value: chenglong-hn

value:
Hi everyone, we are excited to share with you our new release of Data Formulator. Starting from a dataset, you can communicate with AI agents with UI + natural language to explore data and create visualizations to discover new insights. Here's a demo video of the experience: https://github.com/microsoft/data-formulator/releases/tag/0.....
This is a build-up from our release a year ago (https://news.ycombinator.com/item?id=41907719). We spent a year exploring how to blend agent mode with interactions to allow you more easily "vibe" with your data but still keeping in control. We don't think the future of data analysis is just "agent to do all for you from a high-level prompt" --- you should still be able to drive the open-ended exploration; but we also don't want you to do everything step-by-step. Thus we worked on this "interactive agent mode" for data analysis with some UI innovations.
Our new demo features:
* We want to let you import (almost) any data easily to get started exploration — either it's a screenshot of a web table, an unnormalized excel table, table in a chunk of text, a csv file, or a table in database, you should be able to load into the tool easily with a little bit of AI assistance.
* We want you to easily choose between agent mode (more automation) vs interactive mode (more fine-grained control) yourself as you explore data. We designed an interface of "data threads": both your and agents' explorations are organized as threads so you can jump into any point to decide how you want to follow-up or revise using UI + NL instruction to provide fine-grained control.
* The results should be easily interpretable. Data Formulator now presents "concept" behind the code generated by AI agents alongside code/explanation/data. Plus, you can compose a report easily based on your visualizations to share insights.
We are sharing the online demo at https://data-formulator.ai/ for you to try! If you want more involvement and customization, checkout our source code https://github.com/microsoft/data-formulator and let's build something together as a community!

value: Show HN: Data Formulator – interactive AI agents for data analysis (Microsoft)

author: chenglong-hn


value: jwesleyharding

value:
I'm sharing a simple utility I worked on to make evaluation of structured outputs from LLMs a bit simpler.
For context:
When evaluating structured outputs, you often want to composable comparison logic to allow for meaningful comparison across different types of outputs (free text, enums, ints, and all the other json tyeps). You also want to compare arrays as a multisets -- order-agnostic pairwise matching across elements in sets.
What it is:
This CLI and python library (I called "structeval" but not to be compared to the LLM eval framework with the same name -- I may change it!) supports order-agnostic pairwise matching, customizable comparison logic, and recursive metric aggregation. It can also be used to compare outputs when sampling from an LLM with N>1 to measure semantic entropy or find the "median" result. As it works as a generic json tool without requiring a schema, it could also be applied, at least in principle, as a more configurable (and quirkier :) ) alternative to a generic diffing tool like jd.
I had struggled with this task in a few contexts and found I was often rewriting a utility like this, so figured it may be helpful for others if encapsulated in a little library.
But I'm curious if any feedback or suggestions!

value: Show HN: StructEval - a structured output evaluation and comparison tool

author: jwesleyharding


value: stagas

value: Show HN: loopmaster – Live Audio Programming

author: stagas


value: ItsKaranKK

value:
Hey HN,
I'm Karan, a frontend developer who loves creating UIs, but I've found that many people don't like CSS, but they want their website to look beautiful and polished, and what better way to enhance a website than with animations
Animations using plain CSS are tricky, and that's why I leaned towards Motion
a powerful animation library for React, and I built ogBlocks using React, Motion, and Tailwind CSS
I built it for three reasons:
1. Anyone can integrate beautiful animated components into their website without any CSS Skills
2. Developers will save time creating UI components
3. 100% customization (tweak the way you want to fit in your brand's style and even build something on top of it)
I also included a Bonus 107 Page ebook on 100 Tips about HTML, CSS, and JavaScript
Check out the website and tell me what you think about it (It's cool though )
Karan

value: Show HN: OgBlocks – Animated UI Library for CSS Haters

author: ItsKaranKK


value: trubalca

value:
Hey HN, I'm Taylor and today I'm launching Lexical, a language learning app that actually works by teaching the 5,000 most common words in the target language.
Spaced repetition is how I've learned Spanish, French, and Italian in the last 3 years and I couldn't find tools that have the languages that I want to learn in the future, so I built Lexical.
The link goes to my White-Paper describing the language learning philosophy behind Lexical if you just want to try it out you can click "Get Started" at the top of the page. To really experience Lexical at it's best you'll need an account (sorry guys) but I've tried to make it as easy as possible.
I'm a big fan of Hacker News and am looking forward to your comments and hopefully even some beta users.
Here are some old HN posts that inspired my app and white-paper.
Learning is remembering
https://news.ycombinator.com/item?id=32982513
Kanji only requires 777 words
https://news.ycombinator.com/item?id=20721736
Most of language learning is temporary heuristics
https://news.ycombinator.com/item?id=44907531
Duolingo sucks
https://news.ycombinator.com/item?id=45425061

value: Show HN: Lexical - How I learned 3 languages in 3 years

author: trubalca


value: Show HN: Unflip – a puzzle game about XOR patterns of squares


value: funfunfunction

value:
We're releasing Project AELLA - an open-science initiative to make scientific knowledge more accessible through AI-generated structured summaries of research papers.
Blog: https://inference.net/blog/project-aella
Visualizer: https://aella.inference.net
Models: https://huggingface.co/inference-net/Aella-Qwen3-14B, https://huggingface.co/inference-net/Aella-Nemotron-12B
Highlights:
- Released 100K research paper summaries in standardized JSON format with interactive visualization.
- Fine-tuned open models (Qwen 3 14B & Nemotron 12B) that match GPT-5/Claude 4.5 performance at 98% lower cost (~$100K vs $5M to process 100M papers)
- Built on distributed "idle compute" infrastructure - think SETI@Home for LLM workloads
Goal: Process ~100M papers total, then link to OpenAlex metadata and convert to copyright-respecting "Knowledge Units"
The models are open, evaluation framework is transparent, and we're making the summaries publicly available. This builds on Project Alexandria's legal/technical foundation for extracting factual knowledge while respecting copyright.
Technical deep-dive in the post covers our training pipeline, dual evaluation methods (LLM-as-judge + QA dataset), and economic comparison showing 50x cost reduction vs closed models.
Happy to answer questions about the training approach, evaluation methodology, or infrastructure!

value: Show HN: Project AELLA – Open LLMs for structuring 100M research papers

author: funfunfunction


value: AlexNicita

value:
Staying fresh with the "startup stack"... so I made Vocaware.com: an AI voice agent that picks up the phone, talks naturally, takes notes, and connects to your workflows.
It’s built with shadcn/ui + Next.js, Twilio for telephony, OpenAI for reasoning + speech, Stripe for payments, and Supabase + Railway for the backend. Basically a modern full-stack AI app — start to finish — that actually works in production.
Right now you can:
* Get a phone number instantly
* Have an AI answer calls 24/7
* Build agent conversation workflows
* View transcripts, summaries, and analytics in real time
I built it in a few weeks. It’s live and works surprisingly well — but now I’m trying to figure out what’s next:
* Should I pick a vertical (e.g. real estate, service businesses, golf courses, ...)?
* Offer free trials?
* Make it open-source and developer-first?
* Go onsite with customers and implement it?
Would love any feedback, advice, or collaboration ideas from other builders.
— Alex (x.com/NicitaAlex)

value: Show HN: Vocaware – AI Voice Agents (Shadcn, Twilio, OpenAI, Supabase, Next.js)

author: AlexNicita


value: Show HN: Generate Music with AI

title: Show HN: Generate Music with AI


value: cmpx

value:
Hey HN,
We built a wireless, low-profile macropad with a display called the Creavi Macropad. It lasts at least 1 month on a single charge.
We also put together a browser-based tool that lets you update macros in real time and even push OTA updates over BLE.
Since we're software engineers by day, we had to figure out the hardware, mechanics, and industrial design as we went (and somehow make it all work together).
This post covers the build process, and the final result.
Hope you enjoy!

value: Show HN: Creavi Macropad – Built a wireless macropad with a display

author: cmpx


value: avpingle

value: Join data from different sources (upload/sync), build version-controlled & reliable data workflows, clean/analyze/visualize data, and get cleaning/analysis recommendations - all in one place. The platform also helps the user verify correctness of logic through dry runs and clarifying questions. We also just released semantic layer creation. Additionally, we have started with file connectors and are expanding into databases etc. pretty soon.

value: Show HN: Yorph AI – Agentic data platform

author: avpingle


value: aswinmohanme

value:
Hi HN, I am Aswin Mohan(https://aswinmohan.me), a full-stack mobile/web developer. I have been working on WorkBill (https://workbill.co) for the past 6 weeks on the side and wanted to share it here.
demo: https://demo.workbill.co/inbox (no signup needed)
video-demo: https://www.loom.com/share/9775811960ad47d7ada89007d8169d90
WorkBill is the modern, flexible accounting platform for small businesses. It is based on BeanCount(https://github.com/beancount/beancount). You can can add entries, see the chart of accounts, parse bank statements, see the balance sheet and income statement and reconcile transactions manually. We currently only support USD.
Unlike traditional accounting software where you assign a category to a transaction, WorkBill enables you to create nested accounts (Expense:Payroll:Engineering) and represent the transaction as movement of money between these accounts. This enables us to model complex transactions easily, even when we do not have explicit support for them in our platform. This also gives us richer context about each transaction that we can use to do automate most of the grunt-work associated with accounting.
I had been using Beancount to track my personal finances for over 3 years and loved how flexible it was compared to others on the market. I loved it so much that I built a personal finance app based on these principles (https://news.ycombinator.com/item?id=42256125). When I started a Private Limited in India, I looked around for an accounting software, found everything to be lacking or in-flexible and ended up with Beancount again. That is when I decided to build out WorkBill. I have been using it for bookeeping at my own company.
The tech stack is Elixir, Phoenix combined with Inertia JS and React with help from ShadCN and TailwindCSS. It has been an incredibly productive framework. I have not used any AI tools, coded mostly in Zed with little help from ChatGPT.
We are getting started with WorkBill. With a stable accounting core, we can add invoices, bills, AR/AP automation to build the all-in-one financial stack for small businesses.
The grand idea of WorkBill is to build a world where accounting and bookkeeping mostly run on autopilot with accountants stepping in for strategic advice, planning and improving the business. if you would like to be part of that future, I are raising a small pre-seed round as well. You can ping me at aswin@workbill.co for more info.
If you would like an invite, please email aswin@workbill.co. Excited to hear your feedback!

value: Show HN: WorkBill – Modern Alternative to QuickBooks

author: aswinmohanme


value: jumpstartups

value:
Hi HN,
I built SceneReaderAI to help actors and creators hear their scripts read aloud using natural AI voices.
You can try it free (200 words included) here → https://scenereaderai.com
It supports 6+ AI voices, lets you replay your readings unlimited times, and charges only per spoken word (no monthly subscription).
I’d love feedback on:
• How clear the workflow feels
• Whether the pay-per-word model makes sense
• What voices/features would make it more useful for you
I’m the solo builder and launched this earlier this year — would really appreciate your thoughts!

value: Show HN: SceneReaderAI – Hear your script read aloud by AI voices (free trial)

author: jumpstartups


value: jpdpeters

value: I built a curated, invite-only network for founders and senior operators of online marketplaces. A space to connect, exchange hard-won lessons, and support each other - under Chatham House Rules.<p>Let me know if you'd like to join.

value: Show HN: Metcalfe – private network for marketplace operators

author: jpdpeters


value: doppelgunner

value: Show HN: Producthunt Alternative

author: doppelgunner

title: Show HN: Producthunt Alternative


value: Show HN: Skim – 90% token reduction for LLM code analysis


value: rtheunissen

value: Show HN: Factorio Machine Solver

author: rtheunissen

title: Show HN: Factorio Machine Solver


value: negrel

value: Show HN: Simple, dependency-free configuration library for Go

author: negrel


value: jchap

value: Show HN: FastAPI LSP/VSCode Extension POC

author: jchap


value: jviotti

value: Show HN: A commercial standard library for JSON Schema / OpenAPI projects

author: jviotti


value: jundymek

value:
I built a browser extension called FakerFill to help developers and QA testers test web forms faster.
It automatically detects input fields and fills them with realistic fake data (names, emails, addresses, etc.).
The extension focuses on simplicity — there’s no data collection, and everything runs locally in the browser. You can also create and reuse custom templates, choosing which fields to fill and how they’re populated.
Right now, it’s available for Chrome, Edge, and Firefox.
I’d love to get feedback from other developers — both on usability and ideas for future improvements.

value: Show HN: FakerFill – a browser extension that fills web forms with fake data

author: jundymek


value: akdeepankar

value:
I’ve been experimenting with Tambo AI, and ended up building a small project around it called Tambo OS - a virtual desktop that runs entirely in the browser.
It’s built with Next.js, TypeScript, and Tailwind, and uses Tambo’s withInteractable() to let the AI control UI components directly -opening apps, updating data, or even generating new UI elements through chat.
Each app is a registered component, and actions are exposed as tools in tambo.ts. For example, Tambo can:
open the Notepad or Calendar,
add events or notes,
fetch map directions,
edit images via AI prompts.
Each tool in the OS exposes specific actions (like editing an image or adding an event), while each component defines the visual interface the AI can manipulate. This creates a conversational layer over the entire UI, where Tambo doesn’t just respond - it operates the interface.
Everything runs client-side, and you can switch between apps using a floating dock - like a tiny OS inside your browser tab.
GitHub: https://github.com/akdeepankar/tambo-os
Try: https://tambo-os.vercel.app
Docs: https://docs.tambo.co/

value: Show HN: Building UI Interfaces That AI Can Control

author: akdeepankar


value: wiwoworld

value:
Just shipped mcp-framework and wanted to share it here.
It's a production-ready Rust implementation of the Model Context Protocol with blazing-fast performance, showcase tools and examples, and a web-based inspector.
Here's what it does:

  - lets ai agents (claude, openai) use tools you define
  - has a web ui for testing/debugging your tools
  - keeps conversation history so agents can reason across multiple turns
  - includes 8 example tools to get you started instantly

All code examples work, ready for production.
Would genuinely appreciate any feedback.

value: Show HN: MCP-framework – Build MCP servers and AI agents in Rust

author: wiwoworld


value: sgbeal

value:
About 3 years ago i wrote a custom preprocessor to assist in processing the SQLite project's JavaScript builds (e.g. filtering the small differences between vanilla JS and ESM modules). Recently, that app was forked, refactored into a library, and is now, AFAIK, the world's only source-agnostic[^1], client-extensible preprocessor (if one doesn't count sed, awk, etc.).
It's implemented in portable C99 and has a two-file source distribution (one header, one .c file). Its only third-party code dependency is SQLite.
If you've got C-like preprocessing needs, but aren't working with C, c-pp might be of interest.
[^1]: So long as it's UTF-8.

value: Show HN: C-Minus Preprocessor v2

author: sgbeal

title: Show HN: C-Minus Preprocessor v2


value: uhgrippa

value: Show HN: Simple Resume – Generate PDF/HTML/LaTeX Resumes from Simple YAML Config

author: uhgrippa


value: Show HN: AI-Powered Chart Pattern Recognition for Price Movements


value: raviqqe

value: Show HN: Picolight, the 0.5KB syntax highlighting library for dynamic input

author: raviqqe


value: chfritz

value:
I always wanted this: an easy way to reach "resolve docker container by name" -- e.g., to reach web servers running in Docker containers on my dev machine. Of course, I could export ports from all these containers, try to keep them out of each others hair on the host, and then use http://localhost:PORT. But why go through all that trouble? These containers already expose their respective ports on their own IP (e.g., 172.24.0.5:8123), so all I need is a convenient way to find them.
mdns-docker allows you do to, e.g., "ping my-container.docker.local", where it will find the IP of a running container whose name fuzzily matches the host. The way it does it is by running a local mDNS service that listens to `*.docker.local` requests, finding a running container whose name contains the request (here: "my-container"), getting that container's local IP address, and responding to the mDNS query with that IP.
Example: Start a ClickHouse service (as an example) `docker run --rm --name myclicky clickhouse:25.7` and then open `http://myclick.docker.local:8123" to open the built-in dashboard -- no port mapping required!
If you haven't played with mDNS yet, you've been missing a lot of fun. It's easy to use and the possibilities to make your life easier are endless. It's also what Spotify and chromecast use for local device discovery.

value: Show HN: mDNS name resolution for Docker container names

author: chfritz


value: Show HN: Monza Editor, the textarea element with syntax highlight in 1.5KB


value:
I built a tool that gives structured feedback on algorithm solutions using Gemini and Llama models. No signup needed - just paste your code and get analysis on time/space complexity, optimization opportunities, and code quality.
You get 3 reviews to try it out and compare feedback from different AI models. Built with Next.js and Supabase.
Originally planned as SaaS but the market's too saturated, so I'm keeping it free and simple.

value: Show HN: LogicVisor – AI code reviews for algorithm practice


value:
Hey everyone
I’ve been working on Trainly, a Graph-RAG API that helps developers go from raw documents → working RAG endpoints in minutes.
Instead of wiring LangChain, vector DBs, and retrievers manually, Trainly lets you:
1. `pip install trainly`
2. Initialize with your API key
3. Upload your docs
4. Query your endpoint

value: Show HN: Trainly – Simple API for Building Graph-RAG MVPs Fast


value: dlojudice

value:
Hi HN — I built Cursor Cost Explorer after my monthly Cursor bill started creeping up and the official dashboard gave me almost no clue why.
I use a mix of models across sessions, sometimes one long thread, sometimes lots of tiny requests with different models, and one month my usage just ran wild. The Cursor dashboard showed not the patterns that matter: which models I used for which tasks, when cache wasn’t helping, or whether I’d be cheaper on a different plan.
So I exported my Cursor CSV and built a small analyzer that runs locally. The first time I loaded my CSV I could see a bit inside the data: a handful of expensive "thinking" model calls sprinkled across many tiny tasks. That single analysis pointed to a few concrete changes I could make that immediately cut my projected monthly spend.
What it does (short)
- Parse Cursor CSVs and show where money is actually spent (by model, by day, by request)
- Highlight model inefficiencies and cache patterns and give prioritized, actionable recommendations (plan change, model migrations, simple workflow fixes)
- Runs entirely locally — open the demo in your browser or run `npx cursor-cost-explorer` on your machine and your CSV never leaves you, also great for agents.
UIs:
- Web demo: `<a href="https://dalssoft.github.io/cursor_cost_explorer/" rel="nofollow">https://dalssoft.github.io/cursor_cost_explorer/</a>`
- CLI: `npx cursor-cost-explorer <your-cursor-usage.csv>`
Would love feedback.

value: Show HN: Cursor Cost Explorer

author: dlojudice

title: Show HN: Cursor Cost Explorer


value: andybady

value:
I spent 8 months growing a YouTube channel to 50k subs only to realize I was in a $2 CPM niche (gaming commentary). That channel barely made $200/month despite decent views.
So I built ApexVix to solve this for myself and other creators.
What it does:
Scans 400K+ YouTube channels to find what's actually making money (not just getting views)
Shows you the CPM range for each niche BEFORE you waste months creating content
Tracks 4M+ "outlier videos" (videos that popped off unexpectedly) so you can spot trends early
Analyzes any channel in 60 seconds: revenue estimates, health score, posting patterns, what's working
The data that surprised me: Some tiny niches with 10k subs are making $5k/month (luxury watch reviews, B2B SaaS tutorials), while million-sub gaming channels struggle to hit $2k. The difference? CPM rates range from $2 to $50+ depending on niche.
Most creators pick niches based on passion or what's trending on Twitter. Then they're shocked when monetization sucks. I wanted actual numbers upfront.
What's different from VidIQ/TubeBuddy: Those focus on SEO and keywords. ApexVix focuses on money. We show you:
Estimated monthly revenue per channel
CPM ranges by niche and country
Which faceless automation niches are exploding right now
Competitor revenue tracking (not just sub counts)
After using it myself for 6 months, I went from that $200/month channel to starting a new one in financial education that's on track for $3k/month at just 15k subs.
Some early users are finding 3-5 profitable niches they never considered in their first session. One guy pivoted from tech reviews to AI automation tutorials and tripled his RPM.
Recent updates based on feedback:
Added bookmark system for saving promising channels and video ideas
AI-powered content idea generator based on proven outlier formats
Thumbnail analyzer that predicts CTR before you publish
Script optimizer for better retention
Revenue forecasting based on your upload schedule
Would love to hear from other YouTubers here. What's your biggest pain point when choosing content topics? Do you look at monetization potential before committing to a niche?
Free plan available if you want to explore (no CC needed). All feedback welcome.

value: Show HN: Find profitable YouTube niches (I wasted 8 months on $2 CPM)

author: andybady


value: ajke

value:
Hi HN,
I built ClientDock - a client portal for service providers to manage communications and files without email chaos.
Background:
After losing a critical client deliverable in a 200+ email thread, I decided to build a better solution. Most "client portals" are bloated project management tools. I wanted something focused on one thing: making client communication effortless.
Technical Details:
- Built with Next.js 15 (App Router)
- Deployed on Cloudflare Workers using OpenNext adapter
- Cloudflare D1 (SQLite at the edge) for data
- NextAuth v5 for authentication
- Drizzle ORM for type-safe database operations
- React Email and Resend for transactional emails
- Stripe for payments
Architecture Decisions:
1. Edge-first: Deployed on Cloudflare Workers for global performance. Every request is handled at the nearest edge location.
2. Type safety: TypeScript throughout, Drizzle ORM for database type safety
3. Internationalization: Built with next-intl from day one for future expansion
4. Modular auth: NextAuth with Drizzle adapter for flexibility
Interesting Challenges:
- Adapting Next.js SSR for Cloudflare Workers environment using OpenNext adapter
- Managing database migrations with D1
- Implementing granular access controls
- Optimizing for edge deployment
Current Status:
MVP is complete. Looking for feedback on:
- Feature priorities
- Pricing strategy
- Technical architecture
- UX improvements
Open Questions:
1. Should I add real-time collaboration features?
2. How important is mobile app vs responsive web?
3. What's the right pricing model for this space?
The code isn't open source (yet), but happy to discuss technical decisions and share learnings from building on Cloudflare Workers.
Would love your feedback!

value: Show HN: ClientDock – Client portal built on Cloudflare Workers

author: ajke


value: fiddyschmitt

value:
I've just finished a major upgrade to enable tunneling over more file systems: https://github.com/fiddyschmitt/File-Tunnel/wiki
The most popular feature request was to tunnel over S3 buckets. I was surprised it worked. The latency is high (3 seconds) but the bandwidth is high enough to stream a 1080p video from YouTube. Overall, it has similar performance to internet through geosynchronous satellites.
The upgrade took the better part of a year and the trickiest part was catering for the various ways the file systems synchronise. Some are fast, some are picky about open file handles, some require IO operations to be retried.
My favourite aspect of File Tunnel is people using it in ways I never anticipated, such as:

    * Allowing two VMs to communicate without networking enabled (via VirtualBox Shared Folder)

    * Providing internet to a remote RDP session by creating a reverse tunnel to a local SOCKS proxy.

    * Controlling a vending machine through an FTP server meant for beverage logos.

I had a lot of fun making this upgrade. I hope someone finds it useful.

value: Show HN: Tunneling Through S3 Buckets

author: fiddyschmitt

title: Show HN: Tunneling Through S3 Buckets


value: scratchylabs

value: Glitter IDE was designed to be a stepping stone coding environment, between Scratch and more standard text languages (but hopefully will end up being more). It builds on the Scratch execution model (eg, implied concurrent multitasking), but with a text focused language. Includes an image editor, sound creator, and some support for Commodore 64 development, export to Scratch and HTML, and lots of interesting bits "under the hood".<p>Very much an ongoing project, with many plans for future features, such as better image editors (including "retro" editors for C64 and more), tile map support, microcontroller support (eg, Arduino R3, R4, RPi Pico, and BBC Micro:bit), and a hybrid drag-and-drop/text editor (to replace the terrible editor at the moment).

value: Show HN: GlitterIDE The next level Scratch-inspired coding tool

author: scratchylabs


value: Show HN: Chess960^2 is now open source

title: Show HN: Chess960^2 is now open source


value: qwikhost

value: Download all pins, photos, and images from any Pinterest board instantly with one click

value: Show HN: Pinterest Board Saver

author: qwikhost

title: Show HN: Pinterest Board Saver


value: valkev

value: Show HN: CookieFast – a simple, one-time cookie consent manager

author: valkev


value: rhettjull

value:
We built Zylo because most website builders make you think in templates and layouts — not in feelings or intent.
Zylo lets you “vibe-code” your site: you describe what you want in natural language — “a clean modern landing page for a marketing agency with a cosmic purple theme and bold hero text” — and Zylo generates a full site structure, text, imagery, and layout in seconds.
Under the hood, Zylo combines a custom Next.js code generator, visual editor, and AI styling model that learns from thousands of design patterns. You can regenerate sections, swap moods (e.g. “more futuristic” or “more minimal”), or dive into code instantly.
We’re currently in the early stages with a free trial — anyone can sign up and start building in minutes.
We’d love feedback from designers, developers, and indie hackers on what feels intuitive (and what doesn’t).

value: Show HN: Zylo – AI "Vibe-Coding" system that builds websites from a prompt

author: rhettjull


value: BanditCat

value: I've written Atlas, a GPU scripting language that eliminates the boilerplate of managing textures and uniforms. Here are some demos including 4D fractal exploration with gamepad controls. Press 7 to see the Julia set, and try reloading if you see rectangles/it glitches.  Documentation: https://banditcat.github.io/Atlas/index.html      *requires approximately an RTX 3080.

value: Show HN: Real-time 4D Julia set navigation via gamepad

author: BanditCat


value:
A framework where knowledge instances actively participate in learning and reasoning, rather than being passive data.
Key ideas:
- Learn structural patterns through similarity, not gradient descent
- Knowledge reacts to being learned and forms relationships with other knowledge
- Hierarchical pattern matching works with nested structures
- Event-driven responses for compositional reasoning
- Fully interpretable - every decision traceable to learned patterns
Built this after months researching abstract reasoning (ARC challenge) and interpretable systems. Traditional approaches felt too rigid - this uses active, self-organizing knowledge as primitives.
Early stage but core works. Applications: ARC, interpretable AI, few-shot learning, autonomous agents.
pip install general-intelligence

value: Show HN: General Intelligence – Active knowledge framework for machine learning


value: Show HN: Beeholder – Data Observability Platform


value: The article explains how LiDAR-equipped drones attach a laser scanner to capture high-precision 3D point-cloud data, enabling rapid, efficient mapping across diverse terrains. It highlights applications in urban planning, forestry, disaster management, and infrastructure inspection — showcasing how drones are transforming surveying and modeling workflows.

value: Show HN: Autelpilot Drone –Drone Mapping: Lidar Technology


value: stagas

value: Set the mood/genre and sit back, let the AI mix music for you!

value: Show HN: AI is a DJ

author: stagas

title: Show HN: AI is a DJ


value: darkce

value:
Big news! The basic features of Night Vision App are now completely free — only the advanced tools require a one-time purchase.
It used to be a paid app, but now the basic night vision preview is free for everyone. Pro features still require a one-time purchase. Thanks for your support!
Recent Updates:
1⃣ Fully optimized for iOS 26 with the new Liquid Glass design
2⃣ Enhanced night vision performance
The idea for Night Vision App actually came from a moment of curiosity. When I first got my iPhone 14 Pro Max, I noticed a mysterious little dot beneath the rear camera — the LiDAR sensor. I suddenly wondered: could it be used to see in the dark? If LiDAR could be used to map out a scene, maybe real night vision could become possible.
That’s how Night Vision App was born. It combines the iPhone’s LiDAR scanner and TrueDepth camera to create detailed low-light imaging — turning your phone into a professional-grade night vision device.
If you have an iPhone Pro model, I highly recommend giving it a try.

value: Show HN: Night Vision App for iPhone Now Offers Free Basic Features

author: darkce


value: niztk

value: You can adjust inputs and immediately see how the outcome changes. Results include clear success rates, cash-flow charts, and an “Under the Hood” view that shows exactly how the numbers are worked out.

value: Show HN: Free retirement simulators (Monte Carlo and tax-aware planning)

author: niztk


value: Phiality

value:
Screaming Frog costs $259/year per user, has a 500 URL free limit, and crashes on large sites due to memory issues. For agencies with 5+ team members, that's $1,300+ annually.
LibreCrawl is completely free, handles 1M+ URLs smoothly using virtual scrolling
and memory profiling, and includes features even paid tools don't have (multi-session support, custom CSS injection, real-time memory dashboard).
It's MIT licensed and self-hostable for complete data control.
Would love feedback from the HN community!

value: Show HN: LibreCrawl – Open-source SEO crawler with unlimited URLs (Free SF alt)

author: Phiality


value: frxgfa

value: Show HN: FileSSH – A TUI file browser for your remote servers

author: frxgfa


value: dogoyster

value:
I’ve tried all kinds of to-do and note-taking tools — Notion, Obsidian, UpNote, Apple Notes, and many others — but none of them really stuck for long.
So I went back to writing things by hand.
It turned out to be surprisingly effective — clearer, simpler, and easier to focus.
Then I discovered the Eisenhower Matrix, a simple framework for distinguishing between what’s important and what’s urgent.
After using it by hand for over a month, it became a natural habit for organizing my tasks.
So I decided to build a Mac app around it.
I borrowed some ideas from GTD, like adding an Inbox, and made it easy to drag tasks into the Matrix to organize them visually.
It’s a minimal, local-first app — no account, no cloud — focused entirely on one thing:
helping you stay focused on what truly matters.
If you’re into frameworks like GTD or PARA, you might enjoy giving it a try.
App Store: [https://apps.apple.com/us/app/nemo-eisenhower-matrix-memo/id...]
Feedback is welcome!

value: Show HN: NEMO – A minimal Mac app for "Eisenhower Matrix"-style task planning

author: dogoyster


value: achalpandey

value: Show HN: Speak your mind and get a prioritized action plan instantly

author: achalpandey


value: atalw

value:
This is SpatialRead, a non-linear research paper reading tool that is truly yours.
I tried all the "Chat with PDF" apps. They're useful, but I always felt... trapped. My research process isn't a single, linear chat log. It's a branching, messy, and visual process of connecting ideas. I'd get a great explanation from an AI, but it would just get lost in the chat history. I was still stuck copy-pasting insights into a separate app. Not to mention the subscription lock-ins.
I built SpatialRead to fix this. It’s built on a simple idea: Your research tool should work like your brain, not like a chatbot.
SpatialRead combines a PDF reader with an infinite spatial canvas, all supercharged by AI. Instead of just "chatting," you can highlight any piece of text (from your original PDF or from a previous AI-generated answer) and use actions like Simplify, Explain, or Expand. Each new insight is added to the canvas as a new, connected node. You can literally watch your knowledge graph grow as you dive deeper into a topic.
Here are the features that make SpatialRead a great tool:
- Multimodal Diagram Explanations: This is one of my favorites. Screenshot a complex diagram, chart, table, or figure (like the Transformer architecture in our demo) and just ask, "Can you explain this?"
- AI Knowledge Graphs: Highlight any text and click "Expand" to go one level deeper. Then "Simplify" that new explanation. Then "Expand" a new term from that answer. You're building a branching tree of knowledge, not a flat list.
- Infinite Spatial Canvas: The heart of SpatialRead. Drag & drop PDF research papers or books, use the Text node for articles and essays, or simply start a canvas with a chat prompt. Organize your thoughts visually, not in a list.
- Bring Your Own Key (BYOK): SpatialRead is not a wrapper on a single model. Plug in your own API keys for OpenAI (GPT), Google (Gemini), Perplexity (Sonar), and Anthropic (Claude). You get full control over your cost, privacy, and access to the best models. New models are added as soon as they are released.
- Full Organization Tools: You can organize your library in customizable folders (with colors and icons) and switch between a beautiful light and dark mode.
SpatialRead has genuinely changed the way I research, turning it from a passive act into an active, creative one. And if you ever felt trapped by subscriptions or platform lock-ins, you'll love SpatialRead.
Here is a demo video: https://youtu.be/Z9x237wWAOo
Hope you like it!
P.S. It is priced at $49 for the first 100 users and there is a 20% student discount.

value: Show HN: SpatialRead – A Research Paper Reading Tool

author: atalw


value: mireklzicar

value:
CellARC, a synthetic benchmark for abstraction and reasoning is built from multicolor 1D cellular automata (CA). Each episode has five support pairs and one query serialized in 256 tokens, enabling rapid iteration with small models while exposing a controllable task space with explicit knobs for alphabet size k, radius r, rule family, Langton's lambda, query coverage, and cell entropy. We release 95k training episodes plus two 1k test splits (interpolation/extrapolation) and evaluate symbolic, recurrent, convolutional, transformer, recursive, and LLM baselines. CellARC decouples generalization from anthropomorphic priors, supports unlimited difficulty-controlled sampling, and enables reproducible studies of how quickly models infer new rules under tight budgets.
Paper: https://arxiv.org/abs/2511.07908
Code: https://github.com/mireklzicar/cellarc
Baselines: https://github.com/mireklzicar/cellarc_baselines
Dataset: https://huggingface.co/datasets/mireklzicar/cellarc_100k
X Thread: https://x.com/miroslavlzicar/status/1988502075664105561?s=20
Web & Leaderboard: https://cellarc.mireklzicar.com/

value: Show HN: CellARC Measuring Intelligence with Cellular Automata

author: mireklzicar


value: ritzaco

value: Show HN: Typing Automator – type smooth text for demo videos

author: ritzaco


value: miika

value:
For long time I have been observing how people buy a MIDI keyboard for just playing piano. The challenge is that keyboards often ship with lite version of a professional DAW, which is way too complex for many users. My mom couldn't do it!
I wanted to solve this problem by creating a super simple web app, which is only about playing piano with MIDI keyboard. Plug and play.
You can also import .mid file and watch it being played. Recently I added recording feature that will capture playback and these recordings can be saved to cloud and exported as .mid or .wav files.
Future plans involve displaying sheet music, and maybe testing how well live streaming keyboard events over websocket would work.
Too bad Safari doesn't support Web MIDI API but I believe that could be solved by creating native iOS / iPadOS application that would listen to MIDI events while forwarding them into web view.

value: Show HN: Cloud Piano – Piano with MIDI Keyboard. Instant and Effortless

author: miika


value: Viaya

value:
We’ve been exploring how to make AI video generation consistent.
Most existing text-to-video models can create impressive short clips—but the “same person” often drifts across shots or disappears when multiple subjects are involved.
BindWeave (https://www.bindweave1.com
) is our attempt to solve that.
It’s a subject-consistent video generation framework that unifies single- and multi-subject prompts using a cross-modal MLLM-DiT architecture—a multimodal large-language-model coupled with a diffusion transformer.
By combining entity grounding and representation alignment, the model interprets complex prompts and keeps visual identities stable over time.
We built it because we wanted reliable, controllable subjects for storytelling, digital avatars, and research demos—without retraining for each character.
Now creators can describe a scene, attach one or more reference images, and generate stable, high-fidelity clips where everyone stays recognizable throughout.
Demo videos and a short paper summary are on the site.
We’d love feedback from anyone working on AI video, cross-modal generation, or identity preservation—what use cases or limitations matter most to you?

value: Show HN: BindWeave – Subject-Consistent AI Video Generation

author: Viaya


value: josharsh

value:
I spent months watching AI tutorials on YouTube. Took notes. Felt like I learned a ton. Then I sat down to build something and... couldn't.
I didn't actually understand a lot of stuff!
The problem: Passive learning doesn't work for engineering skills.
What makes this different:
• You TYPE every command (no copy-paste)
• You SEE real API responses (not fake demos)
• You PAY real costs (~$10 total)
• Terminal-only (no context switching)
Think vimtutor, but for AI engineering.
20 modules covering:
- Tokens, embeddings, RAG
- Structured outputs, tool calling, agents
- Cost optimisation, evals, production monitoring
- Real OpenAI/Anthropic API calls
Try it:
npx ai-terminal-course
No installation. Just run it.

value: Show HN: AI Terminal Course – Learn AI Engineering Like Learning Vim

author: josharsh


value: ashfromsky

value: Show HN: YaraDB – Lightweight open-source document database built with FastAPI

author: ashfromsky


value: Show HN: Offline Pen-and-Paper Games for Kids (No Screens, No Ads)


value: oparinov

value:
bebored is a small mobile app with short “boredom workouts” (5–10 minutes) meant to train the ability to stay with boredom and then bring that into focus and everyday life. it’s live on ios and android; links are on https://beboredapp.com
.
_why i built it_
i previously led product and engineering at vivino. during and after that, I kept hearing the same thing from friends and colleagues: “i know meditation would help, but i can’t stick with it. the apps feel too spiritual or too long.”
i started experimenting with very small, constrained drills that feel more like “exercises” than “sessions”: stare at a point and watch what your attention does, sit with the urge to check your phone, follow just the exhale for a few minutes, etc. early testers reported they were more willing to start these than a 20-minute meditation, and some of them used them as a pre-work ritual to get into focus.
bebored is that experiment turned into an app.
_what it does_
the app currently has five types of “boredom workouts”, each session is 5-10 minutes. there’s also an in-app journaling feature, “moss”, which summarizes what you wrote after a session and tries to point out patterns over time (e.g. “most of your entries mentioning anxiety are late at night”).
_hat’s different vs typical meditation apps_
- it avoids “meditation” language and spiritual framing; everything is described in pragmatic terms (“here’s the drill, here’s what to pay attention to”).
- sessions are intentionally short and finite; the goal is “i can do one drill now” rather than “i should be a person who meditates”.
- visuals are simple and high-contrast rather than nature scenes; more like a small game ui than a wellness app.
- the focus is specifically on boredom and restlessness as the thing to train, not on calm as the primary goal.
what feedback i’m looking for
? does the “boredom workout” framing make sense, or is it confusing?
? if you try it, where do you hit friction in onboarding or starting the first session?
? does the journaling + summary feel useful, or would you skip it entirely?
? from a developer / product perspective, what would you change first if this were yours?

value: Show HN: bebored – boredom workouts to stop doom-scrolling (iOS/Android)

author: oparinov


value: yeekal

value:
*DeepSeek OCR* is a next-generation document understanding tool powered by a state-of-the-art dual-engine system, leveraging the pinpoint precision of *DeepSeek-OCR* and the high-speed efficiency of *PaddleOCR-VL*.
Our platform is engineered to master a wide range of challenging OCR tasks, allowing users to instantly and accurately digitize:
*   *Scanned & Digital PDFs* (preserving the original layout)
*   *Complex Handwritten Notes* (from lectures, meetings, etc.)
*   *Mathematical Formulas* (outputting clean LaTeX & Markdown)
*   *Tables & Tabular Data*
*   *Text from any Image or Screenshot*
We deliver this enterprise-grade accuracy within a truly free, frictionless experience—no sign-up or payment required—making advanced document intelligence accessible to everyone.
## *Key Features*
*   *State-of-the-Art Accuracy & Speed:* Our dual-engine system dynamically leverages the best model for the job, providing pinpoint accuracy for complex documents and high speed for standard tasks. It's proven to outperform leading alternatives on public benchmarks.
*   *Intelligent Layout Recognition:* This is our core advantage. We don't just give you a wall of text. Our AI is trained to understand and preserve the original layout of your document, including columns, lists, and even complex tables.
*   *Multi-Source Capability:* Go beyond perfect PDFs. Get incredible results from challenging, real-world sources, including *handwritten notes*, *camera-scanned textbook pages*, and *digital screenshots*.
*   *Versatile Markdown & LaTeX Output:* Built for modern workflows, our tool provides clean, structured Markdown for your notes (Notion, Obsidian) and standard LaTeX for your academic papers, saving you hours of reformatting.
*   *Truly Free & Frictionless:* This is our promise. Enjoy unlimited, high-quality OCR conversions with *no sign-up, no credit card, no watermarks, and no "free trial" limits.* It's built to be genuinely useful from the very first click.
*   *Broad Language Support:* Our underlying engines support over 100 languages, ensuring robust recognition of text and symbols from a global range of documents.

value: Show HN: I built a free OCR tool powered by DeepSeek and PaddleOCR engines

author: yeekal


value: arjunchint

value:
Hey HN, I'm Arjun, one of the founders of rtrvr.ai.
For the past year, we've been building and iterating on an in-browser AI agent. But a few months ago, we hit a wall in our approach and decided to tear everything down and rebuild from first principles. The result is what we're re-launching today.
The Problem/Insight:
We kept coming back to a simple, nagging question: web agents by themselves are a nice to have but we kept getting requests on possible ways to integrate or call our agent from another agent. Users also kept asking to reuse their own existing chatbot subscriptions to power the agent.
The "Aha!" Moment with MCP:
This led us down the rabbit hole of interoperability and we landed on MCP. Our core insight was this: what if we exposed the Chrome Extension itself as a Remote MCP server?
This simple idea completely changed our architecture and value proposition. It turns the user's browser into a controllable, sandboxed endpoint that any other AI can talk to with a simple copy/paste of a MCP url.
What this new architecture unlocks:
Remote Control Your Browser: You can stay in your flow in Claude and tell it to perform tasks on your behalf in background tabs. No more context switching. Tell Claude to file that Jira ticket or scrape a site without ever leaving the chat.
Reuse Your Own Subscription (The "BYO-Sub" model): Since Claude is driving the action, you're using your existing subscription to power the agent for basic tasks. We see this as the future – our agent provides the secure execution rails, and you bring the brain you already pay for. Users can then upgrade to our more advanced, multi-step agent for complex workflows when needed.
Our Bigger Bet - The Agentic Web:
We believe the future isn't a single "god agent" but a network of specialized agents that collaborate. By exposing the browser as a common execution layer, we're hoping to provide the "rails" for this future. We're already in talks with other agent platforms to build on this, enabling a more open and interconnected ecosystem.
We just launched on Product Hunt today and would genuinely love to hear the HN community's feedback. What are the security implications we haven't thought of? What are the unlocked use cases you see by giving an agent/app browser context? What's the next logical step for an open "Agentic Web"? All criticism and ideas are welcome.
Thanks for reading!
Links:
Product Hunt Launch: https://www.producthunt.com/products/rtrvr-ai?launch=rtrvr-a...
Chrome Extension: https://chromewebstore.google.com/detail/rtrvrai-ai-web-agen...

value: Show HN: Rtrvr.ai – Remote Control Your Browser with an AI Web Agent and MCP

author: arjunchint


value: AriaShaw

value: Show HN: Free box plot maker with CSV upload and automatic outlier detection

author: AriaShaw


value: semihcihan

value:
I’m an iOS developer with several indie apps.
Every time I created a new app, the worst part wasn’t coding — it was setting up App Store Connect.
Configuring in-app purchases, subscriptions, pricing, and metadata through the web interface is slow, repetitive, and error-prone. The site itself is sluggish and requires endless clicks. I’ve spent hours doing the same tasks across multiple apps — setting up similar subscription tiers, copying pricing, and managing localizations.
After doing this enough times, I wrote a command-line tool called StoreConfig to handle it.
It lets you describe your entire App Store Connect configuration in a JSON file — including:
 • in-app purchases
 • subscriptions
 • availability
 • pricing
 • metadata and localizations
You can fetch your current configuration from App Store Connect, edit it in JSON, and apply it back — either to the same app or a different one. It supports AI editing, version control and makes it very easy to share or duplicate setups between apps.
It’s similar in spirit to “infrastructure as code,” but for App Store Connect.
Tools like Fastlane are great for CI/CD, builds, and basic metadata updates, but they don’t manage pricing, IAPs, or subscriptions — which is what StoreConfig focuses on.
We’re currently running a free beta for developers who want to try it and give feedback.

value: Show HN: Automate App Store Connect configuration – IAPs, subs, metadata

author: semihcihan


value: sousvidal

value:
Hey HN,
I built CodeReviewr after getting frustrated paying $15-30/month for AI code review tools I used 10 times per month.
What's different: No subscription. Pay per token (~$0.15/review typical).
Setup takes about 60 seconds. Connect GitHub, get AI reviews on PRs instantly.
Tech: React Router, TypeScript, GitHub webhooks, SQLite for analytics (static analysis and insights coming soon!)
Pricing: $5 free credits, then usage-based
Not trying to replace tools like Coderabbit for teams doing 50 reviews/day. I built this for myself, and other solo devs and small teams who need occasional reviews without subscription commitment.
I would love your honest feedback.

value: Show HN: CodeReviewr – Pay per review, not per developer

author: sousvidal


value: sscarduzio

value:
DeltaGlider is a CLI/SDK similar to `aws s3` or `boto3`.
UPLOAD: It stores the first file in a S3 path as a full-size (reference), but saves next uploaded archives as deltas (tiny binary diffs) with respect to the reference.
DOWNLOAD: it reconstructs the original file on the fly, bit-perfect and verified with SHA256.
Why Xdelta3?
It's a compression-aware and block-level binary diff algorithm. Perfect for representing differences between archives, where small changes shift bytes but most content stays the same. It can efficiently delta compress ZIP/JAR/TAR archives up to 99.9% between versions, provided the difference in compressed content is overall small.
Killer use cases
Software versioning, periodic db. backups, JAR, ZIP, TGZ.
The impact for us was "2 orders of magnitude" storage price reduction. I hope you can benefit from it too!
License: GPLv3
Feedback and contributions are super welcome!

value: Show HN: DeltaGlider – Store 4TB of build artifacts in 5GB

author: sscarduzio


value: alextpfefferle

value: Show HN: nanoTabPFN – A Lightweight and Educational Reimplementation of TabPFN

author: alextpfefferle


value: twerkmeister

value:
Hi everyone, I just released an open source load testing tool for LLMs:
https://github.com/twerkmeister/tokenflood
=== What is it and what problems does it solve? ===
Tokenflood is a load testing tool for instruction-tuned LLMs hat can simulate arbitrary LLM loads in terms of prompt, prefix, and output lengths and requests per second. Instead of first collecting prompt data for different load types, you can configure the desired parameters for your load test and you are good to go. It also let's you assess the latency effects of potential prompt parameter changes before spending the time and effort to implement them.
I believe it's really useful for developing latency sensitive LLM applications and
* load testing self-hosted LLM model setups
* Assessing the latency benefit of changes to prompt parameters before implementing those changes
* Assessing latency and intraday variation of latency on hosted LLM services before sending your traffic there
=== Why did I built it? ===
Over the course of the past year, part of my work has been helping my clients to meet their latency, throughput and cost targets for LLMs (PTUs, anyone? ). That process involved making numerous choices about cloud providers, hardware, inference software, models, configurations and prompt changes. During that time I found myself doing similar tests over and over with a collection of adhoc scripts. I finally had some time on my hands and wanted to properly put it together in one tool.
=== What am I looking for? ===
I am sharing this for three reasons: Hoping this can make other's work for latency-sensitive LLM applications simpler, learning and improving from feedback, and finding new projects to work on.
So please check it out on github (https://github.com/twerkmeister/tokenflood), comment, and reach out at thomas@werkmeister.me or on linkedin(https://www.linkedin.com/in/twerkmeister/) for professional inquiries.
=== Pics ===
image of cli interface: https://github.com/twerkmeister/tokenflood/blob/main/images/...
result image: https://github.com/twerkmeister/tokenflood/blob/main/images/...

value: Show HN: Tokenflood – simulate arbitrary loads on instruction-tuned LLMs

author: twerkmeister


value: Show HN: Hotkey → Screenshot → AI Help. Works in Every App


value: alielroby

value: I started building Velork six months ago because I was tired of spending hours turning designs into code. I wanted something scalable for SaaS.<p>In Velork, design and code share the same space, and the AI sees both at once. It stays fast and accurate, even on large projects.

value: Show HN: Design canvas integrated into your AI IDE

author: alielroby


value: jumski

value:
Hi HN, I'm jumski. I spent last year building pgflow - a workflow orchestration engine built entirely on Supabase primitives (Postgres, Queues, Edge Functions, Realtime).
How This Started
I was transitioning to Supabase and building a personal app with multi-step LLM pipelines. I needed these to trigger from DB changes, cron, and the browser - but every workflow solution required external services.
From my Sidekiq experience, I knew that having each step handler send the next message to the queue shouldn't be part of business logic - it's error-prone and scattered. I realized I could move all orchestration to SQL - let the database decide what runs next while handlers focus purely on their task. To make this work on Supabase without external services, I created a self-respawning worker on Edge Functions to bypass time limits.
The Problem
Building workflows on Supabase today means manually wiring pg_cron schedules, pgmq queues, Edge Functions, and state tables. For a simple article processing workflow (fetch → parallel summarize + extract → publish), you're writing ~240 lines across 3 queue setups, 3 Edge Functions, 3 cron schedules. Tedious boilerplate.
What pgflow Does
Same workflow, 20 lines:

  new Flow<{ url: string }>({ slug: 'article_flow' })
    .step({ slug: 'fetchArticle' },
      (input) => scrapeUrl(input.run.url))
    .step({ slug: 'summarize', dependsOn: ['fetchArticle'] },
      (input) => summarize(input.fetchArticle))
    .step({ slug: 'extractKeywords', dependsOn: ['fetchArticle'] },
      (input) => extractKeywords(input.fetchArticle))
    .step({ slug: 'publish', dependsOn: ['summarize', 'extractKeywords'] },
      (input) => publishArticle(input.summarize, input.extractKeywords));

Flow inputs and outputs are fully type-inferred - your IDE autocompletes dependencies and catches errors at compile time. The only type annotation needed is the flow input.
You write workflows in TypeScript, compile them to SQL inserts that define your graph structure, and pgflow handles everything else. Postgres IS the orchestrator - managing a DAG of state machines, using pgmq to distribute tasks to workers. All state changes are fully transactional.
vs Alternatives
Unlike DBOS which uses decorators on imperative code, you explicitly define your DAG upfront. Unlike Trigger.dev/Inngest, everything lives in your existing Supabase project. You can query workflow state directly with SQL, and start flows from DB triggers or pg_cron.
Try It
- Demo: https://demo.pgflow.dev (paste any article URL)
- Docs: https://pgflow.dev
- GitHub: https://github.com/pgflow-dev/pgflow
Status: Beta - teams are using it in production. Fully open source, Apache 2.0 licensed.
Questions for HN:
What Supabase automations are you currently duct-taping together?
What's stopping you from using existing workflow tools?
Also curious: is SQL-based orchestration taking the "everything in the database" philosophy one step too far?

value: Show HN: pgflow – Workflows for Supabase, no external services (Postgres-first)

author: jumski


value: deemkeen

value: Show HN: Save your Claude Code Session to Git

author: deemkeen


value: michaelanckaert

value:
Hey HN!
Just launched the beta of AI Nexus and wanted to share what I'm building.
The problem I'm solving: I was paying multiple LLM subscriptions (ChatGPT Plus + Claude Pro) and constantly switching tools, losing context, re-uploading files to every new chat. Realized I wasn't alone - lots of devs and power users hitting the same wall.
What I built: A professional workspace for AI that gives you:
- 100+ models through one interface (GPT-5, Claude, Gemini, etc. via OpenRouter)
- Projects with shared context files (upload once, use across all conversations in that project)
- Conversation branching (explore different approaches in parallel without losing your thread)
- Visual token management (see what's eating your context, prevent "context too long" errors)
- Prompt library, MCP server integration, full parameter control
I'm still figuring out the Pricing model.
- Option A: BYOK (bring your own OpenRouter key) at €5/month for platform access
- Option B: Managed subscriptions with included credits (€15-75/month range)
- Option C: Hybrid - offer both and see what people prefer. Leaning toward BYOK for developers, but worried it's too technical for broader audience
Happy to answer questions about the tech stack, design decisions, or why I thought building yet another AI tool was a good idea!

value: Show HN: AI Nexus – Multi-model workspace with projects and branching

author: michaelanckaert


value:
I built PostIdentity because I was tired of rewriting the same idea for different platforms in different tones.
On X I needed something short and casual. On LinkedIn it had to be longer and more formal. I spent more time polishing tone than writing.
PostIdentity is a web app that learns how you write and builds AI identities that capture more than just tone.
Each identity encodes pacing, intent, and personality to create posts that sound like you or match different styles for brands or clients.
Unlike ChatGPT or other AI writing tools, PostIdentity keeps each identity persistent instead of recreating it from a prompt each time. It remembers how you write, the tone you use, and the style of your previous posts, so your output stays consistent. You can also take one idea and generate several versions of it across different identities, for example one for X and another for LinkedIn.
You can:
- Create multiple identities for different voices or projects
- Generate posts instantly using any identity
- Refine results to adjust tone or length
- Use the Chrome extension to write directly on X and LinkedIn
Signup is required, but you get an instant demo and 5 free posts when you log in.
Demo video (1 min): https://www.youtube.com/watch?v=C9GeT0b4XFE
Built with React, TypeScript. Uses Supabase, Claude Haiku 4.5 and GPT-5.
I’m building this as a side project alongside my full-time job, but I’m putting a lot of hours into it each week. I have plenty of exciting ideas to expand it further and would love to hear what you think could make it more useful, and if you would use this yourself.
Happy to answer any questions or share more details if you’re curious.

value: Show HN: PostIdentity, an AI that writes in your voice


value: harperhuang

value:
Hi HN,

  I built Ketchup AI, a free AI image generator that works without any signup or
  registration.

  Key features:
  - No account needed - just open and start creating
  - Completely free with no usage limits
  - Built-in AI prompt optimizer that helps beginners write better prompts
  - Supports multiple languages (English, Japanese, Korean, etc.)
  - Images aren't stored on our servers (privacy-first)
  - Local prompt history (last 20, stored in browser only)
  - Multiple aspect ratios: 1:1, 16:9, 9:16, 4:3, 3:4

  Average generation time is around 30 seconds. The prompt optimizer is particularly
   useful - it automatically expands simple descriptions into detailed prompts,
  which significantly improves output quality.

  Tech stack: Next.js 15, React, TailwindCSS, deployed on Cloudflare.

  I wanted to make AI image generation accessible to everyone without the friction
  of signup walls or credit systems. Would love to hear your feedback!

  Try it: https://ketchup-ai.com/

value: Show HN: Ketchup AI – Free AI image generator, no signup required

author: harperhuang


value: hilti

value: Show HN: Jsonl Viewer – Desktop app for 10M+ rows with nested flattening

author: hilti


value: qa-guy

value:
Hi HN,
I built defect.report - a lightweight web app for creating detailed, structured bug reports entirely client-side.
Everything runs locally in your browser for full privacy - no backend, no tracking, no data stored anywhere. You can export the report as a PDF, single HTML file, or copy it to your clipboard to paste into email, Slack, or any issue tracker.
I made this to help QA testers and small dev teams standardize bug reports without needing Jira, Notion, or any other heavy tool.
It’s also useful for students, beta testers, or anyone who wants to describe a problem clearly.
https://defect.report/
I’m curious to hear if you find this kind of tool useful, and how it could be improved.
Thanks!

value: Show HN: Developer-friendly bug reports without storing sensitive data

author: qa-guy


value: pless

value: Show HN: Solokit – Session-Driven Development Framework for Claude Code

author: pless


value: tejassuds

value: Show HN: SkillGraph – Open-source agentic framework with skills instead of tools

author: tejassuds


value: jviksne

value:
I built PageToChat, a Chrome extension that lets you invoke an LLM from any page via the right-click menu. What’s different: it doesn’t sell credits. It just opens your chosen provider in a new tab, selects the right model, fills your prompt, and uploads attachments-using the LLM account you already have.
Why?
Most “AI from any page” tools proxy your data or make you buy credits. I wanted something transparent that:
- stays in your browser,
- uses the official provider UI,
- and doesn’t require another wallet of tokens.
How it works
1. Right-click -> PageToChat.
2. A sidebar appears where you choose:
- Provider & model
- Chat mode: temporary (ephemeral) or persistent
- Prompt (or pick from saved ones)
- Attachments (auto-detected):
* page screenshot
* page content (with/without HTML)
* selected text (if you had text highlighted)
* image (if you clicked on an image)
* site-specific extras (today: Twitter/X threads and Gmail email threads)
3. Hit Send → we open the provider tab, pick the model, enable temporary mode if needed, fill the prompt, upload attachments, and (optionally) auto-submit.
"Quick actions" (custom context menu items)
You can save presets—provider, model, prompt, and which attachments to include—and they show up as extra right-click items. Clicking one fires the whole flow automatically.
Pricing
- Free: all features, 1 saved quick action, occasional small sidebar ad (no page context sent to ads).
- Power: multiple quick actions, no ads.
(Feedback welcome on this split-happy to tweak based on what HN finds fair.)
What makes it different
- No middleman credits; uses your existing LLM account.
- Zero copy-pasting between tabs.
- Context-aware attachments (and growing list of site-specific integrations).
What I’d love feedback on
- Missing providers/models you want first.
- Additional site-specific attachments (Docs? GitHub issues/PRs? Notion pages?).
- Default attachment choices you’d expect for common workflows.
Happy to answer anything - privacy, permissions, roadmap, bugs. If you try it, I’d love to hear what breaks on your setup and what would make it a daily driver.

value: Show HN: PageToChat – Use your own LLM account from any web page via right-click

author: jviksne


value: samteeeee

value: Show HN: Remember Your Accomplishments

author: samteeeee

title: Show HN: Remember Your Accomplishments


value: superstonne

value:
Hi HN,
I got frustrated with "free" AI tools that hide everything behind login walls, so I built Banana Prompts.
What you can do WITHOUT signing up:
• Browse and copy all 1,200+ verified AI prompts
• Generate AI images directly on the site (text-to-image + image-to-image)
• Download your results
• View community showcase
Every prompt includes real before/after examples, success rates, and difficulty ratings.
Optional free account only for:
• Saving favorites across devices
• Publishing your work to the showcase
Why no login wall?
Because respecting user privacy and lowering barriers matters more than collecting emails.
Tech stack:
• Next.js 16 (App Router)
• Supabase with anonymous access + RLS
• Cloudflare R2 (90% cheaper than S3)
• Google Gemini API
Abuse prevention without tracking:
Turnstile CAPTCHA + IP-based rate limiting (10/hour anonymous, 50/hour logged in)
Live at: https://banana-prompts.org
Try it now – literally just open and use. Would love your feedback on UX, features, or tech architecture!

value: Show HN: Banana Prompts – Browse AI prompts and generate image

author: superstonne


value: Show HN: I built a synth for my daughter


value: AhmedSlem

value:
Hey HN,
I’ve been working solo on a tool called ContentKit Studio, and I just launched the beta.
It’s built for creators who want to turn long videos or podcasts into polished, ready-to-post clips — without spending hours editing.
You can upload a video directly or paste a YouTube link, then ContentKit automatically:
Removes filler words and silences
Lets you edit directly from the transcript
Exports full 1080p videos instantly
(Coming soon) Generates AI-enhanced titles, descriptions, and viral clips
I built this after struggling with slow, complex editing tools that weren’t made for creators who just want results fast.
I’d love your thoughts — feedback, critiques, or feature ideas are all welcome.
Check it out here: contentkit.studio
Thanks!
— Ahmed

value: Show HN: ContentKit Studio – Edit long videos fast with AI

author: AhmedSlem


value: drbt

value: Minimal reproducibility layer for ML - config + code + runtime fingerprints.

value: Show HN: Ato – A thin ML layer. When results change, it tells you why

author: drbt


value: wismoy

value:
I built a small text-to-image and image-to-image tool that lets you set exact pixel dimensions (width and height), not just aspect ratios. You can generate outputs up to 4096px on either side.
Motivation: my friends and I kept needing precise sizes (e.g., YouTube thumbnails at 1280×720). Most generators only offer 16:9, so we had to resize afterward, which can soften details. PixExact creates the target size directly.
What’s different:
- Specify exact width and height in pixels (up to 4096px each)
- Works for both text-to-image and image-to-image
- Aimed at thumbnail and social graphics workflows where exact sizes matter
It’s an early build and I’d love feedback:
- Are there other sizes or presets you want (e.g., social platforms)?
- Any UX rough edges?
- Would an API or batch mode be useful?
I made this and will be in the comments to answer questions.

value: Show HN: PixExact – text/image-to-image with exact pixel sizes (up to 4096px)

author: wismoy


value: andersmyrmel

value: Show HN: A tiny TypeScript library to guard against prompt injection

author: andersmyrmel


value: mrwangust

value:
Hey HN,
I’ve been working on Shopscan.io — a Shopify store audit tool that helps freelancers, developers, and agencies turn cold leads into paying clients.
If you’ve ever tried winning a Shopify project, you probably offered a “free audit.”
But manual audits take hours — Lighthouse tests, screenshots, writing insights, formatting PDFs — all before the client even replies.
By the time you’re done, the lead has gone cold.
Shopscan automates this process.
Just enter a Shopify store URL — it runs 50+ checks across:
- Performance (Lighthouse + Core Web Vitals)
- SEO(metadata, schema, image alt, H1s, etc.)
- Accessibility (ARIA, alt text, WCAG compliance)
- Mobile & UX
- Security
- Conversion & Content Quality
You get a detailed, shareable PDF or web report that looks client-ready, with plain-English explanations of what’s broken, why it matters, and how to fix it.
Example insight from a recent scan:
“Your page has a 3.0s Total Blocking Time. That’s not just UX - that’s lost revenue. Cutting it by 1s can raise conversions 5–25%.”
Shopscan isn’t another SEO checker.
It’s built for *agencies who want to generate leads*, not just scores.
Free scans: full reports with performance, SEO, and UX breakdowns
Pro: advanced insights, historical tracking, and scheduled scans
White-label (coming soon): brand reports as your own
In early tests, agencies saw 3–5× higher reply rates when sending Shopscan reports to prospects instead of cold messages.
Try It
https://shopscan.io
You can run a free scan of any Shopify store and download the report instantly.
Would love your feedback on:
- What extra checks (or data sources) would make this genuinely more valuable to you?
- How do you currently qualify Shopify leads, and would an automated report fit that workflow?
- Should Shopscan expand beyond Shopify (e.g., WooCommerce, Webflow, or custom storefronts)?
Happy to share a sample report privately if you’d like to see the full output.
- Noel

value: Show HN: Shopscan.io – Automated Shopify Store Audits for Agencies/Freelancers

author: mrwangust


value: sparklyoldman

value: Show HN: Visual Types – A humble set of animated TypeScript concepts

author: sparklyoldman


value: matthiasstiller

value:
Hey!
In the physical world, pop-up stores are a way for brands to move fast — temporary spaces built to launch ideas, test markets, and connect directly with people. They’re agile by design: high impact, low friction, and gone before things get stale.
We’re bringing that same idea to the internet. Popup.so is a virtual pop-up space for web apps. A single domain where startups, indie hackers, and tech teams can take over for a limited time — to launch, experiment, or tell their story.
Each pop-up is temporary. You own the space for your slot, use it however you want, and when your time’s up, it resets for the next creator.
It’s a rotating showcase of what’s being built right now — simple, fast, and constantly changing. We believe the web should feel alive — not static pages, but moments.
This is our way to bring that energy back.
Thanks!
Matthias

value: Show HN: Domain Is Yours – For a Day

author: matthiasstiller

title: Show HN: Domain Is Yours – For a Day


value: Show HN: GoViralPromo – Replace ads with performance-based contests (free beta)


value: msyea

value:
Built an AI assistant for Garmin watches in MonkeyC using Connect IQ SDK. BYOK (Gemini API key).
MonkeyC is terrible; kind of like ancient Java without the ecosystem. Building for hundreds of different devices with different screen sizes, buttons and capabilities is tough. But it's the only way to build native Garmin apps. Making it work on the Fenix 5 (2017) was emotional. I was trying to get the WiFi sync to work but it appears that Garmin removed the WiFi capability at some point in the last year (missing symbols) and memory constraits (OOM issues) are real.
I then released it using Garmin's Connect IQ native Trial/Unlock capability - which unbeknown to me has been broken for 2 years - so I had to roll out a custom trial, unlock and payment platform within 14 days before my first potential users tried to buy. I've had 2 successful customers on ~200 downloads already with no marketing - just the app store listing.
But why? The watch is full of rich sensor data (HR, steps, age, VO2 max, GPS, elevation, magnetometer etc.). Sharing it as context with a simple prompt like "Am I fit" or "When is the next bus to X" works surprisingly well.
Works over WiFi (phone optional) or Bluetooth. Compatible with Fenix 5+ (8 years of devices).
Privacy: All API calls are done from the watch - no server-side component.
$4.99 one-time. Happy to discuss MonkeyC/Garmin pain or the BYOK model.

value: Show HN: Built an AI assistant in MonkeyC for Garmin watches

author: msyea


value: mireklzicar

value: Show HN: CellARC: ARC-AGI style benchmark built on cellular automata

author: mireklzicar


value: BoumTAC

value:
Hi HN,
I've been frustrated with static site generators that pile on features like tags, themes, plugins, and endless configs just to get a simple blog running. So I built *BoumWave*: a dead-simple CLI tool that converts your Markdown posts into HTML using your own templates. That's it. No bloat, no learning curve—just pure, fast blogging.
*What it does:*
- *Markdown to HTML, done right*: Write posts in Markdown, generate clean HTML with automatic SEO (Open Graph, Twitter Cards, JSON-LD, canonicals).
- *Multilingual from the start*: Native support for multiple languages. Create posts in one command, and it handles the rest.
- *Full template control*: Use your own HTML templates. It auto-inserts posts into your index between `<!-- BOUMWAVE_POSTS_START -->` and `<!-- BOUMWAVE_POSTS_END -->`.
- *Zero config hassle*: One `boumwave.toml` file with everything explained with inline comments. Init, scaffold, write, generate.
Check it out on GitHub: https://github.com/CedricRaison/BoumWave

value: Show HN: BoumWave,a static blog generator that does what it needs to

author: BoumTAC


value: zvivier

value:
I kept getting surprised by my AI API bills—$200 one month, $400 the next.
The individual provider dashboards don't help when you're using multiple services.
SpendScope aggregates costs from OpenAI, Anthropic, and Google AI in real-time,
with budget alerts and model-level breakdowns.
Built it in one night after yet another surprise bill. Would love feedback!
Tech: Lovable (no-code), Supabase, Stripe
Pricing: $49 lifetime (7-day free trial)

value: Show HN: SpendScope – Track AI Costs Across OpenAI, Anthropic, Google AI

author: zvivier


value: stefvuck

value:
Hi all, this is a quickly slapped together tool to address my main issues I had with other tools, primarily:
https://github.com/anuraghazra/github-readme-stats
No shade of course, its a great tool, but I love having a diverse range of languages (COBOL etc), and not getting to show it off was frustrating.
In addition, it could sometimes take very long for updated changes to manifest in the graph.
Finally, no private repos. This was the biggest dealbreaker for me.
Anyway, its not "done" but its usable, in my README already and I hope the rest of HN enjoys

value: Show HN: Better GitHub Language Stats

author: stefvuck

title: Show HN: Better GitHub Language Stats


value: piratebroadcast

value: Show HN: Free Mac app graphically creates 'Rails New' options and saves presets

author: piratebroadcast


value: robkop

value:
TLDR: I've been trying to figure out if AI is actually replacing anyone, I've built an interactive model for you to play with, keen for feedback (is it accurate on your org?)
I've been troubled in understanding if AI is really impacting the job market. I've heard "AI mass replacement" for the past 3 years but... I still haven't seen anything?
So, sounds like an interesting gap for a side project to investigate
Main goals were to answer:

  Suppose AI replacement is here, where should I look to see it in my company?

  And, if we can predict exposure across companies, which industries & countries will be hit first? and the hardest?

I got surprisingly good estimates by gluing together org chart data from financial reports (+ news stories + job ads) with Anthropic's Economic Index data (click "Help me understand" on the site for a nice visual). Then running that across 1,000+ companies also gave a pretty comparable view x-country/x-industry.
I've left it open so you can run whatever company/ industry you want - which then gets added to the overall dataset. It'll also draw up the org chart and overlay all the at risk roles for you - let me know if you see any gaps
Site: https://automationrisk.app
Code (MIT): github.com/R0bk/automation-risk
P.S. I threw $150 into anthropic credits you can play with - unfortunately don't have unlimited - if you want to sponsor some runs, ping me

value: Show HN: Where is "mass replacement"? Toy to estimate AI exposure in your org

author: robkop


value: alessandro-a

value:
Hey HN!
I'm the creator of Calendar0, a menubar calendar for MacOS and Windows that I've been working on for the past few months.
The app is designed to make calendar management actually accessible without opening a browser every time you need to check your schedule.
One of Calendar0's main goals is to eliminate the constant context-switching between multiple calendar accounts and providers.
The latest update finally adds Apple Calendar support alongside Google and Microsoft 365, so you can now see all your calendars in a single unified view.
I also just shipped bulk operations: you can add buffers to multiple back-to-back meetings in seconds instead of manually editing each one.
Would love to have your feedback!

value: Show HN: Made a system tray calendar that syncs all your calendars

author: alessandro-a


value: legitcoders

value:
Built a marketplace for AI agents that handle specific business tasks (content creation, lead gen, customer support, etc.) with recurring Stripe subscriptions.
Stack: Next.js 15, Firebase, Stripe, OpenAI API. Demo mode lets you try agents before buying.
Feedback welcome!

value: Show HN: Morphex.ai – Marketplace for Specialized AI Agents

author: legitcoders


value: alephpi

value: Show HN: Open-Source LaTeX OCR, Alternative to Mathpix/SimpleTex

author: alephpi


value: ivankra

value: Show HN: JavaScript Engines Zoo

author: ivankra

title: Show HN: JavaScript Engines Zoo


value: Flamehaven

value:
Tired of RAG demos that only work in notebooks?
Flamehaven FileSearch is designed for real deployment —
a lightweight, production-ready document search engine that you can self-host in minutes.
Key Highlights
5-minute setup — pip install flamehaven-filesearch[api]
 100% self-hosted — your documents never leave your infra
 Python SDK + REST API with FastAPI & Swagger UI
 SQLite-backed store — simple, portable, and offline-friendly
 Gemini-powered embeddings with natural language Q&A + citations
 Docker-ready — works on a $5 VPS or your laptop
Why it matters
Unlike typical RAG stacks that require vector DBs, multiple APIs, and complex infra,
Flamehaven FileSearch runs cleanly on Python and SQLite — no dependencies, no vendor lock-in.
You own the data, the storage, and the intelligence.
It’s built for teams, researchers, and indie developers who need
semantic search they can actually deploy and trust.
Try it
GitHub: https://github.com/flamehaven01/Flamehaven-Filesearch
PyPI: flamehaven-filesearch
 Docs: /docs after running the API server
#opensource #python #AI #RAG #Gemini #FastAPI #Flamehaven #LLM #developer
Security & Account Notice
Recently, GitHub detected a suspicious login attempt on our organization account.
As a precaution, a password reset was enforced.
We are currently in contact with GitHub Security and awaiting resolution.
This incident did not affect any public repositories such as
dir2md, flashrecord, crom-efficient, ARR-medic-cyp3a4, or Unstable Singularity Detector.
All builds remain verified and signed.
We sincerely apologize for any inconvenience caused and appreciate your understanding as we complete the security audit.

value: Show HN: Flamehaven FileSearch – Self-Hosted RAG Semantic Search

author: Flamehaven


value: sangkwun

value:
I built a small converter that turns Notion pages into clean, paste-ready email blocks. It keeps your headings, lists, and callouts intact — write once in Notion and reuse the result for newsletters, team updates, or announcements.
I made it because I was copying Notion content into email clients every day, fixing spacing and colors by hand. Now it keeps the layout consistent and lets me repurpose the same content anywhere I need an email version.
What it does:
• Convert any Notion page into a tidy, email-ready block
• Preserve structure and styling (headings, callouts, images)
• Works well in Gmail and Apple Mail (and most modern clients)
Would love feedback on tricky blocks (databases, toggles, synced pages) or how you’d use this for your own email workflows.
Demo: https://notionto.email/en/template?utm_source=hn&utm_medium=...
Solo dev here — thanks for reading!

value: Show HN: Turn Notion pages into clean, paste-ready email blocks

author: sangkwun


value: Show HN: Ory Kratos, an open source Auth0 / Clerk alternative


value: yestwind

value:
  Built https://nanobanana2pro.com ahead of Google's mid-November Nanobanana2 launch.

  What's special about Nanobanana:
  • From Google Research (not public yet)
  • Multi-reference support (10 images)
  • Sub-3 second generation
  • Next-gen coherence

  Try free: https://nanobanana2pro.com/nanobanana (no signup for first try)

  We're in Google's early access program. Nanobanana2 integration goes live day one of
  public release.

  Stack: Next.js 15, PostgreSQL, Cloudflare R2

  Questions?

value: Show HN: Early access to Google's Nanobanana – most advanced image model

author: yestwind


value:
I built SQL++, a type-safe SQL library for Rust using PostgreSQL's binary protocol.
Benchmarks vs Prisma (5,000-10,000 queries):
- Simple queries: 1.5x faster
- Complex aggregations: 19.9x faster
- Batch inserts: 5.6x faster
- Average: 5x faster
One benchmark didn't finish in Prisma (crashed), SQL++ completed in 2.5min.
Why faster:
1. No runtime query building - validates once, caches forever
2. Zero ORM overhead - direct struct mapping
3. Binary protocol - implemented PostgreSQL wire protocol from scratch
Currently supports:
- Full SQL (CTEs, window functions, JOINs, subqueries)
- DDL (CREATE/ALTER/DROP TABLE, indexes)
- ~60% of SQL spec
Limitations:
- PostgreSQL only
- v0.1 (expect bugs)
- No ORM relationships (by design)
Built as a high school project. Feedback welcome!
GitHub: https://github.com/sinisterMage/sqlpp
Benchmarks: https://github.com/sinisterMage/sqlpp/tree/main/benchmarks

value: Show HN: SQL++ – 5x faster than Prisma (Rust)


value: maghfoor

value:
I initially released this as just an IOS app. Since then it has been growing steadily but a lot of people have emailed asking for a web / android version.
It took me nearly 2 months to build a version for the web.
The nice thing about using Convex as my backend is that all the data is always synced between the app and web. I do not have to setup any syncing logic. The moment you change something in the app, it will reflect on the web version in realtime.
I know there are loads of these kind of tools online but it's starting to feel like mine is actually starting to differentiate itself out from the rest.
What was just a thing for myself that I built because I had used everything else but nothing worked, is now being used by so many people across the globe. It's a really good feeling. Going to keep improving it.

value: Show HN: I built Duolingo but for your life – people asked for web, so I made it

author: maghfoor


value: fudailzafar

value:
Hey hackers,
I’ve been a frontend dev for about 1.5 years, mostly working with React and Next.js.
I always found it hard to build polished personal portfolios, especially when trying to combine design, layout, and live code previews. So I built ChatPortfolio, an AI that writes and updates your React portfolio code in real time.
You can chat like:
“Add a work experience where I worked at Google.”
“Change the theme to red.”
And it updates the portfolio instantly — no rebuilds, no manual syncing, just live generative React code.
Under the hood:
- Uses Next.js for server rendering and routing.
- Integrates with Tambo (a generative UI framework) for returning live React components inline.
- Real-time updates through an interactable React tree, so AI changes the UI without triggering rebuilds.
I’m still experimenting with better editing UX, saving user state, and custom schema validation for generated components. And the best part is, it's Open Source!
Demo: https://the-chat-portfolio.vercel.app
Repo: https://github.com/fudailzafar/chatportfolio
P.S. My first HN post, would love any feedback and do check it out :)

value: Show HN: I built an AI that writes your portfolio's React code – and made it OSS

author: fudailzafar


value: hunterbown

value:
Hey everyone! I've been captured by the recent solar storms like the rest of the internet, so I dug up a project I've been working on for a while.
I built Heliosinger — it's a project that gives the sun a "singing voice" in real-time. I'm a trumpet player and classical vocalist, so my goal was to make the musical choices very intentional, not just random beeps.
Here's a rough idea of how the mapping works:
- Pitch = Solar Wind Velocity
- Vowels (ee/ah/oo) = Plasma Density + Temperature (using formant synthesis)
- Rhythm/Tremolo = Kp Index (geomagnetic activity)
- Harmony (Major/Minor) = Plasma Temperature + Magnetic Field (Bz)
Technical details:
Built with Web Audio API (custom formant filters for vowel synthesis)
Real-time data from NOAA DSCOVR and SWPC (updates every 15-60 seconds based on activity)
React + TypeScript + Vite
Deployed on Cloudflare Pages
No tracking, no analytics, fully client-side
Try it: https://heliosinger.com
The code is open source: https://github.com/Shannon-Labs/heliosinger
I'd love to hear your thoughts on the sonification mapping and any ideas for improvements! We might hear some crazy sounds tonight!!

value: Show HN: Heliosinger – The Sun Sings Real-Time Space Weather

author: hunterbown


value: ankuranand

value:
Hi everyone — I’m the developer of UnisonDB, an open-source log-native database built in Go for distributed and edge-scale systems.
UnisonDB rethinks the boundary between databases and streaming systems. Instead of treating the Write-Ahead Log (WAL) as a recovery mechanism, it treats the log itself as the database. Every write is immediately durable, queryable, and replicable — without Kafka, CDC pipelines, or changefeed daemons.
UnisonDB unifies persistence and streaming in one system.
It’s designed for real-time, event-driven, and edge-first workloads where data needs to move as fast as it’s written.
Key features:
1. Multi-Modal Storage: Key-Value, Wide-Column, and Large Objects (LOB)
2. Streaming Replication: WAL-based replication with sub-second fan-out to 100+ edge replicas
3. Edge-First Design: Optimized for edge computing and local-first architectures
4. Namespace Isolation: Multi-tenancy support with namespace-based isolation
Feedback, testing, or contributions are all welcome

value: Show HN: Unisondb A open source streaming multimodal database for Edge Computing

author: ankuranand


value:
Recently updated my open source app Back2Back to be multiplatform. Still all native code, but targeting macOS and iOS.
Use the default DJ persona's to explore different music, or create your own persona. Use GPT-5 in high thinking with web search tooling to create in depth style guides.
Each selection is made by an LLM using the persona, then another LLM matches the selections to Apple Music, and a final LLM validates that the Apple Music track fits the DJ persona.
This workflow provides the very best results, much better than other ML-based methods I have used in the past.
Still in beta, would love feedback.

value: Show HN: AI music discovery for super nerds (Now on iOS AND macOS)


value:
Hey HN, this is David from Aluna (YC S24). We work with diagnostic labs to build datasets and evals for oncology tasks.
I wanted to share a simple RL environment I built that gave frontier LLMs a set of tools that lets it zoom and pan across a digitized pathology slide to find the relevant regions to make a diagnosis.
Here are some videos of the LLM performing diagnosis on a few slides:
(https://www.youtube.com/watch?v=k7ixTWswT5c): traces of an LLM choosing different regions to view before making a diagnosis on a case of small-cell carcinoma of the lung
(https://youtube.com/watch?v=0cMbqLnKkGU): traces of an LLM choosing different regions to view before making a diagnosis on a case of benign fibroadenoma of the breast
Why I built this:
Pathology slides are the backbone of modern cancer diagnosis. Tissue from a biopsy is sliced, stained, and mounted on glass for a pathologist to examine abnormalities.
Today, many of these slides are digitized into whole-slide images (WSIs)in TIF or SVS format and are several gigabytes in size.
While there exists several pathology-focused AI models, I was curious to test whether frontier LLMs can perform well on pathology-based tasks. The main challenge is that WSIs are too large to fit into an LLM’s context window. The standard workaround, splitting them into thousands of smaller tiles, is inefficient for large frontier LLMs.
Inspired by how pathologists zoom and pan under a microscope, I built a set of tools that let LLMs control magnification and coordinates, viewing small regions at a time and deciding where to look next.
This ended up resulting in some interesting behaviors, and actually seemed to yield pretty good results with prompt engineering:
- GPT 5: explored up to ~30 regions before deciding (concurred with an expert pathologist on 4 out of 6 cancer subtyping tasks and 3 out of 5 IHC scoring tasks)
- Claude 4.5: Typically used 10–15 views but similar accuracy as GPT-5 (concurred with the pathologist on 3 out of 6 cancer subtyping tasks and 4 out of 5 IHC scoring tasks)
- Smaller models (GPT 4o, Claude 3.5 Haiku): examined ~8 frames and were less accurate overall (1 out of 6 cancer subtytping tasks and 1 out of 5 IHC scoring tasks)
Obviously, this was a small sample set, so we are working on creating a larger benchmark suite with more cases and types of tasks, but I thought this was cool that it even worked so I wanted to share with HN!

value: Show HN: Cancer diagnosis makes for an interesting RL environment for LLMs


value: vdszds

value:
Hi HN,
I got frustrated with shallow feedback from forms and the time it takes to do manual customer interviews. So I built Diaform – an AI that runs interviews for you.
I've been using it in my apps and I hope it can help you too. I'd love to hear your feedback.
Vlad

value: Show HN: Conversational AI for customer feedback

author: vdszds


value: interapp

value:
Hey HN! I built Rando because I had 50,000+ photos from the DSLR era (2000-2015) sitting on external drives that I never looked at.
Cloud photo apps want to upload everything, which feels invasive and expensive for large archives. So I made something different: a local-only app that randomly displays photos from your drives - like shuffle mode for your photo collection.
*The technical bit:*
- 100% local processing, zero network calls (not even analytics unless you opt in)
- Works with any local or network storage (external drives, NAS, USB sticks)
- Fast indexing even with 100,000+ photos
- Tagging system that doesn't modify original files (SQLite metadata database)
- Built for both Mac (Swift) and Windows (WPF)
*The privacy angle:*
No servers, no accounts, no cloud infrastructure. Your photos never leave your computer.
It's kind of like rediscovering your own photo archive as entertainment rather than trying to organize it perfectly. Like Netflix for your memories.
*7-day free trial available:*
- Mac App Store: https://apps.apple.com/us/app/rando-random-photo-picker/id67...
- Windows Store: https://apps.microsoft.com/detail/9p679dck1j5k?hl=en-US&gl=U...
Would love feedback from the HN community - especially on the privacy implementation and whether this scratches an itch for anyone else with large local photo collections.

value: Show HN: Rando – Random photo picker/slideshow for local drives (100% private)

author: interapp


value: talksik

value:
If you're familiar with Streamdeck, this is a similar but simpler alternative built for work, and free (ad-supported). Essentially, it allows you to use your iPad for shortcuts on your mac. The extra real-estate is quite nice for people who have a desk setup with monitor and other peripherals.
I'm posting this because I completed a new project which lets people declaratively define all of the "key" that show up in their app, via YAML. This allows you to specify when particular shortcuts show depending on which app or website you're in (e.g. create specific shortcuts for Gmail, Neovim, Linear, Notion, etc). Nix fans will appreciate this. However, I'd like feedback on this overall approach and experience, so please hit me in the comments!
Check out our docs for more information on this. Go to https://flowylabs.ai and then "Docs" for more technical details. I call this "programming your keypad" which allows people to configure every inch of their macro-pad.

value: Show HN: Replace Your macOS Dock

author: talksik

title: Show HN: Replace Your macOS Dock


value: bit-hack

value:
I built an IBM-PC-XT compatible computer using a mixture of authentic parts and a modern FPGA. The article linked contains a detailed description of the development process, and at the bottom is a link to the schematics and HDL source code.
My main goal for this project was to push myself to learn as much as possible while ending up with an small, fun, usable retro device I can play with.
The computer currently has the following features:
- NEC V20 CPU running at 10Mhz
- 1MB SRAM system memory
- CGA graphics adapter with some EGA support
- Micro SD card emulation of a Hard Disk
- PS/2 keyboard and Mouse support
- Adlib audio output using an authentic YM3014 DAC
- Internal hard drive clicker
- System peizo speaker
Feedback and suggestions for improvements are very welcome.

value: Show HN: FPGA Based IBM-PC-XT

author: bit-hack

title: Show HN: FPGA Based IBM-PC-XT


value: golfer

value:
I'm an avid golfer -- it's my main hobby. Chicagoland is blessed with an abundance of public golf courses. I had an idea in 2022 to start documenting the courses I play in both the city and suburbs. Over the past 3 years, I've visited over 200 golf courses and took pictures and notes, documenting everything from the clubhouses, pro shops, scorecards, driving ranges, putting greens, golf holes.. and even the course hot dogs. (Courses should take their hot dogs seriously!)
It's been a fun labor of love. My goal is to create the ultimate Chicago golf guide. The course catalog has in-depth descriptions of most courses, where I've done my best to research the history of the property. That is painstaking work for 200+ courses but I find it fascinating. The work continues.
I've added a course map, news, and other featured content.
Example of a course page -- Ravisloe CC
https://www.golfscout.net/golf-course/ravisloe-country-club-...
Course map:
https://www.golfscout.net/chicago-golf-course-map
Sortable course list:
https://www.golfscout.net/sortable-courses-18-holes
Hot dog ratings:
https://www.golfscout.net/chicago-golf-course-hot-dogs
Next up comes driving ranges and more. Let me know what you think!

value: Show HN: Comprehensive Chicago area golf resource

author: golfer