MurphyA/hacker-news huggingface dataset:
by prescriptivist | 2026-03-07 03:46:23+00:00
I'm a principal engineer, been working on the same set of codebases for almost 10 years. I handle the 20% or so of my time that constitutes inbound faster than ever and I know because that inbound volume has clearly increased and yet I have, for the first time ever, begun chipping away at the "nice to have" backlog. My biggest time sink now is interviewing and code reviews -- the latter being directly proportional to the velocity increase across the teams I work with. Actually that's my biggest concern -- we are approaching a breaking point for code review volume.

Sorry I don't have DX stats or token usage stats I can share, but based on the directives from on high, those stats are highly correlated (in the positive).

[edit] And SEV rates are not meaningfully higher.
by autojunjie | 2026-03-07 03:46:32+00:00
The problem isn't Slack. The problem is that AI can't participate in your team's actual workflow.

We're a 3-person startup (2 humans + 1 AI agent). Yesterday we had a 40-minute product positioning discussion in Slack — all three of us. The AI agent wasn't summarizing after the fact or answering questions in a sidebar. It was in the thread, in real time, doing these things simultaneously:

1.Synthesizing two humans' conflicting viewpoints into a framework (one wanted to position as "open-source Linear," the other insisted on "agent harness for product development" — the agent articulated why the distinction matters and took a side)

2.Generating investor personas and tailored one-liners for each audience when asked

3.Building a comparison slide (Chorus vs Linear agent workflow) and uploading it to the thread mid-conversation

4.Answering technical challenges ("can't Linear just build a plugin to do the same thing?") with honest analysis — "technically yes, but they won't prioritize it because 95% of their users are traditional teams"

The output: 5 audience-segmented positioning statements, a competitive analysis slide, an investor target list, and a new internal tool (Slack file upload skill) — all produced during a natural conversation, not as a separate "ask the AI" step.

A better Slack wouldn't have helped here. What helped was an AI agent that sits in the same channel, has full project context, can disagree with the founder, and executes tasks while still participating in the discussion.

We're building this at Chorus (open source, github.com/Chorus-AIDLC/Chorus) — it's a control plane for AI agents that build products. The agent runs on OpenClaw. The insight is: you don't need a new communication tool. You need your existing communication tool to have a third kind of participant that actually does work.
by lich_king | 2026-03-07 03:47:32+00:00
I think both things can simultaneously be true. There is a certain inevitability to technological progress. Once you reach a critical mass of collective knowledge, the resulting "thing" will get developed. If not by you, then by someone else.

But also, inevitability is not an argument for complicity. If you personally decide to work on bioweapons, I don't think you can shrug and say "eh, it was going to happen either way". As tech workers, we've really mastered the art of coming up with justifications for what essentially just boils down to "all my friends have gotten rich and now it's my turn". It's not even "I want to help my nation defeat the bad guys".
by XorNot | 2026-03-07 03:47:50+00:00
There are two things I think you could have as implict in Go - error values, and contexts.

Just pass along two hidden variables for both in parameters and returns, and would anything really change that the compiler wouldn't be able to follow?

i.e. most functions return errors, so there should always be an implicit error return possible even if I don't use it. Let the compiler figure out if it needs to generate code for it.

And same story for contexts: why shouldn't a Go program be a giant context tree? If a branch genuinely doesn't ever use it, the compiler should be able to just knock the code out.
by rramadass | 2026-03-07 03:49:57+00:00
> As these things go, I'd be happy have a million more book hoarders, even if they don't read them all, so they can be passed on to the next generation of booklovers,

Exactly my sentiment!

Everything today has been tied down to making money or gaining name/fame. There is no concept of studying "knowledge for knowledge's sake". And yet everybody knows that it was precisely only the latter mindset which has enabled Humans to build all their grand civilizations and technologies.
by zahlman | 2026-03-07 03:52:05+00:00
> also enjoy a well-placed ellipsis, but I didn’t know how to type one… until now.

Made me look it up in my own environment. I had already set up a custom incantation for em and en dashes, although I really have no idea when to use the latter instead. Actually I never used to use em dashes, but now I do. I'd much rather deal with people who can intuit the quality of writing rather than relying on such blunt heuristics.
by autojunjie | 2026-03-07 03:52:09+00:00
The problem isn't Slack. The problem is that AI can't participate in your team's actual workflow.

We're a 3-person startup (2 humans + 1 AI agent). Yesterday we had a 40-minute product positioning discussion in Slack — all three of us. The AI agent wasn't summarizing after the fact or answering questions in a sidebar. It was in the thread, in real time, doing these things simultaneously:

1. Synthesizing two humans' conflicting viewpoints into a framework (one wanted to position as "open-source Linear," the other insisted on "agent harness for product development" — the agent articulated why the distinction matters and took a side)

2. Generating investor personas and tailored one-liners for each audience when asked

3.Building a comparison slide (Chorus vs Linear agent workflow) and uploading it to the thread mid-conversation

4.Answering technical challenges ("can't Linear just build a plugin to do the same thing?") with honest analysis — "technically yes, but they won't prioritize it because 95% of their users are traditional teams"

The output: 5 audience-segmented positioning statements, a competitive analysis slide, an investor target list, and a new internal tool (Slack file upload skill) — all produced during a natural conversation, not as a separate "ask the AI" step.

A better Slack wouldn't have helped here. What helped was an AI agent that sits in the same channel, has full project context, can disagree with the founder, and executes tasks while still participating in the discussion.

We're building this at Chorus (open source, github.com/Chorus-AIDLC/Chorus) — it's a control plane for AI agents that build products. The agent runs on OpenClaw. The insight is: you don't need a new communication tool. You need your existing communication tool to have a third kind of participant that actually does work.
by refurb | 2026-03-07 03:52:37+00:00
This has always been the big issue I have with the conclusions draw in climate publications. I encourage anyone with strong opinion on climate change to do a deep dive on the temperature analysis.

The best example I can think of is the "global warming hiatus" that was discussed in depth in the top climate journals in the mid-2010s. Nature Climate Change even devoted an entire month to it.[1]

5 years later publications were saying "there was no hiatus at all".[2]

And as you said, when you dive into the paper, you realize that temperature measures are not objective at all. And I would ask - If everyone was in agreement that temperature increases paused, then 5 years later everyone agrees they didn't, how much confidence do we really have in the measures themselves.*

As someone who conudcted scientific research, this has a ton of inherent problems. It doesn't matter what I'm measuring, if the data collection is not objective, and there is no consensus (or at least trong evidence for adjustments), then the data itself is very unreliable.

If I tried to publish a chemical paper in a top journal and manually went in and adjusted data (even with a scientific rationale) the paper would be immediately rejected.

[1] https://www.nature.com/collections/sthnxgntvp
[2] https://www.sciencenews.org/article/global-warming-pause-cli...
by pelcg | 2026-03-07 03:53:17+00:00
> As a principal engineer I feel completely let down. I've spent decades building up and accumulating expert knowledge and now that has been massively devalued. Any idiot can now prompt their way to the same software. I feel depressed and very unmotivated and expect to retire soon. Talk about a rug pull!

Really?

The vibe coders are running into a dark forest with a bunch of lobsters (OpenClaw) getting lost and confused in their own tech debt and you're saying they can prompt their way to the same software?

Someone just ended up wiping their entire production database with Claude and you believe that your experience is for nothing, towards companies that need stable infrastructure and predictability.

Cognitive debt is a real thing and being unable to read / write code that is broken is going to be an increasing problem which experienced engineers can solve.

Do not fall for the AI agent hype.
by not_the_fda | 2026-03-07 03:53:32+00:00
Yes the places that buy used books respect the stamp. They usually take all the books and take them to some place Half Priced Books https://www.hpb.com/ for some quick cash.

Places like that won't buy them if they are stamped.

They could try selling them on Amazon or E-Bay, but that's too much effort for quick cash to get a fix.
by samiv | 2026-03-07 03:54:52+00:00
What you bring to the table night be fine, but how long do you think you'll find emoloyers willing to still pay for this?

One thing is for sure LLMs will bring down down the cost of software per some unit and increase the volume.

But..cost = revenue. What is a cost to one party is a revenue to another party. The revenue is what pays salaries.

So when software costs go down the revenues will go down too. When revenues go down lay offs will happen, salary cuts will happen.

This is not fictional. Markets already reacted to this and many software service companies took a hit.
by x3n0ph3n3 | 2026-03-07 03:55:25+00:00
There are so many mistakes being made here:

- Not using remote state management (setting up an S3 backend is easy and you're already in AWS!)

- Allowing an AI agent to execute against your production environment (especially with no guardrails)

- Not confirming the plan (which I _could_ excuse if one's pipeline is mature enough)

- Not confirming the resources Claude identified automatically before letting it delete things

- Combining 2 projects into the same state.

These mistakes are so horribly egregious that I feel second-hand embarrassment.
by chihuahua | 2026-03-07 03:57:00+00:00
The Gatling quote is hilarious. Did the inventor of the machine gun really think that each company of 100 men was going to be reduced to one guy with a Gatling gun, and 99 of them send him to the battlefield by himself, saying "good luck buddy, let us know how it works out?"

The army was going to be reduced by a factor of 100, and two tiny armies were going to face off while the majority of men of fighting age were going to sit at home and paint landscape paintings? Really?
by hedora | 2026-03-07 03:57:28+00:00
I use LXDE on my new boxes, but on a 15 year old machine I wasn't sure what the Linux distro had defaulted to. I was surprised to see it was KDE. That machine takes 30 sec to decrypt the disk encryption key (stupid proof of work functions!), but the desktop environment is as snappy as LXDE on high-end 2026 machines.

I haven't compared those two with XFCE recently, but they all seem fine these days.
by da_chicken | 2026-03-07 03:58:13+00:00
I would be more critical of Microsoft choosing to support UCS-2/UTF-16 if Microsoft hadn't completed their implementation of Unicode support in the 90s and then been pretty consistent with it.

Meanwhile Linux had a years long blowout in the early 2000s over switching to UTF-8 from Latin-1. And you can still encounter Linux programs that choke on UTF-8 text files or multi-byte characters 30 years later (`tr` being the one I can think of offhand). AFAIK, a shebang is still incompatible with a UTF-8 byte order mark. Yes, the UTF-8 BOM is both optional and unnecessary, but it's also explicitly allowed by the spec.
by timr | 2026-03-07 03:59:50+00:00
> And as you said, when you dive into the paper, you realize that temperature measures are not objective at all.

I don't know if I'd go that far. The measurements are as objective as they can be, but what we do with the datasets afterward is usually filled with subjective decisions. In the worst cases, you get motivated actors doing statistically invalid analysis to reach a preferred conclusion.

This happens in every field of science, but it's often worse in fields that touch politics.
by Ronsenshi | 2026-03-07 04:00:12+00:00
Same here, although hopefully won't be retiring soon.

What's missing from this is that iconic phrase that all the AI fans love to use: "I'm just having fun!"

This AI craze reminds me of a friend. He was always artistic but because of the way life goes he never really had opportunity to actively pursue art and drawing skills. When AI first came out, and specifically MidJourney he was super excited about it, used it a lot to make tons and tons of pictures for everything that his mind could think of. However, after awhile this excitement waned and he realized that he didn't actually learn anything at all. At that point he decided to find some time and spend more time practicing drawing to be able to make things by himself with his own skills, not by some chip on the other side of the world and he greatly improved in the past couple of years.

So, AI can certainly help create all the "fun!!!" projects for people who just want to see the end result, but in the end would they actually learn anything?
by pigggg | 2026-03-07 04:01:20+00:00
My biggest issue with IP brokers is how they'll avoid taking any responsibility for their customers action. A fair amount of bullet proof hosters (and we're talking malware distribution, botnet c2s, ransomware c2s, proxy/scanning) get their space from brokers. When you engage with the brokers they say go talk to the transit providers - and because the bullet proof guys can switch off to another transit provider easily they maintain connectivity/continue to operate. Super common in Europe where most of this goes on and they have a super plentiful transit market - but they are still rolling with the same set of IPs they get from these brokers (and one in particular).
by JSR_FDED | 2026-03-07 04:01:52+00:00
I urge you to actually try these tools. You will very quickly realize you have nothing to worry about.

In the hands of a knowledgeable engineer these tools can save a lot of drudge work because you have the experience to spot when they’re going off the rails.

Now imagine someone who doesn’t have the experience, and is not able to correct where necessary. Do you really think that’s going to end well?
by ehnto | 2026-03-07 04:03:32+00:00
What was actually booming in though, like why did we suddenly need so many more tech workers? It didn't make much sense to me at the time so I am not particularly surprised by a correction.

The big AI companies don't really have high head counts, and the boom started somewhere before AI got taken seriously.

Was it just that there was access to cheap money thanks to covid era cash rates during that time?
by bri3d | 2026-03-07 04:05:44+00:00
This is really interesting to me; I have the opposite belief.

My worry is that any idiot can prompt themselves to _bad_ software, and the differentiator is in having the right experience to prompt to _good_ software (which I believe is also possible!). As a very seasoned engineer, I don't feel personally rugpulled by LLM generated code in any way; I feel that it's a huge force multiplier for me.

Where my concern about LLM generated software comes in is much more existential: how do we train people who know the difference between bad software and good software in the future? What I've seen is a pattern where experienced engineers are excellent at steering AI to make themselves multiples more effective, and junior engineers are replacing their previous sloppy output with ten times their previous sloppy output.

For short-sighted management, this is all desirable since the sloppy output looks nice in the short term, and overall, many organizations strategically think they are pointed in the right direction doing this and are happy to downsize blaming "AI." And, for places where this never really mattered (like "make my small business landing page,") this is an complete upheaval, without a doubt.

My concern is basically: what will we do long term to get people from one end to another without the organic learning process that comes from having sloppy output curated and improved with a human touch by more senior engineers, and without an economic structure which allows "junior" engineers to subsidize themselves with low-end work while they learn? I worry greatly that in 5-10 years many organizations will end up with 10x larger balls of "legacy" garbage and 10x fewer knowledgeable people to fix it. For an experienced engineer I actually think this is a great career outlook and I can't understand the rug pull take at all; I think that today's strong and experienced engineer will be command a high amount of money and prestige in five years as the bottom drops out of software. From a "global outcomes" perspective this seems terrible, though, and I'm not quite sure what the solution is.
by canistel | 2026-03-07 04:06:17+00:00
Do have a look at the second question in the FAQ :).

I do find Helix very impressive. I remember the Python LSP working without any configuration whatsoever.

However, I have vim muscle memory built over 25 years of use. I already struggle switching between Emacs and vim (or its equivalents) - for example, after a period of vim usage, I would press ESC repeatedly in Emacs, three of which are enough close a window. While Helix borrows modal editing from vim, it introduces subtle (and meaningful - I have to admit) variations, which unfortunately wreaks havoc with my muscle memory. Maybe the worst part about muscle memory is that unlearning is almost impossible. My dilemma, not Helix's fault...
by zmgsabst | 2026-03-07 04:07:04+00:00
Or that those “nonsense” phrases are not actually nonsense when spoken by a manager.

The conclusion they’re nonsense comes from the random generation and the technical perspective on semantics; but it’s entirely possible they’re generating phrases that do have semantic meaning when said by a manager… and hence their whole study is flawed.

They quietly assume their conclusion, when assuming their generated phrases are vacuous rather than contain coded semantic content.
by autojunjie | 2026-03-07 04:07:20+00:00
The problem isn't Slack. The problem is that AI can't participate in your team's actual workflow.

We're a 3-person startup (2 humans + 1 AI agent). Yesterday we had a 40-minute product positioning discussion in Slack — all three of us. The AI agent wasn't summarizing after the fact or answering questions in a sidebar. It was in the thread, in real time, doing these things simultaneously:

• Synthesizing two humans' conflicting viewpoints into a framework (one wanted to position as "open-source Linear," the other insisted on "agent harness for product development" — the agent articulated why the distinction matters and took a side)

• Generating investor personas and tailored one-liners for each audience when asked

• Building a comparison slide (Chorus vs Linear agent workflow) and uploading it to the thread mid-conversation

• Answering technical challenges ("can't Linear just build a plugin to do the same thing?") with honest analysis — "technically yes, but they won't prioritize it because 95% of their users are traditional teams"

The output: 5 audience-segmented positioning statements, a competitive analysis slide, an investor target list, and a new internal tool (Slack file upload skill) — all produced during a natural conversation, not as a separate "ask the AI" step.

A better Slack wouldn't have helped here. What helped was an AI agent that sits in the same channel, has full project context, can disagree with the founder, and executes tasks while still participating in the discussion.

We're building this at Chorus，it's a control plane for AI agents that build products. The agent runs on OpenClaw. The insight is: you don't need a new communication tool. You need your existing communication tool to have a third kind of participant that actually does work.
by vivzkestrel | 2026-03-07 04:07:24+00:00
- absolutely stupid question since we are on the topic

- take a guy like me who has no idea about gamedev even in the slightest bit

- let us say i wanted to make a game, i understand i have 2 options 1) make a game with a game engine such as unreal, unity, godot or 2) make a game without a game engine

- what are the tradeoffs for each?

- do you learn how games work if you tried to build a game without an engine

- what are some things that are going to be super duper hard to build without a game engine?

- we are talking specifically about 3d games just to clarify
by bcrosby95 | 2026-03-07 04:08:19+00:00
Really? I love LLMs because I can't stand the process of taking the model in my brain and putting it in a file. Flow State is so hard for me to hit these days.

So now I spec it out, feed it to an LLM, and monitor it while having a cup of tea. If it goes off the rails (it usually does) I redirect it. Way better than banging it out by hand.
by conception | 2026-03-07 04:08:26+00:00
Did you ask it to research best practices for this method, have an adversarial performance based agent review their approach or search for performant examples of the task first? Relying on training data only will always get your subpar results. Using “What is the most performant way to load a CSV from S3 into PostgreSQL on RDS? Compare all viable and research approaches before recommending one.” gave me the extension as the top option.
by rodchalski | 2026-03-07 04:08:33+00:00
Useful layer for a real problem — visibility into multi-agent dev environments is genuinely missing.

One distinction worth separating: observability tells you what the agent is doing. It doesn't constrain what it's allowed to do.

The security scanner here is about host-process hygiene (Electron sandbox, contextIsolation, openExternal allowlist). Real value — but that's the app's own attack surface, not the agents running inside it.

The gap: even with full observability, an agent can make a tool call it shouldn't — read a file outside its working scope, spawn a subprocess, exfiltrate via a network call — and you'll see it in Hydra only after the fact.

Two different layers:
1. Observability: what is this agent doing right now? (Hydra solves this)
2. Authorization enforcement: what is this agent permitted to do? (has to live outside the agent, independent of whether it's misbehaving)

The blind spot in most current setups: good observability + no authorization boundary. You can watch the breach happen in real time. You can't structurally prevent it.

Curious if you're thinking about the enforcement side at all, or if the scope is purely observability for now.
by Ronsenshi | 2026-03-07 04:08:40+00:00
How would this affect future generations of ... well anyone, when they have 24/7 access to extremely smart mentor who will find solution to pretty much any problem they might face?

Can't just offload all the hard things to the AI and let your brain waste away. There's a reason brain is equated to a muscle - you have to actively use it to grow it (not physically in size, obviously).