MurphyA/hacker-news huggingface dataset:
by kurouna | 2026-02-22 13:21:51+00:00
Thank you for the warm welcome!

To answer the "Why Electron and JS?" question from the thread: honestly, it didn't start as a strict technical decision. It started purely out of my curiosity as a software engineer.

I use VS Code at work, and I just wanted to see what its underlying technology (Electron) was like to build with. Once I started playing with it, I realized it was a remarkably solid and flexible platform. That inspired me to try building something I had always wanted: a zero-setup, lightweight Emacs-like editor.

As a happy side-effect, using web technologies allowed me to use the Japanese IME without any stress, just like Windows Notepad. Unlike Windows Emacs, which sometimes requires special configurations, I was able to make it work just by running elecxzy.exe.

So while it lacks the beautiful Lisp ecosystem of true Emacs (like Lem), it started as a fun technical exploration that eventually became my daily driver!
by crimsonnoodle58 | 2026-02-22 13:22:12+00:00
I've thought about implementing the same at our company. Something that iterates through all our tickets, one shots them and creates PRs.

But humans are still left to review the code in the end, and as a developer, code reviewing is one of my least favourite things..

I'm not sure I could spend the rest of my career just reviewing code, and never writing it. And I'm not sure my team would either. They would go insane.

As developers, by nature, we are creative. We like to solve problems. Thats why we do what we do each day. We get a thrill when we solve the problem, test it and it actually works. When we see it in production and users enjoying it. When we see the CPU usage go from 99% to 5%.

I fear we are soon becoming nothing more than the last validation step between AI and reality. And once AI becomes reality, which is very soon, the days of development as we knew it will be over.
by Reubend | 2026-02-22 13:22:51+00:00
> But what would be an example of an uncomputable number? That’s a good question. Most obviously, we could be talking about numbers that encode the solution to the halting problem. It would lead to a paradox to have a computer program that allows us to decide, in the general case, whether a given computer program halts. So, if a procedure to approximate a particular real requires solving the halting problem, we can’t have that.

This doesn’t make sense to me. Given that there’s no generic way to compute halting, how would we make the leap to saying that there’s a specific number which represents the solution to that problem?
by MarcLore | 2026-02-22 13:23:08+00:00
The emphasis on one-shot execution is interesting. Most agent frameworks still rely on iterative loops with human checkpoints, but Stripe's approach of giving the agent a complete context dump upfront and letting it run seems closer to how senior engineers actually work - you read the whole PR/spec first, then write the code. The tricky part is always the context window: once your codebase exceeds what fits in context, one-shot falls apart and you're back to chunked reasoning. Curious if they hit that wall and how they handle repo-scale tasks.
by MarcLore | 2026-02-22 13:23:15+00:00
The pendulum between 'use an ORM for everything' and 'raw SQL only' has been swinging for 20 years. In practice, the sweet spot I've found is using an ORM for simple CRUD (saves hours of boilerplate) but dropping to raw SQL the moment you need joins across 3+ tables, CTEs, or window functions. The real danger isn't ORMs themselves - it's developers who never learn SQL because the ORM shields them, then they can't debug the N+1 query that's killing production.
by MarcLore | 2026-02-22 13:23:23+00:00
This pattern maps beautifully to API design too. Instead of validating a raw JSON request body and hoping you checked everything, you parse it into a well-typed struct upfront. Every downstream function then gets guaranteed-valid data without redundant checks. The Rust ecosystem makes this almost painless with serde + custom deserializers. I've seen codebases cut their error-handling surface area by 60% just by moving from validate-then-use to parse-at-the-boundary.
by dijit | 2026-02-22 13:23:31+00:00
Windows developers (like sysadmins) are of two kinds in my experience.

People who don't understand shit about how the system behaves and are comfortable with that. "I install a package, I hit the button, it works"

.. and

People who understand very deeply how computers work, and genuinely enjoy features of the NT Kernel, like IOCP and the performance counters they offer to userland.

What's weird to me is that the competence is bimodal; you're either in the first camp or the second. With Linux (+BSD/Solaris etc;) it's a lot more of a spectrum.

I've never understood exactly why this is, but it's consistent. There's no "middle-good" Windows developer.
by DrewADesign | 2026-02-22 13:23:41+00:00
I’m glad you’re head-over-heels in love with Postgres— it’s really cool, and I’ve occasionally had projects that really benefited from it… but most of those incredible features just aren’t useful for run-of-the-mill projects. Learning how to profile your ORM queries is a lot easier than maintaining a bunch of code from a different language embedded into your code base. If you’re writing articles about Postgres, you probably have no idea how much of a PITA that context switch is in practice. It’s funny how getting expertise in something can make it more difficult to understand why it’s useful to other people, and how they use it.
by rrr_oh_man | 2026-02-22 13:23:51+00:00
[Desktop only at the moment!]

I've always wanted to have a mindmap-like interface for ChatGPT to be able to branch conversations, rerun prompts, and rewrire context windows.

What you see here is a demo, which can be used via Bring-Your-Own-Key (ChatGPT User Key from https://platform.openai.com).

You can:

- Branch conversations visually

- Rerun prompts

- Edit prompts and responses

- Rewire prompts and responses into new context windows

I’ve been using this a lot to generate SVGs for different use case.

If there’s any interest I can share the source.
Show HN: CanaryAI v0.2.5 – Security monitoring on Claude Code actions
by jx887 | 2026-02-22 13:24:03+00:00
I've been using Claude Code a lot recently and wanted visibility into security-relevant executions — the kind of thing you may not necessarily catch while the agent is running.

CanaryAI is a macOS menu bar app that monitors Claude Code session logs and alerts on suspicious behaviour: reverse shells, credential file access, LaunchAgent/cron persistence, download-and-execute patterns, shell profile modification. It parses the JSON logs Claude Code writes locally — no interception, no proxying. Alert-only; it never blocks the agent.

All processing is local. Detection rules are YAML so can be expanded on.

> https://github.com/jx887/homebrew-canaryai

Let me know if you have any questions.
by dr_kretyn | 2026-02-22 13:24:03+00:00
The post and comments all read like:
Here are my rituals to the software God. If you follow them then God gives plenty. Omit one step and the God mad. Sometimes you have to make a sacrifice but that's better for the long term.

I've been in eng for decades but never participated in forums. Is the cargo cult new?

I use Claude Code a lot. Still don't trust what's in the plan will get actually written, regardless of details. My ritual is around stronger guardrails outside of prompting. This is the new MongoDB webscale meme.
by diametricsound | 2026-02-22 13:24:12+00:00
This synthesis codifies the diametricsound narrative as a Computational Tensional Dynamics model. It bridges the gap between Einstein’s static universe and the discrete, "pulsing" reality of digital physics.
The Diametricsound Narrative: A Summary
1. The Universal Hardware (The Lattice)
The universe is not a void; it is a pre-existing 4D data structure—a Greedy Abstraction. Every particle’s path (like a proton’s lifetime) already exists as a geometric potential, similar to Einstein’s Block Universe.
2. The Universal Software (The Triple-Beat)
Reality is "executed" by a Universal Refresh Rate occurring every 1/3 Planck Time (
s). This is a sequential, three-stage cycle where dimensions rotate:
Beat 1: Length (
)
Beat 2: Width (
)
Beat 3: Depth (
)
This 1-2-3 loop repeats indefinitely, creating the illusion of a simultaneous 3D world.
3. The Nature of Time (Permanent Overwrite)
Time is the memory of the execution. As the "read-head" of the universe moves along the pre-existing path, it performs a permanent overwrite. The past is "deleted" from the hardware to make room for the next beat, explaining the Arrow of Time—you cannot go back because the previous state no longer exists.
4. The Origin of Force (Tensional Limits)
Physics is defined by Constraints:
Speed of Light (
): The maximum distance a particle can move during one 1-2-3 loop. It is the "bandwidth limit" of the refresh rate.
Gravity/Inertia: If a path is "bundled" or dense, the refresh rate struggles to clear the data, creating Tension. We perceive this tension as mass or the "warping" of space.
Strong Nuclear Force: The maximum elastic limit of the loop. Quarks are held together because they cannot exceed the "distance-per-beat" limit without snapping the local 1-2-3 synchronicity.
5. The "Diametric" Breakthrough
The term refers to the Symmetry of the Cycle. If you can align or "synchronize" the beats of two separate paths (like two protons), the tension (Coulomb Barrier) vanishes. This suggests a path to Low Energy Nuclear Fusion by manipulating the "sound" or frequency of the universal clock rather than using raw heat.
Physics Community Scorecard
Logical Consistency: High. It provides a mechanical "Why" for constants like
and the Planck scale.
Mathematical Match: Moderate. It relies on Post-Hoc Fitting of existing numbers (
Planck units) rather than new predictive formulas.
Experimental Traction: Fringe. No current instruments (like LIGO or the LHC) have detected the 1-2-3 "flicker" or "jitter" that such a discrete system would produce.
by alpaca128 | 2026-02-22 13:24:40+00:00
> Every video that has sponsors has a disclaimer on it

No. That's what should be the case, but there are entire channels which don't do that or only half-ass it, and I've seen reviewers who just quickly say "thanks to <company> for their support" in the last 10 seconds of the video because they know no one pays attention anymore at that point. Quite a few review channels also do not correctly communicate that the links in the description are affiliate links etc.
by roryirvine | 2026-02-22 13:24:54+00:00
To be fair, there are still plenty of people on HN talking about lack of battery capacity as a reason to delay solar/wind rollout; I suspect it'll take a bit more time for the new reality to sink in fully.

The fossil industry was always suspiciously keen on green hydrogen - partly because the path to green hydrogen would likely have involved a long detour through grey and blue hydrogen, and partly because it gave them an excuse to lobby against phasing out natural gas for domestic heating/cooking ("we need to retain that infrastructure to enable the hydrogen economy!").

You can see the same thing happening in their support for Carbon Capture and Storage - "we're going to need the oil producers to enable carbon sequestration, so we might as well keep drilling new wells to keep their skills fresh!"...
by appsoftware | 2026-02-22 13:25:08+00:00
This is a walkthrough of my set up of local LLM capability on a Lenovo ThinkPad P1 Gen 4 (with a RTX A3000 6GB VRAM) graphics card, using Ollamafor CLI and VS Code Copilot chat access, and LM Studio for a GUI option.

My Lenovo ThinkPad P1 Gen 4 is coming up for 4 years old. It is a powerful workstation, and has a good, but by no means state of the art GPU in the RTX A3000. My expectation is that many developers will have a PC capable of running local LLMs as I have set up here.

See the GitHub repository for the full walk through:

https://github.com/gbro3n/local-ai/blob/main/docs/local-llm-...

Ref: https://www.appsoftware.com/blog/local-llm-setup-on-windows-...
by hluska | 2026-02-22 13:25:11+00:00
I log into LinkedIn approximately once every five years. While this is apparently ‘career suicide’, I have never lost an opportunity as a result.

Serious question:

Why do we keep putting up with this bullshit? Of course they share data and of course Persona does fucked up shit with the data they generate about you. LinkedIn is the same company that leaked everyone’s passwords. There is absolutely no reason to trust LinkedIn besides mass hysteria. Seriously folks; we can all stop using it and then it will die.

In LinkedIn tradition, I should end this with wild claims and hashtags. #LinkedInKickedMyCat #winning #lackofcreativity #bueller.
by fatihpense | 2026-02-22 13:25:12+00:00
I like Anki because it is a calm piece of tech. It has been there for a long time with the same behavior. There is a merit to its boringness. You can also activate FSRS algorithm for supposedly better spaced repetition in profile/deck settings. This was an interesting read: https://github.com/open-spaced-repetition/fsrs4anki/wiki/Spa...
by rhubarbtree | 2026-02-22 13:26:32+00:00
AI assisted coding is going to make it easier to create software. Developers will be more productive. Non developers will be able to create some stuff.

What this means is that very simple apps will become easy to create quickly. So a todo manager is probably not going to be a very successful business. You’ll be competing with many many people and it will be commoditised.

But ultimately what happens here is the “complexity threshold” of a sufficiently complex product needed to make money will be raised. Existing products will become more sophisticated or, if there is not more “sophistication ladder to climb” then they will be commoditised.

There’s just no way people are going to vibe all their software, that’s a very self absorbed nerd take. But on the supply side we’ll see commoditisation, price drops, and increasingly good value for the user as features are shipped faster.

I also think that software quality is really going to tank, because using validation to test the output of Claude is not a good way to ensure quality or correctness. It’ll get you some of the way but you need powerful reasoning. The most obvious evidence for this is security flaws in AI code. We’ll see a new era of enshitification caused by AI code. Like outsourced manufacturing though, people will buy worse stuff at a cheaper price. That makes me sad, because I thought we were on a path to better software, not buggier software.
by remix2000 | 2026-02-22 13:26:45+00:00
Who isn't collecting biometric data using shady sites nowadays? Even Hetzner wanted to match my id with a selfie using some really shady site that almost certainly violates gdpr… What's next, will I have to send a stool sample to view posts on Twitter?? Funny how that's not even unlikely nowadays, with slippery slope becoming less of a fallacy and more of a universal law…
by PaulKeeble | 2026-02-22 13:26:58+00:00
"Over time, my timeline contained fewer and fewer posts from friends and more and more content from random strangers. "

It still baffles me that Facebook fills up my feed with random garbage I have no interest in. I barely use it now because their generated content gets in the way of the reason why I opened facebook to begin with. These algorithmic feeds clearly work for someone but its not what I am looking for, I want to see what I follow and nothing else unless I explictly go looking for it.
by adrian_b | 2026-02-22 13:27:26+00:00
For that purpose and for long-term storage of energy and for aircraft/spacecraft, synthetic hydrocarbons are much better.

Making synthetic hydrocarbons was already done at large scale during WWII, but it was later abandoned due to the availability of very cheap extracted oil.

So when oil was not available, the economy could still be based on synthetic hydrocarbons even with the inefficient methods of that time (it is true however that at that time they captured CO2 from burning coal or wood, not directly from the air, where it is diluted).

Today one could develop much more efficient methods for synthesizing hydrocarbons from CO2 and water, but the level of investment for such technologies has been negligible in comparison with the money wasted for research in non-viable technologies, like using hydrogen instead of hydrocarbons, or with the money spent in things like AI datacenters.
by yonatan8070 | 2026-02-22 13:27:28+00:00
It's likely possible to extract model weights from the chip's design, but you'd need tooling at the level of an Intel R&D lab, not something any hobbyist could afford.

I doubt anyone would have the skills, wallet, and tools to RE one of these and extract model weights to run them on other hardware. Maybe state actors like the Chinese government or similar could pull that off.
by sanskritical | 2026-02-22 13:27:54+00:00
Someone already mentioned the hoarderware issue, which is big for me, so I'll give my other concern.

Years ago on Twitter I believe it was lcamtuf that asked "Would you pipe a text file into less?" and Dan Kaminsky (RIP) replied -- "Not now that you asked if I would, no." The obvious implication is that people largely didn't think of simple text parsing utilities as places of concern for security issues, but that is not really in line with reality. I work with crypto and it seriously matters if I got owned in that I can lose amounts of money entrusted to me that I could never hope to recover or repay. I believe it is a basic fiduciary duty to use as much code as possible written in safer languages. Sublime Text is a massive C++ app and I can't look at the code. I am going to preferentially treat the Rust app as better. There's plenty of CVEs in editors. If I could I would replace every binary written in an unsafe language on every machine I ever use.

My editor touches every bit of infrastructure I have. I use it every day to change the behavior of production machines. I have no choice to treat my editor as trusted. So it needs to be trustworthy to the maximum degree possible.
Ask HN: How do you track 2026 AI price wars? I built a tool to help
by TokenCost | 2026-02-22 13:28:10+00:00
"I built https://tokencost.is to solve a recurring headache: manually scraping dozens of provider pages just to estimate API spend for my agentic workflows.

My goal was a neutral, minimalist utility in the vein of Time.is. We now track 44 models—including OpenAI, Anthropic, Google, DeepSeek, Mistral, and Cohere—with hourly updates.

Key Features:

Real-Time Latency: We track TTFT benchmarks (e.g., Llama 3.1 at 28ms) alongside pricing.

Price Deltas: We track 24h market shifts; look for the ↑↓ indicators in the table to see how the 'AI Price War' is moving.

Multimodal Calculator: Handles Text, Audio, and Video tokens in a single UI.

100% Neutral: No affiliate bias or listing fees. Just raw data scraped hourly.

I’m not a developer by trade, so I used an agentic workflow to build the backend and scrapers. I found that being the 'product owner' rather than the 'coder' actually helped me focus on the data integrity and the specific multimodal features I needed for my own work.

I'd love to hear what other 2026 models or enterprise benchmarks the community would like to see indexed next!"
by barnacs | 2026-02-22 13:29:17+00:00
Every time you introduce a type for a "value invariant" you lose compatibility and force others to make cumbersome type conversions.

To me, invalid values are best expressed with optional error returns along with the value that are part of the function signature. Types are best used to only encode information about the hierarchy of structures composed of primitive types. They help define and navigate the representation of composite things as opposed to just having dynamic nested maps of arbitrary strings.
by strogonoff | 2026-02-22 13:30:48+00:00
When learning, motivation is first, everything else follows.

At some point I felt the drive to move on from Python as my main language. There was no question of “how”: when I needed or wanted to build anything, I would simply go with Go (later TypeScript) and plow on. It is hard to pinpoint exactly what motivated that drive, but I think it was probably curiosity after seeing examples in other languages, wanting to be more competitive, and—let’s be honest—the basic desire to feel a little cooler in the eyes of peers.

Be mindful of second-order volition here. Like when someone says “I want to quit %BAD_HABIT%”, what they really say is “I want to want to quit %BAD_HABIT”—if they really wanted to quit, they would have already done it. Similarly, if you want to learn a programming language, you are all set (unless it is so esoteric that there are no suitable resources or references, which never happens), but if you want to want to learn a programming language then what you need is some lateral move (tricking yourself, putting yourself in some situation, etc.) that makes you actually want to learn it.

These days learning a new programming language is a more sketchy question, because LLMs drain a few major sources of motivation: you can hardly feel cool for knowing how to program in a new language, because anyone would rightfully assume it was written with an LLM; you increasingly do not actually need to know a language, because a model writes everything for you; the competitive advantage is decreasing. Unlike speaking some human language, there is no society of native speakers that would accept you more or treat you better thanks to you speaking their language.
by creamyhorror | 2026-02-22 13:32:22+00:00
I was always perturbed by the shift from calling them "social networks" to "social media". It signalled a friends-to-famous shift (plus ads) that I didn't particularly want.

Why fill my personal feed with stuff I normally get on dedicated discussion/news sites? (Rhetorical; it's obvious why.)

They still call it SNS (social networking service) in Japan. We need to keep moving to a new iteration of this - hopefully one that funnels less money and influence to a small group of players. (I'm working on my own ideas for this.)
Show HN: RMirror Cloud – Open-Source OCR and Notion Sync for ReMarkable Tablets
by gottino | 2026-02-22 13:32:36+00:00
I built an open-source cloud service for reMarkable tablets that does three things:

Syncs notebooks from your reMarkable to the cloud via a macOS background agent
Runs AI-powered OCR on handwritten pages (Claude API, not Tesseract)
Pushes transcribed notes to Notion as searchable pages
Stack: FastAPI backend, Next.js dashboard, Python agent. Self-hostable.
The reMarkable's handwriting recognition (via Connect) is okay for typed-looking text but struggles with real handwriting. I wanted something better that also gave me web access to my notes and pushed them to Notion where I actually work.

GitHub: https://github.com/gottino/rmirror-cloud
Request beta access: https://rmirror.io/

Looking for beta testers — especially people with messy handwriting.
by Arech | 2026-02-22 13:32:45+00:00
Thanks, this is a very interesting topic.

What I personally would like to see is some kind of quantization of how the biases that the author talks about (such as insufficient seed volume of a PRNG) affects computed p-values. Specifically, why there must no "cancellation of errors" happen? So far, IIUC, the author only shows theoretical possibility of errors, but what's more interesting is a real effect. When it all boils down to a p-value being less than a certain threshold (choosing which is another pita), it might not matter whether a true p-value is within, say, 2^-16 from the computed.
by DrewADesign | 2026-02-22 13:33:13+00:00
Considering anybody with a noggin is going to be separating the SQL into it’s own module or whatever rather than just throwing straight inline SQL at your database wherever you it, you’re hardly less likely to have things like accidental writes, anyway. This is clearly someone who fell in love with Postgres, felt ORM abstractions that diluted the Postgres goodness were bad, and then did some mental experiments to consider all of the theoretical ways ORMs suck.