MurphyA/hacker-news huggingface dataset:
by II2II | 2026-03-12 23:15:21+00:00
I'm not sure that advice is effective either.

I use an LLM as a learning tool. I'm not interested in it implementing things for me, so I always ignore its seemingly frantic desires to write code by ignoring the request and prompting it along other lines. It will still enthusiastically burst into code.

LLMs do not have emotions, but they seem to be excessively insecure and overly eager to impress.
by lurking_swe | 2026-03-12 23:15:24+00:00
laughed at for having benefits that are similar to the minimum in Europe while _also_ earning 3x? That means I can retire at 50ish if i am even a little bit frugal and financially savvy.

Yes i’ve run the numbers and that’s possible even in a HCOL city. Could probably retire at 45 if i moved to europe (i have dual citizenship). Cheap healthcare and college goes a loooong way…food is cheaper too.

so i’m not sure i understand the joke but that’s fine. I’ll continue enjoying my 4+ weeks off a year and retiring early. Cheers :)
by iwontberude | 2026-03-12 23:15:24+00:00
Yes the entire enterprise and legal precedent is full of shit with intellectual property law being abused left and right. For example, I don’t think Google should have been able to copy the Java API for Kotlin/Android. Java should have just died and everyone would have been better off. By making copyright more weak, free software reaps what it sews.

I love FOSS but I hate that it’s been used to replicate existing code or serve as a way to outsource corporate tech debt. The shadow of profit looms over it all.
by vidarh | 2026-03-12 23:15:32+00:00
> Did you also notice the evolution of average developers over time? I mean, if you take code from a developer ten years ago and compare it with their output now, you can see improvement.

This makes little sense to me. Yes, individual developers gets better. I've seen little to no evidence that the average developer has gotten better.

> However, LLMs might reduce that effort to zero — we just don't know how developers will look after ten years of using LLMs now.

It might reduce that effort to zero from the same people who have always invested the bare minimum of effort to hold down a job. Most of them don't advance today either, and most of them will deliver vastly better results if they lean heavily on LLMs. On the high end, what I see experienced developers do with LLMs involves a whole lot of learning, and will continue to involve a whole lot of learning for many years, just like with any other tool.
by jampekka | 2026-03-12 23:16:22+00:00
> People are just too lazy to put forth even a minimal effort when they believe that there's no payoff to it.

For me just disabling IPv6 has given the biggest payoff. Life is too short to waste time debugging obscure IPv6 problems that still routinely pop up after over 30 years of development.

Ever since OpenVPN silently routed IPv6 over clearnet I've just disabled it whenever I can.
by 369548684892826 | 2026-03-12 23:16:34+00:00
I guess watch out for different line endings in files "\r\n" in Windows, "\n" in Linux. The best thing to do there if possible is use tools in Windows that preserve Linux line endings so you never see "\r\n" in Linux at runtime.

If you're using classes under the System.Drawing namespace then a lot of functionality is missing in Linux, but I don't know much about that. The 3rd party ImageSharp library fills some of the gap and is just generally awesome.

Other than that, I'm sure there's niche things but nothing is coming to mind!
by tabwidth | 2026-03-12 23:16:40+00:00
The worst version of this I've seen is when every layer is like four lines long. You step into a function expecting some logic and it's just calling another function with slightly different args. Do that six times and you forgot what the original call was even trying to do.
Naming helps in theory but in practice half those intermediate functions end up with names like processInner or handleCore because there's nothing meaningful to call them.
by shitloadofbooks | 2026-03-12 23:17:10+00:00
I certainly wouldn't use a compiler that "screws up" 1% of the time; that's the perfect amount where it's extremely common where everything I use it for will have major issues but also so laborious to find amongst the 99% of correct output that I might as well not use it in the first place.

Which is ironically, the exact case those of us who don't find LLM-assisted coding "worth it" make.
by cmrdporcupine | 2026-03-12 23:17:13+00:00
I'm back on Claude Code this month after a month on Codex and it's a serious downgrade.

Opus 4.6 is a jackass. It's got Dunning-Kruger and hallucinates all over the place. I had forgotten about the experience (as in the Gist above) of jamming on the escape key "no no no I never said to do that." But also I don't remember 4.5 being this bad.

But GPT 5.3 and 5.4 is a far more precise and diligent coding experience.
by throwawaytwit9 | 2026-03-12 23:17:15+00:00
It may not work for you but I had years of chronic heartburn. While sick with covid in 2020, I stopped consuming coffee and alcohol. It took a few months and for the long covid symptoms to subside, and then no more heartburn. At all. I felt really dumb that I never connected it to coffee before. I didn’t experience direct symptoms from coffee and I didn’t consume an excess amount. But it definitely was the cause.
by zthrowaway | 2026-03-12 23:17:26+00:00
I was thinking of the 60% global statistic. https://www.sciencedirect.com/topics/immunology-and-microbio...

I had gut dysbiosis for the past couple of years. Went to an alternative/func doctor and she helped me do a program such as this, in a safe manner: https://www.gutprotocols.com/products/full-moon-kit-parasite...

While yes this isn’t scientifically backed, because there’s just no clinical trials yet, doesn’t mean it is bunk. I did a program myself and it fixed all of my problems. My stool inflammatory markers went down drastically, as did my myriad of symptoms that caused me issues every day.

Perhaps I was wrong in strongly recommending people just go do this randomly without any doctor oversight. Whatever. I just wanted to offer my experience because it helped me and can help others. Take it or leave it.
by jacquesm | 2026-03-12 23:17:50+00:00
You're using it as a 'super compiler', effectively a code generator and your .md file is the new abstraction level at which you code.

But there is a price to pay: the code that you generate is not the code that you understand and when things go pear shaped you will find that that deterministic element that made compilers so successful is missing from code generated from specs dumped into an AI. If you one-shot it you will find that the next time you do this your code may come out quite different if it isn't a model that you maintain. It may contain new bugs or revive old ones. It may eliminate chunks of the code and you'll never know and so on.

There is a reason that generated code always had a bit of a smell to it and AI generated code is no different. How much time do you spend on verifying that it actually does what's written on the tin?

Do you write your own tests? Do you let the AI write the tests and the code? Are you familiar with the degree to which AIs can be manipulated to do stuff that you thought they weren't supposed to? (A friend of mine just proved this to his boss by bribing an AI with a 'nice batch of pure random data' to put a piece of unreviewed code into production by giving itself the privileges required to do so...)
by kace91 | 2026-03-12 23:17:52+00:00
Lots of mentions of the term mourning... As they say in my country, don't sell the skin until you kill the bear.

All I'm seeing around me is people dropping best practices in a FOMO driven push for speed: let's stop reviews, let's drive 5 agents in parallel, let's not even look at the code!

This is going to blow up.

Only after we pick up the remains we'll find a more sustainable approach for AI usage. I suspect that version will still require crafters.

If we end up in a place where the craft truly is dead, then congratulations, your value probably just dropped to zero. Everyone who's been around startup culture knows the running jokes about those 'I have a great idea, I just need someone to code it' guys. Now you're one, and you'll find how much ideas are worth.
by AlotOfReading | 2026-03-12 23:18:01+00:00
I've had some luck taming prompt introspection by spawning a critic agent that looks at the plan produced by the first agent and vetos it if the plan doesn't match the user's intentions. LLMs are much better at identifying rule violations in a bit of external text than regulating their own output. Same reason why they generate unnecessary comments no matter how many times you tell them not to.
by lich_king | 2026-03-12 23:18:23+00:00
You realize that the reason you need to manage this organizational complexity is largely because the organization is so huge?...

The reality is that you could run LinkedIn with far, far fewer people. You probably need fewer than 100 for core engineering, and likely less than 1,000 overall if you include compliance, sales, and so on - especially since a lot of overseas compliance stuff is outsourced to consulting firms, it's not like you have a team of lawyers in every country in the world.

Before there was so much money in the system, we used to run companies that way. Two decades ago, I worked for a company that had tens of millions of users, maintained its own complex nationwide infra (no AWS back then), and had 400 full-time employees. That made coordination problems a lot easier too. We didn't need ten layers of people and project management because there just wasn't that many of us.
by simoncion | 2026-03-12 23:18:31+00:00
Why would anyone need IPv6 to be incapable of doing NAT?

To answer your question: Who knows? Perhaps you have a shitlord ISP that only provides you with a /128 (such as that one "cloud provider" whose name escapes me). [0] It's a nice tool to have in your toolbox, should you find that you need to use it.

[0] Yes, I'm aware that a "cloud provider" is not strictly an ISP. They are providing your VMs with access to the Internet, so I think the definition fits with only a little stretching-induced damage.
by furyofantares | 2026-03-12 23:18:48+00:00
I agree the idea of just sending "no" to an LLM without any task for it to do is silly. It doesn't need to know that I don't want it to implement it, it's not waiting for an answer.

It's not smart enough to know you would just not respond to it, not even close. It's been trained to do tasks in response to prompts, not to just be like "k, cool", which is probably the cause of this (egregious) error.
by bushido | 2026-03-12 23:19:05+00:00
The "Shall I implement it" behavior can go really really wrong with agent teams.

If you forget to tell a team who the builder is going to be and forget to give them a workflow on how they should proceed, what can often happen is the team members will ask if they can implement it, they will give each other confirmations, and they start editing code over each other.

Hilarious to watch, but also so frustrating.

aside: I love using agent teams, by the way. Extremely powerful if you know how to use them and set up the right guardrails. Complete game changer.
by mcphage | 2026-03-12 23:19:11+00:00
> that is essentially the same as saying "what I choose causally affects what my opponent chooses".

No, it’s the same as saying “what my opponent thinks I will choose causally affects what my opponent chooses”, which is obviously true. Also, “what my opponent thinks I will choose is positively correlated with what I do choose”, unless my opponent isn’t very good.
by skhatter | 2026-03-12 23:19:14+00:00
I've been experimenting with AI agents and multi-step workflows recently and ran into a problem that reminded me a lot of early distributed systems.

Once agents start calling tools, APIs, and other agents in a chain, debugging failures becomes surprisingly hard. A single task can involve multiple steps—LLM calls, tool invocations, retries—and when something breaks it's often difficult to understand exactly what happened or where the failure originated.

In traditional distributed systems we eventually built things like tracing, circuit breakers, retry policies, SLOs, and other reliability primitives to operate systems safely in production.

I'm curious how people building agent systems today are handling this.

Some questions I'm particularly interested in:
- How do you debug agent failures?
- Do you have visibility into multi-agent workflows?
- How do you replay or reproduce failures?

I've been exploring this problem space and built a small prototype to experiment with reliability tooling for agent systems. The link above shows the demo, but I'm mainly interested in learning how others are approaching this problem.
by nozzlegear | 2026-03-12 23:19:49+00:00
I'm not sure what you mean. The first group here?

> Free trade dems, Clintonite think tankers, third-way corporatists, the self-styled "neoliberal" dems, abundance dems, etc.

These are all very much part of the democrat coalition, i.e. the "left" on the US political spectrum. It's not the entire democrat coalition, but they are a large part of it. I'd call them centrist for sure, but certainly not right wing.
by Luka12-dev | 2026-03-12 23:20:16+00:00
Thanks! Happy to share.

Most helpful references:
Intel Software Developer Manuals
for understanding x86 architecture
osdev.org wiki for the basics
(GDT, IDT, memory management)
Reading source code of other hobby
OS projects to understand different
approaches
James Molloy's kernel tutorial
helped me get started

Most memorable challenge:
Getting the window manager working
with proper overlapping windows and
mouse interaction. The z-ordering
and dirty rectangle system took me
a while to get right, windows kept
rendering behind each other or the
mouse would interact with the wrong
window. Debugging graphics issues
without a working debugger in your
own OS is... an experience haha.

Most surprising thing I learned:
How much modern OSes do that we
completely take for granted. Even
something simple like moving a
window smoothly requires double
buffering, proper

careful
memory management. Made me
appreciate every pixel on
my screen.

What kind of OS project are you
planning?
by dboreham | 2026-03-12 23:21:26+00:00
Em-dashes in this article.

What is described here is basically just CIDR plus NAT which is...what we actually have.

At the time IPv6 was being defined (I was there) CIDR was just being introduced and NAT hadn't been deployed widely. If someone had raised their hand and said "I think if we force people to use NAT and push down on the route table size with CIDR, I think it'll be ok" (nobody said that iirc), they would have been rejected because sentiment was heavily against creating a two-level network. After all having uniform addressing was pretty much the reason internet protocols took off.
by pj_mukh | 2026-03-12 23:22:12+00:00
Yea but this feels like when a Waymo ran over a cat, and a Human driver ran over a toddler and both got the same level of coverage in the media (actually the cat got more follow-up coverage). And I'm supposed to believe both issues are equally important.

No. That's gaslighting, and totally misplaced political activation.
by CharlieDigital | 2026-03-12 23:22:12+00:00
We have human reviews on every PR.

Quality and consistency are going up, not down. Partially because the agents follow the guidance much more closely than humans do and there is far less variance. Shortcuts that a human would make ("I'll just write a one-off here"), the agent does not...so long as our rules guide it properly ("Let me find existing patterns in the codebase.").

Part of it is the investment in docs we've made. Part of it is that we were already meticulous about commenting code. It turns out that when the agents stumble on this code randomly, it can read the comments (we can tell because it also updates them in PRs when it makes changes).

We are also delivering the bulk of our team level capabilities via remote MCP over HTTP so we have centralized telemetry via OTEL on tool activation, docs being read by the agents, phantom docs the agent tries to find (we then go and fill in those docs).
by toraway | 2026-03-12 23:22:17+00:00
"Among his accomplishments has been establishing the department’s Real Time Crime Center that leverages technology and data to support officers in responding more effectively to incidents," the city's release said. "Zibolski also prioritized officer wellness initiatives to strengthen mental health resources and resilience within the department. He reinstituted the Traffic Safety Team to focus on roadway safety and proactive enforcement, and ... played an active role in statewide discussions on various issues affecting law enforcement."

From the same article... He spearheaded a push to "leverage technology and data to support officers in responding more effectively to incidents", then that same technology mistakingly ruins a woman's life by passing along a hit to an officer who compared with her FB photos and said "sure, seems right".

The technology seems highly relevant here. Plus, as we've seen in the software world, when a mandate comes from the top to use the shiny new magic AI tools as much as possible, the officer may have felt pressured to make arrests using the new system they paid a bunch of money for instead of second guessing whatever it spits out.
by jmalicki | 2026-03-12 23:22:18+00:00
Meta has 80k employees to run the world's most massive engine of commerce through advertising and matching consumers to products.

They build generative AI tools so people can make ads more easily.

They have some of the most sophisticated tracking out there. They have shadow profiles on nearly everyone. Have you visited a website? You have a shadow profile even if you don't have a Facebook account. They know who your friends are based on who you are near. They know what stores you visit when.

Large fractions of their staff are making imperceptible changes to ads tracking and feed ranking that are making billions of dollars of marginal revenue.

What draws you in as a consumer is a tiny tip of the iceberg of what they actually do.
by api | 2026-03-12 23:22:22+00:00
I'm a bit in the middle. I enjoy the craft but I also seek and enjoy the result.

The thing about AI is that you don't have to use it for everything. Like any other tool you can use it as much as you'd like. Even though I like the craft, I find myself really enjoying the use of AI to do things like boilerplate code and simple tests. I hate crafting verbose grunt work, so I have AI do that. This in turn leaves me more time to do the interesting work.

I also enjoy using AI to audit, look for bugs, brainstorm, and iterate on ideas. When an idea is solid and fleshed out I'll craft the hard and interesting parts and AI-generate the boring parts.
by casey2 | 2026-03-12 23:22:33+00:00
For the last 12 months labs have been
1. check-pointing
2. train til model collapse
3. revert to the checkpoint from 3 months ago
4. People have gotten used to the shitty new model
Antropic said they "don't do any programming by hand" the last 2 years. Antropic's API has 2 nines
by alex43578 | 2026-03-12 23:22:56+00:00
> cutting out menial decisions such as customer service. … Each person in the US hired to do that job would spend their entire paycheck

This person can no longer get a customer service job, but why can’t they get another job? Customer service is hardly career with a huge sunk cost in training and with a non-fungible skill set.

If they go get another job, compared to the base case of economy = customer service, we now have economy = customer service (AI) + new job.
by rudedogg | 2026-03-12 23:22:57+00:00
I think the real divide is over quality and standards.

We all have different thresholds for what is acceptable, and our roles as engineers typically reflect that preference. I can grind on a single piece of code for hours, iterating over and over until I like the way it works, the parameter names, etc.

Other people do not see the value in that whatsoever, and something that works is good enough. We both are valuable in different ways.

Also, theres the pace of advancement of the models. Many people formed their opinions last year, and the landscape has changed a lot. There’s also some effort requires in honing your skill using them. The “default” output is average quality, but with some coaxing higher quality output is easily attained.

I’m happy people are skeptical though, there are a lot of things that do require deep thought, connecting ideas in new ways, etc., and LLMs aren’t good at that in my experience.
by BeParent | 2026-03-12 23:23:04+00:00
Good catches, thank you for the feedback.

1. Domain: You're right, I'm adding a custom
domain this week. The site runs on Supabase
so pixel data is permanently stored in a
real database.

2. Live feed: The initial seed data was
simulated to show activity, but real purchases
are stored in Supabase and appear instantly.
Fair criticism — I'll make this clearer.

Error messages in French: I'm based in Quebec,
Canada — fixing the locale now.
Show HN: Homecastr - AI home price forecasts on a map
by dhardestylewis | 2026-03-12 23:23:39+00:00
I built homecastr.com/app because you can't easily see where home prices are headed, not even on Zillow.

I used an FT-Transformer & Schrödinger Bridge diffusion model, trained on 20+ years of ACS microdata & 8 FRED macro series. This approach beats Zillow's baseline on 1-year held-out error, achieving 8.0% vs Zillow's 8.4%.

Happy to answer questions about the architecture or anything else!
by swisniewski | 2026-03-12 23:24:19+00:00
I use a DGX spark, with Cosmic as my DE, and it's super awesome.

This is a bit of a franekin-distro, as it's ubuntu + nvdia packgages + system 76 packages, but it works pretty well.

I've been using Flatpack chromium, which is ok for most things. It performs a bit better than Firefox does. Having access to official Chrome will be nice though, as it should come with Widevine support. Chromium doesn't support DRM, so some things like Netflix don't work.
by frankc | 2026-03-12 23:24:28+00:00
I think it's more granular than this, though. I also like to "make computer do thing" and have enjoyed using AI. But I also like building systems, optimizing systems. I find AI is a great partner in that. I can churn out prototypes more quickly, iterate on them more quickly etc. That also applies intra-system level. I might have a theory about how a different data structure or caching layer will affect application performance. It's now so much faster to test those kind of theories, and actually building good scaffolding around them to test them scientifically.

Yes, sometimes I can also ask AI to evaluate things at the system level and it often has surprisingly good insights, but that is usually a collaboration where our powers combined comes up with a better solution. I enjoy that process, too.

I do sympathize with the people "in mourning". I feel like this is really about how your identify is tied up in what you do. I have generally identified as a command line wizard. The xkcd of the guy flying in with "perl" very much speaks to me. But AI absolutely crushes at this. It's not that useful a skill anymore. Now I identify more as a local AI expert instead :D
by operatingthetan | 2026-03-12 23:24:29+00:00
>This is going to blow up.

We are way past wringing our hands over agentic engineering. Every startup and all fast moving companies are onboard. They don't hand code anymore. There will not be some code quality crisis that will stop everyone in their tracks. I'm trying to cope with this too, but I don't think the best path is praying for failure.