MurphyA/hacker-news huggingface dataset:
by garblegarble | 2025-06-03 00:35:15+00:00
I'd be quite interested in a more formal post with a detailed analysis of the effectiveness of the different agent impls, including Claude Code and Jetbrains Junie.

Do you use ChatGPT Code Interpreter because it's better, or is it just something you're more familiar with and you're sticking with it for convenience?

Of course, I don't know how one would structure a suitable test, since doing it sequentially would likely bias the later agents with clearer descriptions & feedback on the tasks. I imagine familiarity with how to prompt each particular model is also a factor.
by j_w | 2025-06-03 00:35:46+00:00
Using map reading skills as a proxy for this is a bit of a strawman. People who use GPS habitually have worse navigational and spatial awareness skills.

https://www.nature.com/articles/s41598-020-62877-0

If you habitually use a calculator for all arithmetic, could the result not be similar? What if you reach to an LLM for all your coding, general research, etc.? These tools may vastly speed up some workflows, but your brain is a muscle.
by kasey_junk | 2025-06-03 00:36:49+00:00
I _think_ I’m the friend being referenced. I’m parallelizing solving different issues. Basically I keep an internal swim lane of a variety of projects and just kick off the next task in the lane I think the agent can handle.

Then I do my “real” work, there’s the stuff I don’t trust the agent with, or is more exploratory or whatever.

As I think of more agent tasks doing that I write them down. When I take a break, say for lunch or winding down at the end of the day I check back in on previous tasks and fire off the new ones.

My flow is very similar to what I did with junior eng except I’m willing to fire off even more trivial tasks at the agent because I don’t care if it sits idle. Similarly if it gets way off base I’m happy to kill the pr more aggressively and start over, what do I care if it wasted its time or if it learns a valuable lesson from the experience?
by presentation | 2025-06-03 00:37:30+00:00
But somehow I was born in the age of GPS and yet I ended up with a strong mental map and navigation skills.

I suspect there will be plenty of people who grow up in the age of LLMs and maybe by reading so much generated code, or just coding things themselves for practice, will not have a hard time learning solid coding skills. It may be easy to generate slop, but it’s also easy to access high quality guidance.
by threeseed | 2025-06-03 00:38:22+00:00
MongoDB as a company is growing 20% y/y and 2B in revenue.

So very far from being a legacy product.

I still use it for new projects because (a) Atlas is genuinely a solid offering with a great price point for startups and (b) schema-less datastores have become more of a necessity as our control of data has decreased e.g. SaaS companies dictate their schema and we need to accomodate.
by toomuchtodo | 2025-06-03 00:38:27+00:00
Title “Salesforce buys Moonhub, a startup building AI tools for hiring”

> Updated 1:13 p.m. Pacific: A Salesforce spokesperson told TechCrunch that Moonhub has not, in fact, been acquired (by the company’s definition of the term). Rather, Moonhub is shutting down, and only some of the company’s team — not the whole team, as MoonHub implied in its post about the news — will be joining Salesforce. The original story follows.
by saghm | 2025-06-03 00:38:30+00:00
Do you find that typos are the biggest barrier to quickly writing code that compiles and runs in a single session? I'm an absolutely _atrocious_ typer (in terms of both speed and accuracy), and yet I still genuinely don't think that actual typing takes within an order of magnitude of the time it takes me to get out a quick prototype compared to debugging.
by calrain | 2025-06-03 00:38:33+00:00
Without making generalisations, I'm trying to leverage LLM as much as possible to see how they can help.

I know there is a lot of hype about LLM's and I'm genuinely interested in the niches that they can fill, and where they definitely shouldn't be involved in the software development process.

I would say I'm an expert level programmer in the small field that I work in, and have set up development teams in the past.

I think that is an advantage to working with integrating LLMs into a dev cycle as I have experience in providing structure with developers, something that LLMs 100% require, without a shred of doubt.

As the capability of LLMs continues to grow, having some framework around where they are 'almost good enough' will help re-evalutate them as they improve.

I'm not trying to prove anything to anyone else, just build a reference point for where we are now.
by jhardy54 | 2025-06-03 00:39:00+00:00
> Think of it this way, if you were going to an event and saw 'buffet available' you'd enquire how to access it. If you saw 'open buffet' you'd know it's just there for the taking.

I think maybe you’re making a different point than you mean to?

- Buffet available = you can view the buffet for free, but you have to pay to use it

- Open buffet = you can use the buffet for free, it’s just there for the taking
by wvenable | 2025-06-03 00:39:45+00:00
I literally pasted these two lines into ChatGPT that were sent to me by one of sysadmin and it told me exactly what I needed to know:

App1: requestedAccessTokenVersion": null App2: requestedAccessTokenVersion": 2

I use it like that all time. In fact, I'm starting to give it less and less context and just toss stuff at it. It's more efficient use of my time.
by CapsAdmin | 2025-06-03 00:39:49+00:00
This is my experience too most of the time. Though sometimes it does work, and sometimes a solution is found that I never thought of. But most of the time I have to change things around to my liking.

However, a counter argument to all this;

Does it matter if the code is messy?

None of this matters to the users and people who only know how to vibe code.
by porridgeraisin | 2025-06-03 00:40:39+00:00
Yes.

I made the mistake of procrastinating on one part of a project thinking "Oh, that is easily LLMable". By God, was I proven wrong. Was quite the rush before the deadline.

On the flip side, I'm happy I don't have to write the code for a matplotlib scatterplot for the 10000th time, it mostly gets the variables in the current scope that I intended to plot. But I've really not had that much success on larger tasks.

The "information retrieval" part of the tech is beautiful though. Hallucinations are avoided only if you provide an information bank in the context in my experience. If it needs to use the search tool itself, it's not as good.

Personally, I haven't seen any improvement from the "RLd on math problems" models onward (I don't care for benchmarks). However, I agree that deepseek-r1-zero was a cool result. Pure RL (plain R1 used a few examples) automatically leading to longer responses.

A lot of the improvements suggested in this thread are related to the infra around LLMs such as tool use. These are much more well organised these days with MCP and what not, enabling you to provide it the aforementioned information bank easily. But all of it is built on top of the same fragile next-token generator we know and love.
by kalkin | 2025-06-03 00:41:06+00:00
If you automatically lump anyone who makes an argument that AI is capable - not even good for the world on net, just useful in some tasks - into "the AI crowd", you will tautologically never hear that argument from anywhere else. But if you've been paying attention to software development discussion online for a few years, you've plausibly heard of tptacek and kentonv, eg, from prior work. If you haven't heard of them in particular, no judgement, but you gotta have someone you can classify as credible independently of their AI take if you want to be able to learn anything at all from other people on the subject.
by dvt | 2025-06-03 00:41:12+00:00
Fully agree with @tptacek here:

> But AI is also incredibly — a word I use advisedly — important. It’s getting the same kind of attention that smart phones got in 2008, and not as much as the Internet got. That seems about right.

However, I just don't think the AI coding part is that interesting or future-thinking. We're seeing so much more progress in semantic search, tool calling, general purpose uses, robotics, I mean, DeepMind just won a Nobel for goodness' sake.

Don't get me wrong, I use ChatGPT to write all kinds of annoying boilerplate, and it's not too bad at recalling weird quirks I don't remember (yes, even for Rust). But hard problems? Real problems? Zero shot. Novel problems? No way.

> But I’ve been first responder on an incident and fed 4o — not o4-mini, 4o — log transcripts, and watched it in seconds spot LVM metadata corruption issues on a host we’ve been complaining about for months.

I'm going to go ahead and press (X) to doubt on this anecdote. You've had an issue for months and the logs were somehow so arcane, so dense, so unparseable, no one spotted these "metadata corruption issues?" I'm not going to accuse anyone of blatant fabrication, but this is very hard to swallow.

Listen, I also think we're on the precipice of re-inventing how we talk to our machines; how we automate tasks; how we find and distribute small nuggets of data. But, imo, coding just ain't it. Donald Knuth calls computer programming an art, and to rob humanity of effecting not just coding—but any art, I'd argue—would be the most cardinal of sins.
by deadbabe | 2025-06-03 00:41:44+00:00
The thing about people making claims like “An LLM did something for me in an hour that would take me days” is that people conveniently leave out what their own skill level is.

I’ve definitely seen humans do stuff in an hour that takes others days to do. In fact, I see it all the time. And sometimes, I know people who have skills to do stuff very quickly but they choose not to because they’d rather procrastinate and not get pressured to pick up even more work.

And some people waste even more time writing stuff from scratch when libraries exist for whatever they’re trying to do, which could get them up and running quickly.

So really I don’t think these bold claims of LLMs being so much faster than humans hit as hard as some people think they do.

And here’s the thing: unless you’re using the time you save to fill yourself up with even more work, you’re not really making productivity gains, you’re just using an LLM to acquire more free time on the company dime.
by xet7 | 2025-06-03 00:42:24+00:00
WeKan https://wekan.github.io has:

1) Per-board webhooks at board right sidebar / Board Settings / Webhooks

2) Global Webhooks at Admin Panel

See right menu of https://github.com/wekan/wekan/wiki , scroll down to webhooks part of menu.

It's possible to send board change events like move card as webhooks, for example to some chat:

https://github.com/wekan/wekan/wiki/Outgoing-Webhook-to-Disc...

Or to NodeRED:

https://github.com/wekan/wekan/issues/2017

or to to some PHP webhook receiver like this, that can use Python code to call WeKan API:

https://github.com/wekan/webhook/blob/main/public/index.php#...

https://github.com/wekan/wekan/blob/main/api.py
by threeseed | 2025-06-03 00:42:26+00:00
a) Big data is more than just the size of the data. It's about how you treat that data i.e. instead of doing expensive and brittle up-front RDBMS modelling you instead dump it all into a data lake and figure out how to handle the data at run-time. And it is still the standard pattern in almost all companies today.

b) Nobody was choosing MongoDB solely for performance. If it was you would choose some in-memory K/V store. It was about it being the only well supported document store that was also fast and scalable.

c) Stripe’s DocDB is an extension of MongoDB Community: https://stripe.com/blog/how-stripes-document-databases-suppo...
by everfrustrated | 2025-06-03 00:43:12+00:00
More email competition is always welcome.

Please do proper folders and not Gmail tags. Tags make writing rules to categorize email impossible as all rules apply independently as AND. IE you can't order rules and say stop matching the remaining now. Makes it impossible to do meaningful filtering.

Fastmail is perfect. Would love to know how you think it could be improved. I'm happy to try a paid search alternative on an impulse (I use kagi and love it) but mail requires huge trust that will take a long while to earn. Especially for a startup that very well might "pivot" and drop the product.
by godelski | 2025-06-03 00:44:40+00:00
> An exponential curve looks locally the same at all points in time

This is true for any curve...

If your curve is continuous, it is locally linear.

There's no use in talking about the curve being locally similar without the context of your window. Without the window you can't differentiate an exponential from a sigmoid from a linear function.

Let's be careful with naive approximations. We don't know which direction things are going and we definitely shouldn't assume "best case scenario"
by cesarb | 2025-06-03 00:45:01+00:00
> Smartphones were financially viable from day 1, though.

Also, they were nothing more than the combination of two things which already existed, and which were already successful and financially viable: cellular phones and PDAs. In fact, I (and plenty of others I presume) already used that combination before smartphones: a PDA and a cellular phone, connected through Bluetooth to share the network connection.
by hiAndrewQuinn | 2025-06-03 00:45:04+00:00
I never said anything about using AI to do your taxes.

I was drawing an analogy. We would probably be better off with a tax system that wasn't so complicated it creates its own specialized workforce. Similarly we would be better off with programming tools that make the task so simple that professional computer programmers feel like a 20th century anachronism. It might not be what we personally want as people who work in the field, but it's for the best.
by Glyptodon | 2025-06-03 00:45:19+00:00
I think he's pretty much right, but it just leaves me managing an AI and hopefully having fewer offshore developers and faster turnaround. So something less than a 50% boost, and kind of variable, but still significant. I don't really think it's world shattering because most software is deeply constrained by business processes (deciding what to build, etc.) that this doesn't help.
by eru | 2025-06-03 00:45:44+00:00
Oh, finitism is perfectly fine by me. I have a lot of sympathy for it!

What is silly is not finitism (or ultrafinitism), but trying to apply concepts like 'regular language' or 'context free language' without modification in such a setting.

I suspect you should be able to suitably alter most of these concepts to make sense in the strictly finite setting. But they are going to become a lot more complicated.

For a similar flavour, you can also check out the differences and similarities between differential equations and difference equations.
by thoughtpeddler | 2025-06-03 00:46:02+00:00
I was recently "pair-vibe-coding" with someone who's much 'smarter' than I am, certainly when it comes to coding, especially Python. He's always been in the LLM skeptic camp, and it was fascinating to see that because of his extensive Python knowledge, his prompting was actually very minimal and weak, one might even say 'lazy'. The output he got from o3 for our given task was therefore really mediocre, and had a few hallucinations (which could've been avoided if he spent a few more seconds or minutes prompting).

I, knowing far less than him, would've had a much more elaborate prompt, and o3 would've proved a lot more competent/capable. Yet with my friend, since he knows so much already, and has such a high bar, he thinks the AI should be able to do a lot more with just a few basic words in a prompt... yet, for that same reason, he (understandably) doubts the inevitable sub-par output.

That's what makes all these debates about "Why are smart people doubting LLMs??" so pointless. The smarter you are, the less help you need, so the less prompting you do, the less context the model has, the less impressive the output, and the more the smart person thinks LLMs suck. With this logic, of course the smartest people are also the biggest skeptics!
by AnthonyMouse | 2025-06-03 00:46:23+00:00
A solid 90% of the problem is that hardware companies think that somebody actually wants their software. Hardware vendors are bad at software. They should not attempt to make software. They should make hardware with the expectation that customers will install whatever software they want on it, and then throw some open source code straight from github on it for the customers who expect it to do something right out of the box.

Their code is bad. It should not be used. They should not even write it to begin with. Just ship the device with existing open source code with the minimum -- and published -- modifications to make it run on your device, and focus on being a hardware company.
by Aurornis | 2025-06-03 00:46:50+00:00
I tried to take this article seriously, but it seems more like HN ragebait than an actual attempt at discussion. The engagement bait appears to be working, given all of the comments.

It’s like half of the arguments are designed as engagement bait with logical consistency being a distant concern:

> If hallucination matters to you, your programming language has let you down.

This doesn’t even make sense. LLMs hallucinate things beyond simple programming language constructs. I commonly deal with allusions to functions or library methods that would be great if they existed, but the LLM made it up on the spot.

The thing is, the author clearly must know this. Anyone who uses LLMs knows this. So why put such a bizarre claim in the article other than as engagement bait to make readers angry?

There are numerous other bizarre claims throughout the article, like waving away the IP rights argument because some programmers pirate TV shows? It’s all so bizarre.

I guess I shouldn’t be surprised to scroll to the bottom and see that the author is a HN comment section veteran, because this entire article feels like it started as a reasonable discussion point and then got twisted into Hacker News engagement bait for the company blog. And it’s working well, judging by the engagement counts.
by 0xbadcafebee | 2025-06-03 00:47:58+00:00
Nice! However some humans can be quite heavy. Depending on the wood species, the board may break, especially if they drop down into it. To strengthen it you can glue+screw a board on-edge to the middle of the bottom of both boards (running front-to-back, not side-to-side). This will significantly increase its bending strength but hardly be noticeable.
by esjeon | 2025-06-03 00:48:09+00:00
It's like the problem of half-full vs half-empty. We see LLM can handle certain tasks, but counter-examples are too far from being rare. So, "LLM can do A" is always followed by "LLM fails at A".

The problem is that LLM never performs consistently. It works when it works. It doesn't when It doesn't. No one knows exactly why, and no one can tell when it's gonna fail. For example, even to this day, GPT sometimes gives me wrong calculations, even when it is instructed to use calculator for that. Who knows why it ignores the instruction, nor why it can't reliably perform the addition of two integers. That really screws up with the automation.

Anyways, I'm really tired of skeptic-skeptics. I hate some people believe "half-full" is genuinely better than "half-empty". I refuse that idea completely. It's more about which context you're in. If you need exactly a cup of water, it's half-empty. If you are lucky to have some water, it's half-full. If you have a clear direction you want to go, you discover a lot of deficiencies. If you're there just enjoying the moment, yeah, you can just keep enjoying the new toy.
by surgical_fire | 2025-06-03 00:48:56+00:00
> Imagine a senior IC staffed with 4 juniors, and they spend 2 hours with each every day. Then the junior is left with 6 hours to think through what they were taught/told. This is very similar to LLM development except instead of context switching 3 times each day, the senior can skip over the 6 hours of independent time the junior required to absorb the changes.

This is not how Juniors work. I don't know what else to say. It is just not true.

I don't give juniors a prompt and let them to implement code for a few hours. They work as any other developer, just generally in features and/or tickets of more limited scope. At least initially. This is not what LLMs do

> But refuting the claim that an LLM is similar in many ways to a junior dev is unsubstantiated

I sometimes get the feeling I talk to people who never worked in a real professional setting.

A LLM can do things that Juniors can't. When I bounce around ideas for implementing a certain feature, when I explore libraries or frameworks I am unfamiliar with, when I ask it to review pieces of code looking for improvements, when I get it to generate boring glue code, scaffolding, unit tests. All those things are helpful, and make LLMs an excellent code assistant in a way that Juniors are not.

But it is completely unable to properly do things without me giving very precise instructions of what it needs to code. The less precise I am, the worse its output. It is very happy to generate completely bullshit code that kinda looks like it does what I need but not really. I constantly need to tweak what it generates, and although it saves my time as it outputs a lot of code in little time, the results are very unreliable to meaningfully act with any sort of independence.

> And there are many things one junior could be helpful with that a different junior would be useless at

Which completely fails to address the point I am making.
by xet7 | 2025-06-03 00:49:25+00:00
WeKan https://wekan.github.io has IFTTT Rules like Trello Butler:

https://github.com/wekan/wekan/wiki/IFTTT

And webhooks:

https://news.ycombinator.com/item?id=44165008

WeKan has these, that Trello does not have: Swimlanes, all code Open Source, On-Premise hosting, etc
by ruchitha_design | 2025-06-03 00:50:38+00:00
Location: Dallas, Texas Remote:Yes Willing to relocate: Yes Technologies:Figma, Voice Flow, WordPress, Qualtrics, Slack, Adobe XD, Trello, Sketch, Miro, HTML5, CSS3 Résumé/CV: https://ruchithagk.com/ Email: ruchithagk99@gmail.com

I'm Ruchitha, a Data-driven Product Designer with over 4 years of experience in B2B, healthcare & finance. My technical background helps to effectively communicate with developers. I enjoy building robust design systems and LLMs.

My specialties include: UX, UI, Flows, wireframes, Mocks, and Prototypes.

I am on my STEM OPT, with H1b lottery picked
by Aurornis | 2025-06-03 00:51:07+00:00
> I like Thomas, but I find his arguments include the same fundamental mistake I see made elsewhere

Some of the arguments in the article are so bizarre that I can’t believe they’re anything other than engagement bait.

Claiming that IP rights shouldn’t matter because some developers pirate TV shows? Blaming LLM hallucinations on the programming language?

I agree with the general sentiment of the article, but it feels like the author decided to go full ragebait/engagement bait mode with the article instead of trying to have a real discussion. It’s weird to see this language on a company blog.

I think he knows that he’s ignoring the more complex and nuanced debates about LLMs because that’s not what the article is about. It’s written in inflammatory style that sets up straw man talking points and then sort of knocks them down while giving weird excuses for why certain arguments should be ignored.
by surgical_fire | 2025-06-03 00:51:22+00:00
> And there are many things one junior could be helpful with that a different junior would be useless at.

That maybbe true, and would be an interesting topic do discuss if people actually spoke in such a way.

"Developers are now more productive in a way that many projects may need less developers to keep up productivity levels" is not that catchy to generate hype however.