MurphyA/hacker-news huggingface dataset:
by marxism | 2025-06-02 22:36:28+00:00
I think we're talking past each other. There's always been a threshold: above it, code changes are worth the effort; below it, they sit in backlog purgatory. AI tools so far seem to lower implementation costs, moving the threshold down so more backlog items become viable. The "5x productivity" crowd is excited about this expanded scope, while skeptics correctly note the highest value work hasn't fundamentally changed.

I think what's happening is two groups using "productivity" to mean completely different things: "I can implement 5x more code changes" vs "I generate 5x more business value." Both experiences are real, but they're not the same thing.

https://peoplesgrocers.com/en/writing/ai-productivity-parado...
by ryoshoe | 2025-06-02 22:36:30+00:00
>The other day, alone in a city I'd never been to before, I snapped a photo of a bistro's daily specials hand-written on a blackboard in Chinese, copied the text right out of the photo, translated it into English, learned how to pronounce the menu item I wanted, and ordered some dinner.

To be fair apps dedicated apps like Pleco have supported things like this for 6+ years, but the spread of modern language models has made it more accessible
by albertzeyer | 2025-06-02 22:36:32+00:00
I'm not sure what type of model Google uses nowadays for their webinterface. I know that they also actually provide LLM-based translation via their API.

Also the traditional cross-attention-based encoder-decoder translation models support document-level translation, and also with context. And Google definitely has all those models. But I think the Google webinterface has used much weaker models (for whatever reason; maybe inference costs?).

I think DeepL is quite good. For business applications, there is Lilt or AppTek and many others. They can easily set up a model for you that allows you to specify context, or be trained for some specific domain, e.g. medical texts.

I don't really have a good reference for a similar leaderboard for translation models. For translation, the metric to measure the quality is anyway much more problematic than for speech recognition. I think for the best models, only human evaluation is working well now.
Show HN: I Made the v0.dev for Workouts
by jack_hanlon | 2025-06-02 22:36:42+00:00
I built the V0 of Workout Builder's, as a fast, no-code tool to help trainers and fitness enthusiasts visually create structured workout programs. It features an intuitive drag-and-drop interface built with React, allowing users to define weekly schedules, exercises, and rest days. All data is stored and synced using Supabase, enabling real-time updates and easy program management. This version focused on speed, simplicity, and setting the foundation for future AI integrations.
by ChicagoDave | 2025-06-02 22:36:50+00:00
There are many aspects to AI push back.

- all creatives are flat against it because it’s destroying their income streams and outright stealing their intellectual property

- some technical leaders are skeptical because early returns were very bad and they have not updated their investigations to the latest tools and models, which are already significantly ahead of even six months ago

- a tech concern is how do we mentor new developers if they don’t know how to code or develop logic. LLMs are great IF you already know what you’re doing

- talent is deeply concerned that they will be reduced and replaced, going from high paying careers to fast food salaries

We have a lot of work to balance productivity with the benefits to society. “Let them eat cake,” is not going to work this time either.
by amrutha_ | 2025-06-02 22:36:56+00:00
Excel has quietly implemented one of the most elegant incremental build systems in software, a reactive DAG engine that updates just what it needs to. We’re building Preswald, a reactive Python framework for data dashboards, and realized Excel solves many of the same problems. This post breaks down what spreadsheets can teach us about DAG runtimes, reactivity, and incremental computation.
by ewild | 2025-06-02 22:37:36+00:00
i mean i can state that i built a company wihtin the last year where id say 95% of my code involved using an LLM. I am an experienced dev so yes it makes mistakes and it requires my expertise to be sure the code works and to fix subtle bugs; however, i built this company me and 2 others in about 7 months for what wouldve easily taken me 3 years without the aid of LLMs. Is that an indictment of my ability? maybe, but we are doing quite well for ourselves at 3M arr already on only 200k expense.
by lelandbatey | 2025-06-02 22:37:58+00:00
If you read post, the article is mostly agreeing with you. What they're pointing out is not "the AI can do everything you do", it's that "an AI coder can do a lot of the boring typing a lot faster than you, leaving you right at the point of 'real implementation'".

Having something else write a lot of the boring code that you'll need and then you finish up the final touches, that's amazing and a huge accelerator (so they claim).

The claim is not "AI will replace us all", the claim of the parent article is "AI is a big deal and will change how we work, the same way IDEs/copy-paste/autocomplete/online documentation have radically changed our work."
by worldsayshi | 2025-06-02 22:38:08+00:00
This doesn't seem like the first time engineers try to work with something useful that is only partially reliable.

The solution is to play at its strengths and reinforce it with other mediums. You don't build structures with pure concrete. You add rebar. You don't build ships out of only sail and you don't build rail with just iron. You compose materials in a way that makes sense.

LLMs are most useful when the output is immediately verifiable. So let's build frameworks that take that to core. Build everything around verification. And use LLMs for its strengths.
by capnrefsmmat | 2025-06-02 22:38:14+00:00
> Well, if you’re a novice, don’t do that.

I agree, and it sounds like you're getting great results, but they're all going to do it. Ask anyone who grades their homework.

Heck, it's even common among expert users. Here's a study that interviewed scientists who use LLMs to assist with tasks in their research: https://doi.org/10.1145/3706598.3713668

Only a few interviewees said they read the code through to verify it does what they intend. The most common strategy was to just run the code and see if it appears to do the right thing, then declare victory. Scientific codebases rarely have unit tests, so this was purely a visual inspection of output, not any kind of verification.
by eqvinox | 2025-06-02 22:38:20+00:00
> but the plagiarism […] Cut me a little slack as I ask you to shove this concern up your ass. No profession has demonstrated more contempt for intellectual property.

Speeding is quite common too, yet if you get caught — especially overdoing it — you'll have a problem.

Also, in this case, presumably everything produced with AI is fair game too? The argument being made here isn't even "it's not plagiarism", rather "it's plagiarism but I don't care" — why would anyone else respect such an author's copyrights?
by yupitsme123 | 2025-06-02 22:38:23+00:00
P/E simply isn't a very good ratio other than just for a quick glance. Real analysts look at 5+ years future cash flows (not earnings), risk free interest, risk premium, cost of capital, and other factors.

Differences in any of those factors between companies or between time periods will determine why a company is valued the way it is. Interest rates are way higher now than a few years ago, and still lower than they were in the 90s. Some companies have cool business models that give them an edge, eg. Being able to generate lots of free cash, being able to invest cash at high returns, borrowing at lower rates, looking in customers, or making deals that will assure high revenue growth for the future.

I dont know much about TSLA but I don't think the market sees them as just a car company any more than Amazon was just a retailer.
by theotherpablo | 2025-06-02 22:38:45+00:00
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by NotAnOtter | 2025-06-02 22:38:52+00:00
The author's central argument seems to be that the current state of LLM development is such that 1 Senior + LLM === 1 Senior + 4 juniors

With that as a metric, 1 Senior + 4 juniors cannot build the company with the scope you are describing.

A 50-eng company might have 1 CTO, 5 staff, 15 Seniors, and 29 juniors. So the proposition is you could cut the company in ~half but would still require the most-expensive aspects of running a company.
by w10-1 | 2025-06-02 22:39:02+00:00
> Kinesis Advantage 360 > literally the lightest keycaps you can

I second recommendations for the Kinesis advantage layout and low-force keys.

Aside from direct ergonomic benefit, both the layout and low-force ends up training one to much better habits.

I go ~50% faster and 2X longer on Kinesis Advantage with low force.

Don't wait for inflamed nerves to reduce the ergonomic friction in your life. It makes work much easier.
by deergomoo | 2025-06-02 22:39:19+00:00
Absurd take. Speed is not the issue! Optimising for speed of production is what got us into the utter quagmire that is modern software.

Lack of correctness, lack of understanding and ability to reason about behaviour, and poor design that builds up from commercial pressure to move quickly are the problems we need to be solving. We’re accelerating the rate at which we add levels to a building with utterly rotten foundations.

God damn it, I’m growing to loathe this industry.
by DavidVoid | 2025-06-02 22:39:25+00:00
This just makes me want to get back into learning stenography again. It requires a hell of a lot of practice, but being able to write at 200 WPM (without frantic finger movement) would be quite nice.

Here's a demo/explainer at 200 WPM for example: https://www.youtube.com/watch?v=7jVXrX5TDk4
by tipofthehat | 2025-06-02 22:39:28+00:00
Hi Andrew, I've been trying to get a similar audio language support app hacked together in a podcast player format (I started with Anytime Player) using some of the same principles in your project (transcript generation, chunking, level & obscurity aware timestamped hints and translations).

I really think support for native content is the ideal way to learn for someone like me, especially with listening.

Thanks for posting and good luck.
by jjcm | 2025-06-02 22:39:44+00:00
The most important thing in this article in my mind is in the level setting section - if you are basing your perspective on the state of AI from when you tested it 6mo+ ago, your perspective is likely not based on the current reality.

This is kind of a first though for any kind of technology. The speed of development and change here is unreal. Never before has a couple months of not being on top of things led to you being considered "out of date" on a tool. The problem is that this kind of speed requires not just context, but a cultural shift on the speed of updating that context. Humanity just isn't equipped to handle this rate of change.

Historically in tech, we'd often scoff at the lifecycle of other industries - Airlines haven't changed their software in 20 years?? Preposterous! For the vast majority of us though, we're the other industry now.
by munificent | 2025-06-02 22:39:58+00:00
"Kids today don’t just use agents; they use asynchronous agents. They wake up, free-associate 13 different things for their LLMs to work on, make coffee, fill out a TPS report, drive to the Mars Cheese Castle, and then check their notifications. They’ve got 13 PRs to review. Three get tossed and re-prompted. Five of them get the same feedback a junior dev gets. And five get merged."

I would jump off a bridge before I accepted that as my full-time job.

I've been programming for 20+ years and I've never wanted to move into management. I got into programming because I like programming, not because I like asking others to write code on my behalf and review what they come up with. I've been in a lead role, and I certainly do lots of code review and enjoy helping teammates grow. But the last fucking thing I want to do is delegate all the code writing to someone or something else.

I like writing code. Yes, sometimes writing code is tedious, or frustrating. Sometimes it's yak-shaving. Sometimes it's Googling. Very often, it's debugging. I'm happy to have AI help me with some of that drudgery, but if I ever get to the point that I feel like I spend my entire day in virtual meetings with AI agents, then I'm changing careers.

I get up in the morning to make things, not to watch others make things.

Maybe the kind of software engineering role I love is going to disappear, like stevedores and lamplighters. I will miss it dearly, but at least I guess I got a couple of good decades out of it. If this is what the job turns into, I'll have to find something else to do with my remaining years.
by frank_nitti | 2025-06-02 22:40:08+00:00
What do you mean by “successfully using AI”, do you just mean some employee used it and found it helpful at some stage of their dev process, e.g. in lieu of search engines or existing codegen tooling?

Are there any examples of businesses deploying production-ready, nontrivial code changes without a human spending a comparable (or much greater) amount of time as they’d have needed to with the existing SOTA dev tooling outside of LLMs?

That’s my interpretation of the question at hand. In my experience, LLMs have been very useful for developers who don’t know where to start on a particular task, or need to generate some trivial boilerplate code. But on nearly every occasion of the former, the code/scripts need to be heavily audited and revised by an experienced engineer before it’s ready to deploy for real.
by blibble | 2025-06-02 22:40:35+00:00
> Whats nuts is watching all these people shill for something that we all have used to mediocre results.

this sort of post is the start of next phase in the battle for mindshare

the tools are at the very best mediocre replacements for google, and the people with a vested interest in promoting them know this, so they switch to attacking critics of the approach

> Its kinda sad to watch what I thought was a good company shill for AI.

yeah, I was sad too, then I scrolled up and saw the author. double sadness.
by mrbungie | 2025-06-02 22:40:50+00:00
You know what's nuts? How so many articles about supporting LLMs and against skeptics are so full of fallacies and logical inconsistencies like strawmans, false dichotomies, appeals to emotion and to authority when they have supposedly almost AGI machines to assist them in their writing. They could at least do a "please take a look at my article and see if I'm commiting any logical fallacies" prompt iteration session if they trust these tools so much.

These kinds of articles that heavily support LLM usage in programming seem to FOMO you or at least suggest that "you are using it wrong" in a weak way just to invalidate contrary or conservative opinions out of the discussion. These are pure rhetorics with such an empty discourse.

I use these tools everyday and every hour in strange loops (between at least Cursor, ChatGPT and now Gemini) because I do see some value in them, even if only to simulate a peer or rubber duck to discuss ideas with. They are extremely useful to me due to my ADHD and because they actually support me through my executive disfunction and analysis paralysis even if they produce shitty code.

Yet I'm still an AI skeptic because I've seen enough failure modes in my daily usage. I do not know how to feel when faced with these ideas because I feel out of the false dichotomy (pay for them, use them every day, but won't think them as valuable as the average AI bro). What's funny is that I'm yet to see an article that actually shows LLMs strengths and weaknesses in a serious manner and with actual examples. If you are going to defend a position, do it seriously ffs.
by jacobgkau | 2025-06-02 22:41:01+00:00
> Biased how?

Biased as in I'm pretty sure he didn't write an AI prompt that was the "opposite" of what he wanted.

And generalizing something that "might" happen as something that "will" happen is not actually an "opposite," so calling it that (and then basing your assumption of that person's prompt-writing on that characterization) was a stretch.
by connorb-coder | 2025-06-02 22:41:37+00:00
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by surgical_fire | 2025-06-02 22:41:51+00:00
> The "5x productivity" crowd is excited about this expanded scope, while skeptics correctly note the highest value work hasn't fundamentally changed.

This is true, LLMs can speed up development (some asterisks are required here, but that is generally true).

That said, I've seen, mainly here on HN, so many people hyping it up way beyond this. I've got into arguments here with people claiming it codes at "junior level". Which is an absurd level of bullshit.
by creativenolo | 2025-06-02 22:42:02+00:00
If you’re leaning out, spend two weeks leaning in.

I did, and learned a ton, and likely not going back to how I was before, or how I used it a week ago.

The comments in the article about not reading the agent is good but it’s more than that…

Vibe coding is for non-coders. Yet, you get a feel for the vibe of the AI. With windsurf, you have two or three files open, and working in one. It starts smashing out the multi, interspersed, line edits and you know with a flutter of your eyes, it’s got your vibe and correctly predicted your next ten lines. And for a moment you forgive it for leading you astray when you read what it said.
by Draiken | 2025-06-02 22:42:45+00:00
Companies are inherently evil because they capture the surplus profit from the workers that actually do the work.

I agreed with you that small companies are many times not yet taking this to the extreme and might not be as evil as a mega corporation, but they are still evil by default.

We've definitely normalized this, but being normal doesn't make it good.

I didn't mean to skip over that but since it's the entire base of capitalism so I thought it would be implied.
by anonymars | 2025-06-02 22:43:03+00:00
Maybe, but I often think fellow developers would get more mileage out of Mavis Beacon than the latest flavor of training from Pluralsight/AWS/etc

When effective comments, appropriate variable names, and the like can flow effortlessly from your fingertips, you're more likely to use them. Plus you're not expending your precious mental energy on the mechanics of typing out your ideas.
by tsimionescu | 2025-06-02 22:43:08+00:00
I don't think decimals, especially repeated decimals or other infinite decimal expansions, show up much if at all in any advanced math subjects beyond the study of themselves, of course). Higher math is almost exclusively symbolic. You're more likely to need to learn that "1" is just a notation for the set which contains the empty set then to learn that it's OK to add 0.22... + 0.44... = 0.66...
by Sammi | 2025-06-02 22:43:37+00:00
Ukrainian intel have said that they were seeing Russia prepare for a large aviation bombing attack. So all the best bombers were out on the tarmac getting fueled when they attacked. Maximum pain. Russia didn't just loose a third of their strategic bombers, they lost their best third. The other lesser two thirds will now have to handle the wear and tear going forward. And these planes are already old and torn and require a lot of upkeep.