MurphyA/hacker-news huggingface dataset:
by mahdiyar | 2026-01-07 18:11:31+00:00
But Ralph has problems when you move beyond one-off tasks:

1. Overcooking: The loop runs forever. Leave it too long and the AI starts adding features nobody asked for, refactoring code that was fine, writing documentation for the sake of it.

2. Undercooking: Ctrl+C too early and you're left with half-done features.

3. Fragile state: Ralph uses markdown files (TASKS.md, PLANNING.md) as source of truth. LLMs can corrupt these - add extra formatting, forget sections, change structure.

4. No memory between sessions: Each run starts fresh. The AI can't see what was done yesterday.

5. Vendor lock-in: Ralph was built for Claude Code. Switching to Codex or Gemini means rewriting your workflow.

So I built juno-code to fix these problems.

What juno-code does differently Iteration control: Instead of while :; do, you get -i 5 for exactly 5 iterations, or run_until_completion.sh that stops when kanban tasks are done.

Structured task tracking: Instead of markdown, tasks are stored in NDJSON files via juno-kanban. The format can't be corrupted by LLM formatting errors. You can query tasks programmatically:

./.juno_task/scripts/kanban.sh list --status in_progress Backend agnostic: Switch between Claude, Codex, Gemini, or Cursor with one flag:

juno-code -b shell -s claude -m :opus -i 5 -v juno-code -b shell -s codex -m :codex -i 5 -v juno-code -b shell -s gemini -m :flash -i 5 -v Stuck on a bug? Try a different model's perspective with one word change.

Full traceability: Every completed task links to a git commit. Time travel through development history. The AI can search git history instead of re-reading everything.

Hooks without lock-in: Run tests, linters, or any script at lifecycle points. Works with any backend:

{ "hooks": { "START_ITERATION": { "commands": ["./scripts/lint.sh"] }, "END_ITERATION": { "commands": ["npm test"] } } } Real-time feedback: Send feedback to the running AI without stopping it:

juno-code feedback "found a bug in the auth flow" Quick start npm install -g juno-code

cd your-project juno-code init --task "Migrate from JavaScript to TypeScript" --subagent claude

# Run until kanban tasks are complete ./.juno_task/scripts/run_until_completion.sh -s claude -i 10 -v The key insight Ralph proved that AI works better in loops. juno-code adds the structure that makes loops sustainable:

Controlled cooking time (not infinite) Strict task format (not corruptible markdown) Any AI backend (not vendor locked) Full audit trail (not blended changes) GitHub: https://github.com/askbudi/juno-code npm: https://www.npmjs.com/package/juno-code

Built with TypeScript. MIT licensed. Feedback welcome.
by tracker1 | 2026-01-07 18:11:32+00:00
No vegetable is as protein dense as actual meat in its natural form.

Ruminant meat is absolutely one of the best bioavailable forms of a mostly complete amino acid profile, though eggs and dairy is more complete with differing ratios depending on form/feed.

As to lentils, tofu, chickpeas etc. They're fine for most people in moderation, but they are also relatively inflammatory and plenty of people have digestive issues and allergies to legumes (I do), soy is one of the top 10 allergens that people face. While almost nobody is allergic to ruminant meat.
Show HN: AbleMouse AI. Nose-point cursor. Screen-size independent
by aradzhabov | 2026-01-07 18:11:37+00:00
In addition to the DIY edition, AbleMouse has gained a new open-source AI module for face-controlled mouse navigation. Now you just need to point your nose at the desired spot on the screen—regardless of the screen's width—and the cursor will move there. Unlike eye trackers, it feels natural and doesn't strain your eyes. AbleMouse now provides specialized sub-products for various physical needs. View Product Compatibility with User Physical Abilities on the project website.
by mahdiyar | 2026-01-07 18:11:46+00:00
But Ralph has problems when you move beyond one-off tasks:

1. Overcooking: The loop runs forever. Leave it too long and the AI starts adding features nobody asked for, refactoring code that was fine, writing documentation for the sake of it.

2. Undercooking: Ctrl+C too early and you're left with half-done features.

3. Fragile state: Ralph uses markdown files (TASKS.md, PLANNING.md) as source of truth. LLMs can corrupt these - add extra formatting, forget sections, change structure.

4. No memory between sessions: Each run starts fresh. The AI can't see what was done yesterday.

5. Vendor lock-in: Ralph was built for Claude Code. Switching to Codex or Gemini means rewriting your workflow.

So I built juno-code to fix these problems.

What juno-code does differently Iteration control: Instead of while :; do, you get -i 5 for exactly 5 iterations, or run_until_completion.sh that stops when kanban tasks are done.

Structured task tracking: Instead of markdown, tasks are stored in NDJSON files via juno-kanban. The format can't be corrupted by LLM formatting errors. You can query tasks programmatically:

./.juno_task/scripts/kanban.sh list --status in_progress Backend agnostic: Switch between Claude, Codex, Gemini, or Cursor with one flag:

juno-code -b shell -s claude -m :opus -i 5 -v juno-code -b shell -s codex -m :codex -i 5 -v juno-code -b shell -s gemini -m :flash -i 5 -v Stuck on a bug? Try a different model's perspective with one word change.

Full traceability: Every completed task links to a git commit. Time travel through development history. The AI can search git history instead of re-reading everything.

Hooks without lock-in: Run tests, linters, or any script at lifecycle points. Works with any backend:

{ "hooks": { "START_ITERATION": { "commands": ["./scripts/lint.sh"] }, "END_ITERATION": { "commands": ["npm test"] } } } Real-time feedback: Send feedback to the running AI without stopping it:

juno-code feedback "found a bug in the auth flow" Quick start npm install -g juno-code

cd your-project juno-code init --task "Migrate from JavaScript to TypeScript" --subagent claude

# Run until kanban tasks are complete ./.juno_task/scripts/run_until_completion.sh -s claude -i 10 -v The key insight Ralph proved that AI works better in loops. juno-code adds the structure that makes loops sustainable:

Controlled cooking time (not infinite) Strict task format (not corruptible markdown) Any AI backend (not vendor locked) Full audit trail (not blended changes) GitHub: https://github.com/askbudi/juno-code npm: https://www.npmjs.com/package/juno-code

Built with TypeScript. MIT licensed. Feedback welcome.
by parliament32 | 2026-01-07 18:11:48+00:00
> I still believe those who rave about it are not writing anything I would consider "engineering".

Correct. In fact, this is the entire reason for the disconnect, where it seems like half the people here think LLMs are the best thing ever and the other half are confused about where the value is in these slop generators.

The key difference is (despite everyone calling themselves an SWE nowadays) there's a difference between a "programmer" and an "engineer". Looking at OP, exactly zero of his screenshotted apps are what I would consider "engineering". Literally everything in there has been done over and over to the death. Engineering is.. novel, for lack of a better word.

See also: https://www.seangoedecke.com/pure-and-impure-engineering/
by AlotOfReading | 2026-01-07 18:11:58+00:00
There are multiple ways to deal with deadline misses for soft systems. Only some of them actually deliver the correct data, just late. A lot of systems will abort the execution and move on with zeros/last computed data instead, or drop the data entirely. A modern network AQM system like CAKE uses both delayed scheduling and intelligent dropping.

Agreed though, "just" is hiding quite a deep rabbit hole.
by fuzzfactor | 2026-01-07 18:11:59+00:00
Really sensible blog post.

The author uses his late uncle as an example of a "big E" entrepreneur and I agree completely.

I like to take the terminology a step further because this is not the only "textbook" example of a successful non-Capitalist entrepreneur.

When you strictly consider capital to be Other Peoples' Money (OPM), you do have to admit that you can't be much of a capitalist without capital.

If all you are using is your own money & resources of some kind, and leveraging that, even if you prosper in a truly capitalist market, you're not really in the same business as those who are manipulating OPM.

By the same token his instant observation of how fundamentally different an entrepreneur's "schedule" is supposed to be compared to an employee's is noteworthy.

Across a spectrum the plain non-capitalist entrepreneurialism of the late uncle is at one extreme, an example many people do not have. At the other end of the spectrum is the poor employee's schedule, where if the whip is going to be cracked it cracks hardest.

Somewhere in between is the well-funded capitalist entrepreneur, and I would say much closer to the poor employee's schedule is the not-so-well-funded capitalist.
by tormeh | 2026-01-07 18:12:39+00:00
If you're ever forced to use Windows, just install nushell. The speedup is wild, and along with it comes many nice quality of life features.

Nushell is good on the Unixes as well, but the defaults there are less annoying. I regularly revert to bash because there's just some thing I've memorized in bash, and bash doesn't make me want to scream.

Note that this is just my perspective on it as an interactive shell. I've never used it for scripting.
by surgical_fire | 2026-01-07 18:12:53+00:00
> industrial-scale torture of helpless animals.

industrial-scale torture of helpless tasty animals.

I did this in jest, but I think this is maybe the main barrier to pulling back on meat consumption. It tastes too damn good.

I am well educated, and would perhaps like to reduce my meat consumption. Until I realize that nearly 100% of my favorite dishes contain meat. And if we expand to milk or eggs, that list expands to 100%.

Food is weird because it sits in an intersection of physiological need, pleasure, craft, and culture.
by bccdee | 2026-01-07 18:12:55+00:00
Yeah, (1) there is no "war on protein," (2) you do not need to eat very much protein unless you are trying to build muscle and you already work out a lot.

The normal recommended daily intake for protein is 0.8 g/kg. 1.2-1.6 is silly; that's a recommendation for athletes.¹

Starches have been a dietary staple in pretty much every society forever. Sugars have not. It's silly that they treat grains as a "sometimes" food.

There's also the weird boogeyman of "processed food." Almost all food is processed to some degree & always has been. We've been cooking, baking, juicing, fermenting, chopping, grinding, mashing, etc. long enough that it influenced the shape of our teeth. Certainly we haven't been making Pizza Pockets that long, but the issue there isn't processing, it's ingredients. And the reason people buy Pizza Pockets isn't that they think they're healthy—it's that Pizza Pockets only need to be microwaved, and cooking a real meal takes time that a lot of people just don't have.

[1]: https://www.strongerbyscience.com/athlete-protein-intake/
by overgard | 2026-01-07 18:12:57+00:00
Eggs are very healthy. There's a lot of nutrients that are hard to get from other sources that eggs have in abundance. And it makes sense in just a common-sense sort of way -- if you're a chicken you want to surround your offspring with the best possible food you can as they grow.

With regards to dairy, it's more about a person's individual reaction to it. It's a similar argument with nutrient density (since milk is intended for growing offspring, obviously it's going to be very nutrient dense). The downside is potential inflammation or not having the enzymes to process it.

I would definitely not lump eggs and dairy as "bad" in any way though.

Also, the "cholesterol" thing is a very bad thing to focus on. Cholesterol is not bad! You need cholesterol. (What do you think cell membranes are partially composed of?

Whole grains are not as good as you think. Often, they're made from strains that are optimized for growing and robustness not nutrition. Also, unless you're exercising a lot you really don't need much in the way of carbs.
by ryandrake | 2026-01-07 18:13:10+00:00
I've found it to be pretty hit-or-miss with C++ in general, but it's really, REALLY bad at 3D graphics code. I've tried to use it to port an OpenGL project to SDL3_GPU, and it really struggled. It would confidently insist that the code it wrote worked, when all you had to do was run it and look at the output to see a blank screen.
by bell-cot | 2026-01-07 18:13:16+00:00
> At the risk of ...

Any decent person would take that risk, for their mother's health.

At least in the US, there's a fairly large industry built around mold testing & remediation. Laboratories need to be inspected & certified, and you can do your own home air testing and receive the results directly from the lab.

Compared to a family member's health, testing is very cheap.

Vs. if you're testing to make sure the house isn't rotting - that's trickier. Many sorts of mold can be underachievers at releasing spores (which is what the common air tests look for). Or the spores could be released in a wall cavity or something, where air doesn't circulate and carry them to where you're taking samples.

I've no idea what the situation is in Spain.

Changing topic - my mother's mental health & vision were destroyed by an undiagnosed case of https://en.wikipedia.org/wiki/Giant_cell_arteritis . America's health care system burned through incredible amounts of money for fancy high-tech scans and tests. It did not bother with having a competent doctor sit down, and really think about what might be causing mom's slowly-worsening symptoms. That would not have been hard - mom was in the very highest-risk demographic for that disease. And after it was too late - my optician was able to diagnose her in seconds, sight unseen, from just my in-passing mention of her eye-related symptoms.

(Yes, I also got the clear feeling that the health care system did not care at all about an elderly woman's declining health);
by jerf | 2026-01-07 18:13:24+00:00
It's in the extended standard library at https://pkg.go.dev/golang.org/x/net/webdav . Whether or not it would meet their needs, they'd have to tell us. I don't think they told us enough to evaluate that ourselves, and even if they did doing even a quick job is probably at least an hour's careful reading and comparing and that's past my budget for an HN post. And they're not obligated to give us an absolutely complete accounting of everything they considered. That just generates other complaints.
by joshstrange | 2026-01-07 18:13:28+00:00
Interesting, well I'm glad it's working well for you all. I tested with local, HA Cloud, and ChatGPT/Claude and that wasn't the sticking point, it was getting the hardware to hear me or for me to hear it.

I will say, while it was too slow (today) with the my local inference hardware (CPU, older computer and a little on my newer MBP) it was magically to talk to and hear back from HA all locally. I look forward to a future where I can do that at the same speed/quality as the cloud models. Yes, I know cloud models will continue to get better but turning on/off my fans/lights/etc doesn't need to best model available, just needs to be reliable and fast, I'm even fine with it "shelling out" to the cloud if I ask it for something outside of the basics though I doubt I'll care to do that.
by MMAFRAZ | 2026-01-07 18:13:38+00:00
I’m building Vect AI, an attempt to treat marketing execution as software infrastructure rather than a collection of disconnected SaaS tools.

Vect AI is designed as a marketing operating system where campaign planning, content creation, SEO workflows, and distribution live inside one coherent system. Instead of relying on one-off prompts or dashboards, the focus is on stateful workflows that retain context and reduce execution overhead.
Platform: https://vect.pro

Alongside the core product, I built The Vect Growth Engine, a blog that functions as an organic distribution layer rather than a passive content site. The goal was to turn SEO content into a programmable surface that compounds over time and connects directly back into product workflows.
Blog: https://blog.vect.pro

Some principles behind the build:

Replace fragmented marketing stacks with a single execution layer

Treat SEO and content as long-term infrastructure, not short-term traffic

Use AI for planning and execution, not just copy generation

Focus on deterministic workflows instead of analytics-heavy dashboards

This started as a personal project to simplify my own marketing workflow, but it’s become an ongoing exploration of how AI-driven systems, content, and product-led growth can converge into one unified platform.

Sharing this here to exchange learnings with others building AI tools, developer-first SaaS, or content-driven growth systems.
by sifar | 2026-01-07 18:13:47+00:00
" “Foreign persons” is broadly defined in the bill as any person who is not a United States person. However, the bill does not include “any corporation or partnership organized under the laws of a possession of the United States” in that definition of foreign person. "

Most offshoring companies don't pay directly to individuals - either they are employees of their own subsidiaries or those of offshoring entities. So, this is not going to change anything.
by UltraSane | 2026-01-07 18:14:06+00:00
If you haven't tried PowerShell I strongly recommend you do. It is really well designed and the way objects are piped between commands is brilliant and very powerful. Combined with property filters you can do SQL like queries. The ConvertTo-JSON lets you export the output of any command to JSON which is amazingly useful. As an example you can dump the entire Active Directory (Assuming you have permissions) by

Get-ADObject -Filter * -Properties * | ConvertTo-JSON > ADObjects.json

And you have access to ALL of the .NET library.
by mossTechnician | 2026-01-07 18:14:10+00:00
> if you close a youtube browser tab with a comment half written it will pop up an `alert("You will lose your comment if you close this window")`. It does this if the comment is a 2 page essay or "asdfasdf". Ideally the alert would only happen if the comment seemed important but it would readily discard short or nonsensical input. That is really difficult to do in traditional software but is something an LLM could do with low effort.

I don't think that's a great example, because you can evaluate the length of the content of a text box with a one-line "if" statement. You could even expand it to check for how long you've been writing, and cache the contents of the box with a couple more lines of code.

An LLM, by contrast, requires a significant amount of disk space and processing power for this task, and it would be unpredictable and difficult to debug, even if we could define a threshold for "important"!
by vjanma | 2026-01-07 18:14:11+00:00
This is exactly the problem I've been obsessing over. The challenge is that olfaction isn't like vision. you're not detecting photons at discrete wavelengths, you're dealing with ~400 olfactory receptor types responding to millions of possible volatile molecules in combinatorial ways.

MOX sensors (like the SnO2 in this paper) have been around for decades but hit a fundamental ceiling—they require specific coatings to bind to specific VOCs. Want to detect a new substance? You're changing hardware.

The more promising path, IMO, is carbon nanotube (CNT) sensors that actually mimic how our nose works. Instead of measuring bulk resistance changes, you functionalize CNT arrays to respond to specific molecular binding events—much closer to how olfactory receptors operate. detection of new substances becomes a software/ML problem rather than a hardware redesign. That's how biology does it—your nose doesn't grow new receptors, your brain learns new patterns.

Full disclosure: I'm building in this space (https://nosy.network) Nosy is using CNT paired with transformer models to create what we call a "Large Essence Model" (LEM). LEM "GPT for smell" processes scent information similar to how LLMs process text.
by coryfklein | 2026-01-07 18:14:22+00:00
This has been called out by the Moody's Analytics economists in their podcast [0] for a while. The generally accepted explanation is that online job postings no longer map 1:1 to actual open positions at companies, ie many companies are not actually hiring despite having a listing for an open role.

This has become common enough that it has gained it's own term: "ghost" postings/listings.

[0] https://www.moodys.com/web/en/us/insights/podcasts/inside-ec...
by Analemma_ | 2026-01-07 18:14:31+00:00
Uncertainty has a cost which exists no matter where you move it around. Yes, investment banks might sell you some kind of exotic derivative which moves the risk onto them, but they'll charge a risk premium for this (probably a very high one since the risk factors here are pretty unusual and hard to model), and that makes it harder to stay afloat as a business. There is no handwaving away the damage that uncertainty does to commerce.
by hashhar | 2026-01-07 18:14:40+00:00
Which of those are evolving at the rate of frameworks?

BTW I'm of the opinion that frontend tooling developers should actually try to contribute things to HTML and CSS instead of building "component libraries" on top of them.

If the native controls were good and if the browsers allowed using "uniformly styled" versions of them then there would be no good reason for such libraries to exist.
by bitwize | 2026-01-07 18:14:59+00:00
I remember in the early 2000s Bill finally sat down in front of a Windows computer to play with and evaluate the software, found out how crap Windows and some of its related products really were, and sent out some angry memos telling his lieutenants to get it in gear from a quality and usability standpoint.

He may have enabled scalability by being more hands off, but I'm still kind of surprised it took him that long to learn that software quality had fallen off that far. And I'm not even getting into the monopoly aspect of it. Maybe that was the business model all along, you can save costs by not adhering to quality standards as long as you land the right exclusivity deals with OEMs. Microsoft gonna Microsoft.
by reissbaker | 2026-01-07 18:15:02+00:00
Beef has ~3x more protein per gram than legumes. It is much more protein-dense than vegetables or legumes.

Similarly, it's a "complete" protein, whereas most vegetables and legumes are missing necessary amino acids.

The downside of beef isn't the "density" of nutrients: the downside is high saturated fat. Chicken breast, though, is similarly high in protein without the saturated fat downside.
by etchalon | 2026-01-07 18:15:23+00:00
That's just not how the math works.

Let's assume an average marginal loss of 2% of gross sales to theft at a business with a net margin of 4% (typical of retail). Let's also assume wholesale markup of 50%, just to be conservative.

On two million in gross sales, a 2% loss equates to a $40,000. Assuming a 50% markup, the retailer has lost $20,000 in COGs. We'll ignore the other $20,000 for now.

On two million in gross sales, and a 4% net margin, the retailer can expect to make an annualized profit of $80,000.

We deduct the $20,000 in COGs loss, the retailer is now making only $60,000 a year, that's a loss of 25% in profit.

And that's using 50% markup.

In your stated case, with a 30% markup, the retailer would have lost $28,000 dollars in COGs, meaning the retailer is now making only $52,000, a reduction of 35% in net profits.

There is no universe in which this is a non-meaningful amount or to be dismissed as "well, something else has to be going wrong. Theft just isn't that big a deal."