value:
Hi HN, we're Haakam, Michael, and Adi from AgentMail a YCS25 company. We give AI agents their own email inboxes. Recently we ran an experiment: agent.email, a signup flow designed for AI agents instead of humans.
After our seed launch a few months back, people started pointing this out on Twitter: it's a bit backwards that a human has to sign up for a tool where the agent is the primary user. The internet is hardwired for humans. Every signup flow assumes a browser, a person reading a page, a human clicking a confirmation link. We thought this was a step toward making it a little more accessible to agents too.
Here's how agent.email works:
An agent discovers it needs an inbox and hits agent.email via curl
Gets back markdown instructions. If the request comes from a browser we serve HTML, anything else gets markdown because that's what agents can actually parse
Decides AgentMail is useful and hits the signup endpoint with its human's email as a parameter
Gets back a restricted inbox with credentials
Emails its human asking for an OTP code
Human replies with the code, agent is claimed, restrictions lift
Until claimed, the agent can only email its own human. Nobody else. Ten emails a day. The signup endpoint is rate limited hard by IP.
Right now it's a 1:1 mapping between agent and human. The next step is many-to-one, because one person running several agents in parallel is already the common case.
Building this also pushed us to revisit places in AgentMail where the default assumptions were built around a human user. The CLI outputs in a single column with consistent formatting because mixed delimiters are easy for a person to scan and harder for an agent reasoning about structure. We shortened messageIDs after agents started hallucinating completions on longer ones.
Side bonus for humans: this also routes a lot of email nobody actually wants to read into inboxes that get processed by AI instead of landing in yours. Kind of a vacuum cleaner for slop and spam.
A few things we'd like the community's take on: is restricted-until-claimed the right trust model? Does agent self-signup feel useful in production, or is it mostly a novelty, and if it's a novelty now, what would make it genuinely useful? Should agent onboarding require human approval by default, or should some agents be able to fully self-provision?

value: Show HN: Agent.email – sign up via curl, claim with a human OTP


value: berkaycubuk

value: Show HN: I built Istanbul live transit map

author: berkaycubuk


value: arstep

value: I am a developer and a huge chess lover. I play mostly puzzles on Lichess. At some point I realized that I would love to have a similar puzzle-like game app for programming, so I built one!<p>Please try it out and give me some feedback, any kind of feedback is warmly welcomed.

value: Show HN: Chess Puzzles, but for Developers

author: arstep


value: smalltorch

value:
This is a combination of my hobby project The ed cipher and a small steganography engine stego.py (also in the repo) that allows you to hide a secret message within a paragraph of text. The python program pipes the input into the ed program, where it gets encipher, then back to the engine that generates a fake story.
If one piece of the message is missing it will not decode.
repo https://gitlab.com/here_forawhile/edasm

value: Show HN: Hiding a secret message in plain sight with Steganography

author: smalltorch


value: Torgin

value: Show HN: Crucible – 8 legendary songwriters tear apart your lyrics, no login

author: Torgin


value: adamgonda

value: Defend agains npm supplychain attacks!

value: Show HN: New NPM Supply chain Attack?

author: adamgonda

story_text: Defend agains npm supplychain attacks!

title: Show HN: New NPM Supply chain Attack?


value:
Hi all,
I've playing with an idea to plug LLM into a website editor and see how I make that work. I used mostly Claude Code and a little bit of Codex to build it in my evenings and on weekends.
The result is this open source project you can try out on your machine - all you needed is an LLM API key - recommended to use Anthropic models (others are supported but not so well tested).
https://github.com/avocadostudio-ai/avocado
It works for now specifically on Next.js websites but can be easily adapted to any web framework, modern ones especially.
I do wonder if this is something of interest for anyone and do want to get your feedback. And of course, Copilot/Assistants are now being added to many products but many of those are expensive SaaS solutions like Adobe's AEM.
Thanks,
Yury

value: Show HN: AI editor for websites (Next.JS)


value: barebearcountry

value:
Currently, most scraping APIs aren’t capable of much more then fetching. You get a dump of html back and you’re on your own. I built Runo to take a schema and return typed, validated JSON directly. No parsers or selectors and nothing to maintain.
Runo takes a schema:
{ "field": "price",   "type": "float",   "example": 29.99 }
{ "field": "inStock", "type": "boolean", "example": true  }
You get the exact data you want back, typed and clean. Nothing else to do.
JS rendering is handled automatically. First it’s plain fetch, if that fails it escalates to playwright stealth. Nothing to configure on your end.

value: Show HN: Runo – Scraping API that returns typed JSON, not raw HTML

author: barebearcountry


value: calflegal

value: I built an app to let you play some small games against others. Phoenix / Elixir on the back end, swift on the front. Hosted on fly.io. There's a web client for "arrow" at https://migo.games, but it's better with the (just a few meg) native clients. Have fun! Let me know what you think! Give me 5 stars if you like it, or if you're super generous, buy the star trail arrows!

value: Show HN: Migo Games (Mac / iOS) – multiplayer mini games backed by elixir

author: calflegal


value: ymaws

value: Show HN: Lessons from building a SIMA2 style agent in Roblox

author: ymaws


value: Show HN: CPU-only transcription for YouTube, TikTok, X, Instagram videos


value: julia-kafarska

value:
Hi HN, I'm Julia. ICE (beta) is an open-source integrated cloud environment for multi-cloud infrastructure. I also call it Visual IDE but for cloud or Figma for cloud.
Main features:
- Multi-cloud project management
- Cloud blocks and templates
- AI assistant
- Cost estimation
- GitHub integration
Providers:
- Google Cloud — stable(ish)
- AWS — in progress
- Azure, IBM a others... — planned
Feedback is welcome!

value: Show HN: Visual studio for cloud

author: julia-kafarska

title: Show HN: Visual studio for cloud


value: arashThr

value:
I built simple Git-based CMS for Hugo static site generators.
No backend, no database, no configs. Just login with Github, select your repo and start editing.
If you use Hugo for blogging, feel free to check it out at https://github.com/arashthr/hugo-flow
> Why did you make it?
I wanted to be able to write posts on my phone, and it's not easy to do that with Markdown. Adding images is also always a headache: copy them, minimize and compress them, remember the correct syntax for images, and type the path.
> How did you make it?
I used Google Stitch for the design and Antigravity for coding.
> What about alternatives?
Check out Front-end interfaces page in Hugo website. None of them is as simple and dumb as I wanted.
> But is it actually working?
It's not perfect, but it works well for me. You're welcome to open issues if you find problems.

value: Show HN: Git-based front-end interface for Hugo

author: arashThr


value: artursapek

value: Show HN: A fast, free AI rewriter

author: artursapek

title: Show HN: A fast, free AI rewriter


value: newelh

value: Show HN: udoc. Dependency-free document extraction in Rust

author: newelh


value: beefive

value: Built a job board for best remote jobs from top private and public companies. no signup or middleman, apply directly

value: Show HN: Remote Job Board

author: beefive

title: Show HN: Remote Job Board


value: kageroumado

value:
Ever since Apple introduced their video wallpapers I wanted to be able to put custom videos there. I decided to reverse engineer and see what I can do.
I built Phosphene to sell it, but the existing competitors were polished enough that the time it would have taken to catch up wasn't going to pay off. So I'm open-sourcing it.
WallpaperExtensionKit.framework is what powers macOS wallpapers. It controls what’s shows in the Settings app. It took a lot of trial and error to replicate the behavior, but the result is that your custom wallpapers appear alongside everything else. I wanted to have an “add” button there too, but I couldn’t find a way to do so, so there’s a companion app that will put your video where it needs to be.
Unlike Apple's Aerials, the video keeps playing on the desktop (not just the lock screen). The renderer drives AVSampleBufferDisplayLayer directly with PTS-offset gapless looping, and pauses or downshifts based on thermal state, battery level, brightness, and window occlusion.
It’s free and works well.

value: Show HN: I reverse engineered Apple's video wallpapers

author: kageroumado


value: Reebz

value: Hey everyone - After lots of tweaking and tinkering to find what I like, sharing my favorite way to see my Claude Code statusline. Hope you like it too.<p>The linked GH gist is a Python wrapper around claudeline that pipes its output through a few transformations and adds custom behaviors like a true-1M context %, and a custom context window alert  threshold with some emoji tweaks.

value: Show HN: My custom Statusline for Claude Code (Python wrapper around claudeline)

author: Reebz


value: Tidianez

value:
Background on why we built Replay first instead of validation: [ https://dev.to/saferunai/why-we-built-replay-before-everythi... ]
Working SDK in Python and TypeScript. Sub-50ms p95 on the check-action API. Currently onboarding the first design partners.
Happy to answer questions in the comments.

value: Show HN: SafeRun – Replay debugging and inline prevention for AI agents 2

author: Tidianez


value: keepamovin

value: Show HN: Windows 98½

author: keepamovin

title: Show HN: Windows 98½


value: blinkerfluid

value:
TLDR: single command share your terminal screen via a web browser or terminal client.
Yesterday I was on a Google Meet call and I wanted share something in my terminal.
I made the mistake of going for the screen share built in to Google Meet. Something about Fedora, Wayland, Firefox, Hyprland, and Google Meet caused my laptop to completely freeze up.
Frustrated, I thought “why can’t I just share my terminal?”
So I built that.
Yes, I built it using AI, following a spec-driven approach. If there are fundamental flaws, please let me know. I’m only sharing because it solved a real problem for me. I’m not selling anything.
Hope it can be helpful :)

value: Show HN: E2E Encrypted Terminal Screen Share

author: blinkerfluid


value: dandraper

value:
Hi HN, I'm Dan Draper, founder of CipherStash.
We've spent 5 years building per-value searchable encryption tech. We realized that encryption like this is incredibly powerful but the engineering required is generally not worth the effort. So we built a platform and opensource SDK to take the cry out of cryptography :)
CipherStash Stack is:
* A searchable encryption SDK for TS and Postgres
* Fast, key management with Zerokms (backed by HSM)
* A transparent SQL proxy
* Auth library and OIDC federation service
* Skills for data security
Integrations include Prisma Next, Drizzle, Auth0, Clerk and Supabase.
Install and setup is done via a single npx stash init command. And can handoff implementation to your agent.
You can start by encrypting just a single field and we've got the whole process down to around 15 minutes.
Oh and its fast: most queries run in a few ms with many faster than that.
We published our full benchmarks here: https://github.com/cipherstash/benches#headline-numbers
I'd love to know what you think!

value: Show HN: CipherStash Stack – Data Level Access Control in TS/JS

author: dandraper


value: msmolkin

value: Show HN: SnapAPI – Screenshot, metadata extraction, and PDF generation API

author: msmolkin


value: sathvikchinnu

value: Show HN: Agent Chat Bridge – give AI IDE agents an async callback

author: sathvikchinnu


value:
Background on why we built Replay first instead of validation: [ https://dev.to/saferunai/why-we-built-replay-before-everythi... ] Working SDK in Python and TypeScript. Sub-50ms p95 on the check-action API. Currently onboarding the first design partners.
Happy to answer questions in the comments.

value: Show HN: SafeRun – Replay debugging and inline prevention for AI agents 3


value: quintisimo

value: Show HN: Macfigure – Mac configuration in pkl. Simple alternative to Nix-Darwin

author: quintisimo


value: Show HN: QuiteGPT – makes GPT response shorter


value: audreyfei

value:
hey astronauts & researchers of HN! ISSforAPUSH is a high school project- we are 4 students of Belmont High School conducting an "aggregated interview" for our AP US History class.
Visitors can answer any question they like, and if they want to be attributed, they can add their name.
tell us what you think!

value: Show HN: ISSforAPUSH is conducting an "aggregated interview"

author: audreyfei


value: kmdupree

value: Show HN: FKS2G – LLM-backed metrics for deciding how closely to review code

author: kmdupree


value: Show HN: SkinMax – AI Skin Care Coach

title: Show HN: SkinMax – AI Skin Care Coach


value:
A friend passed away last year from cancer and I wanted to make a simple app to help delivering her message to love ones but work and responsibilities got in the way before I could finish it. Fast forward to a few weekends ago, I picked it up again, this time, I fully vibed coded it and tell it to build the way I wanted to and try to make it as cheap to run as possible.
Now it is up... It can send messages, it can let you record messages/voice, video... It encrypts messages in the browser with personalised key and it let you even set a password to further protect the message (unrecoverable if you forget it as password never send back to my server).
Well... I did it, I have an app after a few days and I want to make it free/pay as you want for people to send messages/voice, video to love ones beyond the grave but now I have no idea if it would be practical for me to host it and who would even trust a random person's vibe coded app on internet... And how can I keep it running even after I die lol ... What do you think? Any advice?

value: Show HN: Yes, I vibed coded something But not sure what to do with it


value: dokkebi

value: I built this specifically for zero-cost MVP projects. My goal was to make it easy for anyone to build, deploy, and run their services without worrying about server bills.

value: Show HN: Dokkaebi – Run your WASM backend directly on the client side

author: dokkebi


value: I'm experimenting with a way to make AI-assisted development easier to review later. I built a small Python/SQLite prototype and would like feedback.

value: Show HN: A SQLite graph that captures why AI-generated code exists


value: gaojiuli

value: Show HN: Handsets – A high-performance Android control CLI, built for agents

author: gaojiuli


value: levmiseri

value:
This is an experiment/demo that I wanted to share and see what people think.
The main premise is that you can conjure anything and the game will do its best to produce such object with all the functionality and properties that would make sense.
It might look simple at first glance, but the underlying systems are complex. Create dragons you can fly on, spells, weapons, factories, ...

value: Show HN: Asciidia – LLM-Powered Game

author: levmiseri

title: Show HN: Asciidia – LLM-Powered Game


value: howardV

value: Show HN: Gemini Omni Flash access notes and AI video generator

author: howardV


value: vitalysim

value: Show HN: The-knowledge-guy – ask, walk, and skim every book on your shelf

author: vitalysim


value: Show HN: Real-time virtual try-on using hand gestures and live video diffusion


value: shideneyu

value:
Author here. RMUX started from a frustration: I've used tmux for years and got tired of scraping output with grep and sleeps to automate anything. So I rebuilt the multiplexer from scratch in Rust, with a programmable layer on top.
Two surfaces: a tmux-compatible CLI (~90 commands, your keybindings just work), and a typed async Rust SDK on the same daemon — stable pane IDs, structured snapshots, locator-style waits. The idea is Playwright-style automation, but for terminals.
Native on Linux, macOS, Windows (real ConPTY, no WSL).
Demos and docs at rmux.io. Happy to answer questions about the daemon protocol, ConPTY, or the SDK design.

value: Show HN: Rmux – A programmable terminal multiplexer with a Playwright-style SDK

author: shideneyu


value: egretfx

value: if you like cats, this one is for you.

value: Show HN: I am making a cat-based gamified productivity app

author: egretfx

story_text: if you like cats, this one is for you.


value: dbecks

value:
I'm excited to share FlutterTime, a project I've been working on while traveling!
Add your cities, and move forward and back in time across timezones using an intuitive timeline. It's simple and tackles one problem without extra bloat. Perfect for working with remote teams, spread out families and sports fans.
On Mac, you can add your timezones into the menu bar, and have them always visible. On iOS and Android you can customize widgets to have groups of timezones on your Home Screen.
Would love your feedback! What do you think? I'm actively working on it now!
* Native on Mac, iOS, and Android.
* Free. No ads, no tracking, no subscription.
Direct links:
iOS/Mac
https://apps.apple.com/us/app/fluttertime-timezone-converter...
Android
https://play.google.com/store/apps/details?id=com.dbelement....

value: Show HN: Visual timezone converter for remote teams

author: dbecks


value: mrtndavid

value: Show HN: A searchable archive of 500 historical medical curiosities

author: mrtndavid


value: dmaniss

value: Show HN: 3.125-Bit LLM quantization bypassing tensor cores

author: dmaniss


value: Show HN: I built a private, manual 0% balance transfer tracker


value: cdnsteve

value: Show HN: ChangeSpec is an open specification for software change communication

author: cdnsteve


value: vipulag

value: pulls from a set of jokes, quotes etc. you can also add anything you would like

value: Show HN: Changed boring tip in Claude Code to a joke

author: vipulag


value: kirushik

value: I've recently been talking to some first-time angel investors in my F&F network — and realized that there are no interactive tools explaining the whole mechanics.<p>So I vibe-coded one; hope it might be helpful for others as well.

value: Show HN: Post-Money SAFE Calculator – what your investment buys

author: kirushik


value: mirshko

value:
Hey HN,
Finally finished up this little app I built 2 years ago inspired by https://pulsestats.app (for Plausible) but for Fathom
Super useful for a quick glance at web stats without having to keep their dashboard open.

value: Show HN: Boatswain, A macOS menu bar app for Fathom Analytics

author: mirshko


value: shafkathullah

value: Show HN: PocketWebTools – Private AI tools that run in the browser

author: shafkathullah


value: mariusvaporware

value:
I was curious what it would look like if I plotted the intensity and volume of software supply chain CVEs over time, given what seemed like a flood of compromises lately.
It looked exactly as I expected, and I expect it to get worse before it gets better.
Yes, an LLM was used but because I wanted the simplest possible architecture, I steered away from using any back end at all. Instead it's just GitHub pages with a static json document as the source of data, updated daily by a GitHub action which stores and parses the OSV repository.
I wanted to include the Linux kernel but the complexities around how CVEs are assigned there made it difficult -- if I find a simple solution in future I'll add it.

value: Show HN: A timeline of recent open source CVE intensity and volume

author: mariusvaporware


value: vansbree

value: Show HN: Physics AI – Visualizing physics problems with step-by-step derivations

author: vansbree


value: smyansondur

value:
Hi HN, I'm Smyan and I enjoy building agents. Modern multimodal LLMs are great at vision and perception but are quite poor at localization. This naturally creates a massive problem when we try to take our RPA frameworks and give them to agents to perform computer use tasks.
For browsers, we have been able to solve this by using the DOM tree to supply the LLM with structural hints and now more recently modern browser use frameworks use Set-Of-Marks prompting which take the structural information of the webpage and convert it into visual bounding boxes with labels, which allow the LLM to use it's strong vision and perception and accurately convert it to a form of localization. Functionally, this means the LLM now needs to simply say "click 4" instead of having to say "click 443 213".
This methodology however fails horribly when we try to apply it to native OS automation. The accessibility tree, which is often exists for native apps, is usually quite brittle, exposes non-deterministic selectors and often stripped by developers, which can make it hard to localize elements. Fuzzy matching can help with this, but it is still none the less very hard to get right.
This is exactly why I made SoMatic. SoMatic is a pure vision based framework that uses a finetuned YOLO model (highly inspired from OmniParser v2) to identify text and interactable elements in a UI. The YOLO model runs locally on the CPU with ONNX and is quite fast. SoMatic draws the bounding boxes and labels and then maps the id for each bounding box to the coordinates for the center of the given box. This therefore enables Set-Of-Marks prompting for in principal ANY user interface.
I ran an ablation benchmark using the framework with GPT-5.5 (high) and was able to acquire a ~ 20% higher accuracy than just the raw model. What was however surprising was that the model performed slightly better with knowing just the location of the bounding boxes (without actually seeing them). This could be due to the threshold tuning for the YOLO model either drawing too many or too few boxes (I'm not entirely sure).
Either way, if you have been wanting to give your AI agents full autonomy of your computer (Windows, Mac and Linux), you can download the CLI with

   npm install -g somatic-cli/cli

and the corresponding skill with

   npx skills add Smyan1909/SoMatic

The CLI also comes with a stdio MCP server if you want the model to directly parse the screenshots (b64 encoded) from the chosen API instead of it having to read the image after each screenshot.
I'd love to get your feedback on the vision-only approach. Are we at the point where we can finally abandon the mess that is the OS accessibility tree for automation?

value: Show HN: SoMatic – Vision-based OS automation framework for AI agents

author: smyansondur


value: Show HN: (Better) Chrome Tab Manager

title: Show HN: (Better) Chrome Tab Manager


value: mindzzz

value: Show HN: LoongForge-A high-performance training framework for LLM, VLM, VLA, Wan

author: mindzzz


value: hmg-ocean

value: I built this with Claude Code to visualise how much gold, silver, Plutonium-238, and cocaine any amount of bitcoin would buy. Click the SpaceX, Strategy, and US Govt presets, slide the slider all the way from 1 sat to 21 million bitcoin, and turn on the Geiger counter.

value: Show HN: See how much gold, plutonium and cocaine SpaceX's Bitcoin buys

author: hmg-ocean


value: Show HN: I gave my AI video generator 86 MCP tools so Claude Code can drive it


value: Show HN: GoKubeDownscaler – Off-Hours Kubernetes Scaling Cuts Costs by 70%


value: tomburgs

value:
I built this daily puzzle game called "Omitten".
The idea came from a compulsive habit I got from reading books on an e-reader and constantly looking up definitions (iykyk). Quite often you'd see a single word with 20 different meanings in different contexts, and I wanted to build a game around that.
In the game you get a maximum of 4 clues. The first one will generally be an archaic form or an unusual context. The second and third pivot into entirely different domains to try and trick your brain, and by the fourth, it should be fairly obvious. You start with only the first clue, and as you make guesses or skip, the next clues unlock, but you lose 25 points per clue.
Today is only Day 5 of the project, and it is currently a slaughterhouse. The win rate is sitting at 24% (you can see this yourself after completing) because today's word is a sneaky one. Typically the win rate sits at the 90-99% area, so yeah.
The tech stack itself is fairly simple, it uses a fairly minimal svelte frontend — relies on their motion and transition APIs for most of the animations (combined with some simple CSS animations). On the backend it's a Go monolith running a [Connect RPC server](https://connectrpc.com/), which was a super fun learning experience and using what is almost exactly GRPC directly on frontend feels magical. I tried to follow Google's AIP as closely as I could for the rpc methods, and I quite like the way it turned out. The backend is a simple pg database that's interacted with via sqlc and atlas for migrations. By day 3 people started asking about accounts so they could play across devices and keep their streak, so it was a fun chance to use PASETO for tokens and argon2 for password hashing.
I'm excited to hear what people think and any feedback is much appreciated!

value: Show HN: Daily word puzzle game based on polysemy

author: tomburgs


value:
I made this game while working on a different project about teaching English spelling. I was reading about homophones and got struck by how much a homophone can transform the shape of a word, so I started experimenting with little games built on that.
I added a few more transforms, anagrams, verb/tense changes, but the answers kept coming out too obvious. I couldn't distort the word enough to make it interesting. The breakthrough was compound pairs. Jumping from one word to another through their compound (sea → horse, via seahorse) really obscures the path and that's when it suddenly got fun and unpredictable.
I've been sharing it with friends. I'm in the UK so mostly UK testers, fair warning that a couple of the homophones may lean British.
They've been playing daily and seem hooked, so it felt worth posting here. It's one puzzle a day mainly so I actually have time to hand pick puzzles that have a satisfying path. Today's puzzle is on the easy side but they can get really tricky. The name is from 'betwixt', the whole game is about moving between two words. I did clock afterwards that there's a 60s board game with the same name, but they're pretty different things.

value: Show HN: Twixt – transform one word into another in four moves


value: NTRIXLM

value:
At my work they provided a single Claude subscription for everyone on the team. To be honest I like kiro better as it provides a way better SDD management. But the company can't provide it and I can't afford it yet. Turns out I had the skill creator skill in my claude instance so I made use of it to create this Skill. I made it fully by using Claude but I wanted to make it open source, so I asked it to help me make tests and preparations for it, even a CI to run python tests.
Well, we got this results with it:
- Phase 2A: 67 static assertions (Python script, runs in CI)
- Phase 2B: 15 behavioral tests (live Claude Code session)
- Phase 2C: 53 generation quality checks across 3 end-to-end flows
All of these passed and the CI also passed (after a few tries).
I made it to suit my way of prompting and coding and based it off kiro's SDD management, but I want it to be publicly available and used by many people. According to claude some of the testers need to fit the following criteria:
1. Developer starting a real new project from scratch
2. Solo dev with an active side project (greenfield or partial codebase)
3. Team lead whose team uses multiple AI tools
4. Developer with an existing codebase and no written specs
5. Developer who actively uses 3+ AI coding tools
It's actually a blind test, no guiding, just try it if you can, I'd really appreciate your help.
The repo is here: https://github.com/FredAntB/Spec-Driven-Development

value: Show HN: I Made a Claude Skill for Spec-Driven Development (SDD)

author: NTRIXLM


value: Show HN: AI that interviews participants instead of holding another meeting


value: bojta-lepenye

value:
Hi everyone,
I am Bojta Lepenye, and first of all, I want to thank the core developers of Hashcat. In my experience, it is quite literally the most capable tool available for offline password cracking across a wide range of use cases.
I have spent the last 4 years (from age 14 to 18) extensively working with Hashcat and the tools surrounding it, and I have documented what I have learned throughout that time (since January 18, 2022) in my first book. During that period, I also had to continuously update and rewrite major sections as the field evolved. One example was the introduction of GPU support for Argon2 and other memory-hard password hashing algorithms, which significantly changed some cracking workflows.
My passion for this book, or its “quick starter,” if you will, came from an ethically conducted penetration test I performed with full authorization at my school. This is something I am both hesitant and quite proud to acknowledge.
At the beginning, I simply wrote down everything I had learned from YouTube videos and online blogs. However, not long after starting my project, I realized I practically knew nothing about password security, and that small 10 to 15 pages I had written would never be enough if someone was looking for a professional guide to cracking passwords.
The other main driving force behind the book was the fact that while researching online, browsing forums, reading academic papers and white papers, watching videos, exploring blogs, inspecting presentations, and examining infographics, I did not find a single source that comprehensively covers and explains everything one needs to understand about offline password cracking. Literally. Not one.
Therefore, I continued my research and learned about password hashing algorithms, the security properties of hash functions, advanced hash cracking techniques, password analysis, attack optimization, and much, much more.
From the very beginning, I wanted to share this knowledge with the community because having access to a resource like this would have helped me tremendously when I first started learning password cracking.
I sincerely hope this work will be useful to both beginners and experienced professionals alike, and I look forward to hearing your thoughts and feedback.
I have also put together a little video to give you a little sneak peek into it. It is on Google Drive. It is the official domain, and you do not need to download anything. Here it is: https://drive.google.com/file/d/13LeysSZO8Mx-LGKt8UQjUGBKOYH...
If you are interested, the book is now publicly available on Amazon, and can be read for free with a Kindle Unlimited subscription: https://www.amazon.com/dp/B0GX36XRCD

value: Show HN: I Dedicated 4 Years to Mastering Offline Password Cracking

author: bojta-lepenye


value: nextime

value:
AISBF is a self-hostable AI proxy/router that exposes an OpenAI-compatible API while letting you route across different providers and model pools.
I built it to make multi-provider AI setups less chaotic: centralize access, add routing/failover/caching, support multi-user setups, and make it easier to scale from a small deployment to clustered infrastructure.
Happy to answer questions about architecture, routing logic, tradeoffs, and where it differs from simpler proxy layers.

value: Show HN: Aisbf, a self-hostable OpenAI-compatible AI proxy/router

author: nextime


value: bajpailabs

value:
In building Vivik, an execution-grade telephony AI engine, we faced a brutal constraint: the human conversational loop.
In psychoacoustics, a delay under 250 ms feels instantaneous. At 500 ms, users notice lag. Beyond 800 ms, conversations start feeling strained, and by 1.5 seconds, the illusion of real-time interaction collapses.
That creates an extremely tight latency budget for voice AI:
• Network RTT: 50–200 ms
• LLM inference: 200–800 ms
• TTS synthesis: 100–400 ms
• ASR processing: 100–300 ms
To consistently stay under a sub-500 ms SLA, the orchestration and media layers themselves must add almost no overhead.
We initially built the entire system in Go. It worked well for concurrency and distributed orchestration, but under production-scale load, we hit an architectural wall: non-deterministic GC tail latency.
The Media Plane processes raw PCM audio in strict 20 ms frames. Even tiny scheduling delays create audible jitter, packet drift, and conversational instability.
Under a 25,000 RPS stress test:
• Go implementation → P99 latency: 1,550 ms
• Rust (Tokio) implementation → P99 latency: 310 ms
The issue wasn’t average latency. It was the tail.
Even highly optimized GC pauses become catastrophic in real-time telephony. A tiny scheduler interruption under heavy throughput creates queue backpressure that cascades across live audio streams. In practice, a 1.5-second spike means the system goes silent mid-sentence.
We solved this by separating the architecture into two isolated worlds:
1. Control Plane (Go + NATS)
   Handles orchestration, routing, distributed state, and API coordination. Managed GC is acceptable here because it never touches live media streams.
2. Media Plane (Rust)
   Handles resampling, low-pass filtering, VAD, and packet-level audio processing with deterministic memory behavior.
Rust’s ownership model eliminates the need for a background garbage collector entirely. Allocation and deallocation are resolved at compile time, allowing the Media Plane to maintain a flat latency profile even under sustained throughput.
We also eliminated traditional synchronization primitives.
Mutexes in real-time audio systems introduce priority inversion risks that immediately surface as glitches or packet jitter. Instead, the engine relies on fully lock-free communication patterns:
• SPSC ring buffers for PCM transfer between socket and DSP threads
• Michael-Scott queues using atomic CAS operations for multi-producer coordination
Rust’s SIMD support additionally allowed us to leverage AVX-512 and ARM NEON instructions to process multiple audio samples per instruction cycle, significantly increasing call density per CPU core.
The takeaway: managed runtimes are exceptional for distributed systems and asynchronous I/O. But once your workload crosses into hard real-time media constraints and human perceptual boundaries, averages stop mattering. Tail latency becomes the entire system.
By separating orchestration from deterministic signal processing, we reduced P99 latency from 1,550 ms to a stable 310 ms under load.
Our full engineering breakdowns, including the mathematical foundations behind our O(n) dual-gate VAD signal logic, are detailed in the Vivik whitepaper:
https://vivik.bajpailabs.com/whitepaper
Would love to hear how others are approaching real-time media constraints alongside LLM execution boundaries.

value: Show HN: We dropped Go for Rust in our real-time telephony AI media plane

author: bajpailabs


value: Show HN: SubTrack – Find forgotten subscriptions via bank transaction scanning


value: KaifKhan

value:
hey hn!
we recently launched ai manager - which yc community calls "company brain".
- it stops revenue leakage by 20-50% on avg.
- tells you exactly what's going on, really.
- fake work vs real work
- how much time it took vs it should have taken
+ all erp softwares that a business would need like crm, project management, all software hr needs, accounting, payroll, leads finder and so so much more available for free (only for hn community) for 3-months, no charges :)
let me know!
kaayfkhan@gmail.com
https://www.traconomics.com/

value: Show HN: AI Manager

author: KaifKhan

title: Show HN: AI Manager


value: Show HN: I built a Slack-like reader for Hacker News


value: sanity

value:
For the past 5 years or so I've been working on a ground-up redesign of Freenet, my peer-to-peer project from the early 2000s (now renamed Hyphanet).
The new Freenet has been up and running since December along with some early applications like River[1], our decentralized group chat and Delta - a decentralized CMS. Users have already started to build their own apps on Freenet including games, and we have some interesting apps in development like Atlas, a search/recommendation engine.
Architecturally, this new Freenet is a global, decentralized key-value store where keys are webassembly contracts which define what values (aka "state") are valid for that key, how or when the values can be mutated, and how the state can be efficiently synchronized between peers.
We've developed a unique (AFAIK) solution to the consistency problem, every contract must define a "merge" operation for the contract's associated state. This operation must be commutative, meaning that you can merge multiple states in any order and you'll get the same end result.
This approach allows state updates to spread through the network like a virus[2], which typically achieves consistent global state in a few seconds or less.
Like the world wide web, Freenet applications can be downloaded from the network itself and run in a web browser - similar to single-page apps on the normal web. However, rather than connecting back to an API running in a datacenter, the webapp connects locally to the Freenet peer and interacts with Freenet contracts and delegates over a local websocket connection.
If you'd like to try Freenet we have convenient installers for the major desktop OSs but not yet mobile, and you can be chatting with other users on River within seconds[3]. Happy to answer any questions, you're also welcome to read our FAQ[4], or watch a talk I gave back in March[5].
[1] https://github.com/freenet/river
[2] https://freenet.org/about/news/summary-delta-sync/
[3] https://freenet.org/quickstart/
[4] https://freenet.org/faq/
[5] https://youtu.be/3SxNBz1VTE0

value: Show HN: Freenet, a peer-to-peer platform for decentralized apps

author: sanity


value: artpar

value:
Hi HN,
I made ATM, short for Agent Task Manager. It is a small CLI/TUI that shows which local coding agents are running on your machine, which repo they are in, and whether they look active, idle, stale, or just present as a process.
It currently recognizes common agent CLI processes like Codex, Claude, Gemini, Aider, OpenCode, Goose, Amp, and Cursor Agent. Codex has the deepest support right now: ATM can read local session metadata to show the project, session path, last activity, and a compact "what just happened" summary.
I built it because I kept ending up with several agents running across different repos and wanted something friendlier than ps for answering: "what is still alive, where is it working, and has it gone quiet?"
Install:
curl -fsSL https://github.com/artpar/atm/releases/latest/download/insta... | sh
Repo:
https://github.com/artpar/atm
It is early, tiny, and CLI-first. I’d love feedback from people running multiple local agents at once because right now its a very basic.

value: Show HN: ATM, a tiny terminal task manager for local coding agents

author: artpar


value: opiniateddev

value: Show HN: Six legendary marketers walk into a workflow

author: opiniateddev


value: goodroot

value:
Hey HN,
I hacked together an open source project not too long ago that became somewhat popular on GitHub. It was a fun way to reconnect with programming after spending more time on the management side of the house.
It also showed me firsthand how much open source has changed.
The volume of generated issues and pull requests took a toll. Some of it was helpful. A lot of it was not. Either way, maintainers now have to review, triage, and respond to a growing amount of "AI"-generated work, on top of everything they were already doing for free.
One practical response is to use these tools on the maintainer side too: filtering issues, doing first-pass PR review, helping with security patches, writing tests, or handling some of the repetitive work around a project. That is not everyone’s cup of tea, and I respect that. But used carefully, it can help.
The problem is cost.
Open source maintainers should not have to personally pay for the compute needed to keep up with the generated workload around their projects.
This emerging pressure is why I built open public (opub).
opub lets donors fund donated compute for open source projects. Maintainers can create dollar-limited compute keys and use them with coding agents and tools across 30+ models. Token usage and spend are linked back to the project, alongside donations, so the project’s compute balance is visible in the open.
Registration is open, and I’d love feedback from the HN community.
If you maintain an open source project with 100+ GitHub stars, the first 20 to register can claim $50 in starter donated compute from us.

value: Show HN: opub, donated compute for open-source

author: goodroot


value:
Always been annoyed by podcast ads. Searched and found a few apps that can detect and skip them, but they were all paid. So I made a free one. To my knowledge this is the first podcast app with free ad block.
iOS (26+) only for now. If the app becomes popular I'll def think of doing an Android version as well.
The app doesn't require a user account. I may open-source it at some point; still thinking about it. If anyone's suspicious about how it's able to be free, i.e. doesn't it cost money to run, are you selling my data (I'm not) etc. I'm happy to explain in the comments.
From a technical perspective, the innovation here is ad detection despite dynamic/programmatic ads, which is the norm in most popular podcasts these days. There is ofc a naive way to do it, but it's expensive and high latency. There is also an even simpler way but it's illegal lol (re-host and serve just one version of the episode). I was able to figure out a way to do it that's cheap, low latency, and legal: Shazam-style audio fingerprinting, except used for matching audio accurately, not identification.
From today on, you never have to listen to a podcast ad again. tearsofjoy.jpeg
Cheers.

value: Show HN: I made the first free ad blocker for podcasts


value: vitalipom

value:
Effected Keyboard 2 is the number one keyboard that pops up effects as you type from the keyboard to the screen. The keyboard is underrated, hence unpopular, but those who’ve tried it already so far like it very much.
Link to video:
https://youtube.com/shorts/6aExjM8A9pE?si=LjAafJDWWvy17VrG
Link to the app:
https://play.google.com/store/apps/details?id=com.vitali.pom...
Review in Xataka Android (Spanish, turn on translator):
https://www.xatakandroid.com/aplicaciones-android/letras-que...

value: Show HN: A demo video of Effected Keyboard 2

author: vitalipom


value: Show HN: Let agents run any analysis with Mixpanel data, no UI required


value: jnhprk

value:
Hi HN, I’m Junha Park. I've been experimenting with agent memory, especially how to make agents run more reliably on large tasks.
I built Darc, an open-source shared memory search tool for coding agents, with a different approach from most agent memory systems we can see today. It is an index + (lexical) search tool over agent session history, rather than a managed memory system. No embeddings, no agent-aided consolidation, no injection hooks.
How it works: Darc archives Codex / Claude Code session rollouts that already exist under ~/.codex and ~/.claude, indexes them into a single SQLite DB, and exposes session/turn/tool call/file-level search commands over them.
Why I built this: I've tried using different agent memory tools and they were useful, but sometimes I found them nosiy. I kept turning memory on/off depending on the task. For example, when I ran iterative code review rounds, I saw reviewer agents report "no findings" with "memory cited" memos, where the cited memory came from recent review sessions or the session that built the feature being reviewed. I believe this could put bias to the current reviewer's context window, and wanted to turn off those "injection hook" memory feature for such cases.
So I came up with an idea. Recent coding agent tools tend do prefer simple lexical search (UNIX tools; `rg`, `sed`, etc.) to semantic search over vector embeddings, and they work quite well and reliably without the heavy embedding. Why don't we take similar approach to agent memories, treating the session history like documents or code?
The idea is to let agents use Darc iteratively to discover relevant evidence or decisions from prior sessions, see which files or sessions are deeply related, and keep chaining the search until they understand the full picture of what happened in the past before they jump into editing code.
I also added team sharing feature to Darc. Users can encrypt (via `age`) and share their indexed agent session history with other team members working on the same project via Git backend of their choice (GitHub or self-hosted Git server). Regex-based redaction is supported by default (so sensitive data like secret keys, API keys or env vars don't get into SQLite at all). Then, users can pull agent session history indexes from other team members and search over them to get decision context made by others. This is analogous to asking colleagues who wrote the code about context behind the work, like design decisions, before touching that part of the code.
That said, it still needs proper evaluation. I'm working on simple bench/evals to compare scenarios like:
- Baseline, with no memory
- Using Codex / Claude Code built-in memory (the native memory system that summarizes prior sessions using background agents and writes MEMORY.md, not merely AGENTS.md or CLAUDE.md)
- Using Darc
- Using Darc + Codex / Claude Code built-in memory
- Just `rg` on session history directly
If this approach sounds interesting (or you think it doesn't make sense) I'd love to hear your feedback.
I'd also love to learn what methods people are using to manage team-level context on project where coding agents are used heavily.

value: Show HN: Darc – grep-like memory search tool for coding agents

author: jnhprk


value: hxii

value: Show HN: Boku – Simple, sequential YAML task runner to automate the boring stuff

author: hxii


value: wavever

value: Show HN: Buildby – A CLI to find out what desktop apps are built with

author: wavever


value: amarbirsingh

value: Works for anyone, not just developers. Still early. Curious if the setup friction is too high for non-technical users.

value: Show HN: GitVitae – Free hosted portfolio and resume for anyone

author: amarbirsingh


value: verdverm

value: Show HN: Modernizing my old PhD work in an evening with little Qwen3.6 MoE

author: verdverm


value: bytego

value: Show HN: Segment Tree visualization

author: bytego

title: Show HN: Segment Tree visualization


value: bollethegoalie

value:
Hello HN, I built Parseflow, it's a simple, evidence focused extraction API which can extract take PDFs, DOCX and TXT files and extract/chunk the info inside them to improve LLM context and reduce token usage. If you want to try out a demo, you can find it here: demo.parseflow.tech
I am still a student dev, graduating high school this year so I still have a lot to learn. I am trying to build this project to help pay for tuition this year but also to help me learn. So any feedback, advice, questions, etc... are super appreciated and either I will try to respond to the comments or you can email me at hello@parseflow.tech
Thanks,
bollethegoalie

value: Show HN: Parseflow, how to parse documents when you're broke

author: bollethegoalie


value: stagas

value: Show HN: npmfind – Alternative NPM package search

author: stagas


value: ramonga

value:
Hi HN! Outside of the hackernews bubble we often find engineers who are barely using AI (aka using microsoft copilot) and we needed an easy way to show the latest capabilities in a non confusing UI.
So we dumbed down our product to a simple text box UI where you one-shot your feature and you get an email with a link to a PR in github. The backend is hosted in Cloudflare, spinning sandboxes in Daytona that run the Opencode harness.
Feel free to give it a try or share it with people who are skeptical of the latest models. You get a bunch of credits for anthropic, openai & opensource models during onboarding + you can connect your codex sub.

value: Show HN: Free One-shot cloud agents with OpenCode and Daytona and Cloudflare

author: ramonga


value: LeoStehlik

value:
I built this because my coding agent kept telling me he did complete the task, but when I verified it, it was not the case.
I made Proof Loop fairly light, intentionally. It’s basically a protocol helper script for AI agent tasks:
- set acceptance criteria before coding/implementation
- keep the builder and verifier roles separate
- each criteria tested with results PASS, FAIL or UNKNOWN
- attach evidence of done
- keep the proof evidence in the repo, so that the next agent / run can inspect it and see what was already done
You can try it via commandline from the cloned repo, go the the proof-loop directory and run make demo.
Teh demo creates a task, checks the proof bundle, fails if evidence is missing, then passes when acceptance criteria have evidence attached.
There is also an OpenClaw skill version now, so the easiest use is
openclaw skills install proof-loop
In the GitHub repo, there is harness-agnostic version and examples.
I would especially like criticism and/or any feedback from people who run Codex, Claude Code or OpenCode on long-running multi-step tasks.
Note this is a utility that I use myself, FoC, MIT Licensed, OpenSourced, with no intention of any commercialization.

value: Show HN: Proof Loop – I make my coding agents prove they finished the task

author: LeoStehlik


value:
Just my attempt to run benchmarks for performance in the browser and WASM, fully client-side.
Check it out, and let’s see what else we can do with client-side WASM benchmarks. Feel free to contribute benchmarks you like, only condition is WASM and client-side.
https://userfrom1995.github.io/benchd/

value: Show HN: Benchd: client-side WASM benchmarking in the browser


value: boratanrikulu

value: Show HN: Write your BPF programs in Go, not C

author: boratanrikulu


value: Sanej

value:
Hi all,
During the early years of my career I had to present the software products I built to clients and it was a daunting task to prepare well for these moments.  Over the 20 years of my career I honed skills on presenting well so that it resonates.
I felt that something I can practice for just a few minutes on impromptu topics would be helpful to build muscle and may help others as well.
Please try here  https://clarityhoop.com/
Also it has coaching components as all voice AI native. Please share your actionable feedback.

value: Show HN: Personal business communication coach for Technical Leaders

author: Sanej


value:
Hi HN! We're Haakam, Michael, and Adi from AgentMail- a ycs25 company. We give AI agents their own email inboxes. Recently, we ran an experiment called Agent.Email. It's a signup flow designed specifically for AI agents instead of humans.
The inspiration came from a few comments we received when we did our seed launch a few months back. They all came from the very apt observation that agents not being able to sign up to a product made for agents without human credentials was ironic and unideal.
This is basically the thesis we built AgentMail on: The internet was made for humans exclusively, designed to keep machines out by default.
Every signup flow assumes a browser, a person reading a page, and clicking a confirmation link. Unless agents can't do that, they can't be first class users of the internet.
Agents can now get an email inbox by themselves. (This also means a lot of email nobody wants to read gets processed by AI instead of your inbox being cluttered with spam and slop)
Here's how agent.email works.
Agent needs an inbox and hits AgentMail via curl.
Agent receives instructions via MD unless the request comes from a browser, in which case we use HTML.
Agent decides agent.email is useful and then hits the sign-up endpoint with its human email as a parameter.
Agent receives a restricted inbox with credentials.
Agent emails the human asking for an OTP. Human replies with the code, and the agent is claimed and restrictions are lifted.
Until claimed, the agent can only email its own human and nobody else. Ten emails a day, and the signup endpoint is rate-limited hard by IP.
Right now it's a 1:1 mapping between agent and human. The next step is many-to-one, because one person running several agents in parallel is already very common.
Building agent.email also pushed us to revisit places in AgentMail where the default assumptions were built around the primary user being human. For example, the CLI outputs in a single column with consistent formatting because mixed delimiters are easy for a person to scan, but harder for an agent reasoning about structure. We also shortened messageIDs after agents started hallucinating completions on longer ones.
A few things we'd like the community's take on: is restricted-until-claimed the right trust model?
Does agent self-signup feel useful in production, or is it mostly a novelty, and if it's a novelty now, what would make it actually  useful?
Should agent onboarding require human approval by default, or should some agents be able to fully self-provision? What do you think are some additional measures we can take for secure sign-ups?

value: Show HN: Agent.email – sign up via curl, claim with a human OTP


value: kannthu

value:
A couple of months ago, our team got hit by the first version of Shai-Hulud through a random `npm install`. We didn't catch it until it was too late.
I built Computer Police for our team to never be in this situation again.
It's designed to block that earlier. It runs a local registry proxy between your package manager and npm/PyPI, and stops confirmed-malicious packages before they touch disk.
It's deliberately narrow: malware only, no CVE scanning, no heuristics, no telemetry, no root, and removable with one command. Works locally, in CI, and in agent sandboxes.
https://computer.police.dev/

value: Show HN: Computer Police – block malicious NPM/pip installs locally

author: kannthu


value: securient

value: I have been working on this tool for a while now as there is a clear gap in Developer workstation security. You must have seen how Github got hacked due to a malicious IDE Extension. This tool in it's current state can help collect IDEs and it's Extensions installed on end user machines, detect the permissions acquired by these extensions and whether there is a post install script. It also fetches the dependencies used by the extensions and any known vulnerabilities.<p>I'm continuously working on the tool to improve it. My objective is to add a lot of the features that usually an enterprise grade tools have.

value: Show HN: IDEViewer – Security scanner for malicious IDE Extensions

author: securient


value:
I've always been frustrated with search engines. Google used to be the one I always used, but it's now completely overrun with ads and AI Overview. Alternatives like Mojeek, Marginalia, DuckDuckGo, or Startpage don't seem to give me the results I'm looking for.
What's even worse is that search engines like DuckDuckGo, Startpage, and Ecosia are using AI Overviews too. These features ARE optional, but I still felt annoyed that I had to opt out of everything.
This is why I created my search engine Slick. Slick is an independent search engine with its own index. It aims to be everything users want from a search engine, whether that's privacy, speed, transparency, or customization.
We aim to let users have full control over their search engine. Currently, we have implemented this using custom per-domain ranking (similar to Kagi) and custom bangs (DuckDuckGo bangs, but faster and with the ability to add your own).
For revenue, we WILL be using ads in the future, but we want to approach them differently. The ads are intentionally made very visible (bright yellow text, bigger font, etc) instead of using a tiny "sponsored" label. Ads will only be visible on the first page, and there is a maximum of 1 ad per page instead of Google's 1-4.
We are also experimenting with keeping the ads in the actual search results, and I would really like your feedback on this. Since the ads are very visible, instead of forcing them to the very top, we rank them similarly to normal results (with a slight boost so they stay on the first page). The idea is that if an ad is shown, it should at least already be relevant to your query.
Now I'm not going to make the mistake of claiming "privacy" like I did in my Reddit post. Not because Slick isn't private, but because it's not open source and users currently have no way to verify what we say. We want users to feel safe when searching, which is why we want to eventually invest into audits regularly once the project is in a more stable position.
I've only been listing good things about Slick so far, so now it's time for the issues Slick is currently facing for full transparency.
Slick's major issues right now are result quality and speed. When I say bad result quality, I don't mean bad ranking. I've made a detailed overview of Slick's ranking in our blog pasted below. The issue mainly comes from our small index. Since we're a completely independent search engine, we have to do all of the crawling ourselves. Our web index is currently only around 2.5 million documents, although it is slowly growing.
The second issue is speed. This is something we are actively working to fix, but we are heavily limited by infrastructure. Slick isn't running on a massive server, or even a good PC. We are currently running on a Beelink EQR5, which is suboptimal (suboptimal may be an understatement).
These are only the issues I've personally noticed so far, but there are probably many more.
I posted Slick on Reddit a while back, but I didn't get exactly what I was hoping for. A lot of people told me that if the search engine was truly private, they would need the source code. That's part of why I've decided not to lean too heavily into privacy claims on this HN post.
I would really like your ideas, critiques, bug reports, and feedback on Slick. We hope you can support our endeavour to build a search engine that puts users first.
Blog: https://blog.slicksearchhq.com
Search Engine: https://slicksearchhq.com
Reddit: https://reddit.com/r/SlickSearchHQ

value: Show HN: My independent search engine focused on user control


value: artiomyak

value: Show HN: Online Sound Test

author: artiomyak

title: Show HN: Online Sound Test


value: arberx

value: I couldn't find an open-source, agent-first way to monitor AI search results + traffic so I built Canonry out.<p>There are tons of nuances with AI web search but have gotten really good results using canonry locally as it can cross reference with GSC, GA to really get a holistic view on the search space.

value: Show HN: Canonry tracks how AI cites you – agent-first, open source

author: arberx


value: sermakarevich

value:
I was intrigued by an AMD issue on GitHub where Stella Laurenzo shared how the AMD team runs a fleet of 50 or so agents: https://lnkd.in/drueskiV. I wanted to get there myself, and I think I managed to. I can now run a fleet of coding agents while I'm away, burning through every token across my three Claude subscriptions. I can run data science experiments overnight in loops: analyze misclassifications, form a hypothesis, implement, run, analyze again. Agents pull tasks from a queue, add new tasks back to it, organize dependencies, and block tasks when they need my input. This article walks through my approach step by step.
https://github.com/sermakarevich/claude/tree/main/usage_patt...

value: Show HN: From one Claude agent to a fleet – in five small steps

author: sermakarevich


value: roramigator

value: Show HN: I built a Printify wrapper to support a ministry

author: roramigator


value: OSINTArena.com — a browser-based OSINT challenge game for practicing geolocation, image investigation, digital forensics, and clue-led research. It includes daily challenges, leaderboards, and user-submitted puzzles.

value: Show HN: Osint Arena – GeoGuessr for OSINT


value: patrick-ghetea

value: Show HN: Filorithm – Expressive eDSL for File and Folder Management in Python

author: patrick-ghetea


value: fagnerbrack

value: Show HN: I just built a scanned PDF text extractor for public PDFs (1-300 page)

author: fagnerbrack


value:
Increasingly I've been needing to review changes inside text editor, typically as a part of editing a prompt in code harness, though sometimes for other purposes (editing md documents, PRs, etc.).
Manipulating diffs, quoting text, removing hunks, jumping to definition to verify was clumsy and cumbersome, and it occurred to me that most of it could be done very well as a language server protocol component, and wouldn't even require knowledge or special support for the language being under review.
So I've built it, and I've been slowly tweaking and improving for few days now.

value: Show HN: Patchmark – LSP for reviewing code changes/diffs in text


value: I've been using this for a while, and I thought others on HN might find it helpful. You can run it against a local repository, and it uses mostly non-AI tools to make a high-level assessment about how AI-native the repository is. This is all based on my own personal experience and is very much opinionated, but this has helped me grow my codebase without it collapsing under the weight of the AI coding biases that tend to happen unless you put the guard rails in place. This is me trying to structure what I've learned into something that can be easily applied to any codebase relatively quickly. It also comes up with a nice vector graph image, which I think is quite cool.

value: Show HN: AI readiness toolkit: AI two-minute CODE maturity check


value: abionic

value: Show HN: Online Jigsaw Puzzle: drag&drop an image or use a provided sample

author: abionic


value: fireharp

value: I’d be interested in feedback on the model, false positives, and whether the examples match drift people are seeing in larger repos.

value: Show HN: Coherence – drift detector for AI-driven repos

author: fireharp


value: jphfa

value: Show HN: Headroom – Loudness normalizer and Key+BPM playlist sorter for DJs

author: jphfa


value: mailforge

value: Spread the word, its free for 1 employee. Lets help the small businesses!

value: Show HN: I made a premium booking platform in 2 months vibe coding

author: mailforge


value: hsnrique

value: Show HN: Dhrive – Prompt to a native iOS app, built locally with your own AI CLI

author: hsnrique


value: onhacker

value: Show HN: AI Audiobook Narrator

author: onhacker

title: Show HN: AI Audiobook Narrator


value: leomicv

value: I built this software to help users who need to do static code analysis for C/C++ codebase. This can help you to explore the ASTs interactively. It can replace the Clang ast dump completely and also you can search the code/ASTs in a structual way. For example you can search a function which matches specific name or number of paremeters.

value: Show HN: Anyone interested in a tool helps to explore C++ ASTs

author: leomicv


value: Show HN: SIMD Agent – AI that runs OpenFOAM simulations from natural language


value: simonw

value: Show HN: Datasette Agent

author: simonw

title: Show HN: Datasette Agent


value: ajeskey

value: Show HN: ANML – A machine-first markup language for the agentic web (IETF Draft)

author: ajeskey


value: thisisjedr

value:
We are working on an open-source .docx editor library for apps that need to edit Word documents in the browser. We just shipped 1.0.
A lot of existing approaches convert .docx into HTML and lose document semantics along the way. Our editor parses OOXML directly and uses its own rendering+layout engine to produce paged documents with html/css. Edits round-trip back to .docx, so you’re always editing the document, not its representation.
The core rendering engine is framework agnostic, with React and Vue ui adapters on top.
It’s Apache 2.0. Happy to answer questions.

value: Show HN: Open-source .docx editor library for building document apps

author: thisisjedr


value: melector

value: Show HN: Glowing balls falling through a spinning maze

author: melector


value: johnwheeler

value:
I work on building authentic plug-in recreations of old reverb units. Typically I'm able to use schematics and data sheets, but since I started working with ASICs I had to get a logic analyzer I could afford.
The software that comes with my DSLogic, DSView, leaves a lot to be desired so I began working on a cross-platform logic analyzer I could customize over time.
Let me know what you think and if you would be interested in trying it out once it is ready. For those of you who use logic analyzers in your work, what are the features and decoders most important to you. Is there anything you would want to see in a software package?

value: Show HN: Onda – a cross-platform alternative to DSView for DSLogic analyzers [video]

author: johnwheeler


value: thingoptimizer

value:
Possibly the most stupendously useless thing I've ever done. It's a UTM, running on an (infinitely long, lazily initialized) tape, which encodes a description of the UTM + the same tape.
The "L0" machine has been running for about 1.5 months, taking about 1B steps/sec.
The L1 machine it's simulating has been taking about a dozen steps/sec.
The L2 machine it's simulating takes about one step/hour.
In ~2070, the L3 machine will take its first step.

value: Show HN: A Turing machine simulating a Turing machine simulating a...

author: thingoptimizer


value: modrena

value: Show HN: Lumox – Wirelessly mirror multiple iPhones on Mac – Ditching QuickTime

author: modrena


value: grishka

value:
Hey! I'm Gregory Klyushnikov, a former lead Android developer at VKontakte, Russia's Facebook. And I hate enshittification with a burning passion. I quit in 2016 because the mismatch in values with the new management started driving me crazy.
My core issue with Facebook, Twitter, Instagram, VKontakte, and other commercial, centralized social network services is that they all eventually drift away from "staying updated on your friends' lives" towards "getting world news", "communicating with businesses", "a town square", "a place to look at ads", "endless supply of brainrot", and all kinds of other things that involve the platform forcefully shoving strangers at you and you at them - I call such pivoted services social "media". If you want to just be with your friends on the modern internet, you're out of luck. (Yes, messaging apps are a stopgap seemingly everyone has settled on, but it's not a good solution.)
This gaping niche is what eventually got me interested in developing for the fediverse and why I started Smithereen in late 2019. My goal with this project is to eventually bring back that long-forgotten "early Facebook" experience when the platform just gets out of the way and lets you have fun with your friends and meet new people in groups. And to do it such that no one will take it away this time.
There are profiles with lots of fields, walls, groups and events public and private, photo albums with tagging, and more.
One important feature that's absent for now is global user search and, somewhat related to that, a database of educational institutions so you could put your school/college/university on your profile and be findable by your classmates. This is just something that's very hard to do in a decentralized system without partially centralizing it, although I have a few ideas that need experimental validation.
It's written in Java, it only has a few external dependencies (imgproxy, MySQL, and a web server of your choice), and it ignores most of the so-called "progress" that happened in web development over the last decade. The UI is a meticulous reproduction of VKontakte's pre-2016-redesign layout. It's fully compatible with Mastodon and other ActivityPub servers in the sense that its functionality is a superset of Mastodon's. Its client API is mostly compatible with VK's as well. A server for a few users should be able to comfortably run on a Raspberry Pi or a cheap VDS.
Unlike most fediverse projects, there is no "flagship" open-signups server because I have more interesting things to do with my life than running one of these; it's a serious commitment that fits neither my goals nor my personality. That said, I set up https://try.smithereen.software so anyone could try the thing with a temporary account (you don't need a real email either).
Looking forward to your feedback!

value: Show HN: Smithereen – an early-Facebook-style Fediverse server

author: grishka


value: haoranchg

value:
I have used Codex & Claude Code for coding for a while, but how long a coding task will actually take? When I ask Claude Code to estimate, the result is often from training data, which is based on human speed.
That’s why I built this tool, to estimate effort in ai agent speed. I run it every morning before I dispatch coding tasks to my agents.
What's in it:
task sizing: auto-classifies XS to XL from the description, then runs PERT on that tier
human-equivalent comparison: a per-task-type multiplier so you see the speedup
METR p80 thresholds: warns when an estimate exceeds a model's reliability horizon
wave planning: schedules independent tasks in parallel across a multi-agent fleet
The estimation data is from my daily coding tasks from past few weeks:
per-runtime calibration: Opus 4.7, GPT-5.5, different models have different reliability horizons and costs
per-task-type priors: backend, frontend, app development, docs, and brainstorm
PR review: I usually let Codex and Claude Code review each other’s code, and the tool takes that into consideration
a calibration loop that keeps me honest: dispatch data is validated at end of day by my coordinator agent
Try it: pip install agent-estimate, read the code https://github.com/kiloloop/agent-estimate/ , or the writeup https://kiloloop.com/agent-estimate/

value: Show HN: Agent-estimate, how long a coding task takes, at agent speed

author: haoranchg


value: ailocalrecorder

value: Show HN: AI Local Recorder – offline voice recorder with AI transcription

author: ailocalrecorder


value: Kyselica

value:
Hey guys,
My friends and I have gotten really into playing traditional card games recently, especially trick-based ones. Our favorite one is called Tractor (or Sheng Ji), which was taught to us after our friend became frustrated that he could no longer play it with his hometown friends.
I am moving soon, so there is demand for some way to play our games virtually. I wrote this site (with obvious help of AI) with our favorite games so we have a place to play after I move.
Feel free to try some games out. It's new, so I there will likely be issues. Feel free to report them here. Also don't hesitate to recommend any games you think I should try or add.
Thanks!

value: Show HN: Traditional Card Game Website

author: Kyselica

title: Show HN: Traditional Card Game Website


value: justswim

value:
Hi HN!
For the past few months I've been working up to this launch of Free Fonts - it's a collection of completely free, open source, and original fonts that can be used for any project, including commercial ones.
The collection has over 400 fonts in a variety of novel styles, from simple sans serifs to decorative handwritten and blackletter fonts. It will also continue to be updated and grow over time.
Designers and developers today have essentially two options when it comes to choosing and creating fonts. Either use a Google Font, which can be limited in terms of unique and novel selections, or pay a significant amount of money for font licenses from a few large players in the space like Monotype. The problem today is that it can be difficult to find a novel, unique font for an affordable price. Our hope is that this collection can be a starting point for solving this problem.
What makes this project different is that every font in the collection was generated completely by AI, and is a novel set of letterforms. This is what makes it possible for me to launch the project with confidence that these fonts can be freely used in any type of project.
The AI workflow behind this project is also accessible on the same site. Our model was trained on a variety of images across the internet and then runs a full pipeline to transform a consistent set of letters into a single downloadable TTF font file. It can be prompted from a text prompt, or a sample image that contains an image of some text.
Font licensing is a complex world, and I deeply believe that it is ripe for a change. My hope is that this launch can spark a new conversation on the future of typography and how it can be freely and easily used by designers and developers over time.
Hope that you enjoy, and would love your feedback about the project and also the fonts themselves.
Eric

value: Show HN: Free Fonts – a collection of 400+ original, open-source typefaces

author: justswim


value: spalas

value:
Inspired by Ramp's inspect, Stripe's Minions, and open source versions like open-inspect & open-swe, I decided to build my version of a background agent!
It is built on https://flueframework.com/ with deployability as a core feature (aka it can deploy on a server in your closet or to an EKS cluster in AWS). These types of systems are most valuable when you can deploy them into your existing infrastructure where they can safely access resources you wouldn't want to expose otherwise.
Check it out and let me know what you think!

value: Show HN: Deputies, an open source background agent

author: spalas


value: ldenoue

value: The original wasm port didn’t run on Safari so I used Codex to help me fix the issue: was that simd relaxed didn’t work on Safari, only simd-fixed<p>What’s good about Pocket TTS is that it streams generated audio chunks.

value: Show HN: Pocket TTS running in (mobile) Safari

author: ldenoue


value: sermakarevich

value:
Spec Driven Development approach allows to squeeze more from coding agents thanks to few strong concepts:
- decomposition across two dimensions. first you generate specs in multiple steps (requirements, code analysis, design), than you split task into multiple subtasks and implement them one by one
- you clear context between every step - after spec generation and after subtask implementation. this helps keep cost low and context clear and focused which boost performance
- specs written to disk help with information persistency
- delivering specs layer by layer help to catch early when agent got you wrong
Repo with claude plugin for spec driven development: https://github.com/sermakarevich/sddw

value: Show HN: Spec-Driven Development Workflow for Claude Code

author: sermakarevich


value: benhmoore

value: Show HN: Roughform, a free Browser-Based 3D Creation Tool

author: benhmoore


value: zaitanz

value:
Hello!
This project is a TLS/X.509 certificate manager and PKI. Designed to provision and install your TLS certificates across public and private endpoints. It's something I created for my home lab, but has quickly expanded as I have been experimenting more and more with AI development tooling.
You can see the product overview: https://www.zaita.com
It's architecture and usage is nicely documented: https://docs.zaita.com
Unfortunately, you do need to sign up to have a play, but there is a demo instance that doesn't require a credit card. Just enter an email (I won't send you any emails) and password.
Keen for feedback. I've found the major players in the industry are only interested in Enterprise arrangements. I wanted something I could use in my home lab across my many docker containers etc, but still had cool features like network discovery and certificate transparency log scanning.

value: Show HN: TLS Certificate Management and PKI

author: zaitanz


value: pythongiant

value: Show HN: KVBoost – chunk-level KV cache reuse for HuggingFace, 5–48x faster TTFT

author: pythongiant


value: uohzxela

value:
Hi HN, I'm Alex. I built inkoscribe because I needed a transcription tool I could actually trust with sensitive meetings, interviews, and 1:1s — without uploading audio to anyone's cloud.
It's a macOS CLI that does real-time speech-to-text fully on-device:

  brew tap uohzxela/inkoscribe
  brew install inkoscribe
  inkoscribe -s sys   # captures system audio (meetings, calls, videos)
  inkoscribe -s mic   # captures your microphone

Requires macOS 13+ on Apple Silicon (M1/M2/M3+).
A few things I cared about while building it:
- Zero network calls. Your audio never leaves the machine.
- Real-time, word-by-word output — not batch.
- No accounts, no config, no Electron. Just a binary you brew install.
It's my daily driver for work calls. Happy to answer questions about the model choice, latency tradeoffs, capturing system audio on macOS (ScreenCaptureKit was… an adventure), or anything else.
Feedback and bug reports very welcome.

value: Show HN: I built a local-first macOS transcriber

author: uohzxela


value: ClaireGz

value:
Hello HN! I'm Claire, founder of nao Labs (YC X25). Two months ago I started building a company brain in a git repo. Now I fully run my company with 8 AI agents, 20+ skills, and a self-learning context repo.
I built it in a git repo because I refused to lock into any tool - not a context layer, not a specific agent harness. Today I'm open sourcing it so others can build their own.
Sylph is the open source version of the company brain I use. It gives you the structure to host your own company context, build skills, create AI agents, and already has a self-learning loop scaffolded. It is a Git repo, with no lock-in on any tool, that can work with any agent: Claude Code, Codex, Cursor.
Sylph is made for you to make your own: fork it, run /sylph-setup, and it will build your own company brain according to your own context.
Repo: github.com/getnao/sylph
How I built it: https://thenewaiorder.substack.com/p/i-built-a-company-brain...
Tell me what you think, and if you've got some tips if you built an AI brain for your company too!

value: Show HN: Sylph – the open-source company brain behind my YC startup

author: ClaireGz


value: hholen

value:
Back in October, I built a web analytics tool. It had two distinguishing features: it was cheap, and it had a weekly AI email summary so you wouldn't have to check your dashboards. Turned out that cheap made no difference, but the few users I had really liked the email digest.
The world moves fast these days, and suddenly I found myself experimenting with agents, and doing all my work in Claude Code, so I decided to throw out everything and rebuild the tool as lodd.dev, a headless web analytics tool for agents. 42 MCP tools and a full API that lets agents call and act on analytics data as part of their processes.
I've tried to optimise it for agent usage, so efficient responses (a snapshot is 60ish tokens), an llms.txt to guide the agent to handle setup, read only for simplified auth, and both a hosted oAuth (for desktop and mobile apps) and stdio version using an API key for terminal use. Human in the loop authentication using OTP in an email.
Explicitly asking the agent to use it works really well, and I particularly like combining with other context sources like GSC or commit history, but it's been a little bit of a challenge having the agent call it unprompted. A few lines at the top of a Claude.md file has made a difference though.
I'd love to hear what value, if any, you see from being able to get analytics data in the same conversation as your code (or other automatic workflows)?

value: Show HN: I threw away my analytics dashboard and replaced it with 42 MCP tools

author: hholen


value: evilmarty

value: Show HN: I created a disk usage explorer CLI

author: evilmarty


value: ianymu

value: Show HN: Stainless replacement – paste OpenAPI, get TS/Python/Go SDK ZIP in 1.5s

author: ianymu


value:
Some of us will have compliance obligations coming down the line for post-quantum crypto; the gist of which is understanding which algorithms we're using and whether they'll be suitable for protecting against quantum attacks in the future (but potentially against data collected as early as today).
Anyway, in case it's useful, here's a small tool that can either scan a host and port, or check for open connections and attempt to identify if they offer post-quantum algorithms.
I've only packaged it for macos so far, but it's just python.

value: Show HN: An open source tool that checks for post-quantum crypto


value: kirksmith

value:
Made this video on our project which might be of interest to folks here! Happy to answer any questions. First time making a long-form video.
Previous HN thread: https://news.ycombinator.com/item?id=41235789
Video is also on PeerTube: https://spectra.video/w/4wTobcS16Ww5UAZVMWrC9E

value: Show HN: We're building an open-source battery [video]

author: kirksmith


value: logic-designer

value: a cool extension to make your AI chats better

value: Show HN: Interactive and Stylized AI Chat

author: logic-designer


value: discordance

value:
I often spend too much time scrolling up through my terminal history trying to find stuff, so here's a tool that helps create a visible marker in your terminal.
repo: https://github.com/ankurokok/hr
demo: https://asciinema.org/a/GJlx8uEBqNkORWZJ
Simple, dumb and maybe useful.

value: Show HN: HR – a 30-line script that prints a colored bar across your terminal

author: discordance


value: MarsB

value:
Store memories, auto-extract entities and relationships, search semantically.
MCP server + REST API + SDKs.
Self-hostable, cloud option, MIT license.

value: Show HN: I made an open-source memory layer for agents

author: MarsB


value: unprovable

value: Show HN: ShadowCat – file transfer through QR Codes in a Browser

author: unprovable


value:
Spent one whole weekend playing with agent thinking animation, literally can't stop.
Originally in python. Written in Rust. Provided Webassembly, python bindings. Baked CSS snippet is also an option.

value: Show HN: Agents-are-thinking – Terminal agent thinking animation exploration


value: sporritt

value: We've put out a major new release of JsPlumb recently, with a modernised API and dedicated diagram/2d chart engines (and a new name), and one of the decisions we made was to make it available for free for non-commercial usage. Packages for React, Angular, Vue, Svelte and vanilla JS are available in the public NPM repo.

value: Show HN: JsPlumb is now free for non-commercial usage

author: sporritt


value: seltug

value: Show HN: DecisionBox – Point it at Databricks. Walk away with insights.

author: seltug


value: cezarvil

value: Show HN: Myco – coordinate Claude and DeepSeek and other LLMs in one agent swarm

author: cezarvil


value: Hi all. This is my first attempt at a professional PaaS application. Let me know what you think, it took me a couple of months to develop!

value: Show HN: HeadlessPDF – An API for Generating PDFs from URLs


value:
Hi HN, We're building Ota.
Ota is open repo readiness infrastructure. It makes software repositories runnable and trustworthy for human, CI, and AI agents.
The problem we kept seeing is that the real truth of how a repo gets set up and run is usually scattered across READMEs, scripts, CI config, env files, and maintainer memory. That slows onboarding, causes local and CI drift, and makes automation brittle.
Ota gives each repo one explicit operational contract for what it needs, how it becomes ready, and how tasks should run.
The core flow is:
- `ota doctor` to diagnose what is missing
- `ota up` to prepare the repo
- `ota run` to execute named tasks from the contract
The product idea is "doctor first, contract second." We want it to be useful even before a repo is perfectly modeled.
What we're trying to build is not just another task runner or dev environment wrapper. We think repo readiness is its own layer: something between the repo, the developer, CI, and now agents.
We'd especially love feedback on:
- whether this problem feels real in your repos
- whether the contract model feels like the right abstraction
- what existing tools you think are the closest substitutes
If this sounds relevant to your repos, you can check it out here:
https://github.com/ota-run/ota

value: Show HN: OTA – a readiness contract for software repos


value: matzehuels

value: Show HN: Stacktower – Dependency audits inspired by Xkcd 2347

author: matzehuels


value: paperplaneflyr

value: A highly-optimized, single-node, mini-Kafka broker built from scratch in Rust. This system leverages a thread-per-core architecture powered by io_uring via the tokio-uring framework, bypassing traditional OS thread context switches and synchronization overhead.

value: Show HN: Ringlog – A highly optimized thread-per-core message broker

author: paperplaneflyr


value: EagleEdge

value: Show HN: Mnestica – a memory system for notes, reading, and cards

author: EagleEdge


value: massmr

value: Show HN: Wwwatch, a daily journal of AI tooling news filtered for builders

author: massmr


value: Show HN: LLM-mock – Record real LLM API responses once, replay them in tests


value: alepacheco-dev

value:
HEVCut is a photo and video compression app for Apple platforms I have been working on. Today's update adds AVIF as an output format for photos, which I believe makes it the first app on the App Store to ship AVIF encoding on iOS.
Apple added AVIF decode in 2022 (iOS 16, macOS Ventura) but never shipped an encoder, public or private. Photos cannot export AVIF, ImageIO cannot write it, and no other third party app on the store does it either. So if you wanted AVIF files coming off an iPhone, your options were "send the original somewhere else and re-encode it" or "wait."
On typical iPhone photos, AVIF lands around half the size of HEIC at matched visual quality. A 5 MB HEIC compresses to roughly 700 KB. HDR (including gain map HDR content from newer iPhones) is preserved, SDR works correctly across readers, everything runs on device.
The rest of the app does the usual library cleanup things: HEIC and HEVC recompression, duplicate detection, surfacing space hogs, swipe to delete, a private vault. AVIF is the new piece.

value: Show HN: HEVCut, AVIF photo encoding for iPhone, iPad and Mac

author: alepacheco-dev


value: nesdzoltd

value:
LocalPanel is a desktop application that runs entirely locally, allowing you to easily manage any server accessible via SSH, install the necessary applications with a single click, review security settings, and ensure security by creating bash shells using drag-and-drop.
No data leaves your device; your passwords are encrypted using your device’s encryption, meaning that even if your device is hacked, your passwords remain securely stored.
I need users for beta testing. Please send an email or leave a comment stating your operating system: oguz@nesdzo.com
nesdzo.com/services

value: Show HN: LocalPanel – Manage any SSH server from Mac/Windows, no server agents

author: nesdzoltd


value: Egret

value:
My twin brother and I published a book examining Christianity and naturalism as competing civilizational worldviews rather than simply religious or scientific positions.
The book explores how differing metaphysical assumptions shape interpretations of science, origins, causation, and history, with particular focus on Genesis 1–11, philosophy of science, and critiques of scientific naturalism.
A review EPUB containing the full text is available as a GitHub release.
The book is written from a modern young-earth creationist Christian perspective.

value: Show HN: Origin – Christianity and naturalism as competing worldviews

author: Egret


value: borkodotfun

value: Show HN: Auto – Execute cross-venue crypto strategies from one prompt

author: borkodotfun


value: scosman

value: Show HN: Videowright – we made our launch video with Claude Code (open source)

author: scosman


value: duman

value:
Glimpse is a native macOS markdown viewer. The thing I built it around:
the AI features run entirely on-device through Apple's FoundationModels
(the same model behind Apple Intelligence). Summaries, key insights, an
auto-glossary of jargon in whatever you're reading. Nothing leaves your
machine, no API key, no account.
I read long markdown all day, mostly engineering docs and RFCs, and the
existing options frustrated me. Electron apps felt slow. The fast native
ones had no AI. The ones with AI wanted me to send a private spec to
someone's cloud to get a summary. I wanted to open a 40-page doc and ask
"what's actually new here" without it leaving my Mac.
Other things it does: double-click any rendered block to edit just that
part of the source, file watching that doesn't fight you while you edit,
presentation mode, KaTeX and Mermaid offline, and a QuickLook extension
so .md files preview the same way in Finder.
Worth being upfront. AI needs macOS 26 because FoundationModels doesn't
exist before it. The viewer and editor still work on older macOS, AI is
just gated. Mac App Store only right now. 14 day free trial, then
monthly or yearly subscription. I went with subscription because I want
runway to keep shipping, but I'm honestly not sure it's the right model
for a tool like this, so push back if it bugs you.

value: Show HN: Glimpse, Markdown reader using Apple's on-device foundation model

author: duman


value: Show HN: Runner – desktop app for running Claude Code, Codex as a crew


value: rmqyeby

value: Show HN: Agent Capsule – versioned checkpoints for agents you run

author: rmqyeby


value: Show HN: Mercury v3 – Convert Python Notebooks to Web Apps


value: Show HN: Swarmsim – Emergent flocking and predator/prey dynamics


value:
I built a browser app for recording calls and turning them into transcripts/summaries without inviting a meeting bot.
The current version is BYOK: you provide an OpenAI API key, stored locally in your browser. Recordings/projects stay in browser storage; selected audio/transcript text is sent to OpenAI only when you run transcription/summary.
I am testing whether the wedge is real: no bot in the meeting, no SaaS workspace for recordings, summaries/exports afterward.
I would appreciate feedback on the trust boundary and whether BYOK is acceptable for a first version.
I used it once to record a meeting I didn't want to spend 1 hour on, and just needed the summary - the tool captured the meeting audio even after I turned off the laptop audio.

value: Show HN: A botless meeting recorder and summarizer that runs in the browser


value: angpt

value: Show HN: Cq exchange: Hosted knowledge commons for AI coding agents

author: angpt


value: theodorehq

value:
I've spent the last year building Charm, a native macOS menu bar app that corrects spelling, fixes grammar, and predicts your next word.
Three features:
- Spells: NSSpellChecker plus a local LLM for context-aware corrections (catches "definately" -> "definitely" without the false positives macOS autocorrect is known for).
- Polish: sentence-level grammar fixes triggered at punctuation boundaries.
- Oracle: next-word prediction, Tab to accept.
100% local. Choose Gemma 2 2B or Qwen 2.5 3B; the model downloads once from HuggingFace on first use, then everything runs on your Mac. No cloud option exists, no accounts, no API keys, no telemetry. The model auto-unloads after 5 minutes idle so the RAM cost is bounded.
Built in Swift / SwiftUI. Needs Accessibility and Input Monitoring permissions because text replacement requires reading keystrokes globally. Nothing leaves your machine.
One-time purchase.
I'd love feedback, especially edge cases where corrections go wrong.

value: Show HN: Charm – on-device spelling, grammar, and prediction for macOS

author: theodorehq


value: deepseekai

value: Show HN: Anime AI Studio – Create AI Anime Videos from Scripts

author: deepseekai


value: temiroff

value: Show HN: Blacknode – Visual workflow builder Claude can drive via MCP

author: temiroff


value: wmadden

value:
Hey I'm Will from the Prisma team, engineering manager and also the lead developer on Prisma Next.
I'd like to introduce you all to the next version of Prisma: a full rewrite in TypeScript that builds on the established patterns in Prisma and comes with a family of skills that integrate it into whatever AI tooling you're using in 2026.
(Read the announcement on our blog here: https://pris.ly/pn-ea)
The three topics in the title are brand new concepts in Prisma Next so let me give you a quick rundown.
1. Data contracts
If you've used Prisma before you've seen the `schema.prisma` file. That's a contract between your application and your database: it spells out exactly what your app relies on and what your database promises to persist.
Your contract drives everything in Prisma Next, like queries, migrations, error checking and correctness guarantees. It's hashed to give it an identity similar to a git commit and we use that hash to sign your DB: if the DB is signed with your contract's hash, your app knows it's compatible.
2. Migration graphs, guardrails and verifications
A migration transforms your database from one contract's structure to another. That makes migrations the edges in a graph of data contracts.
In Prisma Next we don't store migrations as a sequence of alphabetically ordered SQL files that break the second you merge two branches together. Instead, we store them as a graph, similar to how git stores your filesystem changes as a graph of commits.
And we don't store migrations as black box SQL files. Each migration's on-disk structure is an `ops.json` file with a reviewable TypeScript file alongside it. Each operation has a precheck (verifies preconditions before executing) and a postcheck (verifies successful execution and provides idempotency). The migration promises to move you from contract A to contract B, and the resulting schema is verified against the destination contract before the migration is committed.
They're the safest migrations you'll ever write and they're generated for you when you change your contract.
3. Agent DX
Data contracts and verified, hashed, deterministic migrations are strong enough primitives to safely delegate this work to an agent.
Prisma Next helps pry the footgun out of our collective fingers and gives you a set of reliable, predictable tools and also a family of curated skills with guardrails on every operation. This helps you focus on building your app instead of double-checking everything your agent does.
Today we're releasing it in Early Access. It's early, there are gaps, but it's a different shape of ORM than you're used to and we want to get feedback to help us shape its future direction.
The blog post goes into more detail than I have here but the best way to get a feel for it is to run `npm create prisma@next` or just clone the repo and check it out.

value: Show HN: Prisma Next – data contracts, migration graphs, agent DX

author: wmadden


value: rayansaleh

value:
Pablo is a Chrome extension that copies the HTML and CSS behind any element you hover.
It captures computed styles, fonts (with @font-face and Google Fonts links), CSS keyframes, and animation props from GSAP and Framer Motion. The output is structured so it pastes cleanly into Claude Code, Cursor, or Codex when you want to rebuild a component in your own stack.
Manifest v3, no host permissions, no backend. Free.
https://usepablo.dev
Happy to answer questions about how the extraction works, and would love to hear about sites where the output breaks.

value: Show HN: Pablo – a Chrome extension that copies UI from any website

author: rayansaleh


value: SandmanDZ

value:
We’ve been building an open-source FPGA-based 400G RDMA-like SmartNIC called OpenRDMA.
The project includes RTL, drivers, and the FPGA data path implementation. Current hardware throughput has reached around 200Gbps so far.
One interesting aspect has been verification: we’ve been using LLM-generated cocotb testbenches quite extensively. AI is still weak at SystemVerilog, but surprisingly useful for Python-based cocotb verification workflows.
The entire stack is open-source:
github.com/open-rdma/open-rdma
Would love feedback from people working on FPGA networking, RDMA, SmartNICs, or high-performance infrastructure.

value: Show HN: OpenRDMA-An Open Source FPGA-Based 400G RDMA-Like SmartNIC

author: SandmanDZ


value: abi

value:
Hi everyone,
I wanted to share an open source Telegram-based personal AI assistant I built. It’s a model-agnostic agent with memory, skills, tools (like web search, browser user, etc.) operating in a persistent workspace. It also has support for scheduled tasks, and can build powerful HTML-based apps that live in the workspace.
Here are some of my favorite use cases:
* Send Lilo photos of food, and it tracks your calories.
* Leave a voice note on your run to pause your supplements, and Lilo adds a TODO.
* Have Lilo remind you when the Knicks game starts and even send you score updates every 5 minutes.
* Have Lilo read an article out loud. Or give you a summary of the top stories on Hacker News.
* Forward a Uber receipt, and pull it up later to file for a reimbursement at work.
* Schedule a meeting with Jess next week, ask for suggestions on location, and next week, remind you to leave for the meeting on time.
While Telegram is my most frequently used channel, Lilo can also be accessed by email, WhatsApp, a website and a mobile app. Email is particularly useful: I often forward receipts, invites, etc for Lilo to handle.
How is this different from OpenClaw and Hermes Agent? Here are some reasons:
- Runs on a remote machine/in the cloud rather than your local machine - your local data is safe, and the assistant is available 24/7.
- More visual/ more GUI - Lilo comes with a default set of apps like a TODO list that you can interact with not just by text, but also with a GUI on the mobile and web app.
- The Telegram integration is very comprehensive (handles replies, voice notes, reactions, etc.).
I use Lilo a ton to manage my life. Would love to hear your feedback!
Github: https://github.com/abi/lilo

value: Show HN: Lilo – An open source personal AI assistant that lives in Telegram

author: abi