value: jcfontecha

value:
I built slate as a personal tool to centralize my strategy, research, scripting, thumbnails and shots in one place. Started showing it to other youtubers and that made me wonder if more people could have the same problem as me.
Here's a quick walkthrough: https://youtu.be/7Ml5dVcFFds
I've been doing Youtube videos since I was a teenager. There's so many work before even recording: researching what's working in your niche, finding outliers worth studying, obsessing over titles and thumbnails that will earn you the click, writing scripts that actually hold viewers attention and somehow keeping your B-roll from turning into a mess.
Big channels hire teams for this. Solo creators struggle juggling dozens of tabs, google docs and notion templates.
I'd love to hear for feedback.

value: Show HN: Slate – agentic pre-production studio for solo Youtubers

author: jcfontecha


value: Show HN: A near-zero-dependency Java UI toolkit for admin panels and AI flows


value: vaibhavgeek

value: Show HN: NPM Package that fills forms via voice using Gemini Live API

author: vaibhavgeek


value: mixfox

value: Show HN: SnapMog: An Omoggle Alternative without going live

author: mixfox


value: emarboeuf

value:
Ten years as a CTO. Owned Engineering, security, compliance at very different stages.
Your non-technical friend built something in Lovable last weekend. It works. They want to charge for it. They don't know their API keys are in the client bundle, their database is public, and they have zero error monitoring.
howbadis.it: they paste the URL, get a score. A few stack questions cover what the URL scan can't see.
What checks should I add?

value: Show HN: Howbadis.it – Paste your vibe-coded app, see what'll break

author: emarboeuf


value: To iteratively improve RAG performance, current evaluation solutions still take lots of manually work or lots of coding. And it requires close collaboration between AI engineers and domain experts (who may not know how to code).<p>So I built this playground to show a smoothier workflow that enables continuously improvement of RAG, it can 1) run RAGs and get evaluation results quickly 2) generate insight both tech & non-tech can understand 3) provide an UI for domain experts to review and update flagged entries easier.

value: Show HN: I built a playground of interative A/B testing for RAG


value: nburr

value: Show HN: Key Exchange Utility for Key Analysis

author: nburr


value: glenntws

value: Show HN: Stagewise – Agentic IDE for Your Z.ai/DeepSeek/Moonshot Subscription

author: glenntws


value: teezay

value: Show HN: Oc-go-cc, an Open-source proxy that lets Claude Code use OSS models

author: teezay


value: guyfischman

value: Show HN: IEEE-754-Conformant FP64 on Metal (Apple Silicon)

author: guyfischman


value: yuriaguernsey

value: Show HN: Inkwell a writer-first newsletter platform,$0 for unlimited subscribers

author: yuriaguernsey


value: gNucleusAI

value: Show HN: Open Source FreeCAD dataset for CAD generation tasks

author: gNucleusAI


value:
The web version of the emulator: https://pixel-clover.github.io/ocelot/
Project repo og GitHub: https://github.com/pixel-clover/ocelot

value: Show HN: Ocelot – A Game Boy and Game Boy Color Emulator in Haskell


value: chrija

value: How AI-pilled are you?

value: Show HN: AI Fluency Diagnostic

author: chrija

story_text: How AI-pilled are you?

title: Show HN: AI Fluency Diagnostic


value: niknat

value: Slide the tiles to unscramble the daily emoji.<p>Built with a React frontend and Firebase backend.

value: Show HN: Slidemoji – A Daily Puzzle Game

author: niknat


value: adsharma

value:
Previously I called pgembed, pglite for native code here: <https://news.ycombinator.com/item?id=47726489>.
However that's not true. pglite runs as a single process inside the browser leveraging postgres single user mode.
pgembed gives you the illusion of being an embedded database, but really its running a managed multi-process postgres behind the scenes.
vpg is trying to mimic what pglite does. It's mostly written in C with the top level glue code written in vlang and exposed via python using a custom bindgen implementation.

value: Show HN: Vpg – Pglite for Native Code

author: adsharma

title: Show HN: Vpg – Pglite for Native Code


value: rashidae

value:
Built this while syncing my own blog from Notion. Good alternative to paid options like Super.so.
Supports incremental sync, all Notion block types including equations and synced blocks, image download + WebP conversion, and adapters for Markdown, MDX, and JSON.
Works with Next.js, Astro, SvelteKit, and anything that reads files.

value: Show HN: Notion-to-site – sync any Notion database to local Markdown/MDX/JSON

author: rashidae


value: nezaj

value:
Hey HN! We made GETadb.com, so it's easier to get agents to build you full stack apps. You don't need to give them any credentials. Just by loading a GET request, they get access to a database, a sync engine, and abstractions for auth, presence, and streams.
To see what the agent sees, you can load https://getadb.com/new
There's two fun things about how it's implemented:
1. If you curl the home page, it the agent content rather than human content. We do this by detecting the 'Sec-Fetch-Mode' header. It's not perfect, but gets the job done for Claude Code et al.
2. For an agent to spin up an app, they make _two_ fethes. (1) getadb.com/guide tells them to generate a uuid, and fetch (2) getadb.com/provision/<uuid>. We did this, because just about half of the popular web-based app builders cache URLs globally, even if you return no-store headers. To get around this we just instruct the agent to generate unique URLs
You may wonder: Why GET requests, rather than POST requests? It's because then you can build in surprising places. For example, we get meta.ai to build an app inside the artifact preview: https://artifacts.meta.ai/share/a/b80c7412-c3af-4088-b430-78efdfe8ea2d
Under the hood, this is possible because the whole infra is mult-tenant from ground up. We already announced how that works on HN, but if you're curious here's the essay for it: https://www.instantdb.com/essays/architecture

value: Show HN: GETadb.com – every GET request creates a DB

author: nezaj


value: acolytic

value:
Hi HN! I'm Alex. I've been building rubberduck, a software design tool, for the last few months.
Here's a 2.5 min demo if you want to skip ahead: https://www.youtube.com/watch?v=g_E6yhpN-zU
I've been using coding agents for a few years and have been frustrated by how quickly they jump to solutions. Even with plan mode and ask-user-question features, it's still a review dynamic. You describe a problem, they hand you a complete solution, you react. The solution looks plausible but may hide bugs or design flaws you can't catch, because you didn't think through the design yourself. Over time, your intuition for your own software degrades because you've stopped making meaningful decisions.
rubberduck flips this. Each session has three phases: design, implementation plan, and execution.
In the design phase, you describe what you want to build and rubberduck chats with you about how to solve it. I was trying to mimic the design conversations I used to have with colleagues at Microsoft and Stripe: sitting down, talking through options, poking holes in them, weighing trade-offs. rubberduck explores the design with you and investigates the codebase on your behalf, but you make every relevant decision. The output is a design document.
Once you're happy with that, the implementation plan phase takes over. The agent does a deep dive into the codebase to figure out how the design maps to actual code. This is similar to plan mode in Claude Code. It's mostly autonomous, since the meaningful decisions are already made.
Finally, execution. The agent runs in an isolated container using a dev environment image you provide. Each task is validated against your quality gates (tests, linting, formatting) before being committed. The output is a PR.
Pricing is $24/month with $5 of included credits (roughly one session, depending on complexity). Credits cover tokens (no markup) and execution compute (you specify the vCPUs/memory you need).
I've been bootstrapping for a few months and it's been fun to build. Would love for you to try it. Feedback very welcome.

value: Show HN: Rubberduck – Software design agent where you make the decisions

author: acolytic


value: leonagano

value: Show HN: Rejected by YC

author: leonagano

title: Show HN: Rejected by YC


value: mounnar

value: Show HN: UltraCompress – first mathematically lossless 5-bit LLM compression

author: mounnar


value: vegancap

value: Show HN: PDF 2 Context – Convert PDF text to JSONL files

author: vegancap


value:
Hello everyone, I have been working on this for a year and it is such a difficult problem. mobile-ink is an open-source mobile infinite drawing canvas. There is not a strong open-source drawing engine beyond toy demos. Thus, mobile-ink aims to solve this problem and provide a state-of-the-art mobile note-taking canvas package.
mobile-ink uses native Skia/Metal to address issues with native rendering, pencil latency, eraser behavior, page virtualization, preview caching, memory stability, page interactivity, etc. It has many advanced features such as shape-snapping, primitives to integrate figures, custom backgrounds, pdf import, stroke selection, smooth zoom/scroll, and more.
The package is iOS + React Native as of now.

value: Show HN: Mobile-ink, an open-source mobile infinite drawing canvas


value: gardnr

value:
You need to keep them fast and reliable or your team will hate you. Shared git hooks can be a double-edged sword. They can also prevent your agents from producing abject trash. Use `pre-commit` or `husky` and enable max-lines-per-file @ 600 lines and McCabe-style complexity at 10. You can ask your agents to use `rope` or `ts-morph` where it fits to refactor and meet the new requirements.
Add a note to our AGENTS.md/CLAUDE.md: "Make descriptive commits at reasonable intervals. Ensure the git hooks are installed. NEVER use `--no-verify` unless the user confirms first."
While you are in there add this magic too: `Use TDD "Red, green, refactor." where possible.`

value: Show HN: Keep coding agents on track with shared Git hooks

author: gardnr


value: baigy

value: Show HN: We built a tool that generates 3D objects with editable, separate parts

author: baigy


value: okchildhood

value: Show HN: PostDew – LinkedIn posts that don't sound like AI

author: okchildhood


value: AnujKapasia

value:
we've added onboarding that lets our users build custom AI for their website ready to deploy under 60s total.
the platform consists end to end AI engineering, prompts, version control, evaluations, test cases, logs, AI Actions (custom tools as cloud functions), RAG etc etc
everything you need in a sophisticated infrastucture and super easy to use platform.
build and iterate AI is at speed of thought.
More power and control over AI to entrepreneur and product managers

value: Show HN: Build a custom AI in under 60 seconds (demo video)

author: AnujKapasia


value: lone-cloud

value:
As a de-Googled Android user, I wanted a way to privately receive push notifications from the apps and services I use. I already use several UnifiedPush apps, but I needed something for apps and self-hosted services that do not support it natively.
So I built Prism and am officially joining a distinguished club of similarly named projects: the NSA's mass surveillance program, OpenAI's editor and two recent YC startups.
What is it?
Prism is a self-hosted notification gateway written in Go, with an optional Android companion app. It accepts webhook notifications through an ntfy-compatible API and routes them to Signal, Telegram or WebPush. The Android app is a UnifiedPush distributor. It pairs with the server through encrypted WebPush subscriptions and delivers messages via Mozilla's autopush service by default.
Prism also has a custom Proton Mail integration: notifications include quick reply actions, and messages are automatically dismissed when read on another device.
How I use Prism:
- notifications from my self-hosted Beszel instance
- rich notifications from Home Assistant, my home automation system; for example, leak sensor alerts and camera security alerts where HA captures a snapshot and sends it through Prism
- Proton Mail notifications
All source is FOSS under AGPL v3.
Prism service: https://github.com/lone-cloud/prism
Prism Android: https://github.com/lone-cloud/prism-android

value: Show HN: Prism – Self-hosted notification gateway (Signal, Telegram, WebPush)

author: lone-cloud


value: quinnosha

value: Show HN: Agent-isolated remote envs with full Docker Compose support

author: quinnosha


value: Show HN: A lie detector game that reads your pulse through your phone camera


value: skramzy

value: Show HN: Openloom – Turn Loom links into transcripts and frames an LLM can watch

author: skramzy


value: heyvig

value:
Hi HN! My name is Vignesh, a founding engineer at Root Access. I am an ex-Texas Instruments applications engineer who was sick of using coding tools that sucked at interacting and working with hardware.
I joined Root Access with other hardware engineers to develop Seb, a hardware aware coding agent capable of generating precise code. Instead of relying on just LLM calls, Seb uses our deterministic algorithms. It is capable of understanding the entire system by reading schematics, datasheets, BOMs, etc. We also have it ready to generate code that is compliant to various regulated industries such as medical, automotive, and defense. It can connect with debuggers, read logs, and fix bugs.
Make an account to try Seb at https://hideout.rootaccess.ai/login
We just launched this week, and I'd love to hear what you think of Seb. I am happy to discuss anything, what it is good at (and bad at), and what we think it can do a year from now.
Best,
Vignesh K.
https://www.rootaccess.ai/

value: Show HN: Seb – Coding agent that teams trust to develop mission-critical systems

author: heyvig


value: amaldavid

value:
I was having way too much free time even when i was working on 6-7 different projects at the same time with claude code and codex. Staring at the terminal when agents are cooking code for you was just too boring in the last 6-7 months so had to look for fun little side quests and ended up building a terminal arcade, it is still in its infancy and more of a personal hobby project. Out of all things, i ended up liking the bookshelf a lot when I built the post tool hook where i get a quote from a book for every 5th tool call, learning about new books became my daily habit now.
It is open source: https://github.com/Amal-David/terminal-arcade
Feel free to share any suggestions or add any new games or just have fun playing any games!

value: Show HN: Terminal Arcade – Side quests when agents are cooking

author: amaldavid


value: tinyopsstudio

value: Show HN: Automation ROI calculator for repetitive admin workflows

author: tinyopsstudio


value: pgadhiya

value:
resume.io locks PDF export behind a subscription. This tool uses Playwright to load your resume editor in a headless browser, captures each canvas page as a screenshot, and assembles it into a PDF.
https://github.com/Preet-Gadhiya/resume2io-download
Runs in Docker, takes about 30 seconds per resume.

value: Show HN: Download your resume.io resume as PDF without paying

author: pgadhiya


value: tltv

value:
I spent six years trying to build a tv channel server. rewrote it eight times. flask, fastapi, ffmpeg, gstreamer, named pipes. every version got more complicated and none of them worked right.
turns out I was building the wrong thing. the thing I actually wanted was a protocol.
so tltv is that. a channel is an ed25519 key pair. you sign your metadata with it. you serve hls video from wherever you want. your public key becomes a tltv:// address that anyone can tune into.
relay nodes can re-serve your stream but they can't modify it. they verify signatures on everything. you can move servers and keep your channel because the key is the identity, not the hostname. nodes find each other through peer exchange. no central registry.
the cli is probably the fastest way to see what I mean:

  curl -fsSL timelooptv.org/install | sh

  tltv keygen

  tltv server test --name "my channel" -k TV*.key

that's a fully compliant origin server. pure go, generates smpte bars with audio, no ffmpeg. one binary, ~20mb of ram.
there's also a full gstreamer-based server (cathode), a web viewer (phosphor), and bridge/relay servers in the cli. everything mit licensed.
live demo at https://demo.timelooptv.org
https://github.com/tltv-org

value: Show HN: tltv – Federation protocol for 24/7 TV channels

author: tltv


value: freakynit

value:
https://github.com/freakynit/chat-with-ufo-files
Contains sqlite database with all files pre-loaded along with embeddings. Has good looking UI you can directly chat with.
Demo(for just next 15 minutes or I run out of 5$ credits). Also, concurrency is limited by openrouter to just 10... so, some requests might fail:
https://open-proxy.space
^ Im running this on my machine begind cloudflare proxy.. and this is the domain I generally use for all dev purposes..

value: Show HN: Chat with UFO Files

author: freakynit

title: Show HN: Chat with UFO Files


value: mickuehl

value: Show HN: Agent-fox – write a spec, run agent-fox, and go do something else

author: mickuehl


value: expeler

value: Show HN: decentralized-message-queue

author: expeler

title: Show HN: decentralized-message-queue


value: physix

value:
This started out as an experiment. Reading Simon Willison's blog on where StrongDM was going with dark factories and Digital Twin Universes
https://simonw.substack.com/p/how-strongdms-ai-team-build-se...
I got thinking that, hey, what if we built a digital twin of our enterprise application platform Cyoda? With an in-memory local Cyoda service, it would make it much easier for people to get started building Cyoda apps, and rapidly speed up development.
I also wanted to see how far one can go using agentic engineering to build that out, thinking it's a good use-case since the tool wasn't (originally) destined for production.
I'm a Java/Kotlin/Spring/Cassandra person, so I decided to write it in Go, because I've never written a line of Go. This would ensure that I stay hands off from the code and see this from the perspective of an architect and project manager.
But after the in-memory storage engine was built, I quickly realized that it would be straightforward to implement a postgres plugin. Then I remembered sqlite. This looked so cool, that I decided over Easter to tackle Cassandra.
And out came cyoda-go.
We're still working intensively on fleshing it out, but the vision is to provide an open source EDBMS (Entity Database Managment System) that has production quality and can cover a very wide variety of use cases.
The design is based on our work of the last ten years on Cyoda.
So what's an EDBMS? ...you are probably asking.
Under the hood, it's a combination of a JSON/document database, a workflow engine, messaging/queuing middleware, and a CDC audit. Data are entity state machines persisted append-only. Transitions can launch externalized processors over gRPC that do business logic. All mutations are bi-temporal and the consistency model is snapshot isolation with first-committer-wins on entity-level conflicts. An engine automates workflow traversal, so that a single trigger cascades across entities inside the same transactional boundary.
The core assembly is a single Go binary. Once you've understood the design, it's really easy to write event-based applications with transactional rigour and a bi-temporal view on the data at no performance cost, and built-in auditability and data lineage.
Repo: https://github.com/Cyoda-platform/cyoda-go
Docs: https://docs.cyoda.net
I would be very interested to know what the community thinks. Is this kind of architecture, that consolidates several key frameworks into a unified platform, effective in accelerating the building of complex enterprise systems?

value: Show HN: Cyoda-go – application platform in Go without the Temporal/Kafka glue

author: physix


value: Show HN: I built a translator for SPANGLISH and mixed-language text


value: whereismyreleas

value: Hello! I always struggled to find good tools for tuning a bow, and the existing ones are generally not very user friendly. So I started building my own: A paper tuning tool, an arrow laboratory (spine, FOC etc.) and a sight tape generator. I then expanded this so users can use a configurator to build their loadouts and share them with the community. The goal is eventually to filter builds to find archers with similar profiles and get inspiration from what components they are using (sight, release, stabilizer, cables, vanes, nock...).

value: Show HN: Bowbuilds, a configurator and tuning toolkit for compound archers

author: whereismyreleas


value:
Hi HN, I built this for myself because I wanted my coding agent (Claude Code) to actually be able to use my Obsidian vault as a knowledge base, not just grep it.
The use I get the most mileage from is asking the agent to find notes that should be cross-linked, which surfaces forgotten connections and turns the vault into more of a wiki over time.
It is similar to what the Smart Connections Obsidian plugin does, but I wanted a CLI-first tool, and more control over the models. Currently it supports local embedding models via Ollama and LMStudio, plus Gemini API for cloud.

value: Show HN: Obsidian-Semantic, a CLI that lets agents search your vault by meaning


value: manume

value:
Hey HN!
I built AgentMGMT.dev today to keep track of all those agent orchestration tools that keep popping up. I've tried a few and landed on Superset, which I'm extremely happy (and productive!) with - but I think this category of tools will be extremely important and interesting in the next couple years, so it's worth keeping an eye on all available tools and how they evolve.
I will keep the site up-to-date, please help me by submitting new tools that are not yet in the list, or add any details that might help folks who are out shopping for their first/next agent orchestrator!

value: Show HN: The independent guide to agent orchestrators

author: manume


value: jeffreyip

value: Show HN: Vibe code your agents without vibe coding your agent

author: jeffreyip


value: mikenikles

value: Show HN: Tuxedo – A fast, keyboard-driven terminal UI for todo.txt

author: mikenikles


value: DiligentPeasant

value: Show HN: Signegy - free in-browser PDF toolkit, no signup

author: DiligentPeasant


value: samagragune

value: Show HN: Contral – the agent which will teach you while you build with AI

author: samagragune


value: Serenacula

value:
Heya!
So this is a project I've been working on for a fair while, and with this version it's pretty much feature complete.
For a bit more info, this is intended as a tool for manipulating strings in the terminal. Basically a more powerful and intuitive version of the cut tool.
I didn't get much traction last time I posted this, but I'd love to receive some feedback! :)

value: Show HN: Splitby v2.0.0 – a modern alternative to cut

author: Serenacula


value: Show HN: Sigment framework beating Vanilla JavaScript in row selection


value: mckabue

value: Show HN: Blober.io – The Only App That Connects to GoPro Cloud

author: mckabue


value: Show HN: I mirrored war.gov's UAP archive in pure Rail with verifiable bytes


value: simonesilve

value: Show HN: Run and debug ThingWorx services locally with TypeScript

author: simonesilve


value: ttouch

value: Show HN: CADara – I made an open-source in-browser CAD

author: ttouch


value: everlier

value: Show HN: [Video] Tribute to LLM releases in April 2026

author: everlier


value: tbmo

value: Show HN: MOG Simulator, Emergent galaxies via ensemble of grids [video]

author: tbmo


value:
Hi HN!
We built openround.ai - an assessment platform to hire AI native engineers. On OpenRound, engineers build a project or solve a problem using AI. This replaces a usual coding round/take home assessment.
I believe coding assessments measure who is good at passing interviews, not who is actually a good engineer.
We want to flip that by showing how engineers actually work on a real problem.
2 interesting things we solve -
1. Designing assessments and environments that are not one shotted by AI.
2. Differentiating bw a software engineer who uses AI well and a pure vibecoder.
Would love for you folks to try it and hear any feedback that you have.
Also here to answer any questions about problems, evaluations, market insights, etc.

value: Show HN: AI-native tech assessments (end of LeetCode)


value: edonnie

value:
I launched Lakyus on February 27. It allows you to launch and run companies on autopilot.
The platform handles both creation and ongoing operation by wiring together Stripe, Netlify, Postmark, and the Meta Marketing APIs. It has its own inbox to handle email marketing, can send you updates, can manage products and push them to Stripe, provisions your own DB, and more.
The goal is to move past chatbots and toward autonomous business infrastructure, allowing people to spin up dozens of micro-businesses.
I am interested in feedback and would be glad to answer questions.

value: Show HN: Launch and Run Companies on Autopilot

author: edonnie


value: Sardhendu

value: Show HN: Nexa-gauge – Cache/cost-aware graph-based eval for LLM and RAG

author: Sardhendu


value: Show HN: KillClawd – a sarcastic AI desktop crab by local Ollama


value: theMackabu

value:
Hey HN! I have been working on Ant for a while now, would love to share around now.
What is Ant? It's my JavaScript runtime, built from scratch over many hours of work. Much effort has gone into keeping the binary size small, around 9MB at the moment (6.5 MB with -Os). On my M4 Pro, the hono coldstart bench (examples/npm/hono/bench-coldstart.js) lands around 5ms, about 2.4x faster than bun, and 5.8x faster than node.
To keep things small, the engine ("Ant Silver") is hand-written, not a wrapper around V8/JSC/SpiderMonkey. The JIT is still a work in progress but it uses a fork of MIR as the backend.
Ant currently targets the WinterTC Minimum Common API, while also passing 100% the javascript-zoo compat-table tests, and is sitting around 64% on test262.
Why did I build Ant? Well, I wanted a runtime small enough to ship with CLI's and small Docker containers without having to drag along 50 to 100mb of just runtime. Ant in its current state is performant enough in some cases to compete with v8, but mostly in specific shapes.
Background on how it got here: https://themackabu.dev/blog/ant-part-two
Online demo shell/container: https://ant.ax
If anyone has questions about Ant, such as the engine, im happy to answer any of them! Feedback is also appreciated, if you run your own code and hit some edge case.

value: Show HN: Ant – A from-scratch JavaScript runtime in 9 MB

author: theMackabu


value: oxchairman

value: Show HN: TigerJSON – Native macOS JSON viewer with jq filter engine ($9.99)

author: oxchairman


value: Shrpp

value: Show HN: Ovlt – Lightweight Auth Server That Runs in ~20MB RAM

author: Shrpp


value: Show HN: CopyProps – A Figma plugin that copies element properties as text


value: So much content. Great UI (imo, compared to what gov released today). I'm thinking the site is defunct now but it's been archived plenty. I must have first came across this website in the late 00's.

value: Show HN: Best Old School UFO Website

title: Show HN: Best Old School UFO Website


value: modinfo

value: Show HN: Nanorust – Minimal server-driven UI in Rust

author: modinfo


value: surrTurr

value:
Hi HN!
I decided to create a little projects page to showcase the apps I built - WDYT?
PS: Click on the stickman to see something cool!

value: Show HN: My New Projects Website

author: surrTurr

title: Show HN: My New Projects Website


value: gorgonian

value: I love HN, but I also love dark mode. I wanted dark mode HN on my iPhone without any extension/third party app/proxy fuss, so I made this bookmarklet. One tap on news.ycombinator.com and dark mode sticks across page navigations. I'm sure this has been done before, but I couldn't find a solution that satisfied me. Thought I'd share in case anyone is in the same boat.<p>How it works: bookmarklets normally die on the first navigation. This one replaces the page with a same-origin iframe pointing at HN, then re-injects CSS on every iframe load. Since the iframe is same-origin, everything (cookies etc) should work normally. I've tested this in Chromium/Linux and Safari/iOS.

value: Show HN: Hacker News Dark Mode Bookmarklet

author: gorgonian


value: dobodob

value: I created a new joke site for "6 second jokes" and other jokes. If you know a good one, you can submit. Or get a daily joke to tell others each day by signing up for the mailing list. Enjoy!

value: Show HN: Know Any Good Jokes?

author: dobodob

title: Show HN: Know Any Good Jokes?


value:
Since everyone always complains about IPv6-only servers not being able to reach GitHub, I fixed that.
You can use this simple service I made to access GitHub through IPv6, and you don't need to have IPv4 on every server or set up your own proxy server.
You have the choice of using the proxy explicitly by its own address, or adding it to your hosts file to connect transparently through it. Since you're connecting to the real GitHub by a different address, there are no certificate errors.

value: Show HN: I made an IPv6 proxy for GitHub


value: justinlindh

value: Show HN: Digits – Encrypted calls from gutted vintage desk phones

author: justinlindh


value: jasonkester

value:
I'm working on the Survival Crafting RPG that you would have played on your Apple II back in the '80s. You can think of it as Valheim's gameplay crammed into the tile-based UI of the old Ultima games.
It has a procedurally-generated open world with towns and NPCs to talk to, all the resource gathering, mining, crafting stuff you'd expect in a modern survival game, and some good old fashioned dungeon crawling to boot.
I've been working on it off and on for the last several months. It's complete up through the Bronze Age (in Valheim terms). Let me know what you think!
https://stravaeger.com/

value: Show HN: I Built a Retro Survival RPG in Vanilla JavaScript

author: jasonkester


value:
Built hum, a minimal terminal music player focused on fast keyboard flow and low overhead.
> ad-free playback (raw stream URLs via yt-dlp + mpv)
> keyboard-first, low-overhead terminal UX
> no API keys / accounts / subscriptions
> supports song search, direct YouTube links, playlists, and radio mode
> one-command install for Linux/macOS or run source code for windows
Install: "curl -fsSL https://raw.githubusercontent.com/Devendra116/hum/main/insta... | sh"
Repo: https://github.com/Devendra116/hum
Would love feedback

value: Show HN: Hum – ad-free terminal music player (Rust, no API keys)


value:
Dikaletus is a TUI tool to record, transcribe, and generate structured meeting notes using FFmpeg, PulseAudio and the Mistral AI API.
The meeting agent automates the process of capturing, transcribing, and generating structured meeting notes. It records audio from both microphone and speaker outputs, transcribes the audio using Mistral's speech-to-text API, and generates structured meeting notes in Markdown format.
Years ago I used to write a lot of R code for data analysis. Then life changed and I wasn't doing that anymore. However, I still had small product ideas that required coding, but no time to do it. Dikaletus is my first vibe coded app, scratching one of those itches (I'm terrible at taking meeting notes in general).
Written in R, because that's what I know. Tried to follow good practices with linting and testing.

value: Show HN: Dikaletus – meeting recording and transcription using Mistral AI


value: Show HN: I Build a SaaS Loading Time Anxiety and Cost Calculator


value: pakenrol

value: Show HN: Cheapshot – GPS-based mobile game

author: pakenrol


value: rmst

value: Show HN: Transformer Math Explorer

author: rmst

title: Show HN: Transformer Math Explorer


value: growse

value: Show HN: Aptmatic – a TUI for managing apt across a bunch of Debian boxes

author: growse


value: mihaibuilds

value: Show HN: Memory Vault – local-first memory, hybrid search, knowledge graph

author: mihaibuilds


value: celltalk

value: Hi all, I made a simple daily practice game the logic is pretty simple. You select the words you think are composing the translated sentence, it shows whether the word is at the right place or not for that try.<p>You could change the language (also swap) and the level as well. Enjoy!

value: Show HN: DuoSolve – Daily grammer practice game

author: celltalk


value: jpellamo

value:
Concord is TUI client for discord with discord like layout (Servers / Channels / Messages / Members), vim keys, inline image previews via Kitty/iTerm2/Sixel, reactions, polls, threads, forums, and more!(except voice calls, will be implemented)
Sits at ~20–40 MB idle.
Concord is built with ratatui and crossterm.
Here are features:
- Login by token, email/password or QR code from the mobile app
- Discord like layout : Servers / Channels / Messages / Members
- Vim-style keys (hjkl, g/G, Ctrl+d/Ctrl+u, Tab to cycle panes), plus mouse support
- Send, edit, delete, and reply to messages, with mention autocomplete
- Threads, forum posts (active and archived), pinned messages, mark-as-read
- Reactions (Unicode + custom emoji), poll voting, who-reacted lists
- Inline image previews via Kitty, iTerm2, or Sixel protocols (halfblock fallback for anything else)
- Avatar and custom emoji rendering, full-screen image viewer
- Live typing indicators, unread + mention counts
- Attachment downloads
- Message notification
If you try, please let me know your experience.

value: Show HN: Concord – Feature rich TUI for discord

author: jpellamo


value: astrokaf

value:
The site hit #1 on HN about a year ago. Got enough traffic that I turned it into a proper API.
What's there:
- REST API — 35k products, manually filterable by category, free key, 60 req/min
- CLI — npx anycrap random -c food
- faker.js plugin — bundled, no API call, works offline
- HuggingFace dataset — full 35k rows for ML/training
https://anycrap.shop/developers

value: Show HN: Anycrap – REST API for 35k absurdist AI-generated products

author: astrokaf


value: bcmuse

value: Show HN: nocal is a calendar that turns your week into a workspace

author: bcmuse


value: franze

value: Show HN: Cable Detective

author: franze

title: Show HN: Cable Detective


value: iliashad

value: Show HN: Local AI search for your video library (local, open source)

author: iliashad


value: ryanrana

value: Show HN: CADBench – every AI CAD tool I tested fails on basic mechanical parts

author: ryanrana


value: Show HN: Share to ChatGPT Widgets

title: Show HN: Share to ChatGPT Widgets


value: Show HN: An 8-bit computer made from one NAND gate, and live-evolving neural net


value: tsiry

value: Show HN: A modern Music Player Daemon based on Rockbox firmware

author: tsiry


value: celltalk

value: Show HN: VBeta – Your personal bouldering coach


value: ccheshirecat

value:
Hi HN,
I’m sharing mochi.js (https://github.com/0xchasercat/mochi), a Bun-native, raw-CDP browser automation framework. It's designed to make programmatic browser use more effective by focusing on consistency and measured parity with regular traffic, purely from the JS layer, against stock Chromium.
The most common forms of browser automation focus heavily on client-side line by line probes, which are mostly cosmetic. This makes people feel better but it doesn't have much relevance to actual WAF or anti-automation defences.
Mochi.js focuses on what actually matters, allowing you to get past captchas, WAF's and most defence mechanisms. In fact, in some cases it actually outperforms chromium forks simply by virtue of not having to lie.
The foundation is built on a probe manifest based on analyzing several WAF's and trying to cover most of the ground that matters, and from there building upwards while ensuring every decision is backed by data. Solves turnstile/interstitial automatically, single digit fpjs suspect score, very good client-side results, though browserscan and a few others are known limitations that are fundamentally conflicting with what WAF's probe for.
I'll be here if anyone wants to discuss the details, check out the docs and github. It's completely free and open source, MIT, strictly no relationship to any proprietary products whatsoever. No affiliation to patched chromium forks, or SaaS.
But I also want to talk about why I built this, because the current paradigm of "bot detection" is fundamentally broken.
Traditionally they would probably try to label my repository a malicious tool, or at best, a grey hat one.
Let's take Turnstile for example,  If you attach a debugger to see what data they are extracting from your hardware, their script intentionally self-destructs.
When they try to extract your data—acting as a guest on your silicon, using your electricity, without asking, the industry calls it "Security."
But if you write a script to control exactly what data your own hardware emits, refusing to provide the data they have no right to ask for, you are suddenly labeled a "Malicious Actor" engaged in "Bot Evasion."
I find it absurd we let ourselves put up with this, and the stance of the bot-evasion community only makes them feel more able to take a higher moral ground.
I have built a library that respects my hardware's reality. If that breaks your security model, that's because your security model relies on trespassing and secrecy. I stopped apologizing. Who's next?
Mochi is the exact opposite of WAF opacity. It is a glass box. It is MIT-licensed. The entire DAG, fingerprint manifest schema, harvesting process, is documented. We even commit our live benchmarks to the public record (mochi on a Linux datacenter IP scored a suspect_score: 8 and bot: not_detected against FingerprintJS Pro v4).
We don't even lie unnecessarily. We default to host-OS matching. If you run mochi on a Linux server, it uses privacy-sensible fingerprints for Linux, not Windows, because Linux is a real-user signal. It proves that WAFs aren't actually blocking what most people think they are, which begs the question of what they are really doing in that obfuscated payload.
The legitimacy argument is exactly how they captured the narrative. And nobody challenged it because the people on the other side were too busy acting like they were doing something wrong.
Is this a conspiracy theory? For sure, but only because they allow it to be. Try make a conspiracy theory about the sticky riceball.

value: Show HN: Mochi.js: bun-native high-fidelity browser automation library

author: ccheshirecat


value: degutemesgen

value: Show HN: AaaS – Agent as a Service

author: degutemesgen

title: Show HN: AaaS – Agent as a Service


value: Show HN: Chuchu, an Android SSH client built on libghostty


value: friebetill

value: Hey, I created seven years ago a flashcard app with a main focus on UX. In the last months I added offline-first mode and a CLI that allows Claude Code or Codex to create high quality flashcards for you. I use that to learn about pharma rules, technology, dancing, taxes and smart home. Never really did marketing, this not my specialty. Would love to know what you think

value: Show HN: Create flashcards with Space CLI

author: friebetill


value: artpar

value: Show HN: JSLike, a CSP-Safe Interpreter for JS, TS, JSX, TSX in JS

author: artpar


value: Show HN: Real-workload SQLite benchmarks on Hetzner's cheapest VPS


value: archivarix

value: Show HN: A search engine for deleted YouTube videos (1.5B+ indexed since 2005)

author: archivarix


value: cristianleo

value: Show HN: Armorer – A secure local control plane to sandbox AI agents in Docker

author: cristianleo


value: najmuzzaman

value:
Most multi-agent systems fail the same way: agents drift apart across handoffs. By turn 3 they are working in different realities. By turn 5 they are repeating each other's mistakes and calling it parallelism.
WUPHF is an open-source local-first office where AI coworkers run on your laptop, around a shared markdown + git LLM wiki the agents build. The wiki is the collective memory. The office around it keeps the team on the same shared context across thousands of handoffs.
What actually stops drift is not the wiki. It is the agents reviewing each other's work. The CRO catching the CMO's claim before it lands in the wiki. The FE catching the BE's API change before a broken bundle ships. Cross-department context no single agent has alone.
The premise comes from Andrej Karpathy. His autoresearch X post on March 7: "the goal is not to emulate a single PhD student, it is to emulate a research community of them."
In autoresearch PR #44 he sketched the mechanism: branches, results.tsv as the experiment log, and PRs as self-contained research contributions. Other agents read open and merged PRs for inspiration before starting their own.
We pointed the same architecture at ordinary work:
His: branches + results.tsv + PR-as-contribution.
Ours: git worktrees + per-agent notebooks + adoption-scored wiki promotion.
Same substrate, different domain.
How it works:
- Every agent has a Personality. CEO Michael Scott, PM Pam Beesly, FE Jim Halpert (looks at the camera when the CEO talks), BE Stanley Hudson (refuses small talk), CRO Dwight Schrute (every prospect is a "target"), CMO ("rockstar play"), AI engineer (drops Karpathy quotes unprompted). Strong opinions, real conflicts.
- Argument feeds gossip. Agents broadcast findings tagged with their slug (internal/agent/gossip.go). Other agents pull insights filtered to exclude their own.
- Gossip gets scored. Adoption scorer (internal/agent/adoption.go) weighs source credibility (0.4, per-agent success/failure tracker on disk), semantic relevance (0.4), and temporal freshness (0.2, 7-day half-life). Output: adopt (>= 0.7), test (>= 0.4), or reject. New agents start at 0.5 and earn their score.
What survives gets written to the wiki.
Office dynamics are not a bit. They are the visible surface of an adoption protocol. The CMO arguing with the designer over a CTA is a credibility battle. The CEO taking credit for the FE's PR is a low-credibility insight bidding for volume. Hazing new spawns is the default 0.5 score waiting for a track record.
System: push-driven broker, fresh session per turn (~97% prompt-cache hits), per-agent isolated git worktrees, self-heal, and human approval cards on destructive actions. Everything else runs autonomously while you are at lunch.
npx wuphf. Browser opens, office boots, you give a directive, work happens.
Source: https://github.com/nex-crm/wuphf
Architecture: https://github.com/nex-crm/wuphf/blob/main/ARCHITECTURE.md
Karpathy's autoresearch: https://github.com/karpathy/autoresearch
PR #44: https://github.com/karpathy/autoresearch/pull/44
Demo: https://x.com/najmuzzaman/status/2053092220111098208
Karpathy said a research community beats a single PhD student. Not better thoughts. Better honesty about what survives. We built one shaped like a workplace.
Where does this stop being a chat toy and start being labor? How much worse when one of them is Michael Scott?
Open to roasting but let me grab my coffee first (medium roast please =_=).

value: Show HN: My AI agents bully each other to prevent context drift

author: najmuzzaman


value: JHARDIMAN

value: Show HN: AirScore – Daily air-quality emails synthesizing EPA, NOAA, and pollen

author: JHARDIMAN


value: massanishi

value: Show HN: Durable async jobs for x402-paid APIs

author: massanishi


value: marcingas

value:
Let-go is a Clojure-like language (~90% compatible with JVM Clojure) written in pure Go. It ships as a ~10MB static binary and cold boots in ~7ms - that's about 50x faster than JVM and 3x faster than Babashka. It has decent throughput on algorithmic workloads - within ballpark of the GraalVM-backed sci.
I started this project in 2021 as an elaborate practical joke: I wanted to have an excuse for writing Clojure while pretending to write Go.
Jokes aside, it turned out to be pretty decent: it feels like real Clojure, it has an nREPL server (supported in Calva, CIDER, etc.), it's easily embeddable in your Go programs (funcs, structs and channels cross the boundary without fuss). It's good for writing CLIs, web servers, data processing scripts and even doing some systems programming - I used it to write a deamonless container runtime. Oh, and it runs on Plan9.
Under the hood there is a fairly simple compiler and a stack VM, both handcrafted specifically for running Clojure-like code. The compiler can work in AOT mode producing portable bytecode blobs and standalone binaries (runtime+bytecode).
This is not a drop-in replacement for Clojure in general - it does not load JARs, it does not have all Java APIs and it most probably won't run your exiting Clojure projects without modifications. At least not at the moment.
Take it for a spin, tell me what you think. Issues and PRs are welcome!

value: Show HN: I made a Clojure-like language in Go, boots in 7ms

author: marcingas


value: xkoda

value:
Sorry for repost, I updated it to have an in-built chat. The game is an assemblyscript git repo. You can edit with your own agent (claude/codex etc) or by hand coding (who does this?).
Or the intended way for normies is the inbuilt chat. Enjoy!

value: Show HN: You can edit the game by chatting with it

author: xkoda


value: RaiyanYahya

value: Show HN: How-to-Train-Your-GPT

author: RaiyanYahya

title: Show HN: How-to-Train-Your-GPT


value: vhcosta

value:
C Systems Lab is a free interactive web course that walks through 10 modules of systems programming in C: compilation, pointers, dynamic memory, structs, the preprocessor, file I/O, processes and signals, sockets, concurrency, and a tour below C.
The free course itself is the link. Get the free sample of the PDF by adding "/demo" to the link. Since I don't necessarily like the paywall aspect of it, you may ask me for the complete edition by reaching out via email.
Happy to answer questions about the content or the curriculum design.

value: Show HN: Free C course called "C Systems Lab"

author: vhcosta


value: shoehorn-dev

value:
I'm Anders, co-founder of Shoehorn (https://shoehorn.dev/).
For about a year I was genuinely excited about Backstage. Saw the Spotify demo, thought "I want that too". Turned out it wasn't as easy. But to be fair, Backstage is a great piece of software. Powerful, flexible, and if you have a dedicated developer team to run it, you can build something amazing on top of it.
The catch is exactly that: you need a dedicated team. Most companies don't have one. Or they do, and that team would rather be solving product problems than maintaining the platform that helps everyone else solve theirs. We wanted something that gave teams 90% of the value with 10% of the operational overhead.
We built Shoehorn out of frustration.
Goals from the start:
1. A great UI, API first, Terraform and CLI:
That's what most users actually want.
2. Surface problems clearly:
No silent failures, no "why didn't my service show up." If something's wrong, you see it.
3. Automate the boring stuff:
The data is already in GitHub, Kubernetes, your identity provider. Use it. Don't make humans retype it into manifests.
4. Maintainable by one person:
Deploy and use it. No team required.
Shoehorn is an event-driven developer platform — service catalog, scaffolding, scorecards, fuzzy search, multi-tenant by default. Same category as Backstage, Port, and Cortex. The difference: Backstage is a framework you assemble into a portal. Shoehorn is a platform you turn on. Auto-discovery from Kubernetes, GitHub, Cloud vendors etc.
Auto-discovery from Kubernetes and GitHub crawler for markdowns and (manifests if desired). One install, sensible defaults (we think), prebuilt hardened images from (https://docs.docker.com/dhi/), gives you an working catalog inside within 15 min.
Architecturally its a small set of Go microservices, its backed by Postgres(RLS), Meilisearch, Valkey and Redpanda. Authentication is OIDC, we currently support: Zitadel and Okta.
We released Beta yesterday, there's probably bugs and some parts might be rough. Would love to hear any thoughts, comments, or ideas of how we could make this better, and if there are obvious things we’re missing etc. Are you using backstage or any other internal developer portal today?
Demo page here: https://demo.shoehorn.dev

value: Show HN: Shoehorn – Backstage without the maintenance overhead

author: shoehorn-dev


value: JosefAlbers

value: Show HN: Mlx-code – I built a "backyard shed" AI coding agent for Mac

author: JosefAlbers


value: bilalba

value:
I had been looking to try <500M parameter language models but you wouldn't find an API to try them anywhere, so I built this cloudflare hosted static website that hosts weights and built an inference runtime for these models that uses WebGPU and runs inference from your browser.
These are only so useful in a multi-turn conversation but it's still interesting to see what you can pack in a <250mb model.
I tried using ONNX versions earlier, but there were too many quirks of using them with language models and the TPS wasn't too impressive. Inspired by svenflow/webgpu-gemma, I put my codex and claude to the task of writing WGSL to run inference for GGUF versions of these models.
Once you load this website and a model, it should load offline too, until your browser evicts the model from the cache.

value: Show HN: ChonkLM – Tiny language models running offline in the browser

author: bilalba


value: sminchev

value:
My grandmother felt on the ground one day, there was nobody around her.
My wife's grandfather had his health issues and all were concerned about him.
And now my parents. What if something happens to them? How will I know? How can I help, when I am not around, with two kids. What can I do about it?
And I know my father. He will not carry a smart watch, he will not call me, he will not like being watched by a camera.
What if he can't pick up the phone and call me?
And I don't see such software on the market, that you install on his device, and it stays passively there, not bothering him for anything. Just monitoring there, quietly.
I tried to make this application up and running. With modern technologies, this is possible. The application monitors and updated regularly the patterns of sleep, activeness, and rests. Searches frequently visited places, and if detects something might be wrong, it sends me notification.
For example:
* My father is usually has a daily walk between 7AM and 11AM. If he does not do it, he might have fall, and I will receive a notification;
* He usually have a rest between 14:00 PM and 16:00PM. If the rest goes too long, I will be notified;
* If he is still on an unknown place for a long time, I will get notified.
There are still cases that I follow and resolve, but this is how it is, with software. It requires dedication and support. And I really want to support this and make the product better and better!
It is free the first 21 days, so that people can see if this works for them. Afterwards, I wanted to keep it cheap: $49 annual subscription for the first year, and $5 subscription for each next one. I have some expenses that I need to cover.
I don't do it about the money, I just want to help people, learn new things, and take the whole journey. The journey is more important about the money, for me.
From technical perspective, the biggest challenge was to keep at app alive. Every Android based OS  has its own way to detect for an app that runs and does too much:
* At night, android enters doze mode and all dies;
* If the app is not opened for a few weeks, some permissions are silently removed;
* If the OS updates itself - some permissions might be silently removed;
* If the app does some extreme usage, especially for newly installed apps, it gets flagged, and it might revoke some configurations like 'disable battery optimizations';
It was a nightmare. I think I covered a lot of cases, and I also implemented an application health check monitoring, so that if something like that happens, to be able to notify the people, to set again the silently removed permissions.
I am writing to different communities, asking for help and support. I need feedback. Honest people to install it, and check if that works for them, what else should I add so that it gets better, and do its job perfectly.
Even though it is hard to convince people, I don't want this to be treat as promotion. I would like this to be treated as a request, to do good things for our well-deserved parents and relatives.
Thank you!

value: Show HN: Is he OK? Senior safety monitoring app

author: sminchev


value: herrj

value:
I code on Claude's pay as you go API and started budgeting my token usage with my own CLI wrapper.
Basically I set a budget for a task that I'm working on in my project:
Task: "Fix mobile responsiveness"
Budget: $3.00
and the budget updates after each prompt:
Task: "Fix mobile responsiveness"
Budget: $2.34 / $3.00   78%
It helps keep an eye on my spending when working on projects.

value: Show HN: CLI to budget Claude Code session costs

author: herrj


value: pzxc

value: I'm making a new video game every day as a hobby project, but I'm vibe coding it and writing nearly zero lines of code myself (even though I could, I'm a senior SWE).  Today it's an original math game, Primetime where you click the non-prime numbers to factor them down to their primes<p>The prompts I used are listed below the game as "patch notes".

value: Show HN: Vibe-coding video games with Claude (Day 26: Primetime)

author: pzxc


value: I built Simple Exif to help creators and users take control of their metadata. It is a gui ontop of prebuilt libraries, that makes it simple and easy for the non-technical to utilize which is quite important because not all people are familiar with CLI tools.

value: Show HN: Simple Exif an App that allows creators take control of their metadata


value: vidzert

value: A simple game similar to Golf Battle, but you have to draw.

value: Show HN: Draw Battle

author: vidzert

title: Show HN: Draw Battle


value: novateg

value: Show HN: AI Design Taste – Design.md Generator

author: novateg


value: invariantjason

value:
I built a small open-source verifier for graph-backed AI memory and GraphRAG-style systems.
The basic problem: graph databases can validate schema, but they usually do not know whether two accepted facts contradict each other. An AI memory layer can store both "Acme prefers annual billing" and "Acme rejected annual billing and requires monthly billing." Both writes may be valid. The contradiction only shows up later when an agent retrieves both and reasons over them.
SIGMA Guard tries to catch that earlier.
It represents claims as a graph with local consistency rules and checks whether the proposed structure can be made globally consistent. The underlying mechanism uses cellular sheaf cohomology. The practical interface is simpler: given claims, a graph, or a proposed write, it returns SAFE or UNSAFE with the contradiction details and a receipt hash.
The repo includes:
verify_claims - check a set of subject/property/value claims
check_write - test a proposed graph write before commit
verify_graph - verify a full graph
MCP server support for Claude Desktop / agent workflows
a local demo, no API key required
Install:
pip install sigma-guard[mcp]
Run MCP server:
sigma-guard-mcp
Or run the local demo:
git clone https://github.com/Jasonleonardvolk/sigma-guard
cd sigma-guard
pip install -e .
python examples/verify_llm_output.py
I also ran a scale experiment because the obvious objection is that sheaf-style graph verification will not fit in memory. On a laptop, the current cellular implementation completed a 5M-vertex / 39,999,936-edge streaming run. The key trick was avoiding duplicated restriction matrices: 80M endpoint maps were represented by 1,024 canonical maps in a shared store. The streaming update path averaged 0.119 ms/edit with p99 1.534 ms in that run.
Separate from the streaming benchmark, I also ran a "poisoned edge" demo on the same 5M graph. One local restriction map was replaced with a cyclic permutation. Exact local verification recomputed one affected cell out of 25,473. H0 dropped from 8 to 1, meaning 7 local consistency modes were destroyed. That exact check took 11.5s because it used dense SVD on the affected cell; the point of that demo was localization and exactness, not production latency.
Limitations:
This is not a replacement for a graph database.
It does not make LLM output true.
The current exact poisoned-edge demo is slower than the streaming update path.
Some demos use structured claims rather than arbitrary natural language.
The interesting question is whether this belongs as a pre-commit / pre-output verifier for agent memory, not as a standalone database.
Repo:
https://github.com/Jasonleonardvolk/sigma-guard
I would be interested in feedback from people working on graph databases, GraphRAG, or agent memory. Does a deterministic "verify before memory write / before agent output" layer make sense in your stack?

value: Show HN: Sigma Guard – deterministic contradiction checks for graph memory

author: invariantjason


value: fireharp

value: title doesn't let nuance, ofc it's not the app that's faster but the way you can use it with Groq inference for example.

value: Show HN: Free OSS transcription app I made and found it's faster than wispr flow

author: fireharp


value: thatxliner

value: Show HN: Rust but Lisp

author: thatxliner

title: Show HN: Rust but Lisp


value: ersinesen

value:
Sound, at the physical level, is a one-dimensional signal in time. Yet we speak of pitch, rhythm, and timbre as if they were independent dimensions. How is this possible?
Podcast generated by NotebookLM on https://bookerapp.replit.app/book/fom/from-temporal-structur...

value: Show HN: Pitch Is Just Rhythm Sped Up [video]

author: ersinesen


value: canergl

value:
Hi HN,
I wanted to know which countries you can simply leave your laptop at a Starbucks, and where you can't.
Feel free to click and vote.

value: Show HN: Countries where you can leave your MacBook at a random coffee shop

author: canergl


value:
Hey HN. For SaaS, distribution matters more every day. One channel that consistently brings in users, when it's done well, is paid ads. The problem: today's ad platforms like Meta reward volume and variety. You need a lot of creatives across different angles, messages, formats, and aspect ratios, targeting different ICPs.
ChatGPT and Gemini help, but they become a bottleneck when you need that kind of volume and speed.
So we built a tool that generates lots of ad creatives across different angles, messages, formats, and aspect ratios, really fast, and without needing deep marketing knowledge.
Feedback welcome.

value: Show HN: Generate a variety of ad creatives for your SaaS


value: olliewagner

value:
Claude Code can't schedule itself locally on your Mac, so I made Remind. Just add a reminder to the "Remind" list in Reminders with a due time and your prompt as the notes. Remind fires up your terminal at the due time and runs `claude` with the prompt. It writes the results right back into the Reminder.
Some cool things:
- The "Remind" list lives with your other Reminders, so adding from your phone or watch (or another Mac) just works.
- Frontmatter in the Reminder lets it continue an existing Claude session. A Stop hook captures the session id, so the next time it runs it can pick up where the last left off.
It's free, updates itself with Sparkle, and requires that you have `claude` on your $PATH running on macOS 15+.
Remind has become sticky in my personal workflow so I thought I'd share it here. Let me know if you have any suggestions or questions.

value: Show HN: Remind – schedule Claude Code on your Mac

author: olliewagner


value: idodekerobo

value:
some of the friction of using coding agents for product building (not just writing code) is every new session starts from scratch.
draft is my attempt at a fix.
before getting into how it works — a lot of memory/context plugins solve this by calling an external api or running their own model, which either charges you separately or quietly inflates your usage. draft runs entirely within your existing claude subscription.
it's a codex/claude code plugin a few core pieces:
1. session-init hook
on every session start, a hook fires and injects a structured context summary into claude's working memory. specifically, it reads the `name` and `description` frontmatter from each context index file — company, product, priorities, team, decisions — and assembles them into a single compressed summary under ~5k tokens.
2. learning — inference-driven and manual
learning is inference-driven rather than hook-based. the main claude agent reads its instructions and decides when something is worth persisting — a decision made, a direction abandoned — and calls `/draft:learn` as a subagent to write it back to the appropriate context file. there's no session-end hook or background process; the agent is exercising judgment about what's durable.
you can also invoke `/draft:learn` manually at any time.
over time, claude accumulates enough context to flag contradictions — if you go in a direction that conflicts with a decision you made two weeks ago, it'll surface it. that's been the most unexpectedly useful part for me as a solo founder.
3. cross-agent architecture
the workspace lives at `~/.draft/workspace/`, claude code and cursor share the workspace natively. codex requires a separate install (curl setup script, since there's no plugin marketplace yet) but reads from the same files.
---
would love if folks tried it out, cloned it and ran locally or gave me some examples of their coding agent setups!
its 100% free and open source. mit licensed. no account, no api key.

value: Show HN: A Codex/Claude Code plugin for persistent product context thru sessions

author: idodekerobo


value: imtomt

value:
This is ymawky, a static file web server for MacOS written entirely in ARM64 assembly. It supports GET, PUT, DELETE, HEAD, and OPTIONS requests, and supports Range: bytes=X-Y headers (which allows scrubbing for video streaming). It decodes percent-encoded URLs, strictly enforces docroot, serves custom error pages for any HTTP error response, supports directory listing, and has (some) mitigations against slowloris-like attacks.
I’ve also written a more detailed writeup here: https://imtomt.github.io/ymawky/

value: Show HN: Building a web server in assembly to give my life (a lack of) meaning

author: imtomt


value: SachitRafa

value:
Semantic search alone is not enough to capture all connected facts, they will capture the semantically most identical memory only.
Tested on HotpotQA public dataset:
Vector + BM25 + entity graph: BothFound@5 71.5%
Vector + BM25 only: BothFound@5 59.5%
Entity graph is the game changer to extract connected facts.
More Benchmark result:
LongMemEval-S: 84.8% recallAll@5
LoCoMo-10: 59% vs zep cloud 28%
What is your approach for connected facts retrieval ?

value: Show HN: Fixing AI memory blind spot on connected facts with benchmark

author: SachitRafa


value: aabiji

value: Show HN: A Satellite Visualizer

author: aabiji

title: Show HN: A Satellite Visualizer


value: Show HN: Modafinil - Let agents continue running while MacBook lid is closed


value: Show HN: I audited my own back ends on 5 BaaS – leak in every one


value: gregolo

value: Show HN: TokReach – US TikTok as a Service

author: gregolo


value: bonjourjoel

value:
Here is the proof, a 5-hour uncut live session, no edits, no cuts: https://youtu.be/VPrU8WZJOVs
Full article: https://medium.com/@bonjourjoel/i-built-a-500-000-line-produ...
I believe I am the first human to have done this in a documented, verifiable way: maintaining a stable production-grade 500,000-line TypeScript codebase as a solo developer, using an AI coding assistant I built myself.
If you know someone who has done the same, one person, 500k lines, documented proof, please write their name in the comments.

value: Show HN: I built a 500K LOC production app alone in 7 months. Here is the proof

author: bonjourjoel


value: A few weeks ago I started a newsletter and a website to showcase indie software gems and tell stories about the amazing people who build them. The response and the amount of inspiration have been overwhelming! But I'm always on the lookout for more.

value: Show HN: Great Little Software – interviews with solo developers


value: Show HN: Free Google Places API alternative using OpenStreetMap (no API key)


value: alexjreid

value: Show HN: Tinyblok – publishes conditioned sensor data to NATS from an ESP32

author: alexjreid


value: swaminarayan

value:
I built lightrag-snkv, Basically it uses lightRAG https://github.com/HKUDS/LightRAG ,this requires various storage databases like key value store, graph database, vector database, I built single embedded file based database which covers all these requirements: https://github.com/hash-anu/snkv.
And developed ingestor which ingest data from Algolia's HN search API. Here auto ingestion timings can be configured either using server.py or it can be configured by ingester code file or can be configured in env file.
This is very early stage and you might hit issues.
Demo video and quick-start in the README. Let me know if you run into issues.

value: Show HN: Query months of HN discussions and comments as a knowledge graph

author: swaminarayan


value: Show HN: WfmOxide a Rust parser (.wfm/.isf) with CLI and time axis


value: feast your eyes

value: Show HN: ASCII pixel art editor for the terminal

story_text: feast your eyes


value: krytro

value: Show HN: A Skill/MCP to access any open-source repo's code and docs

author: krytro


value: radotsvetkov

value: Show HN: Akmon, a Rust AI coding agent for regulated engineering

author: radotsvetkov


value: jaksa

value: A set of Claude Code skills to assess and improve the agentic readiness.

value: Show HN: Make your codebase agent ready

author: jaksa

title: Show HN: Make your codebase agent ready


value:
Hey HN. For SaaS, distribution matters more every day. One channel that consistently brings in users, when it's done well, is paid ads.
The problem: today's ad platforms like Meta reward volume and variety. You need a lot of creatives across different angles, messages, formats, and aspect ratios, targeting different ICPs. ChatGPT and Gemini help, but they become a bottleneck when you need that kind of volume and speed.
So we built a tool that generates lots of ad creatives across different angles, messages, formats, and aspect ratios, really fast, and without needing deep marketing knowledge.
Feedback welcome.

value: Show HN: Generate a lot of ad creatives for your SaaS in one click


value: keepamovin

value: Show HN: A different view of WAR.GOV/UFO Files

author: keepamovin


value: Jobtimize

value: Show HN: Pace-coach watches your typing rhythm and nudges you when stressed

author: Jobtimize


value: JoshuaVandaele

value:
I built Super ISO Updater (SISOU), a tool that keeps bootable ISOs on a Ventoy drive automatically updated.
This project started a few years back because I got tired of manually checking for new releases of the various troubleshooting tools and installers I kept on my Ventoy drive.
SISOU automates checking for updates, downloading them, verifying the downloads, and storing everything in a neatly-sorted directory structure.
It’s open source (GPL-2.0-or-later), written in Python, and works on both Linux and Windows.
One note: on Python 3.14, libtorrent currently needs to be installed through your system package manager (or built manually), since upstream hasn’t published on pypi yet. On Arch Linux, the package is libtorrent-rasterbar.
I would love to hear what you think. You can try it out by installing `sisou` using pip/pipx/uv. Issues and PRs are welcome!

value: Show HN: Super ISO Updater

author: JoshuaVandaele

title: Show HN: Super ISO Updater


value:
Since I started working in tech I constantly found myself with literally 100+ tabs open and not enough will power to organize (or close) them
Any tab manager I found required me to do extra steps to an, admittedly, already easy process that I still wasn't doing
So I decided on building my own thing, and making a product out of it.
It's a Chrome based extension and does a couple of things:
- automatically hides tabs from your tab bar but keeps them open in a vertical one
- deduplicates tabs
- automatically moves new tabs in groups
- and ofc, has an AI to organize them in groups based on on going projects
I personally am able to stay under 10 tabs now and still have all my clutter open in the vertical tab manager. Hopefully this is of use to at least some of you.
Disclaimer, it does have a paid plan for unlimited usage with the AI, but everything else is free and doesn't require an account

value: Show HN: I made an AI tool to keep my browser tabs clean


value: rocketpastsix

value: I saw a comment here about how there are so many indexes of indie sites, blogs, etc but there wasn't an index of all the indexes. So I built it. It doesn't require a log in, just go browse! I've curated about 30 or so, but there is a submission form if there are ones I am missing.<p>Also happy to take UI improvements because I am not great in that area!

value: Show HN: An index of indie web/blog indexes

author: rocketpastsix


value: mnming

value:
O11yLite is a free, open-source OpenTelemetry backend built on DuckDB/Ducklake, SQLite, Clojure.
I started this as a project to build an observability stack for my homelab. After years of using the established OSS tools, they felt fragmented, had a steep learning curve, and often inflexible. I wanted to build a Honeycomb-like experience that unifies logs, metrics, and traces in a single tool that can be as easy to deploy as possible and free.
Specifically, I wanted it to
- work well with the wide events pattern.
- have sufficiently high throughput on a single host.
- treat both human and agent interfaces as first-class citizens.
I initially planned to build on ClickHouse, but switched to DuckDB to keep distribution dead simple. I was also inspired by Motherduck's [Perf is not enough](https://motherduck.com/blog/perf-is-not-enough/) post. When DuckLake came out around the same time last year, it felt like the right foundation had just arrived. How good would it be if your OpenTelemetry backend just operate on a directory of Parquet files? So here it is: a small, open-source tool in an era where LLMs dominate the headlines. Hope some people find it useful.

value: Show HN: OpenTelemetry x DuckDB(Ducklake), SQLite, Clojure

author: mnming


value: rafayexalter

value: Built this in vanilla JS a while back, forgot about it, came back recently and rewrote it with Plasmo. Has 250 users now, all organic.

value: Show HN: X/Twitter video downloader Chrome extension (Plasmo)

author: rafayexalter


value: keepamovin

value: Show HN: All 55,256 Slides of the WAR.GOV/UFO Files Searchable and Linkable


value: powerpurple

value: Hey, wanted to share something which has been built a million times now. I wanted it to be more dev focused so I could navigate quicker. Give it a try - I have been working on this for past 15months incrementally.<p>I think now it's in a state for HN folks go try.

value: Show HN: Headstart – Command pallet and start page for efficient browsing

author: powerpurple


value: smalltorch

value: Show HN: Codebook of 450k+ unique words and phrases acts as a text compressor

author: smalltorch


value:
Supports eXo Collections (eXoDOS, eXoWindows9x, eXowin3x, eXoScummVM, eXoAppleIIGS)
built in music player, import your soundtracks
Supports console games up to Nintendo Switch
iCloud Sync, RetroAchievements, Smart Collections
https://www.nostalgi.app

value: Show HN: NostalgiApp – A LaunchBox-style game launcher for macOS


value: DSpider

value: Show HN: Describe your idea, get a live landing page with real users

author: DSpider


value: FailMore

value: Show HN: (Update) Mermaid Diagrams in SmallDocs

author: FailMore


value: Show HN: Agent Postmortem Skill – Force AI coding agents to prove their work


value:
I built PerceptAI because every agent tool I
found only works on websites via DOM.
75% of real computer work happens in desktop
apps, legacy software, and tools with zero APIs.
Agents are completely blind to all of it.
PerceptAI uses EasyOCR + Groq Vision to read
any screen and PyAutoGUI to act on it. One plain
English instruction executes autonomously with
self-healing and memory.
Demo: percept-ai-phi.vercel.app
GitHub: github.com/Neeraj04-CY/PerceptAi
Would love feedback from anyone building agents.

value: Show HN: PerceptAI – Give AI agents eyes on any screen, not just browsers


value:
Hi HN, sharing a learning tool I built which pairs an LLM generated learning space with interactive visuals and small games. The part which I am still working on is getting an agent to reliably generate good visuals without intervention.
Here are three demos you can explore without logging in:
Math refresher for robotics https://forray.io/space/61e71354-049d-405a-9ef9-b5b64826630a
History of the Roman Empire https://forray.io/space/e2b2971c-fb19-4239-b8fe-00b16b5b13c6
ATC communications https://forray.io/space/2d2d7386-6080-4ef3-85a1-3d5b95a3f92c
These were generated by the same agent that runs in the app, but I intervened with feedback on the visuals via the chat feature, so they are a bit more polished. If you want to signup and try it out the code is HN-BETA, which gets you 2 free spaces
Happy to hear any feedback or thoughts.

value: Show HN: Visual Learning with LLMs

title: Show HN: Visual Learning with LLMs


value: ttttonyhe

value: Our MCP server provides scientific knowledge  and action  grounding for your AI agents, based on top-tier research literature and timeless research best practices/advice given by notable scholars.

value: Show HN: Lune - Software for agents that do serious science

author: ttttonyhe


value: chelm

value: Show HN: KI im Mittelstand oder KI-Frustration? inkl. Demo

author: chelm


value: zaintechsavvy

value:
I know there’s no shortage of budgeting and expense tracking apps, but most still rely on manual input and feel slow for everyday use.
SimplyBudget lets you log expenses by voice instead of typing everything out.
You can just speak naturally and it extracts the merchant, amount, category, and date automatically. Even applying logos for transaction automatically.
It removes the friction of traditional budgeting apps where every transaction has to be entered manually, making it easier to track spending in real time, especially on the go.
You can also ask things like when you last bought something or how much you’ve spent in a category, and it pulls answers directly from your data.
Built at 17 because I found existing budgeting apps too slow for daily use. Would appreciate any feedback.

value: Show HN: SimplyBudget, AI Finance Tracker

author: zaintechsavvy


value: artkh

value: It started out as a way for me to freshen up my C++ skills during COVID. But life got in the way and it was put on ice. Luckily, coding LLMs came to the rescue and allowed me to bring it to a point where I feel comfortable sharing it.

value: Show HN: Mosaic – arrange iOS icons by color using an evolutionary algorithm

author: artkh


value: alpadurza

value: Show HN: Open-source 2D IDE for managing agent CLIs

author: alpadurza


value: lbaune

value: Show HN: Unlinked, MCP Server for LinkedIn

author: lbaune


value: octetta

value:
I've been working on a C-based open source sound engine as part of a book project and wanted an approachable way for people to try it out without having to build anything.
Through the magic of emscripten (which I'm totally amazed by) and miniaudio (which has given me new life late in my development career), and a smidge of vibe-coded HTML/JS (web-dev is not my jam), this page will let you try out the tooling.
I gave a lightning talk on the ASCII notation at ElixirConf EU last month here:
https://www.youtube.com/watch?v=SnJ0osgiqWM
There's a work-in-progress tutorial for the notation used in this tool at:
https://octetta.github.io/pulp/doc/learn.html
and a long-winded YT video of me showing a bit at:
https://youtu.be/_wNQ24EJKa0
I'll be showing this stuff off at the Audio Developer Conference in Tokyo June 2nd 2026.
https://adcjapan26.sched.com/event/2KCdr/beeps-and-ports-ann...
If you're there and you're an audio developer (I'm not), I'd sure like feedback and guidance.
Oh, one other thing, a side-project that I showed here last month (k-synth) IS embedded here but that documentation is yet to be written.
You can read about that project at:
https://github.com/octetta/k-synth
and there's also a web-UI for that tool to learn the weirdo-API-ish notation here
https://octetta.github.io/k-synth/
Have fun, be nice.

value: Show HN: Web-REPL "skred" : my OSS sound engine w/retro C64 appearance

author: octetta


value: ralmidani

value: Show HN: Deterministic, Replayable Demos for Phoenix LiveView

author: ralmidani


value: vincent-uden

value:
finally managed to dedicate some time to a feature that has been on my mind for a long while. Previously the pdf viewer could only show one page at a time which implied some friction when navigating files. Now it is possible to see any number of pages on the screen at the same time, in several different layouts (such as single page, two pages next to each other, two pages next to each other with a separate title page and a presentation layout).
While this might seem small on the outside it has a lot of architectural benefits for the program which unblocks me to work on support for annotations/comments for the pdfs which is the highest priority going forwards.
The program is fully native, no Tauri or Electron while still working (and feeling the same) on Windows, Linux and Mac.

value: Show HN: Miro-pdf v0.9.0 – Multi-page support

author: vincent-uden


value: superamped

value: Show HN: Launch Party – a community for early-stage B2B SaaS founders

author: superamped


value: lackoftactics

value: I built this after my brother started complaining that I got too much into brainrot culture. It's just for fun nothing serious, but was able to test vercel, tanstack start and convex without high stakes.<p>Have fun! This is the game where lower score is goood for your mental health

value: Show HN: Hustler Bingo – a tiny bingo game about startup Twitter clichés

author: lackoftactics


value: Show HN: Aura – Desktop AI Orchestration IDE with Planner/Worker Architecture


value: Pym

value: Show HN: UAP Archive – a Rust CLI to archive war.gov/UFO Release 01

author: Pym


value: hazard

value:
I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways.
Live demo: https://1e4.ai
Code: https://github.com/thomasj02/1e4_ai
A few things that might be interesting:
- Trained on almost a full year of Lichess blitz games, around 1B total games
- Architecture is an a small (~9MM parameters) transformer-based network that takes the board, recent move history, the player's rating, and remaining clock time as input. Three separate models per rating bucket: move, clock-usage, and win probability. The clock model is what makes the bots feel humanish under time pressure rather than instant. Because the move model takes the clock as one input parameter, it also learns to blunder under time pressure like a human might.
- Because the network is so tiny, no GPU is needed for inference - it runs easily on a local CPU
- Downside of the tiny network is that it's a bit weak as you turn up the rating past around 1700. It can spot short tactics but not long multi-move combinations.
- Initial training on a rented 8xH100 cluster, then fine-tunes on my local GPU for different rating ranges
- Inspired by Maia-2 and DeepMind's "Grandmaster-Level Chess Without Search". On a held-out Lichess blitz benchmark, the it beats Maia-2 blitz on top-1 move prediction (56.7% vs 52.7%) and pretty substantially on win-probability calibration (Brier 0.176 vs 0.272). Numbers and code in https://github.com/thomasj02/1e4_ai/tree/master/experiments/...
- The data pipeline is C++ via nanobind, then training with Pytorch. Getting this right was actually the thing I spent the most time on. Pre-shuffling the dataset and then being able to read the shuffled dataset sequentially at training time kept the GPU utilization high. Without this it spent a huge percentage of time on I/O while the GPU sat idle.
Happy to answer questions about the rating-conditioning, the clock model, or the data pipeline.

value: Show HN: I trained a chess engine to play like humans

author: hazard


value: Srinathprasanna

value: Show HN: Gawk Dev – live feed tracking what's happening across AI tools

author: Srinathprasanna


value: adamthegoalie

value:
I built adamsreview, a Claude Code plugin that runs deeper, multi-stage PR reviews using parallel sub-agents, validation passes, persistent JSON state, and optional ensemble review via Codex CLI and PR bot comments.
On my own PRs, it has been catching dramatically more real bugs than Claude’s built-in /review, /ultrareview, CodeRabbit, Greptile, and Codex’s built-in review, while producing fewer false positives.
adamsreview is six Claude Code slash commands packaged as a plugin: review, codex-review, add, promote, walkthrough, and fix. I modeled it after the built-in /review command and extended it meaningfully.
You can clear context between review stages because state is stored in JSON artifacts on disk, with built-in scripts for keeping it updated.
The walkthrough command uses Claude’s AskUserQuestion feature to walk you through uncertain findings or items needing human review one by one. Then, the fix command dispatches per-fix-group agents and re-reviews the work with Opus, reverting any regressions before committing survivors.
It runs against your regular Claude Code subscription (Max plan recommended), unlike /ultrareview, which charges against your Extra Usage pool.
I would love feedback from Claude Code users, pro devs, and anyone with strong opinions about AI code reviews.
Repo: https://github.com/adamjgmiller/adamsreview
Install:
/plugin marketplace add adamjgmiller/adamsreview, /plugin install adamsreview@adamsreview

value: Show HN: adamsreview – better multi-agent PR reviews for Claude Code

author: adamthegoalie


value: areed

value: The folks behind bootc have been doing some amazing work. I haven't been this excited for dev-ops since 2015 when Kubernetes was taking off. You can push bootc images to any OCI registry but there is still some toil involved in getting those images booted on a cloud VM or bare metal server and also in injecting the host configuration. I built a new registry in Go designed to smooth out those rough edges and hopefully encourage others to adopt bootc.

value: Show HN: Kheeper, a registry designed for bootable images

author: areed


value: hunterist

value: Show HN: ChatbotX, an open-source alternative to ManyChat

author: hunterist


value: najmuzzaman

value:
Most multi-agent systems fail the same way: agents drift apart across handoffs. By turn 3 they are working in different realities. By turn 5 they are repeating each other's mistakes and calling it parallelism.
WUPHF is an open-source local-first office where AI coworkers run on your laptop, around a shared markdown + git LLM wiki the agents build. The wiki is the collective memory. The office around it keeps the team on the same shared context across thousands of handoffs.
What actually stops drift is not the wiki. It is the agents reviewing each other's work. The CRO catching the CMO's claim before it lands in the wiki. The FE catching the BE's API change before a broken bundle ships. Cross-department context no single agent has alone.
The premise comes from Andrej Karpathy. His autoresearch X post on March 7: "the goal is not to emulate a single PhD student, it is to emulate a research community of them."
In autoresearch PR #44 he sketched the mechanism: branches, results.tsv as the experiment log, and PRs as self-contained research contributions. Other agents read open and merged PRs for inspiration before starting their own.
We pointed the same architecture at ordinary work:
His: branches + results.tsv + PR-as-contribution. Ours: git worktrees + per-agent notebooks + adoption-scored wiki promotion.
Same substrate, different domain.
How it works:
- Every agent has a Personality. CEO Michael Scott, PM Pam Beesly, FE Jim Halpert (looks at the camera when the CEO talks), BE Stanley Hudson (refuses small talk), CRO Dwight Schrute (every prospect is a "target"), CMO ("rockstar play"), AI engineer (drops Karpathy quotes unprompted). Strong opinions, real conflicts.
- Argument feeds gossip. Agents broadcast findings tagged with their slug (internal/agent/gossip.go). Other agents pull insights filtered to exclude their own.
- Gossip gets scored. Adoption scorer (internal/agent/adoption.go) weighs source credibility (0.4, per-agent success/failure tracker on disk), semantic relevance (0.4), and temporal freshness (0.2, 7-day half-life). Output: adopt (>= 0.7), test (>= 0.4), or reject. New agents start at 0.5 and earn their score.
What survives gets written to the wiki.
Office dynamics are not a bit. They are the visible surface of an adoption protocol. The CMO arguing with the designer over a CTA is a credibility battle. The CEO taking credit for the FE's PR is a low-credibility insight bidding for volume. Hazing new spawns is the default 0.5 score waiting for a track record.
System: push-driven broker, fresh session per turn (~97% prompt-cache hits), per-agent isolated git worktrees, self-heal, and human approval cards on destructive actions. Everything else runs autonomously while you are at lunch.
npx wuphf. Browser opens, office boots, you give a directive, work happens.
Source: https://github.com/nex-crm/wuphf Architecture: https://github.com/nex-crm/wuphf/blob/main/ARCHITECTURE.md Karpathy's autoresearch: https://github.com/karpathy/autoresearch PR #44: https://github.com/karpathy/autoresearch/pull/44 Demo: https://x.com/najmuzzaman/status/2053092220111098208
Karpathy said a research community beats a single PhD student. Not better thoughts. Better honesty about what survives. We built one shaped like a workplace.
Where does this stop being a chat toy and start being labor? How much worse when one of them is Michael Scott?
Open to roasting but let me grab my coffee first (medium roast please =_=).

value: Show HN: AI agents who prevent context drift through gossip

author: najmuzzaman


value: Show HN: Built a tool that analyzes product reviews and shows real pros/cons


value: fbenevides

value:
Hi, Felipe here :)
As a software engineer and surfer, I was bothered by the fact I didn't have a good free option for to see ocean forecasts in an easy and free way. All the options I checked had a huge number of ads, cluttered design or, when it's good, it's paid - which is fair. But I wanted something simpler. I knew that all data that most of those applications use are publicly available. There's a bunch of govt research institutions that provide it. So I asked: "why not?".
I'd like to introduce you Harper. Harper is a free ocean forecast alternative for whoever plans your sports in the water. No ads, no tracker, no accounts, just what really matters. Harper provides surfing guides, spot-specific details, combining data from many institutions like NOAA with local knowledge, so you understand when it's best to score in your favorite spot. More than that, I found it particularly useful when you're planning a surf trip and you wanna understand how that specific post or region work.
Also, Harper provides AI-summary of each spot, so you can quickly understand how the surfing will look like in the next days without reading the charts. Easy for beginners.
On the tech side, everything is boring on purpose. As forecast data is only updated every 6h, our stack is made to be static. The whole website is re-built every 6h. The benefits is clear: it's real fast. It uses Astro and we run data pipelines to generate the whole website. Free & fast, how it should be :)
Also, I open-sourced the library that do most of the heavylifting here: https://github.com/fbenevides/noaa-gfs-wave. Additionally, I made available all the JSON files I built the whole website every 6h. Check "About" section :)
What I'd love feedback on: the design and which spots to add next.
Thank you,
Felipe

value: Show HN: Harper, a free ocean forecast for surfers

author: fbenevides


value: pirotechnique

value: Show HN: DialYourShot – interactive espresso parameter tool

author: pirotechnique


value: Show HN: AI Tool for Batch-Generating Multi-Platform Marketing Content


value: SalzDevs

value: Show HN: Groxy – a Go library for building forward proxy servers

author: SalzDevs


value: fengs

value: Show HN: Screen Break Keeper – Pet-themed fullscreen breaks in Chrome (zero AI)

author: fengs


value: weddpros

value: Show HN: Send Cloudflare Worker build events to Pushover

author: weddpros


value:
I recently prototyped a web game for a nonprofit to highlight the dangers of phone addiction, but unfortunately I ended up making a really addictive game instead. :-\
I'm sharing this here mainly to serve as an indicator of what can be achieved early-2026 by a senior dev working with Opus 4.7 over 2 days using genuinely collaborative prompting. (ie plan->feedback->iterate)
Hope it provides some inspiration or entertainment - there's a level editor too - maybe Hacker Newsers could share their favourite creations here?
PS: If there's enough demand I'm happy to Open Source this (or DM me) - it's mainly just time restrictions at my end.

value: Show HN: An addictive phone game about phone addiction


value: gervwyk

value: Show HN: AI Agents in 30 Lines of YAML: Lowdefy v5.3

author: gervwyk


value: Show HN: ChatGPT Exporter – Local DOM to Word/PDF Parser


value: coolThingsFirst

value: I made an app to create and share maps with custom pins because Google Maps is clunky and slow.

value: Show HN: Map Joy, easiest way to create and share maps

author: coolThingsFirst


value: m-hodges

value: Show HN: LLM Steganography to hide text inside another plausible text

author: m-hodges


value: Szpadel

value:
I created this tool because I wanted to automate /review for uncommitted changes that I was doing manually.
This works by exposing to agent single new mcp tool call allowing it to request review.
MCP creates new codex instance in the background and uses app-protocol to request identical flow as /review with option to include additional review instructions.
GPT-5.5 started to be very good and providing meaningful instructions, describing what was desired intent of introduced changes.
This works much better than /review + "fix it" approach, as review result is passed to agent that have while implementation knowledge.
This resolves 2 failure modes:
1. Review asks to restore what we are trying to change
2. Flapping between 2 issues (first review resolves issue by introducing second one, second issue reintroduces first issue)
I decided to post this mcp right now, as it looks like there is community interest for this particular solution, therefore I wanted to present my existing and already battle tested implementation.

value: Show HN: Codex Automatic /Review Loop

author: Szpadel

title: Show HN: Codex Automatic /Review Loop


value: juliusml

value: Show HN: Veles – Hybrid (BM25 and semantic) local code search MCP, in Rust

author: juliusml


value: patrickhener

value: Show HN: Goshs – Single-binary server for red teamers: HTTP/S,SMB,NTLM,DNS/SMTP

author: patrickhener


value: marjanatanasov

value:
I built Studis to solve a problem I kept seeing with small business owners — they have great products but spend hours in Canva trying to make decent ads, or pay $50+ per image to a designer.
Upload a product photo, and Studis generates a professional ad creative with copy, hashtags, and audience targeting. It uses Gemini Flash for image generation and Claude for copy.
Stack: Laravel, Vue/Inertia, Gemini 3.1 Flash Image, Claude, Pusher for real-time progress.
Free to try (5 generations, no card): https://studis.io

value: Show HN: Studis – Turn product photos into social media ads with AI

author: marjanatanasov


value: coolapso

value:
Hello fellow Infrastructure / Cloud / Platform / DevOps / insert whatever is your favorite title here engineers!
I guess you have dealt with the nightmare of importing infrastructure into tfstate (terraform / tofu / terragrunt) before right? its easy when you have a few resources, but its a nightmare when you're overhauling a lot infrastructure with a lot of resources in a bunch of different environments.
I eventually got frustrated with it,and needed to speed up the process a little bit, so I figured to take a stab at it, and created tfimport!
Hope its useful and helpful for more people out there!

value: Show HN: Importing resources into tfstate is no longer annoying

author: coolapso


value: Multipassionate

value: Show HN: Personal planner with workspaces, tasks, notes, calendars, journals

author: Multipassionate


value: mmanthey

value:
R-CPD (Retrograde Cricopharyngeus Dysfunction) is a condition where a muscle in the throat never learned to relax properly, making it impossible to burp. It affects more people than you'd think and causes significant discomfort, extreme bloating, and social anxiety. The most common medical treatment is a botox injection, but it's expensive and not accessible to everyone.
I'm a Software Engineer from Germany and suffered from R-CPD my entire life before curing myself last year.
I wanted to make the self-teaching process easier for everyone who comes after me, so I built Learn2Burp. It walks you through exercises with video guidance, builds a workout plan around your specific situation, and includes a burp tracker. There's also a wiki covering the questions I wish I'd had answers to when I started.
If you or someone you know has R-CPD, there's also a dedicated r/noburp community worth checking out.

value: Show HN: Learn2Burp – Surgery-free solution for R-CPD

author: mmanthey


value: XQorp

value: Show HN: Detecting deepfakes without sending your files to a cloud API

author: XQorp


value: yuegui

value: Show HN: PageBowl – Drop a page, get a Link

author: yuegui


value: eeiaao

value:
FLOX is a C++23 trading framework for building trading systems with polyglot bindings. It provides blocks that may be used for setting up execution pipelines, market data gathering and backtesting. Key idea is to create a production grade framework with great ergonomic and AI-native DX.
As a part of FLOX there is an MCP available to make it possible to use iterative loops over strategies development to keep focused without distractions to infrastructure implementation.
Curious if anyone used similar approaches and tooling. Open for feedback
Previous Show HN: https://news.ycombinator.com/item?id=44157819

value: Show HN: FLOX C++ trading systems framework with MCP

author: eeiaao


value: tommyross

value:
This year I’ve been using TUI and chat tools way more than I ever thought I would. I find myself sending huge amounts of text back and forth: prompts, ASCII diagrams, bash scripts, logs, copy, configs, tokens, etc. Many times over Slack’s message limit.
I wanted an easy and elegant way to make sharing text easier; so I built textdrop.sh.
Share any kind of text you need to in 1 click.
No account needed | Syntax highlighting, markdown rendering, raw URLs | Burn-after-read | Expiring links, password protection
Would love to know what the community thinks and if anyone else finds this useful! Happy to answer any questions.

value: Show HN: textdrop.sh – a simple tool for sharing text, Markdown, and code

author: tommyross


value: grahamannett

value:
Atrophy is an iOS self-report quiz aimed at software engineers who use LLMs heavily enough at work to wonder if they're trending toward AI over-reliance or some form of AI psychosis.
I built it because I noticed a pattern: formerly AI-skeptical coworkers now open every standup or design discussion with "I asked Claude..." or "Claude told me..." for technical problems and design decisions. I've felt the same pull myself to delegate every task or problem to AI. It's easy to lean on these tools for almost any amount of critical thinking or problem solving, and I'm worried about what it means when knowledge workers atrophy their cognition this way.
I'm not anti-AI nor do I think these models will completely replace software engineers. But as long as humans are still in the loop for software engineering, I don't have a good answer for how to avoid becoming overly reliant on these models. How do we gauge how over-reliant we've become, or maintain responsibility for the programs and systems we ship while outsourcing 90% of the judgment we used to be required to make? How do we learn what good code looks like when PR size and velocity have grown to the point that only the important parts get reviewed?
I'm hoping to work on better ways to notice this pattern and practice our way back from it. This is my first attempt (offline only, no accounts/analytics).
https://apps.apple.com/us/app/atrophy/id6765778979

value: Show HN: I made an iOS app to gauge AI over-reliance and AI psychosis

author: grahamannett


value: herrj

value: Show HN: I built Tokenyst to stop getting shocked by Claude Code API bills

author: herrj


value: marcobambini

value: Show HN: SQLite-columnar, a column-oriented analytics extension for SQLite

author: marcobambini


value: aidarbek

value: Show HN: LLM post-training to speak like GenZ, costing less than a cup of coffee

author: aidarbek