax-lexical.h...
by pgedge_postgres | 2026-01-21 16:08:53+00:00
We listened to customers as they refined their AI strategies in response to the rapid evolution of LLMs, Agentic AI and integration technologies such as the Model Context Protocol (MCP), and as we did so a few things stood out to us.

First and foremost, many of the newly available tools and technologies are not suited to the needs of the enterprise, particularly in highly regulated industries or major government agencies. Many of the new AI application builders and code generators – and the database platforms supporting them – do not adequately address enterprise requirements for high availability, data sovereignty, global deployment, security and compliance and the need in some cases to run on-premises or in self-managed cloud accounts. As one CIO from a large financial services firm put it to us recently: “We’ve got a couple of dozen AI generated applications end users really want to put into production, but first we’ve got to figure out how to deploy them on our own internal compliant infrastructure.”

Secondly, as compelling as it is to automate workflows with Agentic AI, or to generate new applications with tools like Claude Code, Replit, Cursor or Lovable, the biggest need is to work with existing databases and applications. While some of the newer Postgres-based cloud services work well with Agentic AI and AI app builders for brand new applications they cannot accommodate existing databases and applications without a costly migration – and perhaps to an environment that doesn’t meet the organization’s strict security and compliance requirements. Enterprise customers need AI tooling – including an MCP Server – that can operate against their existing databases.

Additionally we saw there was no dedicated Postgres vendor offering a fully featured and fully supported MCP Server that works with all your existing Postgres databases. Most of the available Postgres MCP Servers are tied to the vendor's own products, and in particular their cloud database offering.

And thirdly, developing new AI applications such as a chatbot running on top of an existing knowledge base, is overly complex with developers having to stitch together too many tools, APIs, Postgres extensions and data pipelines. We saw an opportunity to make it easier to develop AI applications without having to undertake a major exercise in tool sourcing and integration.

We are addressing each of these with the pgEdge Agentic AI Toolkit for Postgres.
by Lightbody | 2026-01-21 16:08:56+00:00
You can turn on a feature that will not auto-add invites to your calendar if sent from "unknown senders". The downside (significant IMO) is that "unknown senders" is based on Google Address Book + Other Contacts (aka people you email with). So if you're texting with someone, using a Calendly-style link, or pretty much any other non-email method of communication to schedule the meeting, it can easily be lost. It will still end up in your inbox, but you will have to accept the invite there for it to appear anywhere in Google Calendar.

Context: I'm the cofounder of Reclaim.ai.
by pengaru | 2026-01-21 16:09:02+00:00
It will never cease to drive me batty every time I try find a metric fastener for an automotive purpose at a local hardware store.

There are many reasons I can find for leaving the US, but engaging in DIY projects utilizing local suppliers are what's come closest to pushing me over the edge. Especially in this post-SEARS hellscape of low quality made in china junk the market's flooded with. Now not only can I never find the fasteners I need, the tools suck too!
by catlifeonmars | 2026-01-21 16:09:36+00:00
> Actually, you don't have to. You just want to.

Fair.

> The point of Free Software isn't for developers to sort-of-but-not-quite give away the code. The point of Free Software is to promote self-sufficient communities.

… that are all reliant on gatekeepers, who also decide the model ethics unilaterally, among other things.

> (INB4: The fact that good LLMs are themselves owned by some multinational corps is irrelevant - much in the same way as cars are important tool for personal and communal self-sufficiently, despite being designed and manufactured by few large corporations. They're still tools ~anyone can use.)

You’re not wrong. But wouldn’t the spirit of Free Software also apply to model weights? Or do the large corps get a pass?

FWIW I don’t have a problem with LLMs per se. Just models that are either proprietary or effectively proprietary. Oligarchy ain’t freedom :)
by editorializing | 2026-01-21 16:10:08+00:00
> No project should ever be "overlooked" due to the use of AI coding tools.

Why would stolen GPL code spit out poorly by the Chinese Room experiment be interesting or satisfy intellectual curiosity? Anyone can ask a chatbot to make anything, and according to LLM fans they'll do it, now. Zero value and zero intellectual curiosity possible in projects that used LLMs in their creation. Terrible take.

So many bad Show HNs lately, mostly langlemangle garbage. Zero thought, zero effort, zero skill, zero ingenuity, zero usefulness. Completely ruins the historical value of the "Show" tab, killing a valuable historical resource for everyone because of how heavily-invested YC is into the "hit the button to make disposable software" genre of company.
by Braxton1980 | 2026-01-21 16:10:10+00:00
The Democrats made small progress on healthcare.

Insurers couldn't deny coverage due to existing conditions

Kids could stay on parents until 26 even if they aren't in school

There were also subsidies for the lowest income people to help pay for open market plans.

This is something right? This is a step in the right direction?

If one party wants this and the other wants to dismantle then the first is left and the latter right.
by Manuel_TPC | 2026-01-21 16:10:21+00:00
Fantastic article! You nailed the core irony perfectly: the term "PC Compatible" was almost a misnomer from day one, because even in the heyday of cloning, a "compatible" machine could choke on software that poked the hardware directly or relied on the quirks of IBM's specific BIOS. True compatibility was always a spectrum, not a binary state.

It’s a great example of a technological anachronism—a term that outlives its original meaning. We have plenty of those, for example, we still "dial" a phone number on a keypad, "hang up" a call without a physical receiver to hang, and save a file to a "desktop" that’s often just a digital metaphor.

So really, "PC Compatible" fits right in: a useful, socially-agreed-upon label that’s more about practical expectation than technical purity. Thanks for the insightful read—it definitely brought a smile to my face. Cheers
by m-hodges | 2026-01-21 16:10:32+00:00
See: A field guide to sandboxes for AI¹ on the threat models.

> I want to be direct: containers are not a sufficient security boundary for hostile code. They can be hardened, and that matters. But they still share the host kernel. The failure modes I see most often are misconfiguration and kernel/runtime bugs — plus a third one that shows up in AI systems: policy leakage.

¹ https://www.luiscardoso.dev/blog/sandboxes-for-ai
by heliumtera | 2026-01-21 16:10:38+00:00
this is an excellent observation.

the bubble might be a thing of concern, but the phenomenon behind it is much bigger then most can comprehend. even among hackers, we see a very naive and superficial understanding. most are still thinking in the current framework of the game while the game fundamentally changed. the lemon market will persist regardless of an imminent burst!

even if the average tone changes, the fabrics of this game is forever eroded. hacker news current structure makes no sense when consensus can be fabricated (automated karma farming + targeted "collective action" is cheap, people have already realized this and soon will become intolerant).
showing a project means nothing, showing the equivalent of a prompt has negative value.
people will still urge for care and passion, discovery, interesting ideas. people will urge for a way to separate a vibed nothing-project, valued at 25 Claude sonnet prompts, in response to the latest Simon wilinson new hot take in 35 minutes.
people will want a way to separate a good faith idea cultivated with passion from a "look what I did to promote myself while spending 75 cents" idea.
by antisthenes | 2026-01-21 16:10:48+00:00
> (From my viewpoint as a millennial. Gen Z might think the golden years were during Obama, or just pre-COVID. To some extent every generation has a point in time that they see with rose tinted lenses.)

Of course they do. It's the formative years & youth. Roughly from the time you form a mature consciousness (12-14 yo) to roughly your late 20s or maybe early 30s when all your tastes, preferences etc. are formed.
by _alternator_ | 2026-01-21 16:10:48+00:00
My qualitative experience is that, far from lower quality submissions, the Show HN posts that make the front page seem to be increasing in quality.

There are likely to be a number of possible explanations for this that offset the lower average score. The obvious one is that the filtering effect of the front page with a higher amount of content. Perhaps we are also seeing higher standards—a project that used to take 6 weeks and a ton of conviction now wraps up in a few hours, and people are resetting their expectations.
by barrell | 2026-01-21 16:10:51+00:00
I just rewrote all the graphs on phrasing [1] to webgl. Mostly because I wanted custom graphs that didn’t look like graphs, but also because I wanted to be able to animate several tens of thousands of metrics at a time.

After the initial setup and learning curve, it was actually very easy. All in all, way less complicated than all the performance hacks I had to do to get 0.01% of the data to render half as smooth using d3.

Although this looks next level. I make sure all the computation happens in a single o(n) loop but the main loop still takes place on the cpu. Very well done

To anyone on the fence, GPU charting seemed crazy to me beforehand (classic overengineering) but it ends up being much simpler (and much much much smoother) than traditional charts!

[1] https://phrasing.app
by ontouchstart | 2026-01-21 16:10:55+00:00
Engineering is more or less about getting familiar with the proper tools and use them to solve specific problems: add new features, debugging, refactoring and optimizing.

And the tools themselves are built by other engineers and they need new features, debugging, optimization etc. It is turtles all the way down.

But each layer has its own jargons, conventions and unwritten hacks. That is where experience comes in. Once you get out off a rabbit hole or pothole, you are one step closer to becoming the “domain expert”. There is no short cut.
by borenstein | 2026-01-21 16:11:05+00:00
I know, right? The day I initially thought about posting this, there was another one called `yolo-box`. (That attempt--my very first post--got me instantly shadow-banned due to being on a VPN, which led to an unexpected conversation with @dang, which led to some improvements, which led to it being a week later.)

I think it's the convergence of two things. First, the agents themselves make it easier to get exactly what you want; and second, the OEM solutions to these things really, really aren't good enough. CC Cloud and Codex are sort of like this, except they're opaque and locked down, and they work for you or they don't.

It reminds me a fair bit of 3D printer modding, but with higher stakes.
by huntergemmer | 2026-01-21 16:11:17+00:00
Thanks! Leon's uPlot is fantastic - definitely an inspiration.

Worker thread support via OffscreenCanvas is a great idea and WebGPU does support it. I haven't tested ChartGPU in a worker context yet, but the architecture should be compatible - we don't rely on DOM for rendering, only for the HTML overlay elements (tooltips, axis labels, legend).

The main work would be:
1. Passing the OffscreenCanvas to the worker
2. Moving the tooltip/label rendering to message-passing or a separate DOM layer

For your use case with heavy data munging, you could also run just the data processing in a worker and pass the processed arrays to ChartGPU on the main thread - that might be a quicker win.

Would you open an issue on GitHub? I'd love to understand your specific workload better. This feels like a v0.2 feature worth prioritizing.
by alsko | 2026-01-21 16:11:33+00:00
There has been a lot of examples of how to sandbox Claude Code and other agentic tools on HN lately. I decided to look into the options and realized Claude Caude already has a sandbox feature that I never saw mentioned among the suggestions. It uses bubblewrap/sandbox-exec[0] and is baked into Claude Code itself. Does anyone have experience with it compared to more DIY options? The obvious downside I can see is I need to put all my trust in Claude Code as compared to running it completely inside some environment..

[0] https://github.com/anthropic-experimental/sandbox-runtime
by t-3 | 2026-01-21 16:11:33+00:00
> The suggestion of a group you identify as being less, causes a predictable reaction to characterize the other (non-aphantasia) as problematic/hallucinating (i.e. broken/lacking).

No, it's not a defensive/counterattacking reflex. The thought of people hallucinating all the time is terrifying to me, because hallucination is a sign of something being very wrong, like schizophrenia. After getting past the language barrier and finding out these were "mental hallucinations" rather than "visual hallucinations", it's slightly less scary, but still unsettling for me to think about. Finding out that visualization was actually a thing meant that idioms that I thought were metaphors or superstition were suddenly something the majority of the population takes literally. People who have "invisible friends" talking to them all day long scares me though.
by eithed | 2026-01-21 16:11:48+00:00
> A degree used to be a class distinction, a signal that someone belonged to the affluent in-group.

While I understand and agree to a certain degree, (and as a person with degree) it still fills me with dread where I work with senior developers who don't have a clue what is complexity of their algorithms or lack basic problem solving skills that a degree would instill in them. People can absolutely learn on the job but degree would still give me an idea of what I can expect from given person.

As a side note, LLMs are an equalizer that makes degrees less relevant when near keyboard; still, I want to talk to people that understand the concepts they're operating with
by jedberg | 2026-01-21 16:11:50+00:00
How much AI is too much? Are you allowed to use Photoshop to create your digital art? Almost every tool there is now powered by AI in some way (some a lot more than others). Can you use its auto-fill button? What percent of the image can you use it for?

Can you generate something with AI and then manually edit it in Photoshop? How much manual editing is required before it's not considered AI anymore?

My point is, AI is another tool in the toolbox, it can be used well or poorly. How much is too much? Just like back in the day, using Photoshop wasn't allowed, until it was.

Where does one draw the line?
by grayhatter | 2026-01-21 16:11:57+00:00
People make mistakes, it's not that deep. The correct incentive to encourage is admitting, and understand and forgiving when necessary because you don't want to encourage people to hide mistakes out of shame. That only makes things worse.

Especially considering forgetting the delta between yours and someone else's shared context is extremely common. And the least egregious mistake you can make when writing an untargeted promo post.
by cestith | 2026-01-21 16:11:58+00:00
In particular a place I used to work had a plugin for threaded comments in Jira. The specific one we were using slowed things down noticeably with the DB on the same server, but not too much to be an improvement in overall usefulness.

Then we decided trying to make our Jira more reliable by splitting the DB out into a separate clustered DB system in the same data center. The latency difference going through a couple of switches and to another system really added up with those extra 1600 or so DB calls per page load.

We ended up doing an emergency reversion to an on-host DB. Later, we figured out what was causing that many queries.
by amluto | 2026-01-21 16:11:59+00:00
> The key difference in threat models is that the device manufacturer often needs to protect their intellectual property (firmware, algorithms, and data) from the end-user or third parties, whereas on a PC, the end-user is the one protecting their assets.

I would love to see more focus on device manufacturers protecting the user instead of trying to protect themselves.

Prime example where the TPM could be fantastic: embedded devices that are centrally coordinated. For example, networking equipment. Imagine if all UniFi devices performed a measured boot and attested to their PCR values before the controller would provision them. This could give a very strong degree of security, even on untrusted networks and even if devices have been previously connected and provisioned by someone else. (Yes, there’s a window when you connect a device where someone else can provision it first.

But instead companies seem to obsess about protecting their IP even when there is almost no commercial harm to them when someone inevitably recovers the decrypted firmware image.
Ask HN: What's your biggest challenge with context engineering for AI agents?
by karpathunter | 2026-01-21 16:12:04+00:00
I've been building agents for a couple years and context engineering keeps being the bottleneck. Curious what problems others are hitting.

Things I've struggled with:

- Debugging what the agent actually saw at decision time

- Managing context across multi-agent patterns

- Keeping history without blowing up storage

What's eating your time?
by madduci | 2026-01-21 16:12:34+00:00
I use Terraform with the Kubernetes Provider, which is also actively developed by HashiCorp itself.

Templating / injection of values has been much better, skipping the Helm Templating madness and relying on a set of tools that allow perform minting, security scans, generation of docs, unit tests and establish clear dependencies within Terraform, thanks to the graph model.

Helm Charts are a nice idea, but mistakes can happen really easy
by 72deluxe | 2026-01-21 16:12:35+00:00
But that sounds rewarding for the applicants, and the project?? The project gets code, and the guys get some money.

Being a middle aged man working 9 to 5, I would enjoy contributing to a project I was interested in rather than the boring job at work.

Are you saying you only wanted penniless youngsters to contribute, based entirely on their idealism?