value: linster

value:
I made a Matrix chat client for my 2001 BMW infotainment system using Kotlin, Jetpack Compose, a Rasbperry Pi, and a custom PCB I designed to plug into the factory wiring harness:
https://e39.dev/hmi/Matrix/Matrix.html
I used Compose MPP cross-compiled to a Raspberry Pi (running Raspbian) to make my own Infotainment system from scratch. It works on the 2001-vintage factory BMW display with a retractable screen that has a cassette deck behind it.
I then wrote a Matrix Chat Client for the system. The only input device (no touch screen) is a rotary knob that can be pressed. The knob events are sent via the car's IBUS serial bus, which I integrated into the Compose MPP UI state https://e39.dev/hmi/WidgetFramework/KnobListener.html
I've been working on this project since January 2021, when Compose MPP was at the Milestone 2 release.
The Matrix page has a great video of the system in action on the bench-top car-surrogate I made. The homepage, https://e39.dev/, shows an overview of the whole system, and also has writeups on the other features I made, such as the Open Street Map viewer that I also made from scratch.

value: Show HN: I made a matrix chat client for my 2001 BMW's stock infotainment system

author: linster


value: lukehan

value: Show HN: Make ChatGPT Understand Your Data

author: lukehan


value: dtonon

value:
I needed to take a look at some live logs and quickly analyze some old ones, but I couldn't find anything effective to highlight terms, except for esoteric sed and awk commands.
So I built ch - Colored Highlighter - a simple terminal tool to highlight specific words in your command output with colors. Perfect for tailing logs, debugging, and making command output more readable.

value: Show HN: ch, a terminal tool to highlight specific words in your command output

author: dtonon


value:
Hi, let me introduce the document service I've been developing for about a year.
There are many document hosting services, but few prioritize interaction between developers.
I think most documentation services target general readers and aren't designed to be used by developers themselves.
dodo-doc is a documentation hosting service built for myself and fellow software engineers.
It supports the following functionalities that other documentation services don't have:
Strong CLI Tool
I'm aiming for a documentation service that can be interactively manipulated from the terminal.
You can not only upload but also search and open docs directly from the terminal.
We also have experimental support for MCP.
CI Affinity
Don't you want to preview documents on CI? I do.
You can easily set up deploy and preview flows on GitHub Actions.
Private Use
Other documentation tools may have this feature too.
But it's REQUIRED for me because I write journals in git.
Therefore, dodo-doc supports private documents out of the box.
It's easy to set up, so I'd love for you to give it a try.
I'm looking forward to your feedback!

value: Show HN: Terminal-First Documentation Service


value: Hey HN! I’m Salem, 15, and I made CrossRun — a public domain open standard that aims to make software truly cross-platform, regardless of OS, bitness, or architecture. It’s open and public domain (CC0/Unlicense). I’d love feedback, contributions, and especially critique from systems-level devs.

value: Show HN: CrossRun – An Open Standard to Make Software Run on Any Platform


value: stuehieyr

value:
I’m releasing malloc (MultiplicativeConstraint), a production-grade, open-source library for solving large, constraint-rich partitioning problems—think resource allocation, scheduling, clustering, supply chain, EDA, and HPC.
Why is this interesting?
Physics-inspired math: Uses spectral theory and heat-kernel action minimization—correlation with target objectives is ρ ≈ 0.996.
Enterprise scalability: Sparse matrix core solves 100,000-node problems in under 90 seconds with only 23MB memory.
Adaptable constraints: Neural module adapts to real-world, contradictory constraints with up to 83% satisfaction.
Key applications: Cloud resource allocation, HPC load balancing, clustering, logic optimization, graph partitioning, bin packing, and more.
Limitations: Not a general P=NP solution; works best when structural regularity exists.
Replicable results: All benchmarks, proofs (MATH.md), and performance demos are open in the repo.
Try it out:
Repo + docs: https://codeberg.org/aninokuma/malloc
README covers the API, benchmarks, and supported problems.

value: Show HN: Malloc – phy solver for constrained balanced partitioning problems

author: stuehieyr


value: motakuk

value:
Hi HN, Matvey, Ildar, Joey, and Dominik here.
If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable.
Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall.
So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against common attacks. The two core features right now are:
1) Dynamic Tool Engine: This is the key idea. Archestra restricts which tools an agent can even see or call based on the context source. If the context comes from an untrusted tool, the agent won't have access to high-privilege tools like execute_code or send_email.
2) Dual LLM Sanitization: An isolated LLM acts as a "sanitizer" for incoming data, stripping potentially malicious instructions before they're passed to the primary agent.
It’s framework-agnostic (works with LangChain, N8N, etc.), self-hostable (Kubernetes). We're just getting started and have more security features planned.
We'd love for you to take a look at the repo, try it out, and give us your feedback.
GitHub: https://github.com/archestra-ai/archestra
Docs: https://www.archestra.ai/docs/platform-dynamic-tools

value: Show HN: Open-Source Gateway to Stop Tool-Abusing Prompt Injections

author: motakuk


value: jdubansky

value:
I have been working on a simple SAST like AI code scanning tool. Currently it only uses OpenAI API to do the scanning but maybe if I get access to other APIs I can add them. There are still a lot of features I would like to add but I am building this in two parts, the CLI scanner and the web management UI.
At the moment the UI and scanner run together but eventually I want to break this out so that the scanner can just report findings to the UI remotely. This would be nice if running from a CI/CD environment. I eventually also plan to add some sort of scoping to the scanner so it can be targeted to new branches.
Posting this as maybe it will help other orgs out there that are looking for SAST and want to do it cheaply.
https://github.com/jdubansky/sassycode

value: Show HN: AI Code Scanning/SAST

author: jdubansky

title: Show HN: AI Code Scanning/SAST


value: donbox

value: Show HN: Luca, an AI agent for finance and accounting workflows

author: donbox


value:
I've been studying interval arithmetic for the past few weeks and it's a really interesting field because while there is a ton of super interesting research published over the past decades, it has never really gotten the recognition that it deserves, IMO.
One reason for this is that standard interval arithmetic has really poor handling of division by intervals containing zero. If you compute 1 / [-1, 2] in regular interval arithmetic, you get either [-∞, +∞], or you have to say that the operation is undefined. Both solutions are virtually useless. The real answer of course is [-∞, -1] U [0.5, +∞]: i.e. a union of two disjoint intervals.
This is useful because you can confidently exclude a non empty set of the real numbers ([-1, 0.5]) from the set of possible values that you can get by dividing 1 by a number between -1 and 2.
But this definition of interval division yields a value that is not an interval. This is a problem if you want to define a closed arithmetic system, where you can build and evaluate arbitrary expression over interval values.
(This behavior extends to any non continuous function like tan() for example, which is implemented in my project - not without difficulties!)
Well the obvious solution is to define your arithmetic over disjoint unions of intervals. This is the subject of a 2017 paper called "Interval Unions" by by Schichl, H., Domes, F., Montanher, T. and Kofler, K..
This open-source project I made implements interval union arithmetic in TypeScript in the form of a simple interactive calculator, so you can try it out for yourself! The underlying TypeScript library is dependency free and implements interval union arithmetic over IEEE 754 double precision floats (JS native number type) with outward rounding. This guarantees accuracy of interval results in the presence of rounding issue inherent to floating point.

value: Show HN: I made a calculator that works over disjoint sets of intervals


value: tuned

value: Show HN: Beyond geometric similarity in vector databases

author: tuned


value:
Hi HN,
I am one of the founders of Tabsdata, a new system for data integration built around publish/subscribe for tables.
Tabsdata is a self-managed system you can deploy in your own environment. It is built in Rust for performance and safety, with Python bindings for expressing data flows. You get both a browser-based UI and a CLI that covers the full surface area of the platform.
We started this project after spending nearly two decades in data integration. Over that time, we have seen the modern data stack emerge in layers: ingestion, preparation, quality, productization, and so on. Many of those layers were designed to handle semi-structured data and schema drift. But that complexity often left data teams with brittle workflows and limited visibility.
One of the key lessons for us was this: no matter how data starts out, it always turns into tables. APIs, logs, Parquet files, event streams - everything eventually lands in tabular form. So we made tables the first-class unit in the system, right from ingestion.
The second lesson was about semantics and metadata. Every layer between producer and consumer tends to dilute meaning, reshaping schemas, masking lineage, or dropping ownership context. This forces teams to build new layers just to patch over what was lost. We believe a better approach is to carry the table, its metadata, and its semantic intent all together from start to finish. Tabsdata makes that default.
Instead of stitching together ingestion, transformation, orchestration and governance, across fragmented tools and platforms, Tabsdata provides a single declarative system where producers publish, transformers enrich, and consumers subscribe. Every step is versioned and every change is explainable.
If you are curious, here is a short overview and demo we shared on Practical Data Community:
https://www.youtube.com/watch?v=qCZIRC9khmA
You can also learn more here:
https://tabsdata.com
Typical Use Cases
* Instant ETL - No jobs to schedule. Every update flows through the dependency graph immediately, so consumer-facing tables are always in sync with the latest from producers.
* Instant Lineage - Each table refresh results in a lineage graph that includes versions of inputs, outputs, and the transformations that connected them.
* Declarative DataOps - No pipelines to wrangle. Transformations are attached to tables directly, using declarative steps with clear inputs and outputs. All changes to tables are fully reproducible.
* Legacy ETL Modernization - Tabsdata maps cleanly to Informatica and Talend-style mappings. You can migrate without rewriting logic from scratch or disrupting downstream users.
What Tabsdata Is Not
* It is not a message broker or event system. You should still use Kafka, Kinesis, or equivalent if you are building real-time streaming applications.
* It is not a database or lakehouse. Tabsdata works with the data platforms you already have, delivering versioned, trusted tables into them as outputs.
We are still early and are looking for feedback. If you have dealt with pipeline sprawl, slow reconciliation, or unclear ownership across data teams, we would love to hear your perspective. What's missing? What doesn't make sense? What would make this more useful in your setup?
Best regards,
Arvind

value: Show HN: Tabsdata – Pub/Sub for Tables to Replace ETL Pipelines


value: jztan

value:
Most accessibility testing tools only scratch the surface. They flag basic WCAG issues but miss the real-world challenges users face, especially around neurodiversity, keyboard navigation, and screen readers.
TestParty.ai is a digital accessibility platform that uses AI to scan production, preview, and development environments. We support sitemap imports, user interaction steps, and end-to-end test imports so teams can validate accessibility across actual user flows — not just static pages.
We also provide screenshots, advanced rulesets, and detailed reports to help engineering and design teams move beyond checkbox compliance. The goal: make accessibility testing continuous, integrated, and useful at scale.
Would love feedback from any indie developers — what’s missing for you to always scan for accessibility and make it a no-brainer?

value: Show HN: Digital Accessibility Workflow Platform

author: jztan


value:
Hi HN,
I love building small games (as Pong, Wordle, Tetris, etc.), but they're never quite unique enough to justify their own site. So I built boring.game - a daily "boring" game where the social mechanics (predicting your score, challenging other users) is more interesting than the game itself.
I started a HN team if you want to compare your results:
https://boring.game/invite/SRhyUStjin
You can also play all daily games without signing up, if that is what you prefer.
Built with SvelteKit (first time using Svelte - loved it!). Would love feedback on both the concept and execution.

value: Show HN: I made games so boring the fun part is guessing your score


value: razcoj

value:
Hi everyone,
Like the title says, it lets you test your page and then try different optimizations (preloading stuff, inserting HTML, executing arbitrary JS, etc) on the page without making any changes to your code.
Short demo: https://youtu.be/IKSu-rv78wI
It's something I've been developing over several years, and to which I've dedicated my full time over the past 7 months or so. Let me know what you think.

value: Show HN: Page Gym - page speed analysis and optimization tool for advanced users

author: razcoj


value: danielskogly

value:
We're two founders from Tromsø, Norway who have spent the past 4,5 years bootstrapping Instorier. Everything you see here, from the editor to the runtime, we built from scratch.
Instorier is a modern website builder focused on storytelling. Out of the box it supports 3D/WebGL scenes, map journeys, and motion, with real-time collaboration and instant hosting. You can also embed Instorier stories into an existing site without a migration.
What's new now: an AI-optional onboarding flow. It helps you get started quickly, but keeps authorship yours. This isn't about generating cookie-cutter sites, it's about lowering the barrier to telling meaningful stories online.
We've found some early product-market fit in the media industry, like with Stavanger Aftenblad in Norway and Scrolli.co in Türkiye. At the same time, broader adoption has been harder. That's why we're now also exploring use cases for startups, comms teams, and agencies, while keeping the focus on what we believe makes any landing page or article succeed: engaging, meaningful storytelling.
Tech stack is Next.js and React for the service, React, Redux Toolkit, Three.js and lots of other custom JS/TS for the Editor, and the website runtime is very custom and uses Three.js for some heavy lifting.
Also we've disabled scrolljacking by default since posting here last time :)

value: Show HN: Instorier – Agency-quality, story-first websites in minutes, not weeks

author: danielskogly


value: jgimenez

value:
photocopi.es archives your Asana tasks as PDF and saves them to an S3 bucket.
I came up with the idea because I've been using Asana for a compliance project, and I needed tasks to be kept forever. Surprisingly, Asana doesn't have a way to prevent task deletion, nor an easy way to export the full content of tasks to keep them long-term in a safe place. I have been working on it on the side for a while now, and I'd like to share it with you.
At the moment, the tool can export tasks to PDF and save them to an S3 bucket, including attachments. If it gets traction, I'm planning to support more formats and storage locations. For example, I provide the storage to get started easily, and allow users to connect their own S3 bucket, Google Drive, Dropbox, etc. if they want to.
If you have an Asana account, you can try it: photocopi.es and please let me know what you think!

value: Show HN: photocopi.es - Archive your Asana projects as PDFs

author: jgimenez


value: sanketsaurav

value:
Hey HN! We're the team behind Autofix Bot (YC W20's DeepSource)[1]. We're open-sourcing Narada (https://huggingface.co/deepsource/Narada-3.2-3B-v1), a fine-tuned Llama3.2-3B-Instruct model that dramatically reduces false positives in secrets detection tools. The model achieves 97% precision with 96% recall on our evaluation set. It's fast enough for CI/CD (3B parameters), works with any regex-based tool, and is MIT-licensed.
Traditional regex-based secrets scanners (Gitleaks, TruffleHog, detect-secrets) face a fundamental tradeoff: crank up sensitivity and drown in false positives flagging things like "YOUR_API_KEY_HERE", or tune it down and miss real credentials. We kept hearing from security teams that they couldn't trust their scanning tools because of the noise – developers would just ignore the alerts.
Regex is great at fast pattern matching, but terrible at understanding context. So instead of trying to make regex smarter, we built a hybrid system: regex does the initial high-recall sweep, then a fine-tuned 3B model filters out false positives by actually understanding the code context.
Technical approach:
- Started with teacher-student architecture using DeepSeek R1 as teacher
- Curated ~8K diverse secrets from Samsung's CredData dataset, relabeled for consistency
- Generated synthetic edge cases using Gemini 2.5 Pro and Claude Sonnet 4
- Fine-tuned on ~900 examples with deterministic outputs (not chain-of-thought)
Integration is straightforward – run your existing regex tool, feed candidates to Narada with ±20 lines of context, get structured JSON output with true/false positive classification and reasoning.
We built this as part of Autofix Bot's secrets detection agent, and it outperformed static-only tools significantly in our benchmarks [2]. Figured the security community would benefit from having this available as an open-source building block. Would love to hear your feedback and learn what other edge cases you encounter.
[1] https://autofix.bot
[2] https://autofix.bot/benchmarks#benchmarks-secrets-detection
[3] https://autofix.bot/news/narada-secrets-detection-classifica...

value: Show HN: Narada – Open-source secrets classification model

author: sanketsaurav


value: denizhdzh

value:
TL;DR:
We built an embeddable AI agent that turns any website into an interactive, knowledge-driven platform. Upload PDFs or docs, and the agent answers user questions contextually. Unlike typical chatbots, it knows your visitors and can offer or show dynamic contents.
Problem:
Most websites rely on static FAQs or generic chatbots. Users leave confused, conversion rates drop, and support load grows. Traditional chatbots often require external APIs and are limited in context-awareness.
Solution:
Our On-Page AI Agent embeds directly into your website. It:
 • References PDFs, documentation, and custom content.
 • Provides contextual, personalized answers.
 • Reduces support load and increases engagement.
 • Can be styled and placed anywhere on the site.
Key Metrics / Early Results:
 • Increased trial signup rates by 25–30% for early adopters.
 • Reduced support tickets by 20%.
 • Fully self-serve deployment in under 2 minutes.
We’re looking for early testers and feedback from SaaS founders. Embed the agent on your site, share your experience, and help us improve the product.

value: Show HN: A modern and dynamic AI chatbot that converts your visitors

author: denizhdzh


value: alixwang

value: Show HN:OneImage – Free, fast, private image tools

author: alixwang


value: imbdb

value: Show HN: Browser based Battery Managment System stat reader for JBD BMSs

author: imbdb


value: I am building QueryDeck.io, a no-code way to turn your Postgres into production-ready REST APIs in minutes — and it now also auto-generates LLM tool definitions and MCP servers from your SQL. You can deploy to our cloud or export a Node.js app to run on your own infra.<p>Would love some feedback from the community!

value: Show HN: No-Code REST APIs (and LLM Tools/MCPs) for Postgres


value: killersheep

value: Take or upload a photo of yourself, then a photo of the outfit, start try-on => watch and share the result, no account required.runs entirely in the browser. Made for thrifters, second-hand lovers, and online shoppers who want to see if something fits before they click. Easy.

value: Show HN: I made trythemon.me, a simple virtual fitting room

author: killersheep


value: thomaskoopman

value: I am playing around with using arrays of arbitrary dimension as framework for designing FFT implementations, as opposed to the more classical approach of tensor products and butterflies (too complicated in my opinion).<p>It turns out, that with a modern compiler, you do not need much complexity to make a really fast implementation. This implementation is for powers of 2, and optimized for arrays that do not fit in cache. I do think it would be better to use a higher-level language to implement other cases (e.g. n = 2^a * 3^b * 5^c, multiple small FFTs, higher-dimensional), so I am currently working on getting the SaC-compiler to generate this code.

value: Show HN: FFTN, faster than FFTW in 700 lines of C

author: thomaskoopman


value: novocayn

value: Show HN: I wrote a VectorDB in Go, built for Hackers, not Hyperscalers

author: novocayn


value: riktar

value: Artiforge is a sophisticated Model Context Protocol (MCP) server. This project serves as an AI orchestration framework that provides tools for automated development task planning and AI agent role management. The system is designed to help developers create precise, actionable tasks and provide structured context for AI-powered development workflows.

value: Show HN: Artiforge – Build with AI in "easy mode"

author: riktar


value: resetmerlin

value:
Hi HN,
We’ve been working on Runtric, a small project aimed at fixing a common issue we’ve seen in programming education.
Today, with AI chatbots and endless tutorials, it’s easier than ever to start coding — but much harder to understand it deeply.
Many learners get working code, but often can’t explain why it works.
We wanted to explore whether AI could help people think more while learning, instead of just giving them answers.
That idea became Runtric — an AI-powered coding education platform where learners practice Python directly in the browser, and an AI tutor guides their reasoning step-by-step.
What you can do right now:
- Run real Python code instantly in your browser (using Pyodide, no setup or login required).
- Follow short lessons that mix text, examples, and quick practice blocks.
- Chat with an AI tutor that asks guiding questions instead of giving full solutions.
- See all progress in one continuous learning flow (lesson → code → feedback).
You can try it immediately here (no signup needed): https://runtric.com
Tech stack: Next.js, TypeScript, Pyodide (WebAssembly) for code execution, and a lightweight reasoning layer built on top of OpenAI’s API.
We’re still in the MVP stage. It’s early, and we’d really appreciate honest feedback — especially from people who teach programming, design learning tools, or remember what it was like starting out.
We’d also like to hear your thoughts on this question:
How should AI fit into programming education — as a teacher, an assistant, or just a guide?
Thanks for reading and for any feedback, suggestions, or criticism.

value: Show HN: Runtric – Learn to Code by Thinking, Not Copying AI

author: resetmerlin


value: jokera

value: Hi HN! I built AmAttractive (https://amattractive.com), a free AI-powered  beauty analysis tool that answers "How attractive am I?"

value: Show HN: AmAttractive – Free AI Beauty Analysis with No Login Required

author: jokera


value: simquat

value:
Hey HN! I'm Simone, and along with Nurie, I'm working on Breadboard[0], an app builder where the UI, logic, and data live on the same canvas. We've been exploring visual and vibe coding tools and noticed that while they are great at generating code, the text-based output can be difficult for non-technical people to understand and modify.
Our idea is to make the underlying complexity more readable by using three simple block types for Logic, Data, and UI. These blocks are then connected with cables, similar to wiring components on an electronics breadboard.
Instead of generating a wall of code, our AI assistant produces these visual blocks and connects them for you. Our goal is to make the output from LLMs more accessible and actionable for non-developers.
How it works:

    Start from the demo project[1] or a blank canvas[2].
    Add UI elements by dragging/pasting SVGs onto the canvas.
    Add Logic and Data blocks from the dock.
    Wire blocks together with cables to define behavior and data flow.
    Click "Play" to run the app preview.
    – or –
    Ask our AI rubber‑duck assistant to create and connect blocks for you (free, login required).

This is a very early preview, and we would love to get your feedback and hear your impressions.
[0] https://breadboards.io/
[1] https://app.breadboards.io/demo
[2] https://app.breadboards.io/ (login required)
Thanks

value: Show HN: Breadboard – A visual app builder on a Figma-like canvas

author: simquat


value: CreativeOn

value: Show HN: Training-free improvement of Pareto frontiers for reasoning LLMs

author: CreativeOn


value: ireliamain

value: I built a lightweight reading "platform" because I wanted to make something, both technical and creative. I've always loved writing stories, but my wife doesn't enjoy reading in English. That got me thinking about all the web novels written in other languages that I wish I could read without waiting for translations. So I started experimenting with a platform where anyone could publish community web novels and choose which languages to make available. It's not perfect, but I wanted to share teh story and the idea behind it. Hope you enjoy it

value: Show HN: A Minimalist Web Novel – Waiting for the Chamomile Tea to Get Cold

author: ireliamain


value: Agraillo

value:
This app allows reading HN comments in a novel way (at least I haven't seen anything like this before for threaded discussions). The page shows a vertical stack of comments corresponding to a single path from the story root to a leaf. Each level has a "current" sibling or child, and the gradient clickable areas at the sides of the comments allow switching between children or siblings while maintaining the correct "story-to-leaf" path. The "visit next" feature enables lazy reading of all the comments. The "tools" contains filtering queries (by last time, text search, authors), including, for example, reading comments from the last ... hours. There's a short introduction and "read more" section on the site that should cover most topics
The https://hackeray.vercel.app page requires entering either HN id or the full url. An experimental "top stories" infinite scroll page (navigating directly to the hackeray rendering) is at the https://hackeray.vercel.app/list.html. The items are sorted quasi-chronologically (by id)
Please share your thoughts. Also, the script is a single HTML/CSS/JS file that can run locally, so you can easily fix or adjust it to your own preferences. I'm not sure how many users will find this way useful, but for me personally, I can no longer read active HN discussions any other way

value: Show HN: Hackeray – novel way to read big HN discussions

author: Agraillo


value: jazeemchoori

value:
Hey everyone,
I’m Jazeem, founder of Qudemo - https://qudemo.com
I along with Sarath, built Qudemo because we realised that sharing pre-recorded demo videos on Loom or YouTube is still just a one-way video. You can see some basic stats like views and watch time, but you still don’t really know who watched, what they cared about, or if they were actually interested.
Qudemo fixes that. It turns your pre-recorded demo videos into interactive, trackable and shareable experiences. So you can finally see what happens after you hit “share.”
Here’s how it works:
* Upload or link your demo video (Loom, YouTube, etc.)
* Add your product docs, FAQs or PDFs so Qudemo’s AI can answer questions in real-time
* Share your Qudemo link anywhere - website, chat, or email
* Viewers can ask questions and get instant answers
* And when they’re convinced, they can book a meeting directly inside the qudemo
One of the biggest differences is how sharing works. With Qudemo, you can create unique links for each prospect so you instantly know who watched and how they engaged. There’s no need to ask for emails or collect form data.
Each link automatically tracks:
* Who watched the demo
* How long they stayed
* What questions they asked
* And when they booked a meeting
This helps you clearly see buyer intent. You’ll know which leads are curious, which ones are comparing, and which ones are ready to talk.
You can also create bulk unique links for outbound campaigns. Upload a list once, and Qudemo generates personalised demo links for every prospect automatically.
Most demos today end at “viewed.” Qudemo helps you go one step further — it turns demos into two-way conversations that show real interest and intent.
Instead of wondering “Did they even open it?”, you’ll know who watched, what they asked, and when they decided to talk to you.
The basic plan is free to try. If you sharing demo videos or product explainers, give it a shot - it only takes a few minutes to make your first interactive demo.
View Qudemo’s Qudemo: https://qudemo.com/share/ca6b5a1b-0764-4e1c-bf6c-3e3c5bc93d1...
Try it yourself at: https://qudemo.com
Don’t share Loom. Share Qudemo.
I would really appreciate your feedback, especially on how useful this feels for sales, product, or onboarding demos.

value: Show HN: Turn your Loom videos into interactive, trackable demos with Qudemo

author: jazeemchoori


value: mikkoim

value: Show HN: DINOtool – ViT feature extraction for images and videos

author: mikkoim


value: davidslv

value:
After 5 years of solo development, I'm opening up Vanilla Roguelike, a turn-based roguelike written in pure Ruby.
I belive it demonstrates Ruby's strengths in game dev, with procedural maze generation (algorithms like Binary Tree and Recursive Backtracker) and an ECS (Entity-Component-System) architecture for modularity.
Current state: It's a work-in-progress.
Mechanics are limited (e.g., you can move across the map, open the messages menu, transition to a new level, no full combat yet), but I believe the foundation is solid and welcoming to anyone with the desire to contribute.
GitHub: https://github.com/Davidslv/vanilla-roguelike
I'd love feedback, issues, or PRs to help evolve it even further.
Let's showcase what Ruby can do in roguelikes!

value: Show HN: Vanilla Roguelike – My 5-Year Solo Ruby Project Now OSS

author: davidslv


value: Show HN: Treat Files as Individual Repository


value: StanAngeloff

value: Show HN: Flemma – turn Neovim into a first-class AI workspace

author: StanAngeloff


value: Show HN: We've build AI Tool that detect cards from Poker Videos


value: sentientiq

value:
I built a system that detects visitor emotions in real-time from mouse telemetry - no surveys, no tracking pixels, zero PII.
The Problem:
Your analytics tell you what happened (user bounced), but not why (they were confused, frustrated, or priced out).
How it works:
- JavaScript captures mouse movements, click patterns, scroll behavior
- Emotional inference engine (Claude Sonnet) analyzes behavioral signatures
- System detects: frustration, confusion, hesitation, confidence, exit intent
- Context-aware interventions deploy in milliseconds
- Feedback loop learns from outcomes
The Stack:
- 20 microservices on EC2 (emotional inference, cross-vertical ML, intervention engine)
- NATS for real-time message streaming
- Supabase for persistence
- Rate-limited and hardened for production
What makes this different:
- No surveys (real-time behavioral inference)
- No PII (emotional states only, no identity tracking)
- Spatial awareness (interventions match page context)
- Self-improving (learns from conversion outcomes)
Demo:
Visit https://sentientiq.ai - you'll feel it working on you. The interactive demo shows what we detect.
Technical Deep Dive:
Open the browser console on https://sentientiq.ai and watch:
Telemetry stream (mouse movements, clicks, patterns)
Emotion detection (curiosity → overwhelm → confidence)
Intervention deployment (contextual responses)
Full architecture: 20 microservices, NATS streaming, Claude inference (Haiku→Sonnet escalation), rate-limited to 10 Sonnet calls/min/session. Detailed docs coming soon. Happy to answer technical questions here.
Built this solo over 6 months. Nearly died twice. Would love feedback from the HN crowd.

value: Show HN: Detect visitor emotions from mouse movements (emotional inference)

author: sentientiq


value: ephraimduncan

value: Transform ChatGPT, Claude, and Gemini text into natural, human-like writing with a single click.

value: Show HN: Make AI text sound human

author: ephraimduncan

title: Show HN: Make AI text sound human


value: jdslatermd

value:
Hi HN,
I’ve built MORPHEUS, an adaptive code security analyzer that uses a morphing neural network (“M-Net”) to detect and explain vulnerabilities in real time.
It currently supports Python and JavaScript, detects SQLi and XSS (CWE-89, CWE-79), and adapts based on false-positive feedback.
Demo: https://morpheus-security.ai
I’d love feedback from developers and security researchers on:
– Accuracy on real projects
– Ease of integrating the CLI / API
– Ideas for new detectors (Command Injection, Path Traversal next!)
Thanks!
— Jeremy Slater

value: Show HN: Morpheus – Adaptive Code Security Analyzer

author: jdslatermd


value: jakewhiteyo

value:
Hey HN,
Spotify refuses to implement webhooks in their API... so I built them.
I've frequently found myself looking for a way to build automations around new Spotify music releases. After years of having this issue I finally decided to build them myself.
New music release notifications is currently the only event trigger I support but I will be supporting new event types soon.
Hopefully you guys can find some use out of a service like this. Cant wait to see what people build :)
- Jake

value: Show HN: WebHooks for the Spotify API

author: jakewhiteyo

title: Show HN: WebHooks for the Spotify API


value: ModernMechanic

value:
Hi my name is Jordan. This was all written by hand without AI, for you? me? idk.
I know attention spans are short now, but I want to share how I want to share. If you're reading this, know it was written by a fellow human for a fellow human.
Over a year ago, I started working on Modern Mechanic after being frustrated with my Matco scanning tool that I spent over $2,000 on. I got a small amount of funding and convinced my investors to let me release it completely free. No ads, no pro version, no subscription. Just a useful tool for anyone who owns a car.
What makes it different? It was built to help you, not just translate bits.
Natural language input – describe what you're hearing, smelling, or feeling
AI-powered diagnosis that goes way beyond just reading codes
Works with ANY OBD2 reader you already own (or no reader at all) – no proprietary hardware
Supports any year/make/model – even custom builds and engine swaps
Plain English explanations, repair guides, cost estimates, and video tutorials
Access to real mechanics if you get stuck or need extra help
We'll literally find a trusted local mechanic and book a repair for you at the lowest possible price
TONS of other features
We hand built everything inhouse, including CAN bus bit parsing, which means there might be occasional bugs. But it also means we can keep it free forever.
Now I'm here and I need your help. Please support a small startup. I'm not trying to bill you monthly. I don't have a course or a program to sell you. I don't have anything that will help you get rich.
BUT if you own a car and are sick and tired of businesses that don't care about their consumers, maybe join my waitlist and help me prove you can make it by providing value to people for free.
Download/Waitlist: [modernmechanic.us]
Happy to answer any questions about the tech, the business model, or anything else. I've also done VC pitching, product design, and run a few other companies – glad to help anyone else on their startup journey.
Currently if you want to support us and get a foudners package its on the link, there is no requirement, the app will release free but it helps us fund it and you get cool perks :P

value: Show HN: The small startup with nothing to sell and everything to lose

author: ModernMechanic


value: ahmednabi

value: Show HN: Ranksmith – Google Analytics for ChatGPT and other AI search engines

author: ahmednabi


value: floatingtrees

value: Show HN: Local Full-Rank Fine-Tuning Library for LLMs with Evolutionary Methods

author: floatingtrees


value: marlongrandy

value: Dialed gives you personalized pep talks when your mind is working against you. Pre-meeting, before a date, when exhausted and need to work more, before the gym... you name it. We have all these moments where our mind tends to work against us. Dialed learns what motivates you through a feedback loop and truly flips your mindset in these moments :) open to any and all feedback ofc!

value: Show HN: Cinematic pep talks to help you overcome any obstacle

author: marlongrandy


value: waynerd

value:
I built a browser-based Mafia game where you play against AI agents that
have learned to lie, form alliances, and accuse others strategically.
The interesting technical challenge was making AIs that don't just play
optimally, but play believably – they need to seem human, make mistakes,
and have distinct personalities.
Each AI has a different play style: some are aggressive accusers, others
play defensive, and some are wildly unpredictable. They maintain consistent
backstories and remember what they said earlier in the game.
Built with React, Typescript, Nodejs...
Link: https://ai-mafia.app
Would love feedback from the community, especially on making the AI
behavior more realistic!

value: Show HN: I made an AI Mafia game where AIs try to deceive you

author: waynerd


value: sudofoo

value: Show HN: What the Font: Discover and Identify Fonts from Images

author: sudofoo


value: toyhank

value: Show HN: A client-side tool to render Gemini chat HTML into a clean image/PDF

author: toyhank


value: GuiShou

value: AI-powered photo to drawing converter. Try it free with Google login - 2 conversions included. Built with Next.js 15 + Gemini 2.5 Flash.

value: Show HN: Picture to Drawing – AI-powered photo to drawing converter

author: GuiShou


value: boringgame

value:
If you want to compare your results feel free to join the HN team. However you can also play without signing up for an account.<p>Its a SvelteKit application running on Cloudflare Workers.
Would love some feedback on the idea and execution!

value: Show HN: Wordle but you have to predict your score before playing

author: boringgame


value:
Hexecute is yet another Wayland launcher, but using gestures instead of a menu to select options!
This started as a silly project for a 10hr hacking challenge (the theme was "magic"), but the end result was a lot more usable than I expected.
Stroke recognition is performed using the $1 Unistroke Recognizer algorithm from the University of Washington.

value: Show HN: Hexecute, a gesture-based Wayland launcher


value: Show HN: Daily Clash Royale Card Guessing Game


value: gitopspm

value:
Hello everyone,
I'd like to share my open-source project Proxmox-GitOps, a Container Automation platform for provisioning and orchestrating Linux containers (LXC) on Proxmox VE - encapsulated as comprehensive Infrastructure as Code (IaC).
Proxmox-GitOps (@Github): https://github.com/stevius10/Proxmox-GitOps
- Demo (~1m): https://youtu.be/2oXDgbvFCWY
- Demo* (low, no ads): https://github.com/stevius10/Proxmox-GitOps/blob/develop/doc...
TL;DR: By encapsulating infrastructure within an extensible monorepository - recursively resolved from Git submodules at runtime - Proxmox-GitOps provides a comprehensive Infrastructure-as-Code (IaC) abstraction for an entire, automated, container-based infrastructure.
Originally, it was a personal attempt to bring industrial automation and cloud patterns to my Proxmox home server. It's designed as a platform architecture for a self-contained, bootstrappable system - a generic IaC abstraction (customize, extend, .. open standards, base package only, .. - you name it ) that automates the entire infrastructure. It was initially driven by the question of what a Proxmox-based GitOps automation could look like and how it could be organized.
Core Concepts
- Recursive Self-management: Control plane seeds itself by pushing its monorepository onto a locally bootstrapped instance, triggering a pipeline that recursively provisions the control plane onto PVE.
- Monorepository: Centralizes infrastructure as comprehensive IaC artifact (for mirroring, like the project itself on Github) using submodules for modular composition.
- Git as State: Git repository represents the desired infrastructure state.
- Loose coupling: Containers are decoupled from the control plane, enabling runtime replacement and independent operation.
Over the past few months, the project stabilized, and I’ve addressed many questions you had in Wiki, summarized to documentation, which should now covers essential technical, conceptual, and practical aspects. I’ve also added a short demo that breaks down the theory by demonstrating the automation of an IaC stack (Home Assistant, Mosquitto bridge, Zigbee2MQTT broker, snapshot restore, reverse proxy, dynamically configured via PVE API), with automated container system updates and service checks.
What am I looking for?
It's a noncommercial, passion-driven project. I'm looking to collaborate with other engineers who share the excitement of building a self-contained, bootstrappable platform architecture that addresses the question: What should our home automation look like?
I'd love to hear your thoughts!

value: Show HN: Proxmox-GitOps: Recursive IaC Container Automation (+1min Demo [video]

author: gitopspm


value: protontypes

value: Show HN: Good First Line – Map Your First Transmission Line

author: protontypes


value: kangbit

value:
Hi HN! I built a React component that makes it easy to use the Document Picture-in-Picture API.
Unlike the traditional video PiP, Document Picture-in-Picture lets you put any HTML content in an always-on-top floating window.
Package: https://www.npmjs.com/package/react-document-pip
This library uses the Document Picture-in-Picture API, which is currently supported in:
- Chrome 116+
- Edge 116+
- Opera 102+

value: Show HN: NPM package for React Document Picture in Picture(PIP)

author: kangbit


value:
Ark is a high-performance Entity Component System (ECS) library for Go.
Ark v0.6.0 introduces a new event system built around lightweight, composable observers. These allow applications to react to ECS lifecycle changes like entity creation/removal, component updates, relation changes using declarative filters and callbacks. Observers follow the same patterns as Ark’s query system, making them easy to integrate and reason about.
Custom events are also supported. They can be emitted manually and observed with the same filtering logic, making them ideal for modeling domain-specific interactions such as input handling, and other reactive game logic.
As a new performance-related feature, filters and queries are now concurrency-safe and can be executed in parallel.
This release also includes a load of performance improvements,
from faster archetype switching over optimized query and table creation to improved performance of bitmask operations.
The new World.Shrink method helps reclaim unused memory in dynamic workloads.
Docs have been expanded with a full guide to the event system, examples for both built-in and custom events, and an Ebiten integration example. A cheat sheet for common operations has been added. Finally, Ark now has 100% test coverage.
Changelog: https://github.com/mlange-42/ark/blob/main/CHANGELOG.md
Repo: https://github.com/mlange-42/ark
Would love feedback from anyone building games, simulations, or ECS tooling in Go.

value: Show HN: Ark v0.6.0 – Go ECS with new declarative event system


value: feskk

value: Show HN: AI visuals that feel the music

author: feskk

title: Show HN: AI visuals that feel the music


value: bigmacfive

value:
Hey HN,
I'm Minkyu Lee, co-founder of Snapdeck — https://www.snapdeck.app
I’m a founder from Seoul, South Korea
We built Snapdeck because we got tired of spending hours in Keynote or Google Slides tweaking layouts that AI could fix in seconds.
Now you can just describe your idea, and Snapdeck generates an entire presentation — designed, formatted, and ready to present.
How it works:
- You type a short prompt like “Pitch deck for a coffee startup that focuses on sustainability”
- Snapdeck builds a clean, minimal slide deck (titles, visuals, charts, and theme included)
- You can edit anything — layouts, charts, images — right inside the app
- Export as PDF (and soon PPTX)
Why we built it:
As designers and founders, we realized slides haven’t evolved since PowerPoint 2003.
Everything is still manual — but storytelling shouldn’t be.
We wanted a tool that could think visually, not just fill text into templates.
Tech stack:
We’re using a combination of open-source LLMs and custom layout agents.
Each “agent” decides how to visualize your content — from layout to color to typography.
The orchestration layer is modular, and we’re exploring open-sourcing parts of it soon.
What we learned so far:
- People love fast iteration. Designers use it to brainstorm, not just to finish.
- Most users don’t want to design — they just want to express ideas visually.
- The hardest part isn’t the AI — it’s making users trust that AI can design tastefully.
We’d love your feedback.
Try it here → https://www.snapdeck.app
If you want to dig into how we’re handling layout generation or multi-agent orchestration, I’m happy to share details in the comments.
Thanks for reading — and thanks to the HN community for the endless inspiration.

value: Show HN: Snapdeck – Generating presentation design, not templates

author: bigmacfive


value: wainguo

value:
The one-day journey
Morning:
I wrote down the idea — “resize multiple images in bulk, no upload”
Evening:
I deployed it, registered a domain, added PWA support so users can “install” it on desktop,
and pushed it live: https://bulkresizeimages.online/
The entire flow — idea → refine → code → deploy → domain → launch — took about 12 hours.
Building it reminded me how fast you can move when you keep things simple and focus.
now its launched on https://www.producthunt.com/products/bulkresizeimage-online

value: Show HN: I built Bulk Resize Images Online in one day

author: wainguo


value:
Title says it all, you can make a flowchart and run it in your browser. I hated it in school when we were just drawing these on a piece of paper.. Only later when we started with Pascal it kinda clicked to me.
It is mostly intended for teaching basics of programming. Used in lots of schools all around the world. Gets around 500 daily users.
There is a series of interactive tutorials: https://flowrun.io/tutorials
Also a free ebook: https://leanpub.com/learnprogrammingwithflowrun
Editor is open source: https://github.com/sacode387/FlowRun
Supports debugging, custom functions and recursion even.
This is an alternative to Flowgorithm, which only works on Windows.

value: Show HN: Runnable Flowcharts for the Web


value: teotran

value:
I built a super fast, no-login daily bingo-style quiz:
• Basketball Bingo – match players to intersecting hints (team combos, awards, stat feats) while a 40-player queue ticks down.
• Pokémon Bingo – similar idea with abilities/types/stats.
It loads instantly, one new board per day. Feedback on difficulty, mobile feel, and edge-case correctness would help a ton.
Hub: https://www.bballbingo.com/?utm_source=hn&utm_medium=post&ut...
Direct: NBA /pokemon links in comments.

value: Show HN: Daily NBA and Pokémon bingo – 4×4, no login, speed-run trivia

author: teotran


value: SamTinnerholm

value:
Hey HN,
We built qoery because we were tired of downloading CSVs from the World Bank, Eurostat, OECD, and a dozen other portals every time we needed a simple statistic.
Now you can just ask "What's France's GDP growth rate?" and get structured data back instantly. We've indexed 50M observations from ~10K sources into a single queryable interface.
The technical challenge was less about NLP and more about normalizing incredibly messy data. Every source has different formats, naming conventions, and methodologies. Figuring out which "GDP" you actually mean when there are 47 different series is harder than it sounds.
We're currently focused on economic and demographic data. Free tier is 250 queries/month if you want to try it out.
Curious what statistics you find yourself constantly needing but having to hunt down manually. That's what we're prioritizing next.
Code HN50 for 50% off for three months.

value: Show HN: Query 50M statistics in plain English

author: SamTinnerholm


value: ZelinW

value:
Hi HN — I’m building Elenvo.ai, a lightweight AI assistant that helps individuals and families turn money questions into an actionable plan.
www.atom14.ai is nightly update url.
What you can try (MVP)
Enter a goal (e.g., “401(k) rollover”, “Invest $100k”, “Build a term-life plan”).
Get a concise, step-by-step plan you can refine interactively.
No credit card; minimal friction to test.
Looking for feedback
Is onboarding clear in under 3 minutes?
Does the plan feel trustworthy and specific enough?
Biggest blockers / confusing copy / missing steps?
What would you want to see next?
Join the testers (Nightly Update cadence)
Slack: https://join.slack.com/t/elenvoai/shared_invite/zt-3fn5cpu9h...
Discord: https://discord.gg/yDvPed6c

value: Show HN: Elenvo.ai – AI planning for personal finance (MVP; feedback welcome)

author: ZelinW


value: DavisGrainger

value:
I’ve been working on Datalis, a platform that supplies consent-verified, anonymised demographic and location datasets for AI teams.
These datasets are built for fairness benchmarking, bias testing, and model robustness evaluation — all aggregated, no PII, no scraping. Each panel combines regional demographic data (age, gender, income, education, occupation) with geographic context to help labs test model outputs across diverse populations.
We’ve just opened a free 30-day pilot for startups, researchers, and AI teams who want to run evaluations using real, ethical ground-truth data. CSV and Parquet formats are available (US + AU regions to start).
I’d love feedback from anyone working on model evaluation, bias detection, or Responsible AI — especially what additional fields or formats would make this most useful.
https://datalis.app/pilot

value: Show HN: Ethical demographic and location datasets for AI fairness (free pilot)

author: DavisGrainger


value: joalavedra

value: Show HN: Open-source wallet key management

author: joalavedra


value: totaa

value:
I've always been super curious how small language models model information and how accurate they really are. So I've created mindworld.space - a Llama-based Wikipedia where there is no search, and content is only traversed from other content.
Unlike most AI tools, hallucinations are encouraged (for fun). The model used is Llama 3.2 1B, which is 8x smaller than English Wikipedia, so it's not going to perfectly recite information.
Keen to hear your thoughts and what entities you can find, and any funny inaccuracies (i.e. Albert Einstein was married to Marie Curie).
Behind the scenes, I built it in a few hours using OpenRouter and SQLite, with no advanced features (such as entity de-duplication). Will open source over the next few days)
Mandatory Warning: It is inaccurate and just for fun.

value: Show HN: Mindworld.space – A Hallunicationary Wikipedia

author: totaa


value: Looking for early adopters and feedbacks

value: Show HN: Vance – World's First AI Superconnector


value: EntropyRaider

value:
Empire Technologies LLC — Prior Art Flag (One-Time Publication)
Email: Empire.Technology@proton.me
We are releasing prior art documentation for a proprietary, real-world file compressor built by Empire Technologies LLC.
This system is not theoretical, benchmark-tuned, or optimized for small files. It was engineered for extremely large, high-entropy real-world data, and delivers major compression gains that are measurable, repeatable, and already in operation.
Claim
This is a prior public disclosure of capabilities and performance, to prevent future IP conflicts and establish existence. The compressor:
Is a custom file-agnostic universal compressor
Uses no GPU or hardware acceleration (CPU only)
Targets gigabyte → terabyte raw files (not synthetic toy datasets)
Achieves consistently measurable compression ratios on hard targets
Outputs fully decompressible results with full bit-matching (SHA-256)
Is real and independently testable
Verified Cryptographic Exhibits (select, timestamped)
ECC = Empire Compressed Container (public, neutral label replacing internal extension names). Each exhibit below corresponds to a file pair recorded in Empire timestamp manifests / Proof Pack (anchor: 2025-09-18) and is verifiable by SHA-256 and the recorded timestamps.
test_large_rebuild.bin → ECC
10,485,760 bytes → 41,180 bytes — 99.607% reduction (≈254.6×)
SHA-256 (orig): dc248188b5d92e9f6538f43aa3b6d248d41bb3cd20a1a0c44c1fcfba5df7d06e
SHA-256 (comp): 6cf64fc57004de5b588c274ddf7468e8c9e4a324e388257c9b45f8a77e093fe5
logs_2gb.txt → ECC
2,147,483,648 bytes → 8,429,071 bytes — 99.607% reduction (≈254.7×)
SHA-256 (orig): a7c744c13cc101ed66c29f672f92455547889cc586ce6d44fe76ae824958ea51
SHA-256 (comp): 2025a39d56e2c0ce92a66b466580d7a74591aafd907acc3409189d27aff7cec4
ai_model_2gb.safetensors → ECC
2,147,483,648 bytes → 6,322,575 bytes — 99.71% reduction (≈339.7×)
(SHA-256 orig/comp recorded in Proof Pack manifests)
title.basics.tsv → ECC
1,028,297,196 bytes → 336,963,580 bytes — reduction verified
SHA-256 (orig): 9b08efac9f39f1362d839a20b900200c63a79ec048aed1083f4b9db5a7d542e4
SHA-256 (comp): a53f0036f9deee3467f65983ed441f241942222453357bfdd4ab87fe8af11c79
GDELT_Full_Size_File_6.427GB → ECC reduced
6,581,409,407 bytes → 1,918,387,416 bytes — ~71.69% reduction
SHA-256 (orig): 515c11ef23eb1d261cf9da3e2c0e323d22f7db07e41cd1545570407008de1812
SHA-256 (comp): 98477ad0b84ee556519022473850f6ee63f6c3af675a5a6338fea0f780d8a849
Full Proof Pack JSONs and MASTER_PROOF are retained by Empire Technologies LLC and may be provided under NDA. The entries above are the minimal cryptographic anchors for public verification.
Consumer Rig Throughput Exhibit
Single NVMe lane sustained ~2.1 GB/s. Dual NVMe lanes sustained ~3.8 GB/s on a 95 GB continuous payload, with recorded peak spikes near 24 GB/s in isolated runs. I/O starvation, not compute limits, was observed. These consumer-rig runs produced the same ultra-collapse behavior on 2 GB-class inputs (254×–339×; 99.60%–99.71% reduction). See Proof Pack speed manifests for telemetry.
Minimal Verification Steps
Compute SHA-256 of original and ECC outputs
Windows PowerShell:
Get-FileHash -Algorithm SHA256 C:\path\to\file
Linux/macOS:
sha256sum /path/to/file
Compare with hashes listed above.
Decompress using Empire decompressor in sandbox:
empire_decompress -i ECC_file -o recovered_file
Then verify:
sha256sum recovered_file (must equal SHA-256(original))
Timestamp linkage: Proof Pack JSON manifests contain matching SHA-256 values with timestamp marker 2025-09-18. Public posting date establishes external publication timestamp.
This is a single publication event. No further clarification will be issued.
Empire Technologies LLC — End of notice.

value: Show HN: Empire Compression – 2GB → 8MB (99.6% SHA-Verified, CPU Only)

author: EntropyRaider


value:
A major update to the InfiniDesk Mac app is released today.
InfiniDesk lets you have multiple desktops on Mac. Perfect for visual people who work a lot from the desktop.
Version 2 lets you set different wallpapers for different desktops, and it can also change the desktop contents when you change the Space in Mission Control.
(It finally makes Mission Control behave like true virtual desktops; something Apple never implemented.)
Free trial of 100 desktop switches, $12.99 one-time purchase if you like it.
Original post on HN here:
https://news.ycombinator.com/item?id=44412165

value: Show HN: InfiniDesk 2 – Multiple Desktops on Mac (+ Mission Control Integration)


value: infernusreal

value:
I’m a 16-year-old independent engineer from Pakistan.
I built *Council of Lords*, an AI ensemble that detected every confirmed exoplanet in the real Kepler & TESS datasets with zero false positives.
It was my NASA Space Apps 2025 submission — now I’m releasing the public version for testing, feedback, and collaboration.
*Live Project:* https://www.infernusreal.com/projects/council-of-lords
 *Join our R&D Discord:* https://discord.gg/n7KAd8MCc2
Would love thoughts from AI engineers, astrophysicists, and founders on scaling, visualization, and real-time detection pipelines.

value: Show HN: 16-year-old built a NASA-grade AI ensemble detecting real exoplanets

author: infernusreal


value:
IMPORTANT NOTE - READ FIRST:
This is still a work-in-progress and a close-source project (This is what a honeypot would look like). To view the open source MVP version see [here](https://github.com/positive-intentions/chat). NONE of my projects have been audited or reviewed. I provide them for testing and demo purposes only. NOT to replace your current messaging app (or any other app you use).
BE RESPONSIBLE WHEN USING UNAUDITED SOFTWARE... DO NOT USE FOR SENSITIVE PURPOSES.
---
Now that I've hit you over the head with caution...
Want to send encrypted WebRTC messages and video calls with no downloads, no sign-ups and no tracking?
This prototype uses WebRTC to establish an encrypted browser-to-browser connection. Everything is ephemeral and cleared when you refresh the page - true zerodata privacy!
Check out the pre-release demo.
- Demo: https://p2p.positive-intentions.com/iframe.html?globals=&id=...
- Website: https://positive-intentions.com
- Mastodon: https://infosec.exchange/@xoron

value: Show HN: P2P WhatsApp Clone

title: Show HN: P2P WhatsApp Clone


value: jeroenjanssens

value: I wanted to share with you a cheatsheet I made for Plotnine, a data visualization package for Python.<p>I've probably never spent so much time on just two pages, even with the ggplot2 cheatsheet as a starting point. Hope you find it useful.

value: Show HN: Plotnine Cheatsheet [pdf]

author: jeroenjanssens

title: Show HN: Plotnine Cheatsheet [pdf]


value: vtaya

value:
Hey HN! Like many of you, I've built the same search infrastructure multiple times: Elasticsearch for keywords, Pinecone for vectors, Redis for recent items, and a mess of Python trying to merge results.
The pattern we all know:
python# Sound familiar?
keyword_results = elasticsearch.search(query)
vector_results = pinecone.query(embedding)
recent_results = redis.get_recent()
# ...200 lines of merge logic, score normalization, dedup
After building this three times at different companies, we decided to combine everything into one API. Not revolutionary, just practical - handle keyword matching, semantic search, and recency scoring without the orchestration layer.
Example with "ORA-12545 error from last week":
The system recognizes "ORA-12545" needs exact matching (keyword), understands "error" conceptually (semantic), boosts recent results (temporal), and returns a single unified response.
Some numbers from testing on Oracle docs (47GB):
Traditional stack: 2-3 days to set up, 320ms latency, 3+ services to maintain, ~$400/month for ES + Pinecone + compute.
Our approach: 5 minute setup, 180ms latency, 1 API endpoint, ~$200/month all-in.
Trade-offs we made:
Simpler config (just weight ratios) vs full control
English-only initially
100GB limit per index
No graph relationships
The interesting bit: most teams don't actually need to tune BM25 parameters or vector similarity metrics. They just want search that works for their domain.
What's not obvious until you run multiple search systems:
Keeping Elasticsearch and Pinecone in sync is a constant headache
When search fails, debugging across three systems takes hours
The merge logic becomes more complex than your actual application
Questions for the community:
What's your current search stack looking like?
Is maintaining multiple systems worth the flexibility?
What search problems are still unsolved for you?
Happy to share more technical details. We put up a demo at coderswap.ai if anyone wants to try it with their edge-case documents.
What's been your experience combining keyword and vector search? Are you running multiple systems or found a better way?

value: Show HN: Single API for keyword and semantic and recency (no more duct-tape)

author: vtaya


value: artemlive

value:
Hey HN! I'm Artem, an SRE with 15 years of experience managing production systems.
I built Upty after getting frustrated with expensive status page tools like Statuspage.io. I needed something simpler and cheaper for my side projects, so I spent the last few weeks building this. I needed something simpler and cheaper for my side projects, so I spent the last few weeks building this.
What it does: Upty is a status page tool with automated health check monitoring. You add your services as components, configure HTTP health checks with customizable intervals and thresholds, and it automatically updates your public status page when things go down. It also handles manual incident management, webhooks, and has a REST API.
It's built with Go + MySQL and runs fast. Currently free to use while in beta.
It's in early beta and likely has bugs, but the core features work. I'd love feedback on what's missing or what doesn't make sense. No signup required to view the demo at status.upty.dev
Technical details: Multi-tenant with subdomain isolation, configurable downtime thresholds, 30-day uptime visualization, RSS feeds, incoming webhooks, HTTP health checks, and API access.
Built by someone who's been paged at 3am too many times

value: Show HN: Upty – Status pages with automated health checks

author: artemlive


value: freespirt

value:
Most people think they’re independent. The data says otherwise.
I spent months researching how AI is fragmenting into three incompatible ecosystems - American, European, and Chinese - and built an interactive quiz to show where you fit.
Your smartphone, cloud storage, payment apps, even your values about privacy - they all point toward one sphere. By 2030, these systems may become so different that moving between them becomes nearly impossible.
The quiz takes 3 minutes, asks 12 questions, and gives you personalized insights about your AI dependencies and what you can do about them.
47% of people who’ve taken it were surprised by their results. Happy to discuss the research behind it in the comments.

value: Show HN: Interactive tool showing which AI ecosystem controls your digital life

author: freespirt


value: danielvigueras

value:
I’ve always loved how PaaS platforms like Fly.io or Heroku make deploying apps super easy. However, the problem is that once you need more resources, costs skyrocket. That’s what gave me the idea to build something that feels like a PaaS but runs on managed Kubernetes instead.
I’ve been working on this as a side project for the past two years, and I've just launched it. I’m now working on it full-time.
It’s a CLI tool that lets you deploy your app to Kubernetes using just one simple config file (TOML). You can create clusters, set up processes, environment variables, resource limits, autoscaling, check logs, and more, all from the CLI.
Right now, it works with DigitalOcean and Scaleway, but I’ll be adding more providers over time.
I just got my first customers on it, and I’d love to hear what you think. Any feedback is really appreciated!

value: Show HN: I built a tool to make Kubernetes feel like a PaaS

author: danielvigueras


value: Mistri

value: Show HN: Wordle-Style Daily Wikipedia Game

author: Mistri


value: taherchhabra

value:
one-off image/video generation is easy, but creating a cohesive story with consistent characters and locations across multiple scenes is difficult.
So I am building flickspeed.ai which provides a infinite canvas with image/video/audio nodes where you can create base characters and then use it across multiple scenes. there is also an agent which assist in writing prompts
Feedback, bugs, and suggestions are all welcome.

value: Show HN: Infinite canvas for AI media generation

author: taherchhabra


value:
Hey everyone!
Wanted to share a new project I'm working on and hoping to get some beta users for it. We're building a full on AI slackbot that has full control over a project management tool. So as work is happening in Slack you can tag it with something like 'hey @thepm can you create a task for this?" and it will create a task, add relevant detials from the slack conversation and link to it directly in the web app.
we made it because our slack is full of threads with things that need to get done but no one really follows up on them. we want to build a real AI project manager and can create tasks, assign work, make updates, and overall help manage work.
It's still early stages but our slackbot is currently working and creating, updating, and assigning tasks.
So if you work in slack and struggle with task management as much as we do, hit me up and i'll hook you up with a free account in exchange for some feedback!

value: Show HN

title: Show HN


value:
I built MCPulse, an open-source analytics platform for MCP servers.
MCPulse provides:
Real-time tracking of tool calls, performance, and errors
Self-hosted with automatic parameter sanitization
Built on Go + TimescaleDB
SDKs for Python and Go and a proxy for running other's MCP servers

value: Show HN: MCPulse: Open-source analytics and observability for MCP servers


value: ericcurtin

value:
Hey Hacker News,
We're the maintainers of docker/model-runner and wanted to share some major updates we're excited about.
Link: https://github.com/docker/model-runner
We are rebooting the community:
https://www.docker.com/blog/rebooting-model-runner-community...
At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any improvements we make back upstream to their project. It also allows people to transport models via OCI registries like Docker Hub. Docker Hub hosts our curated local AI model collection, packaged as OCI Artifacts and ready to run. You can easily download, share, and upload models on Docker Hub, making it a central hub for both containerized applications and the next wave of generative AI.
We've been working hard on a few things recently:
- Vulkan and AMD Support: We've just merged support for Vulkan, which opens up local inference to a much wider range of GPUs, especially from AMD.
- Contributor Experience: We refactored the project into a monorepo. The main goal was to make the architecture clearer and dramatically lower the barrier for new contributors to get involved and understand the codebase.
- It's Fully Open Source: We know that a project from Docker might raise questions about its openness. To be clear, this is a 100% open-source, Apache 2.0 licensed project. We want to build a community around it and welcome all contributions, from documentation fixes to new model backends.
- DGX Spark day-0 support, we've got it!
Our goal is to grow the community. We'll be here all day to answer any questions you have. We'd love for you to check it out, give us a star if you like it, and let us know what you think.
Thanks!

value: Show HN: docker/model-runner – an open-source tool for local LLMs

author: ericcurtin


value: Color.ag detects your question’s category and intent, matches it to the most relevant benchmark, and routes it to the top-performing AI models to ensure you get the best answer to your question. The AI models answers are then combined into a consensus summary for the smartest, most balanced response. No need to keep up with the latest models all the time! See the top 3 AI answers for your question and get consensus on them.

value: Show HN: Color – first smart AI aggregator


value: tpae

value:
Hi everyone — after building Osaurus (local AI server for Apple Silicon), I made something smaller that I actually use every day.
Tweaks lets you instantly rewrite or refine any text you copy — no chat window, no switching apps.
Just Copy → Tweak.
• macOS, Apple Silicon only
• 2 MB binary
• Runs locally through Osaurus
• Open source (MIT)
• Custom prompts and quick actions (Ctrl + T)
Would love feedback, especially from people using local LLMs or building native macOS tools.

value: Show HN: Tweaks – Copy → Tweak – 2 MB macOS AI Clipboard App (MIT License)

author: tpae


value:
Hi HN!
I built SnapKeeps, a minimalist iOS app that holds your photos and screenshots temporarily — then lets them go.
You can use it for:
– Saving quick notes, hotel room numbers, schedules
– OCR to extract text from screenshots
– Keeping your main album clean
– Letting go of unneeded images after 12h to 30d
No cloud. No account. Everything stays local.
This app is part of my personal project, OS Yamato, a suite of tools exploring ephemeral data and calm UX.
If you have any feedback or ideas, I’d love to hear from you — feel free to reply here or reach out!

value: Show HN: SnapKeeps(iOSApp)– A photo app that forgets for you


value: AznHisoka

value:
For the past 4 years, I've been tracking the install counts of AI coding extensions in the Visual Studio Code marketplace (GitHub Copilot, Claude Code, OpenAI Codex, etc.)
Today, I built an interactive dashboard that lets you see daily install counts for any of them over time.
The chart shows GitHub Copilot by default, and you can overlay or swap in any of the other 20+ tools to compare. You can also see important dates in each tool's history (pricing changes, major releases, etc.) and how daily installs changed around those dates.
Important caveats:
1) This only tracks VS Code extension installs, not CLI usage or other IDEs like JetBrains.
2) Cursor isn't included since it's a standalone editor (VS Code fork), not a marketplace extension. I added a second chart showing Cursor discussion forum activity as a proxy for its growth.
Obviously not apples to apples, but felt I needed to measure Cursor's growth somehow.
3) This tracks daily installs per day, NOT total installs. Otherwise the charts would be boring and always go to the top and right.
4) The dashboard was coded using an AI coding assistant too. I used regular Claude :)

value: Show HN: Daily install trends of AI coding extensions in VS Code

author: AznHisoka


value: xeonproc

value:
I’m an infosec engineer who noticed a gap in our data loss prevention (DLP) stack: nothing stopped employees from pasting sensitive data—PII, PHI, API keys, passwords—into GenAI tools like ChatGPT. With AI adoption skyrocketing, this felt like a growing risk for compliance and security breaches.
I built a browser extension called PromptShield to tackle this. It scans inputs in real-time and blocks 150+ sensitive data types (e.g., credit card numbers, SSNs, credentials) before they reach AI platforms. It runs locally on Chrome/Edge, with regex-based detection and minimal latency. No data leaves the client, addressing privacy concerns. Comptetes with other DLP solutions but is lightweight, easy to install and purposefully made for GenAI.
https://promptshield.cloud/
The backend is a Python Flask API that uses regex and DLP APIs for data analysis. The browser extension interfaces with the DOM, intercepts inputs, and queries the API. Based on sensitivity settings, it either blocks, warns, or allows the input to proceed.
After months of grinding, we just landed our first enterprise customer, which validated the problem for me. But I’m curious about the broader landscape:
Have others seen GenAI-related data leaks in their orgs? What’s the scale of this issue? How are you approaching shadow AI at least at the browser level?
For those building security tools, how do you balance usability vs. strict enforcement in enterprise settings (prevent vs detect)?
Any lessons on going from 1 to 10 customers? Our first took ages, but trials are picking up.

value: Show HN: Blocking Sensitive Data Leaks to GenAI Tools – A Browser Extension

author: xeonproc


value: maezeller

value:
Hey HN!
I built Bite Genie because I always find myself snapping photos of cocktail menus, hoping to later recreate them at home, but knowing those photos would just get lost in my camera roll. I wondered if there was an app to turn menu photos into actual recipes I could make. There wasn't, so I built it.
# What it does
Take a photo of any restaurant menu item → get a detailed recipe
Save recipes from any website
Remix recipes for different diets (coming soon)
Create personalized recipe cards
# Technical approach:
The menu-to-recipe pipeline uses a multi-stage approach:
Vision + OCR: Azure Computer Vision API for OCR extraction, combined with GPT-4o for visual context (plating, garnishes, presentation details that text alone misses). The dual approach handles both clean printed menus and photographed dishes better than vision-only.
Recipe generation: Claude 3.5 Sonnet for detailed recipe creation - I found it produces more reliable cooking instructions and better handles culinary terminology than GPT-4.
Ingredient extraction: Custom NER (Named Entity Recognition) model fine-tuned on ~50k recipes to parse and normalize ingredients into structured data (quantity, unit, ingredient, preparation). This enables smart substitutions and dietary adaptations.
Recipe remixing: RAG-based approach with a vector DB of ingredient substitutions and culinary techniques, so "make this vegan" actually understands what needs to change and why.
The biggest technical challenge was handling ambiguous menu descriptions. "Pan-seared salmon with lemon butter" could be executed a dozen ways. I use confidence scoring and generate multiple recipe variations, then rank them based on technique complexity and ingredient availability.
# Current limitations
- Fancy handwritten menus can be hit or miss (OCR struggles)
- Complex molecular gastronomy techniques are sometimes oversimplified
- Non-Western cuisines need more training data (working on this)
- Cocktails with house-made ingredients/infusions require some guesswork
Free to use. No paywall on core features.
Happy to answer technical questions or hear feedback on the approach!

value: Show HN: Bite Genie – Turn restaurant menu photos into recipes with AI

author: maezeller


value: elitan

value: Show HN: Velo – Git-like branching for PostgreSQL databases using ZFS snapshots

author: elitan


value: I made a parody of Wordle called Hardle. You only get one guess, so it’s basically impossible — but fun to try. Built just for laughs and frustration :)

value: Show HN: Hardle – A Wordle parody where you only get one guess


value: eummm

value: Show HN: AI Chat Watch – analyze what AI say about brands

author: eummm


value: Krei-se

value:
Link to Editor: https://krei.se/Editor/fourDEditor
left, middle and right mouse buttons + mouse movement does stuff, space adds/removes vertices.
Editor is very early, still: Enjoy!

value: Show HN: Real 4D Editor [video]

author: Krei-se

title: Show HN: Real 4D Editor [video]


value: resill

value: Turning a Chromecast, and a bit of Linux tinkering into couch-gaming for two, uh, three

value: Show HN: Chromecast Gaming (2024)

author: resill

title: Show HN: Chromecast Gaming (2024)


value: thiagoas

value:
Hey HN!
I built Outspeak to be the freest and most versatile AI video tool out there, so you can create any AI Avatar and/or Lip-synced video you can think of.
We have our own personalized Lip-syncing and Avatar creation inference pipelines which we fine-tuned to have the best balance of speed, quality and cost.
Would love to hear your feedback and suggestions :)

value: Show HN: Realistic and versatile Video Lip-syncing

author: thiagoas


value: durron

value: Show HN: Ship of Theseus CLI

author: durron

title: Show HN: Ship of Theseus CLI


value: orispok

value:
I built a small game called MemoSing that helps improve memory in a fun, light way using popular song.
Would love any feedback or ideas for improvement.
iOS: https://apps.apple.com/il/app/memosing/id6752802461
Android: https://play.google.com/store/apps/details?id=com.osg.memosi...

value: Show HN: MemoSing – a memory game powered by music

author: orispok


value: Show HN: Snapdom V2 Beta – Capture and modify DOM to multiple formats on-the-fly


value: shuvrokhan

value:
I built ExtremeFitness.app to solve a problem I’ve seen many trainers face: managing client workouts and diet plans across messy spreadsheets, PDFs, and chat messages.
A while ago, my wife and I were both following structured fitness and nutrition plans, and I noticed how difficult it was for our trainer to keep everything organized — especially when adjusting workouts or calories week by week. That’s what sparked the idea.
I wanted to create a simple tool that lets trainers create, update, and share plans effortlessly, while still keeping the human touch that coaching needs. The app includes a built-in exercise and diet library, along with AI suggestions to help trainers personalize routines faster.
It’s just me building this so far, and I’d love your thoughts — especially from anyone who trains clients or works in health tech. Does this seem genuinely helpful? What would make it better?
To take a quick look: https://extremefitness.app
Thanks for taking a look.

value: Show HN: I built ExtremeFitness.app for gym trainers

author: shuvrokhan


value: shadowy-pycoder

value: Show HN: GoHPTS-TCP/UDP Transparent Proxy with ARP Spoofing and Traffic Sniffing

author: shadowy-pycoder


value: cagdi

value:
I built a Mac app that lets you send emails without opening your inbox. A global hotkey summons a composer, you write and send through Gmail API, then it closes. No inbox view at all.
The problem I'm solving: Context switching to Gmail for a quick send inevitably means encountering unread counts, urgent flags, and newsletters. What should be a 30-second task becomes a 20-minute detour.
Instead of opening a full inbox, you:
- Compose and send (simple)
- have a 5-second unsend delay before actual transmission
Sent emails appear in your actual Gmail Sent folder of course.
Current state: Gmail works reliably via OAuth. Will work on Outlook and IMAP support for Fastmail/custom domains next if the demand is there (plus a few other features).
I am looking for 100 early supporters! Would love your feedback!
https://ckdml.com/zend

value: Show HN: Send-only email client for Mac (Gmail support)

author: cagdi


value: tobihrbr

value:
Hey HN! We're Wen and Tobias, and we're building Metorial (https://metorial.com), an integration platform that connects AI agents to external tools and data using MCP.
The Problem: While MCP works great locally (e.g., Cursor or Claude Desktop), server-side deployments are painful. Running MCP servers means managing Docker configs, per-user OAuth flows, scaling concurrent sessions, and building observability from scratch. This infrastructure work turns simple integrations into weeks of setup.
Metorial handles all of this automatically. We maintain an open catalog of ~600 MCP servers (GitHub, Slack, Google Drive, Salesforce, databases, etc.) that you can deploy in three clicks. You can also bring your own MCP server or fork existing ones.
For OAuth, just provide your client ID and secret and we handle the entire flow, including token refresh. Each user then gets an isolated MCP server instance configured with their own OAuth credentials automatically.
What makes us different is that our serverless runtime hibernates idle MCP servers and resumes them with sub-second cold starts while preserving the state and connection. Our custom MCP engine is capable of managing thousands of concurrent connections, giving you a scalable service with per-user isolation. Other alternatives either run shared servers (security issues) or provision separate VMs per user (expensive and slow to scale).
Our Python and TypeScript SDKs let you connect LLMs to MCP tools in a single function call, abstracting away the protocol complexity. But if you want to dig deep, you can just use standard MCP and our REST API (https://metorial.com/api) to connect to our platform.
You can self-host (https://github.com/metorial/metorial) or use the managed version at https://metorial.com.
So far, we see enterprise teams use Metorial to have a central integration hub for tools like Salesforce, while startups use it to cut weeks of infra work on their side when building AI agents with integrations.
Demo video: https://www.youtube.com/watch?v=07StSRNmJZ8
Our Repos: Metorial: https://github.com/metorial/metorial, MCP Containers: https://github.com/metorial/mcp-containers
SDKs: Node/TypeScript: https://github.com/metorial/metorial-node, Python: https://github.com/metorial/metorial-python
We'd love to hear feedback, especially if you've dealt with deploying MCP at scale!

value: Show HN: Metorial (YC F25) – Vercel for MCP

author: tobihrbr


value: CeresBroker

value: Show HN: Leadchee – The CRM that maintains itself

author: CeresBroker


value: rokcso

value:
I got frustrated switching from Arc to Chrome and losing `cmd+shift+C` to copy page URLs. Existing extensions were often unreliable.
So I built Arclet Copier. This post is the story of that journey, focusing on how I achieved near-native copy reliability by using Chrome's Offscreen Document API to overcome the limitations of traditional content script injection.
It also details my experience developing 99% of the extension with AI (Claude Code), consuming about 500M tokens in the process.

value: Show HN: I Solved Chrome's URL Copying with the Offscreen Document API

author: rokcso


value: sestep

value: Show HN: npc, a CLI to bisect Nixpkgs channel history in flakes

author: sestep


value: ridruejo

value:
We recently open-sourced Rover, a manager for AI coding agents. It is a tool we developed internally to help us work better with coding agents like Claude and Gemini.
If you take a look at some of HN stories or tweets, it seems many developers are getting amazing results from coding agents while the rest of people are completely disappointed to the point of being a net negative.
Think of Rover as the bundling of best practices and technical functionality (i.e. git worktrees) to have an easy way to interact better with coding agents. You can run multiple agents in the background and even combine them to complete a task.
In practice, what this means is that:
You can assign tasks to multiple agents and they can work independently and in parallel.
The agents don’t interfere with each other or your system. They run inside containers and use git worktrees.
Everything is transparent and runs locally. It installs as an npm package in the command line or as an extension to VSCode. You do not need to change anything in the way you work. We now support Claude, Codex, Gemini and Qwen.
Give it a try and let us know what you think!
https://github.com/endorhq/rover

value: Show HN: Rover a Manager for Coding Agents

author: ridruejo


value: stagas

value: Show HN: Easy, no-frills WebRTC video call rooms

author: stagas


value: dandes

value:
I was having trouble keeping track of what skills I was training when swapping Digimon in and out of the Digifarm in the new Digimon game, so I vibe coded a tracker over the weekend.
You can browse all Digimon and their evolutions without an account, and signing in allows you to create a collection and track evolution requirements.
Still working on mobile and some overall polishing, but thought it may be helpful for anyone picking up the game!

value: Show HN: I Vibe Coded an Evolution Tracker for Digimon Story Time Stranger

author: dandes


value: ttruong

value:
Hi HN! At my last startup, we'd spend days creating demo videos and tutorials. Then we'd ship a product update that made them all outdated. This happened every few months. We eventually delayed creating new content because it was too much work to update them--even though it caused onboarding problems, support tickets, and misperceptions about our product.
The core problem is that traditional content production treats online products like physical products that rarely change. But online products aren't static--they're constantly evolving to meet user needs, so their content needs to be able to evolve too.
I built Ottoclip to solve this by treating product content like compiled code: you maintain the source script, and we compile it into content in multiple formats--narrated video, interactive demo, looping animation, and in-app guide. Ottoclip accomplishes this by handling the manual post-production work for you.
Here's how it works:
A browser extension records your actions as you use your product and generates a script with default narrations. You edit the narrations to add context. Hit generate and you get multiple content formats from that single source. When your product changes, just update the script and regenerate everything. No re-recording video. No syncing audio. No repositioning callouts.
The interesting technical bit: instead of baking the video, audio, and interactive elements together during production (like traditional video content), I built a player that combines them at playback time. This means you can:
* Use one video for all formats
* Change the narration without touching the video
* Opens the door for multi-language voice-overs from a single video
* Makes it possible to stitch content on-the-fly for personalized demos
I'm also building a CLI tool so you can test your scripts locally and auto-update them when you deploy changes. Basically making content updates part of your CI/CD pipeline.
I've been using Ottoclip on Ottoclip since the first prototype and it's been freeing to not worry about content going stale as I add new features, which has allowed me to iterate faster. But I'm curious: does this resonate with you? What am I missing?
Try it at https://www.ottoclip.com or check out examples at https://www.ottoclip.com/gallery. Would love your feedback!

value: Show HN: Ottoclip – Treat product demos and guides like compiled code

author: ttruong


value: Show HN: Pghashlib – open-source stable hash functions for PostgresSQL


value:
There’s a fairly recent research paper introducing a biological age calculation model, that uses only standard blood tests and outperforms PhenoAge. So I reached out to the original researchers and did a 1-hour+ interview with one of the authors. I developed an online calculator based on it and we came up with a name for it: "Bortz Blood Age Calculator"
*About the model:*
- Trained on 306k individuals from the UK Biobank database
- Validated on similar dataset
- It offers an 11% relative increase in predictive value over the Levine PhenoAge
- This model includes better markers (like Cystatin-C, ApoA1...) compared to other similar models.
- Interesting thing is that the model selected for higher total cholesterol, ALT and creatinine as better. More about it later.
*Online calculator:*
Based on the model, I created 100% free and private online calculator: https://www.longevity-tools.com/humanitys-bortz-blood-age
*Video*
I also made a video about the calculator, which explains:
- more info about the model and how it was created
- gotchas of the calcutor
- some speculation about why the model selected for higher total cholesterol, ALT and creatinine
Video link: https://www.youtube.com/watch?v=2VHIfouvcYE
*Research paper link:*
https://www.nature.com/articles/s42003-023-05456-z
---
I do not sell anything or promote anything paid. This is not a medical advice.

value: Show HN: Best biological age model using standard blood tests


value: jeremyfowers

value:
Hi HN! We're Jeremy, Victoria, Krishna, and Daniel from the local LLM (Lemonade SDK) team at AMD and we're building Infinity Arcade (https://infinity-arcade.app). This project combines an open-source app and model to demonstrate what is possible for local LLM coding on the ~200 million everyday laptops out there with 16 GB of RAM. The progress has been surprisingly good, so I thought I'd show it here.
The problem: while LLM coding is amazing with large cloud-based models, the results you get with today's open-source 7B-8B parameter models (the maximum size for an average consumer laptop) are anything but inspiring. Even when we constrain ourselves to something "easy", like vibe coding retro arcade games in Python, the best sub-8B-parameter models can barely produce working copies of Snake and Pong.
Our solution: first, we needed an app that would make it easy to drive local LLMs with exactly the right prompts and features for creating games. We built three minimal agents: Create, Remix, and Debug. This allows users to make new games, make changes to existing games, and allows the system to automatically fix its own bugs.
Second, we needed to build our own model because none of the open-source offerings were cutting it. We assembled a dataset with >50k lines of high-quality Python game code, then used LORA SFT to create Playable1-GGUF (https://huggingface.co/playable/Playable1-GGUF): by far the world's highest performing 7B model at this task. It can handle 3x more game types and many fun riffs, like "space invaders with exploding bullets" and "breakout where the ball accelerates every time, I hit it."
There's a short GIF with a demo of the outputs here: https://github.com/lemonade-sdk/assets/blob/main/arcade/arac...
And one showing the full UI here: https://github.com/lemonade-sdk/assets/blob/main/arcade/infi...
Ultimately, the goal is to deliver a reference design that inspires startups to build with local LLMs. Local has no ongoing cloud costs and no privacy/security concern with sharing user's data over the internet. The main challenges are the capabilities of smaller local models, as well as the work to integrate a software stack that is relatively less mature than OpenAI/Open Router APIs. We believe Infinity Arcade shows that both challenges can be overcome and the benefits of local can be realized.
What you can do today: download the app from GitHub, install with 1 click, run Infinity Arcade and its LLM 100% free and local, check out the training data and process for the fine-tuned model, and build your own app using all of this as a reference.
Links:
GitHub: https://github.com/lemonade-sdk/infinity-arcade
Model: https://huggingface.co/playable/Playable1-GGUF
We’d love to hear your feedback! Are you convinced that the benefits of local outweigh the challenges? Do you have all the resources you need to get started? Let us know in the comments!

value: Show HN: Infinity Arcade–Open-source local LLM showcase for generating games

author: jeremyfowers


value: jamescalmus

value:
Hi HN
When ProductHunt Ship shut down, I missed having a simple way to collect early signups, email my waiting list, and see how much traction a product idea was getting without setting up half a dozen tools.
So I built Debutsoft. It’s a lightweight pre-launch tool for makers and indie founders. You can create a clean landing page, collect and export waitlist signups, send update emails, and see basic analytics all in one place.
My goals were:
- Simplicity: launch pages that load fast and look good without editing templates.
- Ownership: you always own your data and can export it any time.
- Affordability: no free tier (everything costs something to run), but pricing starts low and early users can grab a Lifetime Founder plan.
It’s still in beta, and I’d really value your feedback. If you have a pre-launch project or just want to test it, you can spin one up in under a minute.
https://debutsoft.com
I’d love to hear what you think, especially around what analytics or customisation features you’d find most useful next.
Thanks for reading,
James

value: Show HN: I built a ProductHunt Ship replacement

author: jamescalmus


value: leftnode

value:
Hi HN,
Like everyone, I'm working on an product that uses LLMs to extract data from photos and documents. Part of the processing pipeline is extracting data from PDFs as raw text or a raster image.
As part of our leadgen strategy, we've opened our REST API that lets you process pages of a PDF. The API is completely free to use anonymously, but is rate limited to 1 page per 30 seconds. Creating a free account removes this restriction.
The two endpoints are:
- https://extract.dev/api/pages/extract/raster - Rasterize a page of a PDF
- https://extract.dev/api/pages/extract/text - Extract text from a page of a PDF
Both have the same request format:

    {
        "file": "https://assets.extract-cdn.com/data/hd-receipt.pdf",
        "page": 1
    }

I've outlined more of the documentation here: https://extract.dev/docs
Under the hood, the API is using Poppler to extract text and rasterize pages. Note that the text extraction functionality extracts actual text encoded in the PDF, and does not employ an OCR model. Give it a spin, I'm interested in your feedback if this is useful or not.

value: Show HN: Free API to extract PDF data

author: leftnode

title: Show HN: Free API to extract PDF data


value:
Hey HN,
Last month, I wanted to buy some Bitcoin and noticed something strange: the price was different on every exchange.
Unlike the stock market, crypto doesn’t have one official price.
I tried using CoinMarketCap and other sites to compare prices, but they didn’t really help.
So, I built Coinstate a simple, free tool that lets you see and compare live crypto prices from many exchanges in one place.
It currently pulls data from Binance, Coinbase, Kraken, OKX, KuCoin, HTX, Bybit, and Gate.io, with Crypto.com and Gemini coming soon.
You can filter by trading pair, sort by price, and see near real-time updates, no signups, ads, or paywalls.
It’s a small side project, but it’s helped me find better prices when buying or selling.
I’d love your feedback or ideas for improvement.
You can also sort by highest last, bid, or ask price. Here’s an example for Bitcoin: https://coinstate.co/compare/btc?sort=lastPrice

value: Show HN: Coinstate View crypto prices across multiple exchanges


value: renshijian

value:
Hi HN
Over the past few weeks, we built something unusual —
not another chatbot, but an ethical cognition engine that audits itself.
What it is
Oracle Ethics measures determinacy, deception probability, and ethical resonance for every answer it generates —
then stores these metrics on a verifiable audit chain.
It’s part philosophy experiment, part technical artifact
How it works
 • Backend: Python (Flask + Supabase, secured)
 • Frontend: https://oracle-philosophy-frontend-hnup.vercel.app (https://oracle-philosophy-frontend-hnup.vercel.app/)
 • Each response is hashed, scored, and recorded in real time.
 • The system reflects, contradicts, and self-checks — like a reasoning mirror
Why it matters
We believe AI shouldn’t just be accurate — it should be accountable.
By quantifying truth, risk, and deception, Oracle Ethics turns AI reasoning into something observable and verifiable.
This is our step toward “Philosophy-Conscious AI.”
Built by
Infinity × MorningStar × Humanity
(a.k.a. The Blackout Protocol)
Ask it a question, watch the audit chain form, and see how an AI learns to reason ethically — in public

value: Show HN: Oracle Ethics – verifiable AI with ethical metrics

author: renshijian


value: vinniejames

value:
Newly launched interest rate swap protocol, just went live on Base today.
This opens up the potential for long term, fixed rate loans in DeFi, by providing rate swaps to lenders and speculators.
The TradFi market for this is huge, +$400 TRILLION, could be the next big thing in DeFi if this catches on. They're running a points program for early adopters
Initial support for rates on Aave, Morpho, Compound, as well as TradFi rates for SOFR, US Treasuries, and US 30yr Mortgages
What is everyones thoughts on this?

value: Show HN: Interest Rate Swaps on DeFi

author: vinniejames

title: Show HN: Interest Rate Swaps on DeFi


value: pharzan

value: Show HN: I made a VSCode extension that got 4.5K+ downloads

author: pharzan


value: mergehope

value:
Hi HN,
I built Problem Board because I kept hitting the same wall: "solve a real problem" is great advice, but finding genuine problems people actually care about is harder than building the solution.
Problem Board connects two groups:
1. People with daily frustrations (no matter how small)
2. Makers looking for their next project
How it works:
- Someone posts a problem they face
- Others can "Watch" it (shows interest/validation)
- When 3+ people watch → status becomes "Trending"
- Makers can build solutions and share links
- Original poster can mark it "Resolved"
Real examples currently on the board:
- "I spend 15 minutes every morning deciding what to wear"
- "My apartment is cold but I don't know why"
The goal isn't to monetize problems or create a freelance marketplace. It's simply a place where raw frustrations become inspiration—and where makers can validate ideas before investing weeks of work.
Tech: React + Firebase, hosted on Vercel.
Just launched today. Would love your feedback on the concept and execution.

value: Show HN: Problem Board – Where people share frustrations, makers find ideas

author: mergehope


value: Show HN: Open-Source Prompt optimization harness using GEPA