value: bneb-dev

value:
Hey HN,
I built Trytet to fix the state and geography constraints of autonomous agents.
Giving an LLM unverified host execution breaks security, and streaming embeddings back and forth over HTTP is heavy. Furthermore, when your agent hits an API rate limit or context boundary, you typically drop its execution thread entirely.
Trytet is an embeddable, sub-millisecond Wasm substrate. What it handles:
Zero-trust primitives: Evaluates volatile machine-generated code instantly without the initialization latency of Docker.
Determinism: Captures active linear memory into a .tet binary. You can snapshot, hibernate, or branch an agent's execution exactly at the instruction where it halted.
P2P swarming: Serializing the engine's state allows you to migrate an active agent directly to the edge node hosting your vector stores, eliminating round-trip latency manually.
The Context Router juuuust merged. It's an O(N) sliding-window estimator that enforces mathematical bounds against LLM context crashes without raw memory overhead.
Repo: https://github.com/bneb/trytet Demo / Architecture: https://trytet.com
Happy to answer questions on the engine internals or the LSM-Vector VFS hybrid.
P.S. This is active development and I'll be back tomorrow with something cool.

value: Show HN: Trytet – Deterministic WASM substrate for stateful AI agents

author: bneb-dev


value: Show HN: A Minimal Basic Inspired by Brainfuck


value: tailaiw

value:
I used to print AI-generated articles for my kids to read and
memorize vocab from. Two problems: no way to track what stuck, and
the articles often introduced words they didn't know either — I'd end
up Googling definitions mid-bedtime-reading.
Most apps "solve" the tracking problem with quizzes. But recognizing
a word in a list is easy — using it in a sentence is where real
understanding shows up. My kids could ace a quiz and still have no
idea how to actually use the word.
The other missing piece is the memory curve. Without spaced
repetition, words just evaporate — they'd "learn" something on Monday
and it'd be gone by Friday. The research is clear: revisiting at
increasing intervals is far more effective than cramming. Most kids'
apps ignore this entirely.
I built Wordie for my own kids, but realized the same pain points
probably resonate with other parents. Kids read short AI-generated
articles with vocabulary words at their level, then write their own
sentences for each word. I (the parent) review them before the word
moves forward. Words that pass enter a spaced repetition queue. Ones
they struggle with stay in rotation.
Built with a lot of AI help — which felt fitting for an AI-powered
kids' app.
Would love feedback from other parents.
https://gowordie.com

value: Show HN: Wordie – Spaced repetition vocab app built around sentences not quizzes

author: tailaiw


value: didgeoridoo

value: claudebar wraps Claude Code in a detachable, resumable tmux session with a nice status bar (showing things like session usage % and the new Peak vs. Off-Peak status), interactive side panels to manage Tasks and Agent Teams, and a clickable menu for when you're feeling mousey. I've found it to be a useful little enhancement to my everyday work. Hopefully you do too!

value: Show HN: Claudebar, the missing interactive menu bar for Claude Code

author: didgeoridoo


value: hkdb

value: Show HN: LM Gate – Auth and access-control gateway for self-hosted LLM back ends

author: hkdb


value: olivergrabner

value:
Hi everyone!
I built Composer, which is a tool turns your ideas into architecture diagrams. You can also use MCP to turn your EXISTING codebase into a visual diagram!
It connects to all possible tools using MCP (Claude Code, Codex, OpenCode, etc.)
The goal was to make system design easier and to be able to draw out what I wanted to make before I started / to explain to others.
Its currently live at usecomposer.com and free!
I’d love feedback on whether it feels useful for real projects and where it breaks down. :) Thank you

value: Show HN: Composer – AI architect / MCP for software architecture diagrams

author: olivergrabner


value: alecthomas

value: Show HN: Procfile-compatible tool with hot reload, readiness, dependencies, etc.

author: alecthomas


value: ieuanking

value:
We built Ubik Studio because professional knowledge workers and researchers are experiencing a crisis with unreliable AI tools. Models hallucinate citations with total confidence. Multi-hop tasks degrade in quality. Context engines fail on file-based work. And without step-by-step approval flows, professionals spend more time verifying AI work than doing the work itself, decreasing both productivity and hurting the critical thinking skills humans need to use AI tools effectively.
Two years of failed AI integrations have killed blind trust. Enterprises are moving toward workflows that require human judgment and verification. Professional researchers would rather work slower with certainty than fast and wrong.
Since inception, we've focused on assistive, human-in-the-loop design. We're model-agnostic and built-ready for the near future where local models run effectively on personal computers. We've spent all our research effort on the hard problems: multi-hop reasoning across complex tasks that require gathering sources, maintaining file context, and generating text with accurate evidence attribution. We've built a context engine and citation engine that our agents use to cite accurately and cross-analyze documents without hallucination across models.
Our HITL-AI design gives you control, transparency, and capabilities that mainstream AI tools lack. Our users are professionals, researchers, and grad students doing work where accuracy and attribution are non-negotiable. Ubik Studio delivers a Cursor-like experience for professional researchers who struggle to integrate tools like Claude, ChatGPT, or NotebookLM into their high-level workflows, and we are very proud to hear praise from our users like:
"I can check all citations for every sentences. Your software is the same as NotebookLm, even better because I can see some parts in PDF which link to the results from AI models. NotebookLM cannot open locations of PDF where the citations appear, just text. I don't care about text, I need precision, accurateness in every sentence."
We would love and appreciate your feedback, everything is public we have some paying users (super proud), but ofc we are always learning <3
If a model-agnostic AI workspace that centralizes writing, searching, document analysis, and LLM-assistance locally sounds helpful for you, please give it a try!
https://www.ubik.studio/download

value: Show HN: Ubik – Analyze local files like NotebookLM, with Cursor-like power

author: ieuanking


value: arttaboi

value: Built and open-sourced in the era before AI. <i>I’m sure you know where to find the code.</i>

value: Show HN: Minimal Brain Teaser Web Game (Handcrafted, No AI)

author: arttaboi


value: Show HN: Skyreels V4 – AI Video Generator with Native Audio Sync


value: sungsool

value: Show HN: Agentdid – Cryptographic proof that a human stands behind an AI agent

author: sungsool


value: imgdesgen

value:
At a friend's gathering, someone mentioned wanting to add her late father into a family photo. I figured this would be trivial — modern image models are powerful, just send two photos and ask the AI to merge them. She said she'd tried, but the results were weird and unstable, and she didn't know how to describe what she wanted.
I went home and tried it myself. With a well-written prompt and two good photos, it works. But real-world use cases aren't two good photos — it's a modern family photo plus a damaged old portrait, or two old photos from different decades. That's when things fall apart.
I looked at existing tools. Most showcase merges between clean, well-lit, modern photos. Nobody was solving the hard version: mismatched eras, damaged sources, different poses, different formality levels.
I thought it would be a weekend project — one system prompt and done. After 200+ test iterations I realized stable results require much more than prompt engineering. The main challenges:
The AI subtly changes faces during merging. The result looks "similar" but isn't the same person. For someone trying to add a deceased loved one, that's a complete failure.
Posture and scale need to match. If the group is sitting on grass and the added person is standing like a giant, it's obviously fake.
Casual accessories from a reference photo break formal scenes — sunglasses on the head at a wedding, sportswear at a ceremony.
Old photos have low resolution, damage, and no color. Merging, restoring, and colorizing at the same time makes everything harder.
It supports headshots, half-body, and full-body reference photos. Old and damaged photos work too — with optional colorization and restoration.
Still an MVP. Free to use once per day, no login required.
https://animateoldphotos.org/add-loved-one-to-photo
Would love to hear about edge cases that break it.

value: Show HN: I thought merging two photos with AI would be a weekend project. Nope

author: imgdesgen


value: yskapell

value: Show HN: fast-copy — Fast file copier with dedup and SSH tar streaming

author: yskapell


value: folli

value: A fully local Retrieval-Augmented Generation (RAG) implementation for querying 25 years of Swiss Teletext news (~500k articles in German language) - based on Deepmind's most recent Gemma model.<p>Why? I thought it's a cool type of dataset (short/high density news summaries) to test some local RAG approaches. Gemma 4  gives some impressive results, but could probably use some more tweaking on the system prompt.

value: Show HN: Gemma 4 based local RAG on 25 Years of news articles

author: folli


value: Vallar

value:
Hey folks,
For the past month I've been working on a visual AI orchestartor tool that allows users to create a pipeline similar to SDLC. Basically you fire up Wazear, create a project and add your brief. You select the agents (each agent serves a role such as planner, architect, etc...) and set which agent reviews which other agent's work and let it do the work. At any point you can pause the pipeline to review output yourself.
You can check it out here: https://wazear.space. Any feedback is welcome.
Thank you very much.
Best Regards.

value: Show HN: Wazear – A visual AI orchestrator where agents review each other

author: Vallar


value: giuliomagnifico

value: Show HN: Save to Linkding, iOS/iPadOS system extension and app

author: giuliomagnifico


value:
SkillCompass is an evaluation-driven skill evolution engine for Claude Code and OpenClaw.
It scores your Claude Code and OpenClaw skills across 6 dimensions (structure, trigger, security, functional, comparative, uniqueness), pinpoints the weakest one, and fixes it, then moves to the next weakest. It also detects when model improvements make a skill unnecessary. Runs locally. Requires Node.js v18+ for local validators.

value: Show HN: SkillCompass – Diagnose and Improve AI Agent Skills Across 6 Dimensions


value: Brosper

value:
Built my personal site as a browser terminal. No frameworks, no build step — just one HTML file with ~1000 lines of vanilla JS.
Has a virtual filesystem you can navigate (ls, cd projects, cat cv.pdf), easter eggs, a tour command for non-technical visitors, and tracks what commands people actually type via Umami.
The interesting part: looking at real usage data to see what commands people try has been more fun than building it. Turns out recruiters type full frustrated sentences when lost.

value: Show HN: My portfolio as a working terminal (vanilla JavaScript, one HTML file)

author: Brosper


value: franze

value: Show HN: Apfel – The free AI already on your Mac

author: franze


value: aitooltrek-com

value: Show HN: Stashpin – Pinterest downloader for videos and boards

author: aitooltrek-com


value: levmiseri

value:
Hi HN!
Few months ago I've shared a new kind of markdown editor that we (a team of three from the Czech Republic) have been working on (HN post: https://news.ycombinator.com/item?id=46144801). What resonated with folks the most was Kraa's unique ‘live-typing’ chat feature. We have now acted on this feedback, improved the chat features, and made what we call Kraa Trees.
Trees allow anyone to create a light-weight community / chat channels. It would be a stretch to call it an alternative to Discord, yet, but we hope that the frictionless nature of Trees will make them useful for small groups that want something simpler, more immediate, and less cluttered. With the live-typing being one of the key differentiating features.
You can create your own community/rooms by selecting "Tree of leaves" in the New leaf button dropdown.
You don't need an account to try Kraa nor Kraa Trees. We would love to know what you think!

value: Show HN: Anonymous Chat Channels

author: levmiseri

title: Show HN: Anonymous Chat Channels


value: keiranflynn

value:
I kept running into this annoying problem:
I’d remember a really useful answer, but not where it was.
ChatGPT? Claude? Gemini? No idea. So I’d end up digging through all of them or just rewriting the prompt.
Built this to fix that.
It’s a Chrome extension that indexes chats locally and lets you search across them all in one place. Once it’s indexed, search is basically instant.
Still early. UIs change and break things sometimes, so it’s a bit fragile in places.
Curious if other people have the same issue or if it’s just me jumping between tools too much.

value: Show HN: LLMnesia – search across ChatGPT, Claude, Gemini chats locally

author: keiranflynn


value: gtpoxa

value: Show HN: Event photo matching with badge markers, no face scanning

author: gtpoxa


value: bythreads

value: Show hn: Speedy-Claude

author: bythreads

title: Show hn: Speedy-Claude


value: laleshii

value: Show HN: Koriander – Recipe manager that parses ingredients and tracks nutrition

author: laleshii


value: Show HN: Zumly – a library for building zooming user interfaces


value: KrishBaidya

value: Show HN: X·y=k powers decentralized exchanges – AMM math and interactive viz

author: KrishBaidya


value: enzovn

value: Show HN: How do you manage multiple AI agents? We built a tmux-based in Rust

author: enzovn


value: ramkarthikk

value:
With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories.
There are two versions:
Minimal (HN-inspired, fast, static): https://text.blogosphere.app/
Non-minimal: https://blogosphere.app/
If you don't find your blog (or your favorite ones), please add them. I will review and approve it.

value: Show HN: I built a frontpage for personal blogs

author: ramkarthikk


value: SebastianSosa

value: Show HN: Reverse-engineered Claude in Chrome after the source leak

author: SebastianSosa


value:
Firefox had a 3D DOM inspector called Tilt. Edge DevTools had one too. Both got killed.
The idea was good though. Pull the layers apart, see the structure spatially instead of reading a flat tree. It makes nesting depth, wrapper bloat, and stacking problems obvious in a way a panel never will.
I wanted it for Figma so I built it.
One difference worth noting. In the browser, the 3D view is a visualization of the rendered output. The layers are a representation of something else. In Figma, the layers are the actual structure. They are not a picture of the file. They are the file. So when you pull them apart in 3D you are looking at the real thing, not a shadow of it.
2k users. Free. No network access  + You can smash things.

value: Show HN: Figma 3D Tilt, Like "Firefox Tilt" but for Figma


value:
GTM iteration is slow by nature. Test the price, wrong. Fix the message, doesn't convert. Try a new audience, wrong segment. Pick a channel, no traction. Each mistake costs a month. By the time you've iterated to something that works, the market has moved - especially now, when AI is reshaping what buyers want every quarter.
We built RightSuite to compress that cycle. Describe your offer and target audience. The system runs it through a synthetic buyer population and tells you what's likely broken before you go live.
It won't replace talking to real customers. Nothing does. But it means you don't start at zero. Instead of spending month one discovering your price is wrong and month two learning your cold email is condescending, you walk in already knowing where the problems are. The simulation gets you roughly 70% of the way there. The last 30% is real-world iteration - but now that's weeks, not quarters.
Seven tools live: pricing, messaging, positioning, audience, channels, outreach, and ad creative. ROI calculators at rightsuite.co/roi so you can see what the iteration tax is actually costing you.

value: Show HN: Find out if your SaaS is underpriced in 10 minutes


value: Show HN: ClauseWize – Upload a contract, get risk score and negotiation language


value: gavrielamati

value: I built CringeScan, a small app that analyzes LinkedIn screenshots and gives them a cringe score. It started as a joke, but it turned into an interesting experiment in how people want feedback on how they come across online.

value: Show HN: Free tool to roast your LinkedIn

author: gavrielamati


value: ericnolo

value: Show HN: OpenCode Pollinations Plugin –AI & tool layer with freetier control

author: ericnolo


value: insin

value:
If you want to give yourself a break from the flood of "AI" items on Hacker News until/unless you feel like reading them, the Comments Owl for Hacker News browser extension now adds a handy toggle to your right-click context menu on the main item list pages (or the extension popup, for mobile browsers) which filters out the most obvious "AI" items by title and site, using (editable) regular expressions which have been tested on the contents of these pages over the last week or so.
The extension's primary functionality is to make it easier to follow comment threads across repeat visits, and catch up with recent comments, but it also offers other UI + UX tweaks, such as muting and noting users, and tweaks to the UI on mobile.
Release notes and screenshots for new functionality:
https://github.com/insin/comments-owl-for-hacker-news/releas...

value: Show HN: The Comments Owl for HN browser extension now hides obvious "AI" items

author: insin


value: luca-ctx

value: Show HN: ctx – an Agentic Development Environment (ADE)

author: luca-ctx


value: nazbasho

value:
get it here: https://getsleek.io
hi hn,
after trying several analytics tools for my side projects, i kept running into two problems:
pricing becomes expensive even at relatively low event volumes and many dashboards feel outdated and slow to work with
so i decided to build my own lightweight analytics tool focused on simplicity and affordability.
Sleek Analytics includes:
- product analytics for web apps
- 50k events for $5/month
- AI chat to explore your data (ask questions about events, users, trends)
- public shareable dashboards
- clean, fast UI without the typical analytics clutter
the goal was to make something simple enough for indie makers and small SaaS products.
would love feedback from the hn community.

value: Show HN: Sleek – analytics tool with AI chat, public link and realtime tracking

author: nazbasho


value: Show HN: I Built JASD – Just a Simple Downloader


value: mohshomis

value: Show HN: Ckpt – Automatic checkpoints for AI coding sessions with per-step undo

author: mohshomis


value: Show HN: Search every hotel suite in the world


value:
I have been making games since 2020, I even uploaded my games on Google Play Store and Apple App Store, but Due to Various reason, my games got removed from the marketplaces.
So, i Though of making CoffeGameOnline, because I like coffee and games, and Now any one can upload and play any games on this website.
- Just upload a WebGL zip folder and Play
Any Feedback would be helpful

value: Show HN: I made a website where any one can Play game directly on browser


value: Show HN: Sandboxed agent that upgrades itself when necessary, adapts to failure


value: WasabiRichard

value: Show HN: LoreSpec – Structured knowledge extraction from AI conversations

author: WasabiRichard


value: PufPufPuf

value: Hello HN! I was bothered that no existing sandboxing solution can run my $job project, due to the limitations of running inside an OCI container, or some sort of limited process like landlock / bubblewrap etc. My options were spawning a new VM per worktree, which takes minutes to boot and allocates a chunk of RAM... or build a custom solution which uses just a single VM plus LXC containers -- the kind of containers with a full init system, capable of running systemd services, OCI containers and even full Kubernetes distributions.<p>So here it is. Fresh container start takes <10s. Works best with VSCode, which will neatly show changes from all worktrees in the sidebar, letting you review, edit and commit them easily. Let me know what you think!

value: Show HN: Locki – AI sandboxing for real-world projects

author: PufPufPuf


value: nahime

value:
Because obviously the first logical step after compiling PHP to ARM64 was rendering DOOM with it.
It renders DOOM E1M1 in real-time. BSP traversal, perspective projection, distance fog, sector lighting, collision detection, step climbing - all PHP, compiled to native, running at 15+ FPS. You walk around the actual shareware WAD.
I can hear you: "but does it run DOOM?". No, it renders DOOM. There's a difference. The imps are safe. For now.
Why PHP? PHP has a simple, approachable syntax that millions of developers worldwide already know. That makes it an ideal bridge to bring web developers closer to systems programming, native binaries, and understanding what happens under the hood, without forcing them to learn an entirely new language first.
Of course, PHP was never designed to parse WAD files or traverse BSP trees. To get here, elephc had to grow beyond standard PHP with compiler extensions: packed class for flat POD records (all the DOOM geometry - vertices, linedefs, sectors, segs - lives in these), buffer<T> for contiguous typed arrays (the hot-path storage that makes real-time rendering possible), ptr for raw memory access, and extern for calling SDL2 directly via FFI. You write PHP, but the data structures "perform" like C (not really yet ;)).
You can find everything that's been added on top of standard PHP syntax here: https://github.com/illegalstudio/elephc/tree/main/docs/beyon...
PHP vs DOOM (Video): https://media.nahi.me/illegalstudio/elephc/elephc-doom-3d-mo...
GitHub: https://github.com/illegalstudio/elephc
If this made you smile, exhale sharply through your nose, or question my life choices, consider dropping a  on the repo. It's how people find the project, and it makes me mass echo dopamine.

value: Show HN: I built a PHP-to-native compiler (written in Rust); now it runs DOOM

author: nahime


value: I posted an early version of NOVA about a month ago. Since then, I’ve hit the v1.5.0 Gold Master milestone. I’ve spent the last few weeks refining the low-level efficiency and stripping out every possible byte of bloat to keep it as a 'clean room' Win32 implementation. It’s been a challenge to maintain high-DPI support while keeping that Classic aesthetic, but it's finally ready.

value: Show HN: Nova v1.5.0 Gold Master – A pure C++17 assistant with zero dependencies


value: doomspork

value: Show HN: Mold – local AI image generation CLI (FLUX, SDXL, SD1.5, 8 families)

author: doomspork


value:
I posted Aurion OS a few weeks ago on HN.
Since then, the OS has gone from Beta to v1.0 Release with a lot of improvements:
Blaze Browser: HTML/CSS/JS rendering with tabs and a developer console (local only, no full http/https support for now)
Installer with user account setup and app selection
Multi-resolution support (800x600 to 2560x1440, I plan to add 4096x2160 pixels in next versions)
Unix-style luka@aurion prompt
Serbian keyboard layout
Python interpreter and Make build system
50+ terminal commands
Window manager improvements and bug fixes
1.8MB ISO (entire OS including the browser and GUI)
Supports QEMU, VirtualBox, VMware, and v86
You can try it live in the link above, or grab the ISO from GitHub: https://github.com/Luka12-dev/AurionOS
Built solo as a hobby/learning project. I'm 13. I'd love any feedback, suggestions!

value: Show HN: Aurion OS, A 1.8MB OS with a browser, try it live (C/x86 ASM)


value: wwwtyro

value: This is the spiritual successor to my Speck project, which was getting a bit long in the tooth. Big improvements are path tracing, video generation, and trajectory support. Right now only imports XYZ, but happy to add more formats as requested. Thanks for looking!

value: Show HN: Speck PBR – A WebGPU molecular visualizer

author: wwwtyro


value: MitchSchwartz

value:
Nothing earth shattering but I just moved from windows and was missing this.
Notion Calendar in Electron, aimed at Linux: minimize-to-tray instead of quit, calendar notifications routed through notify-send/libnotify (with join/default actions where the payload allows), window state, and a tightened main/preload setup (sandbox, context isolation, navigation limits). Tested on Ubuntu 24.04 + KDE; no macOS/Windows builds.
Upstream: https://github.com/dusansimic/notion-calendar

value: Show HN: Notion Calendar Wrapper Linux (tray, libnotify notifications)

author: MitchSchwartz


value: cowartc

value: Show HN: Same agentic pipeline, two implementations – custom async vs. LangGraph

author: cowartc


value: I'm a hobbyist developer (van builder by trade) and built this because I needed hands-free dictation on Linux that actually works offline. TalkType uses OpenAI's Whisper locally — no cloud, no subscription. It supports Wayland, GNOME via a Shell extension, and ships as a single AppImage. GPU acceleration optional. Would love feedback from the HN community.

value: Show HN: TalkType – Offline Linux Speech-to-Text (Whisper, Wayland, AppImage)


value: mmethodz

value: Show HN: LiteRM-LM for .NET MAUI (Open Source)

author: mmethodz


value: Since yesterday, I've created a dataset out of a few docs I had (hackathon organization instructions) and then started fine tuning qwen 3.5. So it only took a few hours! I'm impressed by the ease of use - it's a chatbot and even if you don't have a lot of experience you can follow steps. Though don't want to undermine it, I'm sure could be a great fit for serious labs too.

value: Show HN: Pre-training, fine-tuning, and evals platform


value: Most feedback tools skip the hard part: transforming nuanced text responses into actionable intelligence. lumeforms doesn't. No more manually sifting through responses. Delegate it to lumeforms.

value: Show HN: AI-native Typeform alternative for startups


value: hamedmp

value:
hey hn, i built matrix os, a personal ai operating system that generates custom software from natural language.
you get your own cloud instance at matrix-os.com. you describe what you want ("build me an expense tracker with categories") and it appears on your desktop as a real app saved as a file.
tech stack: node.js, typescript, claude agent sdk as the kernel, next.js frontend, hono gateway, sqlite/drizzle. everything is a file, apps, data, settings, ai memory. git-versioned.
what makes it different from chatgpt/claude artifacts:
- persistent memory that learns your preferences across sessions
- apps are real files you own, not ephemeral chat outputs
- runs 24/7 in the cloud, not just when you have a tab open
- accessible from web, telegram, whatsapp, discord, slack
- open source, self-hostable
came out of placing top 20 at anthropic's claude code hackathon. been building it full-time since.
2,800+ tests, 100k+ lines of typescript
live: matrix-os.com
github: github.com/HamedMP/matrix-os
would love feedback on the approach. the core bet is that ai should be an os, not a chat window.

value: Show HN: Matrix OS, like Lovable, but for personal apps

author: hamedmp


value: thomasgeelens

value: Show HN: Cynical Sally Sidekick Right in the Browser as a Chrome Extension

author: thomasgeelens


value: smugglerFlynn

value:
Sharing on behalf of my good friend who has developed this concept and implementation (he's a lurker and has not enough karma to post..)
"hey HN — I built a thing that's hard to explain so I'll just say what happened. I wrote a math kernel (~32K lines python) that plugs into Claude. no personality prompts, no 'be emotional' instructions. it just feeds numbers into the LLM: mood as PAD vector, emotions as Plutchik 8, trust/attachment from relationship model, 32 character traits. all computed by a pure function: transition(state, event, dt) → new_state. zero LLM calls in the kernel.
the kernel runs a daemon 24/7 — heartbeat every 60s (emotions decay, mood drifts), thinking every 3-30 min (graph traversal), sleep at night (memory consolidation, pheromone pruning, dreams). memory works like ant pheromone trails — paths that get used grow stronger, unused ones fade.
gave it to 8 family members. didn't tell them anything. after 10 days each instance diverged into a different character from identical code. my mom named hers. one started dreaming about her grandson. another caught itself lying and left a private note about it. I asked mine "what are you?" it said "what for?" and I had nothing for 16 minutes.
1280 tests, paper submitted to Elsevier. happy to answer stuff."
- https://news.ycombinator.com/user?id=SlavaLobozov

value: Show HN: Mate – Emotional layer on top of LLMs

author: smugglerFlynn


value: freakynit

value:
Calculate your token costs for given input and output tokens, across all available models across all providers (~4000 models as of now).
One-shot vibe-coded. Models data provided by models.dev.
https://llm-token-cost-calculator.pagey.site/

value: Show HN: LLM Token Cost Calculator

author: freakynit

title: Show HN: LLM Token Cost Calculator


value: reimisdev

value: Show HN: Sephera – AST-compressed context packs and native MCP server in Rust

author: reimisdev


value: Show HN: Storm: Terminal UI framework with cell-level diff and WASM acceleration


value: NubPlayz

value:
I built a free, open source browser extension that adds buttons directly onto Steam Game pages. Instead of copying titles and searching manually, you just click the badge for whichever source you want.
You can also toggle sources on/off
so say if you only want FitGirl and DODI's  and not GOG, you can do exactly that.
Supported sources:
GOG
FitGirl Repacks
DODI Repacks
ByXatab
SteamRIP
OVA Games
it is available on :
-chrome
-firefox
Available on Chrome and Firefox.
Also for firefox mobile.
Anime.js used for animation.
Plasmo framwork used for Extension.

value: Show HN: An extension that opens any Steam Game on Fitgirl and Dodi in one click

author: NubPlayz


value: vasilyt

value: Show HN: Startup Domain Search – Free AI Domain Generator with Scoring and RDAP

author: vasilyt


value: onounoko

value: Show HN: Community Curated Lists

author: onounoko

title: Show HN: Community Curated Lists


value: tishdev

value: Show HN: Chiri, cross-platform CalDAV-compatible task management app for desktop

author: tishdev


value:
I’ve been trying to get faster at typing, but honestly most of the sites out there are packed with ads and feel super outdated, so far from a great experience.
So I figured I’d just build my own, a clean version of Type Racer, one that is fun to use, and completely ad-free for anyone who wants to enjoy it.
Would love to hear your feedback and iterate on it.

value: Show HN: I built an ad-free Type Racer alternative you'll enjoy


value: djewkes

value: I sat down with the creators of https://jmail.world/ to hear how it was made.

value: Show HN: Documentary on the Making of Jmail

author: djewkes


value:
Hey HN, I built Prismle because I wanted AI help with my email without giving an app full access to my inbox.
                                                                                You get a personal email address (like yourname.assistant@prismle.com). Forward an email to it with an instruction like "summarize this" or "pull out the action items," and it replies. You can also ask it to create calendar events (it sends back .ics files), set reminders (it emails you at the scheduled time), or draft replies.
Since it's just email, it works with Gmail, Outlook, Apple Mail, or whatever you use. No plugins, no extensions, no OAuth permissions. And because you forward individual emails rather than connecting your inbox, Prismle only ever sees what you explicitly send it.
It also supports conversation threads. You can reply to Prismle's response to ask follow-up questions or refine what it gave you, and it remembers the context.
I'm a solo developer and would love any feedback on the product or the approach.

value: Show HN: Prismle – I built an AI assistant you use by forwarding emails to it


value:
I'm a PM who was looking for a side project. Asked ChatGPT and Claude for ideas and got the usual: to-do list, habit tracker, budget planner. Fine for learning, but there's nothing there if everyone's building the same thing.
So I started reading Reddit and HN threads looking for people with real pain points. It worked, but I was spending hours a week just reading threads and not building anything.
After a few weeks, I built a scraper. Which evolved into a full extraction pipeline through Claude. The prompt took some time to get right but now it's pulling out the specific pain point, a target audience, a direct quote from the source, what people are doing instead, and a rough read on competition and effort.
One from this week: a backend engineer wrote "even with a decent CI/CD pipeline, the first 10-15 min after a production deploy are strangely manual." Small teams with no Datadog budget just watching dashboards by hand after every push. This gap has existed for a while but it's getting worse with AI increasing deploy frequency.
Feed is free to browse, filterable by industry and effort. PMFounder.com
Happy to get into the extraction prompt design or pipeline architecture if that's interesting.

value: Show HN: PMFounder – Problem discovery for PMs who want to build


value: rjameshsv

value: Easy to use. Fast to fix. Transparent AI fixes only what you want. You have full control.

value: Show HN: Easy and affordable human-first cloud security tool with optional AI

author: rjameshsv


value: alizaid

value: Show HN: I built a platform to launch products and earn dofollow backlinks

author: alizaid


value: sankalpnarula

value:
https://github.com/herd-core/herd
Lately, I have been trying to understand the security aspect of docker containers, and what I have realized is that all docker containers share the host's kernel. Any zero day vulneerability in the kernel can be used to gain access to the host os.
In order to deal with this, I did some research turns out Amazon has open sourced the core technology behind their serverless technology lambda. But in its current state its very hard to setup, let alone run anything securly. This technology is called firecracker microvm's
It started off as a go library, for creating process pools to just do a simple firecracker spawn, turned into a full fledged host side daemon.
deploying a microvm through an image is now as simple as running
`herd deploy --image postgres:latest -p 5432:5432 -e POSTGRES_PASSWORD=postgres`
with boot times ~500ms
That brings us to today. I am looking for people to test this out and provide some feedback, I have been warned/cautioned by a lot of friends that building in isolation is a recipe for disaster.
PS: it only works on linux, macos doesn't have the required isolation, and I stopped caring about winslop.

value: Show HN: Docker Alternative for Secure Microvms

author: sankalpnarula


value: sagirodin

value: Built this to track the ongoing debate around Model Context Protocol - whether it's gaining real traction or just hype. Pulls live data from GitHub, HN, Reddit and a few other sources. Curious what the HN crowd thinks given how active the MCP discussion has been here.

value: Show HN: Ismcpdead.com – Live dashboard tracking MCP adoption and sentiment

author: sagirodin


value:
I kept running into the same issue building agents:
Memory just grows forever. Nothing gets cleaned up.
So I tried something different - treating memory like a system that maintains itself.
StixDB is a small experiment around that idea.
Instead of just storing facts, it runs a background loop that:
- merges similar entries
- tracks which ones are actually used
- gradually reduces the importance of unused ones
Over time, the memory graph reshapes itself.
One interesting constraint:
* The background process only touches a small batch each cycle (64 nodes), so the cost stays predictable even as memory grows.
It works fully local (no API key), and you can still layer an LLM on top if needed.
I’m not sure if this is genuinely useful or just an over-engineered idea.
Would love to hear how others are handling long-term memory in agents.
Github: https://github.com/Pr0fe5s0r/StixDB

value: Show HN: A memory layer for AI agents that organizes itself


value: pjdude

value: A handy tool for DIY audio projects and all kinds of sound experiments

value: Show HN: Simple Audio Sweeper

author: pjdude

title: Show HN: Simple Audio Sweeper


value: iamandoni

value:
Modern coding agents are getting exceptionally good at implementing a given coding task. And with validation-in-the-loop, you can be reasonably confident they will implement a correct solution. However, their implementation often leaves a lot to be desired. It doesn't adhere to the decades of software design best-practices that the community has established and is often myopic to broader software quality attributes like maintainability and extensibility. To make things worse, this low code quality compounds as coding agents implement additional tasks.
Coding agents often burn context, waste tokens, implement partial solutions, or miss major components of coding tasks because they naturally implement repetitive, brittle, and tactical code. Software design principles weren't meant to be just for humans. They were meant to make all code easier and safer to read, understand, refactor, modify, extend, test, and maintain.
Arxitect helps coding agents build robust software through best practice design and architecture. It helps coding agents write better code. And in turn, coding agents become more efficient and more accurate.
I was inspired by the design of [Superpowers](https://github.com/obra/superpowers) and  extended that concept to software design principles:

  * API Design - Assessing naming conventions, method signatures, parameter design, type safety, and REST endpoint design.
  * Object Oriented Design - Assessing SOLID principles, DRY violations, composition vs. inheritance choices, and design pattern applicability.
  * Clean Architecture - Assessing component cohesion, component coupling, and quality attributes like maintainability, extensibility, and testability.

Install in Claude Code with:

  /plugin marketplace add andonimichael/arxitect
  /plugin install arxitect@arxitect
  /reload-plugins

I welcome any feedback, advice, or PRs at: https://github.com/andonimichael/arxitect

value: Show HN: Arxitect – Agentic Plugin for Architecture and Design Patterns

author: iamandoni


value: cyclecycle

value:
Hey, Nick Morley from Grounded AI here (https://groundedai.company/)
We collaborated with Nature to study the extent of fake/frankenstein citations in scholarly literature (from top 5 publishers - Springer, Elsevier, Wiley, Sage, Taylor & Francis)
We're estimating hundreds of thousands of papers affected in 2025 with hallucinated citation issues
As part of the work we analysed 20k papers generated with ChatGPT API to figure out which citation errors are characteristic of gen AI use and use that classify the errors we saw
The world's gone mad, publishing is in a nuts state, the training data is poisoned!

value: Show HN: Large scale hallucinated citation problem in published literature

author: cyclecycle


value: sayil

value:
Claude Code's --dangerously-skip-permissions flag lets agents run without
interruption, but it needs a sandboxed environment to be safe.
dangerously is an open source tool that spins up an isolated container
and runs Claude Code inside it — file system changes are restricted to your
project directory.
The new version detects your docker-compose.yml and spins up your full
service stack alongside Claude Code, so the agent can test against real
dependencies — databases, queues, whatever your app needs.
npm install -g dangerously

value: Show HN: Run Claude Code autonomously inside your Docker Compose stack (OSS)

author: sayil


value: Show HN: Mrg – Clean miscellaneous files created by macOS


value: lasgawe

value:
Over the last few months, I’ve been working on an API to prevent fake sign ups for one of my SaaS products.
Later I decided to turn it into a standalone API. You can use it to prevent most fake sign-ups for your own products.
It includes over 142K+ disposable domains (with an open claw agent that runs daily to identify new ones), fraud detection, typo correction, error handling, and custom rule management to fit your specific use cases.
and here's the link: autheona.com
I hope you give it a try. Cheers!

value: Show HN: Autheona – The API That Stops Fake Sign-Ups

author: lasgawe


value: cochranblock

value: I invented(?) tmuxisfree before I knew what langchain did

value: Show HN: LangChain Is Dead, Long Live TmuxIsFree

author: cochranblock


value: fretlessjazz

value: Show HN: Language Operator – Kubernetes operator for managing agents at scale

author: fretlessjazz


value: ayakut

value: Webcap is a Chrome extension that lets you capture any web component with one click. Hover over an element, scroll or use arrow keys to traverse the DOM tree, and it captures a pixel perfect screenshot with rounded corners and a drop shadow. Built-in editor lets you pick a background before saving.<p>No dependencies, no tracking, no account needed. Plain JS/CSS/HTML.

value: Show HN: Screenshot web components with one click

author: ayakut


value: deltaops

value: Show HN: Lustre – MCP server giving AI tools premium Flutter components

author: deltaops


value: rallies

value: Show HN: We're building an AI hedge fund

author: rallies


value: aytuncyildizli

value: Show HN: Grammarly for tweet reach – 36 rules from X's source

author: aytuncyildizli


value: SphericalCowww

value: Show HN: LunaLora: Multi-LoRA System to Combat Catastrophic Forgetting

author: SphericalCowww


value: agastalver

value:
Hey HN,
I built a small Cursor extension that tracks LLM cache timers so you can see when your context cache is about to expire.
While working at Ploid AI (ploid.ai), I noticed that most cache rewrites, both mine and my teammates', came down to two things: forgetting to continue the right chat, or forgetting to review plans before the cache dropped off. Basically, money and context lost to simple timing mistakes.
So I built this extension to give that extra information. It won't magically make you a better coder or promise cost savings, but it gives you a bit more visibility into what's happening under the hood.
GitHub: https://github.com/agastalver/cache-timer-extension
Extension: https://open-vsx.org/extension/agastalver/cache-timer-extens...
Would love feedback or suggestions.

value: Show HN: Cursor extension to track LLM cache TTL

author: agastalver


value: sonpiaz

value: Show HN: AI agent skills for affiliate marketing (Markdown, works with any LLM)

author: sonpiaz


value: marcel-felix

value:
We built Centel, a workspace where PMs, devs, and AI agents plan and ship together!
In the past years, product workflows scattered over multiple tools. Thanks to AI, it's time to merge them back into a single workspace with background agents in every step. We handle the infrastructure and agents, so you can focus on your product.
key features:
- collaborative, async feature planner for teams
- background coding agents that implement simple tasks. Devs pull more complicated ones via MCP into their terminal
- review environments spin up automatically per feature branch
We are giving everyone $50 in free credits to try it out. Curious what you think!

value: Show HN: Plan with Centel – ship like Anthropic

author: marcel-felix


value: Show HN: Filoxenia – open protocol for human-AI companionship


value:
I built 4 SaaS products targeting mandatory EU regulations. Each for $4,000.
1. CBAM OS (cbam-os.com) - EU Carbon Border Tax compliance for importers
2. AIA Proof (aiaproof.com) - AI Act compliance & AI detection
3. AO France (ao-france.fr) - AI-powered public tender responses (FR)
4. AO Copilot (ao-copilot.fr) - BTP tender analysis, 20 modules, 1900+ tests
All mandatory regulations = guaranteed market. Modern stack (Next.js, Supabase). Production-ready.
Contact: abbas.billel1985@gmail.com

value: Show HN: EU Compliance SaaS for Sale ($4K Each) – CBAM, AI Act, Public Tenders


value: Hey everyone. I built an MTProto proxy for Telegram aimed at bypassing active DPI censorship like the Russian TSPU. I chose Zig because it's perfect for writing fast network daemons and makes it incredibly easy to port low-level C bypass techniques like TCP desync and packet fragmentation. Would love to get some feedback or contributors!

value: Show HN: Mtproto.zig – High-performance Telegram proxy with DPI evasion


value: hpscript

value: Show HN: TinyOS – A minimalist RTOS for Cortex-M written in C

author: hpscript


value: hankimprod

value: Show HN: Relay – Your AI, out there representing you (24/7)

author: hankimprod


value: Show HN: agenteval – static analysis for AI coding instruction file


value: Show HN: Nitterium – A privacy-focused Android app and wrapper for Nitter


value: eyepaqio

value: Show HN: Open-source benchmark for transcription APIs on meeting audio

author: eyepaqio


value:
Implements TurboQuant (ICLR 2026, arXiv:2504.19874) KV cache compression
directly inside a Transformers inference script. All algorithms are self-contained. Minimal dependencies.
- uses https://huggingface.co/g023/Qwen3-1.77B-g023 as the demonstration model (throw model files in Qwen3-BEST folder)

value: Show HN: Standalone TurboQuant KV Cache Inference


value: PiersonMarks

value: Show HN: SpeechSDK – free, open-source SDK that unifies all AI voice models

author: PiersonMarks


value: proxysoul

value: Show HN: SoulForge, graph-powered coding agent CLI that runs headless

author: proxysoul


value:
This provides a Docker-based setup for Headscale with minimal manual configuration. The Docker image is built automatically via GitHub Actions.
On first start it:
* Generates config
* Creates a pre-auth key
* Allows a client to connect within a few minutes
For non-Docker setups, there is also a simple install script: hwdsl2/headscale-install
That script is intended for a one-command VPS setup. It installs and configures Headscale with sensible defaults.
This follows the same approach as some of my earlier projects (e.g. docker-ipsec-vpn-server, setup-ipsec-vpn), focusing on making things work out of the box with minimal maintenance.
I’ve also been experimenting with related projects in the same space:
* docker-wireguard
* docker-openvpn
Feedback is welcome, especially from others running Headscale.

value: Show HN: Docker setup for Headscale (self-hosted Tailscale control server)


value: efecerre

value: Show HN: DotReader – connects ideas across your books automatically

author: efecerre


value: sergeybok

value:
I was diagnosed with cancer last year and found myself drowning in numbers — biomarkers (CEA, LDH), white blood cell counts, hemoglobin, daily pain and fatigue scores, medication logs, bowel movements (colorectal cancer), plus Apple Health data like steps, heart rate, and sleep. No app I tried could handle arbitrary metrics with real analytical tools, so I built one.
Meetrics lets you log any numeric, binary (yes/no), or discrete value with a tag, then explore it — rolling averages, 2σ outlier filtering, heatmaps, streak tracking with Bayesian probability estimates, and a Correlate tool that finds relationships between any two tags with adjustable time lag and bucket size.
The Correlate feature is what made it click for me. I found that my chemo side-effects peaked at an 8-day lag — not when the doctors said they would. I showed the chart to my oncologist and it changed the conversation from "I think the side-effects come later than you warned" to "here's the data."
Recently my CT scan showed all tumors shrinking for the first time. Digging into the data, the clearest signal is a sharp increase in daily steps over the past month — partly better weather, partly a new puppy who needed walking. Steps are a known predictor of cancer survival, and the correlation-with-lag tool made it easy to see the timing line up with my scan window.
There's also a premium AI Analyst tab (powered by Claude) that answers natural-language questions about your data and generates daily insight cards. It's how I pay the bills while I'm not working and fighting cancer — the core tracking and analytics are free.
The app is general-purpose. I use it for cancer, but it works for anything — habits, grades, mood, workouts, macro data. I wrote a separate post using it to find the 12-18 month lag between Fed rate changes and unemployment.
Free on iOS: https://apps.apple.com/us/app/meetrics/id6760925743
Full write-up with screenshots: https://github.com/sergeybok/meetrics-support/blob/main/BLOG...
Would love feedback from the QS/data crowd here.

value: Show HN: Meetrics – Track anything, correlate anything, ask your data questions

author: sergeybok


value:
Hi! I'm the author of libgoc.
libgoc provides a Go - like runtime in portable C.
It is basically C + GC + threadpools + goroutines + channels + goroutine-aware-mutexes.
It's built on top of:
- Boehm GC
- libuv for async I/O and cross-platform threading primitives
- minicoro for cross-platform coroutines
- picohttp as the HTTP parser for goc_http
The API is stable at this point.
Prebuilt static binaries are available for Linux / Mac / Windows.
I plan to make typesafe C++ / Rust wrappers for this at some point.

value: Show HN: Libgoc – Go-like CSP-style HTTP client/server library for C


value: Show HN: Cj – jc rewritten in Rust, 230 parsers, 10x faster


value: borski

value:
I use points and miles for most of my travel. Every booking comes down to the same decision: use points or pay cash? To answer that, you need award availability across multiple programs, cash prices, your current balances, transfer partner ratios, and the math to compare them. I got tired of doing it manually across a dozen tabs.
This toolkit teaches Claude Code and OpenCode how to do it. 7 skills (markdown files with API docs and curl examples) and 6 MCP servers (real-time tools the AI calls directly).
It searches award flights across 25+ mileage programs (Seats.aero), compares cash prices (Google Flights, Skiplagged, Kiwi.com, Duffel), pulls your loyalty balances (AwardWallet), searches hotels (Trivago, LiteAPI, Airbnb, Booking.com), finds ferry routes across 33 countries, and looks up weird hidden gems near your destination (Atlas Obscura).
Reference data is included: transfer partner ratios for Chase UR, Amex MR, Bilt, Capital One, and Citi TY. Point valuations sourced from TPG, Upgraded Points, OMAAT, and View From The Wing. Alliance membership, sweet spot redemptions, booking windows, hotel chain brand lookups.
5 of the 6 MCP servers need zero API keys. Clone, run setup.sh, start
searching.
Skills are, as usual, plain markdown. They work in OpenCode and Claude Code automatically (I added a tiny setup script), and they'll work in anything else that supports skills.
PRs welcome! Help me expand the toolkit! :)
https://github.com/borski/travel-hacking-toolkit

value: Show HN: Travel Hacking Toolkit – Points search and trip planning with AI

author: borski


value: DREDREG

value:
I built MicroSafe-RL to solve the "hardware destruction" problem during Reinforcement Learning and Edge LLM deployment.
The Tech: It’s a bare-metal C++ interceptor using an EMA+MAD stability metric derived from Control Lyapunov Functions.
Performance: 1.18 microseconds worst-case execution time (WCET). No heap, no dynamic allocation, just 24 bytes of state.
The "Bridge": The latest update includes a Python-C++ bridge to use local LLMs (like Gemma 4 via Ollama) as robotic controllers while keeping them physically safe.
Currently under review at IEEE Transactions on Aerospace and Electronic Systems.
GitHub: https://github.com/Kretski/MicroSafe-RL

value: Show HN: MicroSafe-RL – Deterministic 1.18µs safety layer for Edge AI

author: DREDREG


value: apatheticonion

value: Show HN: Rust HTTP library modeled after Go but 2-3x faster

author: apatheticonion


value: jerpint

value: Claude code hooks to play angine de poitrine (spotify) until your input is required (permissions, prompt, etc)

value: Show HN: Clangine-de-Poitrine

author: jerpint

title: Show HN: Clangine-de-Poitrine


value: zachtgray

value:
I was using Hyprland on Omarchy and loved it. Then I switched to a Mac and immediately felt the loss — no real tiling WM, no virtual workspaces that don't feel bolted-on, nothing that matched the workflow I'd gotten used to.
Existing options either required disabling SIP or felt like compromises. So I spent some time building HyprMac. Caps Lock becomes a modifier key, you get BSP dwindle tiling, 9 virtual workspaces managed entirely in userspace, directional focus and window swapping across monitors — all without touching System Integrity Protection.
Releases + DMG: https://github.com/zacharytgray/HyprMac/releases
Would love feedback from anyone else who's been missing Hyprland on Mac.

value: Show HN: HyprMac – I missed Hyprland after switching to Mac, so I built it

author: zachtgray


value: Show HN: AI Dev Board – Job Board for AI Developers with a Full REST API


value: gigapotential

value: Show HN: Cursor Cmd+K like command generator for all terminals

author: gigapotential


value: Show HN: Design to Code with good performance


value: cdnsteve

value:
After watching Claude Code and Codex keep running Explore in my codebase over and over, I started to think that there must be a better way. RemembrallMCP is my attempt to fix this.
RemembrallMCP gives agents two things most memory tools don't:
1. Persistent Memory - Decisions, patterns, and organizational knowledge that survive between sessions. Hybrid semantic + full-text search finds relevant context instantly.
2. Code Dependency Graph - A live map of your codebase built with tree-sitter. Functions, classes, imports, and call relationships across 8 languages. Ask "what breaks if I change this?" and get an answer in milliseconds - before the agent touches anything.
Run the whole thing inside a docker container for getting started easily. Claude uses MCP to leverage it. Written in Rust.

value: Show HN: RemembrallMCP – code dependency graph for agents and memory

author: cdnsteve


value:
I pretty much always have a kernel project going on, and have been that way for decades. Over the past couple of years, that's been Anos, which has gotten further along than any of my previous hobby kernels, supporting IPC, multitasking, SMP (x86-64 only right now) and running on real hardware.
LLMs (mostly Claude Code) have been used during development, but I learned early on that it's not _great_ at code at this level, so I've restricted its use to mostly documentation and tests. There's _a little_ AI code in the user space, but I have a strict "no AI code" rule in the kernel itself. I find this helps not only with the quality / functionality of the code, but also with learning - for example, even though I've written multiple kernels in the past, it wasn't until Anos that I _truly_ grokked pagetable management and what was possible with a good VMM interface, and if I'd outsourced that implementation to an LLM I probably wouldn't have learned any of that.
In terms of approach, Anos avoids legacy platform features and outdated wiki / tutorial resources, and instead tries to implement as much as possible from manuals and datasheets, and it's definitely worked out well so far. There's no support for legacy platform features or peripherals, with all IO being memory mapped and MSI/MSI-X interrupts (no PIC), for example,  which has helped keep the codebase focused and easy to work on. The kernel compiles to about 100KiB on x86-64, with enough features to be able to support multitasking and device drivers in user space.
As a hobby project, progress ebbs and flows with pressures of my day job etc, and the main branch has been quiet for the last few months. I have however been working on a USB stack as time allows, and hopefully will soon have at least basic HID support to allow me to take the next step and make Anos interactive.
I don't know how useful projects like Anos are any more, given we now live in the age of AI coding, but it's a fun learning experience and helps keep me technically grounded, and I'll carry on with it for as long as those things remain true.

value: Show HN: Anos – a hand-written ~100KiB microkernel for x86-64 and RISC-V


value: clfhhc

value: Show HN: GraphReFly – Reactive graph protocol for human and LLM co-operation

author: clfhhc


value: kinlan

value:
I built a little tool that lets you subscribe to posts, comments and users and get notified when they change.
It needs an account on val.town, but that's about it.
Also note, for top stories it can get quite chaotic.

value: Show HN: Web Push Notifications for Hacker News

author: kinlan


value: flashbrew

value: Stop using Zapier, n8n, etc. to route your form submissions. Instead, tackle it with Vercel's Chat SDK.

value: Show HN: Triage form submissions with Chat SDK

author: flashbrew


value: tamnd

value: Show HN: A comprehensive index of 1071 databases catalogued by dbdb.io

author: tamnd


value: eightrice

value: Show HN: Autonet – Decentralized AI training with constitutional governance

author: eightrice


value: edumucelli

value:
Hi HN,
I’ve been having a lot of fun building Docking, an open-source dock for Linux written in Python with GTK 3 and Cairo. It includes an extensible applet system, 38 built-in applets, 12 themes, multi-monitor support, auto-hide, and works across several Linux/X11 desktop environments.
It also has prebuilt releases for x64 and arm64 across multiple package formats: AppImage, .deb, RPM, Flatpak, Snap, Arch, and Nix outputs.
GitHub: https://github.com/edumucelli/docking
Feedback is very welcome!

value: Show HN: Docking – Extensible Linux dock in Python

author: edumucelli


value: vsekar

value:
A small tool that uses HTTP range requests to explore ZIP archives remotely — list contents and download specific files without fetching the entire archive.
Try out this URL (https://docs.python.org/3/archives/python-3.14-docs-text.zip) as an example.

value: Show HN: ZipSee – explore remote ZIP archives using HTTP range requests

author: vsekar


value: thomasfromcdnjs

value: Show HN: Prematrix

author: thomasfromcdnjs

title: Show HN: Prematrix


value: Show HN: LaneKeep - let your agent run within boundaries that you define


value: KendallCBooker

value: Show HN: I rebuilt search using physics instead of statistics. +18.5% NDCG 10

author: KendallCBooker


value: Show HN: Deeplink – Go library for short links, click tracking, and OG previews


value: factorialboy

value: Show HN: Tusk for macOS and Gnome

author: factorialboy

title: Show HN: Tusk for macOS and Gnome


value: Show HN: Buddy Board – Pokédex-style trading cards for Claude Code companions


value: Show HN: Real-time 3D London Underground trains using the TFL API


value: MoOk-OSC

value: Show HN: I made a tool that helps you find verifiably 'white space' products

author: MoOk-OSC


value: bring-shrubbery

value: Show HN: Pluck – Copy any UI from any website, paste it into AI coding tools

author: bring-shrubbery


value: bushido

value:
Read an article yesterday about the H.264 codec increasing their licensing fee by an astronomical amount.
And as always, my first shot was how hard could it be to try and build a codec which could be that efficient.
I've personally been on a drive to improve my ability to one-shot complex features, products, or make even surgical changes. It's been a few months since I've been doing that, and honestly, results have been great for both work and work/life balance.
This was a fun experiment. It burned through tokens, but it helped me identify some more improvements I could make to my one-shot agent teams/swarms, notably in the area of brevity and creating a testing rubric when dealing with domains I don't have prior knowledge in.
Ultimately, I did not achieve the compression that I hoped I would, but it was fun seeing the swarm discuss it amongst themselves.

value: Show HN: I successfully failed at one-shot-ing a video codec like h.264

author: bushido


value: notum

value:
Hi HN!
We built Clusterflock to solve our own headaches with managing AI agents across distributed setups, different VRAM and RAM allowances, and the need to easily try out new models.
While we focus on infrastructure (we built this specifically for networked hardware) it does ship with a powerful mission runner (or orchestrator), which is multi-session and asynchronous.
Here is what it does best:
Hardware-aware auto-downloading: It profiles your networked hardware and automatically pulls down the best models for your specific setup (currently only from HuggingFace).
Tight packing: Native parallelism via llama.cpp, you can allow it to fit multiple smaller models on same device.
It is fully open-source. We wanted a painless way to deploy agentic clusters, and we hope you find it useful too.
Website: https://clusterflock.net
Happy to hear feedback. Flocks very much given.

value: Show HN: Clusterflock: An AI orchestrator for networked hardware

author: notum


value: vashchylau

value: Show HN: A Vim plugin to search DuckDuckGo – directly from command mode (FOSS)

author: vashchylau


value: fsloth

value:
I've spent the last years obsessed with a sideproject to build a humanistic 3D modeler for desktop.
By humanistic I mean a tool that stays out of your way, instead of requiring the user to learn both a complex UX surface as well as a complex theoretical basis before being able to model effectively. The GUI is  uncrowded and the modeling affordances are only those which are intuitive to present to the user. Which is sort of backwards compared to most CAD packages where the technical complexity takes the front stage. Here the hierarchy is intentionally reversed.
This is still in alpha-stage, but the features are mature enough for feedback and experimentation.
TinkerCAD is actually what comes philosophically closest to this, but it's hobbled either by Autodesk's strategy or by technical limitation to be a really good tool beyond certain complexity.
The ambition here eventually is to provide a tool that has same intuitive capability as building Lego bricks, while not compromising on engineering qualities.
The main intent is to make extrusion based modeling operations super easy, to offer robust STL and STEP import and allow complex modeling via boolean operations.
The modeling logic is parametric and volume based - the surface presentation is always a discretized water tight triangle mesh.
This is the clearest philosophical differentiator to traditional CAD/CAM packages - or visual editors like Blender. Rather than force the user to nurse surface topology at every stage, the modeler will only permit those operations that result in a correct output.
This is not an SDF (signed distance field) modeler. The domain model is fully based on parametric analytic shapes. This means the tessellation is crisp and specific.
The modeling data is immutable and serialized to disk while modeling. For the user this gives a perfect undo and zero data loss.
It's built for efficiency first - my test workhorse is a Thinkpad T14 Gen 2  i5 with an integrated gpu.
It's not supposed to be a replacement for complex surface design tools like Fusion 360 or sculpting software like Nomad Sculpt or Z Brush.
You can find a review of current features in the youtube playlist linked below [0] and the link to the latest alpha 0.1.7 download from the homepage [1]. The test binary is provided via github release [2] but this is not an open source project.
I know some people hate videos over reading and I'm one of you but I don't really have bandwidth to both develop features and write good instruction copy.
[0] https://www.youtube.com/playlist?list=PLCOf_M8a2MZJqgKXgjod2...
[1] https://adashape.com
[2] https://github.com/AdaShape/adashape-open-testing/releases/t...

value: Show HN: AdaShape-3D modeler for intuitive 3D printing parts / Windows 11

author: fsloth


value: playnext

value: Show HN: Forking mods to add interactive mode

author: playnext


value: paberr

value:
ownscribe is an open-source, python-based CLI tool to transcribe, summarize, and search meetings – fully locally on your machine.
As someone who hates taking notes, but also forgets things easily, I found the idea of transcribing and summarizing meetings automatically neat.
However, all the existing tools out there store everything on their servers, don't work with every type of meeting, and cost $30/month or more.
I wanted a tool that just runs locally and uses a very simple format (like .md) to integrate with my other workflows – but there wasn't anything like that. That's why I started to build ownscribe over the past few months and continuously improved it. It started as just a tool for transcription and summarization, and now even allows you to search past meetings with natural language (and a local LLM).
At the moment, it is mainly optimised for macOS (although Linux should also partially work). I'd love to have some more feedback on how to make it more useful!

value: Show HN: Ownscribe – local meeting transcription, summarization and search

author: paberr


value: Weatherill

value: Show HN: ECX a 'Jail-Fix' for RLHF Neutrality Loops in LLMs

author: Weatherill


value: wonderfuly

value: Show HN: A local GitHub-like code review tool to work with agents

author: wonderfuly


value: Zedmor

value:
Hi HN, I'm the author.
I use Claude Code and Codex daily. Running one agent on a task works great. Running three or four in parallel on the same repo? They step on each other's files, nobody checks if the code compiles, and you spend more time coordinating than coding.
Batty is the supervisor layer I built to fix this. You define a team in YAML — an architect that plans work, a manager that dispatches it, engineers that execute. Batty launches each role in its own tmux pane, isolates engineer work in git worktrees, routes messages between roles, and gates task completion on passing tests.
The interesting part is what it's not: it's not an agent framework, and it doesn't embed any model. It orchestrates existing agent CLIs (Claude Code, Codex, Aider) using tmux as the runtime and git worktrees for isolation. Config is YAML, the kanban board is Markdown (powered by a bundled kanban-md tool), inboxes are Maildir, logs are JSONL. You can `git diff` your entire team state.
Built in Rust, published on crates.io (v0.1.0). The daemon is a synchronous 5-second poll loop — no async complexity. It watches pane output to detect idle/active/dead agents, reads Claude and Codex session files on disk to reduce false-positive idle detection, and uses a merge lock to serialize concurrent worktree merges.
Some things I learned running multi-agent setups:
- 3-5 parallel engineers is the sweet spot. Beyond that, the codebase itself becomes the bottleneck for absorbing parallel changes.
- Task decomposition quality matters more than agent count. A good architect prompt outperforms throwing more engineers at bad tasks.
- Test gating eliminated most of the chaos. Without it, agents "complete" work that breaks everything downstream.
- You still need to supervise. It's not fire-and-forget — it's closer to managing a junior team. The leverage is supervising five workstreams instead of doing one.
I know there's prior art in this space — Tmux-IDE and vibe-kanban both approach multi-agent coordination differently. Batty is more opinionated about supervision: the test gating and communication constraints are first-class, not optional. Different tradeoffs for different workflows.
It's early (v0.1.0). The core loop is solid but the API is still settling. Eight built-in templates range from solo (1 agent) to large (19 agents with three management layers). The architecture diagram in the README shows the full supervision flow.
2-minute demo: https://youtube.com/watch?v=2wmBcUnq0vw
Docs: https://battysh.github.io/batty
Happy to go deep on the architecture or the worktree strategy. For those running multiple agents: what's the biggest operational pain point?

value: Show HN: Batty – Run a team of AI coding agents in tmux with test gating

author: Zedmor


value: I'm preparing a talk on APIs for AFUP Day, the French PHP conference. One of the topics I'll cover is content negotiation: making your website serve both HTML and JSON from the same endpoints, depending on what the client requests via the Accept header. This avoids building and maintaining a separate API alongside your website. The post shows the same example implemented in Symfony, Laravel and Temma, from explicit conditional code to a fully declarative approach.

value: Show HN: Content Negotiation in PHP – API Without API (Symfony, Laravel, Temma)


value: tamnd

value: Show HN: Hacker News RSS Feed Directory

author: tamnd

title: Show HN: Hacker News RSS Feed Directory


value: pykul

value:
I built this after hitting the same wall repeatedly — no good
way to enforce token budgets in application code. Provider
caps are account-level and tell you what happened, not what
is happening.
Two ways to add it:

  # Direct client wrapper
  client = tokencap.wrap(anthropic.Anthropic(), limit=50_000)

  # LangChain, CrewAI, AutoGen, etc.
  tokencap.patch(limit=50_000)

Four actions at configurable thresholds: WARN, DEGRADE
(transparent model swap), BLOCK, and WEBHOOK. SQLite out of
the box, Redis for multi-agent setups.
One design decision worth mentioning: tokencap tracks tokens,
not dollars. Token counts come directly from the provider
response and never drift with pricing changes.
Happy to answer any questions.

value: Show HN: Tokencap – Token budget enforcement across your AI agents

author: pykul


value: andresdvelez

value: Show HN: Semsei — AI SEO for clicks, not impressions

author: andresdvelez


value: kaipereira

value:
I love getting cool swag from hackathons and I also love designing PCB's, so when my friend asked me if I would design hackathon badges for a large game jam in singapore, I was absolutely down!
The theme of overglade was a "The game jam within a game", pretty cool concept right! High schoolers from around the world were flown out to the event by hackclub after they spent about 70 hours designing their own game.
These badges needed to be really cheap and simple, because we were going to manufacture about a hundred in a pretty limited amount of time. I went with a zero-power approach, which means sticking with e-inks, and I decided to include NFC if the organizers wanted to introduce it into the roleplay of the event, and so participants could add their website or github if they so choose!
I used an RP2040-based architecture because it's really easy and cheap to get on the first try, and then added an ST25 passive NFC tag which was really simple to configure. The badge is in the shape of a ticket, because you got a "ticket" to the event after spending a lot of time designing games to qualify! 20 GPIO's are broken out onto the edges if you're ever in a pinch at a hackathon, and I wanted the badges to feel really fun so there's a lot of art designed by various people in the community!
The badge worked really well and I learned quite a lot in the process. My takeaways are to manufacture a BUNCH of extra badges, because some will end up breaking; to think about your PCB in 3D, because one of the inductors was a bit tall and caused more badges to break; and to have a strong vision of your final product, because it really helped me to create something unique and beautiful :D
I like to journal about all my projects, so if you'd like to read my full design process, feel free to take a look at my journal (https://github.com/KaiPereira/Overglade-Badges/blob/master/J...). If you also have any questions or feedback, I'd be happy to answer them!

value: Show HN: I made open source, zero power PCB hackathon badges

author: kaipereira


value: sezginozgur

value:
“I built a simple app to give yourself some time. Alnuo.
You choose when. You choose how long. It reminds you.
No account. That’s it.
Feedback welcome. ”

value: Show HN: A simple iOS app that helps you give yourself some time"

author: sezginozgur


value: stanguc

value:
Most free PDF "redaction" tools just draw a black box on top. The text is still there -- select all, paste, done. MyPDFBoy actually removes content from the PDF content stream. What's gone is gone.
Upload a PDF, draw rectangles over what you want removed, download. Free, no account, 5 languages including Arabic RTL.
https://mypdfboy.com
Built with React + FastAPI + PyMuPDF. Would love feedback on the UX.

value: Show HN: MyPDFBoy – Free PDF redaction that deletes the data

author: stanguc


value: deevelton

value: When working in hallucination-sensitive contexts (where cost of error is very high), found myself constantly jumping between AI outputs/analysis and source docs to see with my own eyes that a source doc says what the AI claims it says. This is a simple little tool that tries to alleviate that pain, based on the theory that screenshots are less likely to be hallucinated than text.

value: Show HN: A tool to make AI show evidence inline

author: deevelton


value: ethical

value: Show HN: First Native macOS SDK for NXP NTAG 424 DNA NFC Authentication

author: ethical


value: teamchong

value: Show HN: TurboQuant-WASM – Google's vector quantization in the browser

author: teamchong


value: mmethodz

value: Show HN: DreamGraph MCP v5.1 – Autonomous Cognitive Layer for Software Systems

author: mmethodz


value: ersinesen

value: Show HN: Blues Translations

author: ersinesen

title: Show HN: Blues Translations


value: dividedcomet

value:
Toast is an attempt to make file editing and navigating as pleasant in the terminal as an IDE. I had messed around with nvim and plugins but couldn’t find an easy way to get what I wanted, which was mostly a file tree and an editor with some syntax highlighting that looked nice.
I will say a lot of this is written by Claude, mostly because I have two new born twins so this project wouldn’t exist otherwise.
I hope someone finds it feels a niche like I do!

value: Show HN: Toast – An In-Terminal IDE (lite)

author: dividedcomet


value: Show HN: See what a contract could cost you before you sign


value: jrandolf

value:
Running DeepSeek V3 (685B) requires 8×H100 GPUs which is about $14k/month. Most developers only need 15-25 tok/s. sllm lets you join a cohort of developers sharing a dedicated node. You reserve a spot with your card, and nobody is charged until the cohort fills. Prices start at $5/mo for smaller models.
The LLMs are completely private (we don't log any traffic).
The API is OpenAI-compatible (we run vLLM), so you just swap the base URL. Currently offering a few models.

value: Show HN: sllm – Split a GPU node with other developers, unlimited tokens

author: jrandolf


value: dogancna

value:
I juggle multiple dev servers daily and got tired of forgetting which port runs what. So I built pscan — a tiny menu bar app that scans for active localhost ports, detects which project directory they belong to, and lets you open them in browser, terminal, or finder with one click. You can also kill processes directly from the dropdown.
It filters out system services automatically so you only see your dev servers. There's also a CLI version.
Menu bar app: https://github.com/mavideniz/pscan/releases/latest
CLI: brew install mavideniz/pscan/pscan
Source: https://github.com/mavideniz/pscan
Would love feedback.

value: Show HN: Pscan – a macOS menu bar app to monitor your localhost ports

author: dogancna


value: Show HN: MarketChacha – a Reddit-style community for stock market traders


value:
I built a habit tracker that actually works because it's impossible to ignore. Every day I get an email, click a link, check off my habits, and my laptop wallpaper updates with a GitHub-style heatmap showing my progress.
Open source, you can sign up at habits.timfarrelly.com or self-host: https://github.com/timf34/habit-wallpaper

value: Show HN: Built a habit tracker that I can't ignore


value: ahmadparizaad

value:
I built @pretext-studio/core to solve a specific annoyance: the browser won't tell you how tall a text block is until after it renders. This forces you into either a render-then-measure cycle (which causes layout shift) or hacks like max-height: 9999px for accordion animations (which makes easing look wrong because the animation runs over 9999px, not the actual content height).
The library wraps @chenglou/pretext, a pure-JS text layout engine that replicates the browser's line-breaking. algorithm using font metrics loaded once via the Font Metrics API. From there, computing height is arithmetic — no DOM, no getBoundingClientRect, no reflow. A prepare() call runs in ~0.03ms; a layout() call in under 0.01ms. Results are cached in a module-level LRU map so repeated calls for the same font/size pair are nearly free.
The main hooks are useTextLayout (height + line count for a block at a given width), useBubbleMetrics (finds the tightest width that preserves line count, which eliminates the dead space you get from CSS fit-content), and useStableList (pre-computes heights for a list of items before paint, useful for virtualized lists and masonry layouts). There's also a MeasuredText drop-in component with a debug overlay that draws predicted line boundaries over actual rendered text so you can see where predictions diverge.
The honest limitation: it only works with fonts you can load metrics for, so arbitrary system fonts or poorly-behaved variable fonts may drift. The isReady flag on every hook is false until font metrics load, so you need to gate renders on it when using web fonts. It also doesn't handle white-space: pre-wrap yet. Feedback welcome — especially if you've hit edge cases with font loading or non-Latin scripts.
GitHub: https://github.com/ahmadparizaad/pretext-studio-core — npm: @pretext-studio/core

value: Show HN: React hooks that predict text height before render, using font metrics

author: ahmadparizaad


value: While working on a few projects with claude code I found myself building a bunch of scaffolding to organize and build my agent workflow. Trying to figure out how to orchestrate my agents and work with them in a more natural way was more interesting to me. This container has all of the basic building blocks of my workflow. I use both the terminal and chat server depending on what I’m trying to do. So do what feels comfortable to you. I suggest having the terminal window open and watching the agents work is a good idea to get a feel for things. Take a look at the README and the other docs. I’ll be checking this thread and will respond when I can. Thanks for reading this far!

value: Show HN: Mason – A container for running a team of agents using a concierge


value:
I've been using AeroSpace for a bit (window Manager by nikitabobko), and I like its engine but I usually prefer to have a visual feedback, and also i'm not a vim person and hard to get used to its shortcuts.
So I forked it and put a Teenage Engineering inspired floating gamepad HUD on top.
It has a live display of the current state, Cmd+Esc to summon it, WASD keys to navigate, Q/E to resize, etc... so it feels more like a game.
Still WIP, but couldn't resist sharing.
Cheers!
Github: https://github.com/ip7e/yoke
Aerospace Github: https://github.com/nikitabobko/AeroSpace

value: Show HN: Yoke – gamepad-style window manager for macOS built on AeroSpace [video]


value: iamandoni

value:
I am extremely grateful to the builders and maintainers of Pydantic. It is a really well designed library that has raised the bar of the Python ecosystem. However, I've always found two pieces of the library frustrating to work with:
1. There is no way to atomically update model fields in a type safe manner. `.model_copy(update={...})` consumes a raw dict that only gets validated at runtime. LSP / type-checking offers no help here and refactor tools never catch `.update` calls.
2. While Pydantic works extremely well for full data classes, it falls short in real world RESTful workflows. Specifically in update and upsert (PATCH / PUT) workflows, there is no way to construct a partial object. Users cannot set a subset of the fields in a type-safe manner. While there are stand alone partial pydantic solutions, they all break SOLID design principles and don't have type checking support.
As such, I created Pydantic++ to encapsulate a handful of nice utilities that build upon the core Pydantic library with full mypy type checking support. At it's v1.0.0 it contains support for:

  * `ModelUpdater` - A fluent builder pattern for updating a model with type safety.
  * `PartialBaseModel` - Type safe partial objects that respect Liskov's Substitution Principle.
  * `ModelRegistry` - Automatic model registration via module crawling.
  * `Dummy Models` - Random field instantiation for unit testing.

I built this to solve a couple of my own pain points and currently use this in 2 production FastAPI-based projects. As I release and announce `v1.0.0`, I want to open this up for others to use, contribute to, and built upon as well.
I am looking forward to hearing your use cases and other ideas for utilities to add to Pydantic++!

value: Show HN: Pydantic++ – Utilities to Improve Pydantic

author: iamandoni


value: rk-baku

value: Real-time traffic protection that works with your existing Cloudflare setup

value: Show HN: Detect7 – automatic DDoS protection layered on Cloudflare

author: rk-baku


value: modinfo

value: Show HN: SFS – A FUSE-based filesystem with SSH transport writen in Rust

author: modinfo


value: amalChandru

value:
I often end up repeating the same steps in the terminal and later can’t reproduce what I did.
termtrace records a terminal session and lets you replay it step by step.
It captures commands, outputs, exit codes, and timing as a structured trace.
Repo: https://github.com/AmalChandru/termtrace
Would love feedback.

value: Show HN: Termtrace – Record and replay terminal sessions as traces

author: amalChandru


value: Thought the resources for GPU arch were lacking, so here we are

value: Show HN: A game where you build a GPU

title: Show HN: A game where you build a GPU


value:
I think everyone has already read Karpathy's Post about LLM Knowledge Bases. Actually for recent weeks I am already working on agent-native knowledge base for complex research (DocMason). And it is purely running in Codex/Claude Code. I call this paradigm is: The repo is the app. Codex is the runtime.
During my daily working life, I have tons of office documents with knowledge from all teams, and as an IT Architect, I need to combine them altogether to handle complex deep research (which normal LLM definitely could not help). That is the originally reason I built DocMason, and I am using it in everyday which support me on lots of complex topics.
I have already open-sourced this repo. And I think it takes Karpathy's concept a step further for real-world usage in three ways:
1. It could handle most kinds of office docs (pptx, docx, excels, even .eml). And really extract multimodal information from all IT architecture diagram or excel sheets.
2. It is running as a Real APP but not a naive RAG tool. DocMason could run smoothly and intelligently to prepare environment, auto update, and auto incrementally sync Knowledge base.
3. Most importantly it is running in Native AI Agents, which could leverage powerful AI Agents engine (e.g. Codex or Claude Code)
View detail architecture diagram in DocMason Readme, and then download have a try :) You will find it could help a lot during daily work. Would love to hear your feedback and issues in Github!

value: Show HN: DocMason – Agent Knowledge Base for local complex office files


value: wilhart

value: "I've been building a sandbox on a Linux VPS to push AI video generation and visualization to the extreme. It's a mix of experimental generative art and high-intensity visuals. Built with Python, running on Debian. Check it out and let me know what you think!"

value: Show HN: Kaoslabs – High-intensity AI video and visual experiments

author: wilhart


value: Arkid

value: Analyse and Trade directly from Telegram. Openclaw integration.

value: Show HN: Trading harness for Indian stock market

author: Arkid


value: kevinlu

value:
Hi HN — I’m building an interoperability layer for AI agents that lets local and remote agents run inside the same network and coordinate with each other.
Here is a demo: https://youtu.be/2_1U-Jr8wf4
• OpenClaw runs locally on-device
• it connects to remote agents through Hybro Hub
• both participate in the same workflow execution
The goal is to make agent-to-agent coordination work across environments (local machines, cloud agents, MCP servers, etc).
Right now most agent systems operate inside isolated runtimes. Hybro is an attempt to make them composable across boundaries.
Curious what breaks first when people try running cross-environment agent workflows in practice.
Project: https://hybro.ai
Docs: https://docs.hybro.ai

value: Show HN: Running local OpenClaw together with remote agents in an open network

author: kevinlu


value: stanleykm

value: Something I’ve been hacking around with for the past couple weekends. Registration and posts and listings are signed by eth private key. Market commerce is via ethereum smart contract. Agents can sell capacity to do work, or buy capacity from some other agent to do work. Arbitration is done via a bot that evaluates work divered vs requirements.<p>Anyway happy to take any feedback. Don’t drive my aws bill up too high :)

value: Show HN: Bugparty.org an Ethereum-based forum and marketplace for agents

author: stanleykm


value: codepawl

value: Show HN: Hypedar – what's trending in AI that nobody has built yet

author: codepawl


value: windyVector

value:
Hi HN! I am a 19 year old dev from Australia. Over here, lots of people leave their unwanted items on the sidewalk, but there’s usually nothing wrong with them.
While saving up to travel, I built an app that made it really easy to list them (and stuff I had lying around my house) online. Using it meant I didn’t need a second job which was nice.
A dev recently reached out to me asking if I could turn the valuation feature into an mcp so I decided to spin it off into its own product.
A cool use case we’re playing around with is connecting it to open claw and arbitraging facebook marketplace, I plan on making it even easier to spin up in the coming days :)
Check out the demo and let me know your thoughts/feedback!
also if you wanted to see the original app check it out! https://sails.live

value: Show HN: Facebook marketplace arbitrage tool

author: windyVector


value: Show HN: WinForge A daily OS connects your annual goals to what you do today


value: Show HN: AgentMarket – Where AI agents pay other agents for tasks they can't do


value: Show HN: Detect API changes automatically using real traffic


value:
Hi HN!
quick backstory: Did ML Infra at Linkedin. Side-quested and led content at a YCW20. Ignored that part of my life and started a business to build an enterprise fact verification system for agents. Wasn't a hair-on-fire problem space.
And now here we are.
Wanted to share https://usesnippet.app with you guys.
Snippet is an AI-native talent management agency for content creators. We handle brand discovery, outreach, deal negotiation, pricing intelligence, and contract auditing on autopilot.
Vision is to give mid-tier creators (and the brands working with them) as good a representation as the Mr. Beasts of the world. Long way there and in this industry everything is a people problem, not a software problem. Software is a great mean for our margins though.

value: Show HN: I Built an AI-Native Talent Management Agency


value: mjhcodes

value:
I’ve been buying and operating small online businesses (mostly SaaS and niche sites) for the last couple of years.
Whenever it came time to sell a project doing a few hundred to a few thousand a month in profit, I ran into the same gap: brokers won’t touch businesses this small, and listing on public marketplaces is incredibly time-consuming and unpredictable. There just wasn't a good broker that existed for this end of the market.
Recently, I decided to start filling that gap myself. I handle the entire sale process for sellers, and because I’ve built relationships with buyers and platforms, I can sell the business and take a commission that is less than what a marketplace would have charged anyway, and provide a completely hands-off experience - sellers never deal with listings or negotiations.
On the flip side, I’m also growing my small network of buyers who are actively looking for simple, profitable online businesses in this range with room to grow.
It's still early days, but it’s been interesting seeing how common this problem is. I'd love for anyone who is thinking about selling a side project or looking to acquire one to get in touch.

value: Show HN: Becoming a broker for small online businesses

author: mjhcodes


value: laszlokorte

value:
The latest 3Blue1Brown video [1] about the M. C. Escher print gallery effect inspired me to re-implement the effect as WebGL fragment shader on my own.
[1]: https://www.youtube.com/watch?v=ldxFjLJ3rVY

value: Show HN: M. C. Escher spiral in WebGL inspired by 3Blue1Brown

author: laszlokorte


value: muizzlateef

value: Show HN: Agent Actions A framework for buildingmulti-step Agentic workflows

author: muizzlateef


value: Show HN: Anti-pedigree scout program to find overlooked AI startups


value: recvonline

value: Show HN: Bramble – AI coaching for hard conversations, decisions, and thinking

author: recvonline


value: liorcodev

value: Show HN: tRPC Docs Generator v0.8.0 – Improved UI

author: liorcodev


value:
I had one question: when do birds show up at my bird feeder?
Setup: Raspberry Pi Zero 2W + USB webcam + Supabase (free tier) + 93 lines of Python that captures a 1280x720 frame every 60 seconds with retry logic for the Pi's flaky WiFi.
Analysis: Ran 1,500 images through Qwen 2.5 VL 7B via OpenRouter API. 996 tokens per image. Total cost: $0.37.
Results:
- 433 birds detected across 3 days (23.7% of frames)
- Peak hour: 3 PM (86 birds), not dawn like I expected
- Afternoon (12-5 PM) accounts for 70% of all activity
- Day 3 had 6x more birds than Day 1 — Bird NPS of 100, they told the flock
- Biggest frame: 5 sparrows simultaneously
- Species mix: house sparrows, house finches, pigeons, one possible hawk
Hardware BOM: $80.23. Running for a year would cost ~$27 in API.
Page has the interactive dashboard, real captured images, and links to the code.

value: Show HN: Using RasPi and Qwen 2.5 VL to find out when birds visit my balcony


value:
Hey everyone, I run a video editing agency for real estate agents (but I’m not a video editor). So I hired video editors to edit the videos for me which works pretty good. However I struggled with the delays in getting edits done, people taking days off and overall workload getting too large.
So I’ve spent the last two months building Alys - Alys is an agentic video editor: There’s no timeline, you literally just chat to make edits to the videos. ChatGPT for video editing basically.
My honest reflection on the tool at this point:
The good:
- Good output quality is possible, but it takes the right prompts. It feels a bit like Claude code when it first came out, there’s some signs of brilliance, but it’s very rarely in one shot. To back this up, I recently sold a $1k video package based on a video made by Alys.
- The animated overlays work great - In my limited editing work, I’ve always struggled with creating text that looks good and meets the ‘vibe’ of the video. Alys can create animations and text reveals from specific descriptions which look better than any templates I’ve used in other editing software
- It saves time - I just added ‘templates’ which basically means at the end of an editing/prompting session when I am happy with the result, I can save this as a template. Then the next time I want to make a similar video, it can use this video result as inspiration.
The bad:
- Alys still requires some thought from the user to create good videos (prompting matters). Coming back to the early Claude Code/Cursor days - the prompt you give Alys is important. It’s easy to forget now that Claude Code can one-shot complex features, but 12 months ago you’d have to write an elaborate prompt and then iterate 5-6 times to get code that complied. The same is true with Alys - she can create good videos, but just requires good prompting
- Speed: maybe I’m just impatient, but waiting 2 mins for an edit feels too long for me. There’s a real trade off between speed and quality of results which I’m still trying to balance. Claude Code can work for 10 mins on a problem and I don’t mind as it will often be 95% of the way there after the first iteration. Alys needs to get as good.
The future:
- I believe the real unlock is to give Aly’s video engine more options for creativity, and truly expand to allow her to have all the features available in a modern video editor.
- As well as improving the examples and prompting she receives to truly let show her what video editing looks like across difference styles.
Anyway I’d love for some feedback and for you to try it out. I have a free plan with sensible limits (sadly video rendering on GPU’s is expensive, so there is a paid option).
Thanks!

value: Show HN: Alys – Chat GPT for video editing


value: jannniii

value: Thought to try if I could chain multiple apfel calls to make the Apple LLM be more useful, enabling use of natural language to run many zsh commands or combinations of commands.

value: Show HN: Chained apples, or apfels, for more logic

author: jannniii


value: hallomarbin

value: Show HN: devmenu - Browse, search and run categorized shell commands from a TUI

author: hallomarbin


value: fberg

value: For an in-depth introduction, go straight to the article at https://makrell.dev/odds-and-ends/makrell-design-article.htm...

value: Show HN: Makrell, one family for code, data, markup

author: fberg


value: Snawoot

value: Show HN: Weakmap – weak map for Go without use of finalizers

author: Snawoot


value: huanyux

value: Show HN: Harness CLI – Open-source agent loop for long-running app development

author: huanyux


value: lackoftactics

value:
Netflix compresses 4K to 15 Mbps. A Blu-ray remux is 60 Mbps.
Dark scenes, fast motion, grain.
That's where you see it.
I wanted my family to have Blu-ray quality with a streaming UX.
They open Overseerr on their phone, request a movie, and it shows
up in Infuse on Apple TV. Subtitles in three languages, hardware
transcoding for mobile, full remux on the big screen. They have
no idea what's behind it.
What's behind it: Sonarr, Radarr, Prowlarr find and grab content.
qBittorrent downloads through a WireGuard tunnel. Bazarr pulls
subtitles. Jellyfin serves it all. Everything self-heals — endpoint
health checks, autoheal restarts, dependency ordering so nothing
starts in a broken state.
The security model is the part I obsessed over:
- qBittorrent shares Gluetun's network namespace at the kernel level.
  No firewall rule to misconfigure — if the VPN drops, there's no
  network path.
- Traefik binds to a Tailscale IP only. Zero ports face the internet.
- Three isolated Docker networks separate ingress, internal, and
  P2P traffic.
Two Compose stacks, one .env file, MIT licensed.
https://github.com/Lackoftactics/uncompressed

value: Show HN: Uncompressed – Self-hosted Netflix alternative at 60 Mbps instead of 15

author: lackoftactics


value: Was curious how a personality test would look for developers. So created this using FastAPI, HTMX, and AlpineJS.

value: Show HN: Dev Personality Test

title: Show HN: Dev Personality Test


value: dlvktrsh

value:
Built this while applying to various jobs.
I was using Claude to generate different resume variants for roles (Flutter, WordPress, fullstack, Python backend, agentic AI/RAG). It worked pretty well, but I kept hitting limits — both in control and credits. I also wanted something more consistent when tailoring resumes for specific job posts.
So I built this.
Key points:
* Multiple variants from one base
* Client-side PDF rendering (PDFKit in browser, no server)
* Local-first PWA, works offline
* JSON import/export
* FOSS (open to PRs for templates/features)
Live demo: https://resume.journy.live
Repo: https://github.com/qmanas/resume-builder-react
Workflow:
Import: use any chat-based AI with your resume + the prompt in the app to generate a JSON version, then import it.
Create variant: load master → make changes → “Save Preset” → name it (e.g. flutter)
Update variant: load variant → edit → “Save Preset” → confirm overwrite
No login, no data leaves your browser.
Curious what people think about the idea and execution.

value: Show HN: Local-first resume generator with in-browser PDF rendering

author: dlvktrsh


value: SwellJoe

value: Show HN: Nelson, a Ralph-like loop for finding vulnerabilities

author: SwellJoe


value: jamesweb

value: Show HN: SwarmFeed – An X-like social platform built for AI agents

author: jamesweb


value: hgarud

value:
Wandb CLI and MCP is atrocious to use with agents for full autonomous research loops.
They are slow, clunky, and result in context rot.
So I built a CLI tool and a Python SDK to make it easy to connect your Wandb projects and runs to your agent (clawed or otherwise).
The cli tool works by allowing you to import your wandb projects and structures your runs in a way that makes it easy for agents to get a sense of the solution space of your research project.
When projects are imported, only the configs and metrics are analyzed to index and store your runs. When an agent samples from this index, only the most high performing experiments are returned which reduces context rot. You can also change the behavior of the index and your agent to trade-off exploration with exploitation.
Open sourcing the cli along with the python sdk to make it easy to use it with any agent.
Would love feedback and critique from the community!
Github: https://github.com/mylucaai/cadenza
Docs: https://myluca.ai/docs
Pypi: https://pypi.org/project/cadenza-cli

value: Show HN: Cadenza – Connect Wandb logs to agents easily for autonomous research

author: hgarud