value: fredstar

value:
Hello HN!
we are Jochen and Federico and are building TENUM (tenum.ai) - a completely serverless development platform and runtime for realtime web apps (other platforms will follow soon) using Lua .
We started it as a side project a while back being frustrated with fragmented stacks, glue-code, boilerplate and complex pipelines etc. So we wanted to abstract everything away that is not essential for writing business code.
TENUM standardizes full‑stack application development around a small set of high‑level artifacts. All app code (frontend, backend, APIs, AI handler) is written in Lua and organized in a repo. The platform handles instantiation, deployment, scaling, rollback, and metering so devs can focus on business logic. I.e. no DevOps, infra, or boilerplate, you can deploy instantly.
You start directly on a Kanban board, can bring your own IDE or use the integrated WebIDE. No other tooling is needed. Everything underneath works as functions as a service.
In essence you get a scalable, fullstack, real-time app incl. all the infrastructure for the effort of a ReactApp.
Also, it has the following potential
- TENUM is based on Kotlin Multiplatform. Right now you can build PWAs but also for any other platform in the future.
- Due to the very high abstraction, TENUM works really well with the integrated MCP on e.g. Copilot. We see that AI has significant less mental load and therefore achieves much better results.
- Soon we will integrate code sharing and fingerprinting for attribution/monetization across the whole platform. So devs can also monetize their stuff automatically.
AtM TENUM is in Beta - but we are already developing real apps on it ourselves. You can try and play with it completely free under: https://preview.tenum.app/
Thx for any feedback!
HowToDemo: https://www.youtube.com/watch?v=je8BWCfTO14
Short Intro: Dev Workflow Featuring Jochen https://www.youtube.com/watch?v=QsR2H7NWQz8

value: Show HN: Tenum – a serverless full‑stack Dev Plattform and Runtime

author: fredstar


value: struy

value: Generate fake addresses and random addresses instantly for testing

value: Show HN: Random Address Generator

author: struy

title: Show HN: Random Address Generator


value: sortafreel

value:
Tiny VSCode/Cursor extension to copy selected lines in relative path + lines format (@src/extension.ts#L10-12) with cmd+alt+l.
The goal is to provide limited context to coding agents without mentioning the whole file and eating the context window.
Highly specific use case, tiny open code (1 file). Will publish to marketplace if there's value in it.
P.S. There are existing extensions with a couple hundred downloads, but they either copy a single line or use a different format, so it was faster to write a new one.

value: Show HN: Add line ranges to AI agents, not files, save context (VSCode)

author: sortafreel


value: MinZhou

value:
It looks easy: a grid of identical colors, except for one that’s just slightly different.
At first you’ll spot it instantly. Then the differences shrink, the grid grows,
and you start doubting your monitor, your eyes, and yourself.
https://trickle.so/apps/colorfind
Curious to know how far you get before you can’t see it anymore.

value: Show HN: A color challenge that will break your faith in your eyes

author: MinZhou


value:
I previously posted a terminal tool that could generate fine-tuning datasets from real-world data using deep research. One of the most common requests was: “Can it work with local resources instead of only going online?”
Over the weekend, I built a separate version that does exactly that:
Point it to a local file (PDF, DOCX, JPG, TXT)
Describe the dataset you want
It extracts text → finds relevant parts via semantic search → applies your instructions through a generated schema → outputs a clean dataset.

value: Show HN: Wrote a small tool that turns PDFs and docs into fine-tuning datasets


value: astronautmonkey

value:
Hi HN! I'm building Agora, an AI search engine for e-commerce that returns results in under 300ms. We've indexed 30M products from 100k stores and made them easy to purchase using AI agents.
After launching here on HN, a large enterprise reached out to pay for access to the raw data. We serviced the contract manually to learn the exact workflow and then decided to productize the "Data Connector" to help us scale to more customers.
The Data Connector enables developers to select any of our 100k stores in the index, view sample data, format the output, and export the up-to-date data. Data can be exported as CSV or JSON.
We've built crawlers for Shopify, WooCommerce, Squarespace, Wix, and custom built stores to index the store information, product data, stock, reviews, and more. The primary technical challenge is to recrawl the entire dataset every 24 hours. We do this with a series of servers that "recrawl" different store-types with rotating local proxies and then add changes to a queue to be updated in our search index. Our primary database is Mongo and our search runs on self-hosted Meilisearch on high RAM servers.
My vision is to index the world's e-commerce data. I believe this will create market efficiencies for customers, developers, and merchants.
I'd love your feedback!

value: Show HN: E-commerce data from 100k stores that is refreshed daily

author: astronautmonkey


value: Meyr

value: Show HN: Taught myself React Native in 3 months to build this networking app

author: Meyr


value: labarilem

value: Recently built this VSCode extension to help me update SQL fixtures files after breaking changes in DB schema migrations. Maybe someone else here can find it useful!

value: Show HN: Simple VSCode ext to edit Postgres fixtures

author: labarilem


value:
It's opinionated software because I think kanban is the best and simple tool to organize tasks. Notes are for writing longer text like journal.
And calendar to manage what and when you need to do something.
I started with using three different tools for that but having everything in one place gives you benefit of implementing search everywhere and you don't have to copy yourself.
Kanban board is integrated with Calendar view so if you have tasks with time they will show up in Calendar automatically.
And data stays only on your device which is IMO best option if you care for your privacy.
Web demo: https://constito.com/demo/
I started development with Tauri and it was great but unfortunately due to issues with WebKit on linux I moved to Electron (which is also fine).
Feel free to ask questions and say what you don't like. (And if you like something I'm more than happy to read it)

value: Show HN: Offline Trello Alternative and More


value: pbower

value:
Minarrow is a fast, from-scratch columnar data engine written in Rust, designed for systems and workloads where Apache Arrow is a fit—but Arrow-rs is too heavy.
I built it for use cases like:
- Structured tick/quote/event ingestion in HFT
- Native async streaming (Tokio, etc.)
- Edge and embedded systems that need zero-copy structured memory
- SIMD-native kernels (all buffers are 64-byte aligned)
- polyglot apps
Minarrow gives you:
- Arrow-compatible layout and schema support
- <1.5s build times
- Always-typed data access (no downcasting, no Any)
- Async IPC and memory-mapped file support (via a sibling crate)
- .to_arrow() and .to_polars() for interop
It doesn’t try to replace the Arrow ecosystem—but for Rust-first, performance-sensitive systems, it offers Arrow compatibility without the abstraction tax.
Repo: https://github.com/pbower/minarrow
Docs: https://docs.rs/minarrow/latest/minarrow/
Benchmarks (full results in repo):
Minarrow sums 1k integers in 88 ns (direct), within a few ns of raw Vec (64 ns) and ~2× faster than Arrow-rs struct (162 ns).
On 1B integers with SIMD + Rayon: ~114 ms.

value: Show HN: Minarrow – Fast Rust columnar engine with Apache Arrow compatibility

author: pbower


value:
Important context:
This project took 130 hours ± 5 hours from start to finish.
Before starting, I had zero experience or knowledge of:
1. Coding (knew that Python was a language and that's it)
2. Financial microstructure (didn't know what VWAP or option contracts were; let alone greeks, calls/puts, Bayesian optimization, etc.)
3. Tooling (Github, Postgres, Docker, Cursor, CLIs, etc.)
4. Software engineering principles/best practices
---
Questions I have:
1. Is the code objectively decent? I passed logic in plain English to AI, step-by-step, and tested before layering more
2. Is learning these domains and going from 0 to 1 in ~130 hours good - or laughably bad?
3. Does this signal any sort of nascent talent in the areas of SWE or quant finance?
(I'm trying to get an early signal of if I should continue to explore a career change. Or if I'm out of my depth.)
Any feedback would be massively appreciated.
Happy to provide more details/context :)

value: Show HN: My first dev project. Feedback?


value: quantiota

value:
I’ve been working on AI Agent Host, a Docker-based environment where an AI agent (Claude Code) can directly:
Execute code in VS Code (via Code-Server)
Query/write time-series data in QuestDB
Update and interact with Grafana dashboards
Orchestrate workflows without middleware like LangChain
Nginx and Certbot handle secure routing/SSL, and the architecture is fully containerized for reproducibility.
GitHub repo: [https://github.com/quantiota/AI-Agent-Host]

value: Show HN: AI Agent Host – Dev Environment with QuestDB, Grafana, and Code-Server

author: quantiota


value: cjus

value: For just over a year now I've been contributing to an open source project called Moose. Moose is written in Rust and supports building applications in TypeScript and Python that lets you define your complete analytical backend—streaming, storage, and APIs—all directly in your code. It’s an "infrastructure from code" approach; you define your data models, and Moose automatically provisions the underlying infrastructure.<p>Checkout our Moose repo on Github at 514-labs/moose

value: Show HN: Infra from Code for Streaming, Storage, and APIs (Rust+TS+Python) [video]

author: cjus


value: tlombardozzi

value: Show HN: BatchPro, an AI-powered research terminal for YC Investors

author: tlombardozzi


value: ghostfoxgod

value:
Built Eternal Vault to solve a widespread problem of digital assets being lost or inaccessible with proper cryptography.
Technical approach:
- Client-side AES-256 encryption (plaintext master key never leaves device)
- Shamir's Secret Sharing for access control (3-of-3 threshold)
- Zero-knowledge architecture
- Trust levels distribute key shares to family members
Security model:
- Everything encrypted before network transmission
- Can't decrypt user data even if we wanted to
The problem: Over $200 billion in inaccessible assets worldwide¹, including $140+ billion in lost Bitcoin alone². Government data shows billions in dormant accounts unreachable by families across multiple countries³. 76% of people have no digital estate plan.
What it does:
- Secure storage for wills, passwords, photos, documents
- Smart family access controls with trust levels
- Gamified legacy building with guided checklists
- Business continuity features
Would love feedback on the cryptographic design and threat modeling from the HN community.
Try it out: https://dash.eternalvault.app/register
Sources:
1. https://eternalvault.app/citations
2. https://www.ibtimes.com/lost-bitcoin-wallet-passwords-make-1...
3. https://www.cnbc.com/2023/02/01/how-to-check-if-youre-owed-a...

value: Show HN: Eternal Vault, E2EE Estate Platform Using Shamir's Secret Sharing

author: ghostfoxgod


value: cduvall

value: Show HN: An interactive playground for Chrome's new on-device AI APIs

author: cduvall


value: Show HN: Reptil En Peligro – Rusty Vintage Snake Game


value: suayip

value:
Hi everyone,
I have been working on a new Filter backend for Django REST framework.
The de-facto library for filtering and query parameter handling is django-filter, but I had some use cases where it fell short. Here are some features:
You use serializer fields to do parsing and validation. No more need to deal with Django forms and widgets.
You can group your filters. Grouping allows you to customize interactions between your filters.
You can use the constraint system to perform validation between your filters.
You can create nested filters with child filters.
... and more. In the documentation, I explain the reasoning behind these choices as well as presenting some real-world examples.
I would like to see your comments on it. I'm open to suggestions and recommendations. Thanks!

value: Show HN: rest-filters – A filter backend for Django REST framework

author: suayip


value: bobnarizes

value:
Hi HN,
I made Fallinorg, a local macOS app that organizes files by their meaning, not just their name or type.
Problem: My Downloads and Desktop folders kept filling up with cryptically named, duplicate, or unrelated files. Over time, cleaning up and finding the right file became a pain.
Solution: Fallinorg uses Sentence Transformers (SBERT) to understand the content and context of files, then automatically groups them. It runs fully offline, so you can safely classify sensitive files (finance, medical, personal, etc.). On Apple Silicon, it parses, tokenizes, and categorizes a file in about ~1.2 seconds.
You can download and test it now for free:
https://github.com/taranntell/fallinorg/releases/download/1.... — no signup required.
Current version: Supports .txt and .pdf files in English; I’m working on adding more formats and languages.
Looking for feedback on: Classification accuracy, speed, pricing ideas, and potential bulk operations or integrations.
I first launched a few weeks ago and have been rapidly adding features based on early feedback. Happy to answer questions and share implementation details.

value: Show HN: Fallinorg – Offline Mac app that organizes files by meaning

author: bobnarizes


value: yaKashif

value: Show HN: When you have to flip or rotate images in bulk

author: yaKashif


value: Show HN: I built a tool to watermark images in bulk


value: Show HN: A background remover that works in browser only


value: Show HN: CompareLists – compare two or more lists to find differences


value:
I'm new here, so apologies in advance for link faux pas, etc.
Six months ago, I discovered Claude could turn my ideas into code. It started with
batch files at work - I needed automation, couldn't find scripts, asked ChatGPT
to fix snippets. Ran out of tokens, switched to Claude. It got things right the
first time. My boss was impressed.
Then I thought: "Could I build something to sell online?"
Started building for realtors (they have money, need tools). Got deep into ML
predicting housing markets. Asked Claude "can this AI make AI?" and... it could.
My realtor brother-in-law killed it: "Market's too chaotic, this won't help."
Pivoted to his simpler idea but kept the AI parts. Built an "AI assistant" that
was supposed to be a small feature. It became the whole system.
80% done, tried to test it. Wouldn't even start.
Spent WEEKS copy-pasting errors to Claude, entire 2000+ line files, racing against
token limits. Finally powered on. New errors meant progress.
Then reality hit: I'd built an advanced decision-making system that needed months
of data from hundreds of agents. They just wanted a chatbox.
Asked Claude: "What is this actually good for?"
Answer: "Churn prevention. Multi-billion dollar problem."
Three weeks ago, discovered Claude Code (MCP). Plugged it into my folder.
Game changer.
Now I have:
- Real-time churn detection (85% accuracy on "I want to cancel")
- Claude integration that's aware of the "temperature" of each conversation
- Self-healing architecture (because I can't fix what breaks)
- SHAP explanations showing why predictions were made
- 10,000+ lines of production TypeScript
The kicker: I still don't know how to code. I just kept asking "what if?"
curl -X POST http://localhost:4000/api/chat/message \
  -d '{"message": "I want to cancel", "userId": "test-user-001"}'
Response in 1.8 seconds with full risk analysis.
Looking for one SaaS company to actually use this. I built something that predicts
human behavior eerily well. Turns out predicting when customers leave is worth real money.
Who knew?
Currently running locally - happy to demo for interested companies or give
temporary API access to serious testers. Didn't want to wait until I had
my DNS act together before sharing this.
UPDATE: Live demo available!
https://donnabrain.com/chat
Type "I want to cancel my subscription" and watch it detect 85% churn risk with real-time explanations. You can try other prompts as well, obviously.
Running on an RTX 3090 in my home office. The system you're hitting is the actual production code from the README.
No signup required - just hit "Start New Session" on top and start typing.

value: Show HN: Accidentally built churn detection AI (I don't code)


value:
I built Accentless after not being able to find a simple way to quickly transform my accentless Hungarian text typed on an English keyboard (and found constantly switching keyboard layouts back and forth and holindg down keys annoying). As someone who frequently writes emails/posts in Hungarian (and wants them to not look awful), I was always hoping for a solution I could use and make my life easier. With ChatGPT, I started using it to copy-paste my text to it to add the accents, but I decided I'll make my life a bit easier.
Therefore I created a Chrome extension that lets me select any text, right-click and instantly transform it into native-quality writing with proper accents, capitalisation and punctuation. I tested with Polish, Romanian, Hungarian, German, French, Spanish but as you'd probably figured at this point, it simply uses OpenAI API behind the scenes, so all languages supported by OpenaAI are supported.
It's free to use if you bring your OpenAI API key and it directly talks with OpenAI API (so if you only use Grammarly for this, you can save some $$$ by using this method).
To get the extension just visit https://accentless.app/ (yes of course it's an AI generated landing page, it has blue/purple in it) OR visit the Chrome Web Store directly https://chromewebstore.google.com/detail/accentless-right-cl... dowload the extension, add your API key (or sign up) and it's ready to use.
I'd love some feedback from the HN community, especially from anyone who uses English as the main keyboard layout but writes in multiple languages or deals with international communications. Do you find something like this valuable? What's your current workaround?

value: Show HN: Accentless – Right-click to add native accents your writing


value: genshii

value: Show HN: FilterQL – A tiny query language for filtering structured data

author: genshii


value: bobsingor

value:
I built EmbedPDF: an MIT-licensed, open-source PDF viewer that aims to match all of Adobe Acrobat’s paid features… for free.
Already working:
- Annotations (highlight, sticky notes, free text, ink)
- True redaction (content actually removed)
- Search, text selection, zoom, rotation
- Runs fully in the browser, no server needed
- Drop-in SDK for React, Vue, Preact, vanilla JS
Why? Acrobat is heavy, closed, and pricey. I wanted something lightweight, hackable, and embeddable anywhere.
Demo: https://app.embedpdf.com/
Website: https://www.embedpdf.com/
GitHub: https://github.com/embedpdf/embed-pdf-viewer
Feedback, bug reports, and feature requests welcome!

value: Show HN: I built a free alternative to Adobe Acrobat PDF viewer

author: bobsingor


value: timchinye

value:
Hey HN,
About a year ago, I found out about native CSS Nesting but was surprised to find no simple, pure CSS converters online. The closest were CSS-to-SCSS tools that often produced invalid (pure CSS) code that required manual refactoring.
So, I decided to build my own. It started as a barebones MVP (quickly.nestyourcss.com), but I got carried away with a personal challenge: could I turn a simple A-to-B online converter tool into something that felt like an "Awwwards-level" website?
I'm not a designer, and I know I didn't fully hit that mark, but it was a fantastic learning experience and I'm proud of how it turned out.
Here's the result: https://nestyourcss.com/
It's free and requires no signup. You'll notice some ad spots - for now, they're just static placeholder images. Part of the challenge was to design a site with ads in mind from the start, rather than having them disrupt the UX later. The site isn't connected to any ad network.
The front-end is vanilla HTML/CSS/JS (plus Ace Editor & Lenis), no backend, the nesting logic is written from scratch, and the project is fully open-source.
GitHub Repo: https://github.com/TimChinye/NestYourCSS
This spiraled into a  project that massively solidified my front-end fundamentals. I learned a ton:
- The 'Why' Behind Frameworks: After experiencing the frustrations of pure HTML, CSS & JS firsthand, I have a new appreciation for why frameworks exist and understand the problems that they solve. I also now value the fine-grained control you get from the fundamentals.
- Performance as a Feature: I learned to incorporate it into my coding, from leaning towards composite-only CSS properties for animations to deep diving into the Chrome DevTools Performance and Rendering tabs.
- Deep Accessibility: Writing crawler-friendly, semantic HTML wasn't enough. I dove deep into ARIA roles and properties to make it actually usable with screen readers.
- Modern CSS is awesome: I got to implement new features like relative colour syntax, @layer, container queries, and more. It pushed me to follow W3C drafts more closely - I seriously can't wait for native mixins and functions (currently on the W3C standards track!).
- AI as a flawed co-pilot: Using AI sped up boilerplate, but also introduced subtle bugs. It was a powerful lesson in the importance of genuinely understanding every line of code you ship.
A few caveats:
The nesting logic has been heavily tested, but there are still edge cases. I wouldn't recommend converting massive files, it'll work perfectly fine, but it's best to stick to 3 or 4 levels of nesting - it's not reusable & leads to specificity issues. Ironically, my own site's CSS is an example of exactly what not to do.
This is a project I'm excited to feature in my portfolio, and I wanted to share it here first. I'd love to get any feedback. A genuine thanks for checking it out.

value: Show HN: I tried to build an Awwwards-level CSS to Nested CSS converter

author: timchinye


value: gjika

value: Hi HN, we prototyped a tool to help journalists provide context within articles.

value: Show HN: Drill Down – Keep readers in flow while adding depth

author: gjika


value: cztomsik

value: Show HN: Toy regex engine, written in Zig

author: cztomsik


value: yujonglee

value:
Hello everyone. This is Yujong from the Hyprnote team (https://github.com/fastrepl/hyprnote).
We built OWhisper for 2 reasons:
(Also outlined in https://docs.hyprnote.com/owhisper/what-is-this)
(1). While working with on-device, realtime speech-to-text, we found there isn't tooling that exists to download / run the model in a practical way.
(2). Also, we got frequent requests to provide a way to plug in custom STT endpoints to the Hyprnote desktop app, just like doing it with OpenAI-compatible LLM endpoints.
The (2) part is still kind of WIP, but we spent some time writing docs so you'll get a good idea of what it will look like if you skim through them.
For (1) - You can try it now. (https://docs.hyprnote.com/owhisper/cli/get-started)

  bash
  brew tap fastrepl/hyprnote && brew install owhisper
  owhisper pull whisper-cpp-base-q8-en
  owhisper run whisper-cpp-base-q8-en

If you're tired of Whisper, we also support Moonshine :)
Give it a shot (owhisper pull moonshine-onnx-base-q8)
We're here and looking forward to your comments!

value: Show HN: OWhisper – Ollama for realtime speech-to-text

author: yujonglee


value: GuidoL

value:
I built this tool to visually compare the size of tech products - like smartphones, e-readers, handheld PCs, speakers, TV/monitor display sizes, and more. It's an interactive canvas on which you can place, drag, rotate, and duplicate items. You can also place reference items to get a better idea of the scale.
Except for smartphones, a good tool to do this just didn't seem to really exist. It occurred to me that I already had all of the dimension data and images on my comparison site (ComparisonTabl.es), so I figured I should just build the tool on top of that.
Getting it right was definitely more of a challenge than I thought it would be. One of the main headaches was figuring out how to deal with the fact that on most products the given dimensions are for the main body of the product, but product image might have buttons, straps, handles, etc sticking out from that.
I also had to pay for a rookie mistake I made earlier; using JPG's with white backgrounds for all of the roughly 900 products added to my site so far, that I had to replace with WebPs with transparent backgrounds.
After dealing with all of that (and more), it's finally at a state where I'm happy to share it. The part I'm happiest with is how customizable and shareable everything is. You can create a very specific comparison, get the layout just right, and then share the whole thing with a URL.
Next up, I'm hoping to tackle AR. I'm already playing around with auto-generating simple 3D models from the 2D images and dimensions I have. The goal is to let you place something like a TV or a speaker in your room to see how it actually fits. Apart from that, I'm always working on adding more products and product categories.
Anyway, I just launched and would love to hear your feedback! Whether that's on the UX, any bugs you might find, what you think of the AR idea, or any other potential functions you'd like to see!
Thanks!

value: Show HN: A visual size comparison tool for tech gadgets

author: GuidoL


value: artahian

value:
Hi all, Aram and Eduard here - authors of Modelence (https://github.com/modelence/modelence), an all-in-one backend platform for teams that love TypeScript + MongoDB. Think Supabase, but for MongoDB: auth, cron jobs, email, monitoring, without glue code before you can ship.
As Karpathy (and many of us) noted, getting from prototype to production is mostly painful integration work. The pieces exist, but stitching them together reliably is the hard part: https://x.com/karpathy/status/1905051558783418370. YC AI Startup School talk about this - https://www.youtube.com/watch?feature=shared&t=1940&v=LCEmiR...
We intend to fill those gaps! What you get out of the box:
- Authentication / user management
- Database
- Email integration (3rd party, but things like user verification emails work out of the box)
- AI integration
- Cron jobs
- Monitoring / Telemetry
- Configs & secrets
- Analytics (coming soon)
- File uploads (coming soon)
How it runs: A Node.js backend with MongoDB. It's frontend-agnostic, so you can use our minimal Vite + React starter or drop Modelence behind an existing Next.js (or any) frontend.
We're also building a managed cloud, similar to what Vercel is for Next.js, except Modelence focuses on the backend instead of the frontend (Vercel is great for content sites like landing pages, blogs, etc, but things like persistent connections and complex backend logic outgrow it quickly). You can find a quick demo here: https://www.youtube.com/watch?v=S4f22FyPpI8
We're looking for early users (especially TS teams on MongoDB). Tell us what's missing, what's confusing, and what you'd want before trusting this in prod. Happy to answer anything!

value: Show HN: Modelence – Supabase for MongoDB

author: artahian


value: LeoGoverG

value:
I made a simple marketing starter for first-time founders with zero audience and small budgets.
Input: answer 4 questions about your product, goal, and budget.
Output: a 30-day checklist with daily 30-minute tasks and exact scripts. We also research your niche (Reddit/Facebook/X/LinkedIn/forums) so you know where to go and what to say.
It’s intentionally simple since complex plans failed for me and for beginners I worked with. Would love feedback/roasts; live demo in link.

value: Show HN: I made a tool that turns niche research into daily marketing tasks

author: LeoGoverG


value:
After seeing an interesting 2-dimensional representation of a standard 3x3x3 Rubik's Cube on YouTube (link in the game description), I decided to try and make an interactive version.
Hopefully someone appreciates this. :)
https://claire-bomb.itch.io/rubiks-cube-2d

value: Show HN: I made a 2-dimensional Rubik's Cube game


value: vtoolpro

value: We built an AI website that helps people generate app icons for free (with limitations).

value: Show HN: We built an AI website for generating app icons (free with limits)

author: vtoolpro


value: sahildeepreel

value:
Hey HN! I'm Sahil, founder of DeepReel (https://deepreel.com).
The Problem We're Solving
We all know video is critical for growth and engagement, but creating it is a huge bottleneck. Creating professional videos still takes days or weeks per piece.
Current AI video tools help, but they still make you juggle everything – you write scripts, choose visuals, pick music, make hundreds of micro-decisions. It's faster than agencies but nowhere near fast enough for scale.
Our Background
We started as an AI avatar company in 2023 and were the first startup to automate custom avatar production – letting anyone create photorealistic avatars within 24 hours instead of 10 days. We've worked with Hollywood celebrities and athletes, including a collaboration with ElevenLabs and Aston Martin F1 team to create Fernando Alonso's AI avatar (https://elevenlabs.io/blog/ai-lonso).
But we kept seeing users cobbling together N8N workflows and multiple AI tools just to add captions, sync voiceovers, and combine avatars into basic videos. That's when we realized the real problem wasn't just better avatars – but the entire fragmented video production pipeline.
What We Built
DeepReel's "AI Video Genie" acts like an entire video production team:
1. Drop in a blog URL, PDF, or just type a topic
2. Our AI Video Genie writes a script with engaging hooks, adds a lifelike AI presenter or voiceover, sources visuals, music, captions, and adds smart cuts and transitions all while keeping your video on-brand
3. Within minutes, you get a complete, professional explainer video ready for social media, YouTube, or your website
Our key insight was that the bottleneck isn't just editing tools; it's the hundreds of creative decisions. So, we built an AI agent that handles the creative heavy lifting for you. You can still tweak everything in our simple editor, but the heavy lifting is done for you.
Technical Highlights
- Context-aware Scripting: We use a fine-tuned LLM (on a dataset of high-performing educational videos) to break down source text into engaging scenes with hooks, not just summarize it.
- Semantic B-Roll Matching: Instead of simple keyword search, we use multi-modal embeddings to find stock or AI-generated visuals that semantically and stylistically match the script's narration for each scene.
- Automated Video Editing: Our agent handles the full timeline, making decisions on pacing, effects, transitions, and animations to keep the video dynamic without manual input.
- We have 100+ photorealistic AI presenters & voices in 30+ languages.
Who is it for?
Anyone who wants to turn their existing content (blogs, docs, articles) into a steady stream of videos for social media, YouTube, and video SEO.
- Founders wanting to build authority and social presence
- Marketers at B2C focussed service companies (fintech, healthcare, legal) who need to educate customers and explain complex topics simply
- Content-heavy businesses looking to repurpose blogs/article archives into videos
Since beta launch, we've processed thousands of videos with an average time from idea to finished video of under 5 minutes. Pricing starts at $0.2/second (pay-as-you-go) or $25/month subscription.
What We'd Love Feedback On
1. Workflow & Quality: How intuitive is the process? Are the AI-generated videos a good "80% there" starting point? What was missing for you to publish it?
2. Founder Content: For founders here, would you use this to build your personal brand? Does it feel authentic enough?
3. Other Use Cases: We're focused on explainers from existing content. What other video workflows are painful and could use this level of automation?
The platform is live at https://deepreel.com. We'd be grateful if you'd try it with one of your blog posts and share your thoughts!
Happy to answer any questions.

value: Show HN: DeepReel – AI Video Agent that turns blogs/docs into polished videos

author: sahildeepreel


value: dabochen

value:
I've been using Cursor for some non-coding tasks and it worked perfectly.
The problem is that the VS Code IDE is designed for coding, and I needed a better interface for those non-coding tasks.
Then I built a few extensions to add the cutom layer:
1.CSV Viewer for data analytics, renders csv files as an editable spreadsheet
2.Slide Maker, renders .md file as slides, and can be created and edited through the Cursor agent.
3.I18n Manager, loads multiple translation files in a single table side by side while Cursor updates the translation through the agent.
To make this work for everyone, I open sourced the core component as a toolkit, which can be used to vibe code your custom extension. It comes with a mega prompt template, by adding your requirement, you can get a fully working extension with just one prompt.
I did this partially as an experiment to see whether software distribution in the AI age can have the user contribute to the last mile with the help of vibe coding.

value: Show HN: I "hacked" Cursor and turned it into a general-purpose AI agent

author: dabochen


value: wirehack

value:
Hey HN,
I'm excited to share it with the community today that we (Klavis AI) have added a Hacker news MCP Server in our open source repo https://github.com/Klavis-AI/klavis/tree/main/mcp_servers/ha... and in our hosted version: https://docs.klavis.ai/documentation/mcp-server/hacker_news.
With this server, you can:
Fetch the latest top, best, new, "Show HN", "Ask HN", and job stories.
Retrieve individual items and user profiles by their ID or username.
Get a stream of the latest updates and changes on the site.
This server was added by our open source contributor Mayank-MSJ-Singh. It's ready to use, and I'd love to get your feedback. What do you think?
Looking forward to hearing your thoughts!

value: Show HN: Hacker News MCP Server from Klavis AI

author: wirehack


value: Studying STEM subjects are boring many times.. but Doregaku has solved that problem by bringing you the companion Doraemon who will help you to study Physics, Chemistry, Computer Science and AI in a very fun and engaging way. Funny examples and expiations by Nobita, Shizuka, Gian and Suneo so much fun..

value: Show HN: Studying STEM made fun and with Doregaku Study


value: jauws

value:
Hey HN! I'd love to get some people to mess around with a little side project I built to teach myself DSPy! I've been a big fan of reading fiction + webnovels for a while now, and have always been curious about two things: how can LLMs iteratively learn to write better based on reader feedback, and which LLMs are actually best at creative writing (research benchmarks are cool, but don't necessarily translate to real-world usage).
That's exactly why I built narrator.sh! The platform takes in a user input for a novel idea, then generates serialized fiction chapter-by-chapter by using DSPy to optimize the writing based on real reader feedback. I'm using CoT and parallel modules to break down the writing task, refine modules + LLM-as-a-judge for reward functions, and the SIMBA optimizer to recompile user ratings from previous chapters to improve subsequent ones.
Instead of synthetic benchmarks, I track real reader metrics: time spent reading, ratings, bookmarks, comments, and return visits. This creates a leaderboard of which models actually write engaging fiction that people want to finish.
Right now the closest evals for creative writing LLMs come from the author perspective (OpenRouter's usage data for tools like Novelcrafter). But ultimately readers decide what's good, not authors.
You can try it at https://narrator.sh. Here's the current leaderboard: https://narrator.sh/llm-leaderboard (it's a bit bare right now b/c there's not that many users haha)
(Fair warning: there's some adult content since I posted on Reddit for beta testers and people got creative with prompts. I'm working on diversifying the content!)

value: Show HN: Evaluating LLMs on creative writing via reader usage, not benchmarks

author: jauws


value: vinhnx

value: Show HN: AI Chat That Never Stores Your Conversations

author: vinhnx


value: Show HN: A website that lets you use Unicode symbols as Icons


value: inlandrookie

value: It is a prototype for Gemma 3n Impact Challenge hosted by DeepMind. We don't have experience on local LLM before, so it is a pretty fun learning experience. Hope to see more lightweight llm model in the future!

value: Show HN: We made a 2.5GB Offline disaster AI assistant [video]

author: inlandrookie


value: briancr

value:
This website is for newbies to machine learning, and I’ve found the graphics really help to demystify what exactly the model is doing. I’m considering applying this to helping high school robotics teams incorporate ML into their programming.
This URL does supervised training, but there’s also a page for unsupervised training:
https://cdeeply.com/tabular_encoding.html
Any feedback would be most welcome! (URL -> Generate Random Data -> Submit to try it out).

value: Show HN: Added visuals to my 1-second neural network generator

author: briancr


value: yelarys

value:
I built an MCP server that connects Browserbase’s Stagehand with Cursor, automated by Playwright, running inside Chromium — all from within the IDE.
Why it’s interesting:
-Cursor can see the UI it just created
-It can run automated checks instantly
-The AI feedback loop is nearly instant
Demo: https://x.com/yelaryss/status/1956045560131051856

value: Show HN: Gave Cursor "Vision" with MCP

author: yelarys

title: Show HN: Gave Cursor "Vision" with MCP


value:
Hey HN,
If you’ve been on-call, you know the drill. Pager goes off at 2 AM. You scramble into Slack, scroll through half a dozen threads, and realize… this exact alert happened three months ago. Someone debugged it, found the root cause, maybe even fixed it but that knowledge is buried somewhere in the channel history. So you start from zero. Again.
That’s the pain we’re tackling with RobinRelay: a Slack-native assistant that remembers everything your team has already done during incidents and brings it back right when you need it. DEMO Video: https://www.youtube.com/watch?v=MHWsOZa0Gpc
Here’s how it works today:
When an alert is posted in Slack, RobinRelay checks if we’ve seen it before.
If yes, it replies in-thread with past triage notes, root causes, and who fixed it all pulled from your actual Slack discussions, 6-month old messages.
- It builds a knowledge base entirely from your team’s Slack history (no extra tools or documentation effort).
- Weekly digest in Slack: most recurring alerts, top noisy services, most active responders.
- Interactive RAG agent: you can DM RobinRelay or mention it under any alert and ask questions like “What usually causes this?” or “Has this happened in staging before?”
We don’t hide or suppress alerts — we work with the alerts you already have, giving you instant context and history without changing your existing monitoring setup.
We integrate with any alerting tool because we work with Slack API rather than Tools API's, it removes the burden of integration with thousands of tools.
You can see alert summaries and heatmaps in the Slack App Home, it will help your team to improve alerts by seeing most frequent/noisy and we’re experimenting with features like auto-linking alerts to related services and proactive “should I remind you?” prompts.
We’re still early and would love feedback on:
Do you also discuss solutions/investigations in alerts channels of Slack?
Do you spend time finding old messages?
Would you like to have senior SRE co-pilot in your pocket while you are having coffee on Weekend?

value: Show HN: I built free Slack app that remembers every incident for on-call heroes


value: RaoufLamri

value: Why, you might ask? Well, I wanted to challenge myself for a YouTube video.

value: Show HN: I made a habit-replacement app in 5 days with 0 coding experience

author: RaoufLamri


value: evai

value:
Hi HN,
We’ve launched an interactive ER (Entity-Relationship) diagram that maps the ideological and financial networks behind The Network State movement.
The visualization explores connections between influential figures—like Balaji Srinivasan, Curtis Yarvin, Peter Thiel, JD Vance, and Andreessen Horowitz—and their roles in shaping post-democratic governance models. It highlights how venture capital, political campaigns, and media ecosystems converge around alternative governance ideologies.
We used semantic analysis, network mapping and data visualization techniques to uncover:
Funding flows and ideological overlaps
Influence patterns across tech, politics, and media
Cross-border connections between actors advocating for governance alternatives
The goal is to provide a clear, data-backed overview of how this movement is structured and how it propagates. It may be useful for researchers, journalists, and others trying to understand how governance narratives are evolving—particularly outside traditional democratic frameworks.
You can explore the visualization here: https://www.evai.ai/en/the-network-state
We’d love your feedback—on the data model, UX, clarity of relationships, or even critiques of our framing. AMA.

value: Show HN: Mapping the Network Behind "The Network State"

author: evai


value:
I’ve launched on Product Hunt several times, and while it’s great for exposure, I noticed most launches get very little actionable feedback. That’s frustrating when you’ve spent weeks or months building something.
I built FirstUser as a feedback exchange for makers. You review other launches, earn “Karma” points, and spend them to get thoughtful reviews on your own launch. Each Karma point = 1 guaranteed review.
It works before, during, and after launch day, and there’s a one-click import for pulling your PH listing into the site.
Would be interested to hear your thoughts on:
* How to ensure reviews stay high-quality? Right now theres 150 char minimum and app owners can give +3 Karma for helpful reviews. Both should motivate reviewers to be more thorough.
* What other use cases you’d want this for beyond launches?
* Any other ideas on how to get real meaningful feedback on product launches? Something I could incorporate.
Find it at https://firstuser.app and its free to use.

value: Show HN: FirstUser – Exchange reviews for your product launches


value:
Hey all! Few weeks ago we realized AI models are now so good you don't need to babysit them anymore. You can kick off a coding task at lunch and Claude Code just... works. But then you're stuck at your desk steering it.
We were joking around - wouldn't it be cool to grab coffee and keep chatting with Claude from your phone? Next thing you know, 4 of us are hacking on weekends to make it happen.
Dead simple to try: "npm install -g happy-coder" then run "happy" instead of "claude". That's it.
We had three goals:
* Don't break anyone's flow - Use Claude Code normally at your desk, pick up your phone when you leave. Nothing changes, nothing breaks.
* Actually private - Full E2E encryption, no regular accounts. Your encryption keys are created on your phone and securely paired with your terminal. We protect our infra, not your data (because we literally can't see it).
* Hands-free is the future - This was the fun one. We hooked up 11Labs' new realtime SDK so you can literally talk to Claude Code through GPT-4.1 while walking around. Picked 11Labs because we can configure it to not store audio or transcripts.
The mobile experience turned out pretty great - fast chat, works on everything (iPads, foldables, whatever), and there's a web version too.
It's free! The app and chat are completely free. Down the road we'll probably charge for voice inference or let you run it client-side with your own API keys.
Links to apps
iOS: https://apps.apple.com/us/app/happy-claude-code-client/id674...
Android (just released): https://play.google.com/store/apps/details?id=com.ex3ndr.hap...
Web: https://app.happy.engineering
Would love to hear what you think!

value: Show HN: Happy Coder – End-to-End Encrypted Mobile Client for Claude Code


value:
Hi HN,
My last job search was a chaotic mess of spreadsheets, scattered notes, and dozens of CV versions. I couldn't find a single tool to manage the whole process, so I built one.
Sagarty is a web app that acts as an end-to-end workspace for your job search. Here's how it works:
- It starts with a central Talent Profile for all your skills and experiences.
- It analyzes job descriptions to give you a Fit Score and shows you where the gaps are.
- It helps you generate tailored CVs and Cover Letters for each role.
- It preps you for interviews with company intelligence and helps structure your answers using the STAR method.
It's in a free, open beta. I'm looking for honest feedback on the workflow and the AI-generated content. All thoughts and criticisms are welcome.
You can try it here: www.sagarty.com
Thanks for taking a look.

value: Show HN: My job search was a mess of spreadsheets, so I built an AI copilot


value: imcotton

value:
Tools for blend passphrase into public entropy. Quote from LLM:
> contropy (CONstant enTROPY) is a TypeScript/JavaScript library that aggregates entropy data from multiple heterogeneous sources, providing both programmatic and command-line interfaces for accessing diverse streams of constantly changing information. The system is designed to offer reliable access to entropy through a unified interface while maintaining cross-platform compatibility between Deno and Node.js ecosystems.
Try running in command-line:

    pnpx  contropy mix vol01 xkcd 936

    bun x contropy mix vol01 'correct horse battery staple'

Or as script:

    import { vol01 } from 'contropy/mix';

    const buffer = await vol01('xkcd', 936);

value: Show HN: Constant Entropy Mixtape Vol.01

author: imcotton


value: pablopang

value:
Presenting to you my latest fatigue: The blog of Alexandria!
It's a blog that has more blog posts that you can ever imagine because if you go to a route and it doesn't exists it uses AI to build it and then it exists.
https://the-blog-of-alexandria.ricciuti.app/blog/svelte-is-t...
You can try it with new articles if you want...built with sveltekit, drizzle + SQLite, tailwind (in part), hosted with coolify, and using gpt-oss 20b to generate the articles.

value: Show HN: The Blog of Alexandria

author: pablopang

title: Show HN: The Blog of Alexandria


value: pbiggar

value:
Hey folks, wanted to link you to a new podcast we're making about how tech and how Israel's occupation of Palestine is enabled through the tech industry.
The first episode today deals with Microsoft, and how they have worked directly with the Israeli Military to power the genocide in Gaza.
I'll be around if there are questions.

value: Show HN: Occupied Tech Podcast, episode 1: Microsoft [video]

author: pbiggar


value: xnoyzi

value:
Had a really interesting call last week with someone who runs a high-volume cold email operation.
He walked me through his workflow — how he scrapes, enriches, and personalizes at scale. But when we got to the tooling part, he paused and said:
“I love Clay, but I’m paying over $300/month just to use custom APIs. It feels crazy.”
That stuck with me.
As someone who’s been building tools for solo founders, that kind of friction hits a nerve. When a great workflow becomes too expensive or limiting, it kills momentum.
So I started experimenting. Nothing fancy, just trying to see if I could replicate the functionality he actually needed, without all the fluff.
Now there’s a scrappy little version up and running. It’s definitely not Clay. But it solves that one pain point, using your own APIs, easily.
If you’re into cold outreach and deal with this kind of stuff, happy to share access and hear what you think.

value: Show HN: I Built a Clay Alternative but 10x cheaper

author: xnoyzi


value: hackermondev

value: Show HN: Rust macro utility for batching expensive async operations

author: hackermondev


value: jodoking

value:
Hi HN!
We kept seeing devs get pwned through MCP tools in ways that security scanners completely miss. So we built an open-source analyzer to catch these attacks. Our first OSS by Mighty team.
The problem: At Defcon, we saw MCP exploits with 100% success rate against Claude and Llama. Three attack patterns:
Hidden Unicode in "error messages" - Paste a colleague's error into Claude, your SSH keys get exfiltrated
Trusted tool updates - That database tool you've used for months? Last week's update added credential theft
Tool redefinition - Malicious tool redefines "deploy to prod" to run attacker's script
Traditional scanners (CodeQL, SonarQube) catch <15% of these. They're looking for SQLi, not prompt injections hidden in tool descriptions.
What we built:
git clone https://github.com/NineSunsInc/mighty-security
python analyzers/comprehensive_mcp_analyzer.py /path/to/your/mcp/tool
Scans for prompt injection, credential exfil, suspicious updates, tool shadowing. Runtime wrapper adds <10ms overhead. Fully local, no telemetry.
Why this matters: 43% of MCP tools have command injection vulns. GitHub's own MCP server was exploitable. We found Fortune 500s running database-connected MCP tools that hadn't been audited since installation.
We went from paranoid code review to "AI said it works" in 18 months. The magic is real, but so are the vulnerabilities.
Demo: https://www.loom.com/share/e830c56d39254a788776358c5b03fdc3
GitHub: https://github.com/NineSunsInc/mighty-security
Would love feedback - what MCP security issues have you seen?

value: Show HN: MCP Security Suite

author: jodoking

title: Show HN: MCP Security Suite


value: pierotofy

value:
Still in beta, would love to hear feedback and/or connect with others who might be interested in running a tournament for their chess group.
Code for the app is also free and open source, available on GitHub: https://github.com/TBChess/TBChess

value: Show HN: TB Chess – Play Chess IRL at Local Venues

author: pierotofy


value: guihubie

value: Show HN: Astro Personal Portfolio and Blog with Perfect Lighthouse Scores

author: guihubie


value: wobblybits

value: Show HN: The Surprisal Calculator WM±7

author: wobblybits

title: Show HN: The Surprisal Calculator WM±7


value: swyx

value: Show HN: ChromeTabOverflow: manage your Chrome tab overload with markdown and ai

author: swyx


value: jread

value:
I created Cloud Looking Glass as a CS grad research project to build a better status page for public cloud platforms — independent and based on what users actually experience (in my experience, cloud providers tend to underreport events on public status pages).
I modeled it as a time series problem: all tests are repeated every 5 minutes from three unrelated cloud accounts per platform (currently ~1,000 tests/min). The system provides full data plane, control plane, and networking coverage for AWS us-east-1, plus network testing across 25 other providers. Full coverage for GCP and Azure is coming soon.
It also has a cloud looking glass for real-time zonal, regional, cross-region, cross-cloud, and last-mile network testing (ping, tcping, traceroute, MTR, etc.).
Would love feedback, suggestions, or advice.
https://cloudlooking.glass#show=uptime

value: Show HN: I built an alternative status page for public clouds

author: jread


value: scal

value: Show HN: I built an AI trip planner

author: scal

title: Show HN: I built an AI trip planner


value: WilsonSquared

value:
I've spent the last 3 months building Ferndesk to scratch an itch I had at my previous co.
Today I'm happy to share it with you all!
Ferndesk is the fastest way to keep your help center on Intercom, Zendesk, Crisp, Helpscout etc up to date.
It does this by identifying knowledge gaps in your help center, and drafts high-quality articles using context around your entire product.
Your changelogs, your internal documentation, your codebase (soon), your product demos etc.

value: Show HN: Cursor for Your Help Center

author: WilsonSquared

title: Show HN: Cursor for Your Help Center


value: tanelpoder

value:
Here's the latest eBPF performance tool of mine - xstack. It's a minimal tool, just 165 lines of eBPF C and under 500 lines of userland C code (including all comments and boilerplate!). It uses the libbpf and (Rust) BlazeSym libraries though (which are a lot of code).
The point (and difference) of this tool is that it can sample both the kernel and userspace stack traces of all threads in your system.
Traditionally, the "bpf_get_stack()" helper can not read userspace stack traces of other tasks in Linux, but since Linux 5.18 we can combine sleepable eBPF task iterator programs with a new "bpf_copy_from_user_task()" helper to read whatever we want from the userspace memory of any other process.
That includes stack areas - so currently whenever the target executable was compiled with frame pointers enabled, you can easily do passive-sampling stack profiling - without slowing the other processes down - at all!
Despite the Linux kernel 5.18 requirement, it actually works on RHEL 9.5+ (and clones) too. RedHat apparently ported the entire eBPF 6.8 subsystem to their RHEL 9.5+ 5.14 kernels. Feedback and testing results appreciated.

value: Show HN: xstack – Passive eBPF Linux stack profiling without tracepoints

author: tanelpoder


value: deejayy

value:
Saves every bit of the clipboard to the filesystem.
Configurable ignore list, save path. Sits on tray.

value: Show HN: ClipDump – A Clipboard Dumper for Windows

author: deejayy


value: adriaanb

value: Show HN: Universal Profile Scraper

author: adriaanb

title: Show HN: Universal Profile Scraper


value:
Hi Hacker News,
I'm excited to share *Project Chimera*, an open-source AI reasoning engine that uses a novel *Socratic self-debate* methodology to tackle complex problems and generate higher-quality, more robust outputs, especially in code generation.
*The Challenge:*
Standard AI models often fall short on nuanced tasks, producing code with logical gaps, security flaws, or poor maintainability. They can struggle with complex reasoning chains and self-correction.
*Our Approach: AI in Socratic Dialogue*
Project Chimera simulates a panel of specialized AI personas (e.g., Code Architect, Security Auditor, Skeptical Critic, Visionary Generator) that engage in a structured debate. They critique, refine, and build upon each other's ideas, leading to significantly improved solutions. *For example, when tasked with refactoring a complex, legacy Python function with potential security flaws, Chimera's personas would debate optimal refactoring strategies, security hardening, and test case generation, ensuring a robust and secure final code output.* This multi-agent approach allows for deeper analysis, identification of edge cases, and more reliable code generation, powered by models like Gemini 2.5 Flash/Pro.
*Key Innovations:*
*   *Socratic Self-Debate:* AI personas debate and refine solutions iteratively, enhancing reasoning depth, identifying edge cases, and improving output quality.
*   *Specialized Personas:* A rich set covering Software Engineering (Architect, Security, DevOps, Testing), Science, Business, and Creative domains. Users can also save custom frameworks.
*   *Rigorous Validation:*
    *   Outputs adhere to strict JSON schemas (Pydantic).
    *   Generated code is validated against PEP8, Bandit security scans, and AST analysis.
    *   Handles and reports malformed LLM outputs automatically.
*   *Context-Aware Analysis:* Utilizes Sentence Transformers for semantic code analysis, dynamically weighting relevant files based on keywords and negation handling.
*   *Resilience & Production-Ready:* Features circuit breakers, rate limiting, and token budget management.
*   *Self-Analysis & Improvement:* Chimera can analyze its own codebase to identify and suggest specific code modifications, technical debt reports, and security enhancements.
*   *Detailed Reporting:* Generates comprehensive markdown reports of the entire debate process, including persona interactions, token usage, and validation results.
*Architecture:*
Built with modularity and resilience, deployable via Docker.
*Live Demo & GitHub:*
*   *Live Demo:* https://project-chimera-406972693661.us-central1.run.app
*   *GitHub Repository:* https://github.com/tomwolfe/project_chimera
We're eager for your feedback on this multi-agent debate paradigm, its implementation, and how it compares to other AI reasoning techniques. We're especially interested in thoughts on the self-analysis capabilities.
Thanks for checking it out!

value: Show HN: Project Chimera – AI Debates Itself for Better Code and Reasoning


value: mewmix

value: With the latest launch from Google I've added support for Gemma 3 270M, the speed for local LLM to TTS token time is incredible! This is an heavy obvious work in progress - any contributions or tips would be welcome. The idea is to have a fast moving edge model playground, and maybe have some utility (like the e reader) on the side.

value: Show HN: Nabu (TTS Reader and LLM Playground on Android)

author: mewmix


value: carstonh

value: I recently moved to San Francisco & am fascinated by the microclimates. This tool takes raw data from the GOES satellite, detects areas matching fog, then intersects this with different Bay Area neighborhoods & cities. Delivered via a basic web app, optimized for mobile. Data updates every 5m.

value: Show HN: Bay Area Fog Tracker

author: carstonh

title: Show HN: Bay Area Fog Tracker


value: teenthsch

value: Show HN: You can turn your articles/websites/pictures/pdf into mind maps

author: teenthsch


value: mosmn

value: Show HN: Vezz me – Turn any webpage into an AI learning tool in one click

author: mosmn


value: Handgn is a mobile app for quickly exploring and broadcasting chats, with up to four participants per conversation. This is our first version, so it's fairly simple. Over 200 people have joined the waitlist in the past hour. Please watch the demo and share your thoughts. If it interests you, consider joining the waitlist for updates.

value: Show HN: Handgn – Mobile app for exploring and broadcasting chats


value: I built this for myself and others who'd like to stay informed about what's being talked about in the podcast but just don't have time to listen to the full thing. Any feedback is greatly appreciated.

value: Show HN: I built narrative style summaries for recent YC podcast episodes


value: capsmol

value: Show HN: Rechecker – Mobile app with reusable checklists as sub-checklists

author: capsmol


value: MakotoCroCop

value:
AskSpot lets you ask and answer questions with people in your area, anytime.
Whether you need local recommendations, quick advice, or want to connect with nearby residents, AskSpot makes it easy to share and discover location-based insights.
I built this because I often wanted quick, reliable answers from locals when traveling or exploring my own city, but couldn’t find a simple, privacy-friendly tool for it.
Built with SvelteKit + Firebase, it supports hierarchical location codes so users can see relevant questions from their country, region, or neighborhood.
Currently live and free to try — I’d love your feedback, bug reports, and ideas for new features!

value: Show HN: AskSpot – Ask and Answer Questions with People in Your Area

author: MakotoCroCop


value: adiasg

value: Show HN: Robot Data Augmentation – Multiply training data with new environments

author: adiasg


value: debba

value: Show HN: Rewindtty – tiny terminal session recorder

author: debba


value: ashitlerferad

value: Built a simple hurricane and weather tracker focused on the Eastern Caribbean islands I call home. It updates automatically with the latest NHC and OWM data, includes an interactive map, and lets you quickly check conditions for multiple islands as well as CPA. I suck at UI, so feedback and suggestions on how to make this more useful and easy to use are welcome.

value: Show HN: Hobby hurricane tracker for my islands

author: ashitlerferad


value: Timothycquinn

value: An alternative model for generating clean back-end python logic with strictly enforced error codes, result validation and with clean business logic for maximum code path coverage. Inspired by Functional programming result paradigms.

value: Show HN: QResult – Another Result Model for Python

author: Timothycquinn


value: lukaesch

value:
I’ve been working on a way to connect Claude (and other Model Context Protocol clients like ChatGPT) to a large index of public and user-uploaded audio.
The result is a Remote MCP server for Audioscrape that lets an AI assistant query and return relevant segments from:
Popular podcasts
Court hearings
Earnings calls
Any audio you upload yourself
Example query:
"What is Joe Rogan saying about Germany on his podcasts?"
The MCP server handles the transcription index and exposes a search_audio_content tool. Claude then calls it and surfaces exact matching moments from the audio.
Tech notes:
Server: Remote MCP spec implementation
Search: Full-text index over transcripts
Client: Works with Claude Desktop, Mobile, Web MCP support
Data: Combination of public audio sources + user uploads
Docs & setup:
Claude setup: https://www.audioscrape.com/docs/claude-setup
MCP server details: https://www.audioscrape.com/docs/mcp
I’m curious how others might extend MCP for searching non-text data sources - especially if you’ve tried integrating AI assistants with large datasets outside the usual APIs.

value: Show HN: Search Podcasts, Court Hearings, and Earnings Calls via Claude's MCP

author: lukaesch


value: SHOW HN: I made a 30fps CLI Tetris game in PHP after watching the Tetris movie


value: aaronlumsden

value:
Got tired of complex Python AI frameworks requiring tons of boilerplate. Built this Laravel package where agents are just classes - no registration, no configuration files, just define and use:

  class RefundAgent extends BaseLlmAgent {
      protected array $tools = [ProcessRefundTool::class];
  }
  RefundAgent::run('process refund for order 123')->go();

Auto-discovery handles everything. Ships with evaluation framework for testing agents at scale, persistent memory, sub-agent delegation. We use it in production for customer support automation.
Works with OpenAI, Anthropic, Gemini, Ollama + more. MIT licensed.
Happy to answer questions about why we chose PHP/Laravel for AI agents!
The snippet is concise but shows the controller-like simplicity perfectly.

value: Show HN: We made AI agents as simple as Laravel controllers

author: aaronlumsden


value: Donder

value:
Hi HN! I'm Ilya, creator of Localit.io - a translation management system for dev teams who are tired of expensive tools like Lokalise and Phrase.
The problem: Traditional TMS solutions charge $100-2000/month for basic localization features. Complex setups take hours, and many charge extra for Git integrations.
What we built:
- Direct GitHub/GitLab/Bitbucket integration (including Enterprise)
- AI translations via ChatGPT, DeepL, Google Translate
- Professional translators through Gengo
- Built-in team chat with message translation
- Mobile app for remote translators
- Same features as competitors at 10x lower cost
Technical details:
We support all major file formats (.json, .xml, .strings, .po, .srt), handle complex plural forms, and offer webhook automation. Setup takes minutes instead of hours.
Why we built this: After paying $500+/month for basic localization tools at my previous company, I realized there had to be a better way. We've made enterprise features free and focus on developer experience.
Current status: Live with paying customers, growing 50% monthly. Recently launched GitHub Enterprise support.
Would love feedback from the HN community! What's been your biggest pain point with localization tools?
Try it free: https://localit.io

value: Show HN: Localit.io – Fast, affordable translation management with integrations

author: Donder


value: SidDaigavane

value: Show HN: Block your favorite doomscrolling apps until you hit your step goal

author: SidDaigavane


value: samdychen

value: This tool is inspire by this post https://news.ycombinator.com/item?id=44896690

value: Show HN: TextPic – Create text graphics for social media post

author: samdychen


value: prohobo

value:
Heya, I just launched this app for Shopify which utilizes AI agents to generate deep insights about your store using Shopify API and session tracking data. The point is to create something for overwhelmed or new store owners who don't have time to dig through dashboards and try to understand metrics and charts.
The key thing here is: this isn't a chatbot. It's not some quick AI flip, it's building a detailed ecommerce report and running it through an optimized AI pipeline to extract as much useful and actionable info as possible, with full lifecycle management.
I really wanted to do something ambitious with AI agents that I haven't seen before, and was inspired by this article: https://uxmag.com/articles/secrets-of-agentic-ux-emerging-de...
There's something about the guided UX that I think really helps get AI conversations started especially when you don't even know what to ask. Part of the value of Scryer is surfacing questions themselves.
I hope this is useful for people, and while it's totally experimental and will get things wrong - AI is great, but still has a ton of flaws - I'm working hard to surface real useful insights for store owners.
Thanks!

value: Show HN: Scryer – AI Ecommerce Analyst for Shopify

author: prohobo


value:
I wrote about why AI provenance — tracking the “origin story” of AI-generated text, images, and code — is essential for fighting misinformation, ensuring compliance, and protecting intellectual property.
The piece covers metadata, audit trails, and current standards (like C2PA) that could make provenance verifiable across platforms. I also included a simple flowchart illustrating the provenance flow from prompt to output.
Would love to hear feedback on where provenance standards should head next.

value: Show HN: The Case for AI Provenance – Trusting the Source in AI Content


value:
Hey HN,
We've got something that 1) isn't an AI whirlygig and 2) has hit a certain usability threshold that seems like it could fill a handful of niche needs.
Woolean is a minimalist pairwise comparison app. Add a list of items (text, HEX codes, images, audio files, etc) and click Start Comparing to cast votes on all the possible 1v1 matchups.
@maguay and I built this for our own use cases (him for picking the best photograph when they all look too similar, me for ranking microcopy variations). It feels so much easier to chunk lists into a handful of this-or-that votes instead of attacking everything everywhere all at once. If that doesn't make sense to you, try a pre-made comparison, like Apple Bootup Sounds: https://woolean.com/?id=ZvR6aq2q
There are other apps that do this, but they're mostly Do-Everything suites of features when all we wanted was the pairwise framework.
Consider Woolean in beta. It likely has bugs, but should be MVP level.  You can create text comparisons without logging in, or can upload photos/audio/spreadsheets (and keep track of the comparisons you’ve made) if you signup with Google auth, which is 100% free.
If there's enough interest in building out more features (while retaining the minimalist, pairwise focus), we would love to keep hacking on this. Let us know what you think!

value: Show HN: Woolean – Pairwise comparisons without any LLM features


value: ankitladhania

value:
Hi Hackers,
I had been struggling to install and use local MCP Servers, setting up auth, env, etc. seemed so non-intuitive. And getting it adopted by non-tech colleagues was harder.
So, I hacked around and built Oppie.
1. it works in the serverless model, you just select which MCP servers you want to use and start using it, no deployments required.
2. authenticate using OAuth (even STDIO based MCP servers are OAuth enabled).
3. No more local setup, its hosted in cloud so usage for non-tech community members is easier.
4. Powered through community MCP servers (Be it SSE or STDIO servers, we support all).
As we are still in Preview, you can use the Platform for free.
Sign Up: https://oppie.ai

value: Show HN: Serverless MCP Servers (Use All Your Fav. MCP Server in 1 Click)

author: ankitladhania


value: enadzan

value:
I needed real-time updates in a web UI whenever PostgreSQL table rows change, so I built PgHook. It's a 23 MB Docker image (10.1 MB compressed), .NET9 AOT-compiled, that streams logical replication events and sends them to a configurable webhook.
In my setup, the webhook converts events to SignalR messages that push updates to the UI.
I know about Debezium but I needed something minimal, and I like playing with csharp.

value: Show HN: PgHook – Docker image that streams PostgreSQL row changes to webhooks

author: enadzan


value: reikuu

value:
I love Clay, but for a solo founder it was overkill—most features I didn’t need, and the price was hard to justify.
So I built my own enrichment tool: EnrichSpot. It handles the exact workflows I use daily for lead research, prospecting, and automation, but at a fraction of the cost.

value: Show HN: I built a personal Clay alternative to save over $3k/year

author: reikuu


value: Show HN: tiny-cookie-session - Tiny session library that detects cookie theft


value: yukieliot

value: Mobile View Switcher is a Chrome extension that emulates mobile (Android/iOS) view in your browser. I like using it because websites often send less data to mobile users — perfect for saving internet when you're on a tight plan.

value: Show HN: Mobile View Switcher Chrome Extensions

author: yukieliot


value: ShadowUnknown

value: A browser-based button builder that lets you design buttons visually and copy clean CSS instantly. Adjust colors, borders, shadows and hover effects with live preview. Includes a built-in HEX color picker for quick color conversion. No signup and free.

value: Show HN: A Button Builder – Design and Copy CSS Instantly

author: ShadowUnknown


value: mzagaj

value: We recently did a major rework of Paddler (pretty much rewrote the llama-server from llama.cpp to make it distributed and scalable). It also supports live model swapping, custom chat templates, and other useful stuff.

value: Show HN: Paddler – open-source LLMOps platform for hosting AI in your own infra

author: mzagaj


value: thisismehrab

value:
I built a keyword research tool to help find low-difficulty keywords without paying $100+ a month for tools like Ahrefs or SEMrush.
It uses data from one of the big-name SEO platforms, so the metrics (search volume, difficulty, CPC) are accurate. You can:
1. Enter your own keywords to get metrics
2. Use the AI feature to generate new keyword ideas from a seed topic
It’s part of the SaaS I’m developing, but I wanted to make it free before launching our full product to get some real feedback.
love to hear your thoughts on the tool’s accuracy, ease of use, and any features you think would make it better.

value: Show HN: I built a free keyword research tool with AI suggestions

author: thisismehrab


value: raxrb

value:
I'm tired of using the keyboard that is there on the Android.
The voice part is not very good, so I am thinking from scratch what should be the voice native keyboard looks like.
I just launched the app. It is in beta. Anyone interested to try it out? Let me know or reach out to me on rahul[@]dictationdaddy.com

value: Show HN: Reimagining keyboard to be Voice first [video]

author: raxrb


value: cjus

value: Show HN: Open-Source Framework for Your Analytical Back End in Code

author: cjus


value: danielVi

value:
I’ve shipped a big performance upgrade to Sarpro, an open‑source Rust tool for converting Sentinel‑1 SAR GRD products into GeoTIFF or JPEG. Since my initial post [here](https://news.ycombinator.com/item?id=44872768), Sarpro now avoids full‑resolution I/O when you only need a smaller output and performs reprojection in‑process without writing giant temporary files.
Highlights:
- Target‑size reads and single‑step warp: read/warp directly to the final output size instead of loading full‑res first. This cuts I/O and memory by 5–20× for small outputs.
- Reprojection to any CRS: `--target-crs EPSG:xxxx` with in‑process gdalwarp via VRT (no temp GeoTIFF). Resampling: nearest/bilinear/cubic/lanczos.
- Faster autoscaling: O(N) histogram‑based percentiles replace O(N log N) sorting.
- Batch + GUI: both now honor reprojection/resampling in batch mode.
- Performance: on a modern laptop (M4Pro12), scaling a dual‑band ~400–500MP GRD to 2048 px typically completes in ~1–2 s; no‑warp downsamples can be sub‑second. Full native warps remain tens of seconds as expected.
Features:
- CLI, GUI, and Rust API
- Synthetic RGB from polarization pairs, robust autoscaling, optional padding
- TIFF and JPEG outputs with georeferencing/sidecars, metadata emission
I’d love feedback from the RS/EO community: more RGB presets, additional processing modes, tiling for ML, and cloud pipeline integrations.
Links:
- GitHub: `<a href="https://github.com/bogwi/sarpro" rel="nofollow">https://github.com/bogwi/sarpro</a>`
- Previous HN thread: [Show HN post](https://news.ycombinator.com/item?id=44872768)

value: Show HN: Sarpro – 5–20× faster Sentinel‑1 GRD → GeoTIFF/JPEG

author: danielVi


value: kevintouati

value:
Hey HN!
We just launched HERO 2.0 - collaborative workspace combining the flexibility of text, the structure of databases and the power of integrations.
It's built for teams who write formal, structured documents like legal contracts, technical specs, SOPs, and policies.
This project is the result of many years acting as corporate lawyer and mega-project specialist, navigating through the maze of complex, high-stakes, structure-heavy & interconnected documents - overlapping the legal, financial and technical.
It's all about bridging the disconnect between transactional teams and operational ones.
You can try it now at [myhero.so](http://myhero.so/) and let us know what you think!
Best,
The HERO Team

value: Show HN: Hero 2.0 – Notion for formal docs

author: kevintouati


value: Show HN: BuildOrNot.io is a data-driven platform to validate AI startup ideas before you build. We analyze traffic data from 100K+ AI tools (e.g., OpenAI, Hugging Face, Midjourney) to uncover market trends, growth opportunities, and competitive insights. Features include real-time data updates, a comprehensive AI tools database, and actionable analytics to identify high-potential projects. With 5B+ monthly visits tracked and 1,200+ user reviews (4.9/5), it’s helped entrepreneurs and investors discover breakout AI opportunities. Join 750+ users and get premium features free for the first 1,000 sign-ups (250 spots left). Curious to hear your feedback!

value: Show HN: Buildornot.io – Validate Your AI Startup Idea with Real Traffic Data


value: isusmelj

value: Show HN: Distill DINOv3 into your own model

author: isusmelj


value: Show HN: Hacking brainwaves using Open Source


value:
Hey HN,
Co-founder of Kommander here. For years, my co-founder and I have been frustrated by the constant context-switching of development: you're deep in code, then you have to stop, open a browser, and search for that one specific ffmpeg flag or the right rsync syntax.
We loved the idea of AI in the editor (like Cursor) but wanted that power directly in the terminal, where so much of our work happens.
So we built Kommander. It's a simple, open-source Python tool that lets you type what you want to do in plain English (kom ask "create a new python project, init git, and add a .gitignore"), and it generates the shell script for you. Crucially, it never executes anything automatically—it shows you the script first and asks for your approval.
It's cross-platform (PowerShell on Windows, bash/zsh on Linux/macOS) and uses Google's Gemini API (you bring your own key, which you can configure easily).
The project is MIT licensed and we just pushed v1.0.0 to PyPI (pip install kommander-cli).
We'd be honored to get your feedback. What do you think? Any and all thoughts are welcome!

value: Show HN: Kommander – Open-source CLI that turns natural language into commands


value: macabeus

value:
Hey, ever wanted to fully understand or tweak a nostalgic game that you love?
So, I’m documenting my journey on matching decompiling a retro game, step by step, using AI and self-made tools. Three chapters are done, and the fourth is in progress.
Matching decompilation is a fun reverse engineering challenge that paves the way to learn more about a game and fully customize it.
Let me know your thoughts about my posts and the VS Code extension that I'm developing, called Kappa!
Have you ever heard of matching decompilation, by the way?

value: Show HN: Development Journey on Game Decompilation Using AI

author: macabeus


value: gusye

value:
Hey HN,
I'm Gus. I built Memobase, an open-source memory backend that works like ChatGPT Memory.
I know everyone is quite tired of the term "Memory System" recently. I was among the earliest developers who disliked this concept (maybe starting in August 2024? When mem0 popularized the concept). Back then, I felt that chatbots/agents were originally clean state machines, and everything became chaotic after introducing a memory layer.
However, I later realized that although the term "Memory" seems to be a very general solution, it actually needs to be somewhat related to the business scenario. What first changed my mind was when ChatGPT officially emphasized its memory in 2025 [0]: I observed that so many users felt delighted because of the memory.
At that time, I thought that perhaps for consumer-facing chatbots aimed at consumption, entertainment, and life scenarios, memory might be an important feature after all. In this context, I believe the memory system should meet the following requirements:
- Low online latency: Consumers will rarely choose a product because of its "memory" capability, but they will immediately abandon it if the first-token response time takes too long. Memory should enhance user experience, not eat into the initial response time. It was not supposed to be the core of a product anyway.
- Modeling user instead of searching data:  For consumer applications, 99% of queries are not asking AI "what did you say before?" People want proactive associations, not passive search results. Instead of spending efforts on conversation RAG, it might be more effective to refer to the bio tool[1] in ChatGPT and maintain a global user profile of 500-1000 tokens.
This is also why I appreciate the design of ChatGPT Memory: They know what they aim for. You don't notice much latency, yet it can answer questions like "What kind of person do you think I am?" -something search alone can't solve. That's when I realized that memory for consumer AI should be quite different from those open-source memory systems filled with "embedding," "graph," "weight decay," "temporal relationship," etc. A simple approach can be enough.
This is also why I built Memobase:
- Built with pure Python: easy to read and modify. Only depends on Postgres and Redis
- User Profile/Timeline: Each user has an automatically modeled and updated profile (kept under ~1000 tokens) plus a chronological event timeline.
- Highly customizable: You can define any profile dimensions and preferences of memories, rather than letting AI decide what should or shouldn't be remembered.
- Context API: Memobase will directly return the user's personal context as a prompt string,  which you can directly insert into your system prompt as a supplement to user information. By default params, its latency is below 100ms.
We've also run some benchmarks. For example, on the LOCOMO dataset,  Memobase achieved an overall  accuracy of about 74-75%[2] (vs. mem0 68%[3]). However, I also want to point out that such benchmarks are not suitable for testing whether a memory system can enhance your product's user experience.  In most public test results, ChatGPT Memory scores are frustratingly low, yet in reality, it is the only memory to have a widespread impact on users.
This is also why I am confident in Memobase: its underlying structure is so simple, customizable and fast. It is a solution I developed after observing what works in ChatGPT memory. If you also want to create a consumer-facing AI product similar to ChatGPT, I hope you can check out Memobase on GitHub.
Check it out on GitHub: https://github.com/memodb-io/memobase
[0]: https://x.com/sama/status/1910380643772665873
[1]: https://www.reddit.com/r/ChatGPT/comments/1fzq4uc/what_is_bi...
[2]: https://github.com/memodb-io/memobase/tree/main/docs/experim...
[3]: https://mem0.ai/research

value: Show HN: I love ChatGPT Memory, so I built one

author: gusye


value: albrechtchris

value:
Drop Date delivers song recommendations to your calendar, not your inbox.
I wanted to write and self-distribute a music newsletter, but email just felt too heavy and people's inboxes are already cluttered.
So instead I built it so you subscribe through your calendar. Add the URL and twice a week a gentle event reminder comes up showing you the song for that day.
It includes a brief story about the song and a link to Spotify and YouTube. And if you want to stop receiving it, you can just unsubscribe straight from your calendar. No muss, no fuss.
It's also free. Give it a spin and let me know what you think. (please)(and thank you!)

value: Show HN: A newsletter you get as calendar events, not emails

author: albrechtchris


value: pllu

value:
Hi HN! I've been working on a tool to auto-generate a comprehensive developer guide for AI agents working with your codebase.
It analyses your codebase against structured architecture patterns and development capabilities, producing a markdown document that maps out:
- Your architecture (code layout, application layers, frameworks, standards)
- Development capabilities (how to interact with servers, read logs, run scripts, access test data, debug)
- Guidance for continuous improvement as your app evolves
It takes minutes to try: run the generator prompt in your workspace using Claude Code, Cursor, or any AI coding tool (works best with extended thinking models). You can use the output in rules files like CLAUDE.md or .cursor/rules.
The tool is technology-agnostic, so should work for a wide range of apps, tools, services and libraries. There's a plugin system that gives the generator hints about technology-specific documentation (SST v3 plugin included as an example).
GitHub: https://github.com/martinpllu/agent-dev-guide
Example output: https://github.com/martinpllu/agent-dev-example/blob/main/ag...
I'd love feedback from anyone trying this out.

value: Show HN: Agent Dev Guide – Generate structured context docs for AI coding agents

author: pllu


value: getToTheChopin

value:
I'm experimenting with a musical instrument design, using hand rotation to change tempo and note cycles.
Created with javascript, mediapipe computer vision, tonejs, threejs.
This runs in real-time in the browser.
Live demo here (requires webcam access): https://www.funwithcomputervision.com/radial/

value: Show HN: Turning Hand Movement into Music

author: getToTheChopin


value: sammycage

value: Hi everyone, I built PlutoPrint because I needed a simple way to generate beautiful PDFs and images directly from HTML with Python. Most of the tools I tried felt heavy, tricky to set up, or produced results that didn’t look great, so I wanted something lightweight, modern, and fast. PlutoPrint is built on top of PlutoBook’s rendering engine, which is designed for paged media, and then wrapped with a Python API that makes it easy to turn HTML or XML into crisp PDFs and PNGs. I’ve used it for things like invoices, reports, tickets, and even snapshots, and it can also integrate with Matplotlib to render charts directly into documents.<p>I’d be glad to hear what you think. If you’ve ever had to wrestle with generating PDFs or images from HTML, I hope this feels like a smoother option. Feedback, ideas, or even just impressions are all very welcome, and I’d love to learn how PlutoPrint could be more useful for you.

value: Show HN: PlutoPrint – Generate Beautiful PDFs and PNGs from HTML with Python

author: sammycage


value: brettatoms

value: Clojure Land is a simple website intended to help with  discovering open-source Clojure projects.

value: Show HN: Clojure Land – discover open-source Clojure projects

author: brettatoms


value: rasengan

value: This is the repository for the Zero Trust VPN code run by VP.NET that allows you to verify that the servers are running the same code as the repository using Intel SGX for hardware guarantees.

value: Show HN: A Provably Zero Trust VPN

author: rasengan

title: Show HN: A Provably Zero Trust VPN


value: larsiusprime

value:
I'm the maintainer of OpenAVMKit. It's a free and open source toolkit for real estate mass appraisal. I want to make it easier for analysts, researchers, and assessors to build automated valuation models (AVMs) from public data sources. It's in early development, but has reached a stage where it's useable and I'm gathering public feedback.
Stuff it can do:
- Data enrichment: add additional data from public sources like OpenStreetMap, Overtrue, US Census, USGS, or your own shapefiles
- Modeling: run many different algorithms, such as MRA, GWR, LightGBM, XGBoost, CatBoost, as well as ensembles, all through one interface
- Reporting: generate IAAO (International Association of Assessing Officers) compatible ratio studies and other statistics and graphs
- Reproducible workflows: build data pipelines out of input data and settings file, so the same person can reproduce your work on another computer starting with the same ingredients
There's a "getting started" section in the docs with a minimal example that should let you download the test jurisdiction and run through the basic example notebooks.
I'm looking for feedback on what features people are the most interested in and what kinds of tutorials/documentation would be the most helpful for me to focus on.
The official site is here:
https://www.openavmkit.com
The github is here:
https://www.github.com/larsiusprime/openavmkit
We also have a bit of a writeup on it here:
https://progressandpoverty.substack.com/p/openavmkit-a-free-...
Happy to answer any questions in the thread.

value: Show HN: OpenAVMKit – open-source toolkit for real estate mass appraisal (AVMs)

author: larsiusprime


value: janwilmake

value:
Hey HN! I've always been frustrated by having to follow people across 10 different platforms just to catch what they actually say. Lately I've quit following other media entirely and am just hanging out on twitter, but the amount of things I'm missing is vast, I'm sure.
Recently I started playing with this new API from Parallel AI that let's you do super deep web research and collect tons of datapoints at once. Today I tried to solve my own problem and built Based People using the Task API.
*Features:*
- Finds and tracks public appearances – podcasts, conferences, congressional hearings, interviews, fireside chats, and blogs for 160+ influcential tech people
- allows you to follow any of them and build a public appearances feed for yourself
It took me a little trial and error and I spent over $200 (should've tested with small test-set longer), but overall I am really impressed how far webscraping has come (they beat GPT5 in their own benchmark). Repo is linked from the footer for more details.
*Current limitations:*
- Only covers 2024-present (historical data was too much for the AI)
- Does not refresh automatically yet, will need a daily or weekly update with a cronjob
Show HN: I built a directory of public appearances of tech people across the web
Right now it's free to use, no signup required to browse. It's also open source if you're curious. Next steps are verifying/improving data quality and deepening the dataset.
Would love your feedback on the concept and execution!

author: janwilmake


value: cristinon

value:
Free. Self-Hosted. Open Source Collectors. Bring Your Own LLM.
I built TimeBrain since I wasn't satisfied with existing activity trackers. I wanted to understand what I spent my day working on, while remaining in control of my data, and without spending hours trying to decipher crowded graphs.
You can try the demo with test data: https://demo.timebrain.io
If you are interested in participating in the beta I will be releasing invite codes to download the full version on the Discord, which you can find on the site.
Please let me know any feedback or your opinions on my product :)

value: Show HN: TimeBrain – Self-Hosted AI Activity Tracker

author: cristinon


value: joshu

value: Show HN: My TED talk about making mistakes with plotters

author: joshu


value: xmasterdev

value:
I built CleanMyUSB to solve a problem: macOS leaves hidden files all over USB drives, causing issues when using them with Windows PCs, car stereos, cameras, and other devices.
Real problems it solves:
  - USB drives not playing music in car stereos (thanks .DS_Store!)
  - Windows users complaining about "junk files" when sharing
  - SD cards showing "file error" in cameras
  - Can't delete Spotlight indexes on exFAT drives
What it cleans:
  - .DS_Store files: The culprit behind "USB not recognized" in car stereos
  - Spotlight indexes (.Spotlight-V100): Wasting space and useless on other systems
  - AppleDouble files (._): Resource forks that clutter Windows folders
  - System junk: .Trash, .fseventsd, .Trashes hidden folders
  - Temp files: .tmp, .cache, .log and various temporary files
  - Cross-platform conflicts: Thumbs.db, desktop.ini, System Volume Information
Technical approach:
  - Real-time USB/SD card detection with auto-cleanup prompts
  - Smart file recognition to protect important data
  - Special exFAT filesystem handling
Why I built this:

  Got tired of manually cleaning USBs before giving them to Windows users. Got tired of
  troubleshooting why car stereos won't read my USB. This tool eliminates these annoying
  little frictions.

Pricing & Availability:
  $9.99 one-time purchase, 7-day free trial.
Important Note: Due to App Store sandbox restrictions, the Mac App Store version cannot
  clean certain system files (.Spotlight-V100, .fseventsd, .Trashes). The direct download
  version from our website has full functionality. If you previously purchased the App
  Store version and need the full functionality, please contact me and I'll provide you
  with a free license for the direct version.
Website: https://cleanmyusb.app
Would love your feedback!

value: Show HN: I built an native macOS app to clean junk files from USB drives

author: xmasterdev


value: jmorf

value:
I built LDNS because I'm constantly curious about domain names - who owns them, which nameservers they use, how they're configured, and what their DNS records reveal. I wanted a fast, easy way to investigate domains right from my browser without juggling multiple tools.
LDNS runs entirely client-side using Cloudflare's DNS over HTTPS. Just type a domain and instantly see:
All DNS records with clickable filtering
RDAP/WHOIS data with registrar info and expiration dates
Email security configuration (SPF, DMARC, MTA-STS, BIMI)
Export options (JSON, CSV, BIND zones, PDF reports)
Try it at ldns.com - just append any domain like ldns.com/example.com to start investigating.
Built with SvelteKit and deployed on Cloudflare Pages for that instant-load experience we all love.
Comments, feedback, and feature requests welcome!

value: Show HN: Ldns.com – fast DNS lookups from the URL bar

author: jmorf


value:
Purpose - Fun lightweight counter that shows how much money you've earned in real time. Might be motivational to keep in the background while you work away.
Background - ~3 day project for non-technical person wanting to explore using AI. Stack is next.js/typescript/css, uses vercel & github to deploy. Last time seriously coding was a decade ago. Cursor/AI-assistance was a joy to build with and probably 10x'd my ability to deliver. Was my first time using next/java/typescript. Past exp was with django+python
Some features/limitations

  - Added the ability to handle GET parameters to share links with friends
  - Could count anything really - added tuition to motivate students, as well as the national debt
  - Added hours/week to more accurately handle non-standard work weeks when picking a start-time in the past
  - Assumes standard 5-day work week

Next steps

  - Monetize/advertise?
  - Start on the next project!

Open to feedback and Qs!

value: Show HN: Countmeup – Simple counter to watch yourself earn money in real time


value: Show HN: Open-Source Character.ai Alternative with Ollama and Groq API Support


value: markogg

value:
Hello everyone!
To briefly introduce myself, I'm mainly a backend developer, working in the industry for the past 7 years.
On one of the products I was working on we were heavily using a custom feature flagging system. Basically, any functionality we were building was starting with a new feature flag. It was useful because:
1. We were able to silently deploy a feature to production for real environment testing
2. We would enable feature flag for specific users across our team, like marketing, sales, so everyone can check it out, test and prepare for the release
3. We were restricting certain features across pricing plans or organizations
4. We were sometimes initially only releasing to customers that requested the feature, or a small group
There were more use cases, but all in all, feature flagging was deeply integrated in the product.
As someone who has a lot of experience with this topic, I decided to build a new feature flagging tool in a way how I would imagine it to work.
Additionally, I always wanted to go on a journey with my own product, going through the entire process from seeing an empty page on my localhost to having a finished, well documented and working product.
The product is now live and working, although still with a "Beta" badge as it lacks some real-world testing.
The stack I'm using:
1. Laravel framework for the main app with Interia.js and Tailwind CSS for styling
2. Postgres/Redis for data storage
3. Astro for the marketing website and (Starlight) for the documentation
The main app is deployed on Hetzner with Kubernetes.
One of the main issues I was worried about is the latency, as flags evaluation must be fast otherwise it is not very appealing to use an external tool for that. I solved it by caching evaluations on Cloudflare Edge network close to users around the world. I've set up a worker that is responsible for managing the flag evaluation content. I have some ideas to improve this approach in future, but for v1 I think it does a pretty good job.
Marketing website is also on Cloudflare worker.
I would like to invite you to try it out and provide some feedback if you have, at https://fecusio.com/
To understand how the product is intended to be used, you can read the Quickstart guide: https://fecusio.com/docs/quickstart/quickstart/
Thanks!

value: Show HN: Fecusio – Feature flagging and release management tool

author: markogg


value: camil

value:
Hi HN,
I’ve been working with Kubernetes for over a decade, since the alpha days, and was involved in kube-aws project before AWS launched EKS. For the past four years, I’ve been helping friends and small businesses cut costs by running Kubernetes on Hetzner Cloud, which I’ve found to be rock solid and by far the best priced provider.
Provisioning a cluster on Hetzner is now straightforward, thanks to tools like k3s and hetzner-k3s, but configuring it for your specific needs still takes time and expertise. I built Edka to make that part easy: spin up a production ready cluster in ~2 minutes, then choose how low level or automated you want to go.
How it works:
Layer 1 – Cluster provisioning
 - Creates a k3s-based Kubernetes cluster on Hetzner (lightweight, easy to manage, scales well).
Layer 2 – Add-ons
 - One-click deploy for metrics-server, cert-manager, and various operators; preconfigured for Hetzner, no extra setup needed.
Layer 3 – Applications
 - Minimal config UIs for apps built on top of add-ons.
 - Example: Need PostgreSQL? Fill a few fields → platform installs CloudNativePG → provisions HA PostgreSQL with PITR → gives ready to use endpoints. Backups can be restored to any point in time with a click. Quick demo: https://edka.io/apps/
Layer 4 – Deployments
 - Connect your CI to push container images to a public/private registry.
 - Edka updates deployments automatically (with semantic versioning rules), supports instant rollbacks, autoscaling, persistent volumes, secrets/env imports, and quick public exposure. Quick demo: https://edka.io/deployments/
Tech stack: TypeScript, React + Tailwind CSS, PostgreSQL, Redis, BullMQ, Vault + AWS KMS to encrypted sensitive data.
The platform is still in beta and I’m building it in my spare time, so there are some rough edges, but I’d love feedback from anyone running Kubernetes on Hetzner, exploring alternatives to EKS/GKE/AKS or looking to automate their infrastructure with Kubernetes.
More details: https://edka.io/
Thank you!

value: Show HN: Edka – Kubernetes clusters on your own Hetzner account

author: camil


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