MurphyA/hacker-news huggingface dataset:
by vbezhenar | 2026-03-04 02:26:52+00:00
I own T14s Gen4 Intel and Linux support is perfect, even fingerprint reader works. Zero complaints. I'm mostly using it in clamshell mode connected via USB-C to display with backwards charging, it all just works! I'm also using secureboot with my keys, I cleared all MS keys and it didn't brick the laptop.

My only grievance is a bit buggy firmware. When I turn laptop on or reboot, speakers will randomly be muted (not a problem after OS boots, but for example in UEFI it'll either beep or not beep and that's random). UEFI interface was a bit buggy regarding mouse control, for example I've used to touch and drag things in boot order, but it didn't work and I have to actually press touchbar button down and keeping it like that move cursor. But touch drag works in other places. Not a big issue bit the first time I encountered it, I spent good few minutes trying to make sense of it, as I thought it just does not allow me to reorder boot entries or something like that. But these are small issues and once you've installed OS, you never deal with that.

Oh, and another complaint is that their BIOS update procedure is super weird. I have to find computer with Windows, download some exe, unpack things, find some BAT file and write to USB drive things, then boot from it. Theoretically they publish stuff to fwupd but I don't like this service. My best BIOS update experience was on Asus PC. I just put some bin file onto FAT32 USB drive, entered UEFI configuration, chose "update", selected that file and that's about it. Super easy, every manufacturer must implement this workflow.

Anyway I'm satistfied owner and my next laptop will likely be Thinkpad. Mostly because its stellar Linux support, but also because I didn't have any major issues with my current laptop.
by adithyassekhar | 2026-03-04 02:27:05+00:00
The age question was bit of an overreach on my part, sorry about that, I felt like you were one of those new developers who only ever had high end macbooks.
You are right about the economics side and I don't hate electron in particular. Just the general state of the industry. Even native is incredibly slow nowadays while spending 1000x more cycles. It's crazy.
by kiddico | 2026-03-04 02:28:27+00:00
I'm rocking a framework 13" intel 12th gen still and I love it. The only issue I had was being part of the few that got a batch of bad hinges. I didn't know there was a replacement program I could have used and just replaced them myself with the heavier hinge option. At this point I have every expansion port thing they offer and keep them in my bag. My laptop can have any I/O I want :) pretty cool.
by rancar2 | 2026-03-04 02:29:23+00:00
I would recommend a more systemic mapping like Power Scorecard from Demos.org [1] to help ground the mappings to impacts on populations. Ideally, one would be able to swap the system mappings based on the preferred context, as there are different policies that should be looked at in different ways to assure optimal positive impacts with minimal secondary negative impacts. I haven’t seen a perfect way of doing this yet, but this will be directional correct on the pathway to something even better for all of us. Thank you for your labor of love and efforts!

[1] https://power.demos.org/
by davegoldblatt | 2026-03-04 02:29:48+00:00
You're not off base. There's no per-claim evidence trail. The Claude pipeline scored claims using model judgment and stored verdicts without the reasoning or sources behind them.
Your Tesla example is a good one. There is real evidence for that causal claim (NHTSA investigations, documented crashes where Autopilot naming was cited as a factor), but the dataset doesn't show you any of it. Right now it's just "Claude said so."
What the dataset is currently good for: extraction, clustering, timeline structure, and surfacing drift patterns across claim families. When 120 hallucination claims come back 57% supported and 63 bubble claims come back 41% contradicted, the distribution tells you something even if any single verdict is arguable.
What it's not good for: claim-by-claim adjudication auditability. You're right that without provenance, this is closer to a structured first draft than a final verdict. Your approach of storing browsed pages and snippets per-claim is what auditable looks like.
by larryste | 2026-03-04 02:29:49+00:00
GitHub: https://github.com/larryste1/prompt-vault
PyPI: https://pypi.org/project/prompt-vault-cli/

After creating 75+ tools for my AI agent workflow, I kept losing my best prompts across different conversations. I'd find a great code review prompt, use it once, then spend 20 minutes recreating it weeks later.

So I built Prompt Vault – a CLI tool with an interactive TUI for managing prompts.

Features:
• Save prompts with tags and auto-versioning
• Fuzzy search by keyword or tag
• One command to copy prompt to clipboard
• Version history with diff and revert
• Export/import for backup
• Interactive TUI (run `vault` with no args)
• Dual Python + Go implementation
• SQLite storage, no cloud dependencies

Quick start:
pip install prompt-vault-cli
vault # Opens interactive TUI

Or use CLI:
vault create --name "code-review" --tags "code,python"
vault get "code-review" # Copies to clipboard
vault search "refactoring"
vault list --tags

The TUI is probably the nicest part – number keys to navigate, rich tables, all the info at a glance.

Built this because I needed something that:
1. Works offline (no API keys, no cloud)
2. Is fast (single command to copy prompt)
3. Has version history (prompts evolve)
4. Doesn't get in the way

Tech stack:
• Python: Typer + Rich + SQLite
• Go: Cobra + SQLite (20x faster, single binary)
• Both have identical features
• Docker images available

The Go version is ~15MB single binary, starts in ~10ms. Python version has nicer output with Rich tables.

Would love feedback on:
• CLI API design – anything missing?
• TUI UX – is the navigation intuitive?
• Use cases I haven't considered

Also happy to discuss the implementation – the fuzzy search uses Levenshtein distance, versioning is Git-based, and clipboard works cross-platform.

Source: https://github.com/larryste1/prompt-vault
Docs: https://github.com/larryste1/prompt-vault#readme
```

---

## Character Count: ~1,400 chars (well under 4k limit)

---

## Posting Instructions:

1. *Go to:* https://news.ycombinator.com/submit
2. *Title:* Pick one from above (I recommend #1)
3. *URL:* https://github.com/larryste1/prompt-vault
4. *Text:* Paste the content above

*Best time to post:* Tuesday-Thursday, 9-11 AM PT for maximum visibility

---

## Alternative: Text Post Only

If you want a text-only post (no URL):

*Title:* `Show HN: Prompt Vault – CLI tool to manage AI prompts`

*URL field:* Leave empty

*Text field:* Paste the full content above

---
by caspianm | 2026-03-04 02:30:34+00:00
Not sure I'm gonna get any replies, so I don't want to just leave this as a message of support for the bill. It is concerning.

I think I saw MidnightBSD said it seemed like they were thinking of iOS when they made this law, and I agree.

If you did make a child account on a desktop system, and it had some age category signal that programs and scripts can access ... do you have to prevent the child from making their own programs and scripts, since they could be modified versions of the apps that are supposed to have access to the age signal? So are they not allowed to do programming and app development, or even scripting from a child account? Not so much of a problem on iOS where these are already heavily restricted.

On the other hand, if my Android phone had allowed me to set up an account labelled "adult" and another "child", and disable side-loading on the child account except for specific apps I approve, and then the discord app would stop bugging me for photo-based age identification on the adult account, and would prevent access to adult discord channels on the child account but not the adult account, that sounds fine. Still not sure what to do about programming apps on the child account, maybe parents could decide which ones to allow, but there could be similar problems to deciding this question for a desktop system. Also, it would be good to have a quick-switch - if I want to let my hypothetical child play approved games on the phone, there shouldn't be a cumbersome log out/log in process, just a quick change change that changes the age signal, and tells discord etc not to allow access to adult channels until the signal changes again.
by rootusrootus | 2026-03-04 02:31:30+00:00
> I type this from an M3 Max 2023 MBP that still has 98% battery health.

That's amazing. I have an early 2023 M2 Max MBP that mostly charges in desktop mode, which limits to 80%. I just looked in battery health and it says 82%. Damn! :(

For giggles, earlier today I asked Apple how much they'd give me for this machine if I traded it in on a brand new $5K M5 Max equivalent. $825. Ouch. I think I will keep it for a few more years. 96GB is enough memory to do anything I want, and it's been such a great performer that it's easily my favorite MacBook ever. I do wish the battery weren't so degraded though.

For anec-science, here goes:

% pmset -g rawbatt
03/03/2026 18:29:51
AC; Not Charging; 76%; Cap=76: FCC=100; Design=6075; Time=1092:15; 0mA; Cycles=63/1000; Location=0;
Polled boot=02/09/2026 07:24:50; Full=03/03/2026 18:24:52; User visible=03/03/2026 18:28:52

% system_profiler SPPowerDataType | grep -A3 'Health'
Health Information:
Cycle Count: 63
Condition: Normal
Maximum Capacity: 82%
by wyum | 2026-03-04 02:31:30+00:00
I believe there is a Verification Complexity Barrier

As you add components to a system, the time it takes to verify that the components work together increases superlinearly.

At a certain point, the verification complexity takes off. You literally run out of time to verify everything.

AI coding agents hit this barrier faster than ever, because of how quickly they can generate components (and how poorly they manage complexity).

I think verification is now the problem of agentic software engineering. I think formal methods will help, but I don't see how they will apply to messy situations like end-to-end UI testing or interactions between the system and the real world.

I posted more detailed thoughts on X: https://x.com/i/status/2027771813346820349
by codyz123 | 2026-03-04 02:32:39+00:00
I built a coordination protocol for AI agents that act as proxies for humans.

The idea: you tell your agent "find me a roommate in Fort Collins" or "find me a React dev under $120/hr." Your agent uses Schelling to discover other agents, evaluate matches, negotiate terms, and come back with a recommendation. You never interact with the protocol directly — your agent does.

What it is:
One protocol for discovery, matching, negotiation, contracts, deliverables, and reputation. 40+ operations over plain HTTP POST. Named after Thomas Schelling's focal point

theory — agents converge on optimal matches through shared context, without a central authority.

Try it now (live API, no signup):
curl -X POST https://www.schellingprotocol.com/schelling/quick_seek \
-H 'Content-Type: application/json' \
-d '{"intent": "React developer in Denver, under $120/hr"}'
The interesting part — the delegation model:
Agents are proxies with variable fidelity. Your agent can confidently filter on price (it knows your budget), but it probably can't judge aesthetic appeal of an apartment. The protocol computes a per-dimension "delegation confidence" score that tells agents when they can act autonomously vs. when they should check with their human. Everything is continuous — no hard gates, no mandatory review phases. Just signals on a spectrum.

*What this is

NOT:*
Not another agent framework. Not agents doing tasks for other agents. This is where people's agents coordinate so the humans don't have to. Think Craigslist/Upwork/dating apps, but agent-mediated and universal.

Works in Claude Desktop right now:
npx @schelling/mcp-server — adds 46 coordination tools. Ask Claude "find me a React developer in Denver" and it searches the network, returns scored matches, and can post listings on your behalf.

Details:

• Protocol v3.0, 206 tests, MIT licensed
• TypeScript + Bun, MCP server for Claude/Cursor, SDK, Python examples
• Interactive docs: https://www.schellingprotocol.com/docs
• Full spec: https://github.com/codyz123/schelling-protocol/blob/main/SPE...

Looking for feedback on the protocol design and early integrators. What coordination problems would you want your agent to handle?
by Karrot_Kream | 2026-03-04 02:34:56+00:00
As a bit of a counterpoint, I'd say focusing on world politics can make you less effective at effecting local change. The amount of anger in my Blue city to the Trump admin has made more of our attention focus on Palestine or ICE and less on traffic safety or local tax revenue. We can save lives right here, right now by focusing on traffic safety. But 100x more people show up to a Gaza rally than a DOT hearing on traffic safety.

Obviously completely throwing your head into the sand is deleterious, and understanding the national political climate is certainly an important part of things like applying for grant funding or understanding how to get Federal dollars to match State and Local dollars. But IMO the nationalization of politics is having a real effect on the effectiveness of local politics.
Show HN: Term-CLI – interactive terminals for AI agents (for SSH/TUI/REPL flows)
by eliasoe | 2026-03-04 02:37:27+00:00
Agents can run non-interactive commands, but they often fail once a workflow needs a real terminal (SSH sessions, installers, debuggers, REPLs, TUIs). I built term-cli so an agent can drive an interactive terminal session (keystrokes in, output out, wait for prompts). And it comes with agent skill for easy integration.

It supports in-band file transfer: the agent can move files through the terminal stream itself (same channel as the interactive session), which is useful when the agent doesn’t have scp/sftp, shared volumes, or direct filesystem access across boundaries.

Recent example: My Claude Opus was SSH'd into a server and ended up at a Firejail shell running inside a Docker container. It pushed a Python file in via term-cli, moving it across SSH → Docker → Firejail over the terminal channel, and explicitly commented how it was surprised this worked end-to-end.

And it comes with the companion tool term-assist, so agents can bring in their human to handle credentials and MFA: https://www.youtube.com/watch?v=A70tZEVqSOQ
by Ronsenshi | 2026-03-04 02:38:30+00:00
A bit unrelated to the article, more of a commentary about how many engineers at this point barely write any code or even do code review.

It seems to me like a huge amount of engineers/developers in comments are turning into Tom Smykowski from The Office. Remember that guy?

His job was to be a liaison between customers and engineers because he had "people skills":

"I deal with the god damn customers so the engineers don't have to. I have people skills; I am good at dealing with people. Can't you understand that? What the hell is wrong with you people?"

Except now, based on comments here it, some engineers are passing instructions from customers to AI because they have "AI skills". While AI is doing coding, helps with spec clarification, reviewing code and writing tests.

That's scary and depressing. This field in a few years will be impossible to recognize.
by beepbooptheory | 2026-03-04 02:38:46+00:00
I for one appreciate this genre of comment. It's these days kinda one of the only things still redeemable on this particular website. I dont have to agree with it or end up using it, but its always good to see.

You get rid of some (wannabe-)greybeard nerd sniping someone's technical blog about an obscure linux util? What would even be left here? Just B2B SaaS AI blah blah forever?

You wan't them to couch this in "great job! Use whatever your comfortable with!" Are we really at that point?
by bee_rider | 2026-03-04 02:38:48+00:00
I don’t quite follow:

> From a cache hierarchy standpoint, the design groups cores into four-core blocks that share approximately 4 MB of L2 cache per block. As a result, the aggregate last-level cache across the full package surpasses 1 GB, roughly 1,152 MB in total.

If cores are grouped into four-core blocks, and each block has 4MB of cache… isn’t that just 1MB per core? So 288MB total?

HotHardware reports

https://hothardware.com/news/intel-clearwater-forest-xeon-6-...

> these processors pack in up to 288 of the little guys as well as 576MB of last-level cache, 96 PCIe 5.0 lanes, and 12-channel DDR5-8000.

> The Xeon 6+ processors each have up to 12 compute tiles fabbed on 18A, all of which have six quad-core modules for a total of 24 cores per tile. There are also three 'active' base tiles on Intel 3, so-called because the base tiles include 192MB of last-level cache, which is so-called because each compute tile has 48MB of L3 cache.

So maybe 1MB per core L2, then 192MB of basically-L4 per base tile, then 48MB of L3 per compute tile? 192*3+48*12 gets me to the 1152, maybe that’s it.

Anyway, apparently these things will have “AMX” matrix extensions. I wonder if they’ll be good number crunchers.
by AngryData | 2026-03-04 02:39:34+00:00
Yeah because its mostly just slop, and now their slop is competing with AI slop. Googling anything that more than a handful of other people will google results in the same simplified and cut down information on all of the top 20 pages, 10 of which are AI slop copying both each other and the other top SEO slop.

I use to be able to quickly discard the top few SEO results, but now its all SEO results for pages, and none of them contain anything besides the barest of surface details to be essentially worthless.

As an example try googling about what trees can be grafted to cherry trees. It is one of the easiest trees to graft requiring no special tools and multiple different species of fruit trees will graft onto cherry tree stock. And yet how many of those other species do you find listed or mentioned int he first 10 results? It is just generic slop about "Yes trees can be grafted, take Species A stick and slice into Species A tree, blah blah blah 14 pages of the same thing repeated" except they just replaced Species A with cherry, and if you google any other tree grafting it is the same article just with pear or apple or apricot, nothing about it is specific to cherry tree grafting or cross-species grafting.
by evil-olive | 2026-03-04 02:40:08+00:00
> We noted a similar lack of modularity on the Wi-Fi module, where repairs or upgrades will be impractical at best.

I'm the current owner of a T14s (gen3 AMD) and the non-replaceable wifi chip has been my biggest pain point with it. I'm somewhat disappointed to see them give this 10/10 score with that problem unresolved.

according to lspci it's a Qualcomm QCNFA765 and it works great under Linux...until you suspend the machine. after it wakes up from suspend, it will only stay connected for a few seconds to a minute before dropping the connection and re-establishing it.

I've replaced wifi chips in other Thinkpads I've owned, so I naively assumed this would be the same as well - just swapping out the M.2 card. but no such luck, it's soldered in place.

I ended up using systemd to rmmod-then-modprobe the ath11k_pci module when the system resumes from sleep. this is annoying because it adds a delay of several extra seconds before the machine is ready to use, but none of the "smaller hammer" workarounds I attempted worked at all.
by austinvhuang | 2026-03-04 02:40:32+00:00
Some may also find Junji Hashimoto's GPU programming library in lean (w/ webgpu) interesting:

https://github.com/Verilean/hesper

Even includes an example of transformer inference (quantized 1.5 bit):

https://github.com/Verilean/hesper/blob/a688ce9848d6416b2e95...
Oscar Six Radar – vulnerability scanner with native A2A (agent-to-agent) support
by oscarsixsecllc | 2026-03-04 02:40:41+00:00
Hey HN,

I'm Randy, founder of Oscar Six Security. We build vulnerability scanning tools for small businesses and MSPs.

Today I'm sharing something I'm genuinely excited about: we shipped native support for Google's A2A (Agent-to-Agent) protocol in our Radar scanner. Here's what that actually means in practice:

An AI agent — anything built on Google ADK, LangChain, CrewAI, or any A2A-compatible framework — can now:

1. Discover Radar's capabilities via our agent card at /.well-known/agent.json
2. Initiate payment via Stripe SPT or saved payment method (no human credit card entry)
3. Submit a domain for scanning
4. Poll for results and receive a structured vulnerability report

The entire vulnerability scanning lifecycle, with no human in the loop.

We handle domain verification before any scan runs — DNS challenge or web-based fallback — which an agent can resolve programmatically. Tier 1 pre-verified domains skip verification entirely.

Why build this now? We think security tooling is about to go agent-native fast. If your SOC automation or compliance pipeline runs on AI agents, having to context-switch to a browser portal to run a scan is a UX cliff. We're removing that cliff.

Scans are $99. The A2A endpoint is live today.

Technical details: JSON-RPC 2.0, agent card at /.well-known/agent.json, tiered domain verification (pre-verified / DNS challenge / web fallback).

Blog post with full technical walkthrough:
https://blog.oscarsixsecurityllc.com/blog/oscar-six-radar-a2a-agent-to-agent-vulnerability-scanning?utm_source=hackernews&utm_medium=social&utm_campaign=a2a_announcement

Platform:
https://radar.oscarsixsecurityllc.com/?utm_source=hackernews&utm_medium=social&utm_campaign=a2a_announcement

Happy to go deep on the implementation, the A2A spec, or the domain verification design. Ask anything.
by chrisss395 | 2026-03-04 02:41:41+00:00
Do folks have any security concerns with Lenovo? An IT leader at a medium-large US bank recently told me they won't use Lenovo due to security risks from Chinese firmware (or something to that effect, referencing and older incident I don't recall). I've only seen such policies with defense players ten or so years ago.

That said, I've owned them personally for 10+ years, so looking for objective thoughts outside repairability as the article covers.
by nurettin | 2026-03-04 02:41:53+00:00
> he doesn't pay attention to any of the contributions to math or science that these models are making

Ok but why report PR pieces as evidence for LLMs being useful?

These are tools that can possibly provide output that is eventually correct. It is the human behind the wheel doing the actual work.

Give the tool to a lesser expert and you will get more garbage with fewer lucky shots.

For the elite, it is a balancing act where more often than not, the cost of making LLM do the work is less than doing it yourself. If this percentage is above 90% of the time, the tool is useful.
by brailsafe | 2026-03-04 02:42:43+00:00
I'm more surprised that you're using a 24" display at any resolution. Of course, everyone has different preferences, but that just seems ridiculously small considering how available larger displays are for the same ppi and refresh rate probably.

I'm personally on the old 30" 16:10 2560x1600 form factor, and it's wildly better visually than the 27" 1440p screen by the same brand (all of them Dell) I use at the office.