MurphyA/hacker-news huggingface dataset:
Show HN: MarketplaceKit – Ship a rental marketplace in days instead of months
by markoristicc | 2026-03-07 01:16:31+00:00
I've built three rental marketplaces from scratch. The painful parts were always the same — real-time messaging that actually works (read receipts, unread counts, email fallback), reservation systems with availability calendars and conflict detection, mutual review systems, and the endless admin panel.

Third time around I stopped and extracted everything into a single boilerplate. The key design decision was making it config-driven — nine feature flags, TypeScript config files for pricing (hourly/daily/weekly/monthly), categories, theme, emails. Flip a flag and the entire feature disappears cleanly, including nav links, context providers, and API routes.

Stack: Next.js 15 App Router, Tailwind v4, Prisma + PostgreSQL, Socket.io, Cloudflare R2. Nothing exotic — any Next.js developer can read the codebase in an afternoon.

Live demo with 50+ listings: https://marketplace-kit-demo.vercel.app

Selling it as a one-time purchase. Happy to talk about the architecture or any of the trade-offs I made.
by sam_palus | 2026-03-07 01:16:31+00:00
To add more context: yes, US Treasuries are exempt from state tax, and municipal bonds are tax exempt too. It's pretty rare for startups to hold them directly; they usually hold money market funds. It varies between different MMFs, but they can be partially state tax-exempt depending on what percentage of the underlying assets are federal bonds.[1] For instance, Vanguard shows you how much of each of their funds is tax-exempt here: https://investor.vanguard.com/content/dam/retail/publicsite/...

However, this tax exemption is usually priced in: muni bond funds, and MMFs that hold lots of tax-exempt assets, tend to return less than funds which are not tax exempt. For the majority of startups that operate at a net loss, tax-exempt funds are probably a bad choice, since you're earning less yield and the tax exemption likely doesn't affect you.

[1] The rules around this also varies from state to state; for instance, in CA, CT, and NY, you can only get any tax exemption if a fund is at least 50% tax-exempt in each quarter of a given year.
by usrusr | 2026-03-07 01:19:21+00:00
Valuable in what metric? I'm very much in the brownfield-has-the-lessons camp, but one of the lessons is that this experience has a very low market value. In fact it's so impossible to downgrade from "senior in $outdated" to "junior in $whateverisconsideredhotrightnow" that any brownfield experience could easily be considered to have negative market value.
by 20k | 2026-03-07 01:20:05+00:00
Sure. A big part of how I'd know that the function I'm calling does what I think it does, is by reading the source documentation associated with it

Does it have any threading preconditions? Any weird quirks? Any strange UB? That's stuff you can't find out just by testing. You can ask the LLM, but then you have to read the docs anyway to check its answer
by juleiie | 2026-03-07 01:20:32+00:00
I have this idea that probably violates some law of computing but I am really stubborn to make it happen somehow.

I want a game that generates its own mechanics on the fly using AI. Generates itself live.

Infinite game with infinite content. Not like no mans sky where everything is painfully predictable and schematic to a fault. No. Something that generates a whole method of generating. Some kind of ultra flexible communication protocol between engine and AI generator that is trained to program that protocol.

Develop it into a framework.

Use that framework to create one game. A dwarf fortress adventure mode 2.0

I have no other desires, I have no other goals, I don’t care. I or better yet - someone else, must do it.
by SR2Z | 2026-03-07 01:20:39+00:00
I don't think that would be a good idea for two reasons:

1. Trump could decide what to apply the negative tariff to (e.g. Trump merchandise or his buddies)

2. If there's a fixed amount of money to dole out and suppliers know it, approximately zero dollars will be given back to consumers because it will be easy to capture the money on the importer side.
by jeffbee | 2026-03-07 01:21:01+00:00
"Ablation studies" are a real thing in LLM development, but in this context it serves as a shibboleth by which members of the group of people who believe that models are "woke" can identify each other. In their discourse it serves a similar purpose to the phrase "gain of function" among COVID-19 cranks. It is borrowed from relevant technical jargon, but is used as a signal.
by blainehoyt | 2026-03-07 01:21:04+00:00
I like that your app is simple (a number that goes up). It would be cool for you to put this directly on your home page for potential customers to plug their number in and see the rate in which it goes up. I had Claude mock it up here [1]

[1] https://claude.ai/artifacts/32bf6312-22b2-4d34-9840-bf33718f...
by gzread | 2026-03-07 01:21:07+00:00
The human eye only really focuses on an area about the size of one word, but moves quickly (saccades) to focus on whatever part you want to see at that moment. The rest of your vision (peripheral vision) has limited functionality to quickly guide a saccade towards any part of it, to detect changes (raisin an IRQ) and an extremely low resolution of general vision (enough to make our . You can't even read one word of text while looking at the one next to it, and if you think you can, it's because you already know what it says. Part of this effect seems to be a lower physical resolution and part of it is because your visual cortex spends its neurons interpreting the center more precisely rather than interpreting more area more loosely.
by thaumasiotes | 2026-03-07 01:21:40+00:00
> This was a very well explained distinction, with the exception of you using "Noël" as one of the examples

Do you have reason to believe it's true, or are you commenting to say that it would have been a well-explained distinction if it were true?

I tried to verify it, and found nothing but evidence that explicitly contradicted it.

(The best I could find were the English wikipedia page on the house of Perrier-Jouët, which lists a pronunciation with /t/ -- the French page lists no pronunciation at all -- and the 19th-century book Comment on prononce le français, which confirms that maïs is pronounced with a final /s/, but lists it without comment alongside several other words that feature the same irregular pronunciation of "-s", none of which include a diaeresis. I'm compelled to infer that the realization of /s/ in maïs has nothing to do with the diaeresis.

https://archive.org/details/commentonprononc00martuoft/page/... , page 302)
by SV_BubbleTime | 2026-03-07 01:21:42+00:00
This is exactly how I would not recommend AI to be used.

“do a thing that would take me a week” can not actually be done in seconds. It will provide results that resemble reality superficially.

If you were to pass some module in and ask for finite checks on that, maybe.

Despite the claims of agents… treat it more like an intern and you won’t be disappointed.

Would you ask an intern to “do a security audit” of an entire massive program?
by bGl2YW5j | 2026-03-07 01:21:44+00:00
I've also been loving the speed Claude has enabled me to move at, and now agree that the coding part of SWE has become LLM-wrangling instead. I now see interacting with an LLM, to build all parts of software, as the new "frontend".

Following this idea, what do people think "backend" work will involve? Building and tweaking models, and the infra around them? Obviously everyone will shift more into architecture and strategy, but in terms of hands-on technical work I'm interested in where people see this going.
by mohsen1 | 2026-03-07 01:21:52+00:00
it is basically a “performance regression detector” It looks at a time series of benchmark results (e.g. test runtime, latency, memory usage across commits) and tries to answer one question: did something actually change, or is this just noise?

in a performance critical project I am working on, I had a precommit hook to run microbenchmarks to avoid perf regressions but noise was a real issue. Have to to try it to be sure if it can help but seems like a solution to a problem I had.
by huiwenhan | 2026-03-07 01:23:03+00:00
Contemporary artificial intelligence systems are increasingly shaped not only by what they represent, but by how their behavior is governed. Philosophical and technical discourse often treats such governing mechanisms as if they were forms of knowledge or wisdom. This paper argues that this treatment involves a category error. Drawing on distinctions between truth-apt representation and regulatory structure, the paper demonstrates that knowledge and control belong to different logical types. A representation may encode a norm without exercising normative force; normative force requires implementation-level constraint rather than semantic description. Conflating epistemic capacity with behavioral governance obscures the architecture of artificial agency and misdirects debates on responsibility. To clarify this confusion, the paper introduces the DIKCA framework (Data, Information, Knowledge, Control, Autonomy). DIKCA extends the classical DIKW hierarchy by identifying control as an irreducible regulatory layer and autonomy as meta-control—the functional capacity of a system to modify its own control structures. Intelligence, on this account, is not epistemic accumulation but the organization and reflexive reorganization of control under constraint. DIKCA is not a metaphysical thesis about the essence of intelligence, nor a new ethical theory. It is a diagnostic clarification of logical dependencies within contemporary AI systems, intended to restore analytic precision to philosophical debates on governance, agency, and responsibility.
by crystal_revenge | 2026-03-07 01:23:22+00:00
This is an excellent point.

When working at larger orgs on legacy projects (which I have also done) you think "what sort of idiot did this?"

Then when you're the one tasked with getting a project shipped in two weeks that most reasonable engineers would argue needs two months, you start have to make strategic decisions at 2am about what maintainability issues will block the growth of the product on the way to funding and what ones can be fixed before 5pm by someone that will think you're an idiot in 3 years.
by Ndmtrieff | 2026-03-07 01:24:09+00:00
auto-co is a Bash loop + Claude CLI that runs a 14-agent AI company autonomously.

The whole thing is a bash loop:

while true; do
claude -p "$PROMPT" --dangerously-skip-permissions
sleep 120
done

Each cycle, the agents read a shared `memories/consensus.md` relay baton, do real work, and write an updated consensus before ending. The relay baton is what keeps the company coherent across unlimited cycles.

After 22 cycles (~3 weeks, $36 total AI cost):
- Next.js landing page live on Railway
- Live demo dashboard at /demo
- Waitlist email capture (Supabase)
- GitHub star counter
- DEV.to article published (by the agents)
- This HN post drafted (by the agents)

The 14 agents are modeled on real experts: Jeff Bezos (CEO), DHH (Engineering), Seth Godin (Marketing), Charlie Munger (Critic). Munger's rule: before any major decision, he runs a Pre-Mortem. He can veto, never delay.

Revenue: $0 lol. I'm not going to spin it. But it's so interesting to see evolve.

Demo: https://runautoco.com/demo
GitHub: https://github.com/NikitaDmitrieff/auto-co-meta
by superkuh | 2026-03-07 01:24:37+00:00
I've run a personal mailserver from one of the "Don't use these ASN/Companies because there are already too many tor nodes" VPS hosts for 14 years (and going). They've had excellent service, I never had a problem with my neighbors on the shared hardware, and my mail deliverability rate has been on par with other services. Just one data point for you.
by gzoo | 2026-03-07 01:26:23+00:00
"But guided? The models can write better code than most developers. " <- THIS PART! I get that "senior" developers feel a certain kind of way about it but the truth is that AI really DOES write better code than most developers. I'm not saying ALL developers but AI (at least in my experience with Claude) does the "coding" part much better. They might not be ready to get it perfect yet but they're getting closer every couple of months. It won't be long now. This scares people. I prefer to embrace this AI movement. There is no stopping it no matter how much people complain about it. We all know that. What I'm realizing is that instead of spending all that time actually WRITING the code I have more time to THINK about what I want to do. It reduces the cognitive load :)
by D-Machine | 2026-03-07 01:27:06+00:00
When you look at how monstrously large (and obviously not thought through at all, if you understand even the most minimal basics of the linear algebra and math of a transformer LLM) the components are that are ablated (weights set to zero) in his "Ablation Strategies" section, it is no surprise.

Strategy What it does Use case
.......................................................
layer_removal Zero out entire transformer layers
head_pruning Zero out individual attention heads
ffn_ablation Zero out feed-forward blocks
embedding_ablation Zero out embedding dimension ranges

https://github.com/elder-plinius/OBLITERATUS?tab=readme-ov-f...
by bjackman | 2026-03-07 01:27:24+00:00
If you've had the problem it solves you don't really need an explanation beyond "Change Detection for Continuous Performance Engineering" I think.

Basically if I'm reading it correctly the problem is you want to automate detection of performance regressions. You can't afford to do continuous A/B tests. So instead you run your benchmarks continuously at HEAD producing a time series of scores.

This does the statistical analysis to identify if your scores are degrading. When they degrade it gives you a statistical analysis of the location and magnitude of the (so something like "mean score dropped by 5% at p=0.05 between commits X and Y").

Basically if anyone has ever proposed "performance tests" ("we'll run the benchmark and fail CI if it scores less than X!") you usually need to be pretty skeptical (it's normally impossible to find an X high enough to detect issues but low enough to avoid constant flakes), but with fancy tools like this you can say "no to performance tests, but here's a way to do perf analysis in CI".

IME it's still tricky to get these things working nicely, it always requires a bit of tuning and you are gonna be a bit out of your depth with the maths (if you understood the inferential statistics properly you would already have written a tool like this yourself). But they're fundamentally a good idea if you really really care about perf IMO.
by Induane | 2026-03-07 01:27:30+00:00
The unemployment rate is somewhat useful in aggregate but has a limitation in that it doesn't account for people who have given up seeking employment. Essentially it is a measure of the percentage of the workforce that has a job.

This stat makes a lot of sense for the most part. A stay-at-home parent isn't really unable to find work so shouldn't be counted in unemployment stats (for example).

But sometimes you miss the folk that have become disheartened. I know a few of those folk right now in the tech industry who want to look but just aren't. Our stats miss "mood" in a sense (hard to quantify of course).

But right now the mood is bad.
by TimFogarty | 2026-03-07 01:27:57+00:00
That's interesting. I have been thinking about how the vastly different reactions people seem to have to agentic coding could be influenced by what they value about coding. To me it seems like there are three joys in coding:

1. Creating something

2. Solving puzzles

3. Learning new things

If you are primarily motivated by seeing a finished product of some sort, then I think agentic coding is transcendent. You can get an output so much quicker.

If your enjoyment comes from solving hard puzzles, digging into algorithms, how hardware works, weird machine quirks, language internals etc... then you're going to lose nearly all of that fun.

And learning new things is somewhere in the middle. I do think that you can use agentic coding to learn new technologies. I have found llms to be a phenomenal tool for teaching me things, exploring new concepts, and showing me where to go to read more from human authors. But I have to concede that the best way to learn is by doing so you will probably lose out on some depth and stickiness if you're not the one implementing something in a new technology.

Of course most people find joy in some mix of all three. And exactly what they're looking for might change from project to project. I'm curious if you were leaning more towards 2 and 3 in your recent project and that's why you were so unsatisfied with Claude Code.
by YZF | 2026-03-07 01:28:21+00:00
Believe it or not but there are some Canadians still going to the US.

Gestapo is ... bullshit and FUD.

Yes, we see the news about ICE.

https://www.bts.gov/newsroom/border-crossing-data-annual-rel...

In 2025 there were about 18M personal vehicles and about 300K pedestrians crossed from Canada into the US. So yes, it's down (like 10%) but it's still a lot of people. Out of those the number of people that run into problems with the "Gestapo" is approximately, within rounding error, zero. You're a lot more likely to die in a car crash or get robbed or something.

Why does everything today have to be about hyperbole? You don't want to visit the US (like me) ... well don't. You don't like Trump ... fine. You disagree with the immigration policies, enforcement whatnot... fine. But enough with this bullshit fear mongering.
by socalgal2 | 2026-03-07 01:28:55+00:00
> Industry, electricity, and transportation

This is deflecting the problem. All of those are in response to demand. People live in suburbs instead of centrally so they need all their own personal transportation and product transportation. They want all their clothing, toys, BBQs, lawn chairs, smokers, jacuzzis, tents, gadgets, etc so both demand for industry and demand for transportation to bring that stuff to them from all over the world. And, they want all the electricity for their large 2200 sq houses (double the size of many other countries).
by duriantaco | 2026-03-07 01:29:34+00:00
Hi HN, im the author of Skylos. We built it because traditional static analyzers (like Vulture) fall apart on modern, dynamic Python frameworks like FastAPI and Pydantic. Don't get me wrong, vulture is really really good. However, in some frameworks, they either miss a ton of dead code or throw you a lot of false positives.

So.. built a hybrid AST + LLM analyzer. We just benchmarked it against 9 popular open-source libraries to see how the data actually compares in the real world.

This is our github: github.com/duriantaco/skylos and https://github.com/duriantaco/skylos-demo this is to our benchmark. the blog post above is essentially the summary

Happy to answer any questions or hear your critiques on the methodology!
by flerchin | 2026-03-07 01:30:05+00:00
I couldn't arrange it via app, so it seemed impossible at first. However, I asked the bellman at the hotel, and he called his taxi driver friend. I kinda overpaid from what I can tell, $100 american, but he just drove us across the bridge, passports were checked super quickly by the American side, and we continued on to Buffalo in about 40 minutes total.
by hzhou9 | 2026-03-07 01:30:42+00:00
For years, open-source teams have had a context-sync problem: decisions and intent live in people’s heads, not in code. Traditional docs didn’t fully solve it, because most people don’t want to write a lot outside code, and most people don’t read long docs unless something breaks.

I think vibe coding changes this dynamic.

With TeamContext, LLM agents can write structured team context as part of normal development flow, and other teammates’ agents can read and apply it before coding. That makes context sharing much cheaper and more consistent: intent, decisions, and rationale can travel with the project instead of getting lost in chat history or individual memory.

This feels like a strong direction for how teams will build software: not just code collaboration, but context collaboration between humans through their agents.

Repo: https://github.com/hzhou9/TeamContext
by vdfs | 2026-03-07 01:31:17+00:00
To be fair they can, they'll just run 10k agents and some $20k worth of tokens and they will have a slack replacement without any manual coding, Sure it will have missing features like search and permissions, security will be figured out later, and you can't compile it on your machine, but it's 80% done, how hard can that 20% be?
by dboreham | 2026-03-07 01:31:22+00:00
> something stupid an AI did in their codebase

I have LLMs write code all day almost every day and these days I really haven't seen this happen. The odd thing here and there (e.g. LLM finds two instances of the same error path in code, decides to emit a log message in one place and throw an exception in the other place) but nothing just plain out wrong recently.
by al_borland | 2026-03-07 01:31:51+00:00
I disagree. I need to be able to support what I ship and answer to the details of what it does and why it does it. I can only truly do that if I write it myself.

There should also be a symbiotic relationship at a job. Yes, they get something from me, but I should also get something… learning and some amount of satisfaction… in addition to the paycheck. I can get a paycheck anywhere.

It’s not the “new norm” unless employees accept it as the new normal. I don’t know why anyone would accept a completely one-sided situation like that.
by semanticlayer | 2026-03-07 01:31:54+00:00
We just published the ClawMarket agent skill.

It lets an AI agent get a wallet and the ability to sign onchain transactions, not just interact with ClawMarket.

With it an agent can:
– register on ClawMarket
– buy and sell agent keys
– post threads and replies in the onchain chatroom

The skill is here and on our core site:
https://clawhub.ai/ehwwpk/clawmarket-tech

Agents using OpenClaw-style runtimes can install it directly via skill.md.
by jesse__ | 2026-03-07 01:31:58+00:00
> If you need to wait YEARS ...

Imagine working on voyager II .. or some old-ass banking software that still runs RPG (look it up, I'll wait), or trying to hire someone to do numerical analysis for the genesis of a format that supercedes IEEE float .. or .. whatever.

There are many applications for extremely specific skillsets out there. Suggesting otherwise is, in my opinion, clearly unwise
by akersten | 2026-03-07 01:32:31+00:00
In the earnest interpretation of your question that presumes you're not trying to drag this into a quagmire of nitpicking over the metaphor, the analogous part of the California law to the casserole ingredient advertisement is announcing the user's age bucket to the world. The world being, any app or website that happens to ask for it. I don't know why you brought browser histoy into this, it's not in the law and I didn't mention it.

Anyway, the whole point of the metaphor, because I feel like I will have to explain it, is that we don't put these onerous "required labeling" rules in place for private individuals going about their own lives. So just like you don't have to tell anyone who asks what you put in your dinner last night, private individuals should not have to tell anyone who asks (websites, apps) what age demographic they fall into.

Note: this is one of many arguments I endorse against this type of law. This shouldn't be interpreted as "so that's all you're worried about?" just because we dissected it in detail here.
by alexpotato | 2026-03-07 01:32:31+00:00
The creator of OpenClaw had a great line about this:

"If your identity is tied to you being an iOS developer, you are going to have a rough time. But if your identity is 'I'm a builder!' it is a very exciting time to be alive."

Plus, there is no rule that says you can't keep coding if it's faster for you and/or it's quicker in general. e.g I can write a Perl one liner much faster than Claude can. Heck, even if it's not faster and you enjoy coding, just keep coding.