value: qwool

value: Show HN: Soup.lua: making Lua do what it shouldn't

author: qwool


value: Charlieholtz

value: Show HN: Chorus is now open source

author: Charlieholtz

title: Show HN: Chorus is now open source


value: anandbaburajan

value: Show HN: Befa.ke – Destroy Instagram

author: anandbaburajan

title: Show HN: Befa.ke – Destroy Instagram


value: willswire

value: Show HN: DoD CAC Authentication with Cloudflare Workers

author: willswire


value: Show HN: A Grafana you can share with anyone


value: temidaradev

value:
I kept losing receipts and missing warranty deadlines, so I built this tool for myself.
The idea is simple:
You forward purchase emails, and it extracts receipt details (store, amount, warranty dates) and reminds you before warranties expire. Also there is manual data entry, pdf drag and drop too
It’s intentionally small and boring, but useful.
Built with Go and React.
Happy to answer questions.

value: Show HN: I built a small tool to track receipts and warranty dates

author: temidaradev


value:
I built a REST API for REVE (the 60K-hour EEG foundation model
released in October). It's free to use: https://web-production-73111.up.railway.app/docs
Use case: If you're building anything with EEG and don't want to
deploy the model yourself, just hit the API with raw signals and
get back embeddings.
Also working on training a better model on private data from devices/
labs. If you're collecting EEG data and want to partner, DM me.
Feedback welcome!

value: Show HN: Free API for REVE EEG Foundation Model


value: lpipe

value:
I got tired of maintaining resume_google.docx, resume_amazon.docx, and resume_v5_final.pdf.
Version control for resumes is broken. So I built a "Single Source of Truth" system.
The Logic:
The Database: You dump everything (all projects, 10 years of history) into one JSON-like structure.
The Query: You paste a Job Description.
The Render: The system "queries" your history for matching skills/bullets and renders a tailored 1-page PDF using a custom Puppeteer engine.
It’s basically CI/CD for job applications.
Tech Stack:
Next.js 15 (App Router)
NestJS (Backend logic)
Puppeteer (Custom rendering engine to fix page-break issues)
Live Demo: https://resumefy.pro
I’m open to roasting on the code or the "matching" logic.

value: Show HN: I built a "Headless CMS" for my resume (Next.js and Puppeteer)

author: lpipe


value: alvinunreal

value: Show HN: Open-Source Project Discovery and Analytics

author: alvinunreal


value: Show HN: Troql – Auto-generate architecture maps from GitHub repos


value:
I made a clone of the workflow described by Dex Horthy in Advanced Context Engineering in the form of Claude Code Plugin where you can download at https://github.com/billlyzhaoyh/humanlayer-clone.
It enables you to step through the three steps of using coding agent to accomplish complex tasks: research, plan and implement. This is also backed by a Linear based automation flow that you can follow the plug in to setup. The plugin will help you set up the github workflow if you wish or you can copy paste from my repo.
Let me know your thoughts and feedback!

value: Show HN: I made a HumanLayer-clone Claude Code plugin


value: thebrokenway

value: Show HN: Brightened Engine – deterministic incremental computation benchmarks

author: thebrokenway


value: joozio

value:
Hey HN! I built LLMatcher in 10 hours to solve a problem I kept having: which AI model should I actually use?
Instead of trusting marketing claims, I created a blind testing platform where you compare two anonymous AI responses and vote for the better one.
After 50 votes, you get personalized recommendations based on YOUR preferences — not some generic benchmark.
Key features:
- Top AI models (GPT-5.2, Claude Opus 4.5, Gemini 3 Pro, Grok 4+)
- Blind side-by-side comparison
- Personal AI toolkit (unlocked after 50 votes)
- Community-powered rankings by category
- Expanding model selection based on demand
Tech stack: Next.js 16, Supabase, Tailwind, OpenRouter API, deployed on DigitalOcean.
Total investment: ~$97 (domain, hosting, tokens).
Would love your feedback — especially on:
1. Is 50 votes too high a barrier to unlock recommendations?
2. How would you monetize something like this?
3. What categories/prompts would you want to test?
Live at: https://llmatcher.com/

value: Show HN: LLMatcher – Find your perfect AI through blind voting

author: joozio


value: dgellow

value:
Built this over the past two days after yet another release that resulted in 12+ emails for a single repository. npm has this frustrating notion that spamming you with emails somehow keeps your account secure. I built it for myself, but given that npm staff gave up on that discussion a while ago, why not turn it into an actual micro-SaaS? :)
How it works: you set up an email filter to forward npm notifications to a unique address. npmDigest batches them and sends you a single digest (daily/weekly/monthly).
It's a one time setup, and you only pay for months where emails have been forwarded.
Happy to answer any questions you would have when I wake up (Central Europe time), and I would love feedback!

value: Show HN: I built a service to fix NPM's email flood problem

author: dgellow


value: ersinesen

value: Show HN: Vibe coded 3D Scene Animation Studio

author: ersinesen


value: grigio

value: Show HN: Binaural Beat Player

author: grigio

title: Show HN: Binaural Beat Player


value:
I kept opening Twitter to catch up on people I follow. 20 minutes later I'd close the app having scrolled through rage-bait and missed what I actually wanted to see.
So I built Full Signal. You pick the accounts. Every morning, their tweets get turned into a 5-minute digest — highlights, conversations, gems. No scrolling.
https://fullsignal.xyz
Would love feedback.

value: Show HN: Full Signal – Get the signal of Twitter without doomscrolling


value: akshayaggarwal

value:
Hi HN,
I’m Akshay. I built AMP because I was tired of my AI agents having "amnesia" the moment I closed the terminal.
Like many of you, I use Claude/Cursor daily. RAG is great for searching documentation, but it’s terrible for continuity. It chunks text blindly, losing the narrative. When I asked my agent "Why did we decide to use FastAPI last week?", it would hallucinate or just give me generic pros/cons because the specific context of our decision was lost in a vector soup.
So I decided to build a proper *Hippocampus* for my agents.
*What is it?*
AMP is a local-first memory server that sits between your agent and its LLM. It implements a "3-Layer Brain":
1.  *STM*: A scratchpad for what we are doing right now.
2.  *LTM*: Consolidated facts and insights (promoted from STM).
3.  *Galaxy Graph*: A force-directed knowledge graph (d3.js) that physically links related concepts.
*The Tech Stack*
*   *Protocol*: Built natively for the *Model Context Protocol (MCP)*. If you use Claude Desktop or Cursor, it works out of the box.
*   *Backend*: Python, FastAPI, SQLite (no docker needed).
*   *Search*: Hybrid (Keyword + Vector) using FastEmbed.
*   *Viz*: A 60fps local dashboard to actually see your agent's brain growing.
*Benchmarks*
I didn't want just another vector wrapper, so I focused heavily on retention. I benchmarked it against Mem0 (a popular alternative) on the LoCoMo dataset.
*   *AMP*: 81.6% Recall (Context-First)
*   *Mem0*: 21.7% Recall (Extraction-First)
It turns out that preserving the narrative (who/what/when) before summarizing is key to avoiding "I don't know" answers.
I’d love to hear your thoughts on the architecture. Does your agent need a hippocampus?
Repo: https://github.com/akshayaggarwal99/amp

value: Show HN: AMP – open-source memory server for AI agents (MCP, SQLite, D3.js)

author: akshayaggarwal


value: jklioewr

value: Powerlifting programming isn’t as complicated as spreadsheets make it look; once you strip away the noise, the structure fits comfortably on a phone. I think of it as two parts: plain sets/weight/reps/RPE/1RM, and the custom analytics you build on top. SigmaLifting handles the first part entirely on your phone with a mobile-first UI and a flexible data model that can express most spreadsheet-style programs. For the second part, you export the data and run it through your own tools (or an LLM) for whatever analysis you want.

value: Show HN: SigmaLifting – A protocol for powerlifting training data

author: jklioewr


value: Show HN: Brandcaster AI – On-brand Content Creator and Posting Agent


value: atgreen

value: I created this because sometimes I want more than rlwrap but less than emacs. icl aims to hit that middle sweet spot.<p>It's a terminal application with context-aware auto-complete, an interactive object inspector, auto-indentation, syntax colouring, persistent history, and much more.  It uses sly to communicate with the child lisp process and aims to be compatible with any sly-supporting implementation. I hope others find it useful!

value: Show HN: Interactive Common Lisp: An Enhanced REPL

author: atgreen


value: crazyguitar

value:
I’m sharing Libefaxx, an open-source microbenchmark for AWS Elastic Fabric Adapter (EFA) focused on GPU/CPU RDMA communication.
Most existing benchmarks (e.g., nccl-tests, NVSHMEM) measure collective libraries, which makes it hard to isolate raw EFA transport performance. With growing interest in GPU-Initiated Networking (GIN) (e.g., Deep-EP), we wanted a way to directly measure EFA latency, bandwidth, and scaling behavior at a lower level.
Libefaxx complements existing tools by helping engineers and researchers better understand and optimize inter-node communication for large-scale distributed training on AWS.

value: Show HN: Libefaxx – A Microbenchmark for AWS EFA GPU/CPU RDMA Communication

author: crazyguitar


value: TiernanDeFranco

value:
Hey all, I've been developing Perro Engine, a unique game engine written in Rust that allows you to use C#, TypeScript, or the engine DSL: Pup, to script your game, and the engine will transpile your scripts into Rust modules that interop with the engine without running different runtimes, interpreters, or VMs.
Doing this essentially gives you much more performance than a scripting layer since there's no bytecode having to be decoded and no runtime bloat.
It also allows for each language to support all the same features and access to the engines internal APIs because you don't have to worry about them ACTUALLY being implemented in that language and interfacing with the Rust core, it just IS Rust and it's just calling native functions in the api.
Let it be known that of course this means it is not REALLY C# or TypeScript that's unning, it's just the familiar syntax to avoid writing game logic in Rust if you don't want to. If you need to for performance reasons (like very specifically managing memory allocaiton, clones, borrows) then you are able to write a Rust script natively as if it was any other game script, it just needs to follow the structure and conventions the engine expects.
I'd appreciate any feedback and am happy to answer any questions, and if you don't mind starring the repo that'd be great!

value: Show HN: A game engine that transpiles your scripts to Rust for native perf

author: TiernanDeFranco


value: yoloshii

value:
Simple Apify actor that scrapes websites and indexes them in Google's new Gemini File Search API (launched Nov 6).
The workflow: Scrape → Clean content → Upload to Gemini → Get permanent queryable knowledge base with automatic citations.
Technical approach:
- Intelligent scraper selection from 5 Apify-native scrapers
- Automatic content cleaning (strips nav/ads/fluff)
- Uploads to Gemini File Search (persistent storage)
- Per-page PPE pricing ($0.02 start, $0.0015/page)
Potential use cases:
- Turn documentation into AI chatbots
- Make company wikis naturally searchable
- Build RAG apps without managing vector databases
Basically streamline your Gemini file search RAG ingestion with an Apify scraper run AIO.
You can also employ the actor programmatically with agents using Apify's actor mcp.
Built this over a weekend for the Apify 1M Actor Challenge. It's my first Apify actor, so curious to hear if the pricing makes sense.
Note* There is a banned websites to scrape list filter due to the constraints of the challenge. This will be lifted after the challenge ends (Jan 31, 2026).

value: Show HN: Scrape websites into queryable Gemini RAG knowledge bases

author: yoloshii


value: tamnd

value: Show HN: Wiki.txt

author: tamnd

title: Show HN: Wiki.txt


value: Codegres

value: Buy Source Code at https://codegres.lemonsqueezy.com/buy/5abaaea5-6803-41e9-95f...

value: Show HN: ZeroCRM – Simple CRM with Source Code

author: Codegres


value: ssssota

value: Browser-based bundle size analyzer using Rolldown. Inspired by Bundlephobia and Shakerphobia.

value: Show HN: Rolldphobia – Bundle size analyzer with tree-shaking using Rolldown

author: ssssota


value: bimsina

value:
I got tired of writing one-off scripts every time I needed to check what's in my local KV namespace or debug a D1 query while developing Cloudflare Workers apps. So I built this.
It's a simple dashboard you mount on a route (like /dashboard) that lets you:
- Browse and edit KV namespaces
- Run SQL queries against D1 databases
- Navigate R2 buckets and preview files
- See all your env bindings in one place
Works with Hono, Itty Router, TanStack Start, or plain Workers. Just add it as a dev dependency and import it where you need it.
Stack is HTMX + TailwindCSS + DaisyUI + AlpineJS.
GitHub: https://github.com/bimsina/cf-local-helpers

value: Show HN: CF Local Helpers – Dashboard for Cloudflare Workers Local Dev

author: bimsina


value: breezefox

value:
The biggest problem with Tic-Tac-Toe is that it almost always ends in a draw. Tic Tac Flip tries to fix that!
Learn the rules in Learning Mode or below:
- Winning Criteria: 3 Ghosts (Flipped O or X, which can be a mixture). It's not just 3 Os or 3 Xs anymore!
- Flipping Mechanic: When one or more lines having only O and X are formed, the minority of either all Os or all Xs get flipped to a Ghost, and the majority gets removed from the board. E.g., A line of 2 Os and 1 X leads to 1 X ghost and the removal of 2 Os.
- Active Flip: You can actively flip your O/X to a Ghost (or flip a ghost back) once per game.
- Placing Ghost Directly: You can place a "Ghost" piece directly as a final winning move (only once, and only when there are two existing ghosts in a line).
I'm looking for feedback on the game balance and learning curve. Specifically:
- Is the "Ghost" and "Flip" mechanic intuitive?
- Is the Learning Mode helpful?
- Is the game fair? Any rule adjustments needed?
- Any bugs or issues?
Any suggestions or comments would be much appreciated. Thank you in advance!

value: Show HN: Tic Tac Flip – A new strategic game based on Tic Tac Toe

author: breezefox


value:
Basically, paste any job URL and it automatically researches the job posting to draft personalized cover letters and resume tips.
You get to watch the AI research the role like a human would in real-time.
trylockedin.app

value: Show HN: I built this because finding a job f**king sucks


value: xiaoshumiao

value:
Hi HN
I built a Hazbin Hotel OC Maker, an AI-powered tool that helps fans create original characters (OCs) inspired by the Hazbin Hotel universe.
As a fan myself, I noticed that many creators struggle to turn vague ideas into a complete OC — especially when it comes to personality, backstory, visual traits, and tone consistency with the Hazbin Hotel style. Most tools focus only on images or only on text, so I wanted to combine both into a single workflow.
What it does
Generates original Hazbin Hotel–style characters (not existing canon characters)
Helps define:
Name & demon type
Personality traits
Backstory & motivations
Visual description suitable for artists or AI image tools
Designed for writers, roleplayers, and artists
Works entirely in the browser, no setup required
Why I made it
I’m building a broader AI OC creation platform, and this is one of the first focused generators aimed at a specific fandom. Hazbin Hotel has a very distinct tone and aesthetic, which made it an interesting challenge for prompt design and style control.
Link
Hazbin Hotel OC Maker
https://aiocmaker.com/oc-maker/hazbin-hotel-oc-maker
Notes
This is a fan-made tool and is not affiliated with Vivienne Medrano or A24
Feedback is very welcome — especially from writers and artists who create OCs regularly
Happy to answer any questions about the tech, prompts, or design decisions. Thanks for checking it out!
— An indie builder

value: Show HN: Hazbin Hotel OC Maker – Create Original Characters with AI

author: xiaoshumiao


value: Create stunning AI videos with synchronized audio using Seedance2 AI Video. The latest AI video generation tool that adds sound effects, dialogue, and ambient noise.

value: Show HN: Seedance2:AI Video Generator with smooth motion and rich details


value: WoWSaaS

value:
Hi HN,
I dropped out of college 3 months ago to solve my own problem: I kept building SaaS products that nobody wanted.
I realized I was guessing instead of measuring. So I built a system to automate "Market Signal Detection" using LLMs.
The Architecture:
1. Ingests data primarily from Reddit (niche communities), Hacker News, and rising Search Queries.
2. Filters for "Negative Sentiment" + "Financial Pain" (e.g., people complaining about losing money).
3. Calculates a "Velocity Score" to spot trends before they hit mainstream Google Trends.
I wrote a detailed technical breakdown of the methodology and the "3 Signals" I look for (Bleeding Neck, Fragmentation, Wallet Index).
You can read the full guide (no paywall) here:
https://blog.vect.pro/trend-hacking-guide
The tool itself is part of the platform I'm building, but the guide stands alone as a framework for finding ideas manually if you prefer.
Would love feedback on the signal detection logic.
- Afraz

value: Show HN: I built an AI that scans 10k Reddit comments to find 'Blue Ocean' ideas

author: WoWSaaS


value: afrazullal

value:
Hi HN,
I was frustrated by the standard startup advice: "Hire a VP of Marketing, Hire a Content Lead, Hire a Video Editor."
It leads to massive burn ($30k/mo) before finding product-market fit.
I spent the last 3 months asking: "How much of this can be automated?"
I built a framework called the "Zero-Employee Growth Stack." It uses different agentic workflows to handle the entire pipeline:
1. Signal Detection (Scanning trends).
2. Content Strategy (Clustering keywords).
3. Production (Generating SEO blogs & video scripts).
I documented the entire architecture and the "ROI Table" of Human vs. Agent stack here:
https://blog.vect.pro/automated-marketing-strategy-guide
This is my Manifesto for the "One-Person Unicorn." I believe the next $10M SaaS will have 0 employees.
Curious to hear if anyone else is running a fully autonomous marketing stack?
- Afraz

value: Show HN: I replaced a 5-person marketing team with a swarm of autonomous agents

author: afrazullal


value: Show HN: I built a one-click coin flip with no ads or tracking


value: Show HN: I built this after leaking my AWS keys on StackOverflow


value: ankuranand

value: Show HN: KV and wide-column database with CDN-scale replication

author: ankuranand


value: aminekhd

value:
Show HN: How to make Professional Footer for your website!.
a tutorial, it might be useful for some!
designes & developers
or for your personal website.

value: Show HN: How to make Professional Footer for your website (Online-Tool) by me

author: aminekhd


value: dohyeondk

value: Show HN: I scraped Zed's docs into a single PDF so I could read them on my iPad

author: dohyeondk


value: klevo

value: Stepped is a Rails engine, extracted out of Envirobly where it powers tasks like application deployment, that involve complex, out-of-the-band tasks like DNS provisioning, retries, waiting for instances to boot, running health checks and all the fun stuff of a highly distributed networked system.

value: Show HN: Stepped Actions – distributed workflow orchestration for Rails

author: klevo


value:
I built a lightweight WHOIS lookup tool that lets you quickly check domain and IP registration details directly from your browser:
https://myip.casa/whois
It’s designed to be fast, readable, and distraction-free. No ads, no sign-up, no tracking scripts, just the information you need.
What it does :
 - WHOIS lookup for domains and IP addresses
 - Clear, structured output (registrar, dates, nameservers, ASN info when available)
 - Works instantly in the browser
 - No installation or account required
Why I built it :
Most WHOIS tools today are overloaded with ads, captchas, or confusing layouts. I wanted something simple and reliable that works immediately when you need quick registration details or network ownership information.
This tool is part of a growing collection of free, browser-based network utilities, including IP lookup, port checker, DNS leak test, traceroute, SSL checker, and more:
https://myip.casa
Feedback welcome
I’d love feedback on the UI, missing fields, or ideas to improve accuracy or readability.
Thanks for checking it out!

value: Show HN: A Simple, Fast, and Ad-Free Whois Lookup Tool


value: pedrozieg

value:
Shopping search on big retailers feels increasingly hostile. You type something specific and get a wall of “similar” or outright unrelated items, mixed with ads that look like regular results. Sorting by price usually makes relevance even worse. It feels like the results are optimized for sellers and advertisers, not buyers.
I’m building 2zuz, a shopping search engine that puts the user first. Results are never promoted because someone paid more. Only results that are 100% relevant to your query should be shown, sorted by price.
Right now it searches across a few of the big online retailers, with more planned. I also think there’s a lot of room to improve how filtering and refinement works, and I’ll be iterating on that, but the main goal is simple: if you ask for something specific, you should not need to wade through anything else.
I’d especially love feedback on:
- How’s the precision/recall for the queries you care about?
- Where does it fail compared to the others?
- Which online retailers would you most want included next?
- Any “power-user” features you wish shopping sites had?
- Any other rough edges: bugs, UI, confusing behavior?
Thanks in advance for trying it out.

value: Show HN: 2zuz – Shopping search with no irrelevant or promoted results

author: pedrozieg


value: mirzemehdi

value: I made a small tool that creates nice App Store / Play Store screenshots for any mobile app idea. You can even attach your app’s screenshots and it will include them in the generated images. You don't need to know any UI/UX skills<p>Would love any feedback

value: Show HN: Made a simple tool to generate App Store / Play Store screenshots

author: mirzemehdi


value: jackzhuo

value:
I built this because I wanted a digital I Ching that honors the original math, rather than just Math.random().
Technical detail for the curious:
The simulation follows the traditional Yarrow Stalk algorithm (Da Yan). The core of this algorithm relies on modulo-4 arithmetic on the stalks remaining after a random split.
To make it physically realistic, I used a Box-Muller transform to simulate the user splitting the stalks with a Gaussian distribution (since humans naturally tend to split near the middle), rather than a uniform random split.
I was worried this 'human bias' might skew the modulo probabilities, so I ran a 1-million-run Monte Carlo simulation to verify.
The Result: The remainders [0,1,2,3] still emerged with a near-perfect 25% distribution (deviation < 0.05%).
So, the app simulates the physics of human imperfection while preserving the mathematical perfection of the probability distribution (where Old Yin is 1/16).
Stack: Next.js + Tailwind css
Happy to answer any questions about the math or the hexagrams!

value: Show HN: I Ching simulator with accurate Yarrow Stalk probabilities

author: jackzhuo


value: iamdavidmt

value: Simple application that helps you with the job search process - Upload your resume once. Get tailored resumes, compelling cover letters, and personalized interview prep for every job you apply to.

value: Show HN: cvfitr.com – An AI Job Application tailoring site

author: iamdavidmt


value: annakoren

value: I wanted to share CryptoGig, a platform where freelancers can offer services and get paid in cryptocurrency. It makes it easy for anyone to earn crypto for small gigs, while clients can access affordable freelance work worldwide.<p>Would love to hear feedback from the community!

value: Show HN: CryptoGig – A Marketplace for Freelancers Paid in Crypto

author: annakoren


value:
Show HN: LudvigEditor – A lightweight Python alternative to Electron editors
A code editor built on Python 3.14 + PyQt6 + QtWebEngine. It uses Monaco Editor (the same engine as VS Code) without Electron.
Key features: built-in Git GUI, extension system (Python/JS), integrated terminal, support for 20+ languages.
Technical Focus: Seeking feedback on integrating PyQt6 with QtWebEngine for creating native desktop applications with web components. Licensed under GPLv3.
Code: https://github.com/Ludvig2457Ultra/LudvigEditor


value: shinpr

value:
https://github.com/shinpr/sub-agents-mcp
Brings Claude Code's sub-agent pattern to Cursor (and other MCP-compatible tools): define task-specific "specialists" in Markdown, each running in its own isolated context window and returning a concise result to the main agent — without spawning git worktrees.

value: Show HN: Sub-agents for Cursor via MCP (isolated context, no worktrees)

author: shinpr


value: nullure

value: Show HN: A local-first memory store for LLM agents (SQLite)

author: nullure


value: shakauy

value:
Hi HN,
I've been building DNSAudit.io in my spare time during weekends and late nights this year. It started as a small personal experiment and slowly grew into a full DNS security scanner.
DNSAudit.io runs fully remote. No setup, no accounts. Just enter a domain, and it analyzes DNS security posture across multiple areas, not only configuration issues.
It currently checks for:
- Weak or missing SPF, DKIM, DMARC
- Insecure mail routing
- Oversized or suspicious TXT records
- Exposed or sensitive subdomains
- Missing DNSSEC on zones that need integrity
- Old, abandoned, or inconsistent nameservers
- Dangerous wildcard setups
- Malware or payloads hidden inside TXT records
- And more than 50 other security signals across DNS
This has been a fun project to build. It gives me space to experiment, test ideas, and refresh my DNS knowledge. Still early, but I'll keep expanding the scanner monthly.
Would love feedback or criticism!!
Here's the link: https://dnsaudit.io

value: Show HN: Dnsaudit.io – A Free Advanced DNS Security Scanner for Real-World Risks

author: shakauy


value: apoll

value: Show HN: Vanilla, a record player inspired macOS app built with Gemini 3

author: apoll


value: airohitkushwaha

value: Show HN: A unified interface to ask TOP Premium AI Tool side-by-side

author: airohitkushwaha


value: pypt

value:
Hey HN! I'm Linas, and here's my take on XKCD 949.
I've created a file sending/sharing website (think WeTransfer) which I believe is unique in several ways:
* End-to-end encrypted
* Recipients can start their download anytime, i.e. it's not P2P WebRTC-based thing like FilePizza
* (Effectively) no limit on the size of the uploaded data, i.e. it will encrypt/decrypt 100 GB just fine
* (Effectively) no limit the number of files that get sent
* Real-time transfers, i.e. recipients can start downloading their files even before you finish uploading them
* Resumable uploads/downloads
* ZIP downloads - creates ZIPs on the fly in the browser from decrypted data
* Full passkey auth, i.e. can derive data encryption key from a passkey with PRF
* Fast - 10 Gbps link, plus due to the chunking design, uploading 1024 files of 1 KB or a single 1 MB file take about the same amount of time
* No nasty trackers
Also, it has a dark mode!
The upload process joins small files together, splits large files apart, builds ~1 MB chunks from the data, encrypts each chunk with AES-256-GCM (each with its own unique IV), and streams it out via a WebSockets channel; the download process does pretty much the same thing in reverse.
Server-side, incoming uploads get written into a bespoke binary format (something like Protobuf) supporting random access. This enables upload/download resume, selective download of one or more files, and real-time downloads.
When downloading, the website sets up a service worker and adds its URL as an iframe (a known hack to force the browser to download something produced by JavaScript). Said service worker fetches the data, decrypts it, and then creates an uncompressed ZIP archive on the fly; for that purpose, I've implemented a whole new streaming ZIP64 archiver (which I'm considering open-sourcing at some point).
I'm using OPAQUE for authentication (though serenity-kit/opaque and Facebook's opaque-ke), as this seemed to be a good way to prevent me from being able to learn anyone's "hunter2" (passwords are used for encrypting the DEK which in turn encrypts uploads' "secret keys" for authenticated users). Also, OPAQUE would prevent weak passwords from getting cracked in case of a security mess-up on my end.
The website is able to authenticate the user fully using just the passkey. If the passkey provider has support for PRF, the website won't have to ask the user for their master password as it will then be able to decrypt the DEK using the PRF; otherwise, passkeys serve as a way to do 2FA. If you'd like to try it out, use iCloud Keychain (on macOS / iOS), Windows Hello, or Android for storing a passkey.
The frontend uses Svelte 5. I'm no frontend magician like some here, but I think at least I managed to keep it fast and simple.
I figured that if our messages are now E2E-encrypted by default, and even which news articles I'm reading on my news website are protected by TLS, then the users of file sending services should enjoy some privacy too - at this point E2EE should be just basic privacy hygiene.
The whole project took way longer than I'd like to admit, mostly because I got nerd-sniped by a bunch of premature optimization, and also had to fake my way into learning how to do modern frontend.
There's a 2 GB free limit for free transfers, also a Premium subscription option with a 100 GB limit. I want this to exist for the long term, but I have to make the finances work. If you find it useful, I'd love your support! If there's interest from HN, happy to share a promo code for a free trial (no CC required).
Feedback welcome!
(Please excuse the grammatical mistakes if any, I'm not a native English speaker, and I didn't want to feed this to an LLM to make it look like AI slop.)

value: Show HN: aero.zip - E2EE resumable file transfer, not P2P, 100 GB, OPAQUE auth

author: pypt


value: MICHE-japan

value: Show HN: I've taken your phone. If you want it back, pay up

author: MICHE-japan


value: thomoliverz

value:
I built Read Fast after realising I was saving hundreds of things to read and reading almost none of them.
It automatically turns saved content into a scheduled briefing and sends it to my inbox at whatever time I choose.
New version since last post actually allows you to bulk upload URLs. So you can just dump links here and Read Fast will scrape and brief for you.
Great for actually reading the things I want to. Curious if that resonates with people?

value: Show HN: I built time to read all the things I want to

author: thomoliverz


value: i built a simple + clean kanban website targeted at casual users who don't want a complex tool.

value: Show HN: Tasklanes

title: Show HN: Tasklanes


value:
Hi HN,
I built Movyo because I was unable to get good results from other AI video generation tools without learning a lot of prompt engineering.
Movyo takes a plain language idea and turns it into a detailed, model-optimized prompt using structured templates instead of just "making the prompt longer" like other tools do.
It's early, and I'm mainly looking for feedback from people who've tried AI video tools before.
I've been working on this as my very first full-stack project since I went solo, so anything is greatly appreciated. Thanks!

value: Show HN: I built a tool that converts plain language into AI video prompts


value: giovanella

value: Show HN: 0xFeed – An AI filter to remove SEO spam and fluff from tech news

author: giovanella


value: Show HN: 999 Penguins

title: Show HN: 999 Penguins


value: ThailandJohn

value: Show HN: TheAuditor – I indexed my code into SQLite to stop AI hallucinations

author: ThailandJohn


value: Elemenopi

value:
Hi HN!
I built Skyz AI to solve deployment friction with MCP (Model Context Protocol) servers.
The problem: Setting up MCP servers means configuring infrastructure, managing deployments, and debugging connections. I kept wasting hours on this when I just wanted to build AI tools.
What it does:
Simple development
One-click MCP server deployment
Managed hosting (no infrastructure to maintain)
Why it exists: Existing solutions charge premium prices and have poor UX. I wanted Vercel-level simplicity for MCP hosting.
Current state: Free beta. I'm intentionally launching early to build with feedback from people actually using MCP servers rather than guessing what features matter.
Try it: https://skyz.ai
Discord: https://discord.gg/jsT3S98sX9
Happy to answer questions about the technical architecture, MCP challenges, or where this is headed!

value: Show HN: Skyz AI – Host, Deploy and Use MCP Servers with Ease

author: Elemenopi


value: mcone

value:
I built JotBird because I wanted something simpler than Gists
or static site generators for sharing Markdown.
You paste Markdown, click publish, and get a clean link. There's no signup and no friction. Pages are unlisted (not searchable) and auto-expire after 30 days.
It's been running for a week and people are already publishing technical docs, educational content, and guides in 7+ languages.

value: Show HN: Turn Markdown into a web page in seconds

author: mcone


value: OldOtter

value:
built a CLI tool that scans your project dependencies and automatically creates specialized documentation agents for Claude.
How it works:
1. Run npx claude-docs in your project root.
It generates a /sync-docs command for Claude Code.
2. Run claude /sync-docs
3. You get a personalized /research slash command configured specifically for your project's stack and @ specialized subagents for the different dependencies
This is my first open-source project.
Looking for feedback.
Repo: https://github.com/ii-vo/claude-docs
Demo: https://www.claudedocs.com/

value: Show HN: claude-docs – dependencies –> reliable documentation references for CC

author: OldOtter


value: gitpullups

value:
OneShot is an API that routes failed LLM outputs to trained humans, returns corrected outputs or prompt injections, and stores the edits as structured training data.
Privacy Note:
This product is not built for privacy yet. The current use case is internal tools or beta features where users aren’t promised privacy. But the point of this tool is NOT FOR PRODUCTION.
In the future, there will be a feature for anonymizing all private information automatically.
Problem:
My project this year was a tool for pediatricians to do their insurance claims assisted by AI.
Niche industries like this require a ton of examples, fine-tuning and re-prompting to actually get them a product that works. Then, it requires monitoring  the output to some extent (of course with the hospital’s consent) so small model changes or edge cases don’t break outputs for at least the first couple months.
This monitoring takes months of being distracted from doing new features. And every new feature I wanted to ship required this constant beta monitoring to get it to a reliable state. This also includes internal tools and automations that I needed to work reliably. That is when I started wishing I had an AI engineer/architect monitoring outputs 24-7 for every new feature’s first month.  In real-world software, programs need to break less. Like almost never. And current AI models often don’t get us quite there. From 90% to 100 or 95 to 100. We waste months before shipping new features trying to tweak it internally without the model being able to have the hybrid of being improved live in the real world.
In niche agent environments, you sometimes need an actual human to jump in.
How it works:
First, a beta deployment.
You deploy your AI to do X business use case in beta or internally.
Each step of your pipeline queries our API with what models you prefer, etc.
Then, a human who is in charge of a batch of outputs will see a flagged output when something goes wrong (we agree first on what that means). They can then use human judgement to tweak the prompt, prompt a different model, or provide added context over and over in multiple parallel threads until the correct output comes out.
Second, fine tuning.
You now own a dataset of what changes to your prompt and what changes to the output were made that caused that magical output. Thousands of changes and tweaks that can take your model to the next level internally for each feature are in your db. This data allows you to ship faster, with better guarantees and much less manual testing that isn’t being rewarded or punished by the real world.
Who are the humans?
I’m a developer doing the tickets manually with my technical friends I’m paying out of pocket for now (yes, it IS available 24/7!!!).
This is intentionally manual during beta, with clear review guidelines, so we understand the process before trying to hire.
How slow is it?
Most of the time no human will touch it and sometimes a human will take a quick unnoticeable automated action. In some edge cases, you’ll feel some noticeable slowing (10s+) but we’re looking to accelerate those as well, and the alternative is fully broken output.
Who is it not for?
This is not meant for consumer apps, privacy-sensitive production systems, or teams expecting zero human involvement.

value: Show HN: I made a human-in-the-loop system for tuning LLMs in beta

author: gitpullups


value: qzcanoe

value: PhotoToVideoAI is an AI-powered tool that turns your photos into dynamic videos. Upload a photo and a prompt, and in about 30 seconds you'll get a high-quality video in resolutions up to 1080p and durations of 5 or 10 seconds. It’s designed for content creators, marketers, and photographers, Feedback is welcome!

value: Show HN: PhotoToVideoAI – AI photo to video generator

author: qzcanoe


value: tarasyarema

value:
Hey HN!
I kept noticing great posts dying in /new while some mediocre ones hit front page at the right time. So I built a tool that analyzes your post and suggests optimal posting windows based on historical HN data. Also if provides general feedback based on data + similar posts.
From the tech side of it, both the fe and the HN API are open source here:
- Frontend: https://github.com/desplega-ai/ai-toolbox/tree/main/willitfr...
- SQL API: https://github.com/desplega-ai/ai-toolbox/tree/main/hn-sql
The backend is done with a simple python script that fetches data into parquet files, and then queries them using duckdb, which work fine so far. The latencies go from ms to few seconds depending on the query.
PS: I haven't finished the full sync yet (~85% done).

value: Show HN: WillItFront.Page – Test your HN post before submitting

author: tarasyarema


value: wniak

value: Its three main goals are:<p>- Replace repetitive stuff with AI<p>- Keep the creative part<p>- Have the most user friendly interface possible.<p>Mobile version works but it's far from perfect.

value: Show HN: AI Engine Turns Your Plot into a Playable Visual Novel - web demo

author: wniak


value: runtimepanic

value:
Hi HN,
I built PassDetective after realizing how often passwords, tokens, and secrets accidentally end up in shell history during debugging or quick tests.
PassDetective is a small CLI tool that scans shell history files using pattern matching to flag potential secrets before they get committed, backed up, or shared.
It currently works on Kali Linux and NixOS, and is meant to be a lightweight, local-first check rather than a full secret scanning solution.
I’d appreciate feedback on false positives, missing patterns, or how people approach this problem in their own workflows.

value: Show HN: PassDetective – Scan your shell history for leaked passwords and secret

author: runtimepanic


value: mrwizrd

value:
I've had a bit more spare time lately, so I put together this live map of UK buses using data from the Department for Transport and open-sourced it.
It's got rough edges and is practically running on a hamster wheel, but you can try it. I'm too excited not to post.
https://busmap.tail5c8e3.ts.net/

value: Show HN: I made a live UK Bus Map from open data (and you can, too)

author: mrwizrd


value:
Hello HN,
I built "Wax On, Python", a browser-based Python 'dojo' that focuses on syntax precision through repetition and muscle memory.
https://waxonpython.com
The Problem:
When learning to code, it's easy to copy-paste or gloss over syntax. Many tutorials explain the logic but don't force you to actually type the code. Sometimes beginners encounter basic syntax errors (missing colons, wrong indentation, mismatched braces etc) once they graduate to script writing.
The Solution:
Inspired by a classic fictional tale, this app takes an approach as if lessons are given by a 'strict sensei':
- Drills: You are given code snippets and must type them exactly character-for-character.
- Immediate Feedback: Typo? 'FOCUS!' 'SLOPPY.' Correct? 'GOOD.'
- Muscle Memory: starting with simple print statements  and building up to loops, classes, and eventually pandas dataframes.
- Philosophy: Between drills, you get philosophical Sensei wisdom explaining the why behind the concepts (eg:  'Variables are buckets', 'Indentations are choices' etc).
The tech...
- Runs entirely in browser. Code executes locally so no servers or latency.
- Runs a Pyodide Python REPL in-browser so user can see real errors as they make them. Includes Pandas package for data science drills.
- Stack: vanilla js, HTML, css.
Why I made it
I run a Python Learning Group at work and wanted a good engaging starting point for anyone who is curious about Python regardless of their professional or technical background - the goal being to make syntax automatic so you don't have to think about it, freeing the mind for higher-level logic, and giving people a sense of the learning journey they are about to embark on.
Any feedback on curriculum pacing and the "tough love" approach would be helpful - does it work in your case? would love to hear it.
Note: the app was actually blocked at work due to strict wasm rules implemented in Zscaler :(

value: Show HN: Wax On, Python' – learn Python dojo-style


value: markrai

value:
The core philosophy behind GitPow! is that the user should be in-charge of what they want their Git client to be:
- View commits grouped by month/year (or not)
- View the commit graph vertically, or horizontally
- Diff view actually shows image (or relative size change)
- Timestamps v.s. plain english dates - you choose.
- User defines what a "stale branch" means.
You get the idea - it's your software, and you should be able to set it up based on your workflow.
It's a work in progress. Please contribute, if you are experienced in Rust/TS/JS, or even if you have any ideas/features.
Since there is a purely passion project, and there is zero monetary incentive, so much is possible here. The Tauri front-end makes things particularly flexible in terms of development.

value: Show HN: GitPow a cross-platform, open-source Git GUI with unique features

author: markrai


value: kstonekuan

value:
Tambourine is an open source, fully customizable voice dictation system that lets you control STT/ASR, LLM formatting, and prompts for inserting clean text into any app.
I have been building this on the side for a few weeks. What motivated it was wanting a customizable version of Wispr Flow where I could fully control the models, formatting, and behavior of the system, rather than relying on a black box.
Tambourine is built directly on top of Pipecat and relies on its modular voice agent framework. The back end is a local Python server that uses Pipecat to stitch together STT and LLM models into a single pipeline. This modularity is what makes it easy to swap providers, experiment with different setups, and maintain fine-grained control over the voice AI.
I shared an early version with friends and recently presented it at my local Claude Code meetup. The response was overwhelmingly positive, and I was encouraged to share it more widely.
The desktop app is built with Tauri. The front end is written in TypeScript, while the Tauri layer uses Rust to handle low level system integration. This enables the registration of global hotkeys, management of audio devices, and reliable text input at the cursor on both Windows and macOS.
At a high level, Tambourine gives you a universal voice interface across your OS. You press a global hotkey, speak, and formatted text is typed directly at your cursor. It works across emails, documents, chat apps, code editors, and terminals.
Under the hood, audio is streamed from the TypeScript front end to the Python server via WebRTC. The server runs real-time transcription with a configurable STT provider, then passes the transcript through an LLM that removes filler words, adds punctuation, and applies custom formatting rules and a personal dictionary. STT and LLM providers, as well as prompts, can be switched without restarting the app.
The project is still under active development. I am working through edge cases and refining the UX, and there will likely be breaking changes, but most core functionality already works well and has become part of my daily workflow.
I would really appreciate feedback, especially from anyone interested in the future of voice as an interface.

value: Show HN: Open-source customizable AI voice dictation built on Pipecat

author: kstonekuan


value: shivanshsonii

value:
Hey HN!
I'm Shivansh, and I built CodeContext to solve a problem every growing engineering team faces: new developers taking 2-3 months before their first meaningful contribution.
The core insight: Most onboarding time isn't spent learning to code—it's spent figuring out which 15 files (out of 10,000) actually matter, and in what order to read them.
What CodeContext does:
Scans your repository (any language)
Builds a dependency graph using AST parsing
Runs PageRank to identify "knowledge hotspots" (the UserService.java that's called by 47 other files)
Generates a topologically-sorted "reading list" (simple → complex)
Creates interactive D3.js visualizations
Example output:
text
Your Codebase Map
━━━━━━━━━━━━━━━━━━━━━━━
 Knowledge Hotspots:
1. AuthService.kt (89 connections) - CRITICAL
2. DatabaseConfig.kt (67 connections)
3. UserRepository.kt (45 connections)
Week 1 Onboarding Path:
→ README.md, ARCHITECTURE.md
→ Models: User.kt, Product.kt (low complexity)
→ Config: application.yml, DatabaseConfig.kt
→ First task: Add validation to UserDTO
Technical stack:
Kotlin (multiplatform-ready)
Tree-sitter for parsing 40+ languages
JGraphT for graph algorithms
D3.js for interactive visualizations
Git history analysis for change patterns
Why this approach works:
Traditional docs go stale immediately
Code search is great if you know what to search for
AI assistants generate code but don't teach architecture
Juniors need a "start here" button, not a search box
What's different from Sourcegraph/CodeSee:
Lightweight (single CLI command, no infrastructure)
Onboarding-first (not code search)
Free & open source (MIT license)
Runs locally (no code leaves your machine)
I've been testing this with 3 teams (50-200 developers). Average time to first PR went from 47 days → 19 days.
Try it:
bash
npm install -g codecontext
codecontext analyze /path/to/repo
Open to feedback! What features would make this immediately useful for your team?
GitHub: https://github.com/sonii-shivansh/CodeContext

value: Show HN: CodeContext – Cut developer onboarding time from months to weeks

author: shivanshsonii


value: samwho

value: Show HN: Llmwalk – explore the answer-space of open LLMs

author: samwho


value: CharlesW

value:
This is a new, open-source (MIT) Claude Code plug-in for Apple platform developers. I initially built it to help me build my first "real" iOS app, and it made the process so fun and productive that I wanted to share it.
I recently christened it v1.0, but I continue to evolve it quickly. It's biased toward modern frameworks and best practices, but I continue to notably broaden coverage every week. Here are the technologies and concepts Axiom currently has deep coverage for:
• Swift & Concurrency — Swift 6 strict concurrency, actors, Sendable, @MainActor, async/await, data race prevention, actor isolation patterns
• SwiftUI — Performance optimization with Instruments, navigation architecture (NavigationStack, NavigationSplitView, deep linking), adaptive layout (ViewThatFits, AnyLayout), debugging view updates and preview crashes, gestures, Liquid Glass
• Data & Sync — SwiftData, SQLiteData (Point-Free), GRDB, Core Data (migrations, thread-confinement, N+1 queries), Codable/JSON, CloudKit (CKSyncEngine, conflict resolution), iCloud Drive, file protection, Realm → SwiftData migration
• Debugging & Performance — Memory leak patterns (timers, observers, closures, delegates), Instruments workflows (Time Profiler, Allocations, Leaks), Xcode build failures, Network.framework diagnostics, Auto Layout conflicts, build optimization
• Design & Accessibility — Human Interface Guidelines, VoiceOver, Dynamic Type, WCAG compliance, color contrast, touch targets, typography (San Francisco, text styles)
• Apple Frameworks — Foundation Models/Apple Intelligence, App Intents (Siri, Shortcuts, Spotlight), StoreKit 2 (subscriptions, transactions), AVFoundation (audio sessions, spatial audio), WidgetKit, Live Activities, TextKit 2, Now Playing
As with all useful AI tools, what makes Axiom perform so much better than foundation models alone is the thoughtful curation and optimization of the knowledge management at the heart of its capabilities. For example, I've spent a bunch of time "encoding" knowledge from WWDC sessions into relevant components, which gives Axiom a unique and useful "POV" that, in many cases, isn't covered in Apple's reference docs.
Any and all feedback/criticism is welcome, and I'll use it to improve Axiom for everyone. If you use Claude Code, I'd appreciate if you could try one or two of the audit commands (https://charleswiltgen.github.io/Axiom/commands/) on your codebase. You can also use `/axiom:ask` to ask Axiom about it's capabilities, what skills and agents would be most useful for a given issue or area of your app, etc.

value: Show HN: Axiom for Claude Code – Coding skills for iOS devs

author: CharlesW


value: saran-damm

value:
I built depup, a CLI tool to scan Python dependencies, check PyPI versions,
classify upgrade impact, and support CI workflows.
Docs: https://saran-damm.github.io/depup/
Repo: https://github.com/saran-damm/depup/

value: Show HN: Depup – a dependency upgrade advisor for Python projects

author: saran-damm


value: keepamovin

value:
Hello HN,
I basically don't use notifications for anything. The noise is too much. Slack is too loud. Email is too slow. But sometimes you do need a note in your face.
I found myself missing 1990s pagers. I wanted a digital equivalent - something that does one thing: beep until I ack it.
So I built UDP-7777.
Concept:
- 0% Cloud: It listens on UDP Port 7777. No accounts, no central servers. You don't need Tailscale/ZeroTier/WG/etc, it's just easy for device sets.
- CAPCODES: It maps your IP address (LAN or Tailscale) to a retro 10-digit "CAPCODE" that looks like a phone number (e.g., (213) 070-6433 for loopback).
- Minimalism: Bare-bones interface. Just a box, a few buttons, and a big red blinker.
The Tech:
It's a single binary written in Go (using Fyne). It implements "burst fire" UDP (sending packets 3x) to ensure delivery without the handshake overhead of TCP.
New in v2.2.7:
- Frequency Tuning: Bind specifically to your Tailscale/ZeroTier interface.
- Squelch: Optional shared-secret keys to ignore unauthorized packets.
- Heartbeat: Visual/Audio alerts that persist until you physically click ACK.
I built this for anyone looking to cut through the noise—DevOps teams handing off the "on-call IP", or deep-work focus where you only want interruptions from a
high-trust circle.
I'd love to hear your thoughts on the IP-to-Phone-Number mapping logic (it's purely visual, but I'm really into it).
Site & Binaries (Signed for Mac/Win): https://udp7777.com

value: Show HN: A pager

author: keepamovin

title: Show HN: A pager


value:
Hi HN — working with spreadsheets still requires a lot of manual glue work.
Common pain points we kept running into:
- Copy-pasting data from PDFs and reports into sheets
- Cleaning and formatting inconsistent exports before any real work can start
- Building multi-sheet financial models that are fragile and hard to change
- Manually wiring spreadsheets to external data sources
Most AI spreadsheet tools try to help by generating text or formulas, but they don’t remove the underlying manual glue work.
We’re building an open-source AI agent for spreadsheets that operates directly on tables and sheet structure.
What it can do today:
- Extract structured data from PDFs into spreadsheets
- Clean and format messy data while keeping it editable
- Build multi-sheet financial models (DCF, LBO)
- Connect and refresh data from external sources
Available on Google Sheets, Excel and as a standalone web interface.
Would love feedback from people who work in spreadsheets daily.

value: Show HN: Open-source AI agent for spreadsheets


value: theDGA

value:
This is a mouthful, which is why I'm also just calling it "Coco".
What is it?
Coco uses your LinkedIn connections.csv to give you a view of your network in a variety of ways, e.g. by company, seniority, function- but also by "influence". It then compiles that into recommendations for sectors to focus on & people to reach out to.
What's the backstory?
While my dayjob is VC, I'm always thinking of new ideas on the side, fascinated by the 0-1 of it all - how founders meet, how they commit, how they actually start working & reaching out to customers. Accelerators like EF, Antler and YC talk a lot about founder market fit & finding your edge- At the same time, I'm meeting so many "wantrepreneurs" like myself who claim to have no ideas, not sure where they should start. Well, this is where Coco comes in.
I'm trying to build a tool that surfaces users' "network strength" and point them towards people to talk to. Currently, the tool does what I call "alpha" and "beta"- beta being your big chunks, industries & companies you have most of your connections in, alpha being your outlier connections, notable people in notable companies.
It's kinda like Happenstance, but with a specific direction.
To use it, you'll have to go through the painful process of requesting your Linkedin Data - much like with Happenstance - but then you can simply upload & have a look at your data through Coco's lens.
Obviously, I have many ideas as to potential next features, but I'd love to get the community's view first!
I'd be super curious to hear any general thoughts, what your expectations, disappointments, likes & wishes are :)
Thank you!

value: Show HN: Founder Market Fit Mapping Tool a.k.a. "Coco"

author: theDGA


value: milowata

value:
I built live IM chat as a VSCode extension for those who miss the AIM days, or who wish they could chat with dev friends the way finance folks chat through their Bloomberg terminals.
The messages are ephemeral and stored locally only. Pick a username, tell your friends to pick theirs, and chat with friends while your coding agent runs :)
Have fun!

value: Show HN: Instant Messaging in VSCode

author: milowata

title: Show HN: Instant Messaging in VSCode


value: CULPRITCHAOS

value:
Hi HN — I built this and I’m explicitly asking skeptics to tear it apart.”
Interlock is a safety and certification layer for AI infrastructure, not an optimizer or a vector database.
The problem I am solving for is that AI systems (vector search, RAG pipelines, agent frameworks) don’t usually fail cleanly — they degrade silently, oscillate under load, or keep returning corrupted results until something crashes. Monitoring tells you after the fact; circuit breakers tend to be static and blind to context.
Interlock tries to address that by:
forecasting time-to-failure under stress
intervening before hard limits are reached
refusing to serve results when confidence collapses
producing cryptographically signed evidence of what happened (control vs protected runs)
It includes:
integrations with FAISS, Pinecone, Weaviate, Milvus, LangChain, LlamaIndex (Elasticsearch experimental)
TypeScript + Python support
automated stress tests (control vs protected)
long-run stability tests
certification classes (I–V) derived from actual configuration + behavior, not labels
Importantly: Interlock does not guarantee correctness or uptime. It certifies that a given configuration survived a defined stress test without crashing, oscillating, or serving degraded results — similar to a structural load rating rather than a promise.
The repo is fully open source, and all claims link to test artifacts and CI runs. I’m especially interested in feedback on:
failure modes this wouldn’t catch
where the certification model is too strict or too weak
whether this is actually useful in real production AI systems
Repo: https://github.com/CULPRITCHAOS/Interlock
Happy to answer questions or be told why this is a bad idea lol

value: Show HN: I built a circuit breaker that predicts AI failures

author: CULPRITCHAOS


value:
Hello HN,
I built Container-Maker (cm) because I really liked the concept of "DevContainers" (defining your development environment as code in `devcontainer.json`), but I didn't want my development workflow to be tightly coupled to VS Code. I wanted a tool that felt as fast as `make` but offered the isolation of Docker, usable from any terminal or IDE.
Container-Maker is a standalone CLI tool written in Go that manages development environments.
Key features:
- *Standalone:* Fully compatible with the `devcontainer.json` spec but runs independently of VS Code.
- *Zero-Config:* The `cm setup` command auto-detects your OS and installs/configures the optimal runtime (Docker Desktop, Docker Engine, or Podman).
- *Native Experience:* It handles signal proxying (SIGWINCH) and TTY correctly, so tools like `vim` and `htop` feel native inside the container.
- *BuildKit Powered:* Leverages Docker BuildKit for aggressive layer caching to speed up environment spin-up.
- *TUI Dashboard:* Includes a terminal UI (`cm status`) to manage running containers and view logs.
- *Cloud Integration:* Can provision GPU instances (AWS, GCP, etc.) for AI/ML workloads directly from the CLI.
It aims to solve the "works on my machine" problem by making the container the first-class citizen for your shell.
The project is open source (AGPL-3.0).
Repo: https://github.com/UPwith-me/Container-Maker
I'd love to hear your feedback on the TUI experience and the setup flow!

value: Show HN: Container-Maker–A standalone CLI for DevContainers(run without VS Code)


value: Noamis

value: Show HN: Chronos-Track – Identify physical hardware via TCP clock skew (Rust)

value: Show HN

author: Noamis

title: Show HN


value: czvziwzx

value:
When running hands-on sessions or workshops, it’s often hard to tell who has finished and who’s still working, or who needs help.
I built a small web app to make this visible in real time.
It’s designed to be simple and used only during the session.

value: Show HN: A small web app to see who's still working during workshops

author: czvziwzx


value: zuhayeer

value: Show HN: Instantly embed SVG shapes of any location

author: zuhayeer


value: maxiinversiones

value:
I built this for myself after struggling to clearly see my real gains/losses and daily portfolio performance using existing apps.
It tracks buy/sell history, portfolio balance, and daily value over time, and works on both desktop and mobile.
This started as a personal tool and helped me stay more organized with long-term investing.
Happy to answer questions or hear feedback.

value: Show HN: I built a small portfolio tracker for personal investing

author: maxiinversiones


value: Wronnay

value:
I've been building side projects for over a decade. Most failed to find Product‑Market‑Fit - I know the frustration of shipping features that don't stick.
The painful truth I learned: many teams chase features over feedback. Worse, most feedback is shallow or useless because people avoid being critical.
So I built user.mom to fix the process, not just add another tool. It maps the full PMF journey: Landing Pages to validate demand, Surveys to gather structured signals, Feedback Boards to organize requests, Customer Voting to prioritize, and Integrations (CSV, webhooks, API) to scale what works.
If you’re tired of guessing what customers want, start your PMF workflow - the first product is free for every user.

value: Show HN: User.mom – Everything you need to reach Product-Market-Fit

author: Wronnay


value: pkhodiyar

value: Show HN: Reddit and HN for Cybersecurity [Free]

author: pkhodiyar


value: TinTekka

value:
Hi HN,
I'm a first-time founder from Dhaka building TinTekka to solve a real pain point: agencies waste weeks evaluating AI tools, only to struggle with implementation and see minimal ROI.
The core problem: there are thousands of AI tools launching monthly, but no structured way for teams to discover which ones actually fit their workflow* and *how to implement them properly.
TinTekka has two sides:
For agencies & startups:
- Answer targeted questions about your team, workflows, and pain points
- Get a personalized AI tool stack (with implementation steps and ROI projections)
- See which tools solve your specific bottlenecks
- Everything free right now, no credit card
For AI tool builders (the part I think HN might find interesting):
- We're building a partner network connecting emerging AI tools with agencies actively looking for solutions
- Early partners get featured in personalized roadmaps when they're a good fit for a user's needs
- No affiliate nonsense, just direct introductions to qualified teams seeking exactly what you built
- This becomes a distribution channel for builders who are tired of competing for attention on Product Hunt
The thesis: AI tools are fragmenting fast. Most won't survive based on novelty alone. The winners will be ones that solve real workflows and get in front of the right customers early. We want to be that connection layer.
Currently validating the agency side and starting to onboard early builder partners. Would love feedback from HN:
- For agencies: is the roadmap actually useful, or does it feel like just another listicle?
- For builders: would you want structured access to teams actively looking for your type of solution?
- What am I missing about how teams actually adopt AI in their workflows?
Link: https://tintekka.com
Curious what you all think, especially if you're building or using AI tools.

value: Show HN: TinTekka – AI tool roadmap for agencies

author: TinTekka


value: ivanyu

value:
About a year ago I had an idea and I've been very slowly iterating since then. Imagine you play a game in a foreign language that you don't know very well (e.g. you're learning). You see an unknown word in a dialog. You hit a hot key and then:
1. The game is paused.
2. Over the game window an overlay is drawn. On this overlay, the text from the screen is recognized.
3. You can select a word or a phrase and get their translation, ask ChatGPT to explain it, or open Wiktionary.
4. Then you press Esc and continue playing.
There's only one catch: you need to give it a Google Cloud API key, because it uses its OCR and language services. However, what a single person may use, it'd most likely be in the free tier range and would cost $0.00/month. So it's mostly an inconvenience.
It works on Windows and also X11 Linux. Not on Wayland or Mac, for now. Nothing fundamentally impossible there, I just need to test and polish the rough edges.
It's open source, GPL-3.0.
And if you care, it's not Electron, it's Qt. Nowadays we should frugal with RAM :)

value: Show HN: GameTran – Your language assistant in computer games

author: ivanyu


value: doctorslimm

value:
Show HN: Sourcewizard – Turn user feedback into tickets, plans, and PRs
Hi HN! I’m Lukas, one of the builders.
We made a widget that lets users propose changes directly on your product UI. Those proposals turn into structured tickets, a clear implementation plan, and a PR you can review.
Think “Cursor for customer support.”
We built this after repeatedly drowning in feedback spread across Slack, Notion, screenshots, and email. Small teams can’t scale support, but users often know exactly what they want changed.
Instead of replying and triaging, you let users move things forward in parallel.
Try editing the app here:
https://edit-me-two.vercel.app
Twitter post with demo video:
https://x.com/ichebykin/status/1999670255426118068
Would love feedback, questions, and reasons this is a terrible idea.
Made in SF by:
Ivan - https://x.com/ichebykin
Lukas - https://x.com/whysoslimm

author: doctorslimm


value: clarkfannin

value:
Check out my new fully online, terminal-based 1v1 dueling game! duel is easy to install with Homebrew (tested on Mac, not tested on Linux) and allows you to connect to an available lobby from anywhere with one command. Read the short readme on the repo or get started quickly with the commands below:<p>brew tap clarkfannin/duel
brew install duel
duel

value: Show HN: duel, an online, terminal-based 1v1 game

author: clarkfannin


value: imadbkr

value: Show HN: Smart Widgets to Optimise Conversion

author: imadbkr


value: ayaansst

value: Show HN: Shell Breaker – Learn Linux by fixing broken real systems

author: ayaansst


value: admtal

value: I made this JS library you can include on your page, and it will convert your page temporarily into a Scratch Off lottery ticket.

value: Show HN: Transform your site into a scratch-off lottery ticket

author: admtal


value: seekerquest

value:
I am working on Twick Studio, an intuitive visual editor for video built on top of the Twick SDK, react toolkit for creating custom video editing experiences.
Key capabilities include:
 - Multi-track, drag-and-drop timelines
 - Live preview of edits
 - Canvas editing with drag, resize, and rotate
 - Undo/redo and controls for text, video, audio, and images
 - Media utilities for metadata and thumbnail generation
Recently added new cloud functions in the Twick SDK to auto-generate captions and export videos as MP4. You can watch a short demo here: https://youtu.be/zgRcJt8wxLk
Try Twick studio: https://development.d1vtsw7m0lx01h.amplifyapp.com
Auto-generated captions: https://development.d1vtsw7m0lx01h.amplifyapp.com/subtitles
Docs: https://ncounterspecialist.github.io/twick/docs/intro
Source code: https://github.com/ncounterspecialist/twick
If you find it useful, a  on GitHub is appreciated.

value: Show HN: Auto-Generated Captions with Twick

author: seekerquest


value:
I built a small open-source tool called dj-cache-panel after realizing Django gives you almost no visibility into what's inside your cache backends.
It provides a unified Django admin interface to inspect, search, view, and delete cache keys across multiple backend types (Redis, Memcached, LocMem, Database cache, etc.). It auto-detects backends, works without models, requires zero configuration for most setups, and integrates cleanly with the admin.
What it offers:
- Search keys (exact or pattern-based)
- Delete keys, flush keys
- Backend-aware panels (Redis, Memcached, LocMem, DB cache)
- Multi-backend support out of the box
-Zero models, zero migrations, lightweight install
Repo: https://github.com/yassi/dj-cache-panel
Docs: https://yassi.github.io/dj-cache-panel/
pypi: https://pypi.org/project/dj-cache-panel/
Would love feedback, especially from anyone running multi-cache or production Redis setups.
This is a natural extension to my previous work on dj-redis-panel, feel free to check that out as well.

value: Show HN: Dj-Cache-Panel – Inspect and Debug Django Cache Back Ends


value:
Problem: People know they should eat better, but apps fail at long-term engagement. Nutritional tracking is manual and boring, ignoring psychology and social dynamics. Result: 80%+ dropout rates in health apps. We saw this gap in markets like Suriname and the Netherlands, where community health is key but tools are outdated.
Solution: AI Scan a meal, analyzes nutrients, and UPFs. Get AI Cindy insights (e.g., "This meal aligns with habit loops—pair it with a walk"). Share in a social feed, invite your inner circle or join other for inspiration, and participate in challenges for viral motivation.
MVP is partially functional—core analysis and social beta ready. Download the Webapp from mobile browser and add it to your homescreen.
Targeting Suriname/Netherlands first(underserved markets with high mobile adoption), then global.
Test the MVP at nutriqs.ai and help us iterate.
Feedback Requests:
(A) What feature excites you (e.g., AI image analysis or AI Cindy)?
(B) What feature is absolutely engaging/technically solid?
(C) What feature does not add value or has bugs?
Curious about HN's take—let's discuss in comments.

value: Show HN: Nutriqs.ai-AI Social and Gamified Health Network


value: borisandcrispin

value: Show HN: Chat with a Random AI

author: borisandcrispin

title: Show HN: Chat with a Random AI


value: freedomben

value:
I love the look of HN on Christmas Day, but I never feel like I get quite enough of it in just one day.  To rectify this catastrophic problem, I created a browser extension to give me the Christmas HN experience from the day after Thanksgiving until the first work-day of the new year.
I also added a fun "extra festive" mode that enhances the festivity level of the site beyond it's normal look.  I love it, but I expect it to be controversial :-D
It's pretty easy to `git clone` and install it (instructions for Firefox and Chrome in the README.md).  I haven't put it in the extension stores as I have no idea if anybody else would want it, but if it turns out there are dozens of us[1] that want to use it, I will do so.
Goal is to fully support Firefox and Chrome (as I'm a Firefox user primarily), though I haven't found a way to get the Christmas tree animated gif to load in Firefox so that one part doesn't currently work.  I tried all kinds of hacks to convert the tree into an animated svg, and even generate new ones, and they are laughably horrible.  I'll continue to look and try stuff but for now at least it will just display the alt text on Firefox.
Settings are accessible by clicking on the extension in the menu or tray.
[1]: A nod to the iconic Dr. Tobias Fünke from Arrested Development

value: Show HN: Hacker News Christmas colors browser extension

author: freedomben


value: youchen

value: Show HN: Feedvote – A $149 lifetime alternative to Canny for Linear users

author: youchen


value: tannerc

value:
I've worked in tech my entire career, and over time mindfulness meditation has become less of a "wellness habit" and more of a practical tool for keeping my mind clear.
I encourage mindfulness meditation to everyone because it's that impactful on stress and awareness in everyday life.
After years of practice, I've that most meditation apps eventually became distracting or costly.
To me, mindfulness apps that provide guidance, content, forced streaks, and incentives seem to replace the practice of mindfulness itself with some gamification of the act.
So I built Center, a silent meditation timer with a few constraints:
• No guided sessions, voices, or music
• No subscriptions, ads, or paywall
• Optional tracking, no gamification
• Works across iPhone, Apple Watch, iPad, and Mac via iCloud
• Donation-supported, with no features locked
The goal has never been growth or engagement, but reliability. I wanted something closer to a clock than a coach.
This is a side project, but it’s been interesting to see how a deliberately "boring" tool changes how I personally practice mindfulness, and how that carries over into my work (especially decision-making and stress tolerance).
Site: https://centertimer.com

value: Show HN: A meditation timer without guidance, music, or growth mechanics

author: tannerc


value: Pastaza

value: Show HN: Cardly – Manage, track, and get alerts for your gift card balances

author: Pastaza


value: kwakubiney

value:
I built this because I have a specific workflow problem when digging for music. I often have a Spotify playlist of original tracks I like, but to actually play them in a DJ set, I need the "DJ-ready" versions (Extended Mixes, Club Edits, Remixes).
Searching for these one by one is tedious. I wanted a tool that automates the search but leaves the selection to me.
What it does:
Remixify takes a Spotify playlist URL, scans for alternate versions of those specific tracks, and presents them in a crate-style view. You can preview the results and export your selections to a new playlist.
How it's different:
Most discovery tools try to recommend similar music or use AI to guess your taste. Remixify doesn't do that. It strictly looks for versions of the tracks you already provided. It’s designed to be a utility for "completing" a collection rather than finding new artists.
I’d appreciate any feedback on the workflow or the matching logic.
Code:
https://github.com/kwakubiney/remixify

value: Show HN: Remixify – Find alternate versions of tracks in your Spotify playlists

author: kwakubiney


value: Hi HN, I'm a student frustrated by the noise on social media. I built a Discord community where access is gatekept by 'Proof of Work' (a video pitch of a project). No AI-generated text allowed. Trying to create a high-signal environment for deep work. Here is the video manifesto: https://youtu.be/i2xdJ5ISoTI?si=XhSibwJGo_XnqF-X

value: Show HN: Cut the Crap – A meritocratic community for builders


value: parsabg

value:
Hey HN,
We’re Amin and Parsa, and we’re excited to share DataKit, a fully in-browser data analysis platform that lets you work with large datasets directly in a browser tab, with no servers, no setup, and no data leaving your machine.
- GitHub: https://github.com/datakitpage/datakit
- Live demo: https://datakit.page
DataKit processes multi-gigabyte datasets (CSV, Parquet, JSON, Excel) entirely client-side using DuckDB compiled to WebAssembly. Your data stays local to your browser, and nothing is uploaded anywhere by default.
We were frustrated by having to choose between cloud tools that require uploading sensitive data and heavyweight local setups that are painful to install and maintain. We wanted something that just works in a browser tab, but still has real analytical power.
Some of its core features are:

  - Client-side processing of large files (tested up to ~20GB) with no backend
  - Full SQL interface powered by DuckDB-WASM
  - Python notebooks via Pyodide for data science workflows
  - Optional connections to remote sources (Postgres, MotherDuck, S3) via a proxy
  - An AI assistant that only sees schemas and metadata — never raw data

Licensing: DataKit is AGPL-licensed, with commercial licenses available for enterprise use.
We’ve been building DataKit as a side project over the past few months and would really love feedback on:

  - Performance bottlenecks you run into
  - Features you’d need for your workflows
  - Thoughts on the all-client-side architecture vs hybrid approaches

Thanks for checking it out, and we’re happy to answer any questions.
— Amin & Parsa

value: Show HN: In-browser data exploration toolkit

author: parsabg


value: Made a small convenience extension that lets you bind a button to a hotkey. I plan to add some more complex automations like text input. Would be cool if someone finds it useful

value: Show HN: Add keyboard shortcuts to any site with a browser extension


value: ditegashi

value:
Heya HN, I've been working on a vibe-marketing platform as my primary side project for the last few months. Doing a (very) soft launch today, mainly because I want to use it to challenge how we think about AI-generated content (Some people call it SLOP - bear with me).
How PostKing works:
I create a statistical model of your existing content - blogs, social posts, university assignment anything you've written.
It learns your brand voice, tone, and positioning - not just surface-level writing style, but the actual way you think
Generate content across any channel that sounds authentically like you, not generic AI slop
I take these fingerprints from your content:
Stylometric:
- Function word frequency (the, a, and, etc.) — normalized ratios
- Lexical diversity: Matthews (type-token), Yule's K, Simpson's
- Signature Phrases (TF-IDF):
- Top 10 bigrams
- Top 10 trigrams
- Top 15 distinctive words (length > 3)
Sentiment:
- Overall score
- Emotional markers: joy, sadness, anger, fear, surprise (normalized)
- Sentiment variation (sentence-level deviation)
Patterns:
- Collocations: frequent two-word pairs (≥2 occurrences, top 20)
- Recurring phrases: three-word phrases (≥2 occurrences, length > 10, top 10)
- Structural templates: questions, exclamations, lists, quotations
- Rhetorical:
- Metaphor density (like/as/is indicators per sentence)
- Alliteration frequency (adjacent same-letter starts per sentence)
- Parallelism instances (repeated structures per sentence)
- Anaphora instances (repeated sentence beginnings per sentence)
It's a simple model, but I hope it's a better one than the "prompt and pray" approach most AI writing tools use. Fundamentally I feel like most AI content tools improve for volume over authenticity, which creates a race to the bottom. That misalignment is what drove me to make this.
Because this is a soft launch, the voice training algorithm is still being refined. You won't get bad output or anything, but the more diverse your input content, the better it captures nuance. I've opened up free alpha accounts in the meantime if anyone wants to test it with their own brand.
Happy to send more credits your way if you use the provide feedback link in the app.
Edit: Happy to share more about the technical approach to voice preservation if folks are interested - it's not just fine-tuning, there's a lot of contextual layer work involved.

value: Show HN: I vibe coded a vibe marketing platform

author: ditegashi


value: floships

value: Reload to generate a random gradient. Press share button to fix the seed. Go to /clean to hide the UI.

value: Show HN: Gradient.bg – Aesthetic Gradient Generator

author: floships


value: g023's OllamaMan - Ollama Manager OS style GUI management of ollama Server - Open Source LLM Management using PHP/JS/Sqlite and a web browser. Integrated apps for chat, terminal viewer, model management (can pull or delete; huggingface gguf supported too). Advanced model creation now implemented. Supports images in chat and speech to text/history/etc. Lots of quick access buttons, and auto sets itself up if db doesn't exist. Adding more bells and whistles as I go. Not meant for a public facing folder, so protect as you see necessary. Open source, BSD 3-Clause so have fun and thanks for giving it a glance. I just made it yesterday, so I'm sorry if it has some rough bits as I'll fudge those into place hopefully shortly (menus on the topbar/settings tabs). Right now fully functional.

value: Show HN: G023's OllamaMan – Web-based OS for managing Ollama servers


value: eigen-vector

value: Show HN: Watchalong – live chatrooms for sports, shows, and events

author: eigen-vector


value: yusukez

value: Show HN: A Lightweight Hono and Preact Template for Cloudflare Workers

author: yusukez


value: admtal

value:
I made a tiny zero-dependency JavaScript library that turns any webpage into a scratch-off lottery ticket. Just include one script tag and a silver scratch layer appears over your site. Users can scratch with mouse or touch to reveal the content underneath.
I built it mostly for fun. Demo and code here:
GitHub: https://github.com/admTal/scratch-off
Demo: https://scratchy-lotto.com

value: Show HN: Turn every website into a scratch-off lottery ticket


value:
I started giving away badges on X to people who touched grass just for fun and most of them loved it! So I decided to create a whole website about it.
Process is simple:
- Enter X username / url
- Fetch Profile image and choose badge
- Generates a badge page which can be shared with nice OG images
The site is deployed on Vercel, with R2 and Browser rendering for OG images and data storage.

value: Show HN: Silly website to earn badges for touching grass


value: claywren

value: Show HN: A model that estimates when AI can do your job

author: claywren


value: arthurstarlake

value:
"deep union web" is a web tool that facilitates requesting and offering generic help from nearby people that you may not even know yet. It does so by gathering your requests, offers, generic visual appearance and coordinates. Both the requests and offers are in these 7 dimensions: Preservation, Gratification, Definition, Acceptance, Expression, Reflection, Knowledge. You could consider them as increasingly subtler needs. They are somewhat general intentionally but each need has a more concrete example next to each one if you click the "?" button. Then users can find each other in a map, see what they match in, and if they decide to approach, they can see how others have visually described themselves and where they are (i.e. the selected user is 0.03 km North).
How it works
1. Submit your requests, offers, visual description and current coordinates (e.g. grab it from Google Maps). They all stay local to you.
2. You can choose to post everything in our database so others can find you. (All posted data is automatically deleted at midnight Pacific Standard Time every day.)
3. Select other users in the Map section to see how well your requests and offers match.
4. If you choose to approach them, you can see their visual description so you know how they look, and their distance and direction from your location so you know where to go.
19 out of 22 data points are input through checkboxes so it's very quick.
Feel free to use it as an icebreaker, to improve relationships, or to grow your network in a targeted manner!
Why did I do this?
I traveled by bus many times during my Masters degree and was surprised at how little people chatted in the bus. I've always felt particularly hopeful and energetic about us humans. I keeps me going joyfully and smoothly. I though aboout how people naturally had many needs and many skills or resources that they would love to share. I also noticed that many people near me spend too long pursuing some of those needs unnecesarily. So this was my effort in making other needs more explicit and to facilitate deeper conversations with people nearby. If those other people were strangers, and also in order to deliberately not store some types of sensitive information, I designed a manner to visually identify yourself with a few visual characteristics you are anyways broadcasting when you're present anywhere.
The first really valuable uses of this kind of app may be in circumstances where people already feel some trust with those around them (retreats, company, family, friends, etc.). Eventually, strangers!

value: Show HN: web app to match with people nearby on 7 dimensions of needs

author: arthurstarlake


value: It took a while to implement, though now I have generic functions working in Axe. Documentation, repository and site attached.

value: Show HN: I implemented generics in my programming language


value: visvig

value:
Post-GPU compute is a bet that new hardware will make different primitives cheap.
Extropic AI bets the primitive is sampling.
How far does block Gibbs sampling algorithm generalize beyond strictly bipartite models?

value: Show HN: Bets on Post-GPU Compute

author: visvig

title: Show HN: Bets on Post-GPU Compute


value: PaperWeekly

value:
ElasticMM is a newly released open-source serving system designed for modern multimodal large language models (MLLMs). The work was selected as an Oral presentation at NeurIPS 2025.
Unlike existing serving stacks such as vLLM—which are primarily optimized for text-only workloads—ElasticMM introduces Elastic Multimodal Parallelism (EMP), a new execution paradigm that adapts parallelism across different inference stages and modalities.
Key findings from the paper:
Up to 4.2× reduction in TTFT
3.2×–4.5× higher throughput under mixed multimodal workloads
Modality-aware scheduling, elastic stage partitioning, unified prefix caching, and non-blocking encoding
Paper (OpenReview PDF):
https://openreview.net/pdf?id=Zd6VyjmN1S
GitHub repo:
https://github.com/hpdps-group/ElasticMM
Curious to hear what the HN community thinks, especially from those building LLM/MLLM inference stacks or dealing with multimodal serving in production.

value: Show HN: ElasticMM – 4.2× Faster Multimodal LLM Serving (NeurIPS 2025 Oral)

author: PaperWeekly


value: alohaTool

value:
Hi HN,
I built a small Chrome (or any Chromium based: Brave etc) extension that lets you send prompts to ChatGPT straight from the browser address bar (Omnibox), without opening tabs, copying text, or interacting with the UI first. Check here: https://github.com/ParasKoundal/GPTSearch
The goal was to make ChatGPT feel more like a native browser primitive: type, hit Enter, get an answer.
What it does Once installed, you can:
- Focus the search bar (Cmd+L / Ctrl+L) or Click on it
- Type gpt and press Tab or Space
- Type/paste your prompt
- Press Enter
The extension opens ChatGPT and automatically injects and submits the prompt for you.
I will also hopefully make it available on Chrome Web Store soon.

value: Show HN: GPT Prompt from Searchbar – ChatGPT directly from the browser omnibox

author: alohaTool


value: thatsoulyguy

value:
Hi HN,
I’ve been working on an experimental programming language called XXML.
The project started from a frustration I kept running into across systems languages:
Languages with strong ownership tend to avoid runtime reflection.
Languages with rich reflection usually rely on GC or give up memory guarantees.
Compile-time code generation often requires a separate macro language.
I wanted to explore whether those tradeoffs are truly necessary.
What XXML is trying to do
XXML is a statically-typed, native language that:
Uses explicit ownership and borrowing (no garbage collector)
Supports runtime reflection while respecting ownership rules
Allows compile-time code generation using normal language constructs, not macros
Compiles to LLVM IR and produces native binaries
Reflection APIs are constrained so unsafe ownership operations are rejected at compile time. The goal isn’t “dynamic at all costs,” but introspection without losing safety.
What it’s useful for (so far)
Some concrete use cases I’m exploring:
Safe plugin/mod systems for native applications
Auto-generated serialization (e.g., JSON/RPC) without macros
Debugging and inspection tools that can reason about user types
Declarative domains (UI/layout/asset graphs) that benefit from structured syntax
What it’s not
This is early-stage and definitely not production-ready:
The ecosystem is minimal
The language is still evolving
Documentation and tooling are incomplete
I’m mostly interested in feedback from people who’ve worked on:
compilers
language runtimes
systems with heavy serialization or plugin boundaries
Code
GitHub repo:
https://github.com/ThatSoulyGuy/XXMLCompiler or https://xxml-language.com
I’d especially appreciate criticism around:
the ownership model
reflection safety boundaries
where this design is fundamentally flawed
Thanks for reading — happy to answer questions.

value: Show HN: A systems language with runtime reflection and no GC

author: thatsoulyguy


value: hardiksondagar

value:
Hey HN! I built this after my wedding left me with 5,000 photos to sort through.
The key insight: most photo sorting time is spent reviewing near-duplicates. Professional photographers shoot in bursts, so you get 10+ shots of the same moment.
PicPick uses CLIP embeddings to cluster visually similar photos, then adds face recognition to keep groups coherent (so you don't mix up "bride with parents" and "bride with friends" just because they look similar).
Tech stack:
- CLIP for semantic similarity (not just perceptual hashing)
- face_recognition (dlib) for person detection
- DBSCAN clustering on combined features
- FastAPI + vanilla JS for the UI
- SQLite for everything
It reduced my review set from 5,000 → ~1,000 clusters, which I then filtered down to 300 for the album in a few hours instead of days.
The clustering parameters are tunable - tighter for professional shoots with many duplicates, looser for casual photos.
Open to feedback! Especially around:
1. Better clustering algorithms (currently DBSCAN on CLIP embeddings + timestamps + face vectors)
2. UI improvements for rapid reviewing
3. Handling photos without faces (landscapes, food, etc.)
Works entirely offline, no cloud uploads needed.

value: Show HN: PicPick – AI-powered photo curator using CLIP and face recognition

author: hardiksondagar


value: rankiwiki

value:
A small site I built to turn “one person, one vote” into a ranked list.
Designed for small groups where the ranking is a starting point for discussion, not a final verdict.
Feedback welcome.

value: Show HN: Rankiwiki – voting-based rankings for small groups

author: rankiwiki


value: modinfo

value: Show HN: Create multi-voice podcasts with VibeVoice

author: modinfo


value: myfrontpocket

value: Show HN: Track prices and stock on products across 9 major retailers

author: myfrontpocket


value:
Hi HN,
I built Termrex, a terminal-based endless runner game inspired by the Chrome Dino offline game.
It runs in Linux/macOS terminals(POSIX).
I’m looking for feedback on:
- Gameplay feel
- Input handling across different terminals
- Any bugs or quirks you notice

value: Show HN: Termrex – Chrome dino game for terminal


value:
Cloudflare Workers are great, but they’re not Node.js, so native addons don’t run. I wanted a way to keep writing a normal Workers app while still using Node-native libraries (canvas/sharp/etc), without standing up and maintaining a separate service.
This is an experimental Vite plugin that lets you write functions in .container.ts, import them from your Worker, and call them like ordinary async functions. The call actually executes inside a Cloudflare Container (beta).
How it works (black magic):
It statically analyzes .container.ts and “clips/crops” the function body passed to nodejsFn(...)
Bundles that extracted code into a small Node server
Generates a Docker image for it and packages it for Cloudflare Containers
Vite rewrites imports of *.container.ts into generated proxy modules
At runtime, the proxy turns your function call into a container RPC (types preserved)
Caveats: very experimental, requires Cloudflare Containers + Durable Objects, args/returns must be serializable, cold starts exist. Feedback welcome on approach/edge cases.

value: Show HN: Vite plugin to call Node.js native code from CF Workers via Containers


value:
I built an agentless Windows PC inventory workflow for small IT teams/MSPs.
Workflow: run a PowerShell collector on PCs → gather JSON snapshots → generate offline HTML + CSV audit-ready reports (no cloud, no agents).
Links:
Collector (free): https://github.com/ZeroAgent-Labs/ZeroAgent-Inventory
Workflow article: https://zeroagent-labs.github.io/blog/
Viewer/product page ($59, 30-day money-back): https://www.zeroagentlabs.com/
Live sample report (dummy data): https://zeroagent-labs.github.io/za-sample-report/
I’d love feedback on:
what data points you expect for annual inventory/audits
report layout / grouping (sites/departments)
whether $59 feels reasonable for this “run-once inventory + report” use case

value: Show HN: Zero Agent – agentless PC inventory → offline HTML/CSV reports


value: jamescampbell

value:
Launch an interactive terminal UI where you can:
Enter keywords
Select TLDs from a list
See results in real-time
Filter to show only available domains
brew install james-see/tap/gofindadomain

value: Show HN: Gofindadomain super duper fast domain checker

author: jamescampbell


value: itsmeadarsh

value:
I built the fastest React virtualisation library. The core is written in Rust and compiled to WebAssembly.
Live Demo: https://warper.tech
10 million rows at 120+ FPS. No lag. No dropped frames.
Existing libraries like react-window and react-virtuoso hit walls at scale. They rely on JavaScript binary search and O(n) scans for variable heights. Warper is different.
The engine uses:
- Fenwick trees for O(log n) variable-height lookups
- O(1) arithmetic for fixed-height items
- Zero-copy typed arrays between WASM and JS
- Pre-allocated memory pools with zero GC during scroll
Benchmarks on M1 MacBook Pro with 1M rows: Warper hits 119 FPS. react-virtuoso drops to 58 FPS. At 10M rows Warper stays at 118 FPS while virtuoso falls to 31 FPS.
Its not marginally faster. Its 2-4x faster depending on the workload.
Trade-off is bundle size: around 45KB vs 6KB for react-window. Worth it if you need the performance.
Available through GitHub Sponsors at github.com/sponsors/itsmeadarsh2008
Happy to answer questions about the architecture.

value: Show HN: Warper – The fastest React virtualization library, built with Rust/WASM

author: itsmeadarsh


value: WaterRun

value:
There are two common ways to package .lua scripts into binary executables today: the traditional srlua, and the newer luastatic, which can produce a true native binary (instead of simply concatenating the Lua interpreter).
However, both approaches have notable limitations.
srlua:
- Can only package a single .lua file
- Requires manual compilation
luastatic:
- Linux-only
In addition, neither of them provides automatic dependency analysis.
Therefore, I (or, Claude Opus 4.5, haha) wrote luainstaller, similar in spirit to PyInstaller by name and design, wraps both tools and adds automatic dependency analysis and single-file packaging. It also ships with precompiled srlua binaries, working out of the box on both Windows and Linux.
Getting started is straightforward:
pip install luainstaller
For example, suppose you have a.lua, which depends on b.lua, and b.lua depends on c.lua.
There is no need to manually analyze dependencies or merge scripts into a single .lua file for srlua. You simply run:
luainstaller build a.lua
and it produces a standalone binary with no external dependencies.
You do not even need to use the command line. Running:
luainstaller-gui
launches a simple GUI built with Tkinter that covers the basic functionality.
luainstaller can also be used as a Python library. It supports additional parameters, a logging system based on SimpSave, selectable engines (precompiled Lua 5.1.5 for Windows and Linux, both 32-bit and 64-bit, as well as Lua 5.4.8), and more. Detailed usage is documented on GitHub.
Tested on Windows 11 and Fedora 43.
Limitations: only pure Lua scripts are supported. Dynamic module loading is not supported, as dependency analysis is based on a simple static approach.

value: Show HN: luainstaller – Package your Lua scripts into binaries

author: WaterRun


value: luokuo

value: Xhancer provides practical features for X/Twitter web including remark enhancement, @ mention, advanced search shortcuts, draft box, video download, and data export to make your social experience more efficient.

value: Show HN: Xhancer – Enhance Your /Twitter Experience

author: luokuo


value: DinakarS

value: Probably the coolest project I have ever worked on. This features a live audio and dynamic visual generations with patterns, waveforms, and geometry that are beautiful. Open to feedback.

value: Show HN: Beautiful browser-based music frequencies

author: DinakarS


value: jigsawdesigner

value: Show HN: Jigsaw Designer – Generate SVG jigsaw puzzles in seconds, not hours

author: jigsawdesigner


value: satinfive

value: Show HN: KpopAPI – RESTful Kpop API:)

author: satinfive

title: Show HN: KpopAPI – RESTful Kpop API:)


value: AI Powered Feed that fetches Top from HN, HF, GH and MJ. Built it using Antigravity on the weekend, please let me know what you think. I'm using it as a personal dashboard that covers top updates from engineering and creative spaces.

value: Show HN: Naiman.ai – AI Powered Feed

title: Show HN: Naiman.ai – AI Powered Feed


value: neotanp

value:
Hey everyone! I’ve been working on something I hope can help fellow developers: gameenginehub.com. It’s a simple site to help you figure out which game engine to choose for your next project. Whether you’re considering Godot, Unity, or Unreal, we’ve got you covered with comparisons, news, and guides.
Why I Built This Site
Choosing the right game engine can be a huge headache. Should you go with Unity, which is super popular and great for 2D and 3D games? Or is Unreal the better choice if you need powerful graphics and are aiming for something big? Maybe you’ve heard about Godot—the open-source engine that’s getting a lot of buzz lately.
It’s hard to decide, right? I’ve been there too. So I decided to create GameEngineHub as a place to make the process easier.
What You’ll Find on the Site
-Engine Comparisons: We break down Godot, Unity, Unreal, and other popular engines to help you figure out what’s best for your project.
-News & Updates: Stay updated on the latest trends and changes in the world of game engines.
-Guides & Tutorials: Learn how to get started with each engine and dive deeper into what makes them tick.
-Community Feedback: I’m always looking for feedback from other developers. How do you rate these engines? What’s your experience with Godot, Unity, Unreal, or any other game engines? Share your ratings and reviews to help others make a better choice!
The Story Behind It
I built this site because, when I was starting out, I found it hard to find clear, straightforward comparisons of the different game engines. There are so many factors to consider—performance, platform support, ease of use—and it can get overwhelming quickly.
So, I decided to put everything I’ve learned into one place. GameEngineHub is here to give you quick, reliable info so you can make a more informed decision about which game engine to use.
I’d Love Your Thoughts
I’m still working on improving the site and making it better. If you have any feedback, suggestions, or thoughts, please feel free to share! What’s missing? What would help you the most? Let me know!
Check it out at gameenginehub.com

value: Show HN: Find the Right Game Engine – Godot, Unity, Unreal, and More

author: neotanp


value: Show HN: StreamGate – A lock-free observability proxy in Go


value: ngruhn

value: Show HN: Generate Passwords from Regex Constraints

author: ngruhn