MurphyA/hacker-news huggingface dataset:
Show HN: AIWriteBook – AI tool to write, design, and publish full-length books
by marakaci | 2026-02-15 11:27:52+00:00
hey HN, I built this. AIWriteBook takes you from a book idea to a finished, publishable book (outline, chapters, cover, illustrations, audiobook, and KDP ready export) in one tool.

You can try it right away: the free tools (title generator, plot generator, character creator) work without signing up. Also, free account gives you a full 7 chapter book, no credit card.

I run a small publishing platform (NanoReads, 130+ published books, 341K readers). I kept seeing authors juggle 5 to 7 tools to publish one book: outliner, writing tool, Vellum ($250) for formatting, cover designer, TTS for audiobooks, keyword tool for Amazon. Nothing covers the full journey.

How it works: you enter a title and basic info. AI generates a structured outline with characters (arcs, motivations, voice) and a chapter by chapter story bible (events, locations, twists). You edit the outline (most important step). AI writes chapters one at a time using only the relevant character data and chapter spec. You can upload writing samples so it matches your voice. Then generate a cover, add illustrations, convert to audiobook, export as PDF/EPUB/DOCX.

Some technical details: we treat it as a compiler pipeline. Book metadata → character graph → chapter outlines → chapter content. Each step uses schema constrained structured output. Two model strategy: Gemini Flash for structural work (fast, cheap), frontier model for chapter prose (quality matters). Voice calibration uses writing samples as few shot examples plus extracted style features. Fiction and nonfiction have separate architectures. Fiction uses character graphs + plot continuity, nonfiction uses reference material extraction with citation tracking.

After 50K+ books: chapter sweet spot is 2,000 to 3,500 words. Outline detail sweet spot is 150 to 300 words per chapter. Romance and thriller generate well, literary fiction and humor are hard. Practical limit around 15 to 20 characters per book.

Stack: Next.js + Supabase. 30+ languages.

Happy to answer questions about the architecture, publishing space, or anything else.
by nephihaha | 2026-02-15 11:27:53+00:00
Star Trek at the time had better effects (including DS9, even though I prefer B5!).

The trick with effects is to make whatever you have look good. There are a few ways of doing that. 2001's effects are genius and still look pretty good nearly sixty years later. They look better than 2010's from the 1980s. In fact, I'm even impressed with Forbidden Planet — yes, there are a lot of painted backgrounds but it does very well with what it has.
by lucideer | 2026-02-15 11:28:26+00:00
Gentoo's wiki is still great (& Arch's has been great for a long time), but yes, Arch's is probably improving at a faster rate. Arch is also a little more comprehensive when it comes to mainstream tech that's divergent like init & network management - Gentoo's still good here but openrc & netifrc show their influence throughout.
by Sean766 | 2026-02-15 11:28:52+00:00
SQLModel is an open-source, in-browser data modeling tool designed to make data modeling fast, visual, and collaborative.

Recent updates include:

Direct imports from Snowflake, PostgreSQL, MySQL, Oracle, Rails & Prisma

Schema import + reverse engineering

AI-assisted model generation & refinement

Improved DDL export and diagram performance

Cleaner UX and better relationship handling

The goal is simple: make data modeling lightweight, shareable, and actually enjoyable — without installing heavyweight desktop tools.

Would love feedback from engineers, data teams, and architects.
https://www.sqlmodel.org/
by delusional | 2026-02-15 11:29:12+00:00
> but it is better understood as exploiting the natural lack of verification in the GitHub web interface, which doesn’t show the authentic (and in this case malicious) source of a module version, as used by actual Go tooling.

That's a load of crap. It can never become a github issue that the Go ecosystem has chosen to make it look like the packages you pull come from github, but are actually diverted to be served by Google from some strange pull-through cache.

Calling this a "lack of verification in the GitHub web interfaces" completely inverts the abstraction layers and asks GitHub to implement specific features for your incorrect usecase.

Then there's the misnomer of a hash database being anywhere close to analogous to PGP signed sources. This is amateur level stuff.
by 0xecro1 | 2026-02-15 11:30:48+00:00
18 years in embedded. Yes to all three, with caveats.

1. The pattern is real. I write specs and prompts between meetings, agents deliver code by EOD. But deep focus blocks aren't dying, they're shifting from "writing code" to "thinking about architecture and verifying output."

2. Merging, yes. Decreasing value, no. The role is evolving from "person who writes code" to "person who defines what correct looks like." The engineers who thrive will be the ones who can do both — manage agents AND know when the output is wrong. That requires more expertise, not less.

3. Overfitted to Claude Code? Probably a bit. But the delegating to AI agents instead of typing code yourself is tool-agnostic. Cursor, Copilot, Claude Code, whatever comes next. The workflow shift is real regardless of which tool wins.
by RobotToaster | 2026-02-15 11:30:59+00:00
>One study in 2020 found that 95% of asymptomatic patients had some type of "abnormal" finding, but just 1.8% of these findings were indeed cancer.

That can also be reframed as 1.71% of asymptomatic people having cancer, which is a really good argument for better screening.
by mso3i | 2026-02-15 11:32:49+00:00
This is a natural pattern. Treat "coding is becoming accessible to everyone" as writing or reading has become accessible to everyone.

Coding was just a mechanism/tool developed to talk more efficiently to machines. We did it with binary, assembly etc once upon a time. Then it got easier and easier. Less people use the older mechanisms. But the tool was never the point of the story. Talking to the machine to get something done was the point of the story. Just like human language emerged to help move info from one 3 inch chimp brain into another so they could work together more smoothly.

At the end of the day the story is never about a specific tool like Software. It has always been about what problem the tool can be used to produce solutions.
by bananaflag | 2026-02-15 11:33:13+00:00
> Robots are improving fast, but I do not believe that this cute fellow will be stuffing envelopes or affixing stamps anytime soon.

Well, the one and only thing which is constantly improving robots is human ingenuity, and if that is replaced by (yes, symbols-in, symbols-out) artificial superintelligence, I expect that improving to improve quite fast.
by cyphar | 2026-02-15 11:34:17+00:00
> Piltdown was rejected 70 years ago, so hardly a current example

Well of course it wasn't a current example -- to quote their original comment:

> Quite frustrating how archeology swings over the years from "we'll believe anything" to "we won't accept any claim without a preserved example". While some of the excesses of the past were clearly excessive ... [emphasis added]

In other words, they feel that historical examples of fanciful theories being mainstream has resulted in an over correction to modern archeology requiring unreasonably strict proof standards.

(There is a certain irony in a user called "AlotOfReading" not reading a fairly short comment carefully...)
Show HN: Dw2md – Compile all DeepWiki pages into a single, LLM-friendly file
by nwyin | 2026-02-15 11:36:25+00:00
LLMs seem to generate much better specs for me when they have access to higher-level architecture docs for systems. Built this tool to take DeepWiki generated articles and format them nicely for tools like Claude Code and Codex to grep through easily.
by KronisLV | 2026-02-15 11:37:29+00:00
> Trading portfolio -5.55% ($94,454 / $100,000)

If true, then in a few months we might see a post on /r/wallstreetbets.

Either way, pretty cool site and idea! The most I've considered is a more economical version of Gas Town for development and parallel tasks - think Jenkins but for AI (except without it being "Jenkins"). Though the Claude Code desktop app does pretty much that for me, more convenient than multiple open terminals.
by as1mov | 2026-02-15 11:38:18+00:00
Somebody already mentioned the Winnie's Homerun Derby.
I also have fond memories of playing:

* N - https://archive.org/details/nv-12

* Ball Revamped - https://archive.org/details/1100_ballrevampedv2

* Mind Fcuk - https://archive.org/details/tf_20210127

* World's hardest game - https://archive.org/details/the-worlds-hardest-game_202310

* Canabalt - https://archive.org/details/canabalt_202012

* (If you're from one of the commonwealth countries) Stick Cricket - https://archive.org/details/stickcricket_flash

There's honestly a ton more, you can download the archive and go through the various community lists in there. I've spent a few evenings just having a few drinks and playing some old games! :D
by post_below | 2026-02-15 11:39:12+00:00
You can expand it beyond novel applications. The models aren't good enough for autonomous coding without a human in the loop period.

They can one shot basic changes and refactors, or even many full prototypes, but for pretty much everything else they're going to start making mistakes at some point. Usually very quickly. It's just where the technology is right now.

The thing that frustrates me is that this is really easy to demonstrate. Articles like this are essentially hallucinations that, at least many, people mystifyingly take seriously.

I assume the reason they get any traction is that a lot of people don't have enough experience with LLM agents yet to be confident that their personal experience generalizes. So they think maybe there are magical context tricks to get the current generation of agents to not make the kinds of mistakes they're seeing.

There aren't. It doesn't matter if it's Opus 4.6 in Claude Code or Codex 5.3 xhigh, they still hallucinate, fail to comprehend context and otherwise drift.

Anyone who can read code can fire up an instance and see this for themselves. Or you can prove it for free by looking at the code of any app that the author says was vibecoded without human review. You won't have to look very hard.

Agents can accomplish impressive things but also, often enough, they make incomprehensibly bad decisions or make things up. It's baked into the technology. We might figure out how to solve that problem eventually, but we haven't yet.

You can iterate, add more context to AGENTS.md or CLAUDE.md, add skills, setup hooks, and no matter how many times you do it the agents will still make mistakes. You can make specialized code review agents and run them in parallel, you can have competing models do audits, you can do dozens of passes and spend all the tokens you want, if it's a non trivial amount of code, doing non trivial things, and there's no human in the loop, there will still be critical mistakes.

No one has demonstrated different behavior, articles and posts claiming otherwise never attempt to prove that what they claim is actually possible. Because it isn't.

Just to be clear, I think coding agents are incredibly useful tools and I use them extensively. But you can't currently use them to write production code without a human in the loop. If you're not reading and understanding the code, you're going to be shipping vulnerabilities and tech debt.

Articles like this are just hype. But as long as they keep making front pages they'll keep distorting the conversation. And it's an otherwise interesting conversation! We're living through an unprecented paradigm shift, the field of possibilities is vast and there's a lot to figure out. The idea of autonomous coding agents is just a distraction from that, at least for now.
by bonsai_spool | 2026-02-15 11:41:09+00:00
That’s not the correct framing - your assertion first lacks evidence about why we should screen better. In fact, we aren’t improving longevity in many early diagnoses, and may be treating people whose immune system would resolve the cancers.

Further, the denominator is asymptomatic people who were able to get MRI’s they didn’t need. That doesn’t tell us anything about the normal world.
Show HN: Boredom Challenge – Test and Improve Your Boredom Tolerance
by jsattler | 2026-02-15 11:42:28+00:00
Boredom is uncomfortable but important. I built a neat little website to test and improve your boredom tolerance. Data stays in your browser or can be exported/imported. Website is open source: https://github.com/jsattler/boredom-challenge
by DonHopkins | 2026-02-15 11:42:53+00:00
RMS draws a distinction about when it's ok to just say "Linux". We were just discussing the concept of "retrognuification", where a someone (like a parrot) can travel back in time the length of time it takes to say "Linux", then insert "GNU/" into the conversation.

From: Richard Stallman <rms@gnu.org>
Subject: Re: RETROGNUIFICATION special magical parrot power!
Date: 3 February 2026 at 04:32:41 GMT+1
To: Don Hopkins <don@donhopkins.com>
Cc: rms@gnu.org

[[[ To any NSA and FBI agents reading my email: please consider ]]]
[[[ whether defending the US Constitution against all enemies, ]]]
[[[ foreign or domestic, requires you to follow Snowden's example. ]]]

I don't entirely get the joke. It seems to refer to a specific context
and I have no idea what that context is.

But it is not correct to insert "GNU/" before every uttering of "Linux".
Linux and GNU/Linux both exist and are different. Imagine if you said,
"Linux as released contains binary blobs; to make a free version, we
release a version that doesn't have them, which we call Linux-libre,"
and this parrot changed that to
"GNU/Linux as released contains binary blobs; to make a free version, we
release a version that doesn't have them, which we call GNU/Linux-libre."
That statement is incorrect.

--
Dr Richard Stallman (https://stallman.org)
Chief GNUisance of the GNU Project (https://gnu.org)
Founder, Free Software Foundation (https://fsf.org)
Internet Hall-of-Famer (https://internethalloffame.org)

The specific context: a Parrot named Copyleft, a familiar of StIGNUcius, who knows how to quote RMS and explain his philosophy:

https://github.com/SimHacker/tmnn7-8/blob/main/analysis/char...

I accepted his bug report and patched the parrot to follow his GNU/Linux naming protocol.

Thank you for reporting the bugs in the parrot, Richard!

I have applied the following changes:

- Updated the parrot rules in tmnn7-8/analysis/characters/StIGNUcius/parrot-copyleft.yml to follow RMS’s instruction:

- retrognuification only happens when “Linux” clearly refers to the whole OS, and it explicitly does not rewrite kernel-only or Linux‑libre statements.

- What changed and why:

- Clarified the trigger to require OS‑meaning context, not every “Linux” utterance.
- Added explicit DO / DO NOT examples, including the RMS Linux‑libre case.
- Made ambiguity resolve to a clarification instead of a rewrite.
- Tightened the squawk rule to avoid kernel/Linux‑libre rewrites.

https://github.com/SimHacker/tmnn7-8/commit/4c7eab3e8e470410...
by jackfranklyn | 2026-02-15 11:43:11+00:00
I build accounting automation tools and this resonates hard. The codebase has ~60 backend services handling things like pattern matching, VAT classification, invoice reconciliation - stuff where a subtle bug doesn't crash anything, it just silently posts the wrong number to someone's accounts.

Vibe coding would be catastrophic here. Not because the AI can't write the code - it usually can - but because the failure mode is invisible. A hallucinated edge case in a tax calculation doesn't throw an error. It just produces a slightly wrong number that gets posted to a real accounting platform and nobody notices until the accountant does their review.

Where I've found AI genuinely useful is as a sophisticated autocomplete. I write the architecture, define the interfaces, handle the domain logic myself. Then I'll use it to fill in boilerplate, write test scaffolding, or explore an API I'm not familiar with. The moment I hand it the steering wheel on anything domain-specific, things go sideways fast.

The article's point about understanding your codebase is spot on. When something breaks at 2am in production, "the AI wrote that part" isn't an answer. You need to be able to trace through the logic yourself.
by dragonman | 2026-02-15 11:43:23+00:00
Hey,

I created a very simple, lightweight tool to check the security of your web application.
It includes checks for:

- SSL cert's
- HTTPS redirection
- Seurity headers
- Mixed content
- HTTP/3 support
- CAA and DNSSEC

It's free. No registration required.
Check it out: https://httpsornot.com

You can exports results in pdf or csv.
Reports are publicly available, example: https://httpsornot.com/report/google.com

I am currently working on exposing the API. It will be public, with a free plan that allows a limited number of checks per month at no cost.
by chairmansteve | 2026-02-15 11:44:08+00:00
"Not sure how to get progress".

Maybe make small audio recordings and get them transcribed?

Or a notebook and scribble out all thoughts by hand?

Just get all your thoughts out of your head onto "paper" is the first step. Don't even think about the second step yet.

"The journey of a thousand miles begins with the first step". - Lao Tzu
by KronisLV | 2026-02-15 11:45:51+00:00
> However, it is important to ask if you want to stop investing in your own skills because of a speculative prediction made by an AI researcher or tech CEO. Consider the case where you don’t grow your software engineering or problem-solving skills, yet the forecasts of AI coding agents being able to handle ever expanding complexity don’t come to pass. Where does this leave you?

The current Claude Code setup with Opus 4.6 and their Max subscription (the 100 USD one was enough for me, don't need the 200 USD one) was enough for me to do large scale refactoring across 3 codebases in parallel. Maybe not the most innovative or complex tasks in absolute terms, but it successfully did in one day what would have taken regular developers somewhere between 1 and 2 weeks in total.

I hate to be the anecdote guy, but with the current state of things, I have to call bullshit on the METR study, there is no world in which I work slower with AI than without. Maybe with the Cerebras Code subscription where it fucked some code up and I had to go back to it and fix it twice, but that's also because Vue had some component wrapping and SFC/TypeScript bullshit going on which was honestly disgusting to work on, but that's because you really need the SOTA models. The current ones are good enough for me even if they never improved further.

I never want to go back to soul sucking boilerplate or manual refactoring. It works better than I can alone. It works better than my colleagues can. I think I might just suck, maybe I'm cooked because at this point I mostly just guide and check it and sometimes do small code examples for what I want and explore problems instead of writing all of it myself, but honestly a lot of work was done in JetBrains IDEs previously where there's also lots of helpful snippets, autocomplete, code inspections and so on, so who knows - maybe it doesn't matter that I write everything line by line myself.
by mft_ | 2026-02-15 11:46:57+00:00
> So how much internal memory does the latest Cerebras chip have? 44GB. This puts OpenAI in kind of an awkward position. 44GB is enough to fit a small model (~20B params at fp16, ~40B params at int8 quantization), but clearly not enough to fit GPT-5.3-Codex. That’s why they’re offering a brand new model, and why the Spark model has a bit of “small model smell” to it: it’s a smaller distil of the much larger GPT-5.3-Codex model.

This doesn't make sense.

1. Nvidia already sells e.g. the H100 with 80GB memory, so having 44GB isn't an advance, let alone a differentiator.

2. As I suspect anyone that's played with open weights models will attest, there's no way that 5.3-Codex-Spark is getting close to top-level performance and being sold in this way while being <44GB. Yes it's weaker and for sure it's probably a distil and smaller, but not by ~two orders of magnitude as suggested.
by andai | 2026-02-15 11:47:01+00:00
Interesting theory. So how does ChatGPT begin responding instantly, as soon as I send the message? Shouldn't it need to wait for the batch to fill? Or do they have so much traffic that this happens in a few ms?

(I think they might also be filling the message onto a GPU while you're typing over a websocket or something, but I'm not sure.)
by metalman | 2026-02-15 11:47:30+00:00
NewPipe works good enough, learned here that "was able to get it working again immediately by simply changing the www.youtube.com IPv4 address", is a fix for
it breaking, not that it fusses me as watching vids is a very low priority for me, though sometimes a video that tells me which wire to cut first, is invaluable and has saved my sorry ass.Which sometimes I wish there was a similar way to make, edit and upload videos useing nothing but a cheap phone.
Show HN: Custom illustrated kids' book, generated and printed (StoryStarling)
by storystarling | 2026-02-15 11:48:19+00:00
Hi HN, I built StoryStarling. You describe a story idea and it generates a complete illustrated children's book, then prints and ships it.

Every story, character, and illustration is generated from scratch, not a template with a name swapped in. Most books are about a new character your child can identify with: a raccoon starting kindergarten, a knight rescuing the Internet Connection, a superhero with an insulin pump. You can upload a photo and the system will convert your child into the chosen illustration style as a character, but more often it's the story itself that makes it personal.

A few examples from our showcase (storystarling.com/en/showcase):

- A boy obsessed with elevators visiting magical floors: candy floor, dinosaur floor, space floor

- A girl with hearing aids who can hear animals' thoughts, bilingual Polish/English

- Vim vs Emacs, but they're two wizards casting spells. "Choose your weapon wisely."

Bilingual books in 38 languages. Pick a main language and an optional translation and the full book renders in both. We handle RTL scripts like Arabic and Hebrew (right-to-left text, but left-to-right page order so bilingual layouts work naturally) and CJK typesetting. We also support less common languages like Estonian, Maltese, Irish, and Low German where children's book options are limited.

How it works: Type anything from a two-word idea ("dinosaurs soccer") to a detailed storyline, pick a style (~20 styles), choose languages, optionally upload reference photos, and hit generate. You get a free preview with the cover and synopsis, no payment required. If you like it, the full 28-page book generates and you review it in a flipbook viewer. Edit text and regenerate pages before approving, then it goes to print. Booklet (~20 EUR) or hardcover (~40 EUR), shipping included, 3-7 days in the EU.

I'd love to hear what stories you'd make.

https://storystarling.com

Free printed book including shipping (EU only, booklet format, in-house printing in Germany): voucher HN022026, 1 per person, valid February 2026.
by hnlmorg | 2026-02-15 11:48:30+00:00
People are just lazy. It’s got nothing to do with LLMs having more trust because they’re a machine because most people would happily trust their friend over an expert. They’d trust the first blog post they find online over an expert. Most people are just too lazy and not skilled enough to perform independent review.

And to be fair to those people, coming to topics with a research mindset is genuinely hard and time consuming. So I can’t actually blame people for being lazy.

All LLMs do is provide an even easier way to “research”. But it’s not like people were disbelieving random Facebook posts, online scams, and word-of-mouth before LLMs.