MurphyA/hacker-news huggingface dataset:
Show HN: Global Solo – Structural risk diagnostic for cross-border solo founders
by jettfu | 2026-02-12 06:55:50+00:00
Hi HN — I'm Jett, a solo founder operating across US/China/global markets.

I built Global Solo because I kept running into the same problem: as a solo founder with income from multiple countries, an LLC in one jurisdiction, and time spent in another — I had no idea what my actual structural risk looked like. My CPA handled US filing, but nobody was mapping the full picture across entity structure, tax residency, banking, and documentation.

So I built a diagnostic tool that does exactly that.

*What it is:*
A structured risk assessment across 4 dimensions — Money, Entity, Tax, and
Accountability (the META framework). You answer questions about your setup,
and it maps where your structural exposure actually sits. Not advice, not
recommendations — just visibility into what exists.

*What's free:*
- 35+ guides on cross-border structure, tax residency, entity formation,
banking, and compliance
- A 7-question risk screening tool (instant results, no signup):
globalsolo.global/tools/risk-check
- Sample report so you can see what the output looks like:
globalsolo.global/sample-report

*What's paid:*
- Full L1 diagnostic report: $29 (vs. $1,200+ for a CPA to do the same
mapping)
- Deeper tiers at $149 and $349 for structural analysis and judgment layers

*Tech:*
Next.js 16, React 19, Supabase, Stripe. The scoring is deterministic — same
input always produces same output. LLM (Claude/GPT) is used only for
narrative generation in the paid reports, not for risk assessment logic.

I'd love feedback on:
1. Does the free risk check feel useful?
2. Is the sample report convincing enough to pay $29?
3. Any cross-border founders here — does the META framework cover your blind
spots?

Thanks for looking.
by pjmlp | 2026-02-12 06:56:16+00:00
Eventually yes, when incapable becomes a synonymous with finding a job in an AI dominated software factory industry.

Enterprise CMS deployment projects have already dropped amount of assets teams, translators, integration teams, backend devs, replaced by a mix of AI, SaaS and iPaaS tools.

Now the teams are a fraction of the size they used to be like five years ago.

Fear not, there will be always a place for the few ones that can invert a tree, calculate how many golf balls fit into a plane, and are elected to work at the AI dungeons as the new druids.
by thomasfromcdnjs | 2026-02-12 06:56:28+00:00
I was kinda watching it unfold on X, I think this user was a couple days before https://x.com/delba_oliveira/status/2020515010985005255?s=46 and simpler/less-invasive instructions

---

Also, I'd love to use these sound effects, but I am an rts player and love aoe and wc franchise, these noises just trigger me to want to play too much.
by stephenr | 2026-02-12 06:56:41+00:00
> that is why carpenters are still around and no one buys Ikea

The irony in this statement is hilarious, and perfectly sums up the reality of the situation IMO.

For anyone who doesn't understand the irony: a carpenter is someone who makes things like houses, out of wood. They absolutely still fucking exist.

Industrialised furniture such as IKEA sells has reduced the reliance on a workforce of cabinet makers - people who make furniture using joinery.

Now if you want to go ask a carpenter to make you a table he can probably make one, but it's going to look like construction lumber nailed together. Which is also quite a coincidence when you consider the results of asking spicy autocomplete to do anything more complex than auto-complete a half-written line of code.
by gspr | 2026-02-12 06:57:02+00:00
> Never has an old language gained traction, its all about the initial network effects created by excitement.

Python?! Created in 1991, became increasingly popular – especially in university circles – only in the mid-2000s, and then completely exploded thanks to the ML/DL boom of the 2010s. That boom fed back into programming training, and it's now a very popular first language too.

Love it or hate it, Python was a teenager by the time it properly took off.
by youki_t | 2026-02-12 06:58:30+00:00
This is interesting, but I'm curious about the 'hammer' example. You mentioned frequency analysis failed. Did the 'Thinking' interview directly point you to the 'decay rate' (reverberation), or was that still something the engineers had to figure out by trial and error? It sounds like simple feature engineering, but finding which feature to engineer is the hard part.
by torginus | 2026-02-12 06:58:50+00:00
This is maybe a bit of a tangent to this article,but I've tried so many pieces of tech over the years to replace pen & paper notebooks, mainly iPads and eInk based notetaking devices, like the Remarkable.

While I cannot find a concrete flaw with these things, with some of them working quite well, I just couldn't really get a feel for them - they always felt so tech-y and imprecise, that I always went back to an actual sheet of paper.

Another product design misconception I think a lot of companies make is the use of metal cases - metal feels high-end and durable as opposed to plastic I suppose, and with it being quite solid, manufacturers can make it thinner and lighter.

But it's uncomfortable to hold, and hard to manufacture complex shapes, which means these devices often end up in a case. Man I miss the 2000s when product design wasn't dead.
by sjdonado | 2026-02-12 06:59:20+00:00
Went from optimizing typing speed (Neovim) to context-switching (git worktrees) to decision-making (Zed + AI). I feel like the job keeps moving upstream. Would love to hear how other people's workflows have adapted, especially those who have been through a few tool transitions already.

Are you spending less time coding and more time deciding what to build?
Show HN: Building an open-source Google Scholar / Consensus alternative
by nexwastaken | 2026-02-12 06:59:35+00:00
I wanted to build a full-stack app from start to finish to learn the modern dev cycle so I built something that'd be helpful for me in research.

Started with a single Next.js app, switched to Monorepo due to growing complexity. Has analytics, email, payment, ai, backend, frontend, help & docs - everything most modern apps need. Even some barebones for a mobile app and a browser extension (using wxt).

The main features are a search engine powered by Semantic Scholar, AI summaries, folders - with rich text notes (using WYSIWYG) & sharing.

Thinking of adding different AI models and a BYOK feature.

Here's a quick demo video too - https://drive.google.com/file/d/1yv75PEghFN0-53M_Gb4EMefX-sQ...
by querez | 2026-02-12 06:59:48+00:00
That's not how I remember it. Excitement for python strongly predated ML and data science. I remember python being the cool new language in 1997 when I was still in high school. Python 2.4 was already out, and O'Reilly had put several books kn the topic already it. Python was known as this almost pseudo code like language thst used indentation for blocking. MIT was considering switching to it for its introductory classes. It was definitely already hyped back then -- which led to U Toronto picking it for its first ML projects that eventually everyone adopted when deep learning got started.
by 6510 | 2026-02-12 06:59:57+00:00
I one time knocked on the door of a 200+ IQ student simply to ask her why she NEVER socialized with ANY other students. She was so introvert it was funny, she gazed at me for a few seconds, then looked at the ceiling and tilted her head. Stood there for 10 seconds or so. Well... she said, it's terrifying for me. I asked howso, she responded immediately now, almost everything they know is wrong but you cant tell them that because they don't even know what words mean. Some rather hilarious examples followed that I cant even remember. She made herself small and slowly closed her door, okay? she said. I laughed, thanks, I've been curious for a long time, I get it now.

Now go find the legal, medical and scientific definition of a vaccine. And everyone keeps calling it a vaccine? At best we can argue they tried really hard to make something like a vaccine really fast.

We for example have really strict rules for may be called medication. Until elaborately tested you may not call it that.

It doesn't matter if it works or not. You can inject people with something but it ain't vaccination no matter how often you say it. It should be called an experiment. The AstraZeneca experiment.

It doesn't make it any less sad but side effects or terrible outcomes are perfectly normal. We don't do clinical trials for the fun of it.

It is important to do language. If you punch a baby it isn't a fight, if you set fire to 100 babies it isn't a war. etc
by tsimionescu | 2026-02-12 07:02:14+00:00
> You would agree that in the quest to solve x^2+1=0, we had to introduce another dimension, with a multiply operator that lets us move through that dimension.

I don't really agree, no. In the analytic definition, there is no second dimension. Sure, C is isomorphic to R×R, but that is not how you construct it. C is not R×R, it's R+{a + b * i | a,b in R, b≠0} in this view. Just like Z is N+{a * -1 | a in N, a≠0}. You introduce one new number that you need to solve the equation, and then all of the numbers needed to make the new construction a field again. You don't introduce a new notion of multiplication, C uses the exact same multiplication operation as R does, or at least as polynomials over R do, as I showed.

The fact that C is isomorphic to R×R, and that multiplication of numbers in C is isomorphic to scaling+rotation of vectors in R×R, is not part of the construction.

I do agree that there are no accidents in math, so I imagine this isomorphism is related to some more fundamental relationship between polynomials, 2d vectors, and rotation matrices - because our construction of C is strictly motivated by polynomials.

> For reals, the power operator has a strict definition with multiplication and division.

I don't agree with this statement. It's true for the integers, but already for the the rationals it loses any direct relationship to multiplication and division (how do you get 4^(1/2) = 2 by repeated multiplication?). And for the reals, it's completely gone. We can't even define many properties of real-valued exponentials - we don't even know if e^pi is an irrational number, for example.

> When you search for something like taylor series or limit form of e and you see a way to compute e^i what you are doing is basically using operators designed for real numbers and extending them to the complex numbers (when you substitute i for where normally a real number would be in the power term.

We've already agreed that there are no accidents in math. So just as the multiplication of polynomials is fundamentally linked with rotations of 2d real-valued vectors, we must accept that real exponentiation is fundamentally linked to complex exponentiation, otherwise the formulas wouldn't work the way they do.

Note also that calculus is not limited to operations on the number line - you can take the derivatives or integrate or calculate limits of n-dimensional curves, and even differentiate over surfaces and n-dimensional manifolds more generally. Smoothness and continuity are anyway part of the structure of C, regardless what definition of it you use.

> And if you think thats silly, consider the fact that the algebraic view of complex numbers doesn't even consider calculus on them to be valid.

I don't understand what you mean by this. Calculus is well defined for functions over any field of size continuum, and that is exactly what <C,+,*,0,1> is in the algebraic view.
Show HN: AI that replaces the first 15 minutes of every client call
by vira28 | 2026-02-12 07:02:33+00:00
Hi HN — I’m Viggy, founder of MyClone.

We originally built a marketplace connecting startup advisors with founders. After ~6 months, we had hundreds of recorded discovery calls and transcripts.

We noticed something interesting:
The first 10 minutes of most advisory calls were almost identical.
• What do you do?
• Who is this for?
• Pricing?
• What information do you need from me?
• Am I a good fit?

So we pivoted.

Today, MyClone lets service professionals (consultants, CPAs, etc.) deploy an AI voice agent that:
• Answers FAQs in their voice
• Runs structured intake conversations
• Qualifies leads
• Routes good prospects to a human

Technical details

Under the hood:
• Multi-source ingestion (websites, docs, PDFs, media transcripts)
• Structured knowledge graph + chunked semantic retrieval
• Custom RAG pipeline (not using off-the-shelf frameworks)
• Prompt templates generated dynamically based on objective (FAQ vs intake vs qualification)
• Guardrails to prevent hallucination beyond uploaded corpus

We learned quickly that generic “chat with your docs” doesn’t work for client-facing scenarios. The hard part is:
• Controlling tone
• Avoiding overconfidence
• Structuring conversations instead of answering open-ended questions
• Handling partial / messy user inputs
• Maintaining low latency in voice mode

Still early, but we’re seeing adoption from solo and small firms who want a 24/7 “AI associate” for first-touch conversations.

We do share our technical learnings in our blog - https://www.myclone.is/blog Happy to answer technical questions, RAG architecture details, failure modes, or things that broke during the pivot.

— Viggy
by deaux | 2026-02-12 07:02:33+00:00
This just doesn't engage with what I said, being that this is only true because the law has been captured by big capital interests, to the detriment of society. "But it's the law!!" adds nothing - my comment already implies awareness of it being the law.

The idea that using these 24-year old WC3 peon sounds in an open source github project makes one an "AI bro" or even connecting it to AI in general is laughable. There have been thousands of projects on github including this kind of thing long, long before LLMs.

Your anger about big AI and copyright is valid! But it's completely overflowing your common sense, targeting the wrong things indiscriminately. Learn to channel it.
by stevenicr | 2026-02-12 07:03:11+00:00
I've been wondering the past couple of weeks about how is India ready for what AI is already doing to jobs, and what is about to happen.

This is taking over faster than I ever expected, with some places already doing the race to the bottom (I recently discovered a portal for small businesses is now offering AI call answering / support / booking all automated addon for $10 / month - and I thought it was a good deal offering similar for $500 / month not long ago), this is going to make millions obsolete within months.

And I only say months because I see it taking that long for places to wind down contracts and switch over to AI call answering and customer support.

The ai systems available for so many of these tasks are more than good enough, and so many people and even tiny businesses are now aware of their existence, I don't see any going back to non English as first language call answering, support or even IT help at this point (for US based businesses, which I assume has been the lions share of income for many of the call centers in many places).
by pmontra | 2026-02-12 07:03:13+00:00
100 W is only the start. Let's say that I consume 100 W all along the day. I use an LLM for coding assistance in the old way of asking questions and copy pasting code. It's much faster than me at writing that code. I don't think it ever works 1 hour for me per day. It's probably 10 cumulative minutes, probably much less. Round it up to 12 minutes to make it 1/5 of a hour or round it down to 6 minutes for a 1/10. So instead of 24 it's 0.1 hours, 240 times less. Those 100 W could be 24000 W and the total power per day would be the same. Is that LLM consuming 24 kW when working for me? No idea but I hope it's less than that.

Of course I could do all of my coding alone again, but I would be slower. It's like walking to the mall several times per week, several hours per time, instead of once or twice per week with a car, three cumulative hours. I trade a higher energy consumption for more time to do other things and the ability to live far away from shops.
by adamslinhf | 2026-02-12 07:03:45+00:00
Great discussion on the security challenges of openClaw and nanoClaw – these are critical issues for the AI agent ecosystem right now. I wanted to chime in with a key point about early patent explorations out of China dating back to 2023 that directly tie into the core security pain points we’re talking about here.
Back in 2023, two patent applications were filed targeting AI agent and LLM interaction security, well before the recent security vulnerabilities in openClaw/nanoClaw came to light. The first one is CN117234659A, which focuses on the containerized management of AI agents – a technology that addresses the isolation, privilege control and runtime security gaps we’ve seen plaguing openClaw (like unregulated plugin execution and insufficient sandboxing). This patent is currently under substantive examination.
The second one, CN118805166A, has already been granted official authorization. It lays out a comprehensive security management framework that covers all stages of LLM interaction – a holistic solution that could mitigate structural risks like prompt injection, unauthorized command execution and supply chain attacks in tools like nanoClaw and openClaw.
It’s interesting to see that these early technical explorations targeted the exact foundational security issues that are now causing problems for mainstream AI agent tools. The containerization approach in CN117234659A and the full-lifecycle security framework in CN118805166A could both offer valuable technical references for the openClaw/nanoClaw teams to harden their security architecture moving forward.
Curious to hear what the community thinks about how these early patent-backed solutions might apply to the current open source AI agent security landscape!
by rubyn00bie | 2026-02-12 07:04:44+00:00
Can you elaborate on your claim it’s not enough? PasS (platform as a service) has been transformative for modern infrastructure. Containers for better, or worse, have made deployments substantially “easier,” giving every org the ability to provide Heroku like services. But, Heroku provided this sort of ease, and more, long before containers ate the world. And regardless of containers themselves, I fail to see how something “more structured” would even exist. Deploy on push is still subject to being merged and everywhere I’ve worked has had no shortage of checks and approvals to merge.
by oblio | 2026-02-12 07:05:26+00:00
There is one where desktops are slowly being remade, which Windows and MacOS are failing at. Have application repositories, but open ones like Debian or Linux in general, so that application developers can publish and don't ask for a cut of every sale. Sandbox all new desktop applications over the years and publish long roadmaps until everything is sandboxed, say, in 2035.

Provide more education and guidance for users and more corporate controls.

If they would have really started to do this in 2005, we would have been there by now. Instead we get more UI toolkits and more UI refreshes and AI everywhere.
by shinycode | 2026-02-12 07:07:41+00:00
Actually it’s easy to generate « fake discussions ». Just throw text around and wait for the other side to do it. How wait, LLM are build around that premise. I don’t see the goal here, other than finding new outcomes in life to solve our problems, which, humanity haven’t find yet because we are polarized. Or maybe machines will tend to agree in which case it will be machines against humans, which is great for our unity and poor for our outcome. We’ve seen that scenario before.
by andsoitis | 2026-02-12 07:07:49+00:00
> Mozart wrote over 600 songs, but only about 50 of them are widely played.

Calling Mozart’s works “songs” is ignorant.

Mozart wrote some songs (“lieder”, or art songs for voice and piano), but his work spans operas, symphonies, concertos, chamber music, masses and other sacred music, and solo piano works.
by Gagan_Dev | 2026-02-12 07:08:39+00:00
Interesting direction. I agree that most agent frameworks hit a “toy app ceiling” because they conflate conversational state with long-lived system state. Once you move into real business workflows (ERP, reconciliation, async pipelines), the problem stops being prompt orchestration and becomes distributed state management under uncertainty.

The OODA framing is compelling, especially treating exceptions as observations rather than terminal states. That said, I’m curious how you’re handling:

1.State persistence across long-running tasks — is memory append-only, event-sourced, or periodically compacted?

2.Convergence guarantees in your “system of inference” model — how do you prevent correlated failure across k runs?

3.Cost ceilings — at what point does reliability-through-redundancy become economically infeasible compared to hybrid symbolic validation?

I also like the rejection of GCU-style UI automation. Headless, API-first execution seems structurally superior for reliability and latency.

The biology-inspired control mechanisms (stress / neuroplasticity analogs) are intriguing — especially if they’re implemented as adaptive search constraints rather than metaphorical wrappers. Would be interested to understand how measurable those dynamics are versus heuristic.

Overall, pushing agents toward durable, autonomous services instead of chat wrappers is the right direction. Curious to see how Hive handles multi-agent coordination and resource contention at scale.
by deaux | 2026-02-12 07:09:09+00:00
> But 4.6? Apparently better, but it hasn't changed my workflows or the types of problems / questions I put to it.

The incremental steps are now more domain-specific. For example, Codex 5.3 is supposedly improved at agentic use (tools, skills). Opus 4.6 is markedly better at frontend UI design than 4.5. I'm sure at some point we'll see across-the-board noticeable improvement again, but that would probably be a major version rather than minor.
by leptons | 2026-02-12 07:09:37+00:00
What prominent left-wing politician has ever talked about "re-education" camps? None, that's who.

I'm not talking about vile rhetoric coming from reddit commenters, I'm talking about people in the current administration - when Steven Miller said "We are in the process of the second American Revolution, which will remain bloodless if the left allows it to be" - exactly what do you think he meant?
Show HN: A calorie explorer for 5,796 foods (1–900 kcal)
by melvinzammit | 2026-02-12 07:09:54+00:00
I built this free searchable/sortable normalised nutritional facts database. I made it for the users of my App to quickly find how many calories ingredients have for their meal plan. It's very interesting to see the range of calories across 5796 foods.

If you want to replicate it, the data is obtained from the USDA FoodData Central.
by retsibsi | 2026-02-12 07:10:14+00:00
Sounds like you see me as an untrustworthy source, so all I can suggest is that you look into this yourself. Search for "--" in pre-LLM forum postings and see how many hits you get.

Here are my pre-2020 HN comments, with 3 double dashes in 8 comments: https://hn.algolia.com/?dateEnd=1576108800&dateRange=custom&...

As I was in the process of typing the search term to get my comments (and had just typed 'author'), this happened to come up as the top search result for Comments by Date for Feb 1st 2000 > Dec 12th 2019: https://news.ycombinator.com/item?id=21768030

Note that I wasn't searching directly for the double hyphen, which doesn't seem to work -- the first result just happened to contain one. If I'm covering for the Anthropic guy, I could be lying about the process by which I found that comment, but I think you should at least see this as sufficient reason to question your assumptions and do some searches of your own.

edit: and then maybe you can apologise for defaulting to paranoid mode, and implying that I'm a lying stooge, rather than spending 2 minutes looking into this. The more I look, the more obvious it is that the double hyphen is not especially idiosyncratic or unusual, and evidence of this is extremely easy to find.