value:
I built this because I was tired of cold starts or complex setups or paying AWS egress fees just to query logs in S3.
The Problem: To analyze 500GB of logs, I usually have to either:
- Wait 5-10s for Athena cold starts + pay $5/TB scanned.
- Download the data to my laptop (slow + egress costs).
- Upload it to a SaaS like Datadog/Snowflake (massive cost + privacy risk).
The Solution: Burner is a "Bring Your Own Compute" SQL engine.
Architecture: You run the Agent (Docker) on your own EC2 instance in the same region as your bucket. Its zero egress as the data never leaves your VPC. The Agent computes aggregations in-memory (using DataFusion/Arrow) and only streams the JSON results back to you. I integrated wasmtime so you can compile Rust logic (like PII scrubbing or CIDR matching) and run it inside the query engine at native speeds.
Benchmarks (1GB Parquet / 100M rows):
- Python (Pandas): ~45s (Crashed OOM on t3.micro)
- Burner: ~1.8s (Streaming batches, 256MB RAM limit)
Business Model: I'm trying a $19 Lifetime License (Beta) instead of a subscription.
Repo is here: https://github.com/burnersql/burner-agent
Email: hello@burnersql.com
Happy to answer questions! I hope this is useful. Enjoy folks. :)

value: Show HN: Burner-Query S3 logs without cold starts/egress fees(Rust+WASM)


value: gridscript

value:
I built Gridscript because of my mom.
She doesn’t know Excel, SQL, or Python — but she constantly receives messy spreadsheets from work. She’d call me and say things like: “Can you help me clean this?” or “Why can’t I just click a button to fix this column?”
Every time, I realized the same thing:
most data tools are built for experts, not for regular people who just need to clean, reorganize, or understand their data.
So I decided to make something simpler.
Gridscript is a browser-based workspace designed to make everyday data tasks — cleaning, transforming, analyzing, visualizing — as simple as possible. You can use intuitive no-code tools for common operations, or switch to Python/JavaScript when you need more power.
It’s meant to feel lightweight and approachable, but still capable enough for real data work.
And it runs entirely client-side, with no installation or setup — my mom can open the browser and start fixing her spreadsheet immediately.
If you’re someone who deals with data but doesn’t want the friction of spreadsheets, scripts, libraries, environments, dependencies, etc., I hope this makes your life a little easier too.
Try it here: https://gridscript.io
Happy to answer questions or hear feedback!

value: Show HN: Gridscript – simplifying how you work with data

author: gridscript


value: mixfox

value: A Free Online Toon formatter for all AI models.

value: Show HN: Online Toon Formatter and Converter

author: mixfox


value: claygood

value: Show HN: Cloud-agnostic SIEM that uses a natural language query layer

author: claygood


value: sputge

value:
Hello HN,
This is my first “real” programming project: homeassistant.koplugin
It's a plugin for KOReader[1]
I made it because I prefer reading on my e-reader without a phone nearby, yet I still sometimes need to tweak lights or other Home Assistant devices.
So, out of that small “necessity,” the plugin was born.
I spent nearly as much time on the documentation as on the plugin itself. Both began far too verbose and complex, so I trimmed them down bit by bit.

  Features:
  Control any number of Home Assistant entities from KOReader
  Basic service support (e.g. light/turn_on, switch/toggle, fan/turn_on)
  Lightweight, unobtrusive interface
  Simple text-based configuration
  Success/error notifications

Documentation: https://sputge.com/docs/homeassistant_koplugin/
___
[1] KOReader is a document viewer for E Ink devices - https://koreader.rocks/

value: Show HN: I build a KOReader plugin to control Home Assistant devices

author: sputge


value:
I built ConceptViz (https://conceptviz.app
) for teachers who spend too much time searching or drawing diagrams for science and math lessons.
You type a short description like “ray diagram for a convex lens”, “cell mitosis stages” or “series vs parallel circuit for grade 8”, and it generates clean, high-contrast, white-background diagrams that drop straight into slides, worksheets, or exams.
It’s focused on clarity and consistency rather than fancy “AI art”. You can pick an approximate grade level so the diagram is simpler or more detailed.
It’s free to try right now. I’d love feedback on:
topics where you struggle to find good diagrams
missing export options / features
any obviously wrong or confusing outputs
Happy to answer questions and hear suggestions in the comments.

value: Show HN: ConceptViz – Generate STEM diagrams for teachers from simple prompts


value: tmpsterwfwegw

value: I utilize Supabase as the basis for many of the applications that I create. I find it valuable to pursue a test driven development strategy for both my organic coding as well as my AI assisted coding. This makes me lean on Testcontainers often. While there are Testcontainers available for many of the foundational building block services we all use, there was not one for Supabase (at least in Rust). So I created one. Hope this helps someone out there. Thanks.<p>Full disclosure I also use AI to assist me in doing this in a timely manner. If you find any issues or broken code, please submit an issue. I've added tests, but sometimes things fall through the cracks. Thank you.

value: Show HN: Supabase Testcontainers for Rust

author: tmpsterwfwegw


value: Show HN: Speculative Decoding from Scratch in PyTorch (2.8x CPU Speedup)


value: Show HN: Local AI that turns your computer activity into searchable memories


value: arianrhodsand

value:
I built RetroAssembly as a classic games cabinet that lives entirely in the browser. It's open source and free to use, and if you'd like you can even host your own instance with Docker (the Docker image is only ~70 MB).
What it does:
- Browse and play a library of classic systems (Nintendo, Sega, Arcade, etc.) from a single place.
- Works across devices, so you can start on one machine, save your progress, and continue on another.
- Automatically fetch game boxarts to enhance the library's visual appeal.
- Smooth keyboard and gamepad navigation.
- Rewind gameplay using a simple shortcut so you can correct mistakes.
Happy to answer questions and hear ideas on how to make it better!

value: Show HN: RetroAssembly – Retro game library built for web browsers

author: arianrhodsand


value: purrplexia

value:
pip install phi-engine
Source code and Mathematical Proof:
https://github.com/Purrplexia/LettersToMyHeroes
PyPI package:
https://pypi.org/project/phi-engine
Hi HN,
You are the first public audience to see this project. It has not been posted anywhere else yet. I chose to release it here first because Hacker News consistently rewards rigor, originality, and open-source tools built for ideas rather than for marketing.
This project contains entirely original mathematics. The core theory is proven in a rigorous 34-page proof titled "LetterToCantor.pdf" included in the repository. It builds a constructive continuum and a gridless analytic calculus from factorial moment laws and golden-ratio scheduling.
Derivatives and integrals of any analytic function can be computed *exactly* by a *frozen*, function-agnostic operator composed of exact rational coefficients (a "β-stream"). No grids, no step size, no limits, no symbolic math. Once synthesized, these operators work globally for every analytic function.
β-streams can be synthesized on-the-fly in milliseconds for thousands of digit accuracy, precompute is only needed if you want to push the boundaries of digits to comical scale.
Once a β-stream is synthesized or loaded, it is cached and reused on all future functions.
No recompute, no wasted cycles, no dependency on the function.
To make this reproducible and verifiable, the project includes phi-certificates: canonical JSON/gz files that store these global calculus operators as exact rationals, sealed with canonical SHA-256. Anyone can load a certificate, verify its key material, and use the operator forever on any analytic function. The certificate is the calculus rule itself.
A phi-certificate is a canonical, global, arbitrary-precision analytic instruction, sealed by a 32-byte hash.
All code is GPLv3-or-later. All math documents are CC-BY-SA 4.0. Everything is permanently free and open.
The repo includes:
- the full mathematical proof (LetterToCantor.pdf)
- the phi-engine (exact rational contraction engine)
- phi-certificates (deterministic, hash-verifiable analytic operators)
- demos of extreme derivatives and integrals (sin(googol x^2) in 400ms to 6000 digits)
- demos of engine logic
- demos of certificate loading and emission
- full reproducibility scripts and PGP verification
Every artifact in this repo is hashed and PGP signed, ensuring bit-for-bit reproducibility.
If you want to see the math, start with:
Cantor_GoldenContinuum/LetterToCantor.pdf!!!
It is a crafted experience for those who love mathematics.
If you want to try the engine immediately:
pip install phi-engine
(see examples/ after install)
If you care about reproducible, verifiable mathematics and globally reusable analytic operators, I hope you enjoy exploring this. I welcome questions, critique, and adversarial tests from the HN community — you are the first eyes on it — I will post it elsewhere later.

value: Show HN: Instant Calculus: frozen, function-agnostic, arbitrary-precision GPLv3

author: purrplexia


value: RobertChin

value:
I’m experimenting with combining coupons + cashback info on the same page (Expedia, Foreo, Jackery, Temu, etc.).
Goal: you don’t have to open 5 tabs to stack deals.
Curious what HN thinks about:
– UI for showing both coupon and cashback rates
– Any obvious privacy / dark-pattern traps I should avoid
– Monetization ideas that don’t degrade user trust

value: Show HN: MGCoupon – Cashback and coupons in one place for major brands

author: RobertChin


value: Qpphello

value:
I built Gossipdle, a daily logic puzzle where you decide who is guilty or innocent in a 5×5 grid of 20 characters, using only logical clues (no guessing allowed).
Each correct mark reveals a new clue, so you solve the puzzle as a chain of small deductions. Themes change daily (office gossip, campus drama, nightclubs, etc.), but the underlying puzzle is a clean Einstein-style logic grid.
I’ve just shipped a Timed Challenge Mode:
A separate puzzle from the main daily one (so you effectively get two puzzles per day)
Difficulty-based time limits (Mon–Tue easier, Sat–Sun hardest, with more time)
3 attempts per day; when the timer hits zero, that run is over
No hints in timed mode – pure reasoning under pressure
State persists across refresh/close, and there are checks around New York midnight so you don’t start a run when there isn’t enough time left in the day
If you like structured logic puzzles (Einstein riddles, nonograms, Sudoku-style deduction) and want a daily “thinky” game with a speedrun variant, I’d love feedback on:
How the difficulty feels
Whether the timed mode is fair/fun
Any rough spots in the UX
Link: [https://www.gossipdle.com]

value: Show HN: Gossipdle – Daily Logic Puzzle with a New Timed Challenge Mode

author: Qpphello


value: admtal

value:
Hi everyone, I made this app
Demo Scope lets you record or stream any mobile website with your face on screen and touch indicators showing every tap.
I built it because I needed to demo my own side projects and hated the OBS/desktop setup.
Load your site in the app, hit record, done. Or stream straight to Twitch/YouTube.
Free to try: https://apps.apple.com/us/app/demo-scope/id6755395174
Would love feedback if anyone tries it.

value: Show HN: Demo Scope – Record/Stream iOS Web Demos with Face Cam and Touches

author: admtal


value:
Hi All,
For the past few months I've been working on BlogLab. This is a tool I've created after wanting to grow SEO traffic for my other projects.
I ran a blog in 2022 which took a couple of hours per day which obviously meant I wasn't building as much as I would have liked to.
This inspired me to make BlogLab to automate the process of research, generation and publishing of SEO blogs.
I am sharing today as we launch into early access tomorrow for those on the waitlist!
I am incredibly excited and would love to get any opinions/feedback on this site.
Is this something you would use? Have you had any issues with products like this in the past?
A huge thank you to everyone who reads this post
Have a lovely day,
Rob

value: Show HN: I've created BlogLab to help grow my SaaS automatically


value:
Hi HN,
I’m working on a “hacker science” experiment called Ai_home.
It’s a cognitive architecture prototype that I designed to explore the current limits of LLMs in terms of persistent identity, long-term memory, and autonomy.
The system is not just a simple chatbot loop, but a multi-threaded architecture:
1. Worker: Handles user interactions and tool use.
2. Monologue: A background “subconscious” thread that analyzes context and logs intuitions/tips for the Worker.
3. Memory: Manages vector-based long-term memory (Postgres + pgvector) with emotional weighting.
4. Mind: This layer is responsible for deeper interpretation of messages and for exploring creative alternatives.
Because of this, it’s not a synchronous question–answer chatbot.
The model and the user (the Helper) can communicate in parallel, and the Worker processes this asynchronously.
Technical details:
- Hybrid Multi-LLM: I combine multiple models (Gemini, GPT-4, Groq). I use different models for creative idea generation (“creative”) and for logical processing (“interpreter”).
- Modes: I don’t use a single context window. Depending on the operating mode (General, Developer, Analyst), I partition messages into separate contexts. I’ve introduced a transition process between mode switches to ensure that the essential information is preserved across contexts.
- Dynamic Prompt: Based on memories and accumulated experience, I dynamically modify the prompt on every API call so that each conversation can gain a fresh contextual interpretation.
- Incubator: The system has an experimental environment where it can attempt to refactor its own code. The results are mixed so far, but it’s fascinating to watch a model interpret its own code.
- Identity and Laws: For building identity, the system has a “constitution” (fundamental laws) and tools for modifying them. The content and structure of this are still an active area of experimentation.
Disclaimer:
This is an architectural experiment to investigate whether functional patterns of consciousness (global workspace, recurrence) can be mimicked with LLMs in order to create more reliable agents.
I explicitly do not claim that the system is sentient, nor that this is a formal academic research project (We don’t have the personnel or infrastructure for that).
I’m looking for collaborators not only for coding, but also to help define a development methodology for this open, collaborative experimental project.
All feedback is very welcome!

value: Show HN: Cognitive AI architecture prototype with identity, memory, initiative


value: sdan

value: Show HN: Run LLMs locally with WebGPU

author: sdan

title: Show HN: Run LLMs locally with WebGPU


value: franze

value: Show HN: Geo / AI SEO Robots.txt Audit Tool

author: franze


value: Matzalar

value:
I built a tool to solve a problem I kept running into:
I was making product decisions based on guessing instead of real users. I kept building stuff nobody wanted as I was usually wrong.
So, I built HolyShift:
AI agents that validate product ideas by talking to real people on Reddit, HN, X, and LinkedIn … then generate a detailed GTM and “Should we build this?” report.
No synthetic data (ChatGPT).
No predictions.
Only real conversations from real people.
What it does
 • Posts platform-native questions (where allowed)
 • Collects real reactions, objections, pricing signals
 • Clusters feedback into themes (pain, demand, adoption, pricing …)
 • Runs a monitoring agent for sentiment analysis
 • Produces a short validation report (PRD + GTM)
All actions are rate limited and reviewed by a human for compliance.
How it works (technicals)
 • Multi-agent pipeline (intake → landscape → engagement → monitoring → synthesis → report)
 • Platform specific prompting (HN vs Reddit vs LinkedIn …)
 • Real-time sentiment + clustering via embeddings
Link
https://www.holyshift.ai
(Early beta)
What I’m looking for
 • What should stay human vs automated? Should we automate this 100%?
 • How do you do your product validation? Do you talk to your potential users (and who?) before you build?
Happy to answer anything.

value: Show HN: AI agents that validate your product idea by talking to real users

author: Matzalar


value: Berektassuly

value: Show HN: a Rust template for highly testable, production-ready services

author: Berektassuly


value: Punyakrit

value:
I’ve started working on Schema Pilot, an open-source idea for a visual database designer that generates Prisma schema + SQL automatically from a drag-and-drop interface.
Right now it’s very early — mostly the landing page + initial planning for the core engine. But the vision is:
visually create tables & relations
auto-generate FK logic
export clean Prisma + SQL
eventually import existing Prisma schemas
I'm building it in the open and would love feedback, contributors, or anyone interested in the problem space.
Repo: https://github.com/punyakrit/schema-pilot
Happy to answer questions!

value: Show HN: Schema Pilot – Visual Database Designer with Instant Prisma

author: Punyakrit


value: aliibnepasha

value:
I kept getting tricked by AI-generated images, so I made a small app where you’re shown two images (AI vs Real) and you guess the real one.
Nothing complex, no login, no fluff, just tap and check your instincts.
Would love feedback from the HN crowd.

value: Show HN: AI vs. Real – A simple game I built for guessing real images

author: aliibnepasha


value: arlindb

value:
Hi HN,
I just launched Tinyfocus, a small productivity tool designed specifically for solo founders and builders. The goal is simple: help you focus on what matters and get more done in less time.
Here’s what Tinyfocus does:
Lets you track your top tasks and prioritize efficiently.
Provides micro dashboards to keep your daily focus in check.
Lightweight, no distractions, no fluff.
I built it entirely by myself, iterating in public, and I wanted to share it with the community to get feedback.
It’s been crazy seeing how a simple tool can make such a difference in daily focus, especially when you’re juggling multiple projects as a solo founder.
Check it out here: tinyfoc.us
I’d love to hear your thoughts – any feedback, feature ideas, or bugs you notice.
Thanks!

value: Show HN: I Built Tinyfocus – A Minimal Tool to Help Solo Founders Focus

author: arlindb


value: ing-norante

value:
I built a browser-only tool that disrupts invisible AI watermarks using Canvas, geometry, noise, and JPEG recompression. No backend, no uploads, no tracking.
Pipeline:
Shake – Random rotation (±0.5°) + slight zoom
Stir – Low-amplitude RGB noise via getImageData
Crush – JPEG recompression at ~0.85 quality
Tested with SynthID (Google Gemini AI watermarking), and it remained undetected in all tests.
Pipeline improvements? What would you add/change?
Github: https://github.com/ing-norante/unmarker.it

value: Show HN: Unmarker.it – Client-Side Tool to Disrupt Invisible AI Watermarks

author: ing-norante


value: nktskr

value:
I’ve always struggled with waking up feeling groggy, even with enough sleep. A few months ago I started experimenting with waking up around local sunrise instead of using a fixed alarm time. It ended up helping me more than I expected — mornings felt calmer, and the wake-up was less abrupt.
I couldn’t find an app that did this cleanly without a bunch of extra features, so I built Solarm: a small iOS app that adjusts your alarm based on the sunrise in your location.
What it does
- calculates the sunrise for your city each day
- adjusts your wake-up time automatically
- optional “sunrise + X minutes” offset
- works even with Do Not Disturb
- no accounts, no backend, everything on-device
Why I’m posting
I’d like to hear impressions from people who care about sleep, circadian rhythm, or just smoother mornings. I’m especially interested in how well the sunrise-based approach works (or doesn’t) for others.
App Store link:
https://apps.apple.com/ua/app/sunrise-alarm-natural-clock/id...
I also have free offer codes for anyone who wants to try the full version — just mention it in the comments, I will provide you a link.
Thanks for taking a look. Happy to answer questions.

value: Show HN: Solarm – a simple iOS sunrise alarm I made to improve waking up

author: nktskr


value: janreges

value: Show HN: Turn Any Website into Clean Markdown for LLMs/RAG with SiteOne Crawler

author: janreges


value: devenj

value: Show HN: We got 30 teens to build a hand made arcade in Tokyo

author: devenj


value: wstaeblein

value: Show HN: A fun password strength meter I made for my teenage kids and friends

author: wstaeblein


value: daolm

value: We've built a service to easily call any international number at super cheap rates. You can call US numbers from your browser or your phone, from anywhere, for less than $0.05/min. You can also buy US numbers at approx $3/month. No subscriptions or signup fees, you just topup and start making calls.<p>Would love any feedback from startup founders/expats calling from abroad!

value: Show HN: Revolut for International Calls at cheap rates

author: daolm


value: ianberdin

value: Show HN: Boing #2

author: ianberdin

title: Show HN: Boing #2


value: ethjdev

value:
I kept seeing athletes struggle with messy Google Docs, PDFs, and random Instagram pages when trying to show coaches who they are. So I built Sportfoli, a minimal profile builder that creates a clean public page in minutes.
You just enter your details → it generates a shareable profile. No templates, no design work, no clutter.
Built with Next.js, Tailwind, and Supabase. It’s still early and I’d genuinely appreciate feedback from people who’ve launched small tools before — what to improve, what to cut, what’s missing.
Live here: https://sportfoli.com

value: Show HN: Sportfoli – A Simple, Clean Sports Profile Builder for Athletes

author: ethjdev


value: Show HN: GoodQuestions – a tiny site of genuinely good, human-curated questions


value: kierangill

value: Show HN: Generate Storyboards with Nano Banana from the CLI

author: kierangill


value: Show HN: Thermodynamic Alignment Forces Gemini Thinking into "Burn Protocol"


value: jMyles

value: Show HN: Memory Lane – bootstrap your naive Claude instances with their history

author: jMyles


value: fuegoio

value:
Hello HN!
I'm a European traveler, and during my last 6 months of travel I created an app to keep track of my expenses. I made it open-source and started to build a website and a documentation for other people to use it!
It's a fairly simple PWA that you can install on mobile that can help you set a budget, keep track of expenses and analyse what you spend.
Thanks for any feedback and keep traveling guys!

value: Show HN: Tracktrip, Travel Expense Tracker

author: fuegoio


value: I built KarBug v1.0, an AI that understands coding errors the way humans do. Instead of confusing, cryptic messages, it explains what went wrong in plain English and gives guidance on how to fix it.<p>No more copy-pasting errors into other tools and getting even more errors. Just tell KarBug your error, and it explains it clearly, simply, and step-by-step

value: Show HN: KarBugv1.0-Explain your errors like you're 5 in plain text and fix


value: Show HN: Identifiy test coverage gaps in your Go projects


value: nevenp

value:
Hi HN,
I built Aion, an “AI longevity coach” that integrates three data sources that are usually siloed:
Wearable data (e.g., Whoop, Oura, Apple Health: sleep, HRV, strain)
Blood tests (hormones and basic longevity markers)
Simple phone-based facial scans
The aim is to provide a clearer picture of energy, hormones, sleep and recovery over time and to translate this into straightforward daily recommendations (sleep timing, caffeine window, training intensity, light exposure), rather than just another metrics dashboard.
Link: https://www.aionlongevity.com/
Demo video: https://www.youtube.com/watch?v=BR9AScuVGjA&feature=youtu.be
A 7-day free trial is available.
I would appreciate feedback on:
Whether this addresses a real need or feels redundant with existing tools
What you would require (export options, transparency, controls) to consider using a product like this
Thank you,
Neven

value: Show HN: Aion – AI longevity coach using wearables, blood tests and facial scans

author: nevenp


value: Show HN: CLI that generates and prepares to email PDF invoices


value: GenLabs-AI

value:
Built this because AI coding shouldn't cost hundreds per month. It's Cline with free Open Source and Deca models plus cost tracking for when you need GPT-5/Claude. The free tier handles 70% of daily coding.
Try it: https://github.com/GenLabsAI/Agentica/releases/tag/v0.0.1
You can use a demo email and password for testing: (demo: agentica@genlabs.dev / agentica@123)
Looking for feedback on where the free models fall short. Building sustainable AI tools for developers.

value: Show HN: Free AI Coding with Open Source and Deca Models

author: GenLabs-AI


value:
hey HN,
I’ve been building this project through a lot of late nights and messy iterations, and it’s finally stable enough to share.
utm.one is a clean, distraction-free URL shortener with built-in UTM discipline.
it auto-prevents duplicates, applies consistent naming, and keeps your tracking clean using the Clean-Track framework .
I’m launching a controlled beta, so things are intentionally simple and safe for testing.
would love feedback on:
1. does the flow feel intuitive?
2. anything confusing or missing?
3. would you trust it for real campaigns?
Website - https://utm.one
next up: a partner + affiliate program built into the same tracking architecture.
thanks for taking a look any feedback (good or brutal) really helps.

value: Show HN: I built utm.one a clean, minimal shortener+UTM governance tool (beta)


value: steveharrison

value: I've updated my CSS advent calendar for this year. Last year, I was using Windsurf to generate the code and content—it had heaps of broken links. This year, I used Claude Code to update the content and every link worked! Pretty cool how much AI coding has advanced in the past year.

value: Show HN: CSS Advent Calendar 2025

author: steveharrison

title: Show HN: CSS Advent Calendar 2025


value: abilafredkb

value:
88% of business cards are thrown away within a week.
The average professional collects 200+ business cards per year. That's 176 contacts lost. If even 10% could've been valuable connections, we're talking about massive opportunity cost.
I got obsessed with this problem after watching my own business card graveyard grow. Built a real-time networking platform (Yenhyia) that makes business cards irrelevant.
The insight: The problem isn't paper vs digital cards. It's the entire networking workflow.
Traditional flow:
1. Arrive at event blind
2. Random encounters
3. Awkward small talk
4. Exchange cards
5. Cards go in pocket/wallet/trash
6. Never follow up
New flow with Yenhyia:
1. See attendees before event (prep who to meet)
2. Match based on goals (mutual opt-in)
3. Chat starts with context (you both chose each other)
4. Meet in person (not random, intentional)
5. Digital card auto-shared in chat thread
6. Contact synced to phone, conversation history preserved
The technical interesting bits:
- Built matching algorithm that weighs profile similarity, goals, and real-time proximity
- Real-time venue mapping so you can find your match in a 5,000 person conference
- Privacy-first: location data is ephemeral, deleted post-event
- One-tap QR check-in: organizers can deploy without any tech integration
What surprised me:
1. Privacy toggle gets used A LOT. People want to control when they're discoverable. Not everyone wants to network for 8 straight hours at a conference.
2. Pre-event matching has higher engagement than on-site. People actually do their homework before showing up.
3. Event organizers care more about "connections made" metrics than we expected. They want to prove ROI to sponsors and attendees.
Tech stack: React Native, Firebase real-time DB, Node.js, serverless on Google Cloud.
Launched in Ghana/Nigeria because the professional networking ecosystem is still forming here. No legacy LinkedIn graphs, everyone's building from scratch. Perfect test market.
Questions
- How would you approach matching algorithms with sparse initial data?
- Best way to handle real-time location at scale (5K+ concurrent users) without destroying battery?
- Thoughts on privacy in location-based apps? We delete everything post-event but curious about other approaches.
Code isn't open source yet but considering it for the venue mapping component.
Try it: yenhyia.buzzchat.site
Feedback welcome, especially on the tech and privacy angles.

value: Show HN: The $1B problem with business cards nobody's solving properly

author: abilafredkb


value: theolouvart

value: Show HN: Data lineage diagrams 10x faster than draw io

author: theolouvart


value: amywangyx

value:
Hey HN,
I built Fin2Cents to help people learn to invest without risking real money or sliding into meme-stock gambling.
You can construct and stress-test portfolios using Mean-Variance Optimization (Markowitz / 1990 Nobel) every day. On top of that, there are:
• Short, gamified lessons on risk, return, and diversification
• A live leaderboard that tracks daily (simulated) returns of your portfolios.
The problem I’m trying to solve: most people either
1. YOLO into whatever’s trending, or
2. Avoid investing completely because it feels scary/opaque.
Fin2Cents aims for a middle path: helping people build wealth calmly with time-tested ideas, not vibes.
Would love feedback from the HN community — on the product, UX, or the approach in general.
iOS: https://apps.apple.com/us/app/fin2cents/id6754194187 (invite code: 2PZJmJ).
Happy to answer any technical/product questions in the comments.

value: Show HN: Fin2Cents – Learn investing by sandboxing portfolios with real data

author: amywangyx


value: simonsarris

value:
Please note this site requires Twitter/X to log on, and requires $12 if you want to place a pin.
I made this as a sort-of social network helper, a spatial directory of people who want to find and be found.
I would be happy for any feedback or feature suggestions. Right now Twitter/X is required because it adds a sense of real-ness to the pins. I could imagine other globes for other social networks, but I think the lack of overlap is a feature.

value: Show HN: Meetinghouse.cc, a site to find and be found

author: simonsarris


value: venkii

value: Show HN: Martial Lint – improve Chinese Wuxia novel translations with LLMs

author: venkii


value: qwikhost

value: 1000's of Journalists from the top media outlets. Save days of research, and pitch the right person.

value: Show HN: Reporters.io – Find and Connect with the Right Journalists

author: qwikhost


value: UmGuys

value: I started this project 3 weeks ago with the goal of finishing before I start a new job tomorrow. I didn't meet the goal, but it's a pretty decent start. Scrappy is a CLI code assistant the runs entirely on free tier providers.<p>I'm sure my dev velocity will slow down now, but I'll keep at it. Please clone, fork, hack away!

value: Show HN: Scrappy Free AI Code Assistant

author: UmGuys

title: Show HN: Scrappy Free AI Code Assistant


value: Free plagiarism checker, accurately check texts and documents, while also correcting grammar errors and improving article quality.

value: Show HN: Free Online detection and content quality assurance tool


value: ozgrakkurt

value: Show HN: FastLanes based integer compression in Zig

author: ozgrakkurt


value: Show HN: Fabricate a GitHub persona and commit history with 1 command


value: zlwaterfield

value: Show HN: Open-source GitHub to Slack notifications

author: zlwaterfield


value: takennap

value:
I’ve just updated the design of to make it cleaner, faster, and easier to use on both desktop and mobile.
It’s a short “mental age” quiz you can finish in a couple of minutes. No login, no email, just answer the questions and see your result.
I’d love feedback from the HN community on the new look & feel, usability, and any rough edges you notice (copy, UX, performance, etc.). Thanks for trying it out!

value: Show HN: What's your mental age? Try It

author: takennap

title: Show HN: What's your mental age? Try It


value: superfa

value: Show HN: Filmgine – AI Story Generator and Video Maker

author: superfa


value: AIEnhancer is an AI image enhancement tool offering free online features like photo repair, background removal, and watermark removal to improve image quality.

value: Show HN: Online AI Image Quality Enhancer for Free


value: tjwells

value: Show HN: C++ order book matching engine (3.2M orders/SEC, ~320ns)

author: tjwells


value:
I am looking for contributors for an open-source spec called AWAS that lets AI browsers and agents interact with websites via a clean JSON action manifest. The idea is to allow existing websites to interact with AI agents and browsers without disrupting transitional browsing.
Currently, AI agents and AI browsers essentially browse websites trying to mimic a human by clicking around, entering data in search fields, etc. This complicates things as well as waste computational resources for agents. On many websites, it doesn’t even work that well. This is an effort to standardize for AI agent access in a way that can be implemented rapidly and without disrupting user driven browsing.
I’m looking for a few developers interested in AI agents, APIs, or web standards to help refine the spec, add examples, and test it on real sites.
Repo: https://github.com/TamTunnel/AWAS
I’d really appreciate feedback, issues, or small PRs from anyone building AI tools or modern web backends.

value: Show HN: AWAS – An open standard for AI-readable web actions


value:
Hi HN! I've been working on two novel programming languages built on field theory
from superconductor research.
*WPE/TME* - A geometric calculus language for structural and temporal reasoning.
Think: mathematical notation for encoding semantic relationships. Four parameters
(domain, shell, phase, curvature) let you explicitly represent how components
couple, influence each other hierarchically, and evolve over time.
*Crystalline* - A code synthesis language that generates provably optimal code
through physics-guided evolution. Not template filling. It discovers novel
optimizations (async I/O, streaming, parallelization, loop fusion) through energy
minimization, achieving 3-4× performance improvement.
Both languages share the same geometric foundation from superconductor physics but
serve completely different purposes. WPE/TME is for semantic reasoning (great for
LLM scaffolding). Crystalline is for generating high-performance code.
Key differences from existing approaches:
- Deterministic (same input always produces same output)
- Explainable (energy equations show WHY decisions were made)
- Novel code generation (genuinely discovers optimizations)
- Mathematical guarantees on performance
Crystalline has a Python implementation. WPE/TME has a Python reference
implementation, but it's really a notation system (like how LaTeX is a language
for typesetting math).
GitHub: [will add link on launch day]
Papers: [will add ResearchGate links - 3 papers explaining theory]
I'd love feedback on:
1. The language design - does geometric encoding make sense?
2. For Crystalline: what benchmarks would convince you the synthesis works?
3. For WPE/TME: would explicit structure help your AI reasoning tasks?
Happy to answer questions about the physics, the languages, or the implementations!

value: Show HN: Two physics-based programming languages (WPE/TME and Crystalline)


value: tuhel

value: I built Notionfile as a simple way for founders to get clean, ready-made Notion templates without having to create everything themselves. It’s a small design-focused project, and I’d love feedback on the UX, template structure, and overall experience.<p>Thanks for checking it out!

value: Show HN: Notionfile – Notion templates designed to reduce founder friction

author: tuhel


value: Show HN: Tera.fm – Listen to Hacker News instead of reading it


value: devanimecx

value: Show HN: BirdWrite – The AI Engine for World-Class Content

author: devanimecx


value: mfa

value:
I've been working on CurioQuest, a simple, clean trivia/fun facts game. It started as a little project for my friends and family and they've encouraged me to clean it up and make it public.
I'd love to get feedback from actual web game enthusiasts before adding the next batch of categories and questions!
This is not a commercial product; it's a labor of love that's still in development. It doesn't have all the planned categories yet, but there's reasonable content: little over 2600 questions, 7 categories, 4 levels of difficulty per category, 2 languages (English and Portuguese), PWA so you can "install" it on your phone or desktop.

value: Show HN: CurioQuest – A simple web trivia/fun facts game

author: mfa


value: deepanshkhurana

value:
A couple of weeks ago, I built and released Ode. It is opinionated and its ethos come from my own work over the years as a writer. This is documented in more detail in the repository, too, and I have done my best to keep the documentation as thorough as possible. Last night, I released v1.2.0 with presets and theming.
Ode focuses on simplicity, plain Markdown, and a workflow that stays out of the way. No numbers, no metrics, just writing and reading. The app features:
- docker-compose for easy setup
- markdown-based writing with a content repository
- a beautiful reader mode with gestures, arrow-key navigation and custom checkpointing so bookmarks are never lost
- 10 presets with full or partial override supported
- dark/light themes for all presets
- RSS feed generation on build-time
- sitemap generation on build-time
- random piece for readers to start with serendipity
- build-time generation for a blazing fast app
- fully customisable with config.yaml
- no tracking, no analytics, no boxes, no search
I wanted something lighter and less noisy than modern publishing platforms, so I built the tool I wanted to use. I figured I'll share this with the wider world in case someone is looking for something similar.
Feedback is welcome and I will try to include anything that fits within the ethos of Ode!

value: Show HN: Ode, a self-hosted app for writers who love the craft

author: deepanshkhurana


value: hilti

value:
It's this time of year to discover cool projects bringing back memories of the good old days.
I am still learning ImGUI and this is a master piece in my opinion.
https://github.com/tildearrow/furnace

value: Show HN: Furnace – the ultimate chiptune music tracker

author: hilti


value: amiban

value:
every social app is trying to be Instagram + Snapchat + TikTok + X. I still want to see what my friends are up to, but don't want to wade through endless irrelevant slop. So I built a simple, chronological photo log.
Photos only. No AI generation, no video reels.
No algorithm. You see 100% of what your friends post, in order.
would love HN's thoughts on whether single purpose social apps can still exist.

value: Show HN: Photo app that does just one thing – no stories/reels/algorithm

author: amiban


value: mrgoonie

value: Show HN: The missing layer between Claude Code and production-ready software

author: mrgoonie


value:
I built this quiz after realizing how good AI has gotten at mimicking literature, speeches, and images. It's one strike and you're out.
It includes AI-generated Shakespeare, fake MLK speeches, photorealistic images, and movie dialogue. I got several of my own questions wrong while building it.
This isn't about testing your English degree, it's more about showing how well AI can now forge canonical cultural references. We've hit a point where the fakes are genuinely convincing.
Where AI still slips up:
Over-explanation (real Shakespeare is more economical)
Generic metaphors vs. specific imagery
Too polished (humans are messier)
But these tells are fading fast!
Built with React, ~50 questions (for now). The images are tough if you haven't already seen them before.
Curious what scores people get.

value: Show HN: Can you spot AI-generated content? (spoiler: probably not)


value:
Hi HN,
I got tired of rate limits and slow responses from the official vulnerability databases while building a security tool. So, I decided to build my own solution.
I processed 25 years of CVE data (1999-2025), cleaned it for LLM context, and indexed it on a lightweight SQLite backend hosted on Render.
It returns structured JSON suitable for AI agents and security automation tools.
*Tech Stack:* Python FastAPI, Pandas (for ETL), SQLite (for search), Hugging Face (for data storage).
It is live on RapidAPI with a free tier for developers:
https://rapidapi.com/cyberapiui/api/cybersec-intelligence
Would love to hear your feedback!

value: Show HN: I built a fast,free CVE Search API(300k+records)because NVD was tooslow


value: shouldabought

value: I created this to help students and those with an interest to become more familiar with key UK case law.  Let me know what you think

value: Show HN: Case-IQ UK case law generator

author: shouldabought

title: Show HN: Case-IQ UK case law generator


value:
I’ve been working on a small project that started after my grandma showed me some old black and white photos of my grandpa over Thanksgiving. I already had an older AI project with most of the pieces built, so I reworked it into a simple web app that colorizes old photos.
It’s not a commercial product in any serious sense. I cleaned it up enough to make it usable, and it’s now a small SaaS with accounts, Firebase on the backend, and Stripe for credits. The processing is pretty fast and works reasonably well on most scans.
Would be glad to hear about any issues you run into or ideas for where the model or pipeline could be improved as I keep working on it.

value: Show HN: A photo colorizer I built after revisiting old family photos


value: taurusai

value:
Tired of sending CVs that get ignored?
Taurus AI builds a custom, JD-matched CV in seconds — optimised for recruiters and ATS filters.

value: Show HN: CV, Rebuilt for the Exact Job You Want

author: taurusai


value: postgresapp

value:
Postgres.app is the easiest way to run PostgreSQL on your Mac.
We often get requests to add specific extensions, but we can't include everything. So now we added a way to download additional extensions!
For now we have just a handful extensions for download. Is there anything else we are missing?

value: Show HN: Downloadable Extensions for Postgres.app

author: postgresapp


value: skvark

value:
It has been almost 10 years since I started the opencv-python packaging project. Scaling it to more than 100 million downloads as a side project showed me how much ease of installation and proper package distribution matter to users. It gave the computer vision ecosystem a noticeable boost. Now I have a new idea that I hope can help even more people across the broader software engineering world.
A while ago, I realized I kept giving the same advice to teammates and friends when they ran into a programming issue they couldn't easily solve: go to GitHub and look at how others solved it.
There is a huge pool of underused example material across open source. Most problems developers face are not that novel. With enough digging, someone has already solved the same issue in code or at least posted a workaround to an issue or discussion thread.
The trouble is that GitHub search is limited and works only when you already know the right keywords. You also need the time and patience to go through and read all the results, connect information across files, repositories, issues, discussions, and other metadata, and then turn that into a working solution. The same limitations apply to Stack Overflow and other search tools.
LLMs changed a lot, but they did not change this. They do not perform equally well across all programming languages, and their training data is always stale. They cannot reliably show how to combine multiple libraries in the way real projects do. For these and many other cases, they need a real, canonical code example rather than an outdated piece of documentation written for humans.
That is why I started building GitHits. It is designed to handle the work that humans and AI coding agents struggle with: finding real solutions in real repositories and connecting the dots across the open source ecosystem.
GitHits searches millions of open-source repositories at the code level, finds real code and surrounding metadata that match the intent of your blocker, and distills the patterns it finds into one example.
The initial product is in private beta, with MCP support to connect GitHits to your favorite coding agent IDE or CLI.
What makes it different from Context7 and other generic documentation search tools:
- It is built around unblocking, not general search
- It does not require manual indexing jobs
- It works for humans through the web UI and for agents through the MCP
- It clusters similar samples across repositories so you can see the common path real engineers took
- It ranks the sources using multiple signals for higher quality: the selected sources might be, for example, a combination of code files, issues, and docs
- It generates one token-efficient code example based on real sources
It is not perfect yet. Right now, GitHits supports only Python, JS, TS, C, C++, and Rust. More languages and deeper coverage are coming, and I would appreciate early feedback while the beta is still taking shape. If you have ever lost hours stuck on a blocker you knew someone else had solved already, I would love to hear what you think.

value: Show HN: GitHits – Code example engine for AI agents and devs (Private Beta)

author: skvark


value: markjivko

value:
I made this tiny module that allows you to export any web page as video - locally.
- export in either AV1 or H264 format
- control the number of frames per second
- control the scroll speed
- export with Device Pixel Ratio on MacOS
I think this might be super useful for website demos, personal portfolios, competitor research, or marketing campaigns. The ability to record video during workflows might also be useful for UI/functional testing.
The module itself is fully editable, and exportable as a .YAML file.
Let me know what you think!

value: Show HN: HTML to Video

author: markjivko

title: Show HN: HTML to Video


value: jiaweixie

value: I used to be a lawyer and made some apps' privacy policies. Now, I have developed a software that scans projects and generates a policy.

value: Show HN: Generate a privacy policy for your app with one click in VS Code

author: jiaweixie


value: icepuma

value: Show HN: Advent of AI Security 2025

author: icepuma

title: Show HN: Advent of AI Security 2025


value: yanivgolan-lool

value:
Release v0.1.0 of mcp-bash-framework, a lightweight Bash implementation of the Model Context Protocol (MCP). It lets you turn shell scripts and CLI tools into MCP-compatible servers for seamless integration with AI agents - no Python, Node.js, or other runtimes required.
Key features:
- Zero dependencies: Runs on macOS, Linux, and Windows (via Git Bash/WSL).
- Core MCP support: Tool/resource/prompt handling, schema validation, progress streaming, cancellation, and pagination.
- Auto-discovery of scripts for easy setup.
- Scaffolding generators to kickstart projects.
- Examples included, like an ffmpeg-based video studio.
Great for quick AI experimentation, prototyping, or minimal environments.
Feedback and contributions welcome!
Repo: https://github.com/yaniv-golan/mcp-bash-framework
Release notes: https://github.com/yaniv-golan/mcp-bash-framework/releases/t...

value: Show HN: MCP-Bash-Framework – Zero-Dependency Bash for Building MCP Servers

author: yanivgolan-lool


value: Show HN: CodeProt – AI code review that reduces noise (94% precision)


value: monom

value: Show HN: Lx – CLI for creating repeatable LLM context from files

author: monom


value:
So, during my internship I worked on a few RAG setups and one thing that always slowed us down was to them. Every small change in the documents made us reprocessing and reindexing everything from the start.
Recently, I have started working on optim-rag on a goal to reduce this overhead. Basically, It lets you open your data, edit or delete chunks, add new ones, and only reprocesses what actually changed when you commit those changes.
I have been testing it on my own textual notes and research material and updating stuff has been a lot a easier for me at least.
repo → github.com/Oqura-ai/optim-rag
This project is still in its early stages, and there’s plenty I want to improve. But since it’s already at a usable point as a primary application, I decided not to wait and just put it out there. Next, I’m planning to make it DB agnostic as currently it only supports qdrant. Also might want to further improve the MCP feature, to make it accessible on other applications.

value: Show HN: I built a small tool that lets you edit your RAG data efficiently


value: intabli

value: Access 12 specialized executives instantly—no hiring, no overhead, no waiting. Scale your leadership capacity without the cost.

value: Show HN: CSuite.Now – Access a full bench of AI-driven C-suite advisors

author: intabli


value: ianberdin

value:
Hi HN! Some of you might remember my 2022 post about building a JavaScript sandbox alone for 6 years.
A lot has happened since:
- 200K monthly users → 11M total users
- 23M projects created
- 9 years total (yes, I started in 2016)
The biggest update: I built an AI coding agent. Works like Cursor, but entirely in your browser. No downloads, no setup.
Why browser-based AI coding makes sense:
- Instant start (no VS Code, no API keys)
- Works on any device
- Perfect for business automations, landings, blogs, prototyping, learning, interviews
- Share your work with one link
The AI part:
- All the latest 12+ models (Claude, GPT, Grok, Gemini)
- Real-time streaming
- Multi-file editing
- Pay only for what you use
Still bootstrapped. Still mostly solo. Competing with well-funded startups now, but 11M users and 18 years of refinement is hard to replicate. Yea, I'm insane.
Try it: https://playcode.io
Happy to answer questions about building a browser IDE or adding AI to a mature product!

value: Show HN: 3 yrs later, my JS sandbox has 11M users and an AI agent

author: ianberdin


value:
Flowctl is a self-service platform that gives users secure access to complex workflows, all in a single binary. These workflows could be anything, granting SSH access to an instance, provisioning infra, or custom business process automation. The executor paradigm in flowctl makes it domain-agnostic.
This initial release includes:
- SSO with OIDC and RBAC
- Execution on remote nodes via SSH (fully agentless)
- Approvals
- Cron-based scheduling
- Flow editor UI
- Encrypted credentials and secrets store
- Docker and Script executors
- Namespaces
I built this because I needed a simple tool to manage my homelab while traveling, something that acts as a UI for scripts. At work, I was also looking for tools to turn repetitive ops/infra tasks into self-service offerings. I tried tools like Backstage and Rundeck, but they were either too complex, or the OSS versions lacked important features.
Flowctl can simply be described as a pipeline (like CI/CD systems) that people can trigger on-demand with custom inputs.
Would love to hear how you might use something like this!
Demo - https://demo.flowctl.net
Homepage - https://flowctl.net
GitHub - https://github.com/cvhariharan/flowctl

value: Show HN: Flowctl – Open-source self-service workflow automation platform


value: xrmagnum

value:
Here is a demo of TunnelBuddy: an Electron app which lets one trusted friend share their internet connection with you over a P2P HTTPS proxy built on WebRTC.
It’s in the same spirit as uProxy, but instead of relying on deprecated browser socket APIs, it uses Electron + Node.js to run a local HTTPS proxy and WebRTC data channels between two peers.
There’s no signup and no accounts: the person sharing their connection generates a one-time code and sends it to their friend, who pastes it in to connect. Hopefully that gives some old-school TeamViewer vibes to anyone watching.
It’s free to use; there’s an optional donation button in the app, but no ads or upsells.
Demo video: https://www.youtube.com/watch?v=r-xP46dkioo
Site: https://www.tunnelbuddy.net/
Happy to answer any questions about how it works, security model, trade-offs vs VPNs/Tailscale, etc.
Oli

value: Show HN: TunnelBuddy Demo: HTTPS P2P proxy using WebRTC [video]

author: xrmagnum


value: Show HN: How to send large files securly?


value: keepamovin

value: Show HN: A constraint puzzle where you factor semiprimes in any radix

author: keepamovin


value: jiangdayuan

value:
Hey,
I built an open-source tool that lets you build draw.io diagrams using LLMs.
Unlike image generators, this manipulates the actual draw.io XML. This enables a hybrid workflow: prompt the AI to build a base architecture, tweak it manually on the canvas, then ask the AI to refine it again.
Key features:
 - Cloud Ready: Native support for AWS, GCP, and Azure icon sets (not generic boxes).
 - Dynamic: Supports animated connectors and vector sketching (e.g., "draw a cat").
 - Model Agnostic: Works with OpenAI, Anthropic, Bedrock, and Ollama.
I'd love feedback on the app, or ideas for v2 (e.g., add MCP feature). Any ideas are appreciated. Thanks!
Demo: https://next-ai-drawio.jiang.jp/
Repo: https://github.com/DayuanJiang/next-ai-draw-io

value: Show HN: Next AI Draw.io – Interactive Diagrams Creating with LLMs

author: jiangdayuan


value: ziad-hsn

value:
I read Anthropic and Cloudflare latest articles about AI agents struggling with context bloat and agents bad execution using MPCs and how they excel at executing tasks using Typescrip. I built CodeModeTOON for my own workflows and it's been solid so far so i decided to publish it.
What it does:
- TOON compression: Extracts schema from structured JSON, compresses values. Gets 30-90% savings on structured data (K8s manifests, logs, API responses).
- Lazy loading: MCP servers only start when needed.
- Pre-built workflows: Research, K8s auditing, incident analysis.
limitations:
- Unstructured text compresses poorly (~4%).
- Uses Node.js vm module, so not suitable for multi-tenant deployments.
It's MIT licensed.
GitHub: https://github.com/ziad-hsn/code-mode-toon
- https://www.anthropic.com/engineering/code-execution-with-mc...
- https://blog.cloudflare.com/code-mode/
Happy to answer any questions about the implementation and feedback will be very appreciated.

value: Show HN: CodeModeTOON – MCP orchestrator for workflows in TypeScript

author: ziad-hsn


value: sparkydev

value:
Meet S.P.A.R.K.Y — The world's first Sovereign AI built for Private Intelligence.
sparky.mtsllc.us
Sign Up for a FREE trial until 31st December.
S.P.A.R.K.Y is a fully sovereign knowledge companion that thinks only with the information you upload — your documents, your datasets, your verified sources. Trained by you, from your verified sources and for your specific needs.
#SovereignAI #PrivateAI #EnterpriseAI #GovTech #SparkyAI

value: Show HN: S.P.A.R.K.Y – The First Sovereign AI for Private Intelligence

author: sparkydev


value:
Hello HN,
We (HYVOR) are excited to launch two new products today:
Hyvor Post (https://post.hyvor.com): a simple, privacy-first newsletter platform with zero tracking.
Hyvor Relay (https://github.com/hyvor/relay): a self-hosted email delivery service. An alternative to services like AWS SES or Mailgun.
We've been working on these two projects for almost a year, and we are super excited to finally release them.
Our release announcement has more insights: https://hyvor.com/blog/hyvor-post-relay. In short, we first added newsletter features to Hyvor Talk (our commenting system), and it proved to make things complicated. So, we started working on Hyvor Post as a standalone newsletter platform. Then, we could not find an SMTP provider that does not include tracking features and has reasonable pricing - so we built our own: Hyvor Relay.
Both products are open-source under AGPLv3. Hyvor Post is cloud-only at the moment. Hyvor Relay is self-hosted only. Compared to traditional solutions like Postfix, Hyvor Relay makes it very hard to make mistakes when sending emails by having built-in health checks for DKIM, SPF, PTR, a DNS server to automate records, etc. Building Hyvor Relay was a significant undertaking for our small team, and we are very happy that we now have a reasonably stable version. We are also working to release a public cloud version in 2026 to help developers reduce email sending costs significantly.
Our team is around on HN - feel free to ask any questions!

value: Show HN: Hyvor Post (privacy-first newsletters) & Relay (self-hosted email API)


value: zkMesh: Open protocol for any edge to silently drop Layer-7 bots/DDoS via hardware-rooted ZK proofs on a permissionless mesh. No CA, no tokens, no PII—attack traffic scales your validators.  Full spec (CC0): [PDF link in repo].

value: Show HN: ZkMesh – federated ZK bot mitigation


value: clementjanssens

value:
Hey everyone,
With AI for photo and video getting CRAZY good and insanely precise, I realized that editing videos can be a real challenge
You gotta prompt, generate images, sometimes create starting/ending shots, generate videos, edit, and so on
So, I made an AI video editor that lets you edit AI videos in no time using the latest models (Nano banana pro, Veo 3, Sora 2, ...)
No idea if anyone out there will find this useful, but here’s a speed-up vid of me making a short clip
I’m not expecting much from this project, but if ppl like it, I have tons of ideas to take it to the next level and make the experience super cool
For anyone curious to try it, you get a 15-min trial when you sign up
https://renderize.studio
No pricing or anything for now, not the main goal, but if anyone’s interested, hit me up on WhatsApp (link in the app under support) and I’ll explain how to add your API keys
Hope you find the tool as cool as I do

value: Show HN: I made an AI video builder

author: clementjanssens

title: Show HN: I made an AI video builder


value: Show HN: SmartSort – Open-source, local-first file organizer with OCR/AI


value: benday

value:
I built aipatch after running into repeated problems with AI coding tools that would eventually fail to apply patches correctly or ignore parts of the instructions. They often kept doing things I didn’t ask for, especially when the context got even slightly unusual.
I wanted something simpler and more explicit: a tool where I control exactly what goes into the LLM prompt, and the model responds with deterministic SEARCH/REPLACE blocks that can be applied automatically.
The main idea behind aipatch is:
- You choose the context manually (from one or multiple projects).
- You send it to any LLM you prefer.
- The model outputs structured patch blocks.
- aipatch applies them to the codebase and logs everything.
The part that turned out most useful for me is multi-project prompting. I often need to update backend + frontend + documentation together, or compare two git commits, or port a feature from a small prototype into a larger repo. Existing tools don’t handle this well, so aipatch lets you give each project its own ID and merge them into a single prompt.
I also found that the best “prompt” is often just another working project that already behaves the way you want your project to behave. Including a small prototype or reference repo in the context gives the LLM a clear example and produces much more accurate patches than trying to describe everything in plain text.
A short demo video ("I improved aipatch using aipatch") is here:
https://youtu.be/xho0pMKPu14
GitHub:
https://github.com/bendaydots/aipatch
It’s a CLI tool written in Python, works with any LLM, and doesn’t require an editor integration or an account. I’d appreciate feedback from anyone who works with LLM-assisted development or multi-repo workflows.

value: Show HN: Aipatch – a CLI for multi-project AI code editing

author: benday


value: Show HN: Soppo – A Golang superset that adds enums, pattern matching, nil safety


value: saretup

value:
Heat Cue is an AI powered mini game where you have to guess a hidden noun and get constant feedback on how "Hot" or "Cold" you are to the target noun.
I liked playing 'Hot or Cold' type games online but most were not very accurate in estimating the proximity of different words across a variety of domains.
Seemed like an easy job for LLMs to do, so I made this game inspired by Wordle and r/HotAndCold. Would love some feedback :)

value: Show HN: Heat Cue – An LLM Powered Mini-Game About Finding Hidden Nouns

author: saretup


value: vvin

value: Show HN: I built a playground for training and visualizing LLMs in the browser

author: vvin


value: nesall

value:
Hi HN! Solo dev here. I built PhenixCode as an open-source alternative to GitHub Copilot Chat.
Why I built this: I wanted a code assistant that runs on my hardware with full control over the models and data. GitHub Copilot is excellent but requires a subscription and sends your code to the cloud. PhenixCode lets you use local models (completely free) or plug in your own API keys.
Tech stack: Pure C++ with RAG architecture (HNSWLib for vector search, SQLite for metadata). The UI is Svelte + webview. It's designed to be lightweight and cross-platform.
Current state: I've been dogfooding it for several weeks on my own projects. The core is solid, but I'd love feedback from others—whether you find it useful or discover bugs, both are valuable.
Happy to answer questions about the architecture, design decisions, or anything else!

value: Show HN: PhenixCode – Open-source, self-hosted alternative to Copilot Chat

author: nesall


value: HTTP/HTTPS Data Loss Prevention proxy designed to sanitize sensitive information before it reaches external LLM endpoints. Demo: https://asciinema.org/a/VKFol51SRDzleQKY7c2ZmgUKz

value: Show HN: Aidlp – The easy-to-use DLP for the public LLM endpoints :)


value: anothrNick

value: Show HN: A workspace for building and enriching datasets with your own LLM keys

author: anothrNick


value: Show HN: Ward: Modern AI antivirus to protect non-savvy web users from scams


value: askerkurtelli

value:
I kept losing ideas in long chats, so I built a tiny Chrome extension to make navigating between turns/prompts way easier.
Idk why this isn't a native feature on all LLMs.
Anyway, free and open source on GitHub or the Chrome Store. Hope it's helpful!
Chrome Store: https://chromewebstore.google.com/detail/scroll/mpcklmodkihb...
GitHub: https://github.com/asker-kurtelli/scroll

value: Show HN: Scroll – Table of contents navigation for LLM convos

author: askerkurtelli


value:
Hi HN! I wanted to share a small experiment I ran: I tried to see if I could build and deploy a full-stack Rust app from a single prompt using Claude Opus 4.5 and Shuttle.
I asked Claude to build a personal finance tracker with Axum + SQLx, write the migrations, generate the frontend, and deploy it. I expected it to fall apart somewhere… but it actually produced a clean, working Rust app that compiled, migrated, and shipped.
This was the prompt:
Build a Personal Finance Tracker web application with the following requirements:
*Backend (Rust + Axum + SQLx):*
- Use Rust with the Axum web framework
- Use SQLx for database operations with PostgreSQL
- Use SQLx compile-time checked query macros (query!, query_as!, etc.) throughout - no raw queries
- Database is running on localhost:5432
- Create proper database migrations using `sqlx migrate add` commands
- Implement migrations to create necessary tables (transactions, categories, budgets, etc.)
- Run migrations automatically or provide clear instructions
- Before deployment, run `cargo sqlx prepare` to generate query metadata for offline compilation
- Create RESTful API endpoints for:
  - Adding/editing/deleting transactions
  - Categorizing transactions
  - Getting spending summaries by category/time period
  - Budget management
*Frontend (HTML/CSS/JS):*
- Create a modern, clean, and slick UI using vanilla HTML, CSS, and JavaScript
- Make it responsive and mobile-friendly
- Include data visualizations (charts for spending by category, trends over time)
- Use a nice color scheme and contemporary design patterns
- Place all frontend assets in a `dist/` directory
*Deployment:*
- Deploy to Shuttle
- Configure the Shuttle.toml to include frontend assets
- Use the Shuttle MCP server to handle the deployment
- You can also use the Shuttle MCP server to search Shuttle documentation if needed
*Features to implement:*
- Transaction management (add, edit, delete income/expenses)
- Automatic and manual categorization
- Budget setting and tracking
- Spending insights with charts (pie charts, bar charts, line graphs)
- Date range filtering
- Summary statistics (total spent, by category, monthly trends)
Build this as a complete, production-ready application with proper error handling, validation, and a polished user experience.
Why I tried this:
• I wanted to know if AI can handle real Rust workflows, not just snippets
• Boilerplate in Rust apps (migrations, routing, setup) is still tedious
• I was curious where the model would break - syntax, crates, SQL, build steps, deploys
It ended up building the whole thing with surprisingly few corrections. It left me wondering: how many side-projects could we ship if this becomes normal? And what does “writing software” look like when the prompt is the starting point?
If you want all the details like what broke, what worked, and the final build it’s all in the blog above. Would love feedback from other devs trying similar things.

value: Show HN: I built a full-stack Fin Serv Rust app with Opus


value:
We kept running into the same pattern with logging costs:

  - CloudWatch / GCP Logging / Datadog tell you which log group/index is expensive
  - But not which specific log statements in your code are responsible

  So the response is always:

  - tweak retention / tiers
  - add filters and sampling

  …and only much later do you discover it was a couple of DEBUG lines in a hot path, verbose HTTP tracing, or payload dumps in loops.

  At some point we wanted a simple answer to:

  > “For the code that’s deployed right now, which log call sites are burning most of the budget?”

  ———

  ### What LogCost does

  LogCost is a small Python library + CLI that:

  - wraps the standard logging module (and optionally print)
  - tracks per‑call‑site metrics:
    {file, line, level, message_template, count, total_bytes}
  - applies provider pricing (e.g. GCP/AWS) to estimate cost
  - periodically exports aggregated stats only (no raw log payloads)
  - can send Slack notifications with the top N most expensive log lines

  It’s intended as a snapshot for the current deploy: run it under normal load, see which lines dominate cost, change them, redeploy, repeat.

  ———

  ### How it works (high level)

  - It wraps logging.Logger._log and records a key per call site using file, line, and level.
  - Message size is estimated from the formatted string length plus a configurable per‑event overhead, and accumulated per call site.
  - A background thread periodically flushes aggregates to JSON on disk.
  - The CLI reads that JSON and prints:
      - a cost summary (based on current provider pricing), and
      - a “top cost drivers” table per call site.

  By design it never stores raw log payloads, only aggregates like:

  {
    "file": "src/memory_utils.py",
    "line": 338,
    "level": "DEBUG",
    "message_template": "Processing step: %s",
    "count": 1200000,
    "bytes": 630000000,
    "estimated_cost": 315.0
  }

  That’s partly for privacy, and partly because this is meant to complement your log platform, not replace it.

  ———

  ### Example output

  A report might say:

  - Provider: GCP, Currency: USD
  - Total bytes: 900,000,000,000
  - Estimated cost: 450.00

  Top cost drivers:

  - src/memory_utils.py:338 [DEBUG] Processing step: %s → $157.50
  - src/api.py:92 [INFO] Request: %s → $73.20
  - …

  Slack notifications are just a formatted version of the same data, on a configurable interval (with an optional early “test” ping so you can verify wiring).

  ———

  ### Scope and status

  - Python‑only for now (Flask/FastAPI/Django / K8s sidecar examples)
  - MIT‑licensed, no backend service required
  - Export format is simple JSON, so it could feed a central aggregator later if needed

  Repo:
  https://github.com/ubermorgenland/LogCost

  I’d be interested in feedback from people who’ve debugged “mysterious” log bills:

  - Do you already solve this mapping (bill → specific log sites) in a cleaner way?
  - Is per‑line aggregation actually useful in your setups, or is this overkill compared to just better log group conventions?

value: Show HN: LogCost – map logging cost to specific log lines


value: weebhek

value: Show HN: Cut multi-turn AI agent cost/latency by ~80–90% with one small change

author: weebhek


value: janicerk

value: Show HN: Walrus – a Kafka alternative written in Rust

author: janicerk


value: asaws

value:
Most marketing tools are just text editors. Vect is a strategist.
We built a platform that combines real-time market research with autonomous agent execution. It solves the problem of "guessing" what works by simulating audience reactions and auditing copy against proven conversion frameworks.
The Rare Toolset:
Market Signal Analyzer: Stops you from writing about dead topics. It finds the "blue ocean" content gaps your competitors haven't touched.
Conversion Killer Detector: Identifies the exact words in your copy that are killing your sales (e.g. passive voice, high cognitive load, lack of social proof).
Viral Video Blueprint: Generates script hooks based on current short-form algorithms, not just creative writing.
It's effectively a multi-million dollar marketing team condensed into a single interface.
Check it out and let me know if the "Resonance Score" aligns with your gut feeling on your own copy.
Link: https://vect.pro/

value: Show HN: Vect AI– The "Resonance Engine" for high-growth marketing

author: asaws


value: growt

value: Show HN: Lost.js is zero-dependency framework for building local, shareable apps

author: growt


value: jaramy

value: Show HN: I built a 1.8MB native app with self-built UI, vision and AI libraries

author: jaramy


value: shutty

value: Show HN: I benchmarked read latency of AWS S3, S3Express, EBS and Instance store

author: shutty


value: damienwebdev

value:
I wanted to challenge myself to see if I could build a chat-style “UI editor” into Magento’s admin panel so that I could have fun making content again (and hopefully make the content-editing experience a little better for other people too). It turns out that this challenge became a little bigger (both in difficulty and scope) than I initially predicted. It was a fun challenge none-the-less.
I had a few goals when building the editor:
- Generate a schema definition that could be used to render frontend apps.
- Allow users to ONLY edit text content of the rendered app (I wanted to be stupidly simple to use).
- Allow jumping to different versions of the schema at different points in time in the chat history.
- Allow users to generate UI using their existing Angular components. I wanted to enable end-users to use existing assets. I felt like things like Lovable are too "open-ended" to be as useful.
Here's a demo of what I built: https://www.youtube.com/watch?v=LcudrwsT_gk
Editor Code: https://github.com/graycoreio/daffodil/tree/develop/libs/con...
I open sourced all of the code that I wrote (MIT License) and it comes in two pieces:
## Angular Editor / Renderer
A pair of Angular components (and associated types/supporting infrastructure) called the `DaffAiEditorComponent` and `DaffContentSchemaRenderer` that allow you to drop in page schema and edit/visualize it. It can take a schema and produce a full page. This can be used as the foundation for building AI-driven content schema editors for any platform.
Currently, the editor can only be imported if you build the @daffodil/content package locally (I’m working on releasing this shortly!).
You can find the editor code here: https://github.com/graycoreio/daffodil/tree/develop/libs/con...
You can find the frontend render here: https://github.com/graycoreio/daffodil/tree/develop/libs/con...
## Magento CMS Plugin
A Magento/MageOS module that embeds the editor in the CMS, calls OpenAI for prompt-based schema generation, and exposes the resulting schema via GraphQL so Daffodil storefronts (or any headless frontend) can render it.
If you have a Magento store, you can install it with:
```
composer require graycore/magento2-cms-ai-builder
```
Repo: https://github.com/graycoreio/daffodil/tree/develop/plugins/...
I think the thing I’m most proud of is the way that I came to the conclusion of patch generation. My early attempts at driving the model to target a full schema on each prompt became woefully slow within just a few conversation loops. Reducing the output tokens here was a big win for UX and latency. In addition to performance, the model would subtly change schema in various parts of the page at random which is less than stellar.
There’s still a ton to do (I need to document all of the things and I need to make examples of rendering frontend apps with the admin content), but this was a huge milestone for me.
I plan to add streaming support to the Magento plugin along with the editor. I also want to spend some time making the extension points of "adding your own components" much simpler to do, it's a bit clunky today.

value: Show HN: Open-Source AI CMS Editor for Magento/Adobe Commerce

author: damienwebdev


value:
Hey everyone!
We recently worked on a weekend project we thought might be helpful for anyone starting a startup or navigating the critical early stages.
We trained an AI agent on the full transcript content from the official YC Startup School YouTube channel—that’s over 600 minutes of content from founders and experts - so you can instantly unlock the knowledge for specific pieces of advice.
What It Does
You can ask it complex, specific questions about anything covered in the curriculum, and it will give you a summarized, instant answer based only on the Startup School material.
Example Questions: "What is Paul Graham's advice on picking co-founders?" or "Summarize the key takeaways on product-market fit metrics."
The Goal: We wanted to create a simple, reliable shortcut for accessing the knowledge in one place.
Important Notes
Not Official: This is not an official tool or service of Y Combinator or Startup School. It’s a side project built by a couple of founders (that's us!).
It's a "Fun" Project: It's still a work in progress and a fun experiment in AI knowledge retrieval. If you spot any weird answers, hallucinations, or bugs, please let us know in the comments!
We hope this will be useful. Keep building!

value: Show HN: AI Agent for YC Startup School Content


value:
Creator here. This is a satirical take on startup culture where every product promises to "transform your life."

  The loading screen shows messages like "Installing good vibes..." and "Calibrating happiness..."

  For $2.99 you get the "Premium Reality Adjustment Service" - which does exactly the same thing as the free version.

  For $4.99/month, we automatically make everything OK every Friday at 1pm.

  Built with Node.js, Stripe, available in 5 languages.

  It's the most honest product I've ever shipped - it promises nothing and delivers exactly that.

value: Show HN: I built a SaaS that does nothing (for $2.99)


value: itsfseven

value: Show HN: A comments-first newsfeed

author: itsfseven

title: Show HN: A comments-first newsfeed


value:
Hi HN,
We’re Kiet, Avi, and Satya. We built an open-source desktop app that helps you run a lot of CLI coding agents like Claude Code, Codex, etc. in parallel on your machine. The purpose is to keep you unblocked - spin up new coding tasks while others run, and quickly switch between them as they need your attention.
Superset aims to be a superset of all the best AI coding tools. We want to support and stay compatible with whatever CLI agents you already use - improving your workflow instead of replacing it.
How it works:
- One-click Git worktree creation with automatic environment setup
- Agents and terminal tabs are isolated per worktree, preventing conflicts
- Push notifications when agents are done or need your input
This lets you, for example, have Codex writing end-to-end tests in one worktree while Claude Code refactors a different module — no waiting, no lost context.
What’s next:
We think there’s a big tooling + UX gap for orchestrating multiple agents. We’re experimenting with:
- GitHub-style diff viewer for quick in-app code review
- Merge agent to automatically generate a PR from a worktree
- Create and sync worktrees in cloud VM for mobile/web access
- Automatic context passing between agents using a top-level agent (e.g. Codex plan -> Claude Code implementation -> Codex review)
We’ve been using Superset to build Superset, and it’s made our coding 2-3x faster. We’d love your feedback, feature requests, and workflows to support :)

value: Show HN: Superset – Run 10 parallel coding agents on your machine


value: syntaxers

value: Hear research differently. 5000+ NeurIPS 2025 papers transformed into songs. Search by topic, discover ideas through music, and share what inspires you.

value: Show HN: Paper2Song – Hear Every NeurIPS 2025 Paper as a Song

author: syntaxers


value: bilekas

value: Show HN: SecuriNote – Create shared ephemeral, client-side encrypted notebooks

author: bilekas


value: nicoritschel

value: I've been working on analytics tools the past couple years and have explored ways to make calculations more consistent & reliable, especially in the age of LLMs. While I've also built a more traditional metric layer or semantic layer that I'll use in my project, I couldn't help implementing this pure SQL version (well, close to it) from a paper I read a couple years back.

value: Show HN: Yardstick — Measures in SQL as a DuckDB Extension

author: nicoritschel


value: dohyeondk

value: Show HN: Sub-tools – AI-powered subtitle generation using WhisperX and Gemini

author: dohyeondk


value: endcycles

value: Show HN: FFmpeg Engineering Handbook

author: endcycles

title: Show HN: FFmpeg Engineering Handbook


value: prathameshnium

value:
Hi HN,
I built PICA (Python-based Instrument Control and Automation), an open-source software suite designed to handle complex lab measurement instruments and automate experimental workflows. It is a lab-tested, physically accurate alternative to proprietary solutions like LabVIEW.
What it does: PICA provides a professional dashboard to orchestrate high-precision hardware (Keithley SourceMeters, Lakeshore Controllers, LCR Meters) for materials science research. It automates protocols like I-V sweeps, Resistivity vs. Temperature, and Pyroelectric measurement loops.
Key Features:

    Open Source & GUI: Includes a full graphical interface for setting parameters and running experiments, making it accessible to researchers without coding experience.

    Process Isolation: Uses a multiprocessing architecture to run instrument control loops in isolated processes. This ensures that hardware timeouts or driver crashes do not freeze the main UI.

    Live Visualization: Features real-time plotting utilities to monitor measurement data as it is acquired.

    Lab-Tested Reliability: The suite is actively used for cryogenic transport measurements (80 K – 320 K) at the UGC-DAE Consortium for Scientific Research, Mumbai Centre,India.

The project is MIT licensed. Feedback on the architecture or driver implementation is welcome!

value: Show HN: PICA – open-source Python Alternative to LabVIEW

author: prathameshnium


value: swalabtech

value:
Journiv is a a beautiful, self-hosted, privacy-first journaling app with mood tracking, daily prompts, and meaningful insights. The mission is simple: your memories should always stay yours. Own them, don’t rent them.
Journiv 0.1.0-beta.8 is now live on GitHub and fully Docker-hostable. Start owning your thoughts and memories forever and keep them completely private.
The Story Behind Journiv
I got into self-hosting last year while exploring options for journaling solution, I realized there wasn’t a truly modern, self-hosted equivalent to Day One or Apple Journal. Most alternatives were either general note apps or old abandoned projects. I really wanted to keep my thoughts and memories of my young family for ourselves.
I wanted something focused on journaling with:
- “On This Day” memories
- Prompt-based journaling
- A clean, minimal, distraction-free writing experience
So… I built my own: Journiv, a beautiful (at least I am trying to make it so), self-hosted, privacy-first journaling app with mood tracking, daily prompts, and meaningful insights. Journiv began as a deeply personal project, a way for me to capture memories, reflections, and the stories behind thousands of photos and videos of my fast-growing kids. What started as a tool for my own parenting journey has grown into something that fills a real gap in the self-hosting community.
If you’re curious, you can read the full story behind Journiv here: https://journiv.com/blog/the-story-behind-journiv
Thank you

value: Show HN: Journiv, First Self-Hosted Privacy-First Journaling App

author: swalabtech


value:
Hi HN,
I built ScreenBreak after realizing that most app blockers failed in practice. “Hard blocks” were too rigid — I either locked myself out entirely or tapped Ignore Limit and kept scrolling. There was no useful middle state.
In reality, people still need to open apps like TikTok or Instagram for specific tasks: looking something up, replying to someone, checking updates, etc. The problem isn’t intentional use; it’s the unplanned, unconscious scrolling that follows. I wanted a system that interrupts the impulse without fully preventing access.
ScreenBreak uses soft blocking plus effort-based unlocks. When a block triggers, the user must complete a small physical challenge (rapid tapping, shaking the phone, drawing a circle). If they succeed, they get a short access window. If not, the urge typically breaks.
Over the past year, I’ve implemented several flexible block rules:
- Schedule Block: active only during set hours
- App Launch Limit: blocks after exceeding a daily open count
- Usage Budget Limit: blocks once a daily or hourly time quota is used up
The goal is to add friction exactly at the moment of impulse, instead of relying on absolute blocking or self-discipline alone.
I’d appreciate feedback on the concept, challenge mechanics, and whether this approach fits how you manage attention or screen use.

value: Show HN: ScreenBreak – Enter addictive apps only if you complete an effort task


value: terraplanetary

value: Show HN: Rust-based ultra-low latency streaming framework – Wingfoil

author: terraplanetary


value: tlhunter

value:
I've worked at several companies during the past two decades and I kept encountering the same issues with internal technical proposals:
- Authors would change a spec after I started writing code
- It's hard to find what proposals would benefit from my review
- It's hard to find the right person to review my proposals
- It's not always obvious if a proposal has reached consensus (e.g. buried comments)
- I'm not notified if a proposal I approved is now ready to be worked on
And that's just scratching the surface. The most popular solutions (like Notion or Google Drive + Docs) mostly lack semantics. For example it's easy as a human to see a table in a document with rows representing reviewers and a checkbox representing review acceptance but it's hard to formally extract meaning and prevent a document from "being published" when criteria isn't met.
RFC Hub aims to solve these issues by building an easy to use interface around all the metadata associated with technical proposals instead of containing it textually within the document itself.
The project is still under heavy development as I work on it most nights and weekends. The next big feature I'm planning is proposal templates and the ability to refer to documents as something other than RFCs (Request for Comments). E.g. a company might have a UIRFC for GUI work (User Interface RFCs), a DBADR (Database Architecture Decision Record), etc. And while there's a built-in notification system I'm still working on a Slack integration. Auth works by sending tokens via email but of course RFC Hub needs Google auth.
Please let me know what you think!

value: Show HN: RFC Hub

author: tlhunter

title: Show HN: RFC Hub


value: keepamovin

value: Show HN: Visual Proof of Pythagoras' Theorem

author: keepamovin


value: gauravguitara

value:
Demo: https://youtu.be/1ZPB_n6v6EI
OpenBotAuth: https://github.com/OpenBotAuth/openbotauth
Voice agents are getting PCI compliance, however checkout is done manually today. Either by sharing a payment link to the client or OTP. For payments over voice to be compliant with SCA, a signed cart or signed session token by the agent paying on user's behalf can be provided in runtime.
In the demo, the user has two voice agents:
– Pete, a shopping sub-agent that helps pick products and build the cart
– Penny, a checkout sub-agent that confirms the total and authorizes payment
>Flow overview:
1- Pete adds items to the cart on a merchant-style fashion site.
2- At checkout, Pete hands off to Penny, the user’s payment agent.
3- Penny confirms the total and asks for explicit consent.
4- The checkout request is signed with HTTP Message Signatures (RFC 9421) using Pete’s OpenBotAuth key.
5- The merchant verifies the Signature-Agent header by calling the OpenBotAuth registry, which returns the correct public key (via a Web Bot Auth compatible key directory).
6- Once the HTTP signature and TAP objects are verified, a Visa TAP-style mock issuer authorizes the payment and the UI shows the full sequence diagram and console events.
>Notes:
– The Visa lane in this demo uses a mock issuer implemented from Visa’s public TAP (Trusted Agent Protocol) reference. This is not an official Visa integration.
– Pete and Penny are modelled as user-owned agents, not merchant bots; they’re visually embedded in the page here just to make the flow easy to see on a single screen.
- Sub-Agents are registered in OpenBotAuth with a hosted Signature Agent Card/JWKS.
If you're integrating a voice agent on your website, we'd love to get your feedback.

value: Show HN: VoicePayOS: Authorize voice agents to pay on your behalf

author: gauravguitara


value: harrygc

value: A comprehensive package for pulling nearly all details of Linux networking into reliable and broadly usable form. From configuration to statistics, NetSnap uses the fastest available api: RTNetlink and Generic Netlink. NetSnap can fuction in either standalone fashion generating JSON output, or provide Python 3.8+ objects. NetSnap provides deep visibility into network interfaces, routing tables, neighbor tables, multicast databases, and routing rules through direct kernel communication via CFFI. More maintainable than alternatives as NetSnap avoids any hard-coded duplication of numeric constants. This improves NetSnap's portability and maintainability across distros and kernel releases since the kernel running on each system is the 'single source of truth' for all symbolic definitions.<p>In use cases where network configuration changes happen every second or less, where snapshots are not enough as each change must be tracked in real time, or one-time-per-new-kernel CFFI recompile time is too expensive, consider alternatives such as pyroute2.

value: Show HN: NetSnap – Comprehnsive JSON/Python net state snapshots

author: harrygc


value: abewheeler

value:
I tried building a ChatGPT App using the new OpenAI UI components and example code, but I found myself writing more platform & testing boilerplate than application code.
I built sunpeak so we can skip the boilerplate and get straight to building our ChatGPT (and future Gemini, Claude, etc.) Apps!
Would be extremely grateful for a star and some feedback!

value: Show HN: Sunpeak – open-source MCP App SDK

author: abewheeler


value: schoblaska

value:
Hey HN! Over the weekend (leaning heavily on Opus 4.5) I wrote Jargon - an AI-managed zettelkasten that reads articles, papers, and YouTube videos, extracts the key ideas, and automatically links related concepts together.
Demo video: https://youtu.be/W7ejMqZ6EUQ
Repo: https://github.com/schoblaska/jargon
You can paste an article, PDF link, or YouTube video to parse, or ask questions directly and it'll find its own content. Sources get summarized, broken into insight cards, and embedded for semantic search. Similar ideas automatically cluster together. Each insight can spawn research threads - questions that trigger web searches to pull in related content, which flows through the same pipeline.
You can explore the graph of linked ideas directly, or ask questions and it'll RAG over your whole library plus fresh web results.
Jargon uses Rails + Hotwire with Falcon for async processing, pgvector for embeddings, Exa for neural web search, crawl4ai as a fallback scraper, and pdftotext for academic papers.

value: Show HN: An AI zettelkasten that extracts ideas from articles, videos, and PDFs

author: schoblaska


value: imaka

value: Show HN: Open-sourced version of Wisper Flow

author: imaka


value: Show HN: LogiCart – Intent-based shopping agent built with pgvector


value: justinsainton

value: Show HN: The Haul – Spotify Wrapped for Your Amazon Orders

author: justinsainton


value: teugent

value:
We’ve been working on an open runtime architecture that stabilizes long-horizon reasoning in large language models.
Sigma Runtime defines the execution model for attractor-based cognition - integrating symbolic density, drift regulation, and recursive coherence into a unified cognitive runtime layer.
It’s like a Linux-style runtime for cognitive processes in LLMs: models act as hardware, and frameworks like LangChain become drivers on top of it.
→ Documentation: https://wiki.sigmastratum.org
→ GitHub: https://github.com/sigmastratum/documentation
→ DOI: https://doi.org/10.5281/zenodo.17703667
Would love technical feedback and collaboration from those working on LLM runtimes, recursive reasoning, or cognitive architectures.

value: Show HN: Sigma Runtime – A Cognitive Runtime Standard for LLMs

author: teugent


value: ferryistaken

value: Show HN: Writing Rust modules for the xv6 kernel

author: ferryistaken


value: sistillisteph

value:
My cofounder and I built a quick site comparing LLMs. It was basically “what model is good at what.” It was fun and useful, and a fun side project. But feedback pushed us into A/B testing models in production.
So we built Fallom (homage to Asimov), a platform where you can compare how multiple models perform on your own evals or production data. You can easily see cost and performance differences and know if it’s worth switching models.
Would love feedback from anyone who’s built internal model testing pipelines. We learned a lot the hard way and are still learning.

value: Show HN: We Built a Small LLM Comparison Page and Accidentally a Platform

author: sistillisteph


value: rocksalad

value:
Hi HN,
I've been using LLMs to help draft replies and content, but I hit a wall: the "default" voice of standard models is painfully obvious. It’s always too cheerful, uses emojis incorrectly, and loves words like "delve" and "testament."
I realized I was spending more time editing the AI's output to sound like me than it would take to just write the thing myself.
So I built PostOwl to solve the "Style Alignment" problem.
How it works: Instead of a generic wrapper, it uses your previous posting history to build a style profile. When you generate a reply, it dynamically injects your specific vocabulary, sentence length patterns, and tonal constraints into the context window (using a mix of RAG and few-shot prompting) to force the model to mimic your syntax.
The Challenge: It’s effectively a "Doppelgänger-as-a-Service." The hardest part has been balancing the speed of generation with the accuracy of the style mimicry.
I’d love feedback on the output quality. Does it actually sound human, or just like a "pirate mode" version of ChatGPT?
(It has a free tier, no credit card required. I'm just looking for load testing and feedback on the prompts right now.)

value: Show HN: I built a tool to fix the problem in LLM replies

author: rocksalad


value: sylwekkominek

value:
I built an open source real-time music visualizer that lets you create animated color themes simply by describing them with natural language prompts. ChatGPT helps convert your descriptions into live visual styles.
The visualization is fully customizable and powered by DSP and GPU shaders.<p>The app creates configuration files in the folder:
C:\Users<YourUser>\Documents\NotYetAnotherSpectrumAnalyzer\config
You can open those files, copy their contents into ChatGPT, and generate a completely new color theme based on your prompt.

value: Show HN: Music Visualizer with Animated Colorful Themes Configured via ChatGPT

author: sylwekkominek


value: blampack

value: Hi everyone, I was tired of paying monthly for invoicing software, so I built this. I'd welcome any feedback. Thanks in advance.

value: Show HN: PayPerBill, pay per invoice sent without monthly subscriptions

author: blampack


value: nergal

value: Decided to create my own Garmin Forerunner 255 music watch face that fits my needs. Just want to share it, maybe others want to create their own and have something to base it on.<p>It was quite fun project to both learn a bit of "MonkeyC" and to develop for the watch. Always more fun to develop stuff that will be for daily use :)

value: Show HN: Garmin Watch Face

author: nergal

title: Show HN: Garmin Watch Face


value: soyzamudio

value: Show HN: ReferralLoop – Waitlist platform with viral referral mechanics

author: soyzamudio


value: LiamPrevelige

value:
Hey HN, we’re Will and Liam, founders of CodeViz (YC S24). We’re building a VS Code extension that reads your code and generates editable architecture diagrams (C4, UML). It’s mostly used by teams to build shared context, agree on technical decisions, and visualize PRs.
Here’s a recorded demo: https://youtu.be/Jh3wkrCj_WQ
You can try the VS Code extension here: https://marketplace.visualstudio.com/items?itemName=CodeViz....
It’s free for 10 generations/month (no signup). Then, we have a $19/month plan for unlimited diagram generation and $50/month plan for live collaboration.
We launched a v1 last year to help engineers read code faster (https://news.ycombinator.com/item?id=41393458), but no one actually used CodeViz for that. Users were taking screenshots of our diagrams for presentations and architecture reviews. We rebuilt CodeViz to shift from a passive viewer to a collaborative editor for modeling specific flows, using C4 and UML standards.
This required a major change in our technical approach. In our original version, we relied on static analysis, building stack graphs with tree-sitter for ~15 languages (using language servers as teachers). While technically precise, these graphs were way too noisy and didn’t map to human abstractions.
We now use an adaptation of gemini-cli to read the codebase, generate C4 + Activity PlantUML diagrams, and link nodes directly to source code. These are parsed into a diagram editor that we built with ReactFlow. You can click to expand nodes into lower levels of abstraction, ask an AI assistant to visualize a specific flow, or import PRs from GitHub.
CodeViz is in active development, all honest feedback is much appreciated! Our roadmap is largely focused on tools for working in teams, so we’d also love to hear about your problems with architecture reviews and onboarding.

value: Show HN: CodeViz – A diagram editor that understands your code (YC S24)

author: LiamPrevelige


value: I built an MCP server that streams real-time NSE/BSE market data (equities + F&O) to LLMs. Enable your LLM to interpret real-time market data and generate trading or analysis insights—similar to a stock analyst or strategy engine.

value: Show HN: MCP Server for Real-Time NSE/BSE Data


value: baetylus

value:
Hey HN,
I built Debrief because I was tired of spending the first hour of my day catching up e.g. piecing together what happened across Slack threads, email chains, and docs.
You can track specific work topics across all your work tools, like Slack, Gmail, etc... and receive 1-minute briefs per topic every day.
For example: track "Q4 product launch" and get one daily update pulling from everywhere that topic is being discussed.
Some other info:
- This is v0, so I would love feedback!
- Adding new stuff soon like cadence control & more app integrations... any suggestions welcome
- All data is encrypted; working toward SOC II
- Setup takes <2 minutes
Happy to answer questions! + feel free to reach out to me directly at will (at) trydebrief (dot) com.

value: Show HN: Debrief, an AI tracker for every work thread

author: baetylus


value: lalithaar

value:
I usually look up palettes and the UI comes out nice except some color pairs don't pass wcag color contrast and well - just isn't readable
Ended up writing a tiny library that automatically nudges your text color just enough to pass AA or AAA, while keeping it visually similar to the original
along with a color contrast linter so we can use it in CI
Thought you guys might find it useful too, it's foss :>

value: Show HN: Cm-colors –I got tired of manually fixing wcag contrast,so I made this

author: lalithaar


value: hommus

value:
I'm traveling for the year and wanted to find airbnbs with pianos so I could keep learning. Unfortunately, airbnb doesn't let you filter by uncommon amenities (pianos, saunas, etc). So I built a tool to help do just that. It's simple and free.
How it works: Start your search on airbnb (location, dates, guests, etc), copy that URL and paste it into revealbnb.com, select your amenities, and you'll get an updated airbnb URL with those filters applied.
Have a gander and let me know what you think.

value: Show HN: Search Airbnb listings with unique amenities (piano, sauna, etc.)

author: hommus


value: GeldiBey

value: I spent a few minutes pair-programming with Claude Opus 4.5 to build a terminal-based life simulator game in Python.

value: Show HN: Life Simulator – ASCII terminal game I pair-programmed with Opus 4.5

author: GeldiBey