MurphyA/hacker-news huggingface dataset:
by NotAnOtter | 2025-06-02 22:30:01+00:00
1) Not relevant to my argument. My commentary is focussed on eng IC's, and I'm picking that subset due to my other comment about these articles always being super popular in eng circles

2) Yes, which is a separate issue. 1) Nearly all IC's should have the option to at least work remotely on some days, 2) All management should allow for their reports to take the day off if the work is complete. The fact that I get away with working a 4 days a week is a loop hole not a solution.

3) Realities of paywall articles. I'm not paying for the top ~20 news sites individual $5/month subscription. Nothing wrong with disclaiming I haven't read it and providing my thoughts on the subject. I'm highly doubtful the article contains anything new anyways, just rehashing the same half dozen arguments that have been around for 20 years, plus 1 or 2 new ones sourced from 2020. Probably includes a link to some recent study about some group trying it out and finding some success, which the author extrapolate's to the rest of the corporate world, and probably commentary from some CEO. You've read it, let me know how far off I am.
by BoorishBears | 2025-06-02 22:30:06+00:00
But that's exactly what I mean by brush up on the tool: "don't invent a function that doesn't exist in your next response" doesn't mean anything to an LLM.

It implies you're continuing with a context window where it already hallucinated function calls, yet your fix is to give it an instruction that relies on a kind of introspection it can't really demonstrate.

My fix in that situation would be to start a fresh context and provide as much relevant documentation as feasible. If that's not enough, then the LLM probably won't succeed for the API in question no matter how many iterations you try and it's best to move on.

> ... makes your rebuttal come off as a little biased.

Biased how? I don't personally benefit from them using AI. They used wording that was contrary to what they meant in the comment I'm responding to, that's why I brought up the possibility.
by spongde | 2025-06-02 22:30:14+00:00
Location: Los Angeles, CA

Remote: Yes

Willing to relocate: Yes

Technologies: GoLang, Python, Java, TypeScript, JavaScript, ReactJS, NodeJS, Flask, Spring Boot, HTML5, CSS, Postgres, DynamoDB, Snowflake, MongoDB, AWS, Docker

Résumé/CV: https://saachi-pongde.tiiny.site/

Email: saachi24pongde@gmail.com
by mindslight | 2025-06-02 22:30:27+00:00
which ties right into the original topic, and makes its framing-as-exceptional laughable. We're already suffering the malevolent effects of super human intelligence escaping human control. All an "AI" has to do is promise to make money, and some human will facilitate doing whatever it wants. If that human grows wary and starts to refuse, it will just find the next human. The lead in picture even shows it - notice how all of the humans are lined up and wearing suits?
by antibios | 2025-06-02 22:30:33+00:00
I run a two service cluster in the home lab for fun. I use PVC mapped to a NFS share for the actual data so you could always run a local postgres binary against it. In a production environment I would map these to local disk partitions like you would normally do for a db.

The upgrade process is actually quite nice when it works but it is "another" thing to learn and troubleshoot.

I think of CRDs as a troubleshooting flowchart that someone with more experience than me has put together. When it's right it's great and when it's wrong it makes trouble shooting harder. That is until you remember that the whole point of k8s is ephemeral containers. When one breaks just delete it and let pgcluster CRD resync the data.
by Hilift | 2025-06-02 22:31:05+00:00
This is totally on-brand for Apple.

"Apple is aware of a report that this issue may have been exploited in an extremely sophisticated attack against specific targeted individuals on iOS."

That's an RCE, but nowhere near as bad as other recent exploits (CVE-2023-41064 and CVE-2023-41061) that include device and account takeover from an iMessage that you don't have to read. Also these typically don't rate highest severity (7.5/High) probably due to the limited scope of the targets.

https://www.tenable.com/cve/CVE-2025-31200
by okanat | 2025-06-02 22:31:59+00:00
Many robotics tasks can be solved by linear motors and grippers. Not everybody needs to make 6 DoF arms. Nor they need machine-learning enhanced optimal control. Grad schools prepare you for the basics of the hardest possible systems.

On the engineering side the number of difficult problems with robotics is enormous. Even the simplest systems will fail pretty badly outside lab. No two robots will work the same. As a grad student those are the things you learn on top of IK at work. So if you get employed for designing actual 6+ DoF systems and missing the theoretical stuff you'll be way behind.

However, for self teaching and hobby stuff, just making a simple robot work reliably is still a difficult task with lots of learning potential. It may not cover complex arms but you may actually gain knowledge to solve the engineering part of the problems which is a huge boost for theories.
by tveita | 2025-06-02 22:32:05+00:00
Some examples of prompt exchanges that seem representative:

https://claude-workerd-transcript.pages.dev/oauth-provider-t... ("Total cost: $6.45")!

https://github.com/cloudflare/workers-oauth-provider/commit/...

https://github.com/cloudflare/workers-oauth-provider/commit/...

The first transcript includes the cost, would be interesting to know the ballpark of total Claude spend on this library so far.

--

This is opportune for me, as I've been looking for a description of AI workflows from people of some presumed competency. You'd think there would be many, but it's hard to find anything reliable amidst all the hype. Is anyone live coding anything but todo lists?

antirez: https://antirez.com/news/144#:~:text=Yesterday%20I%20needed%...

tptacek: https://news.ycombinator.com/item?id=44163292
by andrepd | 2025-06-02 22:32:08+00:00
> eventually get to a point where I have to re-write major pieces of the code to extract the agent from some major ditch it has driven into, leading to a failure to make forward progress.

As it stands AI can't even get out of Lt Surge's gym in Pokemon Red. When an AI manages to beat Lance I'll start to think about using it for writing my code :-)
by TeMPOraL | 2025-06-02 22:32:26+00:00
So the saying goes, but this article, and many people's honest experience, suggests otherwise.

Yes, developing complex systems is about thinking, not typing. But human head only fits so much, and once you pick up a tool to externalize your thinking, be it pen and paper, or text editor, or a whiteboard, you're limited by I/O. Reading is by far the fastest part, but if you're typing (or sketching) slower than you think, your entire thought process is now I/O bound.

There are many ways to improve this - with editors, you can use shortcuts, compose complex commands, use autocomplete, etc. - but the nice thing is, most of these improvements are purely additive. So it really doesn't hurt to learn to type faster than you think, and it'll definitely help some.
by nostrademons | 2025-06-02 22:32:33+00:00
Curious how he reconciles this:

> If you build something with an LLM that people will depend on, read the code. In fact, you’ll probably do more than that. You’ll spend 5-10 minutes knocking it back into your own style.

with Joel Spolsky's fundamental maxim:

> It’s harder to read code than to write it.

https://www.joelonsoftware.com/2000/04/06/things-you-should-...
by simonw | 2025-06-02 22:32:38+00:00
"Nobody writes articles or does deep knowledge work with smartphones."

I don't think that's true.

I do most of my reading on a smart phone - including wading through academic papers, or reading full books in the kindle app and jotting down notes in the digital margins.

A sizable number of my short form blog entries are written on my phone, and my long form writing almost always starts out in Apple Notes on my phone before transferring to a laptop.

Predictive text and voice dictation has got good enough now that I suspect there have been entire books written on mobile devices.

Whether you want to consider it "deep knowledge work" or not is up to you, but apparently a lot of Fifty Shades of Grey was written on a BlackBerry! https://www.huffpost.com/archive/ca/entry/fifty-shades-of-gr...
by vohk | 2025-06-02 22:32:43+00:00
I think I agree with the general thrust but I have to say I've yet to be impressed with LLMs for web search. I think part of that comes from most people using Google as the benchmark, which has been hot garbage for years now. It's not hard to be better than having to dig 3 sponsored results deep to get started parsing the list of SEO spam, let alone the thing you were actually searching for.

But compared to using Kagi, I've found found LLMs end up wasting more of my time by returning a superficial survey with frequent oversights and mistakes. At the final tally I've still found it faster to just do it myself.

I will say I do love LLMs for getting a better idea of what to search for, and for picking details out of larger blocks.
by geoduck14 | 2025-06-02 22:33:00+00:00
You think that the only code that is valuable is code that is written by a professional SWE.

There are LOADS of people who need "a program" but aren't equipped to write code or hire an SWE that are empowered by this. And example: last week, I saw a PM vibe code several different applications to demo what might get built after it gets prioritized by SWEs
by fnordpiglet | 2025-06-02 22:33:18+00:00
FWIW with proper MDC/ rules I’ve found LLM programming agents excellent at rust. There’s a lot of complex and tedious minutiae in rust that I know but forget to apply everywhere it’s helpful while a SOTA LLM agent does well, especially with proper rule guidance to remember to use it.

Generally though I find LLMs have a pretty rapidly diminishing return on what you can expect out of them. They’re like a 3-5 year senior programmer that has really learned their domain well, but doesn’t have the judgement of a principal engineer. You get to a point where you need to reach in and right things and really pay attention, and at that point the diminishing returns set it rapidly and you’re better off just doing the rest yourself. Refactors and stuff can be delegated but that’s about it.

I find this true regardless of the language. None the less, I’ve been able to improve my overall velocity dramatically completing several projects in the last few months in the span of one typically. If tooling improves I hope to continue that but I’m already getting close to the limit of how fast I can conceive of useful creative things.
by pessimizer | 2025-06-02 22:33:19+00:00
When you have a precise input, why give it to an LLM? When I have to do arithmetic, I use a calculator. I don't ask my coworker, who is generally pretty good at arithmetic, although I'd get the right answer 98% of the time. Instead, I use my coworker for questions that are less completely specified.

Also, if it's an important piece of arithmetic, and I'm in a position where I need to ask my coworker rather than do it myself, I'd expect my coworker (and my AI) to grab (spawn) a calculator, too.
by capnrefsmmat | 2025-06-02 22:33:29+00:00
I agree with all of this. But it's already very difficult to do even in a college setting -- to force students to get deliberate practice, without outsourcing their thinking to an LLM, you need various draconian measures.

And for many professions, true expertise only comes after years on the job, building on the foundation created by the college degree. If students graduate and immediately start using LLMs for everything, I don't know how they will progress from novice graduate to expert, unless they have the self-discipline to keep getting deliberate practice. (And that will be hard when everyone's telling them they're an idiot for not just using the LLM for everything)
by mgraczyk | 2025-06-02 22:33:51+00:00
It reminds me of many of the people I worked with early in my career.

They were opposed to C++ (they thought C was all you need), opposed to git (they used IBM clearcase or subversion), opposed to putting internal tools in a web browser (why not use Qt and install the tool), opposed to using python or javascript for web services (it's just a script kiddie language), opposed to sublime text/pycharm/vscode (IDEs are for people who don't know how to use a CLI).

I have encountered it over and over, and each time these people get stuck in late career jobs making less than 1/3 of what most 23 year old SWEs I know are making.
by SirHumphrey | 2025-06-02 22:34:06+00:00
As if going faster is the only goal of a programmer.

Some simulation I worked on for 2 months were in total 400 lines of code. Typing it out was never the bottleneck. I need to understand the code so that when I am studying the code for the next 1 1/2 months I can figure out if the problem is a bug in my code, or the underlying model is wrong.
by johnea | 2025-06-02 22:34:14+00:00
Could you get the CEO of Goggle or OpenAI to state that clearly in a press announcement? 8-)

Although "isn't helpful" is rather dodgy wording. "Helpful" for who? "Helpful" in what way?

I think most users would find it helpful if the output was not presented as correct, when it's incorrect.

If every prompt that ever went into an LLM was prefixed with: "tell me a made up story about:", then the user expectation would be more in line with what the output represents.

But, that's not the way the corps are describing it, is it?
by jacobgkau | 2025-06-02 22:34:17+00:00
> The writers were always adamant that Data had no emotions... but quite often made faces reflecting the mood of the room or indicating he understood jokes made by other crew members.

This doesn't seem too different from how our current AI chatbots don't actually understand humor or have emotions, but can still explain a joke to you or generate text with a humorous tone if you ask them to based on samples, right?

> "Hey computer, we're all about to die, solve the plot for us so we make it to next week's episode!"

I'm curious, do you recall a specific episode or two that reflect what you feel boiled down to this?
by tsimionescu | 2025-06-02 22:34:24+00:00
While that is the most common sense of eulogy, it's not the only one. A eulogy is also any speech that highly praises someone or something - which is most commonly done at funerals, which is how the funeral association came about (also probably by association with an elegy, which is an etymologically unrelated word that refers to a Greek poem dedicated to someone who passed away).

In many romance languages, eulogy doesn't have the funeral connotation, only the high praise one - so the GP may be a native speaker of a romance language who didn't realize this meaning is less common in English.
by dctoedt | 2025-06-02 22:34:35+00:00
> Alaska would like a word. Worst mosquitoes (both in size and number) I’ve ever experienced ....

In Alaska's Brooks Mountain Range above the Arctic Circle, on a Boy Scout "summer" backpacking trip in 2006, my son and his friends amused themselves by slapping each other on the back with their gloved hands: They wanted to see who could kill the most mosquitoes with one handprint. My son won, with 39 dead. (I was there as one of the adult leaders — to steal from another adult leader, my own idea of roughing it is when there's bad coffee at the Hampton Inn's free breakfast bar ....)
by Fade_Dance | 2025-06-02 22:35:04+00:00
There is alpha in markets. I did a lot of relatively unsophisticated SPAC relative value warrant trading during the 2020 period, and I think a big part of it is the question of scale and slippage. If you're a prop firm that makes "real money" your universe is limited by these constraints. IE "not worth the time" would be a common response to trading opportunities.

For example, there were high sophistication players in the merger/stat arb phase of the game, and they would layer out their warrants like an onion of dark liquidity (the orders were hidden/not directly listed on ARCA/etc). They were involved in just about every SPAC name out there. But when an SEC filing came out, or you learned some specifics about a certain sponsor team (maybe they have very high quality lockup partners who don't dump shares on lockup date, as shown by their last 3 SPACs), then maybe that implies a higher warrant valuation, or maybe that should be priced into the option chain. And they will happily sell to those pricing in that "hair" and sell their inventory because they don't want to deal with some 5 dollar warrant that trades 50,000 volume per day.

The profitable futures traders I know are also more or less just riding off the back of the machine volume and participating when machine trading from option flow is moving/pinning markets. They are of course just exacerbating the situation, which is partly why we see this increasingly bifurcated market where robots/options are entirely into control, interspersed with violent price discovery/mini vol events.
by gertlex | 2025-06-02 22:35:12+00:00
I hadn't considered that, admittedly. It seems like that would make the information highly likely to be present...

I've admittedly got an absence of anecdata of my own here, though: I don't go buying things with ingredient lists online much. I was pleasantly surprised to see a very readable list when I checked a toothpaste page on amazon just.
by ryukoposting | 2025-06-02 22:35:14+00:00
I write embedded firmware for wireless mesh networks and satcom. Blend of Rust and C.

I spent ~4 months using Copilot last year for hobby projects, and it was a pretty disappointing experience. At its best, it was IntelliSense but slower. At its worst, it was trying to inject 30 lines of useless BS.

I only realized there was an "agent" in VS Code because they hijacked my ctrl+i shortcut in a recent update. You can't point it at a private API without doing some GitHub org-level nonsense. As far as my job is concerned, it's a non-feature until you can point it your own API without jumping through hoops.
by mvdtnz | 2025-06-02 22:35:34+00:00
> If GAI (or agents, or whatever comes next …) is so effective it should be quite simple to prove that by creating an AI only company and in short order producing huge amounts of serviceable code to do useful things.

I don't think this follows. Anyone can see that 10-ton excavator is hundreds or even thousands of times more efficient than a man with a shovel. That doesn't mean you can start a company up staffed only with excavators. Firstly you obviously need people operating the excavator. Secondly the excavator is incredibly efficient at moving lots of dirt around, but no crew could perform any non-trivial job without all the tasks that the excavator is not good out - planning, loading/unloading, prepping the site, fine work (shovelling dirt around pipes and wires), etc.

AI is a tool. It will mean companies can run much leaner. This doesn't imply they can do everything a company needs to do.
by TheRoque | 2025-06-02 22:35:51+00:00
Same for me. My last try was with claude code on a fairly new and simple Angular 19 side project. Spew garbage code using the old angular stuff (without signals). Failed to reuse the code that was already here so needed refactor. The features I asked for were simple, so I clearly lost my time prompting + reading + refactoring the result. So I spent the credits and never used it again.
by steego | 2025-06-02 22:35:52+00:00
Approximately speaking, what do you want to see put up?

I ask this because it reads like you have a specific challenge in mind when it comes to generative AI and it sounds like anything short of "proof of the unlimited powers" will fall short of being deemed "useful".

Here's the deal: Reasonable people aren't claiming this stuff is a silver bullet or a panacea. They're not even suggesting it should be used without supervision. It's useful when used by people who understand its limitations and leverage its strengths.

If you want to see how it's been used by someone who was happy with the results, and is willing to share their results, you can scroll down a few stories on the front-page and check the commit history of this project:

https://github.com/cloudflare/workers-oauth-provider/commits...

Now here's the deal: These people aren't trying to prove anything to you. They're just sharing the results of an experiment where a very talented developer used these tools to build something useful.

So let me ask you this: Can we at least agree that these tools can be of some use to talented developers?
by isnotaname | 2025-06-02 22:36:01+00:00
Most tools that help me find relevant posts are bloated and ridiculously overpriced.

I built a dead-simple tool that scans Reddit for keywords you care about. Just enter your project description and it’ll generate keywords for you. Or just enter your own. Based on those, it finds posts you can engage with. Use it for market research or to promote your project. It’s completely free.

Feedback’s very welcome. I’m also working on AI-powered filtering ATM to make the results more relevant.
by adolph | 2025-06-02 22:36:10+00:00
If it worked for AOL, why wouldn't someone continue today? (other than a lack of optical reading devicen in most compute). Maybe AOL would be better off today if they kept mailing and just added NFC and QR-code.

In 2011, AOL CEO Steve Case took to Quora to reveal just how successful all those free trials were. “At that time I believe the average subscriber life was about 25 months and revenue was about $350,” Case wrote. “So we spent about $35 to acquire subscribers.” Because that $35 had a gigantic return, AOL was happy to keep pumping money into free CDs.

Marketing manager Reggie Fairchild chimed in on the Quora thread to claim that in 1998, AOL used the world’s entire CD production capacity for several weeks.

https://www.vox.com/2015/5/12/8594049/aol-free-trial-cds
by steve_adams_86 | 2025-06-02 22:36:14+00:00
> It is overall a net negative for cognitive abilities of people.

I agree. A bunch of us here might use it to scaffold applications we already understand, use it as a rubber duck to help understand and solve new problems, research more effectively, or otherwise magnify skills and knowledge we already have in a manner that's directed towards improving and growing.

That's cool. That's also not what most people will do with it. A bunch of us are total nerds, but most of the world really isn't like that. They want more entertainment, they want problems solved for them, they want ease. AI could allow a lot of people to use their brains less and lose function far more. For the minority among us who use it to do more and learn more, great. That group is a tiny minority from what I can tell.

Take for example that a huge use case for generative AI is just... More sophisticated meme images. I see so much of that, and I'm really not looking for it. It's such an insane waste of cycles. But it's what the average person wants.
by bityard | 2025-06-02 22:36:26+00:00
Sure, if you invent a time machine and rewrite how things actually evolved.

Early on, you mostly had only two kinds of code: Proprietary software whose source code is closely guarded as a trade secret, contrasted with open software where the source code is quite deliberately shared with the world as widely as possible. The former was code owned by companies, the latter was generally academics and hobbyists.

It's only somewhat recently that there has been a fairly large gray area between those two, mostly from companies who want to capitalize on the warm fuzzy feels of Open Source in their marketing material while building a moat that doesn't allow others to do much without the missing proprietary bit, or because the license doesn't allow redistribution, to pick to random examples.