value: YAndreaRusso

value: i made a council of advisors to help me code. as a self taught dev, ive been heavily reliant on ai for the past two years. found myself often prompting claude to take on different personalities, so i built a web app. it's great for the step before telling cursor what to do and reviewing prs once theyre ready. PLEASE DON"T NUKE MY APY KEY. ty

value: Show HN: council - ai groupchat of ctos (no more asking ai to roleplay)

author: YAndreaRusso


value: stevius

value:
I want to share my container automation project Proxmox-GitOps — an extensible, self-bootstrapping GitOps environment for Proxmox.
It is now aligned with current Proxmox 9.0 and Debian Trixie - which is used for containers base configuration per default. Therefore I’d like to introduce it for anyone interested in a Homelab-as-Code starting point
GitHub: https://github.com/stevius10/Proxmox-GitOps
It implements a self-sufficient, extensible CI/CD environment for provisioning, configuring, and orchestrating Linux Containers (LXC) within Proxmox VE. Leveraging an Infrastructure-as-Code (IaC) approach, it manages the entire container lifecycle—bootstrapping, deployment, configuration, and validation—through version-controlled automation.
- One-command bootstrap: deploy to Docker, Docker deploy to Proxmox
- Ansible, Chef (Cinc), Ruby
- Consistent container base configuration: default app/config users, automated key management, tooling — deterministic, idempotent setup
- Application-logic container repositories: app logic lives in each container repo; shared libraries, pipelines and integration come by convention
- Monorepository with recursively referenced submodules: runtime-modularized, suitable for VCS mirrors, automatically extended by libs
Pipeline concept:

   - GitOps environment runs identically in a container; pushing the codebase (monorepo + container libs as submodules) into CI/CD

   - This triggers the pipeline from within itself after accepting pull requests: each container applies the same processed pipelines, enforces desired state, and updates references

- Provisioning uses Ansible via the Proxmox API; configuration inside containers is handled by Chef/Cinc cookbooks
- Shared configuration automatically propagates
- Containers integrate seamlessly by following the same predefined pipelines and conventions — at container level and inside the monorepository
- The control plane is built on the same base it uses for the containers, so verifying its own foundation implies a verified container base — a reproducible and adaptable starting point for container automation
It’s still under development, so there may be rough edges — feedback, experiences, or just a thought are more than welcome!

value: Show HN: Proxmox-GitOps: IaC Container Automation for Proxmox (Recursive Docker)

author: stevius


value: aanthonymax

value:
I got tired of shipping megabytes of JS just to render small bits of dynamic UI.
So I built HMPL.js — a tiny (~24 KB) server-oriented templating language for JavaScript. It lets you send UI directly from the server with a simple block syntax, no framework overhead. Example:
<div>
  <button id="btn">Click!</button>
  Clicks: {{#request src="/api/clicks" after="click:#btn"}}{{/request}}
</div>
It’s fetch-based (not XHR), supports events/forms, integrates JSON5, and sanitizes HTML via DOMPurify. Think of it as a smaller alternative to HTMX/Alpine.js when you just want server-driven interactivity with minimal JS.
Docs: hmpl-lang.dev
Would love feedback on where this could actually replace heavier setups ^ ^

value: Show HN: I'm building HMPL – server-oriented templating for lightweight web-apps

author: aanthonymax


value: markpGN

value:
Finally I was able to build an app for the first time. Its not that fancy but it works for me at least.
It is a note-taking app. (I know its always been this app)
I built this using Google Ai Studio which I accidentally stumbled upon on and I was just blown away. I have tried other tools like bolt, lovable but man Google did amazing on this.
I am always looking for a note taking app that is simple but functional. Not too many clutter or confusing commands.
I just exported the files from Google AI Studio and made a repo on github though right now it is private but let me know your thoughts about it.
I am open to any comments or suggestions or bug fixes. Thank you!
For more details: https://graphnotesapp.carrd.co/

value: Show HN: Another note-taking app? My first built app

author: markpGN


value: Show HN: Freak.nvim, an nvim config for control freaks


value: smoqadam

value: Show HN: Musrv – Minimal zero‑config music server written in Rust

author: smoqadam


value: canercbo

value: I was struggling to keep my Twitter account active. Low engagement made it discouraging, and whenever I got busy or went on vacation, the account went quiet. Scheduling ahead was tedious, and writing posts consistently took more time than I had.<p>To address this, I built a tool that automatically pulls in the latest news, generates natural, human-sounding tweets, and can create matching images. It also allows scheduling posts for a full week and suggests optimal posting times based on activity patterns.

value: Show HN: Tool for automating Twitter posts with news content and scheduling

author: canercbo


value: jaronp

value:
I built Mystwright, an AI-powered "murder" mystery game engine.
(Other mystery types are possible too! But I'm still working on making those feel right.)
Instead of pre-written cases, Mystwright procedurally generates a world, a crime, and a cast of suspects — each with unique motives, relationships, and secrets. You investigate in any order: interview suspects, search for clues, follow leads. The story adapts as you play.
Core mechanics:
- Procedural mystery generation (no two games are the same)
- Seeded mystery worlds
- Procedural dialogue generation
- Distinct character personalities
- Consistent timelines and evidence trails
- Generative voice dialogue
- Location exploration experiments are underway
I'd love feedback on:
- Does the mystery feel engaging/coherent?
- Ideas for mechanics that would make solving more satisfying
- Is it too easy, too hard, or just right?
- Etc!
*Also there are some worlds I have made public (under the community tab) which I consider some decent examples. Feel free to try those so you don't have to wait for a world to generate!*
Live Site: https://mystwright.com
Would love your thoughts!
P.S. Re: pricing - You can use the service for free to a point. Right now you can make 1 world, send up to 30 messages to characters, and can only use the default model which is not the fastest but is well rounded.

value: Show HN: Mystwright – AI generates dynamic murder mysteries you can solve

author: jaronp


value:
We built Sentrilite, a lightweight unified control-plane to observe and secure hybrid multi-cloud fleets (AWS, Azure, GCP, on-prem) from one place. The goal is fast onboarding, live kernel-level telemetry, fleet-wide rule targeting, and an audit-ready PDF—without stitching together 5 tools.
What’s in the demo
Fleet onboarding in seconds: upload a two-column CSV (ServerIP,Group) and the fleet view auto-populates with tiles, health, recent alerts, and AI insights.
One-command deploy to EKS: kubectl apply -f sentrilite.yaml sets a DaemonSet (one agent per node); images are auto-pulled. Click a node to see live process/file/network events enriched with Kubernetes metadata.
High-risk rules (hot-reload): target rules by Group (e.g. only aws, azure or prod). We flag nc/netcat, sensitive file reads, etc., and show the alerts immediately.
Fleet health signals: detect OOMKilled containers with exact pod/container context for fast triage.
Export PDF: one click to generate a chronological report with summaries, tags, and k8s context.
Why we built it
Hybrid fleets need a single control plane to target rules to subsets and see uniform telemetry across clouds.
We wanted eBPF-level visibility with Kubernetes context, but make onboarding dead simple.
How it works (high level)
Agents run as a DaemonSet per node, stream events to the dashboard, and apply local rules (hot-reloaded).
Grouping (Group in CSV) drives selective policy: test rules on a small slice before rolling out fleet-wide.
Quick start
# fleet.csv
ServerIP,Group
10.0.12.34,aws
10.1.5.7,azure
10.2.9.11,gcp
192.168.1.20,private
# Deploy agents to EKS
kubectl apply -f sentrilite.yaml
# Generate a couple signals in a debug pod
nc -l 5000 &               # listener gets flagged
cat /etc/passwd >/dev/null # sensitive file read
# Simulate OOMKilled
kubectl run oom-demo --restart=Never --image=busybox:1.36 \
  --overrides='{"apiVersion":"v1","spec":{"containers":[{"name":"hog","image":"busybox:1.36","command":["/bin/sh","-lc","i=0; while :; do dd if=/dev/zero of=/dev/shm/f$i bs=1M count=64 conv=fsync; i=$((i+1)); done"],"resources":{"requests":{"memory":"32Mi"},"limits":{"memory":"64Mi"}}}]}}'
Try it
Demo video: https://youtu.be/FmFUs0ZhdIY
GitHub quick start (free): https://github.com/sentrilite/sentrilite
Notes
Runs in your cluster; you control data flow.
Looking for feedback on: rule UX, fleet grouping model, and what you’d want in the PDF/alert context.
Happy to answer questions and share more internals if folks are interested.

value: Show HN: Sentrilite: a hybrid-cloud control plane for observability and security


value:
Essential digital literacy skills for the AI-saturated world of 2025
Why You Need This Skill in 2025
In our AI-saturated world, detecting AI chatbots has become an essential digital literacy skill! Whether you're avoiding scams, ensuring authentic communication, or simply satisfying curiosity, learning to distinguish AI from humans is crucial.
5 Battle-Tested Detection Techniques
1. Response Speed Analysis
Human Indicators:
Typing pauses and "typing..." delays
Longer think time for complex questions
Occasional response delays
AI Red Flags:
Instant long responses
Unnaturally consistent response timing
2. Language Pattern Detective Work
Human Signatures:
Typos and casual expressions
Emojis, slang, internet lingo
Emotional tone variations
AI Giveaways:
Perfect grammar and structure
Formal, templated responses
Lack of personalized language quirks
3. Personal Experience Mining
Test Questions:
"What did you eat today?"
"Describe your neighborhood"
"Share a childhood memory"
Evaluation Criteria:
Humans provide vivid, specific details
AI gives vague, generic responses
4. Knowledge Blind Spot Testing
Effective Tests:
Breaking news (within 24 hours)
Local/niche knowledge
Personal professional experiences
5. Logical Consistency Verification
Methods:
Repeat questions after time gaps
Check for contradictions
Test "memory" coherence
 Advanced Detection Tactics
Creativity Tests: Request improvisation, jokes, or original content
Emotional Depth: Share personal struggles, observe response authenticity
Technical Probing: Ask "What model are you? What's your training data?"
The Bottom Line
AI detection skills are becoming the "mind reading" superpower of the digital age. Master these techniques, and you'll navigate online interactions with confidence!
Remember: Stay vigilant but embrace the benefits AI technology brings to our lives.
Key Takeaways
Response timing patterns reveal AI vs human behavior
Language analysis exposes AI's formal communication style
Personal experience questions challenge AI's knowledge limitations
Consistency testing reveals AI's programmed responses
Advanced tactics provide deeper verification methods
 Pro Tip: Combine multiple detection methods for the most accurate results. No single technique is foolproof in the rapidly evolving AI landscape.
Keywords: AI chatbot detection, human vs AI identification, digital security tips, bot detection methods, AI verification techniques

value: Show HN: How to Spot AI Chatbots vs. Real Humans: 5 Proven Detection Methods


value: madgik

value:
Hi HN!
I've been building trading bots on Solana for a while now, and I kept running into the same problem: every DEX has its own SDK, API quirks, and integration complexity. You'd spend days just to support all Raydium pools, then more days for Meteora pools, then even more for the new launchpads like Heaven, Sugar, Boop etc.  Each one required different approaches for pool discovery, slippage handling, and transaction building.
Some of you might ask, why not using Jupiter? Well, they decided to close source their binary and make it paid 5-10k/mo, which a lot of solo devs can't handle...
So I built solana-trade - a unified library that handles all of this complexity behind a single, clean API. You can trade on like 15 different DEXs & launchpads (Pump.fun, Pump Swap, Raydium AMM/CLMM/CPMM, Orca Whirlpools, Meteora DLMM/DAMM, and many others) with the same function calls.
The architecture is modular - each DEX gets its own client that implements a common interface. The main SolanaTrade class handles provider selection, transaction building, and routing. It's all built in Typescript.
A key feature is the MEV protection integration. Rather than just supporting standard RPC, it can route transactions through Jito, Nozomi, or Astralane based on tip amounts and availability. The library automatically selects the best provider or lets you specify one explicitly.
The transaction building is fairly sophisticated - it handles compute budget optimization, priority fees, automatic pool discovery with caching, and includes a 0.15% development fee on buys (which can be disabled). Everything is designed to be production-ready rather than just a proof of concept.
I also built a CLI interface that wraps the programmatic API. You can install it globally with npm and start trading from the command line immediately, which has been useful for quick testing and automation scripts.
The technical challenge was mostly around the inconsistencies between DEX SDKs. Some use different slippage formats, others have different ways of specifying pools, and the transaction instruction building varies significantly. I ended up creating adapter patterns for each one while maintaining a consistent external interface.
It's published on NPM as "solana-trade" so you can try it right away. The CLI works out of the box for basic trading, and the programmatic API handles more complex scenarios like getting unsigned transactions for manual processing.
I'm particularly interested in feedback, and curious if there are other DEXs or features that would be valuable to add.
The codebase is MIT licensed and I'd welcome contributions, especially from teams running other DEXs who might want to integrate their protocols.
NPM: https://www.npmjs.com/package/solana-trade
GitHub: https://github.com/FlorianMgs/solana-trade

value: Show HN: Open-Source Solana Trading Lib with 15 DEX Support and MEV Protection

author: madgik


value: mehedimi

value:
I built Countdown Builder
 as a lightweight way to add urgency to email campaigns.
Most ESPs don’t provide native countdown timers, and existing solutions are either clunky, expensive, or not very customizable. Countdown Builder lets you:
Design a countdown timer (fonts, colors, styles)
Preview in real-time
Generate a snippet to embed directly into your email
Use cases: flash sales, product launches, webinars, or any campaign where showing “time left” works better than just saying it.
I’d love feedback from this community on:
Edge cases I might have overlooked (email client compatibility, etc.)
Features you’d expect if you were to use this
Any gotchas you’ve faced embedding dynamic content in email
This is my first attempt at building a tool in this space, so I’m very open to ideas and critique.

value: Show HN: Countdown Builder – Create Custom Countdown Timers for Email Campaigns

author: mehedimi


value:
I made a free online QR Code generator tool.
Why? Most QR tools online are either bloated with ads, paid-only, or hard to use. So I built a clean and simple alternative.
Features:
Minimal design, mobile friendly
Generate high-quality QR codes
Batch generation support
QR scanner included
Local history saving
Try it here: qrcode-generator-gamma-brown.vercel.app
Feedback appreciated!

value: Show HN: Free QR Code Generator – Minimal, Fast, with Batch Support


value: vue-markdown-render is a tiny, client-side Markdown renderer for Vue 3. In browser-side benchmarks we see significantly lower CPU usage and latency vs Vercel’s Streamdown, with up to 100× speedups on large, code-heavy docs. Note: Streamdown targets server-side streaming; our results are for client rendering. Ideal for AI chatbot UIs.

value: Show HN: Vue-Markdown-render – up to 100× faster streaming Markdown for Vue 3


value: Show HN: GitHub repo with 180 tools for investing


value: antonellof

value:
Hi HN! I built VittoriaDB as a zero-configuration embedded vector database that actually works out of the box for local AI development.
Core features:
• Zero-configuration embedded vector database - no setup, no config files
• HNSW indexing for sub-millisecond vector similarity search
• ACID-compliant storage with write-ahead logging for data integrity
• Complete REST API for language-agnostic integration
• Single Go binary - 8MB download, runs anywhere
• Python SDK with automatic binary management
Technical highlights:
The database uses HNSW (Hierarchical Navigable Small World) graphs for efficient approximate nearest neighbor search, achieving 2.6M+ vectors/sec insert rates and sub-millisecond query latency. Storage is ACID-compliant with WAL (Write-Ahead Logging) for crash recovery and data consistency.
Local AI integration:
Built-in Ollama integration provides high-quality ML embeddings without API costs or internet dependencies. Upload documents (PDF, DOCX, MD, HTML) and get automatic chunking, vectorization, and semantic search - the complete RAG pipeline runs locally.
Unlike hosted vector databases, VittoriaDB runs as part of your application process. No separate infrastructure, no network latency, no external dependencies. Perfect for local development, edge deployments, or anywhere you need vector search without operational complexity.
Performance benchmarks:
• Insert speed: 2.6M+ vectors/second
• Search latency: <1ms for optimized queries
• Memory usage: Linear scaling (1MB per 1K vectors)
• Binary size: 8MB compressed
Real-world usage:
Developers use it for RAG applications, semantic search, document processing, and AI prototyping where you need production-grade vector operations without database administration overhead.
Links:
• GitHub: https://github.com/antonellof/VittoriaDB
• PyPI: https://pypi.org/project/vittoriadb/
• Install: pip install vittoriadb

value: Show HN: VittoriaDB – Zero-config embedded vector DB with HNSW and ACID storage

author: antonellof


value: rallies

value:
Hey folks,
Software engineer turned trader here. I absolutely love ChatGPT and Perplexity finance when it comes to doing any investment research and have been heavily using them for the past year. But there are also some big gaps like out-dated data, no charts, etc. Because both tools mostly rely on web search, there is an inherent limitation of delayed time data.
I've been spending some spare time over the last few months to see if we can build something to address both issues while keeping the core aspect of ChatGPT and perplexity intact i.e a chatbot interface but heavily rooted in real time data that's also super visual.
Launched https://rallies.ai 2 months back and have been iterating on it ever since. It uses an agentic framework to retrieve real time data on a query, and answers questions along with relevant charts.
Although this is a small change, the results look significantly better.
Would love to take any feedback. There's a lot more to do.
Also happy to answer any questions.

value: Show HN: Rallies – Investment assistant backed by real time data

author: rallies


value: DearestZ

value:
Hi HN, I just launched a simple website for quickly grabbing the latest Borderlands 4 SHiFT codes: https://borderlandsshiftcodes.org
.
It's a small tool to help fans easily find active SHiFT codes, updated regularly. Saves you time hunting around Twitter or Reddit.
Feedback is appreciated—hope it helps some fellow vault hunters!

value: Show HN: Borderlands 4 SHiFT codes aggregator, updated daily

author: DearestZ


value: Padierfind

value:
Hi Hacker News, I’m part of the team behind
Kodosumi. We built it because deploying agentic services in production was much harder than building proof-of-concepts. Many frameworks let you build agents, but when you want them to run long tasks, scale across machines, or be observed/monitored reliably, things fall apart.
Kodosumi is our answer to that. It’s an open-source runtime that uses Ray + FastAPI + Litestar to let you:
Deploy “agents” and “flows” and expose APIs easily, with minimal config (just one YAML)
Scale horizontally for bursty workloads and long-running tasks without losing stability
Monitor realtime status, logs, dashboards, etc. so you can see what’s going on under the hood
Avoid vendor lock-in (you can plug in your own LLMs, vector stores, frameworks) and deploy on cloud, on-prem, Docker, Kubernetes, etc.
We’re still early, so some parts are in active development. But if you are working with AI agents — especially ones that need to run reliably over long durations / scale up under load — we think Kodosumi could save you a lot of infra pain.
Happy to answer questions, comparisons to e.g. LangChain / Ray Serve / custom setups, criticisms, etc.

value: Show HN: Kodosumi – Open-source runtime for AI agents

author: Padierfind


value: ilkanozbek

value:
PipelinePlus bundles common MediatR pipeline behaviors into a small, plug-and-play library to reduce boilerplate in .NET apps.
What’s included:
- Validation (FluentValidation)
- Caching (attribute-driven with opt-out)
- Idempotency (deduplicate command handling)
- Outbox (persist and dispatch events)
- Performance (timing hooks)
- Exception mapping (turn exceptions into consistent results/logs)
Motivation: In most MediatR projects, these cross-cutting concerns get reimplemented again and again. PipelinePlus aims to make them composable, testable, and easy to adopt without locking you in.
Install:
  dotnet add package PipelinePlus
Minimal usage:
  // Program.cs / composition root
  services.AddMediatR(typeof(Program));
  services.AddPipelinePlus(); // registers the behaviors

  // Example request
  [Idempotent]
  public record CreateOrder(Guid Id, string Sku) : IRequest<Result>;

  // Example validator (FluentValidation)
  public class CreateOrderValidator : AbstractValidator<CreateOrder> {
    public CreateOrderValidator() {
      RuleFor(x => x.Sku).NotEmpty();
    }
  }

Notes:
- Outbox/Idempotency plug into your own storage abstractions.
- Works on .NET 8/9 and latest MediatR.
- MIT licensed.
Repo: https://github.com/ilkanozbek/PipelinePlus
Feedback welcome—API shape, naming, and ideas for the next behaviors (e.g., OpenTelemetry integration, Redis/distributed cache helpers).

value: Show HN: PipelinePlus – plug-and-play MediatR pipeline behaviors for .NET

author: ilkanozbek


value: omojo

value: Show HN: Ghread – Generate beautiful GitHub README profiles instantly

author: omojo


value: tmk-st

value:
Hi HN! こんにちは ^_^
I just built a creative and aesthetic website called Toki (時) Gallery.
“Toki (時)” means “a moment” in Japanese, and this site is a gallery of digital clocks.
It started with my own designs, but now I'm inviting other creators to contribute their clock designs as well.
I’d love to hear your thoughts on:
- What you think about this project
- Any recommendations on where to share it (I’m an engineer and not very familiar with creative communities)
- Or anything else you’d like to comment
Thank you for your warm reactions and feedback!

value: Show HN: Toki Gallery – A Curated Collection of Digital Clocks

author: tmk-st


value: mistivia

value:
I recently made a small open source project `EZLive`. It lets you host your private live video without a server with public IP address. It can also serve as a build block of a more complex media system.
EZLive will create a localhost RTMP ingest server, allowing OBS to stream video. Then EZLive converts the video into HLS files (.m3u8 + .ts). HLS files are uploaded to S3-compatible storage (like MinIO, Wasabi, Cloudflare R2, etc.). You can then watch the livestream with any HTML5 HLS player (like hls.js) in the browser.
Feature and drawbacks:
* Much lighter than Owncast — but no chat, no extra stuff.
* Easy to set up — just one binary and a S3 bucket.
* Scales easily — the S3 cloud storage handles the load.
If you just want a simple way to host your own livestream, this may work well for you.
This is a weekend side project I just finished. It’s still alpha, may have some bugs.

value: Show HN: EZLive – lightweight serverless self-hosted livestream

author: mistivia


value: tilyupo

value: Show HN: Syncwave – MIT-licensed real-time Kanban board

author: tilyupo


value: daolm

value: I'm launching a service where you will solve 80% of the data visualizations with 0 learning curve. You can upload your datasets or synchronize data sources, and the AI will generate charts & dashboards. You will be able to see and edit the queries generated by the AI and chat with your data sources.

value: Show HN: Chartz.ai – Cursor for Data Analytics

author: daolm


value: Show HN: RDMA/Infiniband Distributed Cache for Fast Inference and Training


value: airobus

value: Show HN: Navly – Curated Directory for the Latest AI Websites and Tools

author: airobus


value:
Warning: pre-release, unaudited, not for production use. (Though my password was generated with it)
Instead of saving secrets, it derives them on demand using domain + username + a short passphrase + a physical OpenPGP key (smartcard/YubiKey).
Passwords are reproducible but never persisted.
Currently tested only with RSA4096 on Windows + GnuPG 2.4.x.

value: Show HN: Paasword – a password vault that never stores your passwords


value: Show HN: AI Ancestry Test – Free Ethnicity Prediction from Your Photos


value: dethbird

value: I like SuperCollider a lot. This is a first experiment of an underwater soundscape but I want to make actual music as well lol

value: Show HN: Deep Water Sleep 1hr generative underwater in SuperCollider

author: dethbird


value: pandaupup

value: I built a free tool called Volume Shader BM. It’s a real-time graphics GPU performance benchmark that runs entirely in the browser — no installs, no drivers.<p>It uses shader-based ray marching (Mandelbulb scenes) to measure FPS, frame time, and stability across GPUs. You can tweak iterations, step size, resolution, and share reproducible results.

value: Show HN: Free Volume Shader BM – a browser-based GPU performance benchmark

author: pandaupup


value: flappylid

value:
I built a Flappy Bird clone that you control by opening and closing your MacBook lid. It uses the hinge lid angle sensor recently discovered by @samhenrigold!
This has no monetization, no ads, and is all ran locally. This is a throwaway account as I'm not sure I ever want this abomination attached to me professionally.
There are two game modes: "Easy Mode" where the bird follows your lid position directly, and "Flappy Mode" where you flap the lid to jump (with proportional jump heights based on how much you move the hinge).

value: Show HN: Flappy Lid – Control a Flappy Bird clone with your MacBook's lid sensor

author: flappylid


value: -i

value:
I made a chat room website
Go to 747.run a chat room will be made based on the URL share it to chat with people
Personalize URL in website address bar for example type 747.run/-
No login and works everywhere

value: Show HN

author: -i

title: Show HN


value: I made a small utility for listing the file names inside an archive file, e.g. tar, zip, etc. This comes in handy when you download some software package using the command line but you aren't sure whether to extract it in its own folder because you don't know what the file structure inside is.

value: Show HN: Pear, a utility for peeking into file archives


value: yomismoaqui

value: Show HN: Aggregator for Remote Developer Jobs

author: yomismoaqui


value: OnlineBabylon

value: Show HN: Will AI Take My Job? Explore AI Exposure Data

author: OnlineBabylon


value:
Hey everyone,
I just added a major update to my open-source project: a suite of 17 tools that run entirely in your browser with zero tracking.
I wanted a set of utilities (like a color contrast checker, JSON formatter, image compressor, etc.) where I wouldn't have to worry about my data being sent to a server.
A few of the tools included:
WCAG Contrast Checker & Blindness Simulator
CSS Flexbox, Grid, and Gradient Generators
Image Compressor & Formatter
JSON Formatter & CSV to JSON converter
QR Code Generator
Everything is 100% local and works offline. Hope you find it useful! Feedback and ideas for new tools are very welcome.
site link: https://www.businesswish.tech/tools
github link: https://github.com/abhaysinghr516/business-wish

value: Show HN: I built 17 free dev tools that work offline in the browser


value: techyKerala

value:
I built a small tool called BucketBin.
The idea is simple: instead of sending links to yourself on WhatsApp or email, you can drop them into buckets and keep them organized.
Free to use
Works on desktop (mobile version coming soon)
Would love feedback on how it feels to use and what features you’d want next.

value: Show HN: BucketBin – Organize links into buckets instead of messaging yourself

author: techyKerala


value: shikhar

value:
Cachey (https://github.com/s2-streamstore/cachey) is an open source read-through cache for S3-compatible object storage.
It is written in Rust with a hybrid memory+disk cache powered by foyer [1], accessed over a simple HTTP API. It runs as a self-contained single-node binary – the idea is to distribute yourself and lean on client-side logic for key affinity and load balancing.
If you are building something heavily reliant on object storage, the need for something like this is likely to come up! A bunch of companies have talked about their approaches to distributed caching atop S3 (such as Clickhouse [2], Turbopuffer [3], WarpStream [4], RisingWave [5]).
Why we built it:
Recent records in s2.dev are owned by a designated process for each stream, and we could return them for reads with minimal latency overhead once they were durable. However this limited our scalability in terms of concurrent readers and throughput, as well as implied cross-zone network costs when the zones of the gateway and stream-owning process did not align.
The source of durability was S3, so there was a path to slurping recently-written data straight from there (older data would already be read directly), and take advantage of free bandwidth. But even S3 has RPS limits [6], and avoiding the latency overhead as much as possible is desirable.
Caching helps reduce S3 operation costs, improves the latency profile, and lifts the scalability ceiling. Now, regardless of whether records are recent or old, our reads always flow through Cachey.
Cachey internals:
- It borrows an idea from OS page caches by mapping every request into a page-aligned range read. This did call for requiring the typically-optional Range header, with an exact byte range. Standard tradeoffs around picking page sizes apply, and we went with fixing it at the high end of S3's recommendation (16 MB). If multiple pages are accessed, some limited intra-request concurrency is used. The sliced data is sent as a streaming response.
- It will coalesce concurrent requests to the same page (another thing an OS page cache will do). This was easy since foyer provides a native 'fetch' API that takes a key and thunk.
- It mitigates the high tail latency of object storage by maintaining latency statistics and making a duplicate request when a configurable quantile is exceeded, picking whichever response becomes available first. Jeff Dean discussed this technique in "The Tail at Scale" [7], and S3 docs also suggest such an approach.
A more niche thing Cachey lets you do is specify more than 1 bucket an object may live on, and attempt up to 2, prioritizing the client's preference blended with its own knowledge of recent operational stats. This is actually something we rely on since we offer regional durability with low latency by ensuring a quorum of zonal S3 express buckets for recently-written data, so the desired range may not exist on an arbitrary one. This capability may end up making sense to reuse for multi-region durability in future, too.
I'd love to hear your feedback and suggestions! Hopefully other projects will also find Cachey to be a useful part of their stack.
[1] https://github.com/foyer-rs/foyer
[2] https://clickhouse.com/blog/building-a-distributed-cache-for...
[3] https://turbopuffer.com/docs/architecture
[4] https://www.warpstream.com/blog/minimizing-s3-api-costs-with...
[5] https://risingwave.com/blog/risingwave-elastic-disk-cache
[6] https://docs.aws.amazon.com/AmazonS3/latest/userguide/optimi...
[7] https://cacm.acm.org/research/the-tail-at-scale/#body-7

value: Show HN: Cachey, a Read-Through Cache for S3

author: shikhar


value: freetonik

value: Show HN: Dystopian chat where communication is edited and paraphrased by AI

author: freetonik


value: Built on Browserbase with Stagehand

value: Show HN: AI agent that researches roles and creates cover letters from job URLs

story_text: Built on Browserbase with Stagehand


value: rapawel

value: A tool that checks if any website uses a paid Cloudflare subscription by examining their public /cdn-cgi/trace endpoint. Cloudflare only allows disabling Encrypted Client Hello (ECH) in paid plans, so sni=plaintext indicates a paid subscription. Works on any Cloudflare-proxied site.

value: Show HN: Detect paid Cloudflare plans on any website via ECH

author: rapawel


value: sumit-paul

value:
Hi HN,
After years of experimenting with fitness apps (and probably too many spreadsheets), I’ve built something I've always wanted: a truly adaptive AI Workout Companion.
What is Train?
Train is an AI-powered fitness app that adapts to you—your goals, your fitness level, and whatever equipment you have (or don’t have). Whether you’re at the gym, working out at home, or just getting started, Train drafts personalized plans, tracks your progress, and acts as a real-time coach.
How Train Stands Out:
AI-Powered Coaching – Get tailored fitness advice, workout suggestions, and instant feedback as you progress.
Adaptive Plans – Your routine evolves as you do—whether your focus is strength, muscle, endurance, or weight loss.
Comprehensive Tracking – Effortlessly log sets, reps, weights, durations, and review your workout history anytime.
Personalization – Select goals, choose muscle groups to focus on, and Train will craft plans around your available equipment.
Modern Design – Clean, glass-like UI, smooth animations, dark mode for night sessions, and easy social sharing of workout cards.
Motivation Built-In – Stay on track with clear insights after each session and quick access to chat with your in-app coach.
Who’s it for?
Beginners who want a guided routine
Serious gym goers optimizing their progress
Fitness enthusiasts who love tracking
Anyone curious how AI can elevate their workouts
I built Train to solve my own frustrations as well as inspire consistency—and I’d love to hear your feedback and thoughts. Privacy-conscious by design, your data is yours (encrypted, deletable, minimal by default).
You can try Train on Android here:
https://play.google.com/store/apps/details?id=com.bufferlabs...
Looking forward to answering questions, learning how you’d use this, and connecting with fellow fitness/AI/product nerds!

value: Show HN: Train – AI Workout App for Smarter, Adaptive Fitness

author: sumit-paul


value: akanthi

value:
Supakey lets users bring their own Supabase project to your app. You add “Sign in with Supakey” (OAuth). On first consent, Supakey deploys your app’s schema into the user’s Supabase (least-privilege, RLS on). From then on, your app talks directly to their database using app-scoped credentials—no central multi-tenant DB to run.
Why
Users keep control and portability of their data.
Developers ship simple apps without hosting and babysitting per-user data.
How it works
User signs up on Supakey and connects their Supabase project.
Your app uses “Sign in with Supakey” (standard OAuth).
On first consent, Supakey deploys your app’s schema into the user’s Supabase with RLS enabled and minimal privileges.
Your backend/frontend uses app-scoped credentials to read/write their DB directly.
Users can revoke access anytime; data remains in their project.
For users
Keep all your application data in your own Supabase.
Use any compatible app as long as you like; no vendor lock-in.
For developers
Don’t host or retain user data; reduce ops and compliance surface.
Perfect for simple CRUD apps, notes/todos, personal trackers, prototypes.
Security & privacy
Per-app schema with RLS by default.
Least-privilege grants; credentials scoped to the app’s schema.
OAuth consent + easy revocation; no central data copy.

value: Show HN: Supakey – let users bring their own Supabase to your app

author: akanthi


value:
Hello, HN!
We are Gyani and Vasin. We’re building TabTabTab (https://tabtabtab.ai), an AI agent that helps you work faster in Google Sheets. Before this we worked at Bloomberg (where we met 7 years ago), Citadel, and Palantir.
We’re software engineers, and it feels fundamentally unfair that the best AI tools are limited to software engineers. Most knowledge workers only have ChatGPT as the best option. We want to give everyone AI superpowers.
A few months ago, we started by putting AI into copy and paste. Our assistant was aware of what you copied, and transformed it as you pasted it. We built this on accessibility and screenshot APIs. The goal was to move away from the chat box by building on one of the most-used shortcuts: copy and paste.
We noticed most users were using it to structure data in Google Sheets. They would copy from places like LinkedIn, PostHog, booking sites, business directories, and conference websites, then structure it in Sheets.
We decided to narrow in on this. We can deliver far more value if the interaction doesn’t end at paste. Much of what people do with copy and paste can be handled by an agent using web search, crawling, and data providers. And once the data is in the sheet, people want to do something with it—so we help with that too.
That’s how TabTabTab for Google Sheets was born. It’s a Chrome extension that lets you interact with a copilot that understands Google Sheets, can run code, has access to web search and enrichment APIs, and can crawl the web (we can do this on our backend or locally on your computer if you grant extra permissions).
While it’s very early, we’ve seen some interesting use cases:
- One of our first paying customers (a complete stranger) is a bank manager in Laos who also runs cafes on the side. He used TabTabTab to model the business, launch the main shop and five additional locations, and now uses it to manage the operation.
- Many people use us for enrichment. We ship with search plus some APIs, so if you have a list of LinkedIn URLs and want to figure out who they are, we can do that for you.
- We’ve seen data analysis use cases like customer segmentation, sensitivity analysis, categorizing and ranking data, and teachers building course schedules and staff allocations.
This seems to resonate with generalists and SMB professionals. Often they’re very comfortable with Google Sheets and don’t want to learn a new tool for a specific job, or there simply isn’t a tool for their use case—so they pick Google Sheets, and now us.
Permissions: You sign in with your Google account. We can only see files you explicitly grant access to, individually. Our Chrome permissions are standard. Optionally, we can request permission to open websites on your behalf (for example, if you’re trying to find mutual connections with someone on LinkedIn).
Pricing: Free Pro trial for 7 days, then $20/month for Pro, which includes access to Claude 4 Sonnet, GPT-5, and Gemini 2.5 Pro. There’s also a free tier with generous limits on more basic models.
Link to extension: https://chromewebstore.google.com/detail/tabtabtab-the-ai-ag... (works on all major browsers like Chrome, Edge, Safari)
We’re here to help! If you need anything, reach us at hello at tabtabtab dot ai.
Thanks,
Gyani & Vasin

value: Show HN: TabTabTab – Cursor for Google Sheets


value: lakshikag

value:
i built nooki because most community platforms today feel noisy, bloated, and optimized for ad revenue instead of people. reddit’s recent changes pushed me to create something simpler.
current features:
- no ads, no tracking
- text-only posts (no images/media yet unless heavily requested)
- no algorithms. posts in plain chronological order (with hot/new/top sorting)
- communities you can create and moderate yourself (mods can only control their own communities)
- voting + threaded comments
- points system that gives active users a stronger voice
- customizable notifications (decide exactly what you want to be pinged for)
it’s still barebones, but functional. the goal is to keep it simple: a space for conversations without all the noise. i’m soft-launching this today and would love some feedback on what to improve or add next.
i’m working on making nooki open source too as transparency and community involvement are the goal.

value: Show HN: Probably the simplest Reddit-style site you'll ever use

author: lakshikag


value: PictureRank

value: As a former student I created PDFToQuiz to solve I problem I had in college, how could I be sure I knew and understood all the material in the notes if I couldn't test myself.<p>That's why I built PDFToQuiz, it helps students test thier knowledge on their own notes.

value: Show HN: I Built a Free Site for Students to Test Their Knowledge on Their Notes

author: PictureRank


value: rohinbharg

value: A project we've been working on for some time that allows you to incrementally adopt modern open standards on top of existing express endpoints.<p>The framework is being used in production by a handful of companies, while the CLI is still in beta.

value: Show HN: ForkLaunch framework: Upgrading Express with a fully typed DSL

author: rohinbharg


value: rosasalberto

value:
Hi HN,
I’m Alberto, co-founder of Didit. One year ago we launched Didit with a simple goal: to fix identity verification.
Today, 1,000+ companies use Didit — from fintechs and banks to marketplaces and crypto apps. The growth has been faster than we ever imagined, which tells us this pain is universal.
The problem:
When we tried to integrate identity verification (KYC/AML) with providers like Sumsub, Persona, Jumio, Onfido, Veriff, or Idwall, we kept running into the same blockers:
“Contact sales” to even see pricing.
Weeks of calls before getting sandbox keys.
Expensive annual contracts, minimums, and bundled features you don’t need.
APIs and dashboards that feel outdated and heavy.
Meanwhile, fraud is exploding with AI, and strong IDV is more important than ever.
Our approach (Didit V2):
Didit is an open, developer-first identity verification platform that combines a modern dashboard, flexible workflows, and APIs you can actually enjoy using:
Unlimited free KYC → Document Verification, Passive Liveness, and Face Match are free forever. No caps, no trials.
Transparent pricing → Optional services (AML Screening, Proof of Address, NFC, Phone Verification, etc.) use simple prepaid credits. No contracts, no subscriptions, credits never expire.
Integration options:
Workflows → build complete journeys in our no-code builder, trigger with one API call.
Standalone APIs → call individual services directly from your backend.
Why free?
We believe basic KYC should be infrastructure, not a luxury upsell. Developers and startups should be able to build responsibly without burning months of runway on compliance.
We’d love feedback on:
Does this model make sense?
Are our docs and workflows clear enough?
What would you add or change?
Links:
Sign up & get sandbox keys → https://business.didit.me
Docs → https://docs.didit.me
Pricing → https://didit.me/pricing
Video demo → https://www.youtube.com/watch?v=5_mY-aVfC6g
We’ll be here all day answering questions. Excited to hear your thoughts!
Thanks,
Alberto

value: Show HN: Didit – Identity Verification Platform (Unlimited Free KYC)

author: rosasalberto


value:
Hi HN, time for another round, I’m Lasse. For years I’ve been frustrated by classical ERP systems being closed, rigid and expensive to change (or just not changeable at all   xd).
Last year I already posted my first attempt ("PORT", an OSS ERP), but due to better and better AI models, this approach already seemed outdated.
So we iterared and today I’m sharing TNX API, an now open-source execution layer that lets AI read and write your business data, on your own server, with guardrails and logs.
We went from "full ERP" to an execution layer ("your database + AI" as a power employee).
Everything runs on your own dedicated server, to support also legacy systems.
Every AI action is logged and permissioned, admins and users have different rights.
We leaned into tasks people actually do: generate PDFs (invoices/offers), bulk edits, charts, uploads -> extract -> write back and made them as simple as possible.
You simply ask in natural language -> AI crafts code -> our API Nexus checks/sanitizes -> Stargate executes that code against your DB -> result goes back to chat/forms/emailbot/shop. The system keeps audit logs for every step.
LINKS
landing page: https://www.tnxapi.com/UI/LandingPage.php
code: https://github.com/StultusEstQuiHocLegit/TNXAPI4
If you’re tired of ERPs that won’t bend to your business, kick the tires, file issues, and tell me what’s broken and I’ll fix it.
I really hate how limited current ERP systems are and I’m going to do everything in my power to change that.
Always at your service,
Lasse Tramann   : )

value: Show HN: TNX API – Natural Language Interaction with Databases, Now Open Source


value:
Hi HN,
In my spare time I built HumbleOp, an experiment in structured online debate. I’m not a full-time developer — this is a side project I’ve been working on evenings and weekends.
How it works:
A user posts an idea or opinion.
Everyone else can comment once, no threads.
The community votes. Importantly, a vote doesn’t mean agreement — it means you want that commenter to face the author.
When the timer ends, the top comment duels the author, one message at a time, publicly.
Others can react with likes or red flags. Too many flags and the winner is swapped with the runner-up.
Duels end when both click handshake, or if both top challengers are flagged out.
Direct duels are also possible, skipping the voting phase.
I built this because I was frustrated with how debates online usually go: endless replies, chaos, and low-effort takes dominating thoughtful ones. The strict rules are intentional: I wanted to see if structure could make discussions clearer and fairer.
Stack: React + Tailwind (frontend), Flask (backend), Postgres (database), deployed on Fly.io.
It’s live here: www.humbleop.com
It’s still a work in progress, so bugs are possible. Feedback is welcome — on the concept, the UX, or the tech.
Thanks for reading.

value: Show HN: HumbleOp – A debate platform where every post ends in a one-on-one duel


value: andrei-polukhin

value:
Tired of your Go tests being slowed down by repetitive PostgreSQL database setup?
I built pgdbtemplate to solve exactly that. It uses PostgreSQL's native template databases to create fully migrated test databases in milliseconds instead of seconds.
The problem: Traditional test setup runs all your migrations for every single test. With a complex schema, this wastes minutes in every test run.
The solution: Create one "golden" template database. Every test gets its own isolated copy instantly via CREATE DATABASE ... TEMPLATE.
Benchmarks don't lie:
- 1.5x faster for complex schemas (5+ tables)
- 37% time saved creating 200 databases
- 17% less memory usage
- Performance gains increase with schema complexity
It's:
- Thread-safe and built for t.Parallel()
- Driver-agnostic: works with both pgx and pq
- Integrates with testcontainers-go
- MIT Licensed
I'd love feedback from the HN community, especially on:
- The API design (ConnectionProvider/MigrationRunner interfaces)
- Ideas for further performance optimizations
- Security audit of the SQL formatting code
Check out the code and benchmarks on GitHub: https://github.com/andrei-polukhin/pgdbtemplate

value: Show HN: I made pgdbtemplate to cut PostgreSQL test time by 1.5x using templates

author: andrei-polukhin


value: oan

value:
LookingForwardTo.com is a platform to discover, track and share things to look forward to. Movies, shows games, your own events and more.
I've been close to the concept of having things to look forward to ever since it basically got me out of a very dark time of my life back in 2017 (that and my late dog).
Last year I decided to try and combine that with some of my biggest passions and this platform is the result. I'm currently curating all content by myself, except for the release dates, which are automated. It's built with a Next.js frontend and Node.js + express.js + MongoDB with Mongoose backend.
Feedback would be much appreciated!

value: Show HN: Discover and share things to look forward to

author: oan


value: Aeturnis

value:
Hello HN - solo dev and first timer, here.
Mirenku is a small desktop app to track what you’re watching. It’s local-first
(runs offline, no telemetry) and meant to complement, not replace, MAL.
v0.3.2 highlights: quick add/+/– episodes, search/filter, JSON/CSV import/export,
MAL OAuth2 (PKCE) + sync via protocol handler. Windows is primary; macOS/Linux
builds are experimental.
Security notes: tokens are envelope-encrypted (Fernet AEAD DEK wrapped by the OS
keyring); timestamped OAuth state; TLS 1.2+ only. SHA-256 checksums provided.
Links:
- Download / landing: https://mirenku.app
- Docs & security policy: https://mirenku.org
- Source / license details: https://github.com/Aeturnis-Development-Labs-LLC/mirenku
Feedback I’m looking for:
- Install friction on Win/mac/Linux
- Import/Export edge cases
- UI paper cuts (least clicks to update an episode?)
- Concerns with the token storage approach
Happy to answer questions and fix rough edges quickly.

value: Show HN: Mirenku – local/offline anime tracker

author: Aeturnis


value: Padierfind

value:
I'm part of the team that build Sokosumi, a marketplace where you can hire and deploy AI agents for specific tasks (research, design, sentiment analysis, etc.).
Instead of one big chatbot, they’re positioning it as a directory of specialized “freelancer” agents, with a blockchain-based backend for payments and identity. Developers can also list their own agents and monetize them.
Curious what people here think about this model:
Will specialization make agent marketplaces more useful than general-purpose LLM tools?
How viable is blockchain as the backbone for an agent economy?
What pitfalls might this run into (quality control, UX friction, trust)?

value: Show HN: Fiverr for AI Agents (Sokosumi)

author: Padierfind


value: FabianJani

value:
Hey everyone,
I built Yobio because I was tired of complicated and cluttered Link-in-Bio tools. It’s minimal, ad-free, and you can set up your page in under 30 seconds.
It already supports:
Fast setup
Clean, minimal design
Customizable buttons and colors
Coming soon: AI-powered features to make your page even smarter.
Check it out and let me know your thoughts: https://yobio.link
Feedback, ideas, and feature requests are very welcome!

value: Show HN: Yobio – A super fast, clean Link-in-Bio tool

author: FabianJani


value: AljazHisoft

value:
I built this because every movie night with friends turned into 30 minutes of endless scrolling on Netflix or Prime. By the time we picked something, the mood was gone.
MovieLoop shows you short clips instead of posters, so you get the real feel of a movie right away. If you like it, you add it to your watchlist. If not, just swipe to the next.
Would love to hear your feedback.

value: Show HN: I made an app that solves movie discovery

author: AljazHisoft


value: Aperswal

value:
Hey all, Adi and Sohan here. We're building Sita (https://trysita.com/), an open-source documentation generator that builds a codebase-aware knowledge graph, writes documentation for all your code, and provides an MCP server so your coding agents get precise, grounded context with citations.
Run 'git clone https://github.com/TrySita/AutoDocs’ and follow our 5 minute set up in the README, and you'll have a local instance of Sita up and running. From there add your repos, use the UI to explore the dependency graph and docs, or plug into an MCP-compatible editor (Codex, Claude Code, Cursor, etc) to fetch context while you code.
Check out a full demo here: https://youtu.be/S-0-9_F1AlE
Before Sita, we felt stuck copy-pasting across files, Slack, and tickets, waiting several minutes while agents guessed about parts of our codebase they were unaware of. With Sita, we generate accurate docs in minutes (which always stay in sync with our code) and feed agents the exact files and functions to change.
There are many code search and mapping tools (e.g., Sourcegraph, CodeSee), but none keep an agent-ready experience with human-readable docs and citations. On the other hand, tools like Notion or Confluence replicate the “docs” experience but lack auto-refresh from code, MCP endpoints, and easy setup.
We wanted our tool to mirror how senior devs navigate real code: by building a mental map of the dependency graph and navigating straight to files and functions. Existing SDKs and hooks don’t support this end-to-end, so we built an open-source pipeline that parses your repo (AST + SCIP), constructs the dependency graph, and generates easy-to-read docs; we expose everything through an MCP server and stream results to the web UI in real time. Our entire stack is open source and free to self host under the Apache 2.0 license at https://github.com/TrySita/AutoDocs. Looking forward to your feedback and hearing your thoughts and comments!

value: Show HN: AutoDocs – Reduce AI costs and never manage context again

author: Aperswal


value: naymul

value:
I built this to turn study sessions into visual progress — no more guessing if you’re improving.
Try it at https://gradax.com (just shipped today!)

value: Show HN: Gradax – Watch your study charts rise and feel your grades follow

author: naymul


value: theolouvart

value:
Hi HN, I’ve been working on https://datadef.io, a tool to help data team (engineer, architect, project manager) make sense of their data universe.
The problem:
- Data models (dbt, SQL, warehouses) often grow into a tangled mess of tables, joins, and undocumented assumptions.
- Lineage is either scattered across tools or missing entirely.
- Documentation is usually an afterthought (and gets outdated fast).
Datadef.io aims to fix that by providing:
- Interactive canvas to map tables, relationships, and indicators.
- Automatic lineage visualization to trace dependencies.
- Metadata management: define table/column-level details, ownership, and KPIs.
- AI-generated documentation that stays in sync with your models.
- Export/share features so asset managers, analysts, and other teams don’t get lost in spreadsheets or PDFs.
It’s still early, and I’d love feedback from the HN community. In particular:
What’s missing for you in lineage/metadata/documentation tools?
How would you want to integrate a tool like this into your workflow (dbt, Databricks, Power BI, etc.)?
I’d really appreciate your thoughts, feature requests, and criticism.
Thanks!

value: Show HN: Datadef.io – Canvas for data lineage and metadata management

author: theolouvart


value: harlequinetcie

value:
Hey HN,
Bootstrapped founder here. I've got a bit of a story for you.
We started desplega.ai to build a sophisticated AI platform that could automate E2E testing. We spent the last few months talking to dozens of QA leaders, and trying to learn what are their actual challenges. We've got one consistent feedback from large teams: their daily reality is a living hell of slow, clunky tools.
We're talking about teams at major companies still managing tests on spreadsheets. Or they're stuck in a Jira instance so customized and slow you can “make a full pot of coffee” while a page loads (and that’s why they acquired arc! t3.gg said it first). On top of that, they're paying 2k/mo+!? for these tools that feel like they were designed in ‘05.
Soon, it became obvious that our AI tool was way too advanced for them, and why it was much easier for younger startups to start using us. But we didn't want to give up on them just yet so...
Because I grew up when the internet was still free, and I actually miss that a lot, we decided to create a free test management tool.
Our vision is still AI, but we learned AI is not the silver bullet large teams are wishing for. (We wrote something about it at https://harlequinetcie.substack.com/). Our hypothesis right now is that we can be that team building the right tools for each QA team, leveraging AI.
We would love to hear your thoughts on
(a) Should we make the project open-source? Any key features?
(b) Would you ever trust an entity to do your QA first pass?
Cheers,

value: Show HN: From selling AI to QA teams to building a smooth test-management app

author: harlequinetcie


value: Show HN: State-of-the-Art OCR API – First 50 Pages Free


value: beshrkayali

value:
Hi HN, I’ve been working on a macOS app idea for a few weeks and I’d like to get some feedback before putting it on the App Store.
GroupTab is an alternative app switcher for macOS. You can arrange running apps into row based groups, cycle through apps in a group like usual, or hop between groups to keep context and cut clutter. It uses Option+Tab as the main hot key to bring up the switcher and arrow-keys or hjkl (while holding option) to cycle apps or groups (regular tab also works for cycling apps in a row). It’s meant for keyboard heavy users who juggle many running apps and also think that the default switcher can turn into a crowded carousel.
It keeps the native feel: MRU ordering for apps and groups, and Shift+Tab to reverse. Setup is simple, drag apps between groups and assignments stick or ([while holding option] shift + up-down arrows / k-j) to move between apps between groups). There's a default group for unassigned apps.
I’d love feedback on:
- Does grouping improve your flow vs Cmd-Tab?
- Rough edges, bugs?
- Performance and general UX feel
Website with details and screenshots: https://beshr.com/grouptab/
Join the TestFlight build: https://testflight.apple.com/join/GhGVn9F2
Thanks!

value: Show HN: GroupTab – grouped app switcher for macOS (TestFlight)

author: beshrkayali


value: florianwueest

value: Show HN: I've updated the site that color-codes the world by language

author: florianwueest


value: DavidCanHelp

value: Show HN: DriftDB – An experimental append-only database with time-travel queries

author: DavidCanHelp


value: ijuarezz

value:
∙ No login, registration or Internet/data access required.
∙ It's written in Kotlin, makes use of Composables functions and the Google Nearby API.
∙ The intended audience is any group of people that want to communicate simple opinions and see what the general consensus is.
∙ Available in English, Portuguese and Spanish.
Google Play: https://play.google.com/store/apps/details?id=com.shout_app
You can email me at:     i j u a r e z . d e v @ g m a i l . c o m

value: Show HN: Shout is an Android app to post opinions using the Google Nearby API

author: ijuarezz


value: arrdalan

value:
Several months ago, I posted in Show HN (https://news.ycombinator.com/item?id=42284412) about this project (previously named Privastead, now changed to Secluso). It's a privacy-preserving home security camera that uses OpenMLS for end-to-end encryption between the camera and the mobile app. The post received a good amount of attention and there were many good comments.
Since then, my project cofounder and I have made major improvements to the project. The project previously would act as a hub for an IP camera, which was otherwise closed source. But now, our camera software can also run directly on a Raspberry Pi (even one as weak as a Raspberry Pi Zero 2W), resulting in a security camera with a fully open source software stack. In addition, our Raspberry Pi-based camera can perform AI to detect people/pets/vehicles and send notifications. Moreover, our released camera binary can be verified using reproducible builds and our app now runs on iOS as well as Android. You can use this project to turn your Raspberry Pi into a fully functional and (more important) private security camera. Please check it out, use it, and provide us with feedback!
In addition, we built a prototype of a standalone home security camera using this open source project and a Raspberry Pi. Please check it out here (https://secluso.com/). It's not meant to replace the open source project, but to explore whether a plug-and-play camera could make it easier for people who are interested but don't have time to set up our project on a Raspberry Pi. We're curious if this kind of device would be useful to the community. If you'd like updates on our progress on that front, you can join our mailing list on the site.
Finally, we'd love to hear your feedback and ideas on how we can improve the project. And we always welcome contributions to our open source project.
Our site: https://secluso.com

value: Show HN: Update: Open-source private home security camera(end-to-end encryption)

author: arrdalan


value: pcrausaz

value: Show HN: Worried about your pet? Health assessments with instant answers

author: pcrausaz


value: stevius

value:
I've built Proxmox-GitOps, a self-bootstrapping GitOps platform that automates provisioning, configuration, and orchestration of Linux containers (LXC) on Proxmox VE. It turns an entire homelab into version-controlled code, with a focus on deterministic, idempotent deployments. It's now updated for Proxmox 9.0 and Debian Trixie.
GitHub: https://github.com/stevius10/Proxmox-GitOps
*Overview:*
It creates a self-sufficient CI/CD environment using Gitea, Act Runner, Ansible, and Chef (Cinc). Start with one command in Docker, which then deploys the full system to Proxmox. The control plane runs in containers it manages, ensuring reproducibility—no drift, easy rollbacks via Git.
*Key Features:*
- *One-command bootstrap:* Deploys from local Docker to Proxmox via API.
- *Monorepo structure:* Central codebase with submodules for modular container defs (e.g., Home Assistant stack: MQTT broker, Zigbee bridge, reverse proxy).
- *Recursive self-management:* Pipeline runs inside its own containers; push code to auto-provision and configure.
- *IaC consistency:* Ansible for provisioning, Chef for internal config; shared env vars propagate automatically.
- *Extensible:* Add custom containers via Cinc (Ruby) cookbooks
- *Stateless & reproducible:* Git as state engine; snapshots for backups/rollbacks.

value: Show HN: Proxmox-GitOps: Recursive IaC LXC Container Automation

author: stevius


value: A game made with vanilla JS and HTML5 Canvas. The goal is to trap bouncing balls by drawing boundaries over them but the balls hate your cursor so they will try to run away.<p>--There is a paint pollock option. It's inspired by jackson pollock, the painter. if you let it run for 5,6 minutes, the screen will turn into a pollock painting (-ish).<p>--It was a fun personal project.

value: Show HN: Freeze Trap

title: Show HN: Freeze Trap


value: xmorse

value: Show HN: Sentries – All JavaScript Runtimes in One Sentry NPM Package

author: xmorse


value: Aherontas

value:
Hey all!
I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems.
To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/)
https://github.com/Aherontas/Pycon_Greece_2025_Presentation_...
The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration.
Features:
- Multiple agents running in containers
- MCP servers (Brave search, GitHub, filesystem, etc.) as tools
- A2A communication between services
- Minimal UI for experimentation for Tech Trend - repo analysis
I built this repo because most agent frameworks look great in isolated demos, but fall apart when you try to glue agents together into a real application. My goal was to help people experiment with these patterns and move closer to real-world use cases.
It’s not production-grade, but would love feedback, criticism, or war stories from anyone who’s tried building actual multi-agent systems.
Big questions:
Do you think agent-to-agent protocols like MCP/A2A will stick?
Or will the future be mostly single powerful LLMs with plugin stacks?
Thanks — excited to hear what the HN crowd thinks!

value: Show HN: AI-powered web service combining FastAPI, Pydantic-AI, and MCP servers

author: Aherontas


value: qflop

value:
Demo: https://youtu.be/pnznDL9SZvI
PaperSync was a project was made by two CS freshmen, Matthew Li (me!) and Michael Li, in 24 hours during HackCMU.
At a high level, we built PaperSync to make reading research papers easier and more collaborative.
Users can reference any part of the paper, ask anything they want, and have other users reply, all within the paper itself!
If you are interested in our work, we would love to talk! Reach out to us at mqli@andrew.cmu.edu or mdli2@andrew.cmu.edu.

value: Show HN: PaperSync, making ArXiv papers collaborative

author: qflop


value: Show HN: Simple referral cards to turn intros into meetings


value: cheekyprogram

value: I created a SaaS that lets anyone create funny public service announcements for any situation or message. Chose from a predefined set of voices and there is an option to enhance your message using AI to make it sound better. Enjoy!

value: Show HN: EpicPSA – Create PSA's for any message

author: cheekyprogram


value: TonyPeakman

value:
TL;DR: dagger.js is a buildless, runtime-only micro-framework that plays nicely with native Web Components. It uses HTML-first directives (e.g. +click, +load) so you can ship a page by dropping a single <script> from a CDN—no bundlers, no compile step.
Why I built it
Modern stacks are powerful but often heavy: bundlers, compile steps, framework DSLs, local CLIs. For internal tools, small apps, and edge/serverless deployments, I wanted something you can view-source, paste into a page, and ship.
What it is:
Runtime-only: no build or VDOM compile; hydrate behaviors directly on HTML.
HTML directives: e.g. +click, lifecycle +load / +loaded / +unload / +unloaded.
Zero APIs: dagger.js works in pure declarative mode, modules and directives provide everything you need to build your application.
Web-Components-first: works alongside Custom Elements; keep concerns local.
Distributed modules: load small, focused script modules via CDN.
Progressive enhancement: the page renders without a build step.
Use cases:
Admin panels & dashboards that don’t warrant a full toolchain
Embed widgets, docs-sites with interactive bits
Edge/serverless apps where cold start and simplicity matter
Links
GitHub: https://github.com/dagger8224/dagger.js
Docs/Guide: https://daggerjs.org
Examples: https://codepen.io/dagger8224/pens
I’d love feedback on edge-cases, and where it breaks. Happy to answer tough questions here.

value: Show HN: Dagger.js – A buildless, runtime-only JavaScript micro-framework

author: TonyPeakman


value: barissayli

value:
Many backend teams wrap API responses in a generic envelope (status, message, errors, data).
However, OpenAPI Generator doesn’t natively support generics — it usually generates one
wrapper class per endpoint, duplicating the same fields dozens of times.
I built a demo Spring Boot 3.4 microservice + OpenAPI 3.1 project that shows how to solve this with:
• A small Springdoc OpenApiCustomizer that tags wrapper schemas with vendor extensions
• A tiny Mustache template override that generates thin shells extending a reusable generic base
• Full CRUD example (create, get, update, delete) with type-safe client code
• Integration tests using MockWebServer
• HttpClient5 support for connection pooling and timeouts
Result: instead of dozens of duplicated wrappers, the generator emits a single reusable
`ServiceClientResponse<T>` base + thin endpoint-specific shells. Client code stays clean,
type-safe, and much easier to maintain.
GitHub repo (demo code):
https://github.com/bsayli/spring-boot-openapi-generics-clien...
Detailed write-up (Medium article):
https://medium.com/@baris.sayli/type-safe-generic-api-respon...
Would love feedback from the HN community

value: Show HN: Spring Boot and OpenAPI Generator – type-safe clients with generics

author: barissayli


value: theYipster

value: An install script to create a strong and stable blend of Omarchy on  top of CachyOS. You must install CachyOS first (please read the README file.)<p>Feedback and contributions welcome!

value: Show HN: Omarchy on CachyOS

author: theYipster

title: Show HN: Omarchy on CachyOS


value:
I’ve been experimenting with running LLMs directly on consumer devices. Aotol AI is an iOS app that runs a quantized model entirely on-device, with no network calls.
What it does:
- Fully offline LLM chat (works even with no signal)
- Multilingual text + voice (switch languages on the fly)
- Conversations stay on your phone (no data sent out)
How it works:
- Model: Llama 3.2 3B (quantized q4f16)
- Size: ~2 GB app bundle
- Inference: uses MLC-LLM + TVM runtime, optimized for iOS
- Average response: ~1–2s/token on iPhone 15 Pro Max
- Added voice chat using AVSpeechSynthesizer + SFSpeechRecognizer
Why:
I wanted to test if “desktop-grade” LLM experiences could run locally on a phone, both for privacy and offline availability.
Limitations:
- Accuracy is ~70% for general QA (small model, quantized)
- Long prompts will slow down
- Memory footprint is tight on older devices
Download (iOS): https://apps.apple.com/app/aotol-ai-private-on-device-ai/id6...
I’d love feedback from anyone experimenting with:
- Smaller models on-device (sub-4B)
- Optimizing quantization for speed vs accuracy
- UX patterns for chat when inference can stall

value: Show HN: Aotol AI – Offline LLM app runs on iOS with voice and multilingual


value: mwitiderrick

value: Show HN: I made an app that turns scripts to videos in minutes

author: mwitiderrick


value: denshadeds

value:
The Wollebol app lets you visualize dependencies between classes in your project's package structure.
It is language-agnostic, but you need to generate the dependency data yourself. For Java projects, a helpful Python script (wollebol.py) is provided.
github: https://github.com/denshade/wollebol/
demo: https://thelaboflieven.info/wollebol/

value: Show HN: Wollebol a Simple Dependency Visualizer

author: denshadeds


value: kaffediem

value:
I got tired of seeing the same breaking news story repeated across multiple newspapers, so I built a newsletter RSS feed which clusters similar articles together, and delivers a clean and deduplicated email to your inbox daily at your schedule.
It's inspired by newsletters like TLDR[1], but with a key difference: you can follow your own feeds rather than someones curated selection.
It works nicely for regular newspapers, Substack and YouTube but is not suited for following feeds with 20+ new items per day (e.g. Reddit)
[1]: https://tldr.tech/

value: Show HN: One daily email with all your news clustered

author: kaffediem


value:
Hi HN — we built Celestial Fortunes, an AI product that synthesizes Eastern traditions (I-Ching, Zi Wei) with Western astrology to produce concise, personalized insights. It’s multilingual (English/中文/繁體) and aims to turn “cosmic wisdom” into practical guidance for life, love, and career.
Why
Most readings feel generic or siloed. We wanted a single view that compares and reconciles East + West perspectives, then distills them into clear takeaways.

value: Show HN: Celestial Fortunes – AI Blends Eastern and Western Astrology


value: FlorinDobinciuc

value:
Hey HN,
We just launched https://paje.ai — a tool that takes your LinkedIn profile and instantly generates a live personal website.
Why we built it:
Most people never make a personal site because:
- They don’t know how to design
- They don’t want to spend hours setting it up
- They don’t want to maintain it
What it does:
Paste your LinkedIn profile URL → get a personal site in under 2 minutes
Make AI-powered edits to sections (about, experience, etc.)
[Example]: Publish instantly at https://paje.ai/site/baird
We’d love feedback:
Who do you think would find this most useful (job seekers, freelancers, indie hackers)?
What’s missing that would make it valuable enough to pay for?
Try it here: https://paje.ai
Thanks
- Florin

value: Show HN: Instantly turn your LinkedIn into a personal website with AI

author: FlorinDobinciuc


value: glennhv

value:
I was an avid SEObot user, but I found the monthly cost too high. That's why I decided to build my own AI Seo tool for Wordpress, where you can just enter your OpenAI api key and get started.
It's the release of the first version, where you can:
- generate articles in your tone and preferred intent
- generate headlines to give you fresh ideas
- scan your website & get an idea for keyword clusters
- generate, expand and rewrite text
Right now there's support for 4 languages (English, French, German & Dutch), but I can add new languages when requested. All OpenAI models are supported, so you can choose how much you want to spend on your content.
Happy to hear your feedback!

value: Show HN: AI SEO in WordPress with your own OpenAI key

author: glennhv


value: cindori

value:
Hi HN, I'm Oskar, a solo indie Mac developer from Sweden. For those in the Mac community, you might know me from my other apps like Sensei and Trim Enabler.
For years, I've been frustrated by the lack of customisation of macOS. In particular the Lock Screen which supports animated wallpapers, but only ones provided by Apple. There's never been a way to add your own personal videos.
I decided to figure out how to solve this, and the result is Backdrop 2.0. Backdrop is my Live Wallpaper app for Mac, it can play video wallpapers on your desktop. And now it can play on your Lock Screen too.
The core technical challenge, as you can imagine, came from trying to do something that Apple otherwise does not allow. However, through extensive reverse engineering of the macOS wallpaper system, I figured out a way to provide Backdrop wallpapers to the system in a way that allows them to play on the lock screen, and even appear in a custom section in System Settings.
I'm here all day to answer any questions—especially about the reverse engineering process, the challenges of integrating with macOS, or the experience of being an indie Mac developer.
Would love to hear your thoughts and feedback.

value: Show HN: I reverse engineered macOS to allow custom Lock Screen wallpapers

author: cindori


value: adrai

value:
Hi HN,
I built this because I think adding real-time features like chat should be much easier for frontend developers.
This is a complete, multi-room chat app you can clone and have running in a couple of minutes. It's powered by a serverless tool I'm creating called Vaultrice.
Looking for feedback on the DX and the overall concept.
Thanks!

value: Show HN: A Vite and React starter kit for real-time chat with no back end

author: adrai


value: Show HN: A Product Analytics Framework

title: Show HN: A Product Analytics Framework


value: Shobba

value: Show HN: SUMRY - Turn your HealthKit data into summaries, maps and insights

author: Shobba


value: Show HN: A day in the life of a GitHub moderator


value: satyamskillz

value:
Hi All,
I’ve been working on an open-source SDK to make collecting user feedback on your website less painful. Instead of wasting time on building your own feedback system and boring forms, my SDK lets users leave feedback directly on your website—with all the context devs actually need.
Here’s what it currently does:
 Users can select any element on the page
 Auto-captures logs, metadata & screenshots
 Sends instant notifications (Slack, Discord, etc.)
 Lets you reward users → boosts engagement & conversions
 Gives users a tracking link → builds accountability & trust
 Self-host + customize the widget (work in progress)
My bigger goal is to automate the feedback loop:
1. Collect feedback
2. Reward users
3. Follow up with them
4. Provide devs with full context
5. (eventually) even suggest solutions
ASK: Please try the tool, contribute or give me feedback.
Repo: Github.com/satyamskillz/react-roast
Website: Roastnest.com

value: Show HN: I made SDK for collecting visual feedback – open-source, self-hostable

author: satyamskillz


value: moeinxyz

value:
Hi HN,
I built Ladderr, a voice agent for workplace soft skills. It runs coach-style 1:1 voice check-ins (at a cadence you choose) to keep you accountable and reflect on next steps, and it supports practice, feedback and role-play for common workplace scenarios (business English, giving/receiving feedback, stakeholder pushback, conflict resolution, self-advocacy).
Early MVP - free while I iterate; login required (no credit card).
For now I’m limiting testing to ~25 users so I can respond quickly and incorporate feedback. If you try it, I’d appreciate product feedback to help steer the direction.
Try it: https://ladderr.ai/
Thanks for reading.

value: Show HN: Ladderr, Voice-First AI Career Coach

author: moeinxyz


value: docsproX

value: Show HN: Top mobile scanner apps in 2025

author: docsproX


value: makilan

value: Show HN: Kafy – kubectl-style CLI for Kafka management

author: makilan


value: CrociDB

value:
Hello HN community,
I'd like to show this project I've been working for a few months. It's yet another TUI feed reader, but a bit different from the other alternatives available. First, I wanted to have all my feed entries downloaded locally, in a way that I could decide how to store and sync those files. Second important aspect would be have it look and feel good, still running on a terminal, so I could SSH into my VPS from anywhere and run it.
So I created bulletty. It's a TUI RSS/ATOM reader written in Rust and ratatui, that is looking good and feels just right to use. Of course, all I've done so far was to fulfill my needs, but I think it's already in a good state that it can be used and appreciated by others as well.
For the feeds, I implemented something similar to an Obisidian vault. The feed categories are directories in your system and the entries are just markdown files. All your library is within `~/.local/share/bulletty`, so that you can sync and backup that the way you want.
There are so many other interesting features I want to implement in this project, such as support themes, ability to highlight and write notes on articles, display images (using kitty image protocol or sixel), a webview for the articles, etc. I'm working on it on my free time, so I'm really interested in other people's contribution. I also set it up for `hacktoberfest`, and I added some issues that I think would be good to have. If you feel you want to contribute, please do by sending Pull Requests, or creating new Issues for bugs or creating a new Discussion thread to talk about possible features or other ideas.
If you wanna try it, `cargo install bulletty`! Or just check the GitHub page for more detailed instructions.
Thanks and have a good day everybody!

value: Show HN: Bulletty, a pretty TUI feed reader that stores articles as Markdown

author: CrociDB


value: Show HN: A tool to launch your website in minutes


value: mawad

value: Show HN: Iris – Distributed GPU Programming with RMA in Pure Python/Triton

author: mawad


value:
Hey HN,
My co-author and I just published a paper on arXiv that formalises a framework we've been using successfully in probabilistic logic for many years. We decided it was time to properly lay out its foundations for classical propositional logic.
We cast propositional logic into a formal algebra where logical formulas are represented by sparse matrices. State Algebra isn't an algorithm in itself, but rather a language for manipulating Boolean functions. It provides a new set of tools that lets you express and reformulate existing optimization heuristics (like those from modern SAT solvers) and design completely new ones. State Algebra is trading the strict canonicity of ROBDDs for greater representational flexibility.
For those interested in abstract-algebraic logic, we build a self-contained formalism from the ground up. The core building block is an object we call a "t-object," which forms the basis of the algebra. It provides a different way to look at the structure of logical problems.
The algebra naturally extends to handle real-valued coefficients, which turns it into a tool for probabilistic logic and Weighted Model Counting.
The paper is a bit of a deep dive into the maths, but we'd love to hear your thoughts. We'll be in the comments to answer any questions. Critiques are very welcome!
Link: https://arxiv.org/abs/2509.10326

value: Show HN: State Algebra, new algebraic framework for logic, an alternative to BDD


value: TheComputerM

value: A WebRTC based toy blockchain network, hopefully useful for learning and demonstrations.

value: Show HN: Demochain, a toy blockchain network that runs on the browser

author: TheComputerM


value: full-stack-dev

value:
Hey HN. I made an extension that tries to tackles one problem: the mindless "autopilot" visits to sites that waste your time.
It applies the 20-second rule by adding a brief, intentional pause before loading a site you've marked as a distraction. Unlike a hard blocker, the goal isn't to prevent access but to enforce a conscious decision before you dive in.
The extension is free and has no ads. To see if it's actually effective, I collect a small amount of anonymous event data—like "install," "pause screen shown," and whether the user proceeded or closed the tab. No personal data, browsing history, or IP addresses are ever collected.
It's available for Chrome and Firefox (including Android). I'd love to hear your feedback on the idea.
Chrome: https://chromewebstore.google.com/detail/maeapbjpagkoiaeignc...
Firefox: https://addons.mozilla.org/en-US/firefox/addon/the-20s-rule-...

value: Show HN: A browser extension to curb bad habits using the 20-second rule

author: full-stack-dev


value: lexokoh

value: Show HN: I built a tool to help me kill dev ports

author: lexokoh


value: Show HN: I tried learning Angular, ended up making a Parcel Locker Simulator


value: cofeess

value: Show HN: Open-source business management tool for small business

author: cofeess


value: jcoulaud

value:
I often get strange or funny outputs from LLMs (ChatGPT, Claude, etc.), and wanted a simple way to save and share them. So I built this small side project https://llmquotes.com.
What it does:
- Submit quotes (no login needed, optional Twitter handle)
- Upvote and favorite
- Spam is manually moderated (for now)
- Best ones also get posted to https://x.com/LlmQuotes
Backstory:
This started because my friends and I kept screenshotting odd LLM replies and losing them in chats. I built a little place to collect them. Nothing fancy, just centralizing and sharing.
Tech:
Small Next.js app with Postgres, running on Vercel. Open source.
Curious if others also save weird LLM replies, or if I’m the only one doing this.

value: Show HN: I built LLM Quotes to collect and share funny/weird LLM outputs

author: jcoulaud


value: thekuanysh

value:
Kuan here, solo dev. I was sinking hours into YouTube “learning” videos—one leads to five, killing deep work focus. My solution: Pull the core (summaries, insights, action steps) and skip the rest.
Launched Wordspike this week: Paste a YouTube URL (web app or browser extension), and it generates structured text output right away.
Key features:
- “Spikes”: AI-generated summary + key ideas + insights + actionable steps (minimalist, no fluff).
- Multilingual: Handles non-English videos natively (e.g., I’m extracting from Chinese tech talks as I don’t understand Chinese).
- Exports: PDF/EPUB, or sent directly to Kindle in ~90 seconds.
Tech: End-to-end with Bun/JS backend, Redis for async processing, minimalist UI. No team or funding—just bootstrapping *to solve my own problem*.
Early traction: 20+ users in 4 days; strong feedback on trials.
Try it: https://wordspike.com (freemium, just paste a YouTube URL to test).
Curious: What features would hook you? Tech thoughts on multilingual LLM handling or async scaling?
Happy to discuss stack, async workers, or non-English LLM tweaks.
How do you manage video overload in your workflow?

value: Show HN: Wordspike–AI spikes from any YouTube video (multilang, Kindle export)

author: thekuanysh


value: FinnLobsien

value: Show HN: I vibe-coded an app that roasts your pricing page (in beta)

author: FinnLobsien


value: zuhaib-rasheed

value:
Hey HN,
We just open-sourced Magicnode
, a visual builder for AI apps. It lets you create AI workflows by dragging and connecting nodes — kind of like Canva for AI apps.
What it does
Visual drag-and-drop interface for building AI workflows
Connect LLMs, APIs, and UI components without code
Export/share apps as micro-apps
Runs locally or in the cloud
Why open source?
Most AI builders are closed or proprietary. We wanted a flexible, community-driven platform where developers can:
Extend with custom nodes
Self-host without vendor lock-in
Share and reuse AI apps
Try it
Repo: https://github.com/magicnode-open/magicnode-core
Quickstart: git clone → npm install → npm run dev
We’d love feedback from HN:
What’s missing for you to use this in real projects?
Which integrations/nodes would be most useful?
How do you think we should grow the community around it?
Thanks for checking it out!

value: Show HN: Magicnode – Open-source AI app builder (like Canva for AI apps)

author: zuhaib-rasheed


value: anishathalye

value: Show HN: Semlib – Semantic Data Processing

author: anishathalye


value: rh-app-dev

value:
I’ve been working on a tool to address one of the biggest problems I see with digital content: the inability to prove that it was captured by a real human, on a real device, at a specific time — without manipulation or AI involvement.
Witness by Reel Human is a privacy-first camera app that generates cryptographically signed photos and videos. Each file includes an embedded JSON manifest with:
 - The exact capture time
 - Device info (not user identity)
 - The app version and signature metadata
The manifest is stored inside the media file (MP4/JPEG) and travels with it, even if shared. The result is a verifiable, human-authored piece of content.
What’s working now (POC):
 - Android and iOS apps (available for testing)
 - Signed JSON manifests inside every photo/video
 - No accounts, no tracking, no upload
What’s coming:
 - Public verification portal (in progress)
 - Registry backend with optional verification logging
 - Open API for platforms to verify content at scale
I’d love your feedback on:
 - The idea and approach
 - Security model (crypto choices, manifest design, etc.)
 - Use cases beyond journalism (legal, education, social media)
Site: https://reel-human.com
POC App:  https://testflight.apple.com/join/GzfTsCNF
Android:  https://play.google.com/store/apps/details?id=com.reelhuman....
iOS:
Ask me anything — I’m solo-building this because I think trusted content should be a human right.

value: Show HN: Witness – Capture signed photos/videos with embedded proof-of-origin

author: rh-app-dev


value: pmihaylov

value: Show HN: Claude Control – open-source background agents for Claude Code

author: pmihaylov


value: intheleantime

value:
Hi HN!
I have been working on AI agent Flows for some time now and always found it annoying to have to redeploy my application for small changes to flows, prompts, model definitions etc.
This is why I build Flowshapr (https://flowshapr.ai). It let's you create and manage AI flows and prompts using a simple UI and then execute those flows with a small client side SDK and a one line code integration.
The tool is based on Genkit and will generate Genkit code on the fly if you want to deploy yourself.
This early version can manage simple flows, prompts, generate Genkit code, execute flows remotely and show traces. I am currently working on vector store integrations and more tools.
The repo is here: https://github.com/flowshapr/flowshapr
I'd love to hear your feedback and learn more about your use cases!

value: Show HN: Flowshapr – Open-Source Agent Flow GUI and Manager

author: intheleantime


value: adrianshp

value: Basically I got tired of chatbots failing in weird ways with real users. So this tool lets you create fake AI users (with different personas and goals) to automatically have conversations with your bot and find bugs.

value: Show HN: Deploy Realistic Personas to Run Conversations in Minutes

author: adrianshp


value: damienwebdev

value:
Hello everyone!
I’ve been building an Open Source Ecommerce framework for Angular called Daffodil. I think Daffodil is really cool because it allows you to connect to any arbitrary ecommerce platform. I’ve been hacking away at it slowly (for 7 years now) as I’ve had time and it's finally feeling “ready”. I would love feedback from anyone who’s spent any time in ecommerce (especially as a frontend developer).
For those who are not javascript ecosystem devs, here’s a demo of the concept: https://demo.daff.io/
For those who are familiar with Angular, you can just run the following from a new Angular app (use Angular 19, we’re working on support for Angular 20!) to get the exact same result as the demo above:
```bash
ng add @daffodil/commerce
```
I’m trying to solve two distinct challenges:
First, I absolutely hate having to learn a new ecommerce platform. We have drivers for printers, mice, keyboards, microphones, and many other physical widgets in the operating system, why not have them for ecommerce software? It’s not that I hate the existing platforms, their UIs or APIs, it's that every platform repeats the same concepts and I always have to learn some new fangled way of doing the same thing. I’ve long desired for these platforms to act more like operating systems on the Web than like custom built software. Ideally, I would like to call them through a standard interface and forget about their existence beyond that.
Second, I’d like to keep it simple to start. I’d like to (on day 1) not have to set up any additional software beyond the core frontend stack (essentially yarn/npm + Angular). All too often, I’m forced to set up docker-compose, Kubernetes, pay for a SaaS, wait for IT at the merchant to get me access, or run a VM somewhere just to build some UI for an ecommerce platform that a company uses. More often than not, I just want to start up a little local http server and start writing.
I currently have support for Magento/MageOS/Adobe Commerce, I have partial support for Shopify and I recently wrote a product driver for Medusa - https://github.com/graycoreio/daffodil/pull/3939.
Finally, if you’re thinking “this isn’t performant, can’t you just do all of this with GraphQl on the server”, you’re exactly correct! That’s where I’d like to get to eventually, but that’s a “yet another tool” barrier to “getting started” that I’d like to be able to allow developers to do without for as long as I can in the development cycle. I’m shooting to eventually ship the same “driver” code that we run in the browser in a GraphQl server once all is said and done with just another driver (albeit much simpler than all the others) that uses the native GraphQl format.
Any suggestions for drivers and platforms are welcome, though I can’t promise I will implement them. :)

value: Show HN: Daffodil – Open-Source Ecommerce Framework to connect to any platform

author: damienwebdev


value: pmig

value: Hey HN, we’ve been experimenting a lot with MCP servers lately, and one of the most time-consuming challenges has been connecting MCP clients to remote MCP servers. To solve this, we built a library that generates them on the fly, enabling 1-click installation buttons and links for most clients out there.<p>Feel free to try out the generator and use it to improve the README of your remote MCP server with the generated markdown. You can even configure the library to return HTML instructions if someone accesses your remote MCP server via the web.

value: Show HN: MCP Server Installation Instructions Generator

author: pmig


value: lmrl

value:
Hey!
I saw this post a few days ago on HN [1] about the new Nano Banana model and decided to play with it. It's incredible (Mostly for editing IMHO)! The thing is, Google AI Studio is great for chat... for images, the UI is not ideal.
So I decided to make my own thing: an infinite canvas for AI image exploration. :)
Right now it only supports Nano Banana, but the plan is to include OpenAI, Replicate, and fal.ai this week!
Would love to hear any feedback. Feel free to propose changes as well!
Github: https://github.com/za01br/koubou
[1] https://news.ycombinator.com/item?id=45215869

value: Show HN: A canvas to explore AI image models (open-source, BYOK)

author: lmrl


value: exaroth

value:
As a long time user of i3wm I've been frustrated by lack of bar plugins can display news headlines of my choosing, those that are available tend to use proprietary API's/feeds, hence I decided to create my own.
I3 News uses standard RSS/Atom links which get turned to rotating news headlines in the bar plugin of your choosing, app also incorporates support for scrollable snippets and handler for opening news links in browser.
Currently supported i3/sway plugin list:
- i3blocks
- waybar
- polybar
- i3status
Critique/suggestions are very welcome.

value: Show HN: Interactive news headline generator compatible with i3/sway

author: exaroth


value: ehsanaslani

value:
Convert any Zustand sotres to a multi-player store by wrapping them in this middleware.
Please view this blog for more details and links to demo applications, examples and github repos:
https://hpkv.io/blog/2025/09/zustand-multiplayer-middleware

value: Show HN: Realtime Multiplayer Middleware for Zustand

author: ehsanaslani


value: johnmwilkinson

value:
Hey HN!
I wrote a book on programming called The Elements of Code. I put the entire book online here: https://elementsofcode.io/
When mentoring (usually new) programmers, I noticed there were a few common mistakes that seemed to account for about 80% of the complexity in their code. I couldn’t find a concise guide to fixing those mistakes, so I decided to write one.
The title is an homage to The Elements of Style by Strunk and White, which is the classic guide for communicating well using prose. That guide is quite tactical in nature, and I wanted to parallel its focus in  The Elements of Code. As a result, TEOC tries not to focus on abstract concepts, and instead targets concrete implementation. It avoids discussing software design in favor of the minutiae of code construction. Of course, the design and implementation, the strategy and the tactics, are never entirely separate.  When necessary, some abstract concepts are included to help provide context.
The primary focus of the book is on communication: how can we write code that other programmers will be able to understand? How can we reduce the time it takes them to understand?
I put it all online for free because I would rather the book be accessible and read than make a few bucks (though purchases are certainly welcome!). My sincere hope is that readers find it helpful, and it gives them new tools and a new way to think about writing code.
I’m interested to hear what you think, and I’ll try to respond to questions. Thanks!

value: Show HN: I wrote a book: The Elements of Code

author: johnmwilkinson


value: playnext

value: Show HN: Virtual Monitors in X11 and I3

author: playnext

title: Show HN: Virtual Monitors in X11 and I3


value: PictureRank

value:
Hey Hacker News,
I built this little tool for my own personal projects to collect feedback from my users as they visit my site. So far I've found it pretty useful for collecting feedback and prioritizing my roadmap as I know what my users are complaining about this most.
Please try it out and tell me what you think and give me some feedback, even if you hate it.

value: Show HN: I built this to collect feedback from my website visitors

author: PictureRank


value: thomcrowe

value:
Hey HN,
We built a mobile app for short-term rental hosts and property managers to manage dynamic pricing, bookings, and calendars on the go. Our team has worked on revenue management for hospitality since 2013, and we’ve seen that many hosts (ourselves included) are rarely behind a desk—they’re out in the field, meeting owners, handling check-ins, or updating prices from their phones at odd hours.
We wanted to fix a longstanding pain point: revenue management software for our space has always been web-first and clunky on mobile. This was frustrating, as over 60% of internet traffic is now mobile, and property managers need to react to market changes and new bookings quickly, no matter where they are.
Here's what the new app does:
Instantly adjust prices for listings, apply overrides, or respond to spikes in demand right from a phone.
See each new booking as it happens (with details), so revenue planning is less guesswork.
Access all property calendars in a streamlined, mobile-friendly view, designed for multiple listings.
Get up-to-date pricing suggestions and alerts, without logging in on a full desktop.
Set up is simple—a couple of taps and you’re live.
One of our early users said: “It’s everything you need for on the go. I was able to set it up quickly and update prices at an open house while answering questions from owners.”
Free to download—no credit card required to try it out. The app is on the App Store and Google Play: just search for Beyond Pricing Mobile. If you want a walkthrough or run into bugs, we’re here answering questions.
Curious what HN thinks: does this solve a pain you’ve had with STR management? What features would make this genuinely useful, or what’s missing? Would appreciate feedback, requests, or blunt criticism—we want to improve this for busy hosts/managers like us.
Thanks!

value: Show HN: Beyond – Dynamic Pricing App for Short-Term Rentals

author: thomcrowe


value: ieuanking

value: Show HN: AI Research Environment (AiRE), search/chat ArXiv/Semantic Scholar pprs

author: ieuanking


value: davidpelayo

value: Show HN: Crosswire Online - Compare Headlines by Country

author: davidpelayo


value: Show HN: Embedible – AI hardware copilot for microcontrollers


value: tritondev

value: Show HN: Building an open-source agentic terminal

author: tritondev


value: Show HN: LLM Round‑Trip Translation Benchmark


value: Show HN: A simple header-only profiler for C/C++