value: mosbyllc

value:
I built AIMovieQuotes ( https://www.aimoviequotes.com/ ).
It’s a tool to find meaningful quotes from movies by searching with a movie title and a theme (like “love,” “betrayal,” or “courage”).
The problem it solves: I often wanted to find a specific quote from a movie that captured a certain feeling, but couldn’t remember the exact words. Traditional keyword searches on existing quote databases are too literal. If you search for “love quote from Inception,” you might get nothing, even if the movie has lines deeply related to the concept of love.
How it works (the technical side): Instead of relying on keyword matching, the tool uses an embedding model to convert movie dialogues and the user’s query into high-dimensional vectors. It then performs a semantic similarity search to find the most conceptually relevant lines, even if they don’t contain the exact keyword. The front end is a simple static site built with Next.js, and the search is handled by a serverless function calling a vector database.
Why I built it: This was a weekend project to experiment with applying semantic search to a concrete, everyday problem outside of the typical enterprise or coding contexts (like documentation search). It demonstrates how AI can understand the meaning behind a request rather than just matching words.
I’d be interested in your feedback, especially on:
The accuracy of the quote matches.
Ideas for other non-traditional datasets where semantic search could be useful.
The overall user experience.
Try it out here: https://www.aimoviequotes.com

value: Show HN: AIMovieQuotes – Find movie quotes by theme using semantic search

author: mosbyllc


value: lnovitz

value: Show HN: I missed a job interview because my spreadsheet failed, so I built this

author: lnovitz


value:
I architected a GitHub streak notification service that scales to 10,000+ users while staying on free tiers. Here's the infrastructure design and cost optimization strategy.
Production: https://streakyy.vercel.app
GitHub: https://github.com/0xReLogic/Streaky
Architecture: Open source, MIT license
=== Architecture Overview ===
Challenge: Build a daily cron system that processes 10k+ users in parallel, sends Discord/Telegram notifications, stays within Cloudflare free tier limits, maintains 99.9% uptime, and costs $0/month.
Solution: Distributed queue system with Service Bindings + Rust proxy for IP isolation
=== Infrastructure Design ===
1. Distributed Processing (Cloudflare Workers)
Problem: Sequential processing doesn't scale. Single Worker has 30s CPU limit.
Solution: Fan-out architecture with Service Bindings
- Main scheduler initializes batch queue
- Dispatches N workers via env.SELF.fetch()
- Each worker = isolated execution context with fresh CPU budget
- Automatic load balancing by Cloudflare
Capacity: 100k requests/day (10k users = 10% utilization)
Performance: 10 users in ~10 seconds, linear scalability
2. Queue Management (Cloudflare D1)
D1 SQLite with atomic operations for distributed queue without external dependencies.
Benefits: Atomic claim, no race conditions, built-in idempotency
Capacity: 50k writes/day (30k used = 60% utilization)
3. IP Isolation Layer (Rust VPS)
Problem: Cloudflare Workers share IP pools → rate limiting (429 errors)
Solution: Lightweight Rust proxy on Koyeb
- Axum framework
- AES-256-GCM encryption
- Stateless, zero-trust architecture
- Cold start ~10s, warm ~3.6s
- 100% success rate
Cost: Koyeb free tier (512MB RAM) - $0/month
4. Data Layer (Cloudflare D1)
Schema: users, notifications, cron_queue
Capacity: 5GB storage (10MB used = 0.2%)
=== Cost Analysis ===
Current (10k users): $0/month
- Cloudflare Workers: 10k/100k req/day
- D1: 30k/50k writes/day
- Koyeb: ~1GB/100GB bandwidth
- Vercel: ~5GB/100GB bandwidth
50k users: $10/month ($0.0002/user)
- D1: $5/month, Koyeb: $5/month
100k users: $25/month ($0.00025/user)
- Workers: $5, D1: $10, Koyeb: $10
Total Cost: $0/month for 10k users
Happy to discuss infrastructure decisions, scaling strategies, or cost optimization techniques.

value: Show HN: Architecting for 10k users on Cloudflare's free tier


value: Yaramsa-Gautham

value:
I built Videoyards, a browser-based screen recording and editing tool made for indie hackers and SaaS founders who want to create clean, professional demo videos without wasting time switching tools.
It works directly via a Chrome extension, no downloads, no setup. You can record your screen, camera, and mic, then instantly edit with auto zooms, cursor highlights, and silence removal right in your browser & Exports are available in HD or 4K 60FPS.
The main benefit is speed. you can record, polish, and share a demo in minutes instead of hours. It’s built to help you show your product clearly, make your demos look professional, and save time so you can focus on building instead of editing.
Free plan includes 1-minute HD recordings with watermark. Early supporters can grab a $39.99 lifetime deal for unlimited 4K recordings, camera/mic support, and lifetime updates. Currently i had 200+ users using it and got an rating of 5.0. Still in the beta version and trying to make it better.
Here are the results after 6-weeks (1&half month ) since launch:- 7000+ visitors, 250+ users signups, 150+ videos are exported, 13 total paid users, $705 in total revenue, 112 install on my chrome extension, 5-Five star review on my chrome extension, My extension got featured by chrome
Would love your feedback on the recording speed, editing flow, and overall UX compared to Loom or Screen Studio.

value: Show HN: Videoyards – Alternative to Screen Studio for Windows

author: Yaramsa-Gautham


value:
I built MuseBot, a multi-platform chatbot that integrates with LLM APIs to provide AI-powered responses.
It supports platforms like Telegram, Discord, Slack, Lark (Feishu), DingTalk, WeCom (企业微信), QQ, and WeChat, so you can talk to your favorite model anywhere.
MuseBot connects seamlessly with OpenAI, DeepSeek, Gemini, and OpenRouter models to make conversations feel natural, dynamic, and responsive.
Key Features
AI Responses – Intelligent chatbot replies using LLM APIs.
Streaming Output – Real-time responses that feel conversational.
Easy Deployment – Run locally or on any cloud server in just a few steps.
Image Understanding – Send an image, and the bot can interpret and respond.
Voice Support – Communicate using voice messages.
Function Calling – Supports MCP-style function calls for extending capabilities.
RAG Support – Enhances context understanding with retrieval-augmented generation.
Admin Platform – Web-based platform to manage bots and configurations.
Service Registration – Automatically register bot instances to a service registry.
Metrics and Monitoring – Built-in Prometheus metrics for observability.
MuseBot is built entirely in Golang, designed for performance, modularity, and easy extensibility.
I’d love to hear feedback from developers working with chatbots, LLM integrations, or Go-based infrastructure — especially ideas to improve scalability and real-time performance.

value: Show HN: MuseBot–An AI Chatbot for Telegram, Discord, Slack, Lark, QQ, and More


value: Show HN: Email Marketing Platform Built on a $1 iCloud Account


value: baquero

value: I wrote a terraform/opentofu module which makes the IP ranges of Azure cloud easy accessible. The IP ranges are updates every night. What do you think?

value: Show HN: Azure IP ranges Terraform module

author: baquero


value: waynerd

value:
I've spent 30 years making games as both a hobby and profession, working with Unity, Unreal, GameMaker, RPG Maker, Ren'Py, Godot, and many others.
A few years ago, I attended a game dev meetup and met dozens of people with incredible passion for making games – but they were struggling because they lacked technical knowledge. That's when I decided to build a tool that anyone could use to create games.
I started developing this as a side project, eventually raised ~$100K through crowdfunding in Korea, then secured ~$200K in angel investment. I assembled a team, and we've been building this together ever since. We're officially launching in November, and we'll also be releasing it on Steam.
What makes this different:
The editor has an incredibly simple structure and UX. I'm also deeply passionate about AI, and I've designed this engine to integrate AI seamlessly. Post-launch, I plan to add prompt-based game generation (think Google AI Studio, Vercel v0, or Lovable, but for games) – allowing anyone to create structured game content just by describing it.
Our mission is "democratizing creativity." We want to empower everyone to express their ideas through games.
Current focus: Visual novels, point-and-click adventures, and 2D animations. But we're also building in a physics engine for more dynamic gameplay possibilities – and it's actually pretty solid.
We're offering early bird pricing until November launch – if you're interested, grabbing it now would really help us build momentum.
We're a small team based in South Korea (yes, the land of K-pop, Squid Game, and KPop Demon Hunters... okay that last one isn't Korean, but you get the vibe ).
Would love to hear your thoughts and feedback!

value: Show HN: A Visual No-Code Game Engine – 50x Easier Than Unity

author: waynerd


value: GuiShou

value:
Hi HN,

    I built DreamOmni to turn text prompts into brand-ready visuals for small marketing teams and indie founders. Describe what you need and get several polished options in seconds.

    Core features:
    - Brand kits to lock fonts and colors
    - Batch generation for campaign assets
    - Version history and quick exports

    I’d love feedback on usability and pricing. Thanks for taking a look!

value: Show HN: DreamOmni – Turn text prompts into brand-ready visuals in seconds

author: GuiShou


value: Viaya

value:
Hey HN
I’ve been experimenting with different image generation tools for months — but I kept running into the same problems: slow generation, repeated outputs, and limited artistic control.
That’s why I built MAI-Image-1, Microsoft’s latest AI image generation model designed for creators, designers, and developers who need fast, realistic results without sacrificing flexibility.
What makes MAI-Image-1 different:
Ultra-realistic rendering — it accurately captures light, texture, and natural shadows.
Lightning-fast generation — create detailed images in seconds.
No style lock-in — experiment freely without repeating patterns.
Seamless integration — works smoothly with other editing tools.
Real-time iteration — perfect for rapid concepting and design workflows.
Typical use cases include concept art, product design, advertising visuals, and any scenario where visual quality and speed both matter.
We’ve focused on performance + creative control, so the output feels closer to what you’d expect from a professional rendering engine than a generic AI model.
Try it here: https://www.maiimage1.com
 (example link, replace with your real URL)
I’d love your feedback:
What’s your impression of the image quality and speed?
What features would make it even more useful for your workflow?
Any integrations or control layers you’d want to see?
Thanks for reading — and I’d be thrilled if you give it a spin

value: Show HN: MAI-Image-1 – Ultra-realistic AI image generator with zero style limits

author: Viaya


value: benporterfield

value:
watch-claude-think is a CLI that monitors Claude Code and displays Claude's internal reasoning across all of your Claude Code instances in a specific directory. It works by watching one of your ~/.claude/projects/ folder for changes - no web requests and no token usage required.
Why? I was enjoying reading Claude's reasoning as it works through problems, but Claude Code only lets you see the thinking at certain points and it's impossible to keep track across muliple Claude Code instances. I created a quick CLI that let me read the thinking as it happened and immediately found it to be suprisingly useful (and fun):
* I can catch it making silly assumptions and interject before it goes off the rails
* It's been a great way to learn how to improve prompting - it will be quite obvious when Claude has the context it needs and when it does not
* Claude will think things that it does not output and sometimes those things are worth reading
* Watching Claude work through problems often gives me inspiration or ideas about architecure, dependencies, etc.
I've actually might be spending more time watching watch-claude-think than the actual Claude output! I now constantly nudge my sessions during large code changes or complex debugging issues because of what I read.
Claude helped a ton by wading through the minified Claude Code CLI and validating (or, often invalidating) my assumptions about how it stored message data. This all started as an exercise in getting to know Claude better - I wanted to try creating a project where all the code was "written" by Claude - but it ended up with a tool I keep using, maybe someone else here will find it useful too.

value: Show HN: Watch-Claude-think – a CLI for watching Claude Code's thoughts

author: benporterfield


value: Show HN: I made a website to track my own subscriptions


value: mxek

value:
Hi HN!
We got frustrated with the fragmented experience of exploring & creating across our file manager, the web and document apps.  Lots of manual searching, opening windows & tabs, scrolling, and ultimately copying & pasting into a document editor.
Surf is a desktop app meant for simultaneous research and thinking to minimize the grunt work. It’s made of two parts:
1) A multi-media library where you can save and organize files and webpages into collections called Notebooks.
2) A LLM-powered smart document which you can auto-generate using the context from any stored page, tab or entire notebook. This document contains deep links back to the source material — like a page of a PDF or timestamp in a YouTube video. Unlike Deep Research products (or NotebookLMs chat) the entire thing is editable. The user also stays in the loop.
With a technology like AI, context / data is proving to be king. We think it should stay under the user’s control, with minimal lock in: where you can own & export, and plug & play with different models. That’s why Surf is:
- Open Source on GitHub
- Open (& Local Data): the data saved in Surf is stored on your local machine in open and accessible formats and mostly works offline.
- Open Model Choice: you can choose which models you use with Surf, and can add custom & Local LLMs
Early users include students & researchers who are learning and doing thematic research using Surf.
Github repo: https://github.com/deta/surf/
Website: https://deta.surf/

value: Show HN: Deta Surf – An open source and local-first AI notebook

author: mxek


value: I heard the host on some radio phone in say "but religion can be used to justify anything", so I made this little site to test that out. You can enter any serious (or not serious) claim and see how cherry picking from the Bible can support or oppose your claim

value: Show HN: Bible Both Ways – See how the Bible can justify any moral claim


value: arivero

value: Show HN: A circular calculator and some others

author: arivero


value: hauxir

value: Show HN: Android TV screensaver that plays live YouTube streams

author: hauxir


value: kvinogradov

value:
Over five years ago, I started publishing the top 20 trending open-source startups every quarter, based on their relative GitHub star growth — the ROSS Index. It has become quite handy for 60K+ developers, founders, and other OSS fans who have visited it to date.
To make it even more convenient, we have just open-sourced its full dataset for 22 past quarters, including the fresh list for Q3 2025, so everyone can play with it — for instance, analyze what happened with startups from the first quarters.
Given that in the very first index issue (Q2 2020), 5 out of 20 early-stage startups (n8n, Hugging Face, Streamlit, Cortex Labs, Framer) eventually reached $0.5B+ valuation, it seems like an interesting area for research.

value: Show HN: Fastest-growing OSS startups for every quarter since Q2 2020

author: kvinogradov


value: zkanda

value:
Hello HN!
I made Comfy Nodekit, a small library to make it easier to build and serialize ComfyUI workflows directly in Python.
If you’ve ever tried to hand-craft large ComfyUI graphs or maintain JSON workflows by hand, you probably know how messy it gets once you reach a few dozen nodes. We needed a better way to generate and modify graphs programmatically, so we built this.
Comfy Nodekit lets you create graphs with typed node factories, then export them back to the exact JSON format ComfyUI expects. It also introspects your running ComfyUI server to generate Python bindings for your custom nodes automatically, so you don’t lose compatibility when your setup changes.
We’re using this internally at Katalist to generate complex workflows with hundreds of nodes on the fly, things that would be impossible to manage and version.
Highlights
* Works with custom nodes (via /object_info)
* Type-safe graph composition + JSON export
* MIT license
* No runtime overhead - just Python + JSON
Why not just use ComfyScript or raw JSON?
Because we wanted a Python-first, typed model that stays in sync with our ComfyUI server and is focused purely on composition, not on adding another runtime layer.
Happy to answer questions what kinds of workflows we're building for our image generation task.

value: Show HN: Comfy Nodekit – build/serialize ComfyUI workflows in Python

author: zkanda


value: snupix

value:
Our team at Clym built an open-source Accessibility Testing tool to help developers and auditors identify and fix web accessibility issues, combining automated and manual testing in one place.
Our tool integrates the open-source axe-core[1] library for automated testing against WCAG 2.0, 2.1, 2.2 and EN 301 549 standards. For issues that automation can't reliably detect, it includes manual review workflows that guide testers through contextual checks (like keyboard navigation and visual contrast validation).
It can also generate Accessibility Conformance Reports (ACRs) in multiple formats and allows teams to define their own rules, mappings and remediation steps through a simple configuration layer.
You can view and contribute to the project on our github[2] or download the app for Mac, Windows and Linux on our website[3].
We'd love feedback from developers or accessibility testers — especially around how you combine automated and manual checks today, and what integrations would make this more useful.
[1] https://github.com/dequelabs/axe-core
[2] https://github.com/clymio/accessibility-tools
[3] https://www.clym.io/products/accessibility-tools

value: Show HN: Open-Source Accessibility Testing for the Web

author: snupix


value: bkrisa

value: Show HN: I made a landing page audit checklist

author: bkrisa


value: LHDNS

value:
LHDNS (Ledger-based Hashed Decentralized Naming System) is a next-generation alternative to DNS — designed to provide censorship resistance, privacy, and cryptographic accountability for name resolution.
It replaces central trust roots with an ephemeral, ledger-backed system that uses rotating hash-tokens, decentralized gossip propagation, and short-lived identifiers instead of static records.
Every query is unlinkable, every service is verifiable, and no single entity controls the namespace.
Key Features:
- Ledger-based resolution with cryptographic proofs
- Ephemeral state (no permanent name mappings)
- End-to-end privacy via onion routing and cover traffic
- Sybil resistance through staking + adaptive PoW
- Compatibility layer with existing DNS (via gateways)
Whitepaper, annexes, and technical modules:
→ https://github.com/twincodesworld/LHDNS
Goal: to make global name resolution private, verifiable, and censorship-resistant — for everyone.
Feedback and collaboration welcome.

value: Show HN: Lhdns – A Ledger-Based, Privacy-Preserving Decentralized Naming System

author: LHDNS


value: jbelthoff

value:
I rebuilt the classic Cactus Kev poker hand evaluator from scratch in modern C# (.NET 8), focusing on algorithmic clarity and performance instead of lookup tables.
• Pure C#, no unsafe code
• Evaluates ~115 million 7-card hands per second
• Uses Span<T> and BenchmarkDotNet
• Detailed benchmarks and architecture in the README
GitHub: https://github.com/JBelthoff/poker.net
Live demo: https://poker-calculator.johnbelthoff.com
Full background: https://www.linkedin.com/pulse/why-i-rewrote-classic-poker-e...

value: Show HN: Poker hand evaluator in pure C# (.NET 8) – 115M evals/SEC

author: jbelthoff


value: wolfejam

value:
I built this Chrome extension to solve my own problem: I was constantly
  testing things in StackBlitz, Monaco playgrounds, and GitHub repos, then
  needing to paste that code into Claude or Cursor to ask questions about
  it. Manually copying files one by one was annoying.

  The extension extracts the entire codebase from whatever environment
  you're in (GitHub, Monaco editor, StackBlitz, GitLab, CodeSandbox, Replit,
   etc.) and copies it to your clipboard as clean .txt. One click, done.

  Chrome Web Store:
  https://chromewebstore.google.com/detail/lnecebepmpjpilldfmndnaofbfjkjlkm

  GitHub (MIT): https://github.com/Wolfe-Jam/faf-chrome-extension

  Built with Svelte 5 + TypeScript. Google approved it. Currently has 9
  downloads (honest number—just launched). But it genuinely works well,
  which is why I use it daily.

  The .txt format is intentionally simple—human-readable, AI-compatible, and
   acts as a pre-cursor to our .faf format (structured AI context). If you
  work with AI coding assistants and ever think "I wish I could just grab
  all this code at once," this is that tool.

  Happy to answer questions about the implementation, platform detection
  logic, or anything else..

value: Show HN: Chrome extension, grab any codebase as .txt (GitHub, Monaco, StackBlitz

author: wolfejam


value: karihass

value:
We built Nostr Web, a new way to publish and host websites that live entirely on the Nostr network instead of centralized servers.
Each website is a collection of signed, verifiable Nostr events distributed across relays—so it can’t be taken down, censored, or lost.
It includes:
• DNS TXT records for domain-based discovery (_nweb.domain.com)
• CLI publisher tool for versioned deployments (nw-publisher)
• Browser extension (nw-extension) for native browsing experience
• Relay v1.3.5 support for Nostr Web event kinds
Try the live demo: https://nweb.shugur.com
Repos: https://github.com/Shugur-Network/relay | https://github.com/Shugur-Network/nw-nips | https://github.com/Shugur-Network/nw-publisher | https://github.com/Shugur-Network/nw-extention
Would love feedback from the HN community—on protocol design, relay performance, or UX ideas for improving decentralized web publishing.

value: Show HN: Nostr Web – decentralized website hosting on Nostr

author: karihass


value: basedsalahuddin

value:
Hey HN!<p>I built EZMind AI - an AI-powered study platform that helps students learn more efficiently.<p>*The Problem:*
Students spend hours reading textbooks and lecture notes, but retention is low. Traditional study methods (highlighting, re-reading) are passive and ineffective.<p>*The Solution:*
EZMind AI transforms any study material into:
• Concise AI summaries
• Auto-generated quizzes with instant feedback
• Smart flashcards
• Podcast-style audio (great for commuting)
• Interactive AI tutor for Q&A
• Automatic transcription of recorded lectures

value: Show HN: EZMind AI – Turn study materials into quizzes, flashcards, and podcasts

author: basedsalahuddin


value:
Hey everyone!
If you’re looking for something self-hostable to organize life and work, check out tududi. It’s an open-source task and project manager where you can keep tasks, notes, projects, and areas together — all taggable and easy to organize. Runs in Docker, lightweight, and keeps your data local.
I am excited to announce tududi v0.84 with the most requested feature yet.
# What's New
Project Sharing
The feature you've been asking for is finally here! You can now share your projects with team members and collaborate in real-time.
Perfect for:
- Coordinating team tasks and deliverables
- Managing group projects with friends or colleagues
- Keeping everyone aligned on shared goals
- Collaborative planning and execution
- Adding users and managing roles through a dedicated page
Simply add collaborators to your project and they'll see all tasks, updates, and progress in real-time.
Improvements and fixes
- More clean, more intuitive interface improving with every release
- Refactored backend services for better performance
- Fixed Project view persisting issue on browser
- Fixed an issue with completing tasks on Upcoming view
I'd love to hear your feedback on project sharing! Give it a try and let me know what you think.
Get started: https://github.com/chrisvel/tududi | Official website: https://tududi.com
Happy organizing!
Chris

value: Show HN: Tududi v0.84 – self-hostable application to organize your life and work


value: bl-ue

value:
Customize Claude Code’s thinking verbs, animations, and system prompt using tweakcc.  Trimmed the system prompt from 15.7k (8%) to 6.1k tokens (3%).
Added modified system prompt to https://github.com/bl-ue/tweakcc-system-prompts.

value: Show HN: Customize Claude Code's System Prompt with Tweakcc

author: bl-ue


value: aaronSong

value:
Clink connects your existing AI coding agents (Claude Code, Codex CLI, Gemini CLI, Z.ai GLM) to build, preview, and deploy apps in isolated containers. No extra tokens needed.
Why? We love Claude Code but needed preview + deploy. Didn't want to pay Lovable $25 when our $20 Claude subscription already does the coding.
What it does:
1) BYO Subscription: Use what you already pay for (Claude $20 = 10x Lovable usage)
2) Multi-agent: Different agents for different strengths - Claude for versatility, Codex for complex tasks, GLM for speed
3) Instant Deploy: Prompt to build to live URL. Free hosting included.
DEV Mode for Beta
Multi-stack support (Node, Python, Go, Rust) /
Import and upgrade existing repos /
Deploy containers to public URLs instantly
We're preparing this
Fork-to-Deploy: Fork any open source project from GitHub, customize it with AI agents, and deploy as your own. Think: fork Slack alternative, customize for your team, deploy instantly.
Try it: https://clink.new
OSS origin: https://github.com/opactorai/Claudable (~2.9k stars)
We ship fast and read every comment. Would love your feedback! (resubmitting)

value: Show HN: Clink – Use your existing AI subscriptions to build and deploy apps

author: aaronSong


value: jborland

value:
Hi HN, we’re Jamie and Matti, co-founders of Twigg.
During our master’s we continually found the same pain points cropping up when using LLMs. The linear nature of typical LLMs interfaces - like ChatGPT and Claude - made it really easy to get lost without any easy way to visualise or navigate your project.
Worst of all, none of them are well suited for long term projects. We found ourselves spending days using the same chat, only for it to eventually break. Transferring context from one chat to another is also cumbersome. We decided to build something more intuitive to the ways humans think.
We started with two simple ideas. Enabling chat branching for exploring tangents, and an interactive tree diagram to allow for easy visualisation and navigation of your project.
Twigg has developed into an interface for context management -  like “Git for LLMs”. We believe the input to a model - or the context - is fundamental to its performance.  To extract the maximum potential of an LLM, we believe the users need complete control over exactly what context is provided to the model, which you can do using simple features like cut, copy and delete to manipulate your tree.
Through Twigg, you can access a variety of LLMs from all the major providers, like ChatGPT, Gemini, Claude, and Grok.  Aside from a standard tiered subscription model (free, plus, pro), we also offer a Bring Your Own Key (BYOK) service, where you can plug and play with your own API keys.
Our target audience are technical users who use LLMs for large projects on a regular basis. If this sounds like you, please try out Twigg, you can sign up for free at https://twigg.ai/. We would love to get your feedback!

value: Show HN: Git for LLMs – A context management interface

author: jborland


value: rohil-nimo

value: Show HN: Everyone is fighting over browsers, so we built something beyond

author: rohil-nimo


value: etherio

value: Show HN: Automated monitoring and orchestration of coding agents

author: etherio


value: ninapanickssery

value: Show HN: I built an SVG-generation tool

author: ninapanickssery

title: Show HN: I built an SVG-generation tool


value: mrcslws

value:
Here's a blog post about how it works: "Web apps over SSH can be surprisingly good"
https://probablymarcus.com/blocks/2025/10/10/web-apps-over-s...

value: Show HN: A browser for Mac that connects to private web apps over SSH

author: mrcslws


value:
Many founders waste months building something only to discover no one wants it. We help you validate ideas first so you can find out in weeks, what others find out in months: "is there any actual demand for my idea?".
Is your idea worth building? Let’s prove it.
The Validation Sprint Process:
① Landing Page
We design and launch a polished one-page site that clearly communicates your idea, building trust fast through strong visuals, benefits, and calls-to-action. Give your idea the best chance possible.
② Wait List
Interested users can sign up, giving you a tangible signal of demand. Beyond numbers, it’s a pool of potential early adopters or beta testers to engage with directly.
③ Deep User Insights
A waitlist shows interest, but not commitment. We gather deeper insights through short surveys and optional interviews, also helping you tailor your build for your potential user base. This way, if you decide to build, you build with confidence and clarity.
④ Targeted Promotion
We help you share your idea in the right places — from niche communities to launch platforms like Product Hunt. The goal: meaningful feedback from potential users, not vanity traffic.
Flexible Involvement
Choose the level of involvement that fits you — whether you want a quick setup handled by us, or a full sprint where we work together closely. We’ll tailor pricing around your level of involvement.
Interested? Get in touch today!

value: Show HN: Don't Build Things No One Wants We Test Ideas for Founders


value: mattewong

value: Show HN: ZSV – A fast, SIMD-based CSV parser and CLI toolkit

author: mattewong


value: tcogz

value:
Hi HN
I built BGBuster (https://bgbuster.com), a background removal API made for developers who were tired of paying €1+ per image.
Why I built it
Existing services are expensive and complicated. I wanted something simple, transparent, and affordable.
What this does
- Upload a file or pass a URL → get a transparent PNG or WebP
- Pay once for credits (credits never expire)
- Simple API: single POST, returns URL or raw image
- Dashboard shows usage, success rate, and recent API calls

value: Show HN: BGBuster ultra-low-cost Background Removal API built for devs

author: tcogz


value: solosquad

value: Show HN: AI that tries to hack your web app

author: solosquad


value: DJSnackySnack

value:
Hello HN - I’m a lover of word games and word play (I even won the New Yorker caption contest.)
My new game combines both: https://puzzle-brothers.boondoggle.studio/puzzles/linchpin
How it works:
You’re given 4 crossword style clues. Each answer overlaps two phrases with a shared "linchpin" word in the middle.
Example clue: Where do plants go to cut loose?
Answer: “Green House” + “House **Party” → **Green House Party.
Build four answers from a shared word bank, but watch out for red herrings.
I’d love to know what you think!

value: Show HN: I made a game that's like Connections x Mini Crossword

author: DJSnackySnack


value: enginyoyen

value:
Based on Richard Cook's research on complex system failures, I wrote a book exploring why disasters like Knight Capital's $440M loss happen when every component functions correctly.
Free sample chapters: https://leanpub.com/how-software-fails
The book explores patterns behind complex system failures—from cosmic rays flipping bits in voting machines to the Therac-25 radiation overdoses. Key insight: traditional  "root cause analysis" fundamentally misunderstands how these systems actually fail—they emerge from interactions between components that were individually functioning correctly.
Feel free to grab the sample chapter and give it a try.

value: Show HN: How Software Fails-A book about complex system failures(sample chapter)

author: enginyoyen


value:
Hi HN!
I'm the founder of InfoBeatLive. I built this platform to help founders avoid early startup failure.
InfoBeatLive acts as an AI-powered operating system for startups — helping you with strategies in marketing, analyze product-market fit, and track performance with real-time insights.
I created this because I noticed most startups fail not because of the idea, but because of a lack of clear strategy and validation. I’d love your feedback, especially from early-stage founders and builders.
https://infobeatlive.com
Thanks for checking it out!

value: Show HN: I Made InfoBeatLive – The Operating System for Startup Success


value:
I'm making a completely offline, minimal, self-organizing journal (using lightweight, self-learning local AI models). That feels just like texting yourself.
Motivation: To avoid the organizational overhead (e.g., what page to use, where to place something), I'd often just text/slack the logs/notes to myself. However, this made it difficult to find the information later.
Idea: A simple text box. You can throw any information into it, and the app will make sense of it so you can find and use it later.
Offline and open-source: Because I wouldn't trust my work logs in anyone else's hands.
It's also extremely minimal on the surface. But when required, it has powerful features built in.
Happy to hear your feedback!

value: Show HN: An offline self-organising journal for work logging [OpenSrc]


value: Hi everyone! I built a 401(k) Traditional vs. Roth calculator in Cursor to give a quick estimate of how your investments might grow and which option could work better for you. I’d love your thoughts and suggestions on how to improve it and make it easier for more people to use.

value: Show HN: 401K Traditional vs. Roth Calculator


value: noamteyssier

value:
Was sitting around in meetings yesterday and remembered an old shell script I had to count the number of unique lines in a file. Gave it a shot in rust and with a little bit of (over-engineering)™ I managed to get 25x throughput over the naive approach using coreutils as well as improve over some existing tools.
Some notes on the improvements:
1. using csv (serde) for writing leads to some big gains
2. arena allocation of incoming keys + storing references in the hashmap instead of storing owned values heavily reduced the number of allocations and improves cache efficiency (I'm guessing, I did not measure).
There are some regex functionalities and some table filtering built in as well.
happy hacking

value: Show HN: hist: An overengineered solution to `sort|uniq -c` with 25x throughput

author: noamteyssier


value: michalwarda

value:
Hey all, we just shipped coyote. it's an ai assistant but built different — everything runs async and feels way more natural. You text it, it handles work in the background and you can keep talking to it. No more stop button.
Instead of creating another app we put it in WhatsApp (iMessage coming soon) so you can just text it for free and get the feeling.
The core idea: most ai assistants make you sit there waiting for an answer. coyote's like texting a friend. you ask it to grab something for you, they say "on it," and you just keep chatting while it's out getting it. no awkward silence, no being stuck.
Built it to handle real tasks — emails, calendar stuff, research, whatever. all non-blocking. Everything happens concurrently so you're never left hanging.
We're still early but it's live and working. Happy to answer questions or get feedback.
We've also worked hard to make it snappy, and friendly. Try it out and would love some feedback! Thanks!

value: Show HN: Coyote – Wildly Real-Time AI

author: michalwarda

title: Show HN: Coyote – Wildly Real-Time AI


value: onecommit

value: Hey HN — Emdash is an open-source UI for running multiple coding agents in parallel. It’s provider-agnostic (10+ CLIs). Each agent runs in its own Git worktree; after a run, compare diffs side-by-side and apply only what you want. Data stays local. Linear tickets can be handed off directly to agents.

value: Show HN: Emdash – OS UI for parallel coding agents and Linear tickets

author: onecommit


value: Eldodi

value:
Hi HN!
Two weeks ago at their Dev Days, OpenAI unveiled ChatGPT apps, interactive widgets that render inside ChatGPT using the Apps SDK and MCP. Building them using their template repository was surprisingly painful: every time you make a change on your React widget, you need to rerun the entire build pipeline to get fresh JS and CSS assets. The dev feedback loop was pretty terrible.
That’s why I built a TypeScript starter that gets you up and running in under a minute. Clone, npm install, npm run dev, paste your ngrok URL into ChatGPT, and you're iterating on widgets with Hot Module Reload in the ChatGPT interface, just like building a regular web app. When you're ready to ship, the production build pipeline deploys instantly to Alpic or any other PaaS.
What's included:
- Vite dev server with Hot Module Reload (HMR) piggy-backed on your MCP server Express server
- Skybridge framework: an abstraction layer I built on top of OpenAI's skybridge runtime that maps MCP tool invocations to React widgets, eliminating manual iframe communication and component wiring.
- Production build pipeline: one-click deploy to Alpic.ai (with bundling, hosting, auth, MCP-specific analytics included) or elsewhere
- No lock-in: uses the official MCP SDK, works with OpenAI's examples
Quick start:
git clone https://github.com/alpic-ai/apps-sdk-template
cd apps-sdk-template
pnpm install && pnpm run dev
ngrok http 3000
# Add https://your-url.ngrok-free.app/mcp to ChatGPT Settings → Connectors
Feedback welcome, especially if you hit rough edges or want specific features!
Starter Kit GitHub → https://github.com/alpic-ai/apps-sdk-template
Skybridge Github → https://github.com/alpic-ai/skybridge

value: Show HN: OpenAI ChatGPT App starter DevXP feels like 2010, I built a better one

author: Eldodi


value: vinhnx

value:
VT Code is a Rust CLI/TUI coding agent that works semantically on code (Tree-sitter + ast-grep), routes across multiple LLMs (incl. local via Ollama), and integrates with editors via ACP and external tools via MCP. It focuses on safety (workspace boundaries, per-tool Allow/Prompt/Deny, sandboxed commands/timeouts) and reproducibility (TOML config, caching, summarization).
What’s different:
- AST-aware search/refactors with preview-before-apply
- Provider-agnostic routing with failover and cost/latency-aware caching
- Policy-gated tools and strict workspace boundaries
- Terminal-first ergonomics you can script
Install:

  cargo install vtcode
  # or
  brew install vinhnx/tap/vtcode
  npm install -g vtcode

Quick start:

  export OPENAI_API_KEY=...   # or another provider key
  vtcode
  vtcode ask "Find md5 usages across the repo and propose SHA-256 replacements (show diff)"
  vtcode ask "Search for .unwrap() on Result and suggest safer handling"

Status: research preview (MIT). Feedback welcome on ergonomics, ACP/MCP DX, safety defaults, and real-world AST refactor recipes.

value: Show HN: VT Code – LLM-agnostic coding agent with MCP/ACP and sandboxed tools

author: vinhnx


value: ladybro

value:
Hey HN,
My name is Brett and I'm excited to share ScreenAsk with you today!
ScreenAsk makes it easy to collect screen recordings from your customers by simply sending a link.
At my SaaS company, we spend hours every week teaching customers to record their screen to show us support issues.
They have to sign up for a new tool, download and install it, create the recording, and then upload it somewhere to send it over…
Most of the time spent on support wasn't fixing the issue but rather understanding it.
I built ScreenAsk to solve this exact problem, making it simple to see what your customers see:
- Send over your recording link
- They follow a few easy steps to record their screen
- You instantly see what they’re experiencing
No sign up, no installing extra software, and no uploading to another service just to share.
You can get notified via Email + Slack + Zapier + Webhooks when somebody records, and recordings include transcription + AI summaries for quick scanning.
We also offer a widget that can be embedded in your site and is fully customizable + controllable with javascript.
- Show / hide it when you want
- Change colors and language
- Listen for a recording and populate a form field with the viewing link
- Add metadata like name, email, ID to the recording
- Capture network and console
I’d be grateful if you gave it a spin! You get 10 free recordings per month and a personalized recording link: https://screenask.com
Launch tweet + demos + discussion: https://x.com/balindenberg/status/1981394673173205418

value: Show HN: ScreenAsk – Free Screen Recording Links for Customer Support

author: ladybro


value:
Hi HN! I would like to present my project called TOMMY, which turns ESP32 devices into motion sensors that work through walls and obstacles using Wi-Fi sensing.
TOMMY started as a project for my own use. I was frustrated with motion sensors that didn't detect stationary presence and left dead zones everywhere. Presence sensors existed but were expensive and needed one per room. I explored echo localization first, but microphones listening 24/7 felt too creepy. Then I discovered Wi-Fi sensing - a huge research topic but nothing production-ready yet. It ticked all the boxes: could theoretically detect stationary presence through breathing/micromovements and worked through walls and furniture so devices could be hidden away.
Two years and dozens of research papers later, TOMMY has evolved into software I'm honestly quite proud of. Although it doesn't have stationary presence detection yet (coming Q1 2026) it detects motion really well. It works as a Home Assistant Add-on or Docker container, supports a range of ESP32 devices, and can be flashed through the built-in tool or used alongside existing ESPHome setups.
I released the first version a couple of months ago on Home Assistant's subreddit and got a lot of interest and positive feedback. More than 200 people joined the Discord community and almost 2,000 downloaded it.
Right now TOMMY is in beta, which is completely free for everyone to use. I'm also offering free lifetime licenses to every beta user who joins the Discord channel.
You can read more about the project on https://www.tommysense.com. Please join the Discord channel if you are interested in the project.
A note on open source: There's been a lot of interest in having TOMMY as an open source project, which I fully understand. I'm reluctant to open source before reaching sustainability, as I'd love to work on this full time. However, privacy is verifiable - it's 100% local with no data collection (easily confirmed via packet sniffing or network isolation). Happy to help anyone verify this.

value: Show HN: Tommy – Turn ESP32 devices into through-wall motion sensors


value: digitalDP

value:
I’ve been building an infrastructure platform called smartNOC, aimed at managing server environments cohesively and comprehensively, and I have finally achieved a version 1.0 release. I hope you guys think this is as cool as I think it is.
When ChatGPT was released on November 30, 2022, the realization hit me that somebody is going to start using these tools for evil, and knowing how we typically manage our networks didn't bring much comfort. I thought we would need a complete re-envisioning of how we architect our edge networks. So I started building it. I went full time on the project in March 2023, and began writing code May of '24.
What I have built is a "network in a box" that provides the following:
1. Fully hardened linux instances.
2. 100% auditable lifecycle operations across fleet.
3. One-touch provisioning.
4. An entirely new monitoring method to permit real time notification of issues.
5. Scoped to be a zero-ops, self-managed environment.
6. AwarenessUI, my answer to dashboard sprawl and alert fatigue.
Every instance starts from a trusted base image, provisioned with our custom security-guard software: fred - the first-responding enterprise daemon.
I think can be great for managing cloud repatriation migrations, government contractors and it might be a good cloud offering.
I have posted a brief video to YouTube here: https://youtu.be/cFqHfP-PPvo
I'd love to hear your thoughts on my project.

value: Show HN: smartNOC – network in a box for zero-ops

author: digitalDP


value: keterslater

value:
Hello Hacker News,
I’m a solo indie hacker building in public. Over the last few days I built *TrendRadar*, an AI tool that automatically finds trending posts on X (Twitter) within topics you care about and writes comments in your voice. You choose the tone and sentiment, and the system handles the rest – even controversial angles.
Some highlights:
- *Single‑click authentication:* Connect your X account via the official API. No scraping or grey‑area methods – TrendRadar uses an approved X/Twitter application and is fully compliant with their terms of service (FAQ on the site explains this).
- *Personalised auto‑comments:* You can tweak the level of controversy, review/edit comments before posting, and set custom prompts so the comments match your brand or personality.
- *Real‑time trend detection:* The tool monitors your chosen topics and jumps on trending conversations 24/7 so you don’t miss out.
- *Analytics dashboard:* See impressions, follower growth, engagement rate and more in a single panel.
I launched it on my own account three days ago and saw impressions jump to ~40k and my follower count increase by ~50%. There’s a free Starter plan (3 auto‑comments per day) and an Early‑Bird Pro plan for early adopters.
I’d love feedback from the HN community. You can try it here: *https://trendradar.app**.
(If you do sign up, the promo code `EARLYBIRD` will apply a discount to the paid plan – there are 100 codes available.)
Thanks for checking it out!

value: Show HN: TrendRadar – AI auto-commenter to grow on X

author: keterslater


value: joseatanvil

value:
We’ve been working on IG Email Finder, a web tool that helps marketers, founders, and small teams find verified business emails from Instagram accounts that do not list their contact info.
We just released an update that improves the deep research process. It now identifies more verified business emails from accounts that are otherwise unreachable and connects directly with MillionVerifier to clean and validate every contact before download.
All data sourcing follows GDPR and CCPA guidelines. The tool only uses publicly available information and verified business records to ensure compliance.
The goal is to help people who rely on Instagram for client outreach or partnerships reach verified business contacts instead of guessing addresses or relying on DMs.
Would love feedback from anyone interested in data enrichment, lead research, or compliance-focused contact discovery.

value: Show HN: IG Email Finder – find verified business emails from Instagram

author: joseatanvil


value: we finetuned Google's Gemma 270m (and 1b) small language models specialized in having conversations as non-playable characters (NPC) found in various video games. Our goal is to enhance the experience of interacting in NPSs in games by enabling natural language as means of communication (instead of single-choice dialog options).

value: Show HN: Distil-NPC: a family of models for non-playable characters in games


value: tjgreen

value:
I built pg_textsearch, a Postgres extension that brings proper BM25 ranking to full-text search. It's designed for AI/RAG workloads where search quality directly impacts LLM output.
Postgres native ts_rank lacks corpus-aware signals (no IDF, no TF saturation, no length normalization). This causes mediocre documents to rank above excellent matches, which matters when your LLM depends on retrieval quality.
Quick example:

  CREATE EXTENSION pg_textsearch;
  CREATE INDEX articles_idx ON articles USING bm25(content);
  SELECT title, content <@> to_bm25query('database performance', 'articles_idx') AS score
  FROM articles
  ORDER BY score
  LIMIT 10;

Works seamlessly with pgvector or pgvectorscale for hybrid search. Fully transactional (no sync jobs). Preview release uses in-memory architecture (64MB default per index); disk-based segments coming soon.
I love ParadeDB's pg_search but wanted something available on our managed Postgres. You can try pg_textsearch free on Tiger Cloud: https://console.cloud.timescale.com
Blog: https://www.tigerdata.com/blog/introducing-pg_textsearch-tru...
Docs: https://docs.tigerdata.com/use-timescale/latest/extensions/p...
Feedback welcome, especially from folks building RAG systems or hybrid search applications.

value: Show HN: Pg_textsearch – BM25 Ranking for Postgres

author: tjgreen


value: dreadsword

value:
An honest to god, non-algorithmic reverse chrono list of tech news that passes my signal-to-noise tests, updated hourly.
A lightweight a page design as I've been able to keep; simple, clean, fast. No commercial features or aspirations - this is a passion project, something I've been fooling around with on and off for decades.
There's a "Top" view too with an LLM edited front page & summary, and categorized views for a large number of topics - see the Directory. A few more buried features to explore, but the fundamental use case is pop in, scan, exit - fast and concise.
Your feedback would be appreciated!

value: Show HN: I built a tech news aggregator that works the way my brain does

author: dreadsword


value: incogdev

value: Show HN: Base64 Decode – A fast, privacy-first Base64 decoder in the browser

author: incogdev


value:
(see demo at bottom of gist)
Type your goal then press [ESC]+[;]
ChatGPT explains the command, options, and places the command on your prompt, ready to edit or run.
> $ list images
> thinking...
> List all JPEG files (case-insensitive) recursively.
> $ find . -type f -iname '.jpg' <-- cursor ends here
> $ omg delete the leftover git merge files
> thinking...
> Find and delete leftover Git merge files (typically named '.orig').
> • find . -type f -name '.orig' # preview
> This will permanently delete all '.orig' files. Run without '-delete' to preview files.
> $ find . -type f -name '.orig' -delete <-- cursor
> $ ps | grep node
> thinking...
> Close... 'ps | grep node' works, but often shows less info and may miss some processes depending on your shell/OS. 'ps aux' lists all processes, including the full command line.
> $ ps aux | grep node <-- cursor
If there's a tool that does this, I'd love to know because I wrote this one and i suck at bash.

value: Show HN: Isuckatbash – convert plain wording to zsh commands inline


value: etherio

value: Show HN: Orchestra – an interface to usefully run coding agents in parallel

author: etherio


value: kyrylo

value: Show HN: Emojiwhat – Unicode and TikTok emojis to copy and paste

author: kyrylo


value: neurobloom

value:
Hi HN! Creator here.
I built Story Keeper to solve a problem I kept hitting with AI agents: they remember everything but lose coherence over long conversations.
The Core Idea
Instead of storing chat history and retrieving chunks (RAG approach), Story Keeper maintains a living narrative:
Characters: Who you are (evolving), who the agent is
Arc: Where you started → where you're going
Themes: What matters to you
Context: The thread connecting everything
Think of it as the difference between reading meeting notes vs. being in the relationship.
Technical Approach
~200 lines of Python. Three primitives:
Story State (not message list)
Story Evolution (not appending)
Story-Grounded Response (not retrieval)
Works with any LLM - tested with GPT-4, Claude, Llama 3.1, Mistral.
Why This Works
Traditional memory is about facts. Story Keeper is about continuity.
Example: Health coaching agent
Normal: Generic advice each time
Story Keeper: "This is the pattern we identified last month. You do better with 'good enough' than perfect."
The agent carries forward understanding, not just data.
Implementation
Part of PACT-AX (open source agent collaboration framework). MIT licensed.
Simple integration:
pythonfrom pact_ax.primitives.story_keeper import StoryKeeper
keeper = StoryKeeper(agent_id="my-agent")
response = keeper.process_turn(user_message)
Use Cases I'm Exploring
Long-term coaching/mentorship
Multi-session research assistants
Customer support with relationship continuity
Educational tutors that understand learning journeys
What I'd Love Feedback On
Is this solving a real problem or am I overthinking it?
Performance concerns at scale?
Other approaches people have tried for this?
Use cases I'm missing?
The full technical writeup is in the repo blog folder.
Happy to answer questions!

value: Show HN: Story Keeper – AI agents with narrative continuity instead of memory

author: neurobloom


value: cassettetourist

value:
Hey y'all. First HN post, so...
I built a web DAW using Typescript, Faust, Web Audio Modules, and WASM. (fourtrack.fm)
I spent a year building this, and about 4 months of that doing a from-scratch rewrite.
It features virtual instruments and effects, sampling, re-sampling, audio recording, MIDI input. There is a piano roll for writing rhythms and melodies. There is a chart that allows you to write lyrics and arrange songs, and each part on the chart is tied to its music (e.g. verse, chorus, bridge)
The DAW and all the current instruments and effects are totally free to use. You can save and import projects offline too. Cloud save through google drive works, but it's not yet verified so I wouldn't use it yet.
In the future I may have sample packs, some other effects and instruments for sale as add-ons. No subscriptions, because that is anathema to creative culture.
Basically, in fourtrack you can write songs on the "Chart" with your lyrics, and all the MIDI and audio clips will be associated with that part on the chart.
As a songwriter, I always got annoyed that I was left with a 'notes' section in most DAWs or my email or notepad open next to it to write lyrics while writing a song.
The aim of this software is to make this experience of songwriting, lyrics and music, more integrated.
Furthermore, even though I could have gone the route of a more traditional waveform view multi-track recorder, I wanted to encapsulate the feeling of using a four track tape recorder. Sometimes limits give us freedom, especially in the creative realm.
I hope that this tool reaches people interested in writing songs and trying to focus on the essence of what makes a song memorable - lyrics, melodies, rhythms. There are many superior tools for sound design and full fledged production. This is more along the lines of a musical sketchpad.
I hope you enjoy and, sorry for all the bugs (:
Thanks

value: Show HN: I built a web DAW for lyricists and indie songwriters

author: cassettetourist


value: darkolorin

value:
Hi guys. We made own Mac app for M series hardware. Based on own engine called uzu (available with MIT on GitHub).
Completely written from scratch and inference too. Our goal is to show what you can do with local models. In the app section we will publish use cases which you can easily implement in your app.
Would appreciate any feedback.<p>Right now there is no set of proper benchmarks from us. In general we are faster than llama.cpp and on par with MLX. In a next release we will be faster than both.

value: Show HN: We made LM studio alternative based on own engine

author: darkolorin


value: lpellegr

value: Support for the Geo-Object Bundle (GOB) format, a tightly compressed, fast-to-import representation of a GOL (typically half the size of a GOL and 30% smaller than OSM-PBF)

value: Show HN: GeoDesk Geo-Object Librarian version 2.1

author: lpellegr


value:
Anthropic recently released an experiment called "Imagine with Claude" (https://claude.ai/imagine/). However, it was limited time only and available only for Pro and Max users which I am not.
I liked the idea and wanted to reverse engineer it just from public content like youtube videos and reviews.
Turns out, there were a bunch of limitations in their implementation
- The LLM cannot generate any JavaScript which means it cannot do any crazy animations
- They are capturing all user interactions using code and invoking the LLM with that info which means form data is not captured
I went ahead and implemented what they already had and a bit more
- All windows go into iframes which means it can have JavaScript
- I let the LLM write code to send iframe messages from any window to be invoked. This way the LLM writes the logic to invoke itself
You can also use this with both OpenAI and Anthropic models. Gemini models were not working well with these instructions.
I have hosted the app and you can use it by BYOK. There is no backend. LLM requests are made directly from your browser. There's no tracking and analytics as well.
This is a small experiment project that took me a couple of weekends and would love any feedback.

value: Show HN: Generative UI: OSS "Imagine with Claude"


value: onounoko

value: Drift is just a journal, a place to write. No complex features, no habit trackers, no prompts telling you what to write, no subscriptions. Just a place for you and your thoughts. Check it out and let me know what you think!

value: Show HN: I built drift journal, a simple app to reflect

author: onounoko


value: joaocorreia

value:
I’ve been a long-time Snowplow user and unofficial evangelizer. I have deep respect for its founders, Alex and Yali, who I met a few times.
What made me fall in love with Snowplow was that it was unopinionated, gave access to raw event data, and was truly open source. Back in 2013, that changed everything for me. I couldn’t look at GA the same way again.
Over the years, analytics moved into SQL warehouses driven by cheaper CPU/storage, dbt, reproducibility, and transparency. I saw the need for a democratized Snowplow pipeline and launched a hosted version in 2019.
In January 2024, Snowplow changed its license (SLULA), effectively ending open-source Snowplow by restricting production use. When that happened, I realized the spirit of open data and open architecture was gone.
A week later, I forked it, I wanted to keep the idea alive.
OpenSnowcat keeps the original collector and enricher under Apache 2.0 and stays fully compatible with existing Snowplow pipelines. We maintain it with regular patches, performance optimizations, and integrations with modern tools like Warpstream Bento for event processing/routing.
The goal is simple: keep open analytics open.
Would love to hear how others in the community think we can preserve openness in data infrastructure as “open source” becomes increasingly commercialized.
That's it, I should have posted here earlier but now felt right.

value: Show HN: OpenSnowcat – A fork of Snowplow to keep open analytics alive

author: joaocorreia


value: zepist

value:
Hi HN! We'd like to share something we built: BesiegeField — an environment where large language models design, test, and refine machines in the physics-based construction game Besiege.
Machine design is treated as a code generation problem: LLMs choose standard parts and specify how to connect them, making the task well-suited to language models.
The environment includes tasks like throwing a stone far or navigating bumpy terrain, and supports custom goals and environments.
We used it to explore both agentic workflows (no finetuning) and reinforcement learning, trying tasks like building cars and catapults.
It runs 100+ parallel processes on Linux clusters for scalable RL training.
Feedback from the AI, RL, engineering, and game dev communities is welcome.
GitHub: https://github.com/Godheritage/BesiegeField
HuggingFace Demo (single-agent): https://huggingface.co/spaces/Godheritage/BesiegeField-Machi...

value: Show HN: BesiegeField – LLM Agents Learn to Build Machines in a Physics Sandbox

author: zepist


value: tanelpoder

value:
This is the first proper release of xcapture eBPF thread sampler and xtop frontend TUI tool.
xCapture gives you an efficient, always-on observability signal for dimensional performance analysis of thread-level activity. In passive sampling mode on a 104 vCPU machine (~2000 threads), xcapture used 0.07% of a single CPU out of all CPU capacity.
We just had a "launch party" at P99CONF and the 20 minute talk is available at:
https://www.p99conf.io/session/xcapture-v3-efficient-always-...

value: Show HN: xCapture v3 for thread-level dimensional performance analysis with eBPF

author: tanelpoder


value: rokontech

value: When the backend team updates APIs, the frontend team can spend days syncing and updating documentation. I built middlerok.com

value: Show HN: Front end says back end changed again? Stop that with middlerok

author: rokontech


value: kaashmonee

value: Show HN: Desponsorize – Gray out Amazon sponsored search results

author: kaashmonee


value: uppnrise

value: Show HN: Production-ready rate limiter with Web Dashboard and 5 algorithms

author: uppnrise


value: I rewrote (from Rails to node) and open-sourced my personal self-hosted RSS reader. It's working pretty well on mobile devices. Desktop is in progress (or help me out).

value: Show HN: A self-hosted RSS reader

title: Show HN: A self-hosted RSS reader


value: alphabrevity

value:
Hey HackerNews,
We’re pumped to launch HiiPitch (hiipitch.com), an app that flips the script on B2B salesShow HN: HiiPitch - Make Sales Reps Buy You Lunch to Book Your Calendar. Tired of relentless cold emails and pointless demos? With HiiPitch, you hold the power: sales reps must buy you an Uber Eats lunch to unlock your calendar and book a meeting.
How It Works:
Create your unique HiiD link on hiipitch.com to share your availability.
Sales reps use your link to book a demo, paying for your meal credit + our service fee.
You get an Uber Eats voucher 90 minutes before the meeting—eat or donate it to feed the homeless.
Reps get insights on your needs, ensuring tailored, high-value pitches.
Why You’ll Love It:
Free Lunch: Get a meal for every demo you take, no strings attached.
Control Your Time: Your HiiD link stops spammy outreach and puts you in charge.
Social Good: Donate your meal credit to help those in need, making every meeting meaningful.
Better Meetings: Reps come prepared with relevant pitches, respecting your time.
Why It’s Game-Changing: HiiPitch turns your calendar into a gated asset, forcing sales reps to invest in you before they pitch. It’s like Uber (pay for rides) or Airbnb (pay for stays), but for your time. This consumer-driven model could redefine B2B sales dynamics, making prospects the priority.
HN, We Need Your Input:
Prospects: Would a free lunch make you more open to demos? Try a mock HiiD link scenario!
Sales folks: How would prospects demanding lunch for meetings change your game?
Check out hiipitch.com and share your thoughts. Would this make you rethink scheduling?
Let’s make B2B sales rewarding—literally. Join us in turning calendar access into lunch and meaningful connections!

value: Show HN HiiPitch – Make Sales Reps Buy You Lunch to Book Your Calendar

author: alphabrevity


value: Show HN: Browse previous Git tags easily


value: aanthonymax

value:
Hello HN! We're pleased to announce the release of a new version of our template language.
In it, we've improved server security and simplified the handling of asynchronous functions.
We're on track to deliver the perfect solution for HATEOAS applications, replacing many of its competitors in terms of functionality.

value: Show HN: New Version 3.1.0 of Hmpl

author: aanthonymax

title: Show HN: New Version 3.1.0 of Hmpl


value: neom

value: Show HN: Hacker News sans AI content

author: neom

title: Show HN: Hacker News sans AI content


value:
Hi HN,
We often run into this with coding agents like Claude Code: debugging turns into copy-pasting logs, writing long explanations, and sharing screenshots.
FlowLens is an MCP server plus a Chrome extension that captures browser context (video, console, network, user actions, storage) and makes it available to MCP-compatible agents like Claude Code.
You can try it here: https://magentic.ai/flowlens
Any feedback—good, bad, or brutal—is welcome.

value: Show HN: FlowLens – MCP server for debugging with Claude Code


value: goldenCeasar

value:
Hi HN,
I'm the author of Kumi, a project I've been working on and would love to get your feedback on.
The Original Problem:
The original idea for Kumi came from a complex IAM problem I faced at a previous job. Provisioning a single employee meant applying dozens of interdependent rules (based on role, location, etc.) for every target system. The problem was deeper: even the data abstractions were rule-based. For instance, 'roles' for one system might just be a specific interpretation of Active Directory groups.
This logic was also highly volatile; writing the rules down became a discovery process, and admins needed to change them live. This was all on top of the underlying challenge of synchronizing data between systems. My solution back then was to handle some of this logic in a component called "Blueprints" that interpreted declarative rules and exposed this logic to other workflows.
The Evolution:
That "Blueprints" component stuck in my mind. About a year later, I decided to tackle the problem more fundamentally with Kumi. My first attempts were brittle—first runtime lambdas, then a series of interpreters. I knew what an AST was, but had to discover concepts like compilers, IRs, and formal type/shape representation. Each iteration revealed deeper problems.
The core issue was my AST representation wasn't expressive enough, forcing me into unverifiable 'runtime magic'. I realized the solution was to iteratively build a more expressive intermediate representation (IR). This wasn't a single step: I spent two months building and throwing away ~5 different IRs, tens of thousands of lines of code. That painful process forced me to learn what it truly meant to compile, represent complex shapes, normalize the dataflow, and verify logic. This journey is what led to static type-checking as a necessary outcome, not just an initial goal.
This was coupled with the core challenge: business logic is often about complex, nested, and ragged data (arrays, order items, etc.). If the DSL couldn't natively handle loops over this data, it was pointless. This required an IR expressive enough for optimizations like inlining and loop fusion, which are notoriously hard to reason about with vectorized data.
You can try a web-based demo here: https://kumi-play-web.fly.dev/
And the repo is here: https://github.com/amuta/kumi

value: Show HN: I built Kumi – a typed, array-oriented dataflow compiler in Ruby

author: goldenCeasar


value: anuarsh

value: Show HN: Fine-tune Llama3-8B on 8GB GPU without quantization

author: anuarsh


value: RyanZhuuuu

value: Show HN: Open-source TypeScript SDK for sending and operating iMessages

author: RyanZhuuuu


value: juliusai

value: Show HN: Julius Slack Agent (and how to build your own)

author: juliusai


value: iaiuse

value:
Hi HN!
I'm iaiuse, and I've been working on MyRise Coach for the past few months. It's an AI-powered personal growth platform that combines 8 proven methodologies (resilience, cognitive reframing, self-determination theory, etc.) with GPT-4o to provide personalized coaching.
*The problem I'm solving:*
Most personal development advice is generic. Traditional coaching is expensive ($200+/hour). I wanted to make expert-level guidance accessible through AI, while grounding it in research-backed frameworks.
*What makes it different:*
- Based on 8 psychological principles (from positive psychology, cognitive behavioral therapy, etc.)
- AI analyzes your reflections against these frameworks and provides specific, actionable advice
- 12-week growth cycles with progress tracking
- Assessment system that measures improvement across 8 dimensions
*Tech stack:*
- Next.js 14 + TypeScript
- Supabase for auth and database
- OpenAI GPT-4o-mini (cost-optimized)
- Creem for subscriptions
- Deployed on Vercel
*Interesting technical challenges:*
1. Designing prompts that combine multiple psychological frameworks coherently
2. Building a subscription system that gracefully handles webhook delays
3. Creating a growth assessment algorithm that maps user inputs to 8 dimensions
*Current status:*
- MVP is live at https://myrisecoach.com
- Free tier: 1 assessment + 3 AI conversations/day
- Paid: $29.9/month or $299/year
*What I'm looking for:*
- Feedback on the AI coaching quality (is it actually helpful?)
- Ideas on how to better visualize growth progress
- Thoughts on the pricing model
- Any suggestions to make it more valuable
I'm here to answer questions! Would love to hear what you think.
Try it out: https://myrisecoach.com

value: Show HN: MyRise Coach – AI-powered growth platform with 8 proven methodologies

author: iaiuse


value: perryraskin

value: Show HN: Transit app for NJ-NY commuters (SwiftUI) – looking for feedback

author: perryraskin


value: JonanJ

value: Show HN: Myjourney – subscription-less Midjourney alternative

author: JonanJ


value: whyfinder

value:
OpenAPI specs are code that can be run!
Here is a Chrome extension that automatically detects OpenAPI files on any web page and lets you open them with one click in your favorite API tools like Swagger UI, ReDocly, etc.
Install - API Factory - Chrome Web Store
Pin the extension
Open any webpage containing OpenAPI - https://www.canva.dev/docs/connect/ or https://www.weather.gov/documentation/services-web-api
That's it. If the webpage contains an OpenAPI file, extension open opens a popup with all the tools. Launch the detected OpenAPI file in your favorite tool including Swagger UI, ReDocly, etc.

value: Show HN: Stop staring at OpenAPI files, open them instantly in your fav tools

author: whyfinder


value: VatanaChhorn

value:
I remember the feeling of using physical sticky notes. I would dump small thoughts, make quick checklists, and toss them once they were done. Life felt simple and convenient.
In this digital age, we’re prone to using note apps or to‑do list apps to replace sticky notes. I’m not saying there’s a problem with that, but most of the time I don’t need a full on note app or a full on to‑do list.
So how does a digitalized, transitional sticky note help my productivity? Imagine this: you’re going to the grocery store. Most of the time, you would use your note app with a checklist to list the items you want to buy. I’ve talked to a couple of close friends, and that’s how everyone does it.
The problem is:
- The notes (which are supposed to be for important things) end up cluttered, and over time, it’s harder to find the important ones because they’re buried under throwaway lists.
- When I arrive at the grocery store, I have to open the note app and sometimes even search for the note just to view the items and tick them off. More often than not, those notes stay there alongside my important ones because there’s no simple way to remove or archive them once I’m done.
How we used to do it with sticky notes:
- Note down the grocery checklist, and the widget will automatically update on the home screen.
- Arrive at the grocery store → check off all the items I’ve picked up.
- The sticky note automatically archives once every checklist item is ticked.
This simple workflow keeps my notes uncluttered and actually improves my productivity.
Feel free to try it out at https://apps.apple.com/ae/app/sticky-notes-notes-todos/id6754217076?platform=iphone.
I am open to constructive feedback.

value: SHOW HN: Remember the last time you used Sticky Notes?

author: VatanaChhorn


value: weijunext

value: Show HN: A Complete Dokploy Deployment Guide for Next.js Project

author: weijunext


value:
I built Seed3D, a next-generation 3D reconstruction and modeling tool that turns 2D inputs into solid, physics-ready 3D models — with millimeter precision, physically accurate PBR materials, and export formats ready for any major engine.
Unlike traditional photogrammetry or AI mesh tools, Seed3D doesn’t fake geometry with normal maps — it reconstructs real surfaces, edges, and micro-details for simulation-grade accuracy and realism.
What it does
• Generates watertight polygonal meshes with crisp, true geometry
• Outputs full PBR texture sets (albedo, roughness, metalness, normal, AO)
• Delivers 6K textures that hold up in extreme close-ups
• Ensures physics-stable topology for simulations and collisions
• Exports USD/USDZ, FBX, and GLTF — compatible with Omniverse, Unity, and Unreal Engine
Who it’s for
• Embodied AI and robotics researchers
• Game, XR, and VFX developers
• Product visualization and digital twin creators
• Simulation and graphics educators
Try the Seed3D 3D model generator here: https://www.seed3d.xyz/
Would love feedback from the HN community — especially on fidelity, physics performance, and engine integration.

value: Show HN: Seed3D – Generate Physics-Ready 3D Models with Millimeter Precision


value: sharms

value: There are a lot of registries out there but they are pretty legacy - SpreadCheer is modern React, can store lists inside your browser, and is fast / responsive, fun.  Runs on Vercel / Planetscale MySQL

value: Show HN: SpreadCheer Christmas Gift Registry

author: sharms


value: rane

value: Show HN: WalkingMate – Control a WalkingPad treadmill and track history on Mac

author: rane


value: Hi HN, we’re Ball x Pit Wiki, your go-to hub for mastering Ball x Pit.<p>Ball x Pit blends arcade-style ball-bouncing combat with city-building progression, delivering a fresh roguelite experience across major platforms. Our wiki consolidates 16 playable characters, 18 ball types, and 42 evolutions into a single, reliable resource—with clear unlock paths, optimal builds, and up-to-date strategy guidance.

value: Show HN: Ball X Pit Wiki

title: Show HN: Ball X Pit Wiki


value: whario

value: "Hi HN, I'm Mario, a full-stack developer. I built this 100% free, no-install web tool (using Python/FastAPI and FFmpeg) to simplify professional audio tasks for creators and small teams. I was frustrated by expensive, clunky desktop apps, so I focused on advanced features like a seamless multitrack mixer with crossfades, universal video-to-audio extraction (from URLs like YouTube), and robust conversion for challenging formats like WhatsApp OPUS/AMR. It's designed for efficiency in fast-paced production environments. Happy to answer any questions!"

value: Show HN: Free Online Audio Utility with Multitrack Mixer and Opus/AMR Support

author: whario


value:
ai-video-gen.org is a newly launched AI video generator currently in its promotional and trial phase. This early rollout invites creators, marketers, and teams to test the platform at lower prices while collecting feedback to sharpen features and reliability. The aim is to validate workflows, output quality, and pricing before a full-scale launch, with an emphasis on fast iteration and user input.
What to expect during this phase
Affordable entry: Generating videos now comes at reduced prices to encourage experimentation and rapid content production across campaigns and experiments.
Risk-free trial: The platform prioritizes a low-barrier experience, making it easy to try different concepts without heavy upfront commitments.
Free first-generation credit: New users receive a one-time free video generation, enabling immediate hands-on evaluation of capabilities and output quality.
Billing and policies you should know
Low-cost testing: The current stage prioritizes accessibility; pricing is designed to be favorable for early adopters while feedback is gathered.
Failed generations: If a generation attempt fails to produce a usable result, charges are not applied, aligning with a forgiving testing policy.
Ongoing terms: As the service evolves, pricing and terms may adjust; staying informed helps plan future productions.
How to get involved
Sign up during the promotional window to access the introductory pricing and the free generation credit.
Submit prompts or visuals to gauge quality, then refine inputs for desired tone and style.
Share feedback to help improve the platform during this early deployment.
Join ai-video-gen.org now to explore AI video creation at a very approachable price during the launch phase, and help shape the product with your feedback.

value: Show HN: AI Video Generator

title: Show HN: AI Video Generator


value: rohangnaneshjh

value: Show HN: GenerativeIDE – an offline AI‑powered code editor (privacy first)

author: rohangnaneshjh


value: yoavfr

value:
Knowing it might soon be obsolete, I still went ahead and built aisessions.dev - a place to share sessions from Claude Code, Codex, and Gemini CLI.
It was a fun zero-to-one project and an excuse to think through:
- Safely accepting user generated data (security, PII scrubbing, etc)
- Building a privacy conscious service
- Designing for long-term low-maintenance operation
- Developer experience — CLI tools, onboarding, and good defaults
- UI, design, and simplicity
- Keeping everything open source
Kudos to AMP and opencode for the inspiration.
If OpenAI, Anthropic, or Google launch native session sharing tomorrow, that’s fine. The experience is well worth the effort (which wasn't that big considering I wrote very little of the code).

value: Show HN: Share your coding agent sessions

author: yoavfr


value: alvinunreal

value: Show HN: Open-Source Project Discovery

author: alvinunreal

title: Show HN: Open-Source Project Discovery


value:
Hi HN, I'm Nick and I built Inspec with my partner Caitlin (she's the interior designer, I'm the developer).
Inspec lets interior designers create and manage FF&E schedules - basically spec sheets listing everything that goes in a room before the furniture: flooring, paint, countertops, lighting, fixtures, etc.
This process is currently exclusively done using Excel, and while this works to some degree, it comes with a lot of manual work and clunkiness. When Caitlin started working remotely, I watched her deal with these issues daily. So I spent the past 9 months building a better solution.
Key Features:
- Realtime collaboration
- Revision control (versioning)
- Professional PDF exports
- QR codes to print out on-site for contractors, builders etc. to always have the latest version
- Completely customisable fields and a familiar workflow to Excel to keep learning curve small
When we first started building this we thought it was completely unique, but turns out there are 2 competitors. I think our positioning is quite different though as we seek to only replace this document creation, rather than overhaul the entire project management and try to be a complete solution. So that’s helped to guide our focus, but also validated that interior designers are looking to modernise their software.
Tech stack:
I used my SaaS boilerplate which is just a modified T3 stack template with everything set up just how I like it. So Next.js with the pages router, TS, Trpc, Prisma + PostgreSQL, and TailwindCSS. I’ve also got Pusher for realtime collaboration, Redis and BullMQ for keeping a seperate background worker for PDF and web scraping jobs.
I can’t imagine many interior designers are on HN, but figured I would share this for anyone who wants to take a look :) feedback always welcome! The landing page is at https://inspec.design

value: Show HN: Inspec – Specification scheduling software for interior designers


value: supernihil

value: Show HN: Geophone PWA Using Accelerometer

author: supernihil


value: DeveloperOne

value: Show HN: Hashmate update is rolled out

author: DeveloperOne

title: Show HN: Hashmate update is rolled out


value:
I built two tools designed specifically for traders — the Position Size Calculator and the Compounding Profit Calculator.
The first helps traders determine their optimal position size based on risk tolerance, while the second visualizes account growth through realistic compounding projections, daily returns, and withdrawals.
Both tools were created completely no-code, using only smart formulas and logic — proving that powerful, useful tools can be built without writing a single line of code.

value: Show HN: Free Trading Tools – Quantify AI


value: An intelligent file organization tool that uses AI to automatically categorize and organize your files from your terminal

value: Show HN: AI-rganize: Just another file/folder organizing AI terminal tool


value: arthursw

value: ldbg is a minimal Python library that lets you ask an LLM questions while debugging — your prompt is automatically enriched with your current call stack, variables, and source context.<p>It’s like ShellGPT but for pdb, ipdb, Jupyter, or the VS Code Debug Console.

value: Show HN: Ldbg: a Python library to ask LLMs while debugging

author: arthursw


value:
Introducing NanoPhoto AI (https://nanophotoeditor.com), the revolutionary AI Photo Editor that transforms your creative ideas into stunning reality in seconds.
The power behind NanoPhoto AI is its advanced Nano Banana AI engine. Forget about layers, masks, and confusing tools. Here, your words are the only tool you need. Simply describe what you want, and the AI does the heavy lifting. Imagine typing "remove the photobomber" or "swap this boring wall with a professional studio backdrop," and watching it happen flawlessly.
But that's just the beginning. With this powerful tool, you can:
- Enhance Images Instantly: Turn dull, blurry photos into sharp, vibrant masterpieces with a single click or command.
- Create Consistent Characters: Develop a brand mascot or storybook character and maintain its look and style across multiple scenes—a game-changer for creators and marketers.
- Transfer Artistic Styles: Apply the aesthetic of a famous painting or a classic film to any photo, unleashing your inner artist.
Whether you're a marketer designing social media campaigns, an e-commerce seller optimizing product photos, or a creator making eye-catching YouTube thumbnails, NanoPhoto AI adapts to your needs. The process is effortless: upload your image, describe the change, and download your perfected visual.
Ready to unlock your creative potential? Visit nanophotoeditor.com for free today and see how Nano Banana AI can elevate your photos to the next level.

value: Show HN: NanoPhoto AI – Next Generation Photo Editor


value: Show HN: Orbyt – Job Search Analytics from Your Inbox


value:
Every company wants useful AI.
Few can afford the chaos that comes with it.
Cloud LLMs mutate daily. A prompt that worked yesterday breaks today.
You don’t own the model, the weights, or the risk surface.
Hallucinations are still running rampant through sensitive AI workflows.
Self-hosting sounds sovereign but turns into a maintenance treadmill: patches, GPUs, uptime, compliance audits.
Data privacy remains a liability: the more you automate, the more you expose.
We built:
Pyrinas MaaS (Model-as-a-Service) gives organizations their own private, fully serviced model stack.
Core mechanics:
We build, fine-tune, and deploy the model inside your boundary.
All inference runs on your hardware or our sealed unit (no data egress).
Continuous digital-twin testing keeps outputs within a 99% expected-result window.
Built-in data-labeling loop retrains and validates new information automatically.
Compliance layer emits auditable packets for HIPAA, GDPR, and FedRAMP alignment.
Predictable pricing: one flat model service fee; no tokens, no usage roulette.
In short: we turn AI from an experiment into infrastructure.
Yeah, yeah... what about it?:
Persistent problem -> MaaS outcome
Model drift -> Deterministic inference validated on-prem
Runaway API costs -> Flat cost, predictable ops budget
Privacy exposure -> Encrypted, sealed, customer-keyed runtime
Audit pressure -> Automated evidence packets
Stagnant models -> Continuous labeling + incremental retrain
A 30-person company running on Pyrinas typically reclaims about 1,350 staff-hours per year and saves around $50k in variable API spend while meeting compliance without a full-time ML ops team.
Early-builder offer
Sovereignty Suite: $25k list -> $15k Sovereignty Lock for teams that complete the 30-Day Sprint (data + workflow setup).
Technical trade-offs
12–32 core NPU configs; GPU optional.
Self-serve fine-tuning planned Q1 2026; handled via managed gateway today.
Determinism favors precision over open-ended creativity.
Zero telemetry by design; no usage analytics.
Open discussion
What part of your business would break if your model gave an inconsistent answer during an audit?
How much of your current AI stack would you rebuild if "predictable" and "private" were the default settings?
When you say you own your data, do you actually own the model that learned from it?
If every workflow was 99% repeatable, what new problems could your team finally trust AI to handle?
How close are you to regulatory exposure you can’t explain to a board or investor?
Whitepaper: https://pyrinas.co/the-convergence
We’ll be in the thread all day discussing architecture, validation methodology, and compliance design.

value: Show HN: I "invented" Model-as-a-Service for 95% Predictable Private AI


value:
https://www.amazon.com/dp/B0FX144F9R
A $$$ annual cost hidden in plain sight: manual certificate management doesn't appear as a line item, but it's bleeding elite engineering time, delaying projects, and creating phantom downtime costs across every small, large, scaling company.
$0 eBook today only (PDT).
Best Sellers Rank: #3,443 Free in Kindle Store (See Top 100 in Kindle Store)
#1 in Security & Encryption
#1 in 90-Minute Computers & Technology Short Reads
#1 in IT Project Management

value: Show HN: 15M Line Item That Doesnt Exist: Invisible Certificates ($0 Today Only)


value: LinkdAPI

value: This API is insane, it lets you get public data in real time and not like most services out there that let you search old, outdated databases

value: Show HN: LinkdAPI, the best LinkedIn unofficial API

author: LinkdAPI


value: tcogz

value:
I got tired of how expensive background removal APIs are some charge almost €1 per image.
So I built a simpler alternative: a pay-per-credit background removal API with no subscriptions and credits that never expire.
You just buy credits, send an image, and get a clean background-free result in seconds.
No account tiers, no monthly resets, just transparent pricing and easy integration.
Built for developers who want to add background removal to their SaaS, e-commerce tools, or automation workflows without the crazy costs.
https://bgbuster.com/

value: Show HN: A cheaper background removal API (no subscriptions, pay-per-credit)

author: tcogz


value: DenisDolya

value:
I made a terminal game called Digital Virus. It's a logic puzzle where you predict how a 4-digit code mutates after each wrong guess. Starts simple but gets tricky with combo rules at higher levels.
Wrote it in C to feel like those old 90s games. No graphics, just numbers and logic. Source is on GitHub: https://github.com/Ferki-git-creator/Digital-Virus
Curious what you think - especially if you remember when games came on floppies!

value: Show HN: I created a light logic game in the style of the 90s

author: DenisDolya


value: A terminal version of Cheat Engine written in Rust. It lets you explore and change live process memory right from the command line.<p>You can search for 4-byte or 8-byte integers, strings, or raw hex values. For strings and hex, you can set how many bytes to read, which helps with prefix searches. The list view uses Vim-style keys (j/k/G/gg) for easy navigation.

value: Show HN: CheatEngine-Rs – A Cheat Engine Rewritten in Rust for the Terminal


value: mariusMDML

value:
Hey Data folks,
Over the past two years we built a community of data analysts, scientists and engineers, with 570+ members right now on the discord.
This community has the goal to help and carry each others to improve our data skills.
We also developed a web-app to help students or job looking people practice their skills with 14 data projects including, dashboarding, ETL, SQL, R and Python to help them build a strong portfolio for job interviews. The app has a small cost to help the team develop future updates and spend time correcting the members projects, reviewing them, giving feedback, etc.
We also want to involve our professionnal network on Linkedin in a near future to allow students of the program to find real data jobs opportunities or short missions.
The community is free and you are all welcome to join our discord.

value: Show HN: We built a community of data learners

author: mariusMDML


value: a fast zero-copy sqlite implementation only for dumping the contents of a sqlite3 file

value: Show HN: Sqlite3-dump - a fast SQLite to CSV and parquet


value:
Hello HN!
Earlier this year, we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework for building agents with MCP. Since then we have tried to push the protocol to the limits, including hosting agents as long-running tools on MCP [3], and seen other creative approaches surface (mcp-ui, chatgpt apps sdk).
Today, we are launching mcp-c – a cloud platform designed for hosting any kind of MCP server, including agents, ChatGPT apps, etc. We are in open beta and free to use, and would love your feedback.
Here are some key choices we made:
1) Everything is MCP - Each application is deployed as a remote SSE endpoint, and implements the full MCP spec, including advanced features like elicitation, sampling, notifications and logging.
2) Durable execution via Temporal - We use Temporal as the runtime environment, allowing you to run long-running operations. This is especially critical for agents, which need to pause/resume, be fault-tolerant, and run for a long time.
3) Local to Cloud - we're fans of how easy it is to deploy a Next.js app to Vercel, so we've made it simple to take your local mcp-agent, mcp server, OpenAI app, etc. and deploy it to the cloud. We have several examples and even a handy CLI to get started quickly [4].
It's as simple as:
- uvx mcp-agent init
- uv init
- uv add "mcp-agent[openai]"
- uvx mcp-agent login
# add your openai key to mcp_agent.secrets.yaml
- uvx mcp-agent deploy
You can also try out these hosted mcp servers to get an idea. These can be connected to any MCP client (ChatGPT, Claude Desktop/Code, Cursor, etc.)
OpenAI Pizza App - https://18t536mliucyeuhkkcnjdavxtyg66pgl.deployments.mcp-age...
Basic Agent Server - https://1m82g32x8nkoppinayx0k5ye12oar6vk.deployments.mcp-age...
The HN community has been a big part of mcp-agent's growth, and we're super excited to share this with you as well. We would love to hear your thoughts and feedback!
---
[1] - https://news.ycombinator.com/item?id=42867050
[2] - https://github.com/lastmile-ai/mcp-agent
[3] - https://news.ycombinator.com/item?id=44053754
[4] - https://github.com/lastmile-ai/mcp-agent/tree/main/examples/...
[5] - https://docs.mcp-agent.com/get-started/welcome

value: Show HN: MCP-C – cloud platform for running MCP agents and apps


value: wainguo

value:
Hey HN
I built ImageConverter.dev
 because I got tired of “free” image converter sites that force uploads, or throttle conversions.
So I made a tool that runs 100% client-side — meaning your images never leave your device. It’s built for speed, simplicity, and privacy.
What it does
Convert images between JPG, PNG, WebP
Works offline once loaded (PWA support)
How it works
It uses the Canvas API and WebAssembly to handle conversions directly in the browser.
There’s no upload, no tracking, no server costs, and it’s fast even on mid-range devices.
Why I built it
I wanted an instant, no-ads, privacy-safe way to handle images for my personal projects — something lightweight enough to replace desktop tools.
Try it
https://imageconverter.dev
Would love feedback from the community — especially on:
Performance on different browsers/devices
Thanks for reading!

value: Show HN: A fast, privacy-first image converter that runs in browser

author: wainguo


value:
Hi HN,
I’m building Worthunt, a unified workspace for digital professionals
Today, independent professionals use scattered tools for payments, clients, analytics, and workflow. It’s expensive, fragmented, and hard to track what’s actually driving growth. Worthunt simplifies this by combining everything into one platform your network, payments, analytics, and AI insights built for the modern working economy.
Our vision is to help every digital professional operate frictionless we want to be the salesforce or Microsoft for this new digital first workforce: own their data, understand their metrics, and grow faster without relying on multiple platforms or marketplaces.
We’re partnering with teams like Framer and Lovable to integrate creative and workflow tools directly. Our target is to save users ~30% on costs and 4–5 hours a week from reduced tool-switching.
You can try it at worthunt.com
Would love feedback on usability, workflow logic, or integrations you’d like to see.

value: Show HN: Worthunt – a single workspace for freelancers, creators, and agencies


value:
Hey HN
I built ResizeImage.dev that runs 100% client-side — nothing gets uploaded, and it’s instant.
What it does
Resize, crop, and optimize images directly in your browser
Supports JPG, PNG, WebP
Works offline (PWA-ready)
No tracking, no server, no data collection
How it works
It uses the Canvas API and WebAssembly codecs to process everything locally.
All transformations happen in-memory, so no files ever leave your machine.
Why I built it
I needed a simple, no-BS way to resize images for web and social media — something fast, private.
Try it
https://resizeimage.dev
Feedback welcome
I’d love feedback from the HN community
Thanks for reading!

value: Show HN: ResizeImage.dev – A fast image resizer runs in browser


value: FiloSottile

value: Show HN: Run a GitHub Actions step in a gVisor sandbox

author: FiloSottile


value: barodeur

value: > "In a world without nil safety, one gem dares to ask: 'What if we just guessed?'"

value: Show HN: LLM Rescuer – Fixing the billion dollar mistake in Ruby

author: barodeur


value: epaga

value: Show HN: Mindscope 2 – visual and hierarchical thought organizer (iOS/macOS)

author: epaga


value: sql-hkr

value:
I built a tiny 8-bit CPU simulator in Python to better understand how computers work at a low level.
It visualizes registers, memory, and instructions in real-time, so you can actually see each operation as it happens. You can write simple assembly code and watch how the CPU executes it step by step.<p>The project is mainly for learning and experimentation, but I’d love feedback or ideas for improvement.

value: Show HN: I built an 8-bit CPU simulator in Python from scratch

author: sql-hkr


value: npetz

value:
Hey
I wanted to share a website i've made.
It'a redesign of the UNV ( United Nations Volunteers ) Dashboard.
I quit my job lately to take some sort of a gap year.
I've been pondering between working in the non-profit sector, or trying to make my own little business.
This is a little step towards both ideas :)
I'm trying to get used to ship things, and also do things just to be useful.
The original UNV dashboard has pretty bad UX, so I hope my version can help make people finding a volunteering opportunity a less stressful endeavour.
It's not perfect, but I intend to keep making it better.
https://volunteerwiththeun.com/
cheers <3

value: Show HN: UN Volunteers Opportunities Dashboard

author: npetz


value: simoelalj

value: Show HN: I Built a Multi-Region MongoDB Replica Set on Hetzner Cloud

author: simoelalj


value: jakedahn

value:
Hello HN!
I’ve been playing with Claude Skills and stumbled on a simple pattern for tiny, durable personal data systems:
* CLI: a small, self-contained executable
* SKILL.md: the operator guide (what to run, how to parse output, how to think about the system)
* SQLite: a local DB for persistent state
It’s nothing mind-blowing, but the ergonomics of this combo feel great.
If you define a process/flow, Claude can "turn the crank" by running the CLI, accumulating context, and animating the system to life over time.
They’re also easy to share: you can distribute System Skills via Claude Code’s `/plugin marketplace add <repo>`.
More details in the blog post and the toy Pomodoro System Skill reference implementation here:
Blog: https://www.shruggingface.com/blog/the-system-skill-pattern
Repo: https://github.com/jakedahn/pomodoro
--
Curious whether any of this resonates. Also excited to hear any interesting System Skill ideas worth exploring!

value: Show HN: The System Skill Pattern

author: jakedahn

title: Show HN: The System Skill Pattern


value: sagibo

value:
I built a curated library of AI art prompts that fully supports multiple languages. Each prompt links to a real output/example, with categories like portraits, fantasy, comics, products, landscapes, and storytelling.
Why I built it:
- Tired of repetitive, low-signal prompt dumps
- Wanted language-inclusive prompts (not only English)
- Each prompt paired with actual result for quality gauge
What's inside:
- Curated prompt vault for ChatGPT, Gemini, Perplexity, and more
- Multilingual support + local cultural twists
- All open, free, no sign-up
Happy to hear feedback: missing categories, UX, prompt quality, speed, anything.

value: Show HN: Nano-Banana AI Art – Curated multilingual prompts with examples

author: sagibo


value: damarberlari

value:
Hi all, I've started a blog at https://visualrambling.space/ where I document my learnings on various topics in a visual format.
The latest topic I explored is about dithering, and in this latest post I tried to visualize the mechanism behind it. This is only the first part out of three, so it only cover the basics. (I’m still working on the next 2 parts).
Feel free to visit, and let me know what you think!

value: Show HN: Visualizing Dithering

author: damarberlari

title: Show HN: Visualizing Dithering