MurphyA/hacker-news huggingface dataset:
Show HN: AgentUQ, a token-logprob runtime gate for LLM agents
by AntoineN2 | 2026-03-10 15:28:19+00:00
I built this over the weekend because agent systems seem to jump from static guardrails to much heavier judge-style loops, with not much in between.

AgentUQ uses provider logprobs to localize brittle action-bearing spans in an agent step and route actions like continue, retry, verify, ask for confirmation, or block.

The claim is intentionally narrow. It isn’t trying to determine truth. I know uncertainty work can feel theoretical, so I wanted to test whether a smaller operational use of it could be useful in practice.

My bigger belief is that agents need infrastructure that learns from production history (failed runs as well as unconfident ones) instead of just accumulating patches. This is one concrete experiment in that direction.
by Nevermark | 2026-03-10 15:28:25+00:00
> causing major headaches for social media companies attempting to strike a balance for users between legal compliance and privacy.

I can see how the problem is real. (Not sarcasm.)

In technical terms, "balance" is trivial. Put an air/security gap between information collected for age verification and the dossiers they have on users.

In business terms, conflict. They have relentless incentives and pressures to collect, collate and leverage every bit of information that can increase their return on users. Legal gray and black behaviors are rampant and tolerated where protectable. The number of paths to a creative interpretation of "balance" is unbounded. Right up to the c-suite.

It is sad, but self-aware, if they feel awkward trusting themselves with a mandated database full of tasty information they are not supposed to taste.
by dimitrios1 | 2026-03-10 15:28:30+00:00
I distinctly remember from university in one of my more senior classes designing logic gates, chaining together ands, nands, ors, nors, xors, and then working our way up to numerical processors, ALUs, and eventually latches, RAM, and CPUs. The capstone was creating an assembly to control it all.

I remember how thinking how fun it was! I could see unfolded before me how there would be endless ways to configure, reconfigure, optimize, etc.

I know there are a few open source chip efforts, but wondering maybe now is the time to pull the community together and organize more intentionally around that. Maybe open source chipsets won't be as fast as their corporate counterparts, but I think we are definitely at an inflection point now in society where we would need this to maintain freedom.

If anyone is working in that area, I am very interested. I am very green, but still have the old textbooks I could dust off (just don't have the ole college provided mentor graphics -- or I guess siemens now -- design tool anymore).
by ppcvote | 2026-03-10 15:28:44+00:00
Thanks for the insight on prompt drift. You're right — flat prose breaks down fast across iterations. We ended up with a similar solution: a modular spec system where the engine rules (shared across all brands) and theme files (brand-specific: colors, fonts, narrative structure) are separate named documents. The LLM reads both before generating, so roles never bleed across runs. Essentially named blocks, just at the file level instead of XML tags. Will check out flompt — the visual decomposition could be useful for auditing where drift starts.
by ajross | 2026-03-10 15:28:56+00:00
> If you're relying on Python garbage collection to free file descriptors in a loop

Again, that's a proscription for how to write python code for future execution. It's emphatically not a statement for the behavior expected by python code already in production, which tends to rely on this behavior (along with many other such warts and subtleties) implicitly.

And the fact that PyPy doesn't feel the need to clone it (and all the others) explains why PyPy basically doesn't work for existing python code.

I mean, me being an idiot python developer in your eyes does nothing to make the ancient code I received run. It just makes you feel smarter. That's a bad trade.

PyPy needs to be compatible before anyone is going to use it. And it isn't. And so people didn't. And so now it's basically dying as no one wants to work on a project no one uses.
by ppcvote | 2026-03-10 15:29:02+00:00
The domain + company name trick is solid — wish I'd known that earlier. And agreed on parsing page source for tech stack detection, it's surprisingly reliable and the cost is literally zero.

The last_engaged timestamp filter is a good catch. We had a similar issue with our scheduling system where a stuck "busy" state caused the entire pipeline to freeze for over a day. Ended up adding a simple guard: any early exit from a busy state must release the lock first. Same philosophy — one cheap filter prevents a cascade of wasted work.
by cgearhart | 2026-03-10 15:29:17+00:00
Eh. I think my point is that the OP is presented as a “how to” (literally: “how to do important research”) and then it immediately dodges the question by saying “have good taste”. That does not help anyone do important research or improve the quality of the research they do; it’s a cop out.

If I wrote about “how to paint great art” or “how to cook great meals” or “how to build great things” then it would be silly to say “have good taste”—even if that’s part of the answer. It won’t help anyone else to improve in any of those endeavors.
by sidkshatriya | 2026-03-10 15:29:30+00:00
The networking subsystem is probably the place where FreeBSD is most competitive with Linux.

Linux just supports so much more hardware capabilities and fancy ways of doing things (e.g. io_uring, bpf logic in kernel etc.) that an expertly setup and tuned Linux system will probably exceed the networking speed of FreeBSD and provide more features while doing so. I'm not a networking expert by any means but this is what my understanding is.

I use FreeBSD for mostly for taste and the other reasons I outlined in my detailed answer above even though Linux is superior performance wise.
by PurpleRamen | 2026-03-10 15:29:39+00:00
I kinda disagree. Doing something about open questions which are bothering you can be valuable in itself, even if the result of the process is useless in the end. And usually you are also learning some valuable things along the way, or just push your life into a necessary direction. That isn't related to OCD or perfectionism, it's just gaining more control and insight about some aspects of your life.
by techwizrd | 2026-03-10 15:29:46+00:00
I agree. If the real concern is the flood of low-effort slop, unmaintainable patches, accidental code reuse, or licensing violations, then the process should target those directly. The useful work is improving review and triage so those problems get filtered out early. The genie is already out of the bottle with AI tooling, so broad “no AI” rules feel like a reaction to the tool and do not seem especially useful or enforceable.
by chasil | 2026-03-10 15:29:47+00:00
I think that OpenIndiana is where those with general interest in Solaris on x86_64 should go.

https://en.wikipedia.org/wiki/OpenIndiana

SmartOS, for example, is a more specialized application of the scions of OpenSolaris.

Here is a list of other distros that originated from the Illumos efforts after OpenSolaris was terminated:

-DilOS, with Debian package manager (dpkg + apt) and virtualization support, available for x86-64 and SPARC.

-NexentaStor, distribution optimized for virtualization, storage area networks, network-attached storage, and iSCSI or Fibre Channel applications employing the ZFS file system.

-OmniOS Community Edition, takes a minimalist approach suitable for server use.

-OpenIndiana, a distribution that is a continuation and fork in the spirit of the OpenSolaris operating system.

-SmartOS, a distribution for cloud computing with Kernel-based Virtual Machine integration.

-Helios, a distribution powering the Oxide Computer Rack.

-Tribblix, retro style distribution with modern components, available for x86-64 and SPARC.

-v9os, a server-only, IPS-based minimal SPARC distribution.

-XStreamOS, a distribution for infrastructure, cloud, and web development.

https://en.wikipedia.org/wiki/Illumos#Distributions

Edit: From this blog entry, this is suspicious: "the committed support for Oracle Solaris until at least 2037" - does Solaris have a 2038 problem?
by conductr | 2026-03-10 15:30:07+00:00
I think that's the problem, the greatest generation were sort of a moral compass in the US (like it or not, they obv had their own problems - eg. racism). Without them to scold us, it seems we're all too infantile/selfish/greedy and can't even show each other basic respect or do something as simple as stop at a red light. Sure, the internet and social media accelerate it but I think there's also a fundamental loss of parental figures that went out with that generation too.

As a Gen X'er myself I know I grew up respecting the hell out of older people, especially 70+ ages. The past couple of decades as that cohort churns, I can't say the same. It's more of a case by case basis now, many of them seem outright evil in their self-righteousness. They all seem angry and ready to fight in any passing interaction (granted, I live in Texas where most of them are amped on FoxNews, too) and that's not how it used to be. They used to be the friendliest cohort alive, hell when I was maybe 10-14 I even used to volunteer at senior living homes just to hang out and chat with them and can't imagine anyone wanting to do that now.
by lpcvoid | 2026-03-10 15:30:40+00:00
No. You're a human, who went through real life experiences. You learned, developed as a human being. You made mistakes and grew from them. You did what you have to do to advance. What you output has intrinsic value because of all this. I argue that even when you roll your face on your keyboard, the output is more valuable than ten pages of slop output from an LLM, since it's human, with all the history, experience, emotions and character which came before it.
by drivers99 | 2026-03-10 15:30:53+00:00
> Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.

That's definitely me (most recent ones: using engineering notebook techniques but for my own life, and WOOP method), but I recognize that feeling like I've found THE solution when I'm only a few days into it, so I tend to wait and see, or if I tell someone I say "...but ask me again in a week or a month if I'm still doing it." (At least with the engineering notebook, I can still go back and use it to remember what steps and settings I used in KiCad or use WOOP on a new goal at any time. So it's not a total loss.)

I will say one thing that I have stuck with and is pretty useful is a morning checking and an evening checklist. I'm currently using a paper version with the days of March in the columns and the checklists in the rows, and X them off as I go. A slash for the one I'm doing now/next and X when it's done. Leave it blank (or write N) if I choose to skip it. As a back-up, when I can't get around to make a paper version (I'm planning to type in the steps in a spreadsheet so I can just revise and print it each month) I keep the lists in two Google Keep checklists. Those are great because you can reset the checklist each day for reuse, and you can drag to reorder it as you edit it, and you can indent one level to organize it a bit. The disadvantage is I might get distracted by notifications and stuff on my phone.
Show HN: Timelog – C-native, fast, in-memory LSM-style time index for Python
by vld_chk | 2026-03-10 15:31:17+00:00
I built *Timelog*, a Python library for time-indexed workloads with a C17 core and CPython bindings. My goal was to make [t1, t2) as first-class citizens and enable fast workloads under out-of-boundary semantics.

- PyPI package: `timelog-lib`
- Import: `from timelog import Timelog`
- Model: in-memory, LSM-inspired layered index, timeseries queries as first-class citizens
- Query semantics: half-open ranges `[t1, t2)`, snapshot-consistent reads, zero-copy views
- Correctness focus: sequenced range deletes, so insert → delete → reinsert behaves correctly
- Concurrency model: single writer, concurrent readers
- Complexity: ~O(1) insert; O(log N + M) with bounded fanout range queries; ~O(log N) point lookup; O(C) deletion where C is number of overlapping active tombstones
- Benchmarks: in C engnine-only benchmarks Timelog reaches 20M+ inserts/sec; ~1M/sec range scans. Python end-to-end throughput is constraint by Python object creation

Install:
```bash
pip install timelog-lib
# or
uv add timelog-lib
```

Quick example:
```python
from timelog import Timelog

log = Timelog(time_unit="ms")
log.append(1772964242, "A")
del log[1772964244] # log.delete()
log.append(1772964246, [39, "B"])
print(log[1772964246]) # [[39, 'B']]
print(list(log[1772964242:1772964246])) # [(1772964242, 'A')]
```

V1 limitations:
- No in-built flush-to-disk/read-from-disk method (persistent copy)
- `.copy()` and `.copy(deep=True)` not supported yet.

I’d value feedback on API design, semantics clarity, and where this fits vs existing options.
by steego | 2026-03-10 15:31:38+00:00
I think people MOSTLY foresee and anticipate events in OUR training data, which mostly comprises information collected by our senses.

Our training data is a lot more diverse than an LLMs. We also leverage our senses as a carrier for communicating abstract ideas using audio and visual channels that may or may not be grounded in reality. We have TV shows, video games, programming languages and all sorts of rich and interesting things we can engage with that do not reflect our fundamental reality.

Like LLMs, we can hallucinate while we sleep or we can delude ourselves with untethered ideas, but UNLIKE LLMs, we can steer our own learning corpus. We can train ourselves with our own untethered “hallucinations” or we can render them in art and share them with others so they can include it in their training corpus.

Our hallucinations are often just erroneous models of the world. When we render it into something that has aesthetic appeal, we might call it art.

If the hallucination helps us understand some aspect of something, we call it a conjecture or hypothesis.

We live in a rich world filled with rich training data. We don’t magically anticipate events not in our training data, but we’re also not void of creativity (“hallucinations”) either.

Most of us are stochastic parrots most of the time. We’ve only gotten this far because there are so many of us and we’ve been on this earth for many generations.

Most of us are dazzled and instinctively driven to mimic the ideas that a small minority of people “hallucinate”.

There is no shame in mimicking or being a stochastic parrot. These are critical features that helped our ancestors survive.
by bobbiechen | 2026-03-10 15:31:46+00:00
Agreed. When I was working on TEEs/confidential computing, just about everyone agreed that FHE was conceptually attractive (trust the math instead of trusting a hardware vendor) but the overhead of FHE was so insanely high. Think 1000x slowdowns turning your hour-long batch job into something that takes over a month to run instead.
by orbital-decay | 2026-03-10 15:31:56+00:00
I do both in real life, and it's quite clear that what you say is false. Remember that media and online spaces are not a reflection of the reality on the ground. Your own link even discusses one of the reasons for that: dissident media tries to fill the gap avoided by loyal media, of course all that seems similar and manipulative as a result, because they don't write about anything else. Some do understand that, but they operate from abroad - try covering anything mundane about Russia in Latvia, where e.g. Meduza resides, and see how it goes. (Meduza in particular making a lot of stuff up doesn't help). Naturally people grow tired of the media that feels the same. Online spaces are simply suppressed, you can't even give a thumb up without facing 20 years and likely being sent to the meat grinder head-first.
by iamEAP | 2026-03-10 15:31:58+00:00
I moved to Sweden a little over 5 years ago for work after literally making a spreadsheet comparing potential countries.

Sweden wasn't at the top of the list (not even close), but I landed on it because the tech ecosystem seemed unusually strong and because I could secure my (and my family's) place in society (via citizenship) reasonably quickly and predictably, especially compared to other European countries.

Fast forward to today: my partner no longer qualifies. I have an application in, but the government is pushing forward reforms that will see it rejected, just because they plan to apply new rules on all existing applicants (and because I'm stuck in a 3+ year queue).

Turns out I forgot to account for policy stability in my modeling.

How'd you make your decision to move abroad, and has it worked out the way you thought?
by rosasalberto | 2026-03-10 15:32:07+00:00
Stripe builds great products, including identity. But it’s not a specialized identity platform.

A few differences:
- Limited global document coverage (not all IDs or countries supported). https://docs.stripe.com/identity
- No advanced workflow orchestration for complex identity flows
- Missing features like NFC chip verification
- Pricing similar to traditional IDV vendors (expensive)

Stripe Identity works well inside the Stripe ecosystem, but companies that need more flexible, global identity infrastructure usually look for specialized solutions.
by chriswarbo | 2026-03-10 15:32:08+00:00
> I think having a globally shared buffer state, etc. is an antifeature.

As someone who mostly lives in Emacs, I like it. If I'm away from a machine, I can SSH into it and carry on with whatever I was in the middle of.

It's also nice to set emacsclient as EDITOR, so that e.g. running `git commit` will open up a buffer in the existing Emacs session. This is especially useful since I use shell-mode, and it would be confusing/weird to have new Emacs instances popping up when I'm already in an editor! (They open in a "window" (i.e. pane) in the existing "frame" (i.e. window) instead)
by ghostlyInc | 2026-03-10 15:32:11+00:00
That's fair. It probably depends a lot on which corners of engineering culture the training data comes from. In some communities (older Unix culture, Hacker News, ops/debugging discussions) terms like “gremlins”, “yak shaving”, etc. pop up more often as humorous shorthand for messy problems.

But you're right that in day-to-day professional environments they aren't used nearly as much. So it might also just be the model over-generalizing a small stylistic pattern it saw frequently in certain parts of the corpus.
by neya | 2026-03-10 15:32:18+00:00
Here's a better idea: Eradicate requirement of the most personal details of someone to do basic tasks...such as using a web application.

Unless it's a government organisation, no private provider should have the ability to use or process people's identities. It's too much power in one entity's hands. I wish someone would actually solve this instead of yet another ID solutions. We all saw how a literal job seeking app (LinkedIn) abused this.
by datsci_est_2015 | 2026-03-10 15:32:39+00:00
> It's why "no AI allowed" is pointless … If you tell me AI isn't allowed because it writes bad code

I disagree that the rule is pointless, and your last point is a strawman. AI is disallowed because it’s the manner in which the would-be contributors are attempting to contribute to these projects. It’s a proxy rule.

Unfortunately for AI maximalists, code is more than just letters on the screen. There needs to be human understanding, and if you’re not a core contributor who’s proven you’re willing to stick around when shit hits the fan, a +3000 PR is a liability, not an asset.

Maybe there needs to be something like the MMORPG concept of “Dragon Kill Points (DKP)”, where you’re not entitled to loot (contribution) until you’ve proven that you give a shit.
by palmotea | 2026-03-10 15:32:57+00:00
> I don't get how AI fits in here. Software already had massive scale. You aren't replacing a massive data entry team with AI, you're replacing a reliable piece of software written by a human with a reliable (?) piece of software written by AI controlled by a human. There's no increase in scale. Until the reliability issues are fixed a very noticeable decrease in reliability (sure, some software was bad already, but now the good developers are also writing bad code).

> This doesn't seem like a natural step to me at all. The best explanation I can come up with is AI is just being used as an excuse for destructive penny pinching.

I think a big part of the explanation is business leaders aren't actually as smart or thoughtful as they're made out to be. They may have an inaccurate and unrealistic view of LLMs, and making policy and decisions based on that view.

Also business leaders and management are often extremely tolerate and even seem to encourage bad code. The code is a black box that they usually don't even have to use, bugginess and unreliability are often hard to quantify and can be swept under the run. "Saving" $5,000 by not fixing a bug could over time lead to say $10,000 in unquantified costs, but it looks like the "smart" decision on a budget spreadsheet. They only really pay attention once quality is disaster level, or there's some unusually high-profile problem.
by littlestymaar | 2026-03-10 15:33:13+00:00
I can't log-in to linkedin right now, but here's a few things:

- the profile picture is almost certainly (like 99%, certainty) AI-generated (I can even tell you it's ChatGPT-generated, the style is way too characteristic to miss).

- the LinkedIn profile shows prolific activity for the past few days, but almost nothing before that, I'm not sure the profile existed before.

- the github account is just 2 weeks old.

Having a mutual connection doesn't mean much, the interesting question would be who's the mutual and for how long has he be a connection. It's not hard to get to 500 LinkedIn connections on LinkedIn in a few days, you just need to add headhunters and other hiring specialists, they'll never refuse an invitation from a profile that look interesting. They could also have added someone who interacted with their LinkedIn slop submission, making the person more likely to accept the invitation.
by embedding-shape | 2026-03-10 15:34:00+00:00
> Why would the US miss out here?

Personally I don't believe anyone is missing out on anything here.

But rvz earlier claimed that Europe is missing out, because US investors are investing in a European company. That's kind of surprising to me, so asking if they also believe that the US is "missing out" whenever European investors invest in US companies, or if that sentiment only goes one way.
by vladms | 2026-03-10 15:34:05+00:00
> Now your countries are little different from Russia or China or Dubai etc where the old money cabals run everything

If that's what you strongly believe then "western countries" are definitely quite bad at communication and the others quite good at propaganda.

Having lived in a communist country (years ago) and in the west I know from first hand experience that the difference is huge. No need to believe me, see for yourself if you can, alternatively distrust everybody similarly (Rusia, China and the west) - nobody wants your well-being...

Sad part is that probably the poor (everywhere) are the ones suffering the most from the wars and stupid decisions, it does not matter west/east/south/north. Western countries were a richer which means less poor, but it's not like it's a heaven for everybody either.
by usrbinbash | 2026-03-10 15:34:19+00:00
> The submitter is supposed to be the good programmer;

And how will that be assured? Everyone can open a PR or submit a bug.

> The problem is the time.

But not the time spent TYPING.

The problem is the time spent THINKING. And that's a task that LLMs, which are nothing other than statistical models trying to guess the next token, really aren't good at.