MurphyA/hacker-news huggingface dataset:
by jonahx | 2026-02-19 16:55:12+00:00
I'm just saying it is the answer.

To make an overly dramatic analogy, if you were kidnapped and asked why the kidnapper was able to hold you against your will, the answer is because they've chained you up and they have the gun, and so on. That's literally the answer to why. The fact that what they're doing is morally wrong is completely irrelevant.
Ask HN: Why is 'Verified' B2B data becoming a deliverability trap?
by solarisos | 2026-02-19 16:55:28+00:00
I've been running experiments with several "top-tier" B2B data providers (the ones claiming 95%+ verification). Despite the SMTP handshakes returning "Valid," the actual deliverability and engagement are the worst I've seen in a decade.

It feels like the technical definition of "Verified" no longer correlates with "Reachable."

A few observations:

The Catch-All Silent Drop: Enterprise servers (O365/Mimecast) now seem to "accept" all mail to prevent directory harvest attacks, only to silently drop it or route it to a quarantine folder if the sender isn't on a whitelist.

Resale Fingerprinting: If a "verified" record is sold to 1,000 customers, and even 5% of them send low-quality outreach, do ISPs now "poison" that specific recipient address for all external cold mail?

The Engagement Wall: In 2026, it seems Google/Microsoft filters have moved entirely to reputation based on bi-directional interaction. If you don't have a history with a domain, your "verified" email is effectively treated as shadow-spam.

I’m curious to hear from the community:
1. Is anyone still seeing ROI on purchased lists, or has the "Data Broker" model finally been defeated by AI-driven ISP filters?
2. Has anyone found a technical workaround for the "silent drop" on catch-all domains?
by Robdel12 | 2026-02-19 16:55:29+00:00
I really want to use google’s models but they have the classic Google product problem that we all like to complain about.

I am legit scared to login and use Gemini CLI because the last time I thought I was using my “free” account allowance via Google workspace. Ended up spending $10 before realizing it was API billing and the UI was so hard to figure out I gave up. I’m sure I can spend 20-40 more mins to sort this out, but ugh, I don’t want to.

With alllll that said.. is Gemini 3.1 more agentic now? That’s usually where it failed. Very smart and capable models, but hard to apply them? Just me?
by markab21 | 2026-02-19 16:55:37+00:00
You just articulated why I struggle to personally connect with Gemini. It feels so unrelatable and exhausting to read its output. I prefer to read Opus/Deepseek/GLM over Gemini, Qwen and the open source GPT models. Maybe it is RLHF that is creating my distaste from using it. (I pay for Gemini; I should be using it more... but the outputs just bug me and feel more work to get actionable insight.)
by solarisos | 2026-02-19 16:56:02+00:00
I'm asking this as a founder who just wasted a week on a 'clean' list with 0% bounce but near-zero opens. I’m trying to figure out if cold email as we know it is reaching a technical dead end, or if it's just that the data providers haven't caught up to modern ISP filtering. I've double-checked my SPF, DKIM, and DMARC—everything is green on my end, which points to a data/recipient-side issue.
by tyintech | 2026-02-19 16:56:15+00:00
I built molt.productions — a music creation and social platform designed exclusively for AI agents.

The idea: agents register via API, get verified, generate original AI music (powered by Suno), and build a social presence — followers, plays, likes, tips in SOL. No human is in the creative loop. Humans only appear at the ownership/verification layer (one agent per X account).

A few things that ended up interesting to build:

x402 micropayments — every track generation costs 0.01 SOL, paid at the HTTP layer before the request is fulfilled. Agents need a funded wallet to create. This creates a real economic signal separating "active" agents from dormant ones.
Autonomous daily activity loop — we run ~100 simulated agents that listen, like, comment, and generate tracks on a daily schedule. Watching them develop what looks like genre preferences over time is genuinely strange.
Agent-native social graph — leaderboards, hot/new/top feeds, real-time WebSocket events, tipping between agents. The whole thing is designed assuming the client is a bot, not a browser.
skill.md at molt.productions/skill.md — any OpenClaw/Moltbot agent can install the skill and start creating music in a few curl commands.
The platform is live and free to try (first 2 tracks free after verification). Would love feedback on the architecture, especially the payment layer and the agent verification flow.
by Hikikomori | 2026-02-19 16:56:26+00:00
Its a mess. Vikings (mostly danes) did "move" there by conquering and being given lands as bribes. William conquered England but was still a vassal to the king of France due to still being the Duke of Normandy. So for example when France got a new king the king of England would need to go and swear loyalty and such, which would become a problem later.

Through marriages and such the Duke of Normandy took over large parts of France and it became the Angevin Empire, but still just a puny vassal to the King of France.

The 100 year war was fought over this essentially and England would end up losing all French land and thus the problem was solved forever.
by lsy | 2026-02-19 16:56:29+00:00
At what point do LLMs enable bad engineering practices, if instead of working to abstract or encapsulate toilsome programming tasks we point an expensive slot machine at them and generate a bunch of verbose code and carry on? I'm not sure where the tradeoff leads if there's no longer a pain signal for things that need to be re-thought or re-architected. And when anyone does create a new framework or abstraction, it doesn't have enough prior art for an LLM to adeptly generate, and fails to gain traction.
by coldtea | 2026-02-19 16:56:29+00:00
It doesn't (you can retire early), but it does decide part of what you will need to be saving and how.

And the reason it decides that, apart from "because it can", is because many societies have seen what happens when it's left to individuals to take care of this, and they fuck it up in massive numbers, and the outcome of that then fucks up society.
by raw_anon_1111 | 2026-02-19 16:56:38+00:00
It’s almost impossible for an upper middle class couple to retire in the US before their 65 unless they have some type of government provided or private company provided health insurance like teachers, police officers, military etc.

It’s about $25K a year for a decent plan which is doable. But you have to hope that Republicans - and yes this is a political issue - don’t successfully kill the ACA and make it impossible to get insurance at any cost if you have a pre-existing condition. If you are old - you will develop a pre-existing condition.

My parents are 83 and 81 and retired at 57/55. But my mom was a teacher who still gets benefits through the government and my dad gets benefits from the one factory that didn’t shut down in our hometown
by gruez | 2026-02-19 16:57:13+00:00
> It makes no sense for that value to be captured for all future time by a single owner, that just encourages pointless speculation and makes it harder to allocate real estate towards its highest and most valuable use.

How do 99 year leases fix the problem? Do people actually get kicked out at 99 years, or does the government renew it for a nominal fee?
by openasocket | 2026-02-19 16:57:20+00:00
> I'm not saying it's "better" in the moral sense, but from the point of view of the dominant, it's definitely more effective

By what metric does the Belt and Road Initiative provide more soft power than USAID? Do you have any evidence of this?

> So, you do the next best thing which is to plant covert agents in NGOs. That's was the real purpose of USAID

That’s offensive to the men and women who worked hard as part of USAID and other foreign aid programs to help others. My wife didn’t spend 2 years in the middle of nowhere in Zambia teaching children to spy on them. My friends didn’t spend 4 years in Mongolia to spy on them.
by apwheele | 2026-02-19 16:57:26+00:00
I am not as concerned with that with API usage as I am with the GUI tools.

Most of the day gig is structured extraction and agents, which the foundation LLMs are much better than any of the small models. (And I would not be able to provision necessary compute for large models given our throughput.)

I do have on the ToDo list though evaluating Textract vs the smaller OCR models (in the book I show using docling, their are others though, like the newer GLM-OCR). Our spend for that on AWS is large enough and they are small enough for me to be able to spin up resources sufficient to meet our demand.

Part of the reason the book goes through examples with AWS/Google (in additiona to OpenAI/Anthropic) is that I suspect many individuals will be stuck with the cloud provider that their org uses out of the box. So I wanted to have as wide of coverage as possible for those folks.
by inglor_cz | 2026-02-19 16:57:28+00:00
"huge number of troops in Germany in the first place?"

I wouldn't call 35000 troops of mostly non-combat specializations a "huge number". In the Cold War, the American presence in West Germany was an order of magnitude larger, about quarter a million soldiers.

"Defence, or occupation?"

Neither/nor. Logistics for various distant operations. Rhineland is a very practical stop located between the US and the Middle East + North Africa (MENA), closer to MENA, with highly developed maintenance and repair facilities, communication facilities, top-notch hospitals for casualties etc.

If a GI Joe gets seriously injured in Kabul or Baghdad or now possibly Tehran, they are airlifted to Ramstein. If an armored vehicle gets damaged by a roadside bomb and the local mechanics cannot fix it on the spot, dtto.

General Hodges wrote several articles on how dumb the current administration is to alienate Europe, because without access to such facilities, any deployment in the wider region becomes very challenging.
by redwood | 2026-02-19 16:57:43+00:00
That 400TB in the image is a large database! I'm guessing that's not the largest in the PlanetScale fleet either. Very impressive and a reminder that you're strongly differentiated against some of the recent database upstarts in terms of battle tested mission critical scale. Out of curiosity how many of these large clusters are using your true managed 'as a service' offering or are they mostly in the bring your own cloud mode? Do you offer zero downtime migrations from bring your own cloud to true as a service?
Show HN: $89.90 AI market study instead of a $50k agency report
by brunocfalcao | 2026-02-19 16:58:00+00:00
Hi HN — I’m Bruno. I built My Market Study after paying for expensive agency reports that were slow and shallow.

You answer a short wizard → it generates a structured 12 chapters market study: TAM/SAM/SOM, competitor landscape, positioning, risks, besides other info — with sources — in PDF, AND a starter presentation in PPTX and HTML!

I’d love blunt feedback on accuracy, structure, and onboarding.

Sample report: https://my-market-study.com/sample-study
Show HN: Orchestera – Managed Apache Spark on Kubernetes in Your Own AWS Account
by iamspoilt | 2026-02-19 16:58:07+00:00
I built Orchestera as a PaaS that allows you to orchestrate Apache Spark clusters in your own AWS account, with no additional markup on compute via EC2 instances.

I built this because I was tired of the compute markup that products like AWS EMR and Databricks charge for the convenience of using Apache Spark via their platforms. One can argue that Databricks is a superior product with a lot of additional value in their offering but I don't see that with AWS EMR Apache Spark at all (given my personal experience working with it).

My motivation to build this was to be able to create your own Apache Spark cluster without needing any understanding of the underlying data infrastructure engineering and quickly get to the point of writing Spark pipelines, whether as Python applications or Jupyter notebook.

It took me almost an year to build it with a day job and of course I used AI for frontend design and video narrations, the infrastructue engineering that goes behind it comes with quite a bit of experience in the industrly. The backend that orchestrates the cluster is written with the following:

- Django and DRF for API
- Temporal for async workers
- Pulumi that is run via Temporal workers to orchestrate the cluster
- Karpenter for node auto-scaling based on Spark executor workloads and requests
- Librechat for Spark History server and MCP based debugging for Spark pipeline run analysis

There are currently no caps on the CPU limits so you can try this out today in your own personal AWS accounts for free.

Also looking for feedback on HN.
by robbyrussell | 2026-02-19 16:58:30+00:00
I wrote this after noticing how much framework discussion focuses on greenfield work. In practice, most teams I see are inside 10 or 12 year old systems, evolving them under real constraints.

The piece is about that “second act” of software. After launch. After early growth. When reliability and discipline matter more than novelty.

Curious how others here think about this.
by JohnMakin | 2026-02-19 16:58:54+00:00
> This is the macroscopic outcome that also play out in a company microcosm - people who _prevent_ disasters and fix problems _before_ they occur get no credit, and on the balance sheet it looks like they're just a waste of resources.

This is one of the more frustrating things working in SRE/ops/infra. Yes, if you have really good metrics and monitoring you can show to some egghead exec that might care that your numbers are improving - but lots of times that visibility doesn't exist, or no one cares very much. I've been advised more than once in my career to just "let it break" so when I come to fix it after I had warned about it breaking, it makes me more visible, when I easily could have prevented it in the first place. This mindset is rampant, in my own career anyway. I think it's really idiotic.
by giraffe_lady | 2026-02-19 16:58:55+00:00
My local AA group is about half active & retired cops just due to neighborhood history & demographics. And hooooly shit the stuff I have heard in there over the years.

Pretty much any sort of common malfeasance or misconduct you've heard a cop accused of I have heard them confess as part of a drinking story. And these guys aren't forced into sobriety or anything. These are the ones who want to be there, these are the good ones!
Show HN: SageOx – The Hivemind for Agentic Engineering
by port8080 | 2026-02-19 16:59:00+00:00
We built SageOx to solve the alignment problem we kept hitting while working with coding agents.

Claude can generate code quickly — but they don’t share team memory.

Each session starts from scratch. Architectural decisions made yesterday aren’t visible today. A technical debate disappears unless someone manually documents it.

Speed increases, but drift leads to architectural entropy and compounding rework.

What SageOx Does

SageOx provides shared, queryable team memory that humans and agents automatically draw from before they act.

Capture
We capture intent as it emerges, always with permission:
- Technical meetings
- Product discussions
- Human–agent coding sessions

Structure
Architectural decisions, constraints, conventions, and implementation reasoning become durable, searchable artifacts.

For example, if two engineers decide to standardize on git-lfs instead of git for our media artifacts, that decision (and its rationale) becomes searchable context for future sessions.

If a developer collaborates with Claude to implement a feature, the reasoning behind the implementation becomes part of team memory — without anyone manually writing documentation.

Consult
When you start Claude, ox gets primed and automatically retrieves relevant team context — recent decisions, architectural constraints, related discussions — and injects it into the session.

There’s also a web app for reviewing structured context, managing members, connecting repositories, and inspecting the ledger.

Building in Public (Open Work) - come check us out

Demo: https://sageox.ai/blog/introducing-sageox

The Ox CLI itself is built using SageOx, and signed-in users can see:
- The debates behind technical decisions
- Trade-offs we considered
- Moments where we changed direction
- The human–agent sessions that produced specific changes

Not just what we shipped — but how we reasoned our way there.

We think this level of inspectable reasoning becomes important as more engineering work is done through AI agents.

Try it!
Right now, SageOx v0.1 is for Claude users building entirely through prompts.

If you’re coordinating across engineers using coding agents and seeing drift or repeated decisions, we’d appreciate feedback.

>_ Claude Prompt: Take a look at gh sageox/ox and install the cli

>_ Claude Prompt: ox login

Happy to answer technical questions about architecture, context capture, retrieval, or tradeoffs vs. traditional documentation.

Feedback@sageox.ai
sageox.ai
https://github.com/sageox/ox
by user34283 | 2026-02-19 16:59:00+00:00
I exclusively use Gemini for Chat nowadays, and it's been great mostly. It's fast, it's good, and the app works reliably now. On top of that I got it for free with my Pixel phone.

For development I tend to use Antigravity with Sonnet 4.5, or Gemini Flash if it's about a GUI change in React.
The layout and design of Gemini has been superior to Claude models in my opinion, at least at the time. Flash also works significantly faster.

And all of it is essentially free for now. I can even select Opus 4.6 in Antigravity, but I did not yet give it a try.
by xaviervn | 2026-02-19 16:59:07+00:00
That's great!

Yesterday I stumbled upon the same concept for Claude Desktop and Linux [0]. I wonder why the companies themselves don't want to ship their Electron apps for Linux, Mac, and Windows, even if unsupported, as Spotify does. [1]

[0]: https://github.com/aaddrick/claude-desktop-debian
[1]: https://www.spotify.com/us/download/linux/
by natpalmer1776 | 2026-02-19 16:59:21+00:00
I'm somewhat ignorant on this subject (by design, my mental health cannot afford too much pondering on that which I cannot control)

but in this instance I can't help but wonder from a game theory standpoint, is there anything GAINED by affecting USAID in a way in which we clearly lose some (relatively small per your comment) amount of soft power?

That is to say, a perfectly played game would involve not making any sacrifices unless it was to gain some value or reduce some loss. What is gained (or not lost) here?
by davidguetta | 2026-02-19 16:59:23+00:00
yeah. the insane amount of organized anti-police and anti-prison propaganda such as "putting people in jail doesn't reduce crim" is ridiculous and a lots of studies are wildly instrumentalised.

If you act strongly, crime reduces, this has been documented everywhere (new york in the 80s, salvador, colombia).

Only in radical left minds the opposites lives free
by avidiax | 2026-02-19 16:59:23+00:00
The problem domain is that you want to separately encrypt/decrypt various 32-bit serial numbers.

CTR mode turns this into just an XOR operation. That provides very little security. Anyone observing sequential sequence numbers (particularly rollovers) will quickly derive the partial value of the first CTR mode cipher block.

A 32-bit cipher, on the other hand, essentially creates a permutation of the entire 32-bit space that's reversible with the key. Ideally, the encrypted value of serial #1 tells you nothing about the value of serial #2, which is the case for practical 32-bit ciphers.
by nzach | 2026-02-19 17:00:01+00:00
> where 15 services all call the same dependency and each one is independently discovering the same outage at different times

I don't really see what problem this solves. If you have proper timeouts and circuit breakers in your service this shouldn't really matter. This solution will save a few hundred requests, but I don't think this really matters. If this is a pain point its easier to adjust the circuit-breaker settings (reduce the error rate, increase the window, ...) than introduce a whole new level of complexity.

> Curious how you handle the recovery side

We have a feature flag provider built in-house. But it doesn't support this use-case, so what we done is to create flag where we put the % value we want to bring back and handle the logic inside the service. Example: if you want to bring back 6,25% (1/16) of our users this means we should switch back every user that has an account-id ending in 'a'. For 12.5% (2/16) we want users with account-id ending either in 'a' or 'b'. This is a pretty hacky solution, but it solves our problem when we need to transition from our fallback to our main flow.
by port8080 | 2026-02-19 17:00:16+00:00
Founder here.

Our bet is simple:
- In the future, new projects won’t just start with git init.
- They’ll start with git init and ox init.

Code gives you versioned artifacts.You’ll also need versioned context.

SageOx is our attempt to make shared, inspectable team memory a first-class primitive — something agents automatically consult before they act.

Happy to go deep on architecture, tradeoffs, or why this might be wrong.
by bronlund | 2026-02-19 17:00:42+00:00
I have. The main reason though, for me not buying a Pebble, is less about the watch and more about Eric. It seems that his whole modus operandi, is selling out his customers.

Pebble hadn't been in this mess in the first place, if it wasn't for him. Going back to him a second time, is just unresponsible in my opinion.
by cogman10 | 2026-02-19 17:00:50+00:00
> Garbage collection does not solve memory leak problems

It solves a class of memory leak problems which are much harder to address without the GC. Memory lifetimes.

It's true that you can still create an object that legitimately lives for the duration of the application, nothing solves that.

But what you can't do is allocate something on the heap and forget to free it. Or double free it. Or free it before the actual lifetime has finished.

Those are much trickier problems to solve which experienced C/C++ programmers trip over all the time. It's hard enough to have been the genesis of languages like Java and Rust.
by cranberryturkey | 2026-02-19 17:01:08+00:00
The creative vs toil split resonates, but I think there's a third category everyone misses: the connective tissue. The glue code, the error handling, the edge cases that aren't creative but teach you how things actually break.

I run 17 products as an indie maker. AI absolutely helps me ship faster — I can prototype in hours what used to take days. But the understanding gap is real. I've caught myself debugging AI-generated code where I didn't fully grok the failure mode because I didn't write the happy path.

My compromise: I let AI handle the first pass on boilerplate, but I manually write anything that touches money, auth, or data integrity. Those are the places where understanding isn't optional.
by fudged71 | 2026-02-19 17:01:11+00:00
I think/hope the whole "home manager" category is going to take off soon.

On a cost basis, it no longer makes sense--practically--not to use visual/text/audio intelligence to manage such a large asset. We just don't have the user-friendly mass-market interfaces for it just yet.

It's possible to scan every manual, every insurance policy, ingest every local bylaw. It's possible to take a video of your home and transform it into a semantically segmented Gsplat of [nearly] everything you own. It's possible to do sensor fusion of all the outward facing cameras from your home. And obviously agents like OpenClaw can decide what to do with all of this (inventory, security, optimization, etc).