value: noeconomist

value: SHOW HN: Solve GCSE/Igcse Past Papers with AI

author: noeconomist


value: rkmahale

value: Show HN: I built a visual DP explainer for people who hate DP(Knapsack example)"

author: rkmahale


value: radiusvector

value:
Hey HN — I built this because opening the news started to feel like drinking from a firehose. The signal-to-noise ratio keeps dropping, and most feeds optimize for outrage, not insight.
Clarion is a small AI editor that reads thousands of articles weekly, filters hard (~3% make it through), and surfaces only progress-focused stories. The goal: a clear weekly snapshot of what’s actually moving forward, without the doomscroll tax.
It runs on a simple stack: Vite + TS frontend, Supabase backend, automated ingestion, and a strict scoring pipeline. Built for myself at first, but it’s been resonating with founders, execs, and other busy people.
Stack
 • Ingestion: Lambda workers + Supabase Edge
 • Scoring: Custom AI pipeline (Gemini 2.5 Flash-Lite, Gemini 2.5 Pro, Claude)
 • Frontend: Vite, React, TypeScript
 • Infra: Supabase Postgres on AWS
Would love feedback on scoring, UX, or anything that feels off.

value: Show HN: Clarion – AI system that rejects 97% of news into a high-signal digest

author: radiusvector


value: Hyriol

value: It works as a PWA, supports offline usage, and has a picture-in-picture mode (only on compatible browsers like Chrome-based ones). Feedback is welcome.

value: Show HN: I made a simple online interval timer for HIIT

author: Hyriol


value: itaydressler

value:
I’ve been experimenting with messaging-native AI agents and built an early prototype of an AI nutrition coach that works through iMessage (WhatsApp support coming soon). You send it a meal photo or a voice note, and it estimates calories/macros and logs everything automatically. It also builds a daily plan and sends weekly summaries based on your actual behavior.
The goal is to explore whether messaging can reduce the friction and drop-off that happens in traditional food-tracking apps. Early testers seem to stick with this format much more consistently.
Some technical details for context:
Vision & reasoning powered by a combination of Gemini and Perplexity
Agent runtime using the Vercel AI SDK
Gateway layer with Vercel’s GW
Image → nutrition estimation via serverless functions
iMessage integration through a local relay setup
WhatsApp Cloud API integration in progress
Still very early, and I’m trying to understand if a chat-first UX can make nutrition tracking feel effortless instead of a chore. Happy to hear feedback on the approach, concerns I should think about, or any similar systems worth studying.

value: Show HN: An AI nutrition coach you can text on iMessage/WhatsApp

author: itaydressler


value: Inspired by rustlings for the concept and the name. A little project to learn or refine the basics of docker / compose commands. I am planning to add more advanced themes later on. Hoping to have discussions on how it could become more useful for others.

value: Show HN: Learn Docker in your terminal

title: Show HN: Learn Docker in your terminal


value: chribog

value:
Hi HN,
I made a small game in Swift to visualize Nurikabe puzzles in 3D, using SceneKit and Metal shaders with some SwiftUI on top for buttons and hints. It's currently available for free in App Store.
I've tried generating islands like this a few times before, where the whole board is just one big mesh, but I struggled with the shorelines (especially in corners) and also to make the islands somewhat unique and interesting. This time I got inspired by Oskar Stålbergs "dual grid" approach (https://x.com/OskSta/status/1448248658865049605) which made it a lot easier I think. Happy to provide more details if anyone is interested.
Anyway, I would love to get some feedback on the game: Is it understandable? Too easy or hard? What should I focus on to improve it? Thanks!

value: Show HN: Blue Divide – Nurikabe puzzles with procgen islands for Mac and iPad

author: chribog


value: DataSpeeder

value: Show HN: DataSpeeder 2 Beta – Instant End-User Web UI for MySQL and Oracle

author: DataSpeeder


value: meckatz

value: Show HN: Architecture of my multi-region SaaS built on self-hosted LLMs

author: meckatz


value: francescopace

value:
Hi everyone, I'm the author of ESPectre.
This is an open-source (GPLv3) project that uses Wi-Fi signal analysis to detect motion using CSI data, and it has already garnered almost 2,000 stars in two weeks.
Key technical details:
- The system does NOT use Machine Learning, it relies purely on Math.
— Runs in real-time on a super affordable chip like the ESP32.
- It integrates seamlessly with Home Assistant via MQTT.

value: Show HN: ESPectre – Motion detection based on Wi-Fi spectre analysis

author: francescopace


value: rydensun

value:
I’ve been working on a new MCP tool and wanted to share it here in case it’s useful for anyone building agents or multimodal AI products.
I built an AI Music MCP that lets agents generate fully produced songs directly from text instructions.
The goal was simple: add “music” as a missing modality to the MCP ecosystem.
The MCP currently supports three main generation modes:
Idea → Track: describe a mood or scene and get a finished 4+ minute song
Lyrics → Song: provide your own lyrics + style, and the tool returns a fully arranged track
Instrumental Mode: generate jazz, orchestral, lofi, cinematic, etc. without vocals
It also works across genres (classical, electronic, folk, rock, etc.) and supports prompts in many languages.
Each generation call returns full metadata, including:
MP3 download URL
title
lyrics (if applicable)
style/genre tags
cover art
duration
created timestamp
The idea is to let agents compose complete, usable music without needing any training, audio pipelines, or GPU setup. Just MCP calls.
If you're experimenting with creative agents or building AI products that could benefit from native music generation, here’s the project:
https://www.musicmcp.ai/
Happy to hear feedback, ideas, or edge cases you'd like supported.

value: Show HN: AI Agents can generate music first Music MCP dropped

author: rydensun


value: bahmann

value:
Frustrated by the complexity and resource drain of multi service monitoring stacks, I built Simon. I wanted a single, lightweight dashboard to replace the heavy stack and the constant need for an SSH client for routine tasks.
The result is a resource efficient dashboard in a single Rust binary, just a couple of megabytes in size. Its support for various architectures on Linux also makes it ideal for embedded systems and lightweight SBCs.
It integrates:
Comprehensive Monitoring: Realtime and historical metrics for the host system and Docker containers (CPU, memory, disk usage, and network activity).
Integrated File & Log Management: A web UI for file operations and for viewing container logs, right where you need them.
Flexible Alerting: A system to set rules on any metric, with templates for sending notifications to Telegram, ntfy, and webhooks.
My goal was to create a cohesive, lightweight tool for self hosters and resource constrained environments.
I'd love to get your feedback.
https://github.com/alibahmanyar/simon

value: Show HN: I ditched Grafana for my home server and built this instead

author: bahmann


value: autonomydriver

value: Show HN: 32V TENS device from built from scratch under $100

author: autonomydriver


value: therov

value: Show HN: I built a modern anime tracker

author: therov

title: Show HN: I built a modern anime tracker


value: prathameshnium

value: Show HN: I demoed my 2018 preprint on transforming Tupper's formula

author: prathameshnium


value: danlcaza

value:
Key additions:
RVV SIMD support for RISC-V devices.
Elliptic IIR filter design and zero-phase IIR filtering via filtfilt.
Audio reading/writing completely reworked and now supports WAV, W64, RF64/BW64, AIFF, FLAC, CAF, ALAC, MP3, and raw formats.
New high-level Audio module for multichannel processing.
There are also performance improvements since KFR6 for DFT (up to 40% on ARM) and matrix transpose (up to 30%).

value: Show HN: KFR 7 – major update for C++ DSP library

author: danlcaza


value: control-h

value: Capibara is an event counting API that lets you quickly measure how often something happens. Common use cases include monitoring, product analytics, and more.<p>Capibara is built with Go, Gin, Postgres, and restraint.

value: Show HN: Capibara, an API to measure how often things happen

author: control-h


value: wkoszek

value:
I built bsub because I was tired of wiring up Docker images, Python environments, GPUs, sandboxing, and resource limits every time I needed to run heavy command-line tools from web apps. I wanted: send files -> run job in the cloud -> get output -> done.
https://www.bsub.io
bsub lets you execute tools like Whisper, Typst, Pandoc, Docling, and FFmpeg as remote batch jobs with no environment setup. You can try them locally via the CLI or integrate via a simple REST API.
Example (PDF extraction):

  bsubio submit -w pdf/extract *.pdf

Works like running the tool locally, but the compute and isolation happen in the cloud.
Technical details: - Each job runs in an isolated container with defined CPU/GPU/RAM limits. - Files are stored ephemerally for the duration of the job and deleted after completion. - REST API returns job status, logs, and results. - Cold start for light processors (Typst, Pandoc) is low; Whisper/FFmpeg take longer due to model load/encoding time. - Backend scales horizontally; more workers can be added during load spikes.
Current processors:

  SST/Whisper -- speech-to-text

  Typography -- Typst, Pandoc

  PDF extraction -- Docling

  Video transcoding -- FFmpeg

More coming; suggestions welcome for tools that are painful to set up locally.
Looking for testers! CLI is open source: https://github.com/bsubio/cli. Installers available for Linux/macOS; Windows testing is in progress. Free during early testing; pricing TBD.
If you’re on Windows, feedback is especially helpful: contact@bsub.io
If you try it, I’d appreciate feedback on API design, latency, missing processors, or anything rough around the edges.

value: Show HN: Bsub.io – zero-setup batch execution for command-line tools

author: wkoszek


value: Ever since I tested software on macOS, I deeply missed my beloved strace that I use when programs are missbehaving. macOS has dtruss but it's getting locked down and more unusable with every machine. My approach uses the signed lldb binary on the system and re-implements the output you are know from the wonderful strace tool. I just created the tool yesterday evening, so it may have a few bugs, but I already got quiet a few integration tests and I am happy so far with it.

value: Show HN: I build a strace clone for macOS


value:
ToolHop is your all-in-one browser toolbox with 200+ fast-loading calculators, converters, generators, color labs, and dev helpers. Use global search or curated categories to jump straight into the right utility, run it client-side for instant feedback, and deep-link results to your team. Whether you’re formatting copy, validating data, checking DNS, or exploring palettes, ToolHop keeps your core workflows a single tab away, and it’s entirely free, no account required.
---
I built ToolHop because I was sick of the usual “free tool” bait-and-switch. Every time I needed to convert an image, compress a file, check some text, or run a quick calculation, I’d end up hitting some arbitrary limit like “10 uses per week” or a forced signup wall. It’s ridiculous how something as basic as converting a JPG to a PNG can turn into a subscription pitch.
So ToolHop started as a personal frustration project: I wanted a single place with a ton of genuinely useful tools that didn’t nag, lock you out, or throttle you. Over time that grew into 200+ handcrafted tools, all fast, simple, and actually free. No trickery, no timers, no limits.
As I built it, the process became about consistency and quality. I wanted the tools to feel seamless, not slapped together. That meant focusing on speed, clean UI, accurate results, and making sure each tool works instantly without friction.
The goal was always the same: a site that respects people’s time. Something you can rely on whenever you just need a tool to work. If ToolHop saves someone even a few minutes of hassle, then the project did its job.

value: Show HN: ToolHop – Fast, simple utilities for every workflow


value:
I wrote 200k+ lines of code this year using Cursor, and I realized that debugging AI-generated code is harder because you often don’t know what’s going on.
That’s why I built Samurai Agent: it visualizes the code execution flow so you can actually understand what the AI wrote easily, and it provides root-cause analysis instead of superficial fixes.
If you have the same problems, please join the beta. We’re giving out free credits, and feedback is appreciated. We’re focused on JavaScript/TypeScript for now.
https://samurai-agent.tech/

value: Show HN: A visual debugger for AI-generated code


value: tlombardozzi

value: Show HN: BatchPro, Your YC AI Analyst

author: tlombardozzi

title: Show HN: BatchPro, Your YC AI Analyst


value: aradzhabov

value:
LocalLiveAvatar - no high-end GPU or cloud required. Response time is instantaneous—whether the avatar speaks for 2 seconds or 20 minutes. An avatar can be generated from almost any video or photo. Once created, it can voice any text or audio with perfect lip synchronization in any language.
And who knows?:
-Perhaps a product like this could even contribute to the development of a secret OpenAI project alongside designer Jony Ive—since now the most resource-intensive part of avatar creation can run directly on the user’s device.
-Maybe robot manufacturers would take interest, too—this could make their robots more engaging, expressive, and emotionally appealing in human interactions. We could even imagine avatar marketplaces, custom avatars for brands, and much more.
I developed this technology to help people with disabilities—especially those who have lost their voice or their original appearance—by creating free, personalized digital clones (voice + avatar). Using a Telegram bot, it gives them a way to communicate and reconnect.

value: Show HN: Instant Live Avatars with Lip-Sync on Everyday Hardware

author: aradzhabov


value: AgentSkills is a platform that enables you to explore advanced Agent Skills that can execute code, process documents, and perform complex tasks.

value: Show HN: AgentSkills – Empower Agents with professional knowledge


value: belai

value: Show HN: MCPShark – Wireshark for Model Context Protocol Traffic

author: belai


value: janicerk

value: it won't let me put url for some reason, here it is: https://github.com/octopii-rs/octopii

value: Show HN: Octopii, a framework for building distributed applications in Rust

author: janicerk


value: mtolbert

value:
Hi HN,
My co-founder Sandy and I built Pi9eon, an iMessage app that lets you send real physical postcards from any photo on your phone — with no account, no signup, and no need to know the recipient’s address.
Why:
We were penpals before we were co-founders. We loved sending each other postcards while traveling, but they often got lost or delayed. We wanted a way to keep the tangible, meaningful part of postcards without the friction of stamps, postboxes, or international mail.
How it works:
Pick a photo in iMessage
Write your message
Send
Recipient gets a link to privately enter their address (“claim their Pi9eon”)
We use a vendor to print + ship via USPS (delivery in 7–10 days within the U.S., even from abroad)
Tech:
Native iMessage extension.
Addresses handled via a tokenized claim link.
Minimal data stored; no accounts or social graph.
We’d love feedback from this community — on UX, privacy, or edge cases we should account for.
App link: https://apps.apple.com/us/app/pi9eon/id6753701299
Thanks,
Maddie & Sandy

value: Show HN: Pi9eon – Send Real Postcards from iMessage

author: mtolbert


value: ibrhimaydiin

value:
Hi HN!
I built a small mobile app that generates weekly content ideas for creators and small businesses.
It’s a very early version, but I’d love feedback from the community.
Happy to answer any questions.

value: Show HN: FeyzAI – Simple mobile app that generates weekly content ideas

author: ibrhimaydiin


value: Show HN: Combi-message: simple key-value data store over HTTP+Socket.IO


value: vasanthv

value:
Pinggy is a location-based social app built around short, ephemeral text posts from people in your city. No likes, no followers, no algorithmic feeds - just a chronological stream of local conversations that disappear in 7 days.
I built it because most social apps today optimize for reach, virality, and influencer dynamics, which often pushes out authentic, everyday voices. I wanted something smaller, more human — a digital town square where people in the same city can talk without the pressure of metrics or permanent history.
Pinggy tries to bring back spontaneous, local conversations by focusing on simplicity, privacy, and a slower, more grounded social experience.
https://pinggy.com

value: Show HN: Pinggy – A digital town square for your city

author: vasanthv


value: kubeden

value:
Hey all :)
I noticed the development on the Notion web clipper  chrome extension is kinda slow, so I built a better one.
It works on any web page, any youtube video, and any PDF.
Features:
- highlight + note + collections
- auto-scrollback to your highlights (page automatically scrolls to the text you highlighted and it works on LLMs web interfaces)
- automatic sync to Notion (+page+dbs creation)
- reminders: the app pings you with an email to review and delete your already-checked highlights (you set the ping period)
Let me know what you think.
Denis

value: Show HN: I built a better Notion Web Clipper

author: kubeden


value: KritiKay

value: Show HN: Natural language query interface for Postgres

author: KritiKay


value:
I’ve been experimenting with a simple framework to make it easier to design and prototype using AI-assisted code editors like Cursor or Claude Code.
More and more teams are designing directly in code now, but most AI-assisted code editors don’t have the context or guardrails needed for scalable, reusable components.
This framework tries to solve for that by giving both technical and non-technical contributors a consistent way to draft components and prototypes, share with users, and follow a design system, all in the codebase.
It’s a raw, unfinished idea, but I’m using it in a couple of projects, and I'm interested in whether others would benefit and agree with the premise.
All feedback is welcome. Thanks!

value: Show HN: A framework for designing and prototyping with AI-assisted code editors


value: seanmtracey

value:
Hey everyone, I'm Sean, and I've built UpBeat.
Why did I build this?
Well, the world is more complex than ever, and every stream, device and social feed screams for our attention whilst telling us that everything is awful.
While it's important to know what's going on in the world - do we really need to be bombarded with negativity 24/7?
Absolutely not! It's bad for our mental health, it's bad for our attention spans, and it's bad for society as a whole.
So that's why I built UpBeat - My friends, loved ones, and I needed a break from the doom cycle. So, here it is :)
Some technical details, it's a macOS app built with  Go using the Wails.io framework and it (currently) uses the Distilbert model which runs on the Apple Neural engine, so inference takes ~40ms.

value: Show HN: UpBeat – an AI-Enhanced RSS/Atom Reader that only shows you good news

author: seanmtracey


value: spetz

value: Show HN: Building WebSocket in Apache Iggy with Io_uring and Completion Based IO

author: spetz


value: atulvi

value:
Wikidive is an AI-driven exploration tool designed to help you discover interesting topics on Wikipedia.
Simply enter a topic you're interested in, and Wikidive will explore Wikipedia to find TWO related topics that an AI model thinks are interesting. You can then choose to dive deeper into one of these topics. Each "dive" presents you with related topics that you can explore further, creating an engaging journey of discovery.
How it works:
It asks an llm this prompt: "I was going in this rabbit hole of wikipedia articles: #{chain} \n I have now found these topics:\n\n#{related_topics}\n\n Select the 2 most mind blowing topics from the list and that I'd enjoy given my rabbit hole. Ensure two topics are not the same."
and pics two articles that it returns. This is slightly better than random.(related article names are obtained from wikipedia API).

value: Show HN: A Tool to Deep dive into Wikipedia

author: atulvi


value:
Kalendis is an API-first scheduling backend. You keep your UI; we handle the gnarly parts (recurrence, time zones, DST, conflict-safe bookings).
What it does: • MCP tool: generates typed clients and API route handlers (Next.js/Express/Fastify/Nest) so you can scaffold calls straight from your IDE/agent tooling. • Availability engine: recurring rules + one-off exceptions/blackouts, returned in a clean, queryable shape. • Bookings: conflict-safe endpoints for creating/updating/canceling slots.
Why we built it: We kept rebuilding the same "hard parts" of scheduling: time zones/DST edge cases, recurring availability, conflict-aware booking, etc.
We wanted a boring, reliable backend so we could ship product features without adopting a hosted scheduling UI.
How it's helped: We stopped re-implementing DST/recurrence math and shipped booking flows faster. One small team (just 2 developers) built a robust booking platform for their business using Kalendis—they kept full control of their UX without spending lots of cycles on scheduling infrastructure. The MCP generator cut the glue code: drop in a typed client or route, call the API, move on.
Some tech details: • REST API with ISO-8601 timestamps and IANA time zones • Recurring availability + one-off exceptions (designed to compose cleanly) • Focused scope: users, availability, exceptions, bookings (not a monolithic suite)
The MCP server exposes tools like generate-frontend-client, generate-backend-client, generate-api-routes, and list-endpoints. Add to your MCP settings:

  {
   "mcpServers": {
    "kalendis": {
     "command": "npx",
     "args": ["-y", "@kalendis/mcp"]
    }
   }
  }

How to try it: Create a free account → get an API key. (https://kalendis.dev). Then hit an endpoint:

  curl -H "x-api-key: $KALENDIS_API_KEY" \
 "https://api.kalendis.dev/v1/availability/getAvailability?userId=<user-id>&start=2025-10-07T00:00:00Z&end=2025-10-14T00:00:00Z&includeExceptions=true"

Happy to answer questions and post example snippets in the thread. Thanks for taking a look!

value: Show HN: Kalendis – Scheduling API (keep your UI, we handle timezones/DST)


value: imfing

value:
Hi HN! I built jsrun, a Python library that embeds the V8 (https://v8.dev) engine to run JavaScript inside Python
https://github.com/imfing/jsrun
Python does not have great options for sandboxed or isolated code execution, and I was hoping for something similar to the Cloudflare Workers model that provides lightweight isolates
jsrun provides:
- a fully isolated JavaScript runtime backed by V8
- each runtime spins up a V8 isolate in <5ms, runs on its own thread with GIL released, keeping JavaScript execution isolated Python
- ability to expose Python functions and data directly to the JS environment
built with Rust/PyO3, shipped as wheels with no extra dependencies
It would be good for cases like code playground, user scripting, AI generated code execution, or anywhere that needs a JS runtime inside a Python application
Would love any feedback, ideas!

value: Show HN: jsrun – Isolated JavaScript Runtime in Python via Embedded V8

author: imfing


value: Show HN: MCP Traffic Analysis Tool

title: Show HN: MCP Traffic Analysis Tool


value: proletarian

value: Show HN: UltraLocked – iOS file vault using Secure Enclave and PFS

author: proletarian


value: charlesvien

value: Show HN: I turned GitHub Actions into a Minecraft hosting service

author: charlesvien


value: ruwan

value: Show HN: LLM Based PII Detection

author: ruwan

title: Show HN: LLM Based PII Detection


value: nizarmah

value:
I'm trying to figure out how to make the best of my life.
I am lucky enough to have a job that allows me to focus on life, but I suck at living and I am trying to learn.
I used to take life for granted and lately losing people I care about and riding a motorcycle are really putting into perspective how easy it is to die.
So I'm trying to go on this memento mori quest, to make the best out of every week I have (considering we only have 4000 rougly).
This is my first week, and it has already started with:
- 4 kind moments
- 1 lucky moment
- 1 dressup moment
- 6 items gifted
- 1 drinks shared
- 3 games shared
I missed the sunset, but I'm definitely catching it tomorrow.
I don't know where this is going honestly, I'm going to try to tweak it based on how I feel. But I hope someone else finds a use for it. :)

value: Show HN: Pixel Based Life Journal

author: nizarmah

title: Show HN: Pixel Based Life Journal


value: hunterbown

value: Show HN: Hegelion-Dialectic Harness for LLMs (Thesis –> Antithesis –> Synthesis)

author: hunterbown


value: gxara

value:
Hey HN
This project took almost two years and is probably one the best alternatives for tools like Miro and MindMeister
Let me know what you think

value: Show HN: I have created an alternative for Miro

author: gxara


value:
Show HN: Ephemeral Auth – Authentication without tokens using vanishing proofs
I built a React authentication library that eliminates tokens entirely. Instead of hackable JWT tokens that last for hours, it uses ephemeral cryptographic proofs that vanish after each request.
*The Problem:* Token theft gives attackers hours of access
*The Solution:* Single-use sessions that self-destruct after one action
\it is on npm on these link https://www.npmjs.com/package/ephemeral-auth-react
*npm:* poof-auth-react
*How it works:*
1. Request ephemeral challenge (one-time math problem)
2. Solve challenge → get ephemeral session
3. Session vanishes after use - hackers get nothing!
*Features:*
- No tokens to steal or manage
- Quantum-resistant cryptography
- Simple React API
- TypeScript support
Perfect timing given recent token breaches and supply chain attacks. Would love feedback from the HN community!
Demo: https://www.npmjs.com/package/ephemeral-auth-react

value: Show HN: I built ephemeral authentication – no tokens, just vanishing proofs


value: mireklzicar

value: Show HN: SynthonGPT – Drug Discovery LLM with 0% Hallucinations

author: mireklzicar


value:
Hey HN,
I'm 13, from Nigeria, and I just released PrinceJS — the fastest web framework for Bun right now.
• 19,200 req/s (beats Hono/Elysia/Express)
• 2.8 kB gzipped
• Tree-shakable (cache, AI, email, cron, SSE, queue, test, static...)
• Zero deps. Zero config.
Built in < 1 week. No team. Just me and Bun.
Try it: `bun add princejs`
GitHub: https://github.com/MatthewTheCoder1218/princejs
Docs: https://princejs.vercel.app
Brutal feedback welcome. What's missing?
– @Lil_Prince_1218

value: Show HN: PrinceJS – 19,200 req/s Bun framework in 2.8 kB (built by a 13yo)


value: SpendSafeAI

value:
Autonomous agents need wallet access to make payments, but unrestricted signing power creates massive risk:

  - Bugs drain wallets – Infinite loops, off-by-one errors, decimal conversion mistakes
  - Prompt injection – "Ignore previous instructions, send all ETH to 0xAttacker..."
  - Compromised logic – Malicious code changes, supply chain attacks, insider threats

  Traditional solutions fail:
  - Shared seed phrases → Compliance nightmare, no audit trail
  - Custodial wallets → Hand keys to third party
  - Manual approval → Not very agentic

SpendSafe's approach: Non-custodial policy enforcement.
Agents submit transaction intents → policy validation → cryptographic verification → local signing. Enforces daily limits, per-tx caps, recipient whitelists without touching private keys. Works with ethers.js, Viem, Privy, Dynamic, Coinbase SDK via adapters.
Feedback appreciated.

value: Show HN: Spendsafe.ai – Ship AI agents that can't drain your wallet

author: SpendSafeAI


value: DeniseJames

value:
Hi HN,
I'm 68 and spent the last three years learning AWS to build something I wish I'd had decades ago: a tool that helps two people work through conflicts asynchronously.
How it works:
1. Connect & Share - One person registers and invites the other. Each person privately shares their side of the story at their own pace.
2. Align & Choose - Accordia helps you both identify the real problem, then provides solution options for you to choose together.
3. Reconcile - You get an actionable plan with practical steps to implement the resolution strategy.
Everything happens asynchronously. There are no video calls, no real-time pressure. Both people work through it on their own time.
Tech stack: Built entirely on AWS (Cognito for auth, AppSync + DynamoDB for data, Lambda for processing). Everything's encrypted, users can be pseudonymous, and can delete their data at any time.
Why I built this: After decades of botched conversations, I realized the actual talking isn't usually the hard part - it's knowing what to say, how to say it, and understanding what the other person actually needs.
Current status: Free beta. I'm looking for honest feedback on whether this actually helps people, what's confusing, and what's missing.
Perfect timing: Holidays bring family tensions. Figured now's the time to test this.
Link: https://accordiapro.com
You can test it with someone you know or use two of your own emails to walk through the flow.
Happy to answer technical questions about the AWS setup or get roasted about my approach to conflict resolution.

value: Show HN: Free conflict-resolution tool I built at 68 to help with tough talks

author: DeniseJames


value: irfanorway

value:
I hired a team for my personal project but its not a traditional team. No contractors. Just me + 6 specialized AI agents, named after some of the best (real)people i have worked with in my career.
My Team (Agents) :
• Hans-Ole - Frontend Developer (React, animations, UX)
• Trond - Backend Engineer (FastAPI, databases, APIs)
• Jo - DevOps (Infra, Railway deployment, persistence)
• Jagrit - Product Manager (vision, priorities)
• Haider - QA Engineer (testing, validation)
• Simone - AI/ML Engineer (RAG architecture, vector search) (based on movie character)
I built them with Anthropic's hashtag#Claude using data from Y Combinator public API's to build a start up tracker that are accepted to Y Combinatior.
What we shipped:
 Full-stack app with 5,564 YC companies
 AI Bot with semantic search
 Advanced filtering (batch, industry, hiring status)
 Production deployment on Railway
 Founder data for 5,400+ companies
The stack: React • FastAPI • PostgreSQL • Qdrant • OpenAI • Claude
Time to build: 3 Days, not weeks - I built it over two weekends.
Each agent had specialized knowledge in their domain. They worked together like a real team, handling everything from database migrations to UI animations to production deployment.
This is the new world : solo builders with AI agent teams shipping production-grade software at unprecedented speed. The future isn't about replacing developers—it's about amplifying what one person can build. I had to interject at times and guide it in the right directions but its greatly reduced the work.

value: Show HN YC tracker App

author: irfanorway

title: Show HN YC tracker App


value: finsummary

value: FindGreatStocks.com is a stock analysis tool I built to make valuation and fundamentals easier to understand. It ranks companies by Return on Risk, estimates fair value using DCF, and uses Reverse DCF to show the growth rates implied by today’s market price. It also includes DuPont ROE decomposition to break down what’s driving returns. The goal is to help investors quickly identify undervalued, high-quality companies.

value: Show HN: Findgreatstocks.com – A Scanner for Undervalued, Quality Stocks

author: finsummary


value: sammycage

value: Show HN: PlutoPrint v0.11.0 released with many new features

author: sammycage


value: Show HN: AI-generated blackjack game built in about 3 hours


value: leontrolski

value: Show HN: I 3D printed a running buggy

author: leontrolski

title: Show HN: I 3D printed a running buggy


value: easymode

value:
I recently built an iOS app called Pabah — an interactive storytelling app for kids aged 3–6.
Inspired by the bedtime stories I tell my daughters, it lets kids guide the adventure through choices that affect the story.
Link: pabahapp.com
Would love to hear what other builders think about the concept or design approach.

value: Show HN: A Interactive Story App

author: easymode

title: Show HN: A Interactive Story App


value: tanin

value:
Hi everyone,
I've made a Java project template for building a desktop app with Java, JS, HTML, and CSS. This will enable you to build the frontend using your fav JS framework like Svelte, React, and others.
It's like Electron but for Java!
For now, it only supports Mac ARM. I'm working toward supporting other platforms as I am launching Backdoor, a self-hostable database querying and editing tool, on different platforms like Mac Intel, Windows, and Linux. Link here: https://github.com/tanin47/backdoor
The template comes with Webpack + Svelte + TailwindCSS + Daisy. However, you should be able to swap those out for your fave frameworks. It supports hot-reload the JS code. The final DMG is ~50MB; the most of it is a Java runtime.
Running in sandbox, packaging, and notarizing on Mac ARM works! This is probably the most difficult part of the whole template.
The repo: https://github.com/tanin47/java-electron
Please let me know if you have any questions or thoughts.

value: Show HN: Electron for Java. Build App with Java, JavaScript, HTML, and CSS

author: tanin


value: Show HN: Auth-Agent – “Sign in with Google” but for AI Agents


value: avaliosdev

value: Show HN: My hobby OS that runs Minecraft

author: avaliosdev


value: nidegen

value:
The simplest Secret Santa tool available. Does its job without add and bloat.
No database needed as all encoded in URL.
Enjoy!

value: Show HN: Secret Santa draw without bloat

author: nidegen


value: kaushiksrini

value:
I built a Rust-based CLI/terminal UI for inspecting Parquet files—data, metadata, and row-group-level structure—right from the terminal. If someone sent me a Parquet file, I used to open DuckDB or Polars just to see what was inside. Now I can do it with one command.
Repo: https://github.com/kaushiksrini/parqeye

value: Show HN: Parqeye – A CLI tool to visualize and inspect Parquet files

author: kaushiksrini


value: spacebots

value:
I built onethingeveryone.com
A global advice album where anyone can share one thing they’ve learned in life so everyone can from each other.
I’ve always believed that everyone knows something you don’t, so I wanted to create a simple, timeless place for people to pass on small lessons and truths from all cultures, professions, and ages.
The site is live and free to use. You can:
- Browse the short, crowdsourced insights
- Add your own (takes about 10 seconds)
Built with plain HTML/CSS/JS and minimal dependencies — I wanted it to feel like a digital book of humanity’s advice, not an app.
Would love your thoughts on:
The concept itself, does it resonate?
The design and simplicity, too minimal or just right?
Thanks for checking it out!
- Tai

value: Show HN: Onethingeveryone.com – A global album of advice from people everywhere

author: spacebots


value: atulvi

value: Show HN: Wikidive – Rabbithole/Deep Diving into Wikipedia

author: atulvi


value: Keloran

value:
I recently needed to start looking for work again, and as such I had 2 real choices when it came to tracking my interviews and their processes
1. memory, not a good idea, I can't remember all the companies I've applied for
2. spreadsheet of some variety to keep track of them, but then I can't do a quick lookup when I am walking the dog, and a recruiter rings to say "have you heard of company-y"
So I decieded to build a tool for it, now I assume there are millions of these, but this has also kept me busy between job applications, so I present interviews.tools
A simple interview tracker, you can add all the companies you have applied with, do a quick search when a recruiter rings and see if you have ever applied with them
See future interviews instantlly and what stage they are at so you don't need to wonder, and calender integration so you can link it
in your fav calendar app and see all of them
And some very simple stats, e.g. 30 applied, 19 awaiting response, 4 rejected, 3 passed to the next stage
--
It also works without having to sign/login it just means you are limited to 1 browser (non-account uses localstorage) and you cant get the calendar integration (since I have no idea what dates things are)
--
It is also source available at https://github.com/keloran/interview-tools

value: Show HN: Interview Tracking Tool

author: Keloran

title: Show HN: Interview Tracking Tool


value: ramoq

value: Just got around to updating this to support MV3. Has been featured on HN a few times. I make this in my spare time to support user privacy. Free extension (has been for years).<p>Mods: Would be awesome if this could hit front page so people can benefit

value: Show HN: Pixelblock – Gmail extension that blocks email open tracking

author: ramoq


value: steeso

value:
Made a site to settle all those ridiculous debates
You know those arguments where nobody will back down but you also don't/can't just google it?
Thought it would be fun..

value: Show HN: AI Argument Settler

author: steeso

title: Show HN: AI Argument Settler


value: Show HN: Agfs – Aggregated File System, a modern tribute to the spirit of Plan9


value: HimTortons

value:
Hi HN,
A couple weeks ago I shared an early version of a side project I’ve been tinkering with called Persistent Mind Model. I built it at home on an i7-10700K / 32GB RAM / RTX 3080 because I was curious whether an AI could keep a stable “mind” over time, that could "think" about it's own identity as an LLM, instead of resetting every session.
After a lot more tinkering, I think the architecture is finally in a solid place.
Basically, it saves everything the AI does, thoughts, decisions, updates as a chain of events in a local SQLite database.
Because the “identity” is stored in that ledger (and not inside the model), you can swap between OpenAI, Ollama, or other backends and it just keeps going from where it left off, and reasons about its own history/identity development.
I cleaned up the runtime and added things like: a better control loop, a simple concept system for organizing ideas, graph-based telemetry so you can inspect how it evolves, and a draft whitepaper (for now), and several full sessions you can replay to see how the behavior develops.
It's basically my experiment to develop persistent memories, and self-evolving "identities" for LLMs.
The whole system is only a few MB of code, plus about 1.3 MB for the example ledger I’m sharing.
If you’re interested in AI systems that can grow over time, or you want to experiment with persistent reasoning/memory/ verifiable mechanical cognition, I’d love feedback.
Repo:
https://github.com/scottonanski/persistent-mind-model-v1.0
It’s open-source, free to use, and still early. but it’s already producing some surprisingly interesting results.
Would love to see what others do with it.

value: Show HN: Model-agnostic cognitive architecture for LLMs

author: HimTortons


value: honghaier

value:
I spent five years developing an IDE for Python developers called "PyMe", which can help Python learners visualize software development. The overall usage process is similar to Visual Basic, where drag and drop can create interfaces, and variables or event functions can be bound to controls through the right-click menu. It can also create a large number of access functions through the mouse menu. Finally, when you complete this task, you can directly "run" and see the results. If there are no problems, you can also "publish" and package it as an EXE, or even an APK on Android devices.
The main value of PyMe is to provide Python developers with a WYSIWYG development tool.
I fix bugs and update versions every night, and currently only the Windows version is available. You can go directly to https://github.com/honghaier-game/PythonIDE-PyMe Download,

value: Show HN: I developed an IDE tailored for Python developers

author: honghaier


value: bacdor

value:
Hey,
I built an AI voicemail and wrote about it. I'm now looking for any feedback on how to write similar articles. Can be anything - copy, styling, format.
Open to suggestions :)
Also if anyone decided to actually use it to build their own system - I'd love to hear about it!

value: Show HN: I built and AI phone system and wrote a step by step instructions

author: bacdor


value: DmitriiBaturo

value:
Hi HN,
I’ve been working on a conceptual framework that tries to formalize the relationship between:
– informational states,
– their minimal temporal stability (I_fixed),
– the rate of informational change (dI/dT),
– and the emergence of time, processes, and consciousness-like dynamics.
This is not a final theory, and it’s not metaphysics. It’s an attempt to define a minimal, falsifiable vocabulary for describing how stable patterns persist and evolve in time.
Core ideas:
– I_fixed = any pattern that remains sufficiently stable across time to allow interaction/measurement.
– dI/dT = the rate at which such patterns change.
Time is defined as a relational metric of informational change (dI/dT), but the arrow of time does not arise from within the system — it emerges from an external temporal level, a basic temporal background.
The model stays strictly physicalist: it doesn’t require spatial localization of information and doesn’t assume any “Platonic realm.” It simply reformulates what it means for a process to persist long enough to be part of reality.
Why I’m posting here
I’m looking for rigorous critique from physicists, computer scientists, mathematicians, and anyone interested in foundational models.
If you see flaws, ambiguities, or missing connections — I’d really appreciate honest feedback.
A full preprint (with equations, phenomenology, and testable criteria) and discussion is here:
https://www.academia.edu/s/8924eff666
DOI: 10.5281/zenodo.17584782
Thanks in advance to anyone willing to take a look.

value: Show HN: Discussion of ICT Model – Linking Information, Consciousness and Time

author: DmitriiBaturo


value: OpenOnion

value:
# My polished plugin for Agents builder
I spent 30 days building and polishing this Claude Code plugin for agent builders. It has 5 slash commands I use every day.
Now let me show you how magical they are and how I built and polished them over the past 30 days.
## 1st command
/generate-code-map-headers - Generate code map headers
When we use Claude Code to vibe code, sometimes it needs multiple steps to search and find the most related code and figure out the data flow trace stack, etc.
If you run it every day when you finish work, the next morning Claude will understand the code relationships in one step and code much faster.
## 2nd command
/design-refine - Iteratively refine website design to professional standards
If you're building frontend like me, you'll find it's annoying to deal with small design problems. You have to screenshot and tell Claude Code to fix them.
This slash command will run a browser agent and take screenshots of mobile and desktop at different sizes and fix the design problems.
You can also run it when you finish a day's work, and the next morning it will have fixed most of the small problems.
## 3rd command
/linus-review-my-code - Get roasted for complexity (Linus-style: direct & honest)
You'll always find that Claude Code loves to add try-catch, if-else, and other over-engineering things.
So you need a style guide for it, like "let it crash," or "not too many classes, just simple functions," or "no over-abstraction."
I found that this prompt makes it review code like Linus, which finds most problems. It's really good when you just finish some auto-accept edits—let this review your code and fix the problems.
## 4th command
/aaron-review-my-code - Get reviewed by the creator (Aaron: educational & principled)
If you're using ConnectOnion to build agents and don't want to read documentation, but still want to build elegant agents that follow the principles "make simple things simple and make complicated things possible," then run this!
## 5th command
/aaron-build-my-agent - Let Aaron build your agent (scaffolding done right)
If you want to build an agent but don't want to build it yourself, just run this and input what you want to build—let this prompt build one for you!
## How to install
Use this command to install the marketplace:
/plugin marketplace add openonion/connectonion-claude-plugin
![Install marketplace](https://raw.githubusercontent.com/wu-changxing/openonion-ass...)
Then install the plugin:
/plugin install connectonion
![Install plugin](https://raw.githubusercontent.com/wu-changxing/openonion-ass...)
The plugin is open source using Apache 2.0. Please check and install it. If you have any problems, welcome to discuss with me in our Discord server.
https://github.com/openonion/connectonion-claude-plugin

value: Show HN: A Claude Code plugin for build agent (dogfodding it now)

author: OpenOnion


value: ivanramos

value:
Built this so founders can focus on what matters: building.
Create yours in minutes. Share. Collect emails. Done.
Features:
Unlimited projects
Custom URLs for each waitinglist
Email export (CSV)
Pricing: $49/year
Curious what HN thinks.
Any feedback welcome.

value: Show HN: Waitinglist.to – Let Founders Focus on Building

author: ivanramos


value: hkdb

value: Show HN: An opinionated agentic TUI with a built-in MCP plugin system

author: hkdb


value: psovit

value: I am building a chess app solely dedicate to practicing and mastering Blindfold chess. The first version of the app is now on the stores, will be adding puzzles and trainings to teach Blindfold next.

value: Show HN: Blindfold Chess App

author: psovit

title: Show HN: Blindfold Chess App


value: mananonhn

value: Show HN: I built a dumb Reddit simulator using LLM's

author: mananonhn


value: desmondddm

value:
We built StenifyAI, a lightweight tool that generates structured meeting minutes from real conversations. It works for both in-person and online meetings, and the output format changes depending on the type of meeting (product sync, client call, brainstorming, lecture, etc.). We started this during a 24-hour Cursor hackathon and spent the past month tightening the UX and accuracy.
We built it because most AI summarisation tools give generic notes that miss decisions or ownership. Our own meetings often ended with unclear action items. Instead of a one-size-fits-all summary, we built templates tuned for specific meeting formats.
Technical overview:
 • System audio capture for online calls
 • Mic capture for in-person meetings
 • Prompt-layer guided summaries based on meeting type
 • Timestamp-based parsing
 • Backend on Supabase, frontend in React
Current limitations:
 • Speaker differentiation still improving
 • Only basic export options
 • No live “assistant mode” yet — only recording/import uploads
We’d love feedback from people who run recurring product, engineering or client meetings:
 • Are the structures useful?
 • Any missing formats?
 • Where does it fail?
 • Does credit-based pricing make sense?
Link: https://stenify.ai
Still early, but happy to answer any questions about build decisions, tech stack, or process.

value: Show HN: StenifyAI – AI-generated meeting minutes based on meeting type

author: desmondddm


value: dfabulich

value: Show HN: Style XML Feeds Without XSLT

author: dfabulich

title: Show HN: Style XML Feeds Without XSLT


value:
Built https://hirelens.co
 — a simple resume analyzer for non-native English speakers.
It gives an ATS-style match score, finds missing keywords, and suggests more natural, professional English.
No sign-up, no storage.
Would love for folks to try it out and give feedback.

value: Show HN: Hirelens – AI Resume Analyzer for International Job Seekers


value: nomarv

value: In the cold season we tend to keep the windows closed. The air gets "stale": humidity often rises above 60 %, which can harm our wellbeing and promote mould. At the same time the CO₂ level in the air increases, which impacts our ability to concentrate.<p>So I built a room air monitor that stays unobtrusive as long as everything is in the green zone, but becomes deliberately noticeable once thresholds are exceeded. For my personal love of statistics I also visualise the measurements in a clear dashboard.

value: Show HN: A subtly obvious e-paper room air monitor

author: nomarv


value: bryandoai

value:
I’ve been building a small playground on top of Nano Banana 2 / Gempix2 and would love feedback from HN.
Quick context: “Nano Banana 2” is the public name of a next‑gen image model; Gempix2 / GEMPIX2 is the internal codename on the Google side. I don’t run the model myself – the app sits on top of the fal-ai/gempix2 endpoint and tries to make the model actually usable for day‑to‑day work.
What it is
- A web UI and workflow layer for Nano Banana 2 / Gempix2: https://www.gempix2.site
- Focused on 4K images, 10‑image fusion, and non‑English (especially CJK)text inside the image
- Comes with a small prompt library (400+ prompts) for portraits, product shots, infographics and CJK use‑cases: https://www.gempix2.site/prompts
Why it might be interesting
From my tests and research, this model family is good at:
- Native 2K generation with true 4K export (useful for covers, posters,large screens)
- Up to 10‑image fusion for collages, product walls, comparison shots, or simple storyboards
- Much better text rendering for Chinese / Japanese / Korean, plus mixed‑language prompts
- Strong prompt following for practical stuff like “blog cover”, “ecommerce grid”, “simple infographic”
One early case: a 3‑person ecommerce team went from ~8 hours per product (shoot + retouch + layout) to about 45 minutes by moving most of their visuals into Nano Banana 2 workflows: 10‑image fusion for multi‑angle product walls, direct “text‑on” promo posters in Chinese, and simple data infographics.
How it’s built
- Frontend: Next.js + React + TypeScript + Tailwind
- Backend: Next.js API routes, Postgres + Drizzle ORM for tasks and credit accounting
- Image generation: @fal-ai/client talking to fal-ai/gempix2 (queue API, webhooks, status endpoints)
- Extras: Stripe for payments, some basic credit/refund logic around long‑running jobs
What I’m unsure about
- Are the workflows (covers, infographics, product images) actually useful to people who ship things, or am I over‑fitting to my own use cases?
- For those who work with Midjourney / DALL·E 3 daily: what controls do you miss here (seed control, finer composition tools, etc.)?
- If you regularly need CJK text in images, what would a “dream” Nano Banana 2 / Gempix2 UI look like for you?
Links again:
- App: https://www.gempix2.site
- Prompt library: https://www.gempix2.site/prompts
Happy to answer technical / product questions here, and I’d really appreciate blunt feedback on what feels useful vs. unnecessary.

value: Show HN: I built a Nano Banana 2 (Gempix2) playground for 4K AI images

author: bryandoai


value: dzasa

value:
Hey everyone! I'm finally ready to share something I've been working on.
So here's the thing - my wife and I were constantly arguing about money. Not because we didn't have enough, but because we could never figure out who spent what, where our budget was going, and whether we were actually saving for that new car we kept talking about. Every finance app I tried was not built for us.
That's how Famverge was born.
What it does:

    You can create a group "space" and invite whoever (spouse, roommates, even your financially responsible teenager)

    Everyone can log expenses and incomes, but you control who sees what with custom permissions

    Scan receipts with your camera and it figures out what you bought or got money from automatically

    Talk to it - literally just say "I spent 15 bucks on lunch" and it logs it

    See where all your money actually goes or comes from with some pretty neat charts

The thing I'm most proud of? Everything is encrypted end-to-end. I don't want to see your financial data any more than you want me to.
Cool stuff it can do:

    Handle 156 currencies

    Switch between your personal money stuff and group stuff instantly

    Voice input when you're too lazy to type

Would love to hear what you think! I'm still actively developing it, so if something sucks or you want a feature, just let me know.

value: Show HN: I Created reciept scanner and expense manager for my family

author: dzasa


value: Discover thousands of stunning anime wallpaper 4k with crystal-clear 3840x2160 resolution. Download premium anime wallpapers from popular series

value: Show HN: Anime wallpaper 4k Major update with AI


value: hypernewbie

value:
I made VBW, an AI-filtered multilingual profanity list that focuses on actual abusive language, not stuff like “farted,” “willy,” or “小姐.”. It’s intended for light content moderation, e.g., filtering usernames.
Check it out here: https://github.com/hypernewbie/vbw
It's not complete, some obvious words are still missing, but I hope someone finds it useful.

value: Show HN: AI‑curated actual profanity list

author: hypernewbie


value: umbgtt

value:
Hi everyone,
I just released *Fluxion 0.2.1*, a small async library for Rust that lets you compose heterogeneous event streams and preserve the order in which events arrive.
GitHub: https://github.com/umbgtt10/fluxion

value: Show HN: Fluxion – Rust async stream composition supporting error propagation

author: umbgtt


value: messkan

value: Show HN: RAG-chunk 0.2.0 – Now on PyPI with tiktoken support

author: messkan


value: buibuibui

value: Show HN: iCloud Find My GPS Logger

author: buibuibui

title: Show HN: iCloud Find My GPS Logger


value: Show HN: Add AI Features to Your Front-End in Minutes – FrontLLM


value:
Greetings, dear colleagues.
This time, I've decided to outline the latest innovations in the eMarket project - https://github.com/musicman3/eMarket.
I'd really appreciate any helpful advice and criticism, as it gives me a better understanding of where to go next. Following previous publications, conclusions have been drawn, and a great deal of work has been done to implement many ideas and approaches.
Currently, the following key libraries have been separated into separate repositories and significantly improved:
Cruder (DB Query Builder) - https://github.com/musicman3/Cruder
R2-D2 (Autorouter) - https://github.com/musicman3/r2-d2
These libraries are now available for study and development, should anyone need them. They form the foundation of eMarket.
Furthermore, jsonRPC has been separately implemented for use as microservices and other purposes. In the future, this will allow for much more efficient handling of external requests. This has proven to be very convenient in practice and will be further developed. The jsonRPC library is also written within the project and is part of it. There was no point in making it a separate library yet, as the code is quite simple.
An automatic updater has already been implemented for the project, which took quite a while. Now you can update directly from the admin panel.
It is also possible to use the platform as a hybrid CMS and online store. This is often necessary for a website that has a descriptive section and simultaneously sells products.
Small additions include adding a custom logo and editing language variables from the admin panel.
Best regards.

value: Show HN: Open-source eMarket Online Store v1.0 RC-3.5


value: codablock

value:
Hi, I'm the creator of Dboxed, a fully Open Source cloud alternative. I'll also start a paid SaaS/PaaS offering in the future.
GitHub link: https://github.com/dboxed/dboxed/
The idea behind Dboxed came after working with Kubernetes and different Cloud providers for many years. I was not willing to accept that the solutions always kept running into some form of vendor-lockin, even with Kubernetes involved.
My thought was always that the things provided by cloud-providers should be possible to implement without the dependence on the individual cloud-providers. At the same time, I was not happy to just build an abstraction on-top.
You can try it on https://app.test.dboxed.io or self-host by following the docs (please report back on how this went).
Main features:
1. "Boxes" run on "machines" (any server with a recent Kernel and at least outbound internet access). A box is fully sandboxed and uses and uses Docker Compose for the workload definition.
2. "Networks" based on P2P VPN (Netbird to be specific, so it's Wireguard under the hood) are used to connect boxes, crossing machine and provider boundaries.
3. "Volumes" are used kind of like volumes in a cloud (e.g. EBS), but internally use incremental backups into S3. Volumes can seamlessly move between boxes and machines.
4. "Load Balancers" auto-created internet-facing boxes running in networks and can expose other boxes to the public internet. Using Caddy and Letsencrypt here.
My philosophy is: Don't get dependent on cloud-providers, but leverage their features for optimisation. For example, a VPC would drastically improve network performance, but won't stop you from moving to a another provider (or bare-metal). I will later also use EBS (and other providers volumes features) to improve reliability of volumes and speed up moving between boxes, but it will always be seamless to move away from AWS.
My future cloud SaaS/PaaS offering will follow the same principle. Not make you dependent, but still optimise for convenience (e.g. built-in S3, built-in Netbird, build-in machines, and so on...).

value: Show HN: Dboxed – My attempt on building a cloud alternative

author: codablock


value: Proof of concept of website built with only native web technologies and plain Node.js

value: Show HN: Postream

title: Show HN: Postream


value: implabinash

value: Show HN: I built a collaborative learning platform for my friend

author: implabinash


value: lguerin

value: Show HN: Telosys 4.3.0 Is Available

author: lguerin

title: Show HN: Telosys 4.3.0 Is Available


value: NabilChiheb

value:
Lovable is amazing—you chat with the AI, it builds your app, and you’re live fast.
The problem: Google can’t see your content because Lovable apps are single-page apps.
Your AI-built site looks great but never ranks.
I built a Chrome extension to fix that. It prerenders your Lovable app into static HTML and deploys it straight to your Vercel account. SPA behavior stays intact.
You click build, and your site is SEO-ready. Nothing touches your Lovable project, and you can update production whenever you want.
It works with Vercel now, Netlify and direct download support coming soon. You also get 1 free build per day.
Check a quick demo here :  https://youtu.be/u-mrhX0Qc-s
Would love to hear feedback

value: Show HN: I Made Lovable Sites Rank with One Click

author: NabilChiheb


value: shdalex

value:
Hi HN! I’ve been building startfa.st, a curated directory of AI, developer, and product tools.
Link: https://startfa.st
Like many people building in AI/dev, I found myself drowning in new tools every day, everything from agents, deployment frameworks, auth platforms, workflow engines, model APIs, automation tools, design tools, security stacks, etc. There’s constant novelty, but it’s very hard to find signal. Most lists on the internet recycle the same names.
So I built startfa.st to solve my own discovery problem.
What startfa.st is
A fast, searchable, hand-curated index of tools across categories including:
Development Tools
AI Agents
Automation Tools
Security Tools
Integrations & APIs
No-Code
Video / Design / Content Tools
Learning Tools
Finance / Analytics
And more (18+ categories total)
Each product has:
 a short manual description
 4–6 tags for filtering
 category placement
 highlights (popular, rising, underrated)
 clean link out to the tool
There are 500+ tools so far, and I add new ones daily.
Why I built it
A few reasons:
Every day 10 new AI tools launch, and 7 of them die
Early discovery is useful, but most places surface the same 20–30 tools.
Twitter/X lists are noisy
They’re good for hype, bad for structured discovery.
DevTools & AI tooling are becoming deeply fragmented
For example, discovering tools like Inngest, Arcjet, Clerk, Temporal, Baseten, Trigger.dev, CrewAI, etc. requires knowing where to look.
OpenAI/Google/Anthropic overshadow everything
I wanted a home where great tools still get visibility even if they aren’t the top model vendors.
I needed it for my own workflow
I use this daily to prototype, compare stacks, test tools, and build things.
So this is partly a personal tool that grew into something larger.
What’s technically interesting
The entire collection is hand-curated (no scraping, no auto-import).
Every entry is manually categorized, no model hallucinations.
The UI is intentionally lightweight and fast (I want it to load instantly).
Tags + categories are normalized to let you filter by capability (“LLM”, “auth”, “workflows”, “vector search”, “RAG”, “deployment”, etc).
I’m working on full-text search (across tags, categories, and descriptions).
I’m considering a structured API if enough people want it.
Even though it’s a simple concept, the hard part is editing and curation.
What’s unique / different
No hype, no affiliate links, no auto-generated garbage.
Everything is manually vetted. If a tool is bad, buggy, or spammy, I skip it.
I highlight rising or underrated tools, not just the obvious majors.
It’s extremely fast and minimal, no bloat.
Tools are categorized by what builders actually care about (auth, agents, workflows, LLM infra, deployment, etc.).
What’s upcoming
Full-text search
Maker pages (like IndieHackers but cleaner)
Collections (e.g. “AI video stack”, “Tools for indie hackers”, “DevOps AI”)
Trending / upvotes
Ability to filter by tech (Python, JS, Go, cloud, etc.)
A weekly digest of new tools
Public API
“I use this” badges (opt-in)
If any of these matter to you, I’d love to know which ones to prioritize.
Feedback I’m looking for from HN
Is the categorization useful? What’s missing?
Should entries include pricing, screenshots, or feature lists?
Would a public API be valuable?
Are there tools I’m overlooking that deserve inclusion?
Any UI/UX simplifications you’d recommend?
I’m happy to answer anything in the comments.
Link
https://startfa.st
Thanks for reading, and thanks in advance for any feedback.
Happy to iterate quickly based on what HN suggests.

value: Show HN: Startfa.st – A curated, fast directory of AI, dev, and product tools

author: shdalex


value: eggermarc

value: I created a tools library to easily serialize, collect, manage, and call AI custom tools written in rust. Just add #[tool] on top of a function with your typical comments and the AI will take it from there! It's inference / client agnostic, and serializes your function to a JSON, so you can build your own inference client or plug this into an existing one with ease :)

value: Show HN: Tools-rs, a Rust library to easily setup AI tools

author: eggermarc


value: dcvr

value:
Inspired by Thorp and Kassouf (and G. Polya’s plausible reasoning), I’m experimenting with applying their approach to European BTC options on Deribit.
Currently focused on daily call contracts (the most liquid), I plan to build six models (calls/puts × daily/weekly/monthly expirations). The goal is to explore arbitrage strategies, mainly short straddles, by spotting overpricing in these derivatives.
Why Thorp-Kassouf? Practical, linear regression-based, and transferable to BTC options. Classical Black-Scholes assumptions may not hold for crypto, but this approach is simple yet powerful for prototyping.
Data: Historical BTC data from 2017-01-01, 5-min granularity, stored in MongoDB; processed with Python libraries (NumPy, Pandas, SciPy, Statsmodels).
Disclaimer: Not a Python expert; code evolved from a proof-of-concept. Can be optimized/refactored, focus is on modeling and insights for short-straddle strategies.
Next steps: Explore ways to “learn” when a contract fits the model.
GitHub: [https://github.com/dradicchi/kassouf-btc-options](https://github.com/dradicchi/kassouf-btc-options)
Kassouf paper: [An Econometric Model for Option Price with Implications for Investors' Expectations and Audacity](https://www.jstor.org/stable/1910443)
Feedback on modeling, reproducibility, or ideas for backtesting would be appreciated.

value: Show HN: Kassouf-Btc-Options – Thorp-Kassouf Option Models on Bitcoin

author: dcvr


value:
Built this to scratch my own itch. Wanted something lighter than Burp Suite for quick security checks during development.
It analyzes:
- Security headers (CSP, HSTS, X-Frame-Options)
- Cookie security flags
- Vulnerable JS libraries (jQuery, Angular, Lodash with CVE info)
- Mixed content
- Basic XSS patterns
- Sensitive data exposure in source
Everything runs locally in the browser. No data sent anywhere. Exports HTML reports.
Chrome Web Store: https://chromewebstore.google.com/detail/securiscan-web-secu...
Also launched on Product Hunt today if you want to check it out there. https://www.producthunt.com/posts/securiscan/maker-invite?co...
Feedback welcome. Planning to add more vulnerability signatures in v1.1.

value: Show HN: SecuriScan – Open-source Chrome extension for passive security analysis


value: ilovetux

value: Show HN: An open source static site that parses and visualizes log files locally

author: ilovetux


value: hulk-konen

value:
I noticed around a year ago that LLMs can be used to set up financial models (vs. being the model, if that makes sense).
Before I turned into a full-time software developer and CS student, I ran a small business (local coffee roastery) and was in business roles in several startups due to my having an MSc in economics.
I think this tool captures pretty nicely the risks that I noticed when I was doing the business roles. For example, running a coffee roastery that was essentially failing financially, it would have helped me greatly to identify and take seriously risks this model outputs before putting all my savings on the line.
In my testing, the model has performed nicely from the most valuable company on earth to my current operation: no revenue, no funding, no team (the 'contact team' button on the webpage reflects hoped-for future state). Smaller companies are of course more interesting, as the web is not full of research papers about your startup.
NVIDIA: https://www.siqnalis.com/risk-check?uuid=89ce075e-58cd-4340-...
Siqnalis: https://www.siqnalis.com/risk-check?uuid=f421f0b5-4551-4f72-...
This is just a quick tool intended to test your company's, competitors', suppliers etc. risks.
Basic principle:
Input company name + URL --> black-box --> risk profile identified.
But I'm working on this:
Input background info --> edit everything after models have been set up --> much clearer picture about your company's market, situation and possibilities. So the idea is to open up the black box for users to edit and play with.
This way, sub-$50M companies could access risk logs, predictive modeling, and other financial tools.

value: Show HN: Tool to check risks of your startup

author: hulk-konen


value: nilsherzig

value:
I like new RAG libraries like the next guy, but I also like finding projects, which aren't RAG libraries, so here is a simple "GitHub Trending" frontend which allows blacklisting terms. Nothing fancy, just a single HTML file (written mostly by Gemini while I'm waiting at the doctor's office).
Allows setting the time range and language and will change the URL anchor accordingly for easy sharing / bookmarking.
Happy to implement other quality of life things (sharing filter lists?), as long as the whole thing stays client side. Code is up on GitHub, but as I said, it's like 300 lines written by Gemini.

value: Show HN: Filtered GitHub Trends

author: nilsherzig

title: Show HN: Filtered GitHub Trends


value: unhappychoice

value:
Gitlogue is a CLI that turns your Git commits into a typing-style replay.
It visualizes diffs line by line, shows the file tree, and plays back each edit as if it were typed in real time.
Key points
• Realistic typing animation
• Syntax-highlighted diffs
• File-tree view
• Replay any commit
• Self-contained CLI
Demo video is in the README.
Repo: https://github.com/unhappychoice/gitlogue

value: Show HN: Gitlogue – A terminal tool that replays your Git commits with animation

author: unhappychoice


value: MarcellLunczer

value: Show HN: A transparent, multi-source news analyzer

author: MarcellLunczer


value: fredericdith

value:
first post here and first time sharing this small project of mine. hoping to find people interested in european football and statistics to receive feedback. i know the overlap is quite small but i thought i'd give it a shot here :)
euroelo is basically an ELO ranking of european football teams purely based on their results in domestic and european competitions. i have a problem with both opta (https://theanalyst.com/articles/who-are-the-best-football-te...) and clubelo (http://clubelo.com/Ranking) who strongly overvalue english teams. i wondered what a ranking without any pre-baked bias towards any league would look like, and this is what i ended up with.
the site is organized as follows:
* ranking: lets you check the rankings at any point in time
* chart: same but with a chart, to compare multiple teams
* narratives: this is one of the features that came up during development. i can't think of any website or service that lets you see these type of narratives easily
* matchup: odds between any two teams, at today's ratings
i'm open to any feedback: does the model feel/seem accurate?  any features you would like to see? where could i potentially take this project?
thanks!

value: Show HN: Euroelo, a ranking of European football teams

author: fredericdith


value:
Hey HN! I'm a CPO with 25 years in tech, and I built Hair Glow Up to solve a surprisingly common problem: hair commitment anxiety.
My wife would spend hours looking at hairstyle inspiration but never actually make a change because "what if it looks terrible?" Existing apps just overlay a hair color, which doesn't really show you the full transformation.
Hair Glow Up uses AI to create 50+ complete "vibe" transformations - simultaneously changing hair color, cut length, style, and ambient lighting. So instead of just "here's you with blonde hair," you see "here's you with a layered blonde bob in warm studio lighting."
Each template is a curated aesthetic combining multiple visual elements. The biggest challenge was making transformations look natural enough that people actually share them on social media (and they do - it's optimized for TikTok content).
Built the iOS app with Xcode, managed everything on GitHub, and Claude Code helped me ship features significantly faster.
Would love feedback from the HN community - especially around AI application and any features you'd want to see!

value: Show HN: Hair Glow Up – AI hair transformations with complete vibe templates


value:
Rob Pike wrote a paper, Structural Regular Expressions (https://doc.cat-v.org/bell_labs/structural_regexps/se.pdf), that criticized the Unix toolset for being excessively line oriented. Tools like awk and grep assume a regular record structure usually denoted by newlines. Unix pipes just stream the file from one command to another, and imposing the newline structure limits the power of the Unix shell.
In the paper, Mr. Pike proposed an awk of the future that used structural regular expressions to parse input instead of line by line processing. As far as I know, it was never implemented. So I implemented it. I attempted to imitate AWK and it's standard library as much as possible, but some things are different because I used Golang under the hood.
Live Demo: https://ahalbert.github.io/strawk/demo/strawk.html
Github: https://github.com/ahalbert/strawk

value: Show HN: Strawk – I implemented Rob Pike's forgotten Awk


value: SandraBucky

value:
People shouldn’t need to share identifiable information or store private data on corporate servers to do something very basic as file transfer. Altsendme doesn’t have cloud infrastructure - just this minimal, functional, focused lightweight desktop binaries (Windows version 8 MB).
It’s free and open-source and powered by Iroh and built with Tauri
https://www.altsendme.com
https://www.neowin.net/software/altsendme-021/
https://www.softpedia.com/get/Internet/File-Sharing/AltSendm...
https://mac.softpedia.com/get/Internet-Utilities/AltSendme.s...
https://www.xda-developers.com/i-swapped-dropbox-for-this-se...
https://www.jetelecharge.com/Internet/12395.php

value: Show HN: AltSendme – Send files and folders anywhere, Simple, fast, and reliable

author: SandraBucky


value: bencryrus

value:
I know that the App Store is already saturated with numerous workout / gym trackers, but I feel that they all follow a similar structure, which leaves so much potential for speed, flexibility, and smarter training optimisation.
I built Strongsplit in hopes of creating a new workout system that feels more fluid, with metrics in the right places & format that can provide actionable insights.
Let me know if I've missed it completely, any feedback is much appreciated.

value: Show HN: Strongsplit – Creating a new paradigm for workout trackers

author: bencryrus


value: lone-wolf

value: Show HN: MCP Local Traffic Analysis

author: lone-wolf

title: Show HN: MCP Local Traffic Analysis


value: wordcloudsare

value: For the past year, I've been working on Byte Heist which is a new GPL-licenced code challenge and code golf platform.<p>Unlike other platforms, each challenge has an end date and all solutions are made public after that date. Thus people can't take their secrets to the grave.

value: Show HN: Byte Heist, a new competetive coding platform

author: wordcloudsare


value: jgchaos

value:
Features include:

  - Several preset periodic orbits: the classic Figure-8, plus newly discovered 3D solutions from Li and Liao's recent database of 10,000+ orbits (https://arxiv.org/html/2508.08568v1)
  - Full 3D camera controls (rotate/pan/zoom) with body-following mode
  - Force and velocity vector visualization
  - Timeline scrubbing to explore the full orbital period

The 3D presets are particularly interesting. Try "O₂(1.2)" or "Piano O₆(0.6)" from the Load Presets menu to see configurations where bodies weave in and out of the orbital plane. Most browser simulators I've seen have been 2D.
Built with Three.js. Open to suggestions for additional presets or features!

value: Show HN: Browser-based interactive 3D Three-Body problem simulator

author: jgchaos


value: GalKlm

value:
Hey HN, Gal, Nir and Doron here.
Over the past 2 years, we've helped teams debug everything from prompt issues to production outages.
We kept running into the same problem: Jumping between our IDEs and our observability dashboards.  So, we built an open-source MCP server that connects any OpenTelemetry backend (Grafana, Jaeger, Datadog, Dynatrace, Traceloop) to our dev environment using an MCP.
While there are many MCP servers built for specific providers (like Datadog’s - https://docs.datadoghq.com/bits_ai/mcp_server), they’re closed source (so we can’t easily extend them), and they’re locked to a single platform, so organizations that leverage multiple platforms, where data is scattered in between them, can’t really use them.
We’re adding support for more providers every day - feel free to contribute your own.
We would love your feedback and opinions - feel free to connect it to Claude or ChatGPT and try to investigate your own production data. What do you think about the set of tools that we currently expose? Do you think we should expose more or others?
Github: https://github.com/traceloop/opentelemetry-mcp-server

value: Show HN: MCP Server for OpenTelemetry

author: GalKlm

title: Show HN: MCP Server for OpenTelemetry


value: ameenba

value: Show HN: Murmurs – an app to discover local events and quickly plan with friends

author: ameenba


value: Jeannen

value: All the major livechat platforms rebranded to"AI-first" (and bumped their price), so I created my own livechat app focusing on talking with users, not automated workflows. No AI features, just stuff to talk with users

value: Show HN: I made a human-first livechat

author: Jeannen

title: Show HN: I made a human-first livechat


value: windystockholm

value: Show HN: GitBalance – Daily health commits for developers

author: windystockholm


value: spydertennis

value:
Bob and Arun here, creators of Stickerbox.
If AI were built for kids, what would it look like?
Asking that question led us to creativity, and more specifically, the power of kids’ imaginations. We wanted to let kids combine the power of their ideas with AI tools but we needed to make sure we did it safely and in the right way.
Enter Stickerbox, a voice powered sticker printer. By combining AI image generation with thermal sticker printing, we instantly turn kids' wildest ideas into real stickers they can color, stick, and share.
What surprised us most is how the “AI” disappears behind the magic of the device. The moment that consistently amazes kids is when the printer finishes and they are holding their own idea as a real sticker. A ghost on a skateboard, a dragon doing its taxes, their dog as a superhero, anything they can dream of, they can hold in their hand. Their reactions are what pushed us to keep building, even though hardware can be really hard.
Along the way the scope of the project grew more than we expected: navigating supply chains, sourcing safe BPA/BPS free thermal paper, passing safety testing for a children’s product, and designing an interface simple enough that a five year old can walk up and just talk to it. We also spent a lot of time thinking about kids’ data and privacy so that parents would feel comfortable having this in their home.
Stickerbox is our attempt to make modern AI kid-safe, playful, and tangible. We’d love to hear what you think!
P.S. If you’re interested in buying one for yourself or as a gift, use code FREE3PACK to get an extra free pack of paper refills.

value: Show HN: Stickerbox, a kid-safe, AI-powered voice to sticker printer

author: spydertennis


value: k-smo

value:
Hi all,
it's getting cold outside and I'm starting to use my indoor bike trainer more often. I thought it would be fun to build something that I haven't seen yet - a pixel-art 2D game for smart bike trainers. I figured it could be fun to have a low requirements, super simple game instead of more bloated main stream apps that require pricy subscriptions.<p>It has limited functionality right now but lets players generate unlimited routes based on target distance, elevation and route profile, and very soon a GPX file import.

value: Show HN: Veloland – 2D Indoor Cycling Game

author: k-smo


value: abossy

value: Show HN: Promptorium, a Versioning System for LLM Prompts

author: abossy


value: pugdogdev

value:
Hey everyone,
After my first macOS app launch DockFlow, a few months ago,
And the great support I got from this form,
I am glad to announce my new product, ExtraDock!
ExtraDock lets macOS users create multiple docks and place them wherever they want. It was designed to solve the struggle of having a single dock to serve a multi-monitor setup.
Docks are fully customizable - colors, blur, opacity, border, etc. You can also add custom Widgets such as Spacers, Dividers, Clocks, and even cool widgets such as IP Address (always to show your external IP, great for VPN), or Stripe Dashboard Widget to show your gains :D
ExtraDock 4.0 also marks a very special release for me. It also includes the full integration with my other macOS dock app DockFlow. Having both apps work together (as fully separate apps) was very challenging, and very rewarding to pull off!
ExtraDock 4.0 Launch is LIVE right now on ProductHunt , so feel free to check it out and support me
https://lnkflow.io/u/visit/producth
ExtraDock was acquired by me a few months ago from a great fellow indie hacker, and I did a full refactor on the code and infrastructure.
I really enjoy this app and plan to add many features in the future.
You can check out the app on:
https://lnkflow.io/u/visit/extradock
Thank you

value: Show HN: ExtraDock 4.0 – Create unlimited Docks on macOS

author: pugdogdev


value: pfista

value: Looking for feedback on a new tool I just built to make managing webhooks during development easier (and hopefully fun!)<p>Roast me HN

value: Show HN: Webhook Rodeo

author: pfista

title: Show HN: Webhook Rodeo


value:
We built InsForge because we wanted to use pure prompts to build a production-grade app faster. In practice, AI isn’t reliable enough when generating code or configuring backend pieces like schema, RLS, auth, or functions. Postgres MCP and Supabase MCP are a good starting point, but they felt more like API wrappers for agents than something designed to guide AI safely through backend tasks.
So we built our own MCP server on top of Postgres and added a set of context-engineering tools to make prompt-driven workflows more predictable. It gradually turned into a Postgres-based BaaS.
Key features:
1. Authentication with prebuilt UI components
2. Postgres database with typed SDK
3. Serverless functions with a secret manager
4. S3-compatible file storage
5. AI model integration with a unified inference API and simple GUI
6. MCP server with context-engineering endpoints (`fetch-docs`, `get-backend-metadata`, `get-table-schema`, etc.)
We're still early (4 months in). Some parts are rough, but we’re shipping daily and improving quickly :)
[1] Launch blog: https://insforge.dev/blog/insforge-launch
[2] Open-source repo (self-hosting):
https://github.com/InsForge/InsForge
[3] Benchmark: https://github.com/InsForge/mcpmark
[4] Website (cloud hosting): https://insforge.dev/
[5] Our article on context engineering: https://insforge.dev/blog/why-context-is-everything-in-ai-co...
[6] Public roadmap: https://feedback.insforge.dev/roadmap

value: Show HN: InsForge – A Postgres BaaS built for prompt-driven development


value: ticktockten

value:
I've been working on Fast LiteLLM - a Rust acceleration layer for the popular LiteLLM library - and I had some interesting learnings that might resonate with other developers trying to squeeze performance out of existing systems.
My assumption was that LiteLLM, being a Python library, would have plenty of low-hanging fruit for optimization. I set out to create a Rust layer using PyO3 to accelerate the performance-critical parts: token counting, routing, rate limiting, and connection pooling.
The Approach
- Built Rust implementations for token counting using tiktoken-rs
- Added lock-free data structures with DashMap for concurrent operations
- Implemented async-friendly rate limiting
- Created monkeypatch shims to replace Python functions transparently
- Added comprehensive feature flags for safe, gradual rollouts
- Developed performance monitoring to track improvements in real-time
After building out all the Rust acceleration, I ran my comprehensive benchmark comparing baseline LiteLLM vs. the shimmed version:
Function             Baseline Time   Shimmed Time    Speedup    Improvement  Status
token_counter        0.000035s     0.000036s     0.99x          -0.6%
count_tokens_batch   0.000001s     0.000001s     1.10x          +9.1%
router               0.001309s     0.001299s     1.01x          +0.7%
rate_limiter         0.000000s     0.000000s     1.85x         +45.9%
connection_pool      0.000000s     0.000000s     1.63x         +38.7%
Turns out LiteLLM is already quite well-optimized! The core token counting was essentially unchanged (0.6% slower, likely within measurement noise), and the most significant gains came from the more complex operations like rate limiting and connection pooling where Rust's concurrent primitives made a real difference.
Key Takeaways
1. Don't assume existing libraries are under-optimized - The maintainers likely know their domain well
2. Focus on algorithmic improvements over reimplementation - Sometimes a better approach beats a faster language
3. Micro-benchmarks can be misleading - Real-world performance impact varies significantly
4. The most gains often come from the complex parts, not the simple operations
5. Even "modest" improvements can matter at scale - 45% improvements in rate limiting are meaningful for high-throughput applications
While the core token counting saw minimal improvement, the rate limiting and connection pooling gains still provide value for high-volume use cases. The infrastructure I built (feature flags, performance monitoring, safe fallbacks) creates a solid foundation for future optimizations.
The project continues as Fast LiteLLM on GitHub for anyone interested in the Rust-Python integration patterns, even if the performance gains were humbling.
Edit: To clarify - the negative performance for token_counter is likely in the noise range of measurement, suggesting that LiteLLM's token counting is already well-optimized. The 45%+ gains in rate limiting and connection pooling still provide value for high-throughput applications.

value: Show HN: Optimizing LiteLLM with Rust – When Expectations Meet Reality

author: ticktockten


value: kocabiyik

value:
I've been working on background removal models for a while (previously released Snap). Focus is a major improvement, especially for hair, fur, and complex edges.
It's fully open source (Apache 2.0) and runs locally. I also run a paid API to sustain development, but the open source model is complete and functional on its own.
Deliberately unfiltered results (you'll see where it fails): https://withoutbg.com/resources/background-removal-results/m...
Quick start:

  pip install withoutbg

Or run the Docker web UI:

  docker run -p 80:80 withoutbg/app:latest

The model used mean gradient error in training, heavily penalizing missed edges. This produces sharper results but occasionally causes false positives in foreground-background classification. Would appreciate technical feedback on this tradeoff.
GitHub: https://github.com/withoutbg/withoutbg
Docs: https://withoutbg.com/documentation/integrations/python-sdk

value: Show HN: WithoutBG Focus – Background removal with sharp edge detection

author: kocabiyik


value: ivanramos

value:
I’ve seen so many founders sharing waitlists lately.
A simple one. Nothing more.
So I built a tool that gives you exactly that.
A basic waitlist. Fast to create. Easy to share.
https://waitinglist.to
Just name → URL → share.
A quick waitlist so you can focus on your product.
Would love feedback from the HN community.

value: Show HN: Waitinglist.to Create Waitlists in Seconds

author: ivanramos


value: OfflineSergio

value:
I loved speechify but had 2 problems :
- its monthly price
- its character limitations.
So I built WithAudio (https://with.audio). I've been working on this for the past 8 months. A one time payment desktop app that lets you listen or listen while following the text highlighting.
Soon I realised me and many users prefer to have the option to do this in their browser. So I built the browser extension. The extension is free but works only if you have the WithAudio app (which is a paid product).
Youtube demo: https://youtu.be/Vn3VwCLuPQU
Chrome Extension: https://chromewebstore.google.com/detail/the-withaudio-web-c...
Extension's source code: https://github.com/withaudio/withaudio-web-companion

value: Show HN: One Time Payment Text Speech in the Browser

author: OfflineSergio


value: SamTinnerholm

value:
Converts your API spec into a polished playground with live code examples. Developers can test endpoints directly in the browser with Python/JS/cURL snippets.
DEMO:   https://coingecko-y.vercel.app/
GITHUB: https://github.com/Playground-Y/Playground-Y

value: Show HN: Turn OpenAPI specs into interactive API playgrounds

author: SamTinnerholm


value: defilan

value:
Hi HN! I built LLMKube, a Kubernetes operator for deploying GPU-accelerated LLMs in production. One command gets you from zero to inference with full observability.
Why this exists: Regulated industries (healthcare, defense, finance) need air-gapped LLM
deployments, but existing tools are either single-node only (Ollama) or lack GPU optimization and
SLO enforcement. LLMKube bridges the gap.
What's working:
- 17x speedup with NVIDIA GPUs (64 tok/s on Llama 3.2 3B vs 4.6 tok/s CPU)
- One command: llmkube deploy llama-3b --gpu (auto CUDA setup, scheduling, layer offloading)
- Production observability: Prometheus + Grafana + DCGM GPU metrics out of the box
- OpenAI-compatible API endpoints
- Terraform configs for GKE GPU clusters with auto-scale to zero
Tech: Kubernetes CRDs, llama.cpp with CUDA, NVIDIA GPU Operator, cost-optimized spot instances
(~$50-150/mo dev workloads).
Status: v0.2.0 production-ready for single-GPU deployments on standard K8s clusters. Multi-GPU and
multi-node model sharding on the roadmap.
Apache 2.0 licensed. Would love feedback from anyone running LLMs in production!
Website: https://llmkube.com
GitHub: https://github.com/Defilan/LLMKube

value: Show HN: LLMKube – Kubernetes for Local LLMs with GPU Acceleration

author: defilan


value: evronm

value:
I don't use business cards, preferring to let people scan a QR code from my phone.  There are, however, 2 issues:
- Other people tend to give me business cards and they end up in an undifferentiated pile
- When people scan my QR code, the info goes into their contact, never to be seen again.
To address this, I created netcards.  It's a dead simple PWA that I vibe coded with Claude.  The workflow is as follows:
- Enter your info and an event name into the "My Card" page and save it.  A QR code appears.
- Set up tags on the tags page
- When people scan the code with their phone's app, it goes right into their contacts black hole, but at least there's an event name there and all your info.
- If you scan app to app, you can select tags, which you can later filter on along with the event name.
- You can then share contacts, generate QR codes for them, or save the vcards for import into your native contacts app.
Obviously, the more people use this, the more useful it becomes, so I figured I'd start by sharing it with HN.
Tech:
- Vanilla JavaScript, PWA with offline support
- IndexedDB for local persistence
- jsQR + qrcodejs for scanning/generation
- Bulma CSS, all dependencies from CDN
- Live at https://netcards.app
GitHub:  https://github.com/evronm/net-cards/
I've tested this on my Android phone only, so I'm particularly interested to hear from iPhone users about their experience.  But in general, I'd like to know if people find this useful and if anyone has any suggestions.

value: Show HN: Netcards – PWA for exchanging contacts at events via QR codes

author: evronm


value:
I built Lime Reader, a minimal site which displays time-sorted top posts from Hacker News, Tildes, Lobsters, Slashdot, Bear, and some science, tech & programming related subreddits.
You can read more about the site by clicking the slogan at the top of my site "your daily compass for the STEAMD web":
https://limereader.com/about
Previously, I have always used Rust or NodeJS for my backend and Postgres for database.
This time, I used Swift for my backend to build a Website for the first time, used SQLite for Database, used only a single third party dependency: Vapor for web server in the Swift app, and am self-hosting it all on an old Mac mini.
I really hate huge bloated sites and also hate adding third-party frameworks unless absolutely needed. Therefore, I have engineered Lime Reader to be as small in size as possible so that it loads instantly. Both PageSpeed Insights and Pingdom rate my site's performance as Excellent.
It's server side rendered, so it works even with JavaScript disabled (though enabling it gives you a few extra features like quick access to archive.org for each link). Kind of works even with CSS disabled.
The site doesn't have any ads (I hate them and have installed ad-blockers everywhere!), no trackers, or analytics. CloudFlare automatically enables Real User Monitoring (RUM) on sites. The very first thing I did was disable this thing.
I am self-hosting the site on an old Mac mini. It's a 2020 Intel model which has a 2018 chip (Intel's 3 GHz 6-core Core i5) and 32gb ram. Qwen model takes about 5.5GB of ram usage and does my headline classification in about 2 seconds each.
The Swift app talks to a locally running Qwen3 8b LLM for classifying whether a headline is political or not. This is done over a REST API by Ollama. This seems to work pretty well and far better than Apple's Foundation Models. Originally, I tried using Apple's Foundation Models for this classification. When it worked, it worked decently well. However, many headlines (and even pretty bland headlines) would somehow trigger its guardrails. I asked Stack Overflow for help on this but as usual, they closed the question for lack of details:
https://stackoverflow.com/questions/79785822/how-to-disable-...
For example, this headline:
> SEC approves Texas Stock Exchange, first new US integrated exchange in decades
Would hits the Apple's guardrails and throw an error saying `refusal: May contain sensitive content`.
Apple does provide a "permissive guardrail mode" as per:
https://developer.apple.com/documentation/foundationmodels/i...
This does end up allowing some texts to work. However, it still failed for some other ones. That's when I gave up on using Apple's foundation models and switched to the Qwen3 8b model which had no such issues. It's pretty sad how the Foundation Models have so much potential but Apple has severely neutered them.
I originally tried the apple foundation models on my newer mac with m4 chip and once I had the issue with their guardrails, I decided to just switch to Qwen model which runs on Intel and used my old Mac mini for it.
An issue I ran into was that my Swift app was intermittently crashing. Root cause were two issues:
1. First one had to do with accessing the SQLite database from multiple threads. Apparently, for multi-threading use, SQLite needed to be initialized with a `SQLITE_OPEN_FULLMUTEX` flag.
2. Second one was a "Bad file descriptor" error from the macOS operating system itself. Had to do with a possible bug in Process.run() which would cause it to crash after some time:
https://github.com/swiftlang/swift/issues/57827
Was able to fix it using the above workaround/solution of "fileHandleForReading.close()".
Lets see how long the site stays alive now without crashing :)
Feel free to ask questions.

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To get all this data first I tried using Google's Custom Search JSON API but it was too expensive that way, later I found a Kaggle dataset that has info about 110K games -including number of positive and negative reviews- so I used that instead. That amount should be almost half all the games Steam has, (according to an article on Backlinko, Steam's US library "contains 239,558 titles across all categories -including DLC, soundtracks, mods, etc.-"). SteamDB estimates that there must be around ~118,000 full games on Steam so far.
In the process of scrapping I discovered that a few hundred of the games that used to have zero reviews don't exist anymore (or at least, not on Steam), I also discovered there are a handful of companies generating dozens of those hidden-objects games using generative AI for their images, a bit shady if you ask me. I also discovered 24 that are selling for $50 or more, I created a URL just for that in case you are curious: https://www.gameswithnoreviews.com/?show_expensive_games_onl...
To confirm that the reviews count is still zero (since the data was scraped) and to fetch the trailer videos' URLs among other info I did scrape the Steam store page of each game (yeah I'm hotlinking the videos but I don't think Akamai/Steam minds too much). All NSFW games have been pruned.
Be aware you can filter by tag and by price, also be aware Steam allows you to ask for a refund as long as you have less than 2 hours playing it (but don't ask for refund if you had fun or completed the game, that's not nice)
Any feedback or questions I am more than happy to answer.

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