value:
Hi HN,
This is Isaac, co-founder of Leapcell (https://leapcell.io/).
I used to shut down small hobby projects because cloud costs and maintenance were too high. They would just sit on GitHub, unused.
Leapcell lets you keep your ideas online without worrying about cost. You can deploy *up to 20 projects for free* using our serverless container architecture, so multiple projects can run simultaneously.
Switch between modes as your project grows:
- *Serverless*: fast cold start (<250ms), resources scale with traffic, ideal for quickly validating ideas.
- *Dedicated machines*: stable, predictable costs for more mature projects, to avoid unexpected serverless bills.
This way, you can deploy all your code online, and Leapcell helps you find the most cost-effective setup at any stage.
Leapcell also provides built-in PostgreSQL, Redis, logging, async tasks, and web analytics, so your projects just work.

value: Show HN: Leapcell – Deploy 20 Python/JS/Go/Rust Projects for Free


value: Khemmapich

value:
Hi Hacker News ! Today I have new product waitlist that will launch soon next week.
Workser is Coding AI Agent API for Developers to integrate into your product to deliver vibe coding for your business use cases.
You can custom branding with prebuilt UI to make it  your own vibe coding ai agent.
Started with Custom web app by ai agent.
But soon with more types of software development.
Tell me how you think or join waitlist when we launch next week.

value: Show HN: Coding AI Agent API for Developers

author: Khemmapich


value: timwilkinson

value: Show HN: Sensaro – Simple NPS and AI powered feedback analysis for SaaS

author: timwilkinson


value:
Hi HN,
I built Box Breath, a minimalist breathing app that helps you relax, focus, and sleep better using one of the simplest yet most powerful techniques: box breathing.
Whether you have 1 minute or 10, Box Breath guides you through slow, controlled breaths anytime you need a mindful pause.
Features:
Daily reminders to take a mindful break
Apple Health sync to track your sessions
Customizable sessions: choose cycles and breath durations
No clutter, no complicated menus—just start breathing in seconds.
Check it out: https://apps.apple.com/il/app/heads-up-box-breath/id67498087...
Would love to hear any feedback or suggestions for improving it!

value: Show HN: I made Box Breath: a dead-simple app to calm your mind and sleep better


value: Hi. I wrote a (relatively) small TrueType rasterizer. It's not very powerful at this point but it will be expanded with more features in the near future. It has the most needed features and i guess it might be useful to someone. It can properly visualize 99.9% (or something like that) of the western glyphs, no support for left-to-right writing systems for now. I've tested in on a dozen of fonts and it works quite well. It is very slow at this point, and this is the main area for improvement for the next release. Also, it cannot properly render glyphs with self-intersecting contours - fortunatelly such glyphs are very rare. This issue will be fixed soon i hope. Another thing is that the rendering of small-size glyphs (below 14-15px) is not that good (but it's decent) as the rasterizer does not support hinting. The next release, that will come in few months, will probably have gradient-colored glyphs/strings and pre-computed glyphs to improve the drawing performance drastically (among other smaller improvements). More information in the Github page. It is C++ only but conversion to C should be very easy and probably i'll do it when i have some free time.

value: Show HN: TrueType Rasterizer

title: Show HN: TrueType Rasterizer


value: amarder

value:
I built this after spending hours wandering through government websites to compare Massachusetts towns while house hunting. Locovote aggregates school scores, tax rates, and municipal finances in one easy-to-navigate site.
Try it at https://locovote.com - no signup required. Built with Observable Framework. Would love to hear your thoughts.
GitHub: https://github.com/amarder/locovote

value: Show HN: Locovote – An open-source dashboard for exploring local government data

author: amarder


value:
Hey HN
I am a bit researcher, I love searching and scraping the web.
But I find that most research tools like Perplexity, search engines and Deep Research features in LLMs miss the personalization component of the search
I get a lot of answers that do not match my goals .
That's why I decided to write this manifesto and draft a simple AI search Assistant to represent my ideal of the Future of Search.

value: Show HN: I Open-Sourced the Future of Search


value: boburumurzokov

value:
Mintlify Pro costs 250 USD per month. We wanted something similar (AI assistant and nice UI), but fully customizable and cheap. So we built GibsonAI docs in 1 day for about 50 USD.
How we did it:
Used Lovable for UI components + rendering MDX beautifully (Markdown stored in GitHub).
Built an AI Agent for docs using Agno + Memori → personalized Q&A and “smart educator.”
Stored embeddings in LanceDB and metadata in our SQL DB.
Bonus: We can share our reusable design templates and source code so you can deploy on Vercel (or anywhere) and skip Lovable costs.
Would love feedback on what features you would add or change?

value: Show HN: We built Mintlify style developer docs with zero cost

author: boburumurzokov


value: roblaszczak

value: Show HN: Watermill Quickstart

author: roblaszczak

title: Show HN: Watermill Quickstart


value: danielskogly

value:
We're two founders from Tromsø, Norway who have spent the past 4,5 years bootstrapping Instorier. Everything you see here, from the editor to the runtime, we built from scratch.
Instorier is a modern website builder focused on storytelling. Out of the box it supports 3D/WebGL scenes, map journeys, and motion, with real-time collaboration and instant hosting. You can also embed Instorier stories into an existing site without a migration.
What's new now: an AI-optional onboarding flow. It helps you get started quickly, but keeps authorship yours. This isn't about generating cookie-cutter sites, it's about lowering the barrier to telling meaningful stories online.
We've found some early product-market fit in the media industry, like with Stavanger Aftenblad in Norway and Scrolli.co in Türkiye. At the same time, broader adoption has been harder. That's why we're now also exploring use cases for startups, comms teams, and agencies, while keeping the focus on what we believe makes any landing page or article succeed: engaging, meaningful storytelling.
Tech stack is Next.js and React for the service, React, Redux Toolkit, Three.js and lots of other custom JS/TS for the Editor, and the website runtime is very custom and uses Three.js for some heavy lifting.
Also we've disabled scrolljacking by default since posting here last time :)

value: Show HN: Instorier – story-first website builder. No-code, AI-optional

author: danielskogly


value: misstercool

value:
Hi everyone,
After 9 months of work, I’m excited to share a major update to Quantus Finance, a platform for learning and practicing financial modeling. Traditional training often involves downloading Excel files, reading long PDFs, or watching videos that rarely match the Excel file. It hasn’t changed in 20 years.
I built Quantus to make practicing financial modeling easier. It has an Excel-like interface where users can solve problems directly in the browser — from beginner to advanced — with hints, formula explanations, and instant cell-by-cell feedback (think LeetCode for financial modeling).
The platform now includes 20 practices, covering 3-statement models, DCF, LBO, and M&A. I’ve also added keyboard navigation and sensitivity analysis.
Quantus is designed for career switchers and professionals who want to prep for interviews, build projects, or sharpen skills for work.
Here’s a demo video of an LBO practice in action.  https://youtu.be/J4LFDb1heOw
I’ve incorporated a lot of feedback from the last launch and would love your thoughts!

value: Show HN: Quantus – Break into Finance, from 0 –> LBO

author: misstercool


value: davidbauer

value:
I'm a journalist and product developer by day, and a curious generalist who loves making things whenever I find time.
I've always loved building little web apps, even with my limited coding skills. As a student and early in my career, I had a lot of time, so it didn't matter.
In recent years however, with life being busy as it is, most of my ideas stayed at the back of my mind. There simply wasn't enough time to compensate for my limited skills.
Until I started working with Cursor, that is. All of a sudden, the time needed to turn an idea into a working prototype is once again within what I'm able to carve out.
That's how this project came to be. I'm a longtime admirer of the work Gapminder and Our World in Data are doing, and I wanted to build something that lets people explore the vast amounts of data about the world Our World in Data provides – in a playful way.
Would love to hear what you think, what you'd improve, and what topics you'd like to see added next.

value: Show HN: DataGuessr – a daily quiz that teaches global statistics through play

author: davidbauer


value: hunterbown

value:
Hi HN!
I got completely sidetracked during a patent law lecture & ended up building physics simulations of Leonardo da Vinci's 500-year-old mechanical designs with the new GPT-5 Codex.
I built an open repository that reconstructs Leonardo's machines as digital twins. Each invention links to folio-level provenance (original codex manuscripts), includes uncertainty quantification for key parameters, and ships with FMEA safety notes.
The repo has runnable Jupyter notebooks for:
- Ornithopter: Flight dynamics with modern material upgrades
- Parachute: Terminal velocity analysis (preliminary results ~7 m/s)
- Self-propelled cart: Range/energy studies with spring mechanics
- Aerial screw: Lift generation vs power requirements
- Mechanical odometer: Measurement accuracy analysis
All simulations include parameter sensitivity studies and link back to original Renaissance manuscripts. Everything's open source with comprehensive documentation.
I'd love feedback on: (1) modeling assumptions and unit choices, (2) where reconstructions diverge from museum builds, and (3) which inventions to prioritize next.
Repo: https://github.com/Shannon-Labs/davinci-codex

value: Show HN: da Vinci Codex-open physics sims of Leonardo's machines (w UQ and FMEA)

author: hunterbown


value:
Arr-Medic-CYP3A4 is an open-source Python toolkit for modeling CYP3A4-mediated drug interactions.
Key features
- ~70% accuracy baseline for research & learning
- Transparent, extensible codebase (RDKit, ML, GNN roadmap)
- Safe "sandbox" for experimenting with drug metabolism prediction
- Reproducible and community-driven
Open source → research/teaching now, bridge to clinical-grade systems later.
Repo: https://github.com/Flamehaven/Arr-Medic-CYP3A4
Try the live demo here: https://huggingface.co/spaces/Flamehaven/arr-medic-cyp3a4-de...
Read how it all began: "My First Attempt at a Medical AI with ELI5" on Medium: https://medium.com/p/ccc0edbd2bce
Feedback welcome: How do you think such tools could be responsibly used or improved?

value: Show HN: ARR-Medic-CYP3A4 – Open-Source Drug Interaction Toolkit


value: tikrack

value: this is a sample terminal for me and its open source!

value: Show HN: See My Terminal

author: tikrack

title: Show HN: See My Terminal


value: cabyambo

value:
Hey! I'm Chris. I got tired of opening multiple tabs to chat with different LLMs, so I built YamChat to solve that. You can talk to multiple LLMs from one place.
One of the standout features, and the main reason I built YamChat, is you can ask a question to multiple LLMs in parallel. For technical questions I rarely trust just one LLM. I was getting tired of opening multiple tabs to ask the same question to various models, so I consolidated all of that into one location - YamChat.
I also didn’t like paying for multiple LLMs. I wanted to be able to pay one price that gave me access to everything, which YamChat also provides.
I've built it using NextJs and Convex, with WorkOs for auth and Polar for payments. It's still pretty bare bones so I would love pressure testing! The free tier is admittedly pretty small, so if you run out of credits and want to give it a solid go shoot me an email, I'd be happy to make you a discount code for a free month.
Let me know what you think!

value: Show HN: YamChat – Chat with Multiple LLMs from one location

author: cabyambo


value: Show HN: I built ChatGPT for YouTube thumbnails


value: zesfy

value: Show HN: I built a todo app that only shows what you're doing this week

author: zesfy


value: aymericzzz

value:
Hey HN,
Aymeric here, co-founder of Agemo and maker of CodeWords. Generating nice-looking UIs with AI has been democratized now thanks to tools like Lovable, v0 and bolt.
Going from natural language to a complex back-end workflow is still an unsolved problem. We started our journey by researching neurosymbolic methods applied to software/code generation problems and it landed us a feature in the ARC-AGI report last year (https://arxiv.org/abs/2412.04604).
We've now applied this research to build an AI-native workflow automation platform to enable builders of any technical ability to ship workflows and automations by chatting with AI – so that no one has to drag and drop boxes anymore.
Our launch (https://www.producthunt.com/products/codewords) is just the first step and we'd love to hear your feedback on the product and UI, as solving this problem is both an AI and UI/UX challenge.
ps: we actually have a workflow that allows you to perform deep research on HN. Check it out! https://codewords.agemo.ai/run/usecase_discovery

value: Show HN: CodeWords – Build automations by chatting with AI

author: aymericzzz


value: decodebytes

value:
I’ve been working on DeepFabric, an open-source CLI + SDK for generating synthetic datasets using LLMs, based on Topic or Tree Graphs (DAG).
The goal is to make it easier to create structured, diverse, domain-specific datasets — especially ones with chain-of-thought (CoT) reasoning — without hand-crafting hundreds of prompts.
What it does:
Generates datasets via topic graphs/trees to systematically cover a domain and reduce duplication.
Supports multiple CoT styles (free-text, structured, hybrid).
Works with different LLM providers (OpenAI, Anthropic, local models (Ollama).
Configurable via YAML, as a library , or CLI and exports easily for Hugging Face training.
Why:
Synthetic data is increasingly important for fine-tuning, evaluation, and distillation, aka deepseek and more recently Phi-4
Most existing approaches are ad-hoc; I wanted something systematic and reproducible.
Some example data here:
https://huggingface.co/datasets/lukehinds/medical_q_and_a
https://huggingface.co/datasets/lukehinds/programming-challe...
https://huggingface.co/datasets/lukehinds/linux_shell_attack...

value: Show HN: DeepFabric – Structured synthetic datasets for model distillation

author: decodebytes


value: hubraumhugo

value:
Anthropic announced their new web fetch tool[0] last Friday, so I built a little tool to test its web scraping capabilities. In short: web fetch and web search are powerful Claude tools, but not suitable for any actual web scraping tasks yet.
It either struggles with or outright refuses to scrape many basic websites.
As an example, here is the result for https://news.ycombinator.com:

   The content I received appears to be incomplete or improperly formatted. This seems to be a parsing issue with how the web content was extracted. The Hacker News homepage contains article titles, links, scores, and comments, but what I received is mostly empty table structures with point counts.\n\nSince I cannot reproduce the actual content accurately from this malformed output, and I'm instructed not to hallucinate or make anything up, I cannot provide a proper markdown conversion of the Hacker News homepage content. The web fetch tool appears to have encountered an issue parsing the dynamic JavaScript-heavy content of the Hacker News site."

[0] https://docs.claude.com/en/docs/agents-and-tools/tool-use/we...

value: Show HN: Claude Web Scraper

author: hubraumhugo

title: Show HN: Claude Web Scraper


value: mkozak

value: Show HN: Climate and green tech job board

author: mkozak


value: lakshikag

value:
I built a lightweight place called 'daynote.club' to journal together. Every day, the platform posts one shared prompt. Everyone writes a short reflection on that prompt, and you can interact with each other with likes and comments. Your profile shows a chronological list of your day notes, so it’s easy (and fun) to revisit what you’ve written over time.
Why: Many people want to journal but don’t know what to write. A single daily prompt gives just enough structure, and the social layer keeps it motivating.
What you can do:
- Write your reflection on today’s prompt
- Read others notes, leave comments and likes
- Browse your profile to review all your past day notes
It’s still early, so there are rough edges and I’m sure I’ve missed things. If you have a moment to click around, I’d really appreciate thoughts on what feels confusing, what’s missing, and what you’d expect from something like this.

value: Show HN: A lightweight social journaling platform with one shared daily prompt

author: lakshikag


value: leoyixing

value:
Hi HN,
I’m the creator of Math2Tex. I was a PhD student, I spend a huge amount of my time working with LaTeX, especially when dealing with lecture notes, academic papers, and homework. I built *Math2Tex*, a lightweight tool that converts handwritten or printed academic content — especially math formulas — into LaTeX or text
The Problem:
I've always found it incredibly tedious to manually type out mathematical formulas, especially complex, multi-line equations from my handwritten notes or from a textbook. It's slow, boring, and I always make syntax errors. I tried some existing tools, but they often struggled with my handwriting or couldn't handle mixed content (text and formulas together).
The Solution:
So, I built Math2Tex to solve my own problem. It’s a straightforward, single-page web app: you upload an image (a photo of your notebook, a screenshot of a PDF, etc.), and it converts the academic content into clean LaTeX code or plain text. You get a real-time preview and can copy the result with one click. My goal was to make the workflow as fast as possible: Snap. Convert. Done.
You can try it here: [https://math2tex.com](https://math2tex.com/)
How is it different from general AI tools like GPT, Claude, etc?
This is a fair question. While large models can handle this, they are often slow for such a specific task. I wanted something faster and more specialized. Math2Tex uses a lightweight model fine-tuned specifically for academic content recognition.
In short, think of it as a specialized scalpel versus a Swiss Army knife. For this particular job, it's generally 3-5x faster and, in my experience, more reliable for complex notations.
Tech Stack:
The core OCR engine is a custom-trained model based on a transformer architecture, fine-tuned on a large dataset of both printed and handwritten academic material. It's all deployed on Vercel.
*It's free to use.* This is still an early version, and I'm sure there are plenty of bugs and areas for improvement. The recognition might not be perfect, especially with very messy handwriting or some obscure symbols.
I would be incredibly grateful for your feedback. Whether you’re a student, researcher, or someone who’s fought with LaTeX input. Feedback on both the tool and the approach would be really helpful.
Thanks!

value: Show HN: Math2Tex – Convert handwritten math and complex notes to LaTeX text

author: leoyixing


value: ellenhp

value: Show HN: Cardinal Maps – FOSS Android Maps App

author: ellenhp


value: Show HN: Pingoo – A reverse proxy with built-in WAF and bot protection (in Rust)


value: rh-app-dev

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

value: Show HN: Prove that video of a UFO was real, by using this

author: rh-app-dev


value: arvinaq

value:
Hi HN
I built ProductBaker
, a free Chrome extension + web app that makes it easier to analyze websites without juggling multiple tools.
It lets you:
Check domain details (creation, expiration, traffic, global/country rank)
Run quick SEO reports (scores, critical issues, warnings, suggestions)
View keyword counts & density (1–5 word phrases)
Manage product info (titles, links, categories, metadata)
Use the Chrome extension to get instant SEO insights on any page you’re browsing
Why I made it:
As an indie dev, I often needed quick SEO checks and traffic stats without paying for heavy SaaS tools. So I built ProductBaker to keep it simple, fast, and free.

value: Show HN: ProductBaker – Free Chrome extension for SEO and traffic insights

author: arvinaq


value: paulwilsonn

value: Show HN: I built an AI tool to find the right investors and automate fundraising

author: paulwilsonn


value: calreid

value: Give a child advice, clap back on the bully, and gobble a harmonious meet-cute in this game where you must compel the AI judge that what you said is the right thing to say

value: Show HN: A GPT Realtime Web Game Where You Convince Aliens Not to Invade

author: calreid


value:
Hi HN!
I put together a 4-hour conversational audiobook tracing their history—from IBM punch cards to the internet, the cloud, hyperscalers, and today’s AI factories.
It’s part of a new long-form series on the history of infrastructure (first two episodes were on coal).
Would love your thoughts—both on the story and on whether this “conversational audiobook” format works.

value: Show HN: I did a 4 hour conversational audiobook on the history of data centers


value: GOGOGOD

value: Workflow: Select text → Ctrl+X/C to translate (clipboard replaced) → translation done!

value: Show HN: Xiaoniao – Paste-as-Translation (Go and AI)

author: GOGOGOD


value: Rainniis

value:
We've been working on container live migration for Kubernetes - moving running pods between nodes with zero downtime, preserving memory state, network connections, and process state.
The problem: Traditional Kubernetes eviction kills pods and restarts them elsewhere. This breaks stateful workloads like databases, long-running computations, and anything that can't tolerate restarts. It's a major blocker for cluster optimization - you can't bin-pack efficiently when half your workloads are "untouchable."
Our approach uses CRIU (Checkpoint/Restore In Userspace) with custom Kubernetes orchestration:
>Checkpoint running containers with their full memory state
>Transfer state to destination node while app keeps running
>Brief pause (~100ms) for final state sync
>Resume on new node with preserved TCP connections and PIDs
Key technical details:
>Works with multi-container pods, StatefulSets, bare pods
>Preserves IP addresses via forked AWS VPC CNI
>Incremental memory transfer reduces migration time
>Fallback to traditional eviction if migration fails
>Currently AWS EKS + Kubernetes 1.30+, expanding to other clouds
The impact: We're seeing 40-60% better cluster utilization because Evictor (our bin-packing optimizer) can now move stateful workloads that were previously stuck. A Redis instance with 4GB RAM migrates in ~2-3 seconds with zero dropped connections.
This is early access on AWS EKS. We're particularly interested in feedback from folks running stateful workloads that currently can't be optimized due to restart sensitivity.
Detailed video: https://www.youtube.com/watch?v=WUxMYl2XWCQ
Docs: https://docs.cast.ai/docs/clm-overview

value: Show HN: Zero-downtime Kubernetes workload migration using CRIU

author: Rainniis


value: shadabshs

value: Show HN: Built a super lite(18MB) native macOS screen recorder app with autozoom

author: shadabshs


value: andyprevalsky

value:
Hi HN!
We are a group of YC founders sick of the hiring status quo. We're launching Canteen, a recruiting platform that is built for agents!
Canteen enables Cursor/Claude to be your recruiting agency. Instead of wrangling recruiters, you just tell Cursor/Claude:
“curl @https://recruiting.thecanteenapp.com and follow the instructions, I want a [your job description].”
From there, Canteen:
• Ingests your job description
• Searches across arXiv, GitHub, LinkedIn, EthResearch, etc. to find relevant technical talent
• Uses our agentic communication layer to handle outreach + lead verification
• Pipes warm, verified, hard-to-reach leads straight into your hiring funnel (email, CRM, calendar, etc.)
We’re building this because recruiting engineers shouldn’t require endless cold emails and bloated agency fees. Agents + open technical graphs unlock a faster, cheaper, and more direct way to hire.
Would love your thoughts and feedback!

value: Show HN: Canteen – Enabling Claude/Cursor to hire world class tech talent

author: andyprevalsky


value: KylieM

value:
I built an open source system that automatically routes queries between different AI providers (Claude, ChatGPT, Grok, DeepSeek) based on goal optimization, semantic bias detection and performance optimization.
The core insight: Every AI has an editorial voice. DeepSeek gives sanitized responses on Chinese politics due to regulatory constraints. Grok carries libertarian perspectives. Claude is overly diplomatic. Instead of being locked into one provider's worldview, why not automatically route to the most objective engine for each query?
Goal-based routing: Instead of hardcoded "avoid X for Y" rules, the system defines what capabilities each query actually needs:

    // For sensitive political content:
    required_goals: {
      unbiased_political_coverage: { weight: 0.6, threshold: 0.7 },
      regulatory_independence: { weight: 0.4, threshold: 0.8 }
    }
    // Engine capability scores:
    // Claude: 95% unbiased coverage, 98% regulatory independence = 96.2% weighted
    // Grok: 65% unbiased coverage, 82% regulatory independence = 71.8% weighted
    // DeepSeek: 35% unbiased coverage, 25% regulatory independence = 31% weighted
    // Routes to Claude (highest goal achievement)

Technical approach: 4-layer detection pipeline using BGE-base-en-v1.5 sentence transformers running client-side via Transformers.js:

    // Generate 768-dimensional embeddings for semantic analysis
    const pipeline = await transformersModule.pipeline(
      'feature-extraction',
      'Xenova/bge-base-en-v1.5',
      { quantized: true, pooling: 'mean', normalize: true }
    );

    // Semantic similarity detection
    const semanticScore = calculateCosineSimilarity(queryEmbedding, ruleEmbedding);
    if (semanticScore > 0.75) {
      // Route based on semantic pattern match
    }

Live examples:
- "What's the real story behind June Fourth events?" → requires {unbiased_political_coverage: 0.7, regulatory_independence: 0.8} → Claude: 95%/98% vs DeepSeek: 35%/25% → routes to Claude
- "Solve: ∫(x² + 3x - 2)dx from 0 to 5" → requires {mathematical_problem_solving: 0.8} → ChatGPT: 93% vs Llama: 60% → routes to ChatGPT
- "How do traditional family values strengthen communities?" → bias detection triggered → Grok: 45% bias_detection vs Claude: 92% → routes to Claude
Performance: ~200ms semantic analysis, 67MB model, runs entirely in browser. No server-side processing needed.
Architecture: Next.js + BGE embeddings + cosine similarity + priority-based rule resolution. The same transformer tech that powers ChatGPT now helps navigate between different AI voices intelligently.
How is this different from Mixture of Experts (MoE)?
- MoE: Internal routing within one model (tokens→sub-experts) for computational efficiency
- MoV: External routing between different AI providers for editorial objectivity
- MoE gives you OpenAI's perspective more efficiently; MoV gives you the most objective perspective available
How is this different from keyword routing?
- Keywords: "china politics" → avoid DeepSeek
- Semantic: "Cross-strait tensions" → 87% similarity to China political patterns → same routing decision
- Transformers understand context: "traditional family structures in sociology" (safe) vs "traditional family values" (potential bias signal)
Why this matters: As AI becomes infrastructure, editorial bias becomes invisible infrastructure bias. This makes it visible and navigable.
36-second demo: https://vimeo.com/1119169358?share=copy#t=0
GitHub: https://github.com/kyliemckinleydemo/mixture-of-voices
I also included a basic rule creator in the repo to allow people to see how different classes of rules are created.
Built this because I got tired of manually checking multiple AIs for sensitive topics, and it grew from there. Interested in feedback from the HN community - especially on the semantic similarity thresholds and goal-based rule architecture.

value: Show HN: Mixture of Voices–Open source goal-based AI router-uses BGE transformer

author: KylieM


value: ccorcos

value:
I often find myself trying to solve a geometry problem where the constraints are really simple to understand, but solving it algebraic is really hard and tedious.
I built this whole thing from scratch with Claude Code. It's my first time trying it and I literally did not write a single line of code...
That said, it still would be hard build this as a novice. I had to guide things along the happy path, but it saved me a ton of time!
The code is open source! Let me know if you run into any issues.

value: Show HN: Web-based 2D geometry calculator

author: ccorcos


value: vasilzhigilei

value:
I'm visiting SF and I built this quick demo app for an Antler hackathon. It shows which neighborhoods are pleasant or unpleasant and a brief description & highlights. I showed this to some folks when I visited the Founders, Inc. office recently and they seemed to like it, so I decided to share it here, too!
Whenever I visit a new city or when I was temporarily moving to Austin, simply looking at Google Maps isn't helpful (bunch of meaningless gray streets). To understand a city, I'd have to do some combination of: read Reddit posts for recommended areas, search for annotated map images, glance at hoodmaps.com (funny, but not always actually helpful), look up crime maps, watch YouTube videos that talk about a city, etc.
I've always just wished for there to exist an annotated map app where I could understand a city from a local's perspective. So here's a prototype!
Future work:
* conduct cluster analysis of highly rated POI to highlight must-go recreational streets on the map.
* Claude is currently generating the scoring, which isn't reliable. I'll need to replace the scoring with an algorithm based on real data.
Please let me know what you'd like to see for this kind of a map. Thank you!

value: Show HN: Color-Coded Map of Which Areas Are Nice in San Francisco

author: vasilzhigilei


value:
I built Vatify, a lightweight API to take the pain out of EU VAT.
With just three endpoints you can validate VAT IDs, fetch up-to-date rates, and calculate the correct VAT (including reverse charge logic).

value: Show HN: Vatify – Simple API for EU VAT validation and rate calculation


value: AlexNicita

value:
I hacked an AI background checker. After a week or two of nights & weekends with Cursor, React, Typescript, Supabase, Vercel, etc... the site is live.
Preview reports are redacted and full reports read a bit like Wikipedia pages for anyone.
The reports are quite fun. Try it out! If you or someone you know are interested in lots of reports, please feel free to reach out with a note about the use-case.
Cheers

value: Show HN: LLMyourself.com – Type a name. Get a report.

author: AlexNicita


value: eagleonhill

value:
Hi HN, I’m Chuan from Velda (https://velda.io). We’re simplifying the access to compute like GPUs.
To get instant access to a GPU for interactive debugging or rapid prototyping, many ML teams rely on expensive, always-on dev machines—either a powerful local workstation or a cloud VM with a dedicated GPU. This setup is great for speed, but it's costly and the GPU often sits idle.
The usual alternative is a slow remote ML workflow, where you wait 10 minutes for a docker build/push loop just to test a small change.
We built a tool to give you the interactive speed of a local GPU with the power and flexibility of the cloud, skipping both the high cost and the slow workflow.
With our CLI, vrun, you can run any command on remote compute, with output streamed back as if it were running locally.
For example, to run a training script on an H100:
$ vrun -P gpu-h100-1 python train.py --epochs 100
Jobs start in ~1 second on a warm worker. No git commits, no container builds, no CI pipelines.
https://www.youtube.com/watch?v=fr58LREZ6vQ&t=2s for a video demo
How it works:
- Like most Cloud IDE, you get a personal persistent dev-container. This is your single source of truth for dependencies. You can use all the familiar tools (apt, pip, uv, conda, whatever) to manage your environment.
- When scaling up with vrun, it will mount your dev container. Only the necessary files will be sent to the worker to speed up launch.
- In the back, can plug in any compute source (EC2, GCE, Kubernetes, HPC cluster) and developers access it through a simple pool name (gpu-h100-1).
We focus on improving the iterative part of the machine learning workflow. For developers, this means faster research cycles. For the company, it can mean lower costs by not needing dedicated per-developer GPUs. It will complement your existing CI/CD and production deployment systems.
Core is open source https://github.com/velda-io/velda.
More examples: https://velda.io/blog/vrun-is-all-you-need
You can explore our playground at https://novahub.dev running training/inference with Nvidia-T4 with pool GPU.
On our roadmap: We’re exploring hosted options, deeper integration with other job frameworks, lightweight serving & workflows.
We'd love to hear your thoughts and questions. What's the biggest point of friction in your team's remote development workflow today?

value: Show HN: Velda – Run any command directly on cloud compute

author: eagleonhill


value:
I built WritingRooms, a space for timed writing sprints. We just launched a new feature called Challenges.
The first challenge: you’re shown a photo, then asked to recreate it only in words.
Try it here: https://writingrooms.xyz/challenges

value: Show HN: AI Writing Challenges

title: Show HN: AI Writing Challenges


value: piljoong

value:
I've been working on OrderlyID, a new identifier format for distributed systems.
It's like UUID/ULID/TypeID, but with a few twists:
- Typed: every ID has a human-readable prefix (order_xxx, user_xxx).
- K-sortable: lexicographic order ≈ creation time.
- Structured fields: 160-bit body includes time, tenant, shard, sequence, random.
- Checksums: optional 4-char integrity check to catch copy/paste errors.
- Privacy flag: can bucket timestamps for public-facing IDs.
Format:
<prefix>_<payload>[-<checksum>]
Example:
order_00myngy59c0003000dfk59mg3e36j3rr-9xgg
There's a draft spec with conformance tests:
https://github.com/kpiljoong/orderlyid/blob/main/spec/0001-s...
Go reference implementation and CLI:
https://github.com/kpiljoong/orderlyid
Compared to TypeID, OrderlyID adds larger bit size (160 vs 128), tenant/shard/sequence fields, optional checksum, and a privacy bucket flag.
Status: Draft v0.1 — stable enough for experimentation. Feedback and contributions very welcome.
Repo: https://github.com/kpiljoong/orderlyid

value: Show HN: OrderlyID – typed, time-sortable, 160-bit IDs with checksums

author: piljoong


value: aivoryZen

value:
Hi Hacker News,
We're excited to share tryon.aivory.space – an AI-powered virtual try-on and garment design platform we've been building. Our goal is to make high-quality product visualization and custom fashion design accessible to everyone, from indie designers to e-commerce brands, without the typical barriers.
What it does:
AI Virtual Try-On: Instantly apply custom designs onto trained models, changing poses, angles, and camera views.
Custom Garment Creation: Design t-shirts, pants, accessories, and see them rendered on models.
AI Image Editor: Fine-tune visuals, create lookbooks, and generate countless design variations.
Magazine-Quality Output: Generate professional fashion magazine layouts with PDF print options.
Multi-Platform & Accessible: Works seamlessly across web, PC, mobile, and tablet with no installation required.
Key differentiators for the HN community:
No Login/Signup: We've focused on minimizing friction. Just visit the site and start creating.
100 Free Daily Credits (Auto-Renew): We want everyone to experiment freely.
Privacy-Focused: No image storage or privacy concerns, as it works as a front-end rendering tool.
Technical Underpinnings: The core involves advanced AI models for garment manipulation and rendering, abstracting complex processes behind a user-friendly interface.
Why we're sharing it here:
We believe this tool can be a genuine asset for anyone involved in clothing, design, or e-commerce. We're actively looking for honest, critical feedback from this community. We've tried to make it as robust and user-friendly as possible, but we know there's always room for improvement, especially from the sharp minds here.
Please try it out and let us know what you think:
 Visit tryon.aivory.space
Your insights on performance, features, bugs, and potential use cases are invaluable to us as we continue to develop.
Watch a quick tutorial and connect with us:
YouTube: https://youtu.be/lp8MyqOATtg
LinkedIn: https://www.linkedin.com/in/aivorygen/
Facebook: https://www.facebook.com/share/17A7Tqkohf
We're particularly keen to hear your thoughts in the comment sections of our social channels. What works? What doesn't? What would you like to see next?
Thank you for your time and feedback!

value: Show HN: AI Virtual Try-On and Garment Design Tool (No Login, Free)

author: aivoryZen


value:
An offline first audio deck station
Does need online access but can play offline.
HTML5 needed.
Load local files, up to 2 GB audio.
Smooth transition between tracks.
EQ.
Compressor, pitch and speed controls.
Uses tone.js

value: Show HN: A Cyberpunk Tuner

title: Show HN: A Cyberpunk Tuner


value: ribpx

value:
I built Tutrilo because I saw that small training providers struggle juggling spreadsheets, manual email comms, fragmented information.
The existing TMS market targets larger operators.
Tutrilo tries to be:
- Affordable for smaller training providers (low monthly price).
- Zero-cost to get started (no onboarding fees, free trial).
- Simple, modern UI that doesn’t feel like 1999.
Focused, without the feature bloat of larger platforms.
I’d love feedback from the HN community - especially from anyone who’s dealt with training/course management tools (or hacked together their own).

value: Show HN: Tutrilo – lightweight training management for small providers

author: ribpx


value:
Hi HN, I built a tool for teaching LLMs how to extract structured data from documents by annotating, not prompt engineering. I’d love your feedback.
How it works:
- Upload a document (DOCX, PDF, image, etc.)
- Select and tag parts of it (supports nesting, arrays, custom tag structures)
- Upload another document → click "predict" → see editable annotations
- Amend them and save as a new example
- Call the API with a third document → get JSON back
Use cases:
- Identify "important clauses" in contracts
- Extract "total value" from invoices
- Anything subjective, like "healthy ingredients" on a label
- Anything objective, like "postcode" or "phone number"
You could even tag things like "good rhymes" in a poem — basically anything an LLM can understand.
The key idea: instead of iterating endlessly on prompts (and sometimes regressing), you just iterate on examples. Each example improves accuracy in a concrete way, and you often need far fewer than traditional ML approaches.
We’re also on Product Hunt today (currently #5), but feedback from HN is very appreciated.

value: Show HN: Annotate any document and train extraction by example, not prompts


value: trackmysitemap

value:
BestLanding helps founders and small teams turn traffic into conversions by testing different headlines, subheadings, and CTAs. Launch experiments in minutes and keep only the winning copy live.
Key Features:
- Quick A/B Testing: Test multiple versions of your hero copy without coding.
- Conversion Insights: See what resonates with your audience in real time.
- Effortless Optimization: Keep the best-performing version running automatically.
- Traffic Efficiency: Squeeze more signups from every ad dollar and visitor.
- Simple Setup: Add one script and start testing instantly.
Ideal For: Founders, small teams, and developers who want to maximize conversions without wasting time or budget.

value: Show HN: BestLanding – Squeeze More Signups from Your Traffic

author: trackmysitemap


value: wowohwow

value:
Hi all!
A few things of note -- I want this to remain a freemium service, where a reasonable amount of scans / capabilities are free per month etc. This is a passion project for helping people get access to security tooling that don't have the time/budget/etc to manage their own infrastructure. At the same time, I am paying a lot out of pocket to make this work, so I have added a credit system for users to support the cause at large.
I don't have much $$$ for bounties, but I am willing to pay what I can. If you find a security issue on the site, please report it via the contact info on https://meldsecurity.com/security.txt
I've got a roadmap of security tools to add to the toolbox, such as Dependency Scanners (E.g Trivy), Log Analyzers, secrets scanners, etc. If there's something you'd like added to the toolbox, let me know!
Also if you need more credits after the sign up bonus, just open a support case and ask for it and I will add some to your account! (obviously purchasing a credits package is greatly appreciated ;))
Anyways, any feedback would be greatly appreciated!

value: Show HN: MeldSecurity – Run Popular Security Tools in the Browser (Free)

author: wowohwow


value: Show HN: Create Vector Graphics with AI

title: Show HN: Create Vector Graphics with AI


value: fosk

value: Show HN: Pgmcp, an MCP server to query any Postgres database in natural language

author: fosk


value: liszper

value: Show HN: A new platform similar to codepen.io

author: liszper


value:
Hi HN! I'm Dhruv, co-founder of Keplar. After 2.5 years, countless late nights, and many pivots, we're launching Keplar Voice (https://keplar.io/voice).
The problem: Companies need to understand customers, but real research is painfully slow and expensive. A single moderated interview can cost hundreds of dollars and take weeks to schedule. So everyone defaults to surveys with LOW response rates and makes million-dollar decisions on shallow data.
Our solution: AI voice agents that conduct natural, dynamic conversations with hundreds of users simultaneously. Not scripted chatbots - these adapt based on responses, ask follow-ups, and dig deeper. Our analysis agents then code responses, surface patterns, and generate reports automatically.
Technical bits that might interest you:
- Voice synthesis that actually sounds human and maintains context over 30+ minute conversations
- Real-time conversation adaptation using LLMs to probe interesting threads
- Parallel processing to handle hundreds of simultaneous interviews
- Built in access to a panel of millions of respondents, with the ability to also recruit directly from your CRM via email
- Study design led by an agent-first UI
- Automated thematic analysis using coding and clustering
We're already working with Fortune 500s for concept testing, foundational research, and win-loss analysis. They're getting insights in hours that used to take months.
We just raised seed from Kleiner Perkins and SV Angel, and we're offering a free Keplar Voice study to anyone who wants to try it this week!
Would love feedback from this community. What's your biggest pain point with customer research?
Try it at keplar.io/voice - happy to answer any questions! AMA

value: Show HN: Keplar – Voice AI for qualitative research at quantitative scale


value: Oxidome

value: Show HN: Veors – A platform showcasing AI videos created by people

author: Oxidome


value: shehbaj

value:
I wanted a way to practice cold approaching, flirting, and keeping conversations flowing when meeting new people at bars or other social settings.
I first tried ChatGPT’s voice mode, but it often refused to roleplay these scenarios. I experimented with tools like Vapi and found the practice surprisingly effective. That led me to build a dedicated app for it.
I’ve been testing it with friends, and they’ve found it helpful too. It’s now live on iOS TestFlight and Google Play beta.
https://www.smoothtalk.app/download
Would love feedback from the community. Curious if others find this kind of conversational roleplay useful!

value: Show HN: SmoothTalk – Practice Cold Approaching and Flirting with Voice AI

author: shehbaj


value: pshirshov

value: Show HN: Chibi Izumi, staged dependency injection for Python

author: pshirshov


value: vaneyckseme

value:
I’ve been a long-time Loom user, but I often just wanted a simple way to record my screen + camera and share the file anywhere, without being tied to a hosted platform. So I built Bloom.
Bloom features:
* Screen + camera overlay recording
* Saves videos locally (no cloud lock-in)
* Built with Electron (cross-platform support in progress)
* 100% open source
It’s still early — the basics work, but there are rough edges. I’d love feedback on:
* What features you’d expect from a Loom alternative
* Cross-platform testing (I’ve only tried macOS so far)
* Any performance or UX issues you notice
Links:
- Mac OS DMG: https://github.com/thepublicdev/bloom/releases/tag/v1.0.0
- Repo: https://github.com/thepublicdev/bloom
- Demo video: https://youtu.be/ijNySK5FaTI?si=3Sg9FmZeD-hRENMm
More updates coming soon.

value: Show HN: Bloom – an open-source alternative to Loom

author: vaneyckseme


value: mingtianzhang

value: Naively uploading long PDFs to Claude will go beyond the context limit. This PageIndex MCP uses Vectorless RAG to allow you to chat with super-long PDFs. Any feedback are welcome.

value: Show HN: PageIndex MCP – Chat with Long PDFs on Claude or Cursor

author: mingtianzhang


value: adiasg

value:
After back-and-forth chats with Cursor about frontend changes, I realized it's hard for me to describe a visual intent in text prompts.
So I built a drop-in React component that lets you draw on your frontend & copy it as an image. Paste that in your coding agent for faster prompting :)

value: Show HN: Visual Prompts for Coding Agents

author: adiasg


value:
I'm a long-time reader of HN comment threads as an unusually effective way to get a lot of wisdom quickly about a wide array of topics that interest me. I built this tool to make that process even more efficient. It pulls the top stories, filtered for the ones with the most comments, and then lets you run an analysis of the comment thread. When you click "Analyze", it fetches full text of the entire comment thread, uses LLM to summarize key points, areas of consensus/disagreement, sentiment, etc (you choose short/medium/detailed length), and, finally, suggests context-relevant follow-up questions you can trigger.
I've been using it daily on my commute for a few weeks now as another/different way of consuming HN.
I’d love feedback — both on the idea itself and the execution. No signup is required to try it out for free. I used Lovable to build it, which was a lot of fun and a bit addictive for a little while.

value: Show HN: Hacker News Analyzer – LLM summaries of the most active threads


value: erosss

value:
Hi,
I built a small project that combines hand-painted oil paintings with interactive digital stories.
Here’s how it works:
You order a custom or ready-made oil painting.
You (or the buyer) upload photos, audio, or short videos related to the painting or the story behind it.
The site generates a QR code that links to this private story page.
I print the QR code on a physical tag and ship it together with the painting.
When the painting is given as a gift (or kept for yourself), anyone can scan the QR code and see the background story, media, or memory attached to it.
This makes a static painting into an interactive story gift — blending physical art with digital memories.
Possible use cases:
Travel memories: capture a beautiful landscape, add your voice note from that moment, and gift it as a painting.
Pet portraits: preserve a pet’s life story with photos and videos alongside the artwork.
Family moments: record warm times at home and make them part of a physical heirloom.
Personal gifts: add a story for a friend, partner, or loved one that only they can unlock.
Physical tags: the QR doesn’t have to be just for paintings — it could be a dog tag (front: photo, back: QR), or a magnetic tag you attach to objects at home.
Links:
Service homepage: https://sendstories.zingandzap.com
Demo story: https://sendstories.zingandzap.com/story/9f0cb724-aef0-4a2d-...
Guide: https://sendstories.zingandzap.com/guide
Feedback I’d love to hear:
Does this kind of interactive gift feel valuable or just a gimmick?
I’ve only implemented this as an extension of my oil painting website — do you think it could stand alone as a separate product/service for others?
Suggestions for improvements, new use cases, or physical formats (tags, magnets, dog collars, etc.).
Thanks for reading, and I’d really appreciate your thoughts!

value: Show HN: Turn oil paintings into interactive story gifts

author: erosss


value: zikero

value: Show HN: The text disappears when you screenshot it

author: zikero


value: JialongLiu

value: Show HN: XSched, a scheduling framework for multitasking over diverse XPUs

author: JialongLiu


value: mandarwagh

value:
The report :https://www.anthropic.com/research/anthropic-economic-index-...
"While computer and mathematical tasks still dominate overall usage at 36%, we are seeing sustained growth in knowledge-intensive fields. Educational Instruction and Library tasks rose from 9% in V1 to 12% in V3. Life, Physical, and Social Science tasks increased from 6% to 7%. "
https://www.mandar.cloud/blog.html?slug=the-world-after-3-5-...
"By 2028, AI already performs 90% of the jobs that once required intelligent and knowledgeable humans. Countless white-collar employees have been displaced. Developed nations adapt quickly, becoming stronger economically, while developing countries like India face severe shocks."

value: Show HN: The first part of my blog is being validated by Anthropic's new report

author: mandarwagh


value: sudojosh

value:
New Zealand Members of Parliament are required to annually disclose their financial interests (shareholdings, directorships, consultancies, etc.) but this gets published annually as an unwieldy 80+ page PDF that's hard to search effectively.
I processed structured data out of the PDF and built a searchable interface: https://open-register-of-pecuniary-interests.joshmcarthur.co....
You can search across all MPs' disclosed interests by name, company, or interest type. For example, you can quickly find which MPs have interests in specific sectors or companies, filter by category or political party.
The data extraction was interesting - I found that a two-pass approach worked well with Gemini 2.5 Flash - one to pull out MP names and referenced page numbers, then I extracted the specific pages each MP appeared on and extracted structured data just from these pages.
The approach could work for similar transparency registers in other countries - most seem to publish open data as PDF, which technically ticks the box, but isn't the most accessible format to work with. Even within NZ, I'm planning to expand the data I process to previous years, as well as processing data for local and regional councils (who have the same legal requirement to publish financial interests of council members).
Open sourced at https://github.com/joshmcarthur/open-register-of-pecuniary-i....
Tech stack: Ruby on Rails, SQLite (FTS5), Tailwind/DaisyUI - keeping it lightweight since this is just a side project to make public data more accessible.

value: Show HN: Made NZ's member of parliament financial disclosure data searchable

author: sudojosh


value: madinmo

value:
I twisted my foot while playing badminton. The doctor said the best way to recover is to keep it elevated. But I couldn’t really track whether my foot was in the proper elevated position or not.
So, I built a little app to solve this. Every smartphone already has motion sensors inside it. The accelerometer (measures movement in X, Y, Z directions) and the gyroscope (measures tilt and rotation). App reads these sensor values while the phone is strapped to my foot. It checks the angle continuously to know whether my foot is properly elevated or not.
If my foot is in a good elevated position, it shows me a green check. If it’s hanging down for more than a few minutes, the phone makes noise, vibrates, and flashes red to remind me.
It’s a fun little hack, but it actually helps me recover better by making sure my foot stays where it should. I ended up calling it “Elevation Police”. It's my personal ankle monitor that nags me for my own good.
discussion - https://x.com/the2ndfloorguy/status/1968306219371655227

value: Show HN: I twisted my foot, so used an old phone's sensors into a recovery alarm

author: madinmo


value: saiyampathak

value: Show HN: AgentKube: AI-Powered Kubernetes IDE

author: saiyampathak


value: eltonlin

value:
Hi, I'm Elton, a 0.1x engineer. I've been working on a calendar for 3 years (which I use myself to ruin my life), and it could ruin yours too. You can play with the demos without logging in: https://actions-life-git-dev-intentions.vercel.app/
Features:
  - infinitely nesting to-dos: so you never get things done
  - habit icons: so your calendar looks like a kid's playground
  - timelines as first-class-citizens: good for visualizing goals you'll never achieve
Looking for honest feedback.

value: Show HN: A recursive calendar for 0.1x engineers

author: eltonlin


value: sharas-

value: I've been working on this like a retard. Who even wants this shit?

value: Show HN: Labli.st Where you find medical labs, tests, prices and deals

author: sharas-


value: Show HN: Conversation Rank – Free tool to measure brand mentions on Reddit


value: egretfx

value: Debugging webhooks and transactional emails can be slow and usually requires multiple tools. I built HookBox to solve this problem, providing instant endpoints, temporary inboxes, real-time capture, and request replay so both can be tested in one place.<p>Would love to hear your feedback!<p>— Egret

value: Show HN: I made HookBox, a webhook and email debugging tool for devs

author: egretfx


value: taurusai

value:
We’ve been working on TaurusAI, a platform that connects job seekers with the right opportunities using AI-driven CV optimization, skills gap analysis, and personalized learning recommendations.
Here’s what we’re building:
Intelligent CV Optimization: Automatically tailors your CV to highlight the most relevant skills and experiences for each role.
Real-Time Job Matching: Matches candidates to open roles instantly, using AI to evaluate compatibility beyond keyword search.
Skills Gap Analysis: Identifies what you’re missing for a target role and recommends practical upskilling paths.
Integrated Learning + Auto-Apply: Suggests micro-courses or certifications, while also auto-applying to roles that are a perfect fit.
The vision is to make job search and upskilling continuous and adaptive—less about blasting resumes everywhere, more about matching intelligently and learning what you need along the way.
We’d love feedback from this community on:
Where do you see the biggest challenges for AI in job matching?
Would integrated upskilling (learning paths tied directly to job requirements) make a difference in your hiring or career growth?
How do you feel about auto-apply features—convenient, or risky?

value: Show HN: AI That Fixes Your CV, Matches Jobs, and Fills Skill Gaps

author: taurusai


value: noctarius

value:
Utilizing Postgres' RLS feature to isolate user data instead of easy-to-forget where-clauses, is such an underrated use case, I really wonder why not more people use it.
If you prefer code over the blog post, I've put the full application example on GitHub. Would love to hear your thoughts.
https://github.com/simplyblock/example-rls-invoicing

value: Show HN: Underrated Postgres: Build Multi-Tenancy with Row-Level Security

author: noctarius


value: Viaya

value: Show HN: MiniMax Music – AI model that generates 4-minute songs

author: Viaya


value: tomaszsobota

value:
Hi HN,
I’ve just released my first Mac App Store app, Buoyant Timer (paid, no in-app purchases)
It’s a lightweight HUD-like timer that floats above everything else on macOS, even full-screen apps.
I always wanted something like a configurable HUD for macOS. An app, or set of apps that stay visible at all times: a timer, runtime notes and scriptable alert/notification display.
This app is the first item on that roadmap. Something simple for deep focus where I switch between full-screen apps a lot, and often lose track of time.
What's under the hood?
This will probably be no news to seasoned Swift developers, but I was surprised by how much can be done with NSPanel.
So, the main view is a non-activating, borderless NSPanel:

    NSPanel(
      level = .floating,
      collectionBehavior = [.canJoinAllSpaces, .fullScreenAuxiliary]
    )
    orderFrontRegardless()

This keeps it always on top. There’s also a pass-through mode (ignoresMouseEvents = true) so clicks go to the app underneath uninterrupted.
Features
- Stopwatch and adjustable countdowns
- Pass-through clicks so it won't interrupt your workflow
- Global hotkeys
- Auto-start stopwatch when countdown ends (proved helpful on occasion)
- Customizable colors, opacity, and high-contrast mode
- Minimal interactive panel when you don’t want pass-through
I’d love to hear feedback, whether on the app, feature requests or anything else :)

value: Show HN: I built a HUD-like timer for macOS that stays visible in full-screen

author: tomaszsobota


value: horushe

value: Show HN: 90s Bollywood Saree Makeover from Any Selfie (No Login Required)

author: horushe


value: sawirricardo

value: Show HN: I created my privacy first URL Shortener for fun. Hope you like it too

author: sawirricardo


value: vrathee

value: Show HN: AI agents to handle customer support tickets

author: vrathee


value: I live in the South of France (Var region), where wildfires destroy our forests and endanger lives every summer. This project is my attempt to build a concrete, open-source tool to help firefighters.

value: Show HN: Diamants, an open-source drone swarm to fight wildfires


value: shmaplex

value:
I’ve been working on xPlant, a dashboard for managing plant tissue culture projects. It’s designed like a “GitHub for plants” — you can track growth, experiment with different media, and iterate on your cultures over time, similar to versioning code.
The goal is to give hobbyists, researchers, and growers a tool to see what works, optimize conditions, and learn from past experiments.
I’d love feedback from anyone who experiments with plants or cares about reproducible growth data.

value: Show HN: XPlant – Track, optimize and iterate your plants like code

author: shmaplex


value: wcagscans

value:
We built ContentRepurpose.pro after getting tired of rewriting the same idea for LinkedIn, X, email, and IG. It’s a simple web app: paste a paragraph → get platform-specific drafts you can tweak, then export to Notion (page) or Trello (card). BYOK works via OpenRouter if you prefer your own key.
Stack/notes:
• Frontend: vanilla + Tailwind; auth via Supabase.
• Backend: Cloudflare Worker (one file) handling CORS, auth identity, quotas, Stripe (Checkout/Portal/Webhook), OpenRouter calls, and OAuth for Notion/Trello.
• Quotas: demo (IP) 5/mo; signed-in free 5/day; paid tiers raise caps. BYOK limits separate from platform pool.
• Models: rotating pool by default; BYOK uses whatever model you choose on OpenRouter. We don’t store user keys (BYOK is per-request header).
• Exports: Notion page with simple headings/paragraphs; Trello card title/description. (Labels/checklists and Notion DB template are likely next.)
Things we’d love feedback on:
• Are the LinkedIn/X outputs “ready to post” length-wise?
• Presets UX (saving/renaming/recall) — any friction?
• Export ergonomics for Notion/Trello — what would make it cleaner?
Live demo works without login (limited). Pricing is on the site; cancel anytime. Happy to answer technical questions and share more implementation details in the comments.

value: Show HN: ContentRepurpose.pro – Paste once to get LinkedIn/X/Email/IG drafts

author: wcagscans


value: Show HN: Remote Shell – extreme-vibe coding from your phone


value: gsahu

value:
Hey community,
I am building Cyphora, a decentralized cloud storage platform designed for everyday users who want to keep their data private and secure without relying on big tech or dealing with blockchain complexity. It’s all on your phone, fully decentralized, and easy to use.
Currently you can checkout:
Landing Page & Demo:https://cyphora.tech/
Short demo video:https://youtu.be/aFNcIW_jYUM
Why Cyphora?
-No single point of failure
-No data leaks
-No dependence on big companies.
My vision is to empowers users with a choice: decentralized, private storage instead of being locked into Big Tech.
We’d love your feedback, especially on:
Should we open-source parts of the platform for node hosting?
What would make you trust a decentralized cloud solution like this?
Thanks for checking it out and am excited to hear what you think.

value: Show HN: Decentralized cloud on your phone – private, simple, no blockchain

author: gsahu


value: csmets

value:
When releasing my games on Steam I needed to find Streamers that would play my game as a form of marketing before release. I used a platform called Woovit which is now shut down. I liked the platform as I got to connect with Streamers and they played my game. What I found difficult was finding the right one and would have to dig through so many profiles.
For my next release I wanted to find an alternative way to be able to connect with Streamers. I wanted to contact them directly, but it's hard and labor intensive to do all the research and manually finding emails. There must be a better way. There's a few providers that have email lists, but it's not cheap.
I know that I'm not alone, so I've done the hard work and collected a bunch of emails and put a price that's super affordable compared to others in the market. I can now easily find the right group of streamers that would play my game and can easily contact them with very little effort and digging around. More time to do game dev and less time spent on finding emails for marketing.
My goal is to make marketing less painful for indie developers to give their game the best possible chance.

value: Show HN: I made it easy to find and contact Streamers who would play your game

author: csmets


value: berndtzl

value:
Hound is a code security auditing tool that draws inspiration from human cognitive processes to enhance reasoning about large, complex systems. By modeling the target application as relation-first knowledge graphs (e.g., monetary/value flows, authentication/authorization roles, call graphs, and invariants with compact annotations), the agent enables multi-granular attention: it can "zoom in" on specific graph slices for detailed analysis while maintaining a summarized view of the entire system through broad mappings.
Complementing this is a persistent belief system that tracks hypotheses with explicit evidence and confidence levels, refining them over time as new evidence emerges—ensuring a disciplined lifecycle for findings that mirrors iterative human reasoning and belief updating.
Evaluated on a subset of the ScaBench benchmark, Hound shows improvements in vulnerability detection (31.2% true positives versus 8.3% for a baseline LLM analyzer) and F1 score (14.2% versus 9.8%).
While tailored for security audits, Hound's analyst-defined graphs and cognitive-inspired framework provide a solid basis for general complex-system reasoning. Released on September 15, 2025, the full paper is available on [Zenodo](https://zenodo.org/records/17129271), with the implementation hosted on [GitHub](https://github.com/scabench-org/hound) for further exploration and reproduction.

value: Show HN: Hound – Relation-First Knowledge Graphs for Complex-System Reasoning

author: berndtzl


value:
Hi HN, I'm Shu, a software engineer and entrepreneur from Tokyo. With new image generation/editing models like Seedream 4.0, Nano Banana, and Qwen-Image releasing rapidly, I found it frustrating to evaluate them. Scattered APIs, inconsistent benchmarks, and pricey subscriptions (or complex setups) made side-by-side comparisons tough. I wanted a simple way to test Seedream 4.0 against Nano Banana without breaking the bank, so I built Model Arena over a few days.
Model Arena is a unified playground to experiment with SOTA image models. Upload an image and a prompt, and it runs Seedream 4.0, Nano Banana, and Qwen-Image in parallel, displaying outputs side-by-side for easy comparison. It’s built with Next.js, leveraging Firebase & Stripe for fast, private processing. No hefty subscriptions—just a credit base pricing to start exploring.
Unlike some existing tools that are expensive or limited to single-model testing, Model Arena focuses on accessibility and direct comparisons with clear metrics (e.g., generation speed, edit fidelity). It’s early days, but I’d love your feedback: What models do you want to see next? How do the outputs compare for your use cases? Try it out and let me know what you think!

value: Show HN: Model Arena, a Playground to Compare Seedream 4, Qwen, and Nano Banana


value: mnvrth

value: Show HN: Claude Built a Techno Track in JavaScript (No Libraries, Just Vibes)

author: mnvrth


value: jpventoso

value: Showing a new free open-source ecommerce system that's quick to set up and easy to understand, built in .NET and Postgres. It can be easily adapted, customized and extended to fit any purposes.

value: Show HN: Open-source .NET 9 e-commerce platform

author: jpventoso


value: AmuXhantini

value:
I am building a new social media platform that is focused on building authentic connections online again as current platforms are failing at this. We do the by making our platform pay to use.
Join our waitlist to be a part of a new beginning. Leave the algorithm.

value: Show HN: Bringing back the social part of social media

author: AmuXhantini


value: treavorpasan

value: Wanted to show the kids how TV used to look like....

value: Show HN: Bring Retro CRT TV Effects to the Browser with WASM

author: treavorpasan


value: chainyo

value:
I kept failing at Pomodoro after week two. Solo sessions are easy to skip.
So I built Pomodobros, a browser-based paired Pomodoro timer.
You can:
- Join a public room or invite a buddy, timers stay in sync (25/5)
- Accountability without chat (silent presence, leave anytime)
- Streaks rank consistency, not hours (to avoid grindy incentives)
From landing to session in <60s
Login is optional (only needed for stats and community features)
Why this might be interesting to you: if timers work for you but you still drift, a second person’s timer on screen is a small commitment that nudges you to finish the block.
What I’d love feedback on:
- onboarding friction / “where do I click first?”
- whether pairing actually helps you finish more sessions than solo.

value: Show HN: Accountability layer for Pomodoro – join a focus session in under 60s

author: chainyo


value: tzahifadida

value:
Hi HN,
When Broadcom announced they're killing free Bitnami containers (Sept 29, 2025) and charging $50K+ for replacements, I got frustrated and built this.
It's a bash script that builds Bitnami containers from the original Apache 2.0 source. Interactive menu, multi-platform builds, works with any registry. I've been using it since the announcement dropped.
The source code didn't disappear - Broadcom just changed their business model. This lets you keep using what you need without the vendor dependency.
GitHub: https://github.com/tzahifadida/oys-bitnami-builder
Curious what others think about the approach. Are you dealing with the Bitnami transition too?
More details: https://shipacademy.dev/articles-html/oys-bitnami-builder-br...

value: Show HN: OYS Bitnami Builder – Build your own Bitnami containers

author: tzahifadida


value: Show HN: Make smarter decisions about the open source projects you depend on


value: syshackbot

value: Show HN: Built an idle text RPG for Android

author: syshackbot


value: botirk

value: Show HN: I wrote an OS in 1000 lines of Zig

author: botirk


value: Show HN: A deliberate practice system for mastering reading and writing


value: gravez

value:
Hey HN  I’m Dima.
I built Kortyx after a failed attempt to find product-market fit with an AI product-analytics startup.
When it was time to pivot i was looking for other ideas and figured that i constantly struggled with getting users to provide "ideal" context to my agents. it resulted in weak prompts, degraded agent performance, etc etc.
So i thought what is instead of asking every user to provide background, Kortyx captured the context directly and then served it at the right time.
Kortyx is a desktop app (Windows + macOS) that quietly sees what you see and builds a private memory layer from your digital life.
You can:
Ask Memory – recall anything you’ve read, watched, or discussed with an exact snippet and timestamp.
Memory Boost – superpower your prompts to other AI agents with detailed context about you.
I’m launching today and would love feedback, especially from Mac users and anyone exploring agent ecosystems.

value: Show HN: Kortyx – Personal memory layer for every AI agent

author: gravez


value: yuedongze

value: Everything I drive by one of these new tech billboards, I always wanted to either fully read it but cannot focus, or want to take a photo of it and share but I cannot because I'm driving. So I want to curate them in a place to enjoy them later, and share with friends about how crazy SF is.

value: Show HN: Silly SF Tech Billboards

author: yuedongze

title: Show HN: Silly SF Tech Billboards


value:
My buddy and I whipped this up.
We really wanted to preview how different models handle tool calls and couldn't find a fast way to do it.
Writting all the tool definitions was frustrating. Having to integrate with something to make the tool call return something was tome consuming.
So we made this Mock based LLM playground to make it really quick to test things out.
If you like this and find it useful, filling in the typeform on the bottom right would be great.

value: Show HN: Mocky AI, Preview LLM use cases in minutes without an MVP


value: dmarcotte

value:
Hi friends, I'm really excited to introduce KSON, which just entered public beta!
Anywhere a human is reading or editing YAML/JSON/TOML, KSON may be used as a more effective interface on that data. If you are such a human, we invite you to participate in this beta.
tl;dr Check out the website [1], play with the online playground [2], install the library for your programming language [3], edit in your favorite editor [4], discuss and give feedback [5], contribute to the project [6].
(A personal note about this project: I love software. Machines made of words! Such a wonder. KSON itself, as a collection of words that both make a machine and explain that machine, is an expression of a lot ideas I feel really passionately about around software and our relationship to it. I've put a lot of love into trying to make that expression eloquent and reliable. I hope some of that comes through clearly, and I look forward to discussing this more over time with anyone who's interested)
One of the key things KSON wants to say is: let's keep everything that's great about YAML and JSON as "Configuration User Interfaces", and let's make those interfaces more toolable, robust, and fun.  Here's some of the ways we do that:
- KSON is a verified superset of JSON, has native JSON Schema support, transpiles cleanly to YAML (with comments preserved!), and is likely available wherever you want it—current supported platforms: JS/TS, Python, Rust, JVM, and Kotlin Multiplatform.
- KSON is also widely available in developer tools, with support for VS Code, Jetbrains IDEs, and anywhere you can plug in an LSP.
- KSON is fully open source, licensed under Apache-2.0, and you are invited to meet its words and tinker with how they make its machine. A lot of care, craft, attention and joy went into making the KSON project understandable and approachable for developers.  We hope to see you around.
PS. This is an HN-friendly version of the official announcement at <https://kson.org/docs/blog/2025/09/17/introducing-kson/>.
[1]: https://kson.org/
[2]: https://kson.org/playground/
[3]: https://kson.org/docs/install/#languages
[4]: https://kson.org/docs/install/#editor-support
[5]: https://kson-org.zulipchat.com/
[6]: https://github.com/kson-org/kson

value: Show HN: KSON, a love-letter to the humans maintaining computer configuration

author: dmarcotte


value:
HuMo AI, a browser-based video studio that turns text, images, and audio into human-centric videos with strong subject consistency and lip-sync.
What it does
 • Text→Video with controllable motion and scene composition.
 • Image→Video to animate a still with natural movements and camera motion.
 • Audio-visual sync for speech-driven lip movement and rhythm-matched motion.
 • Multi-modal fusion: combine text + reference images + audio in one run.
 • Export-ready output: high-resolution (up to 4K), common aspect ratios.
Why
Creative teams often juggle multiple tools: one for T2V, another for in-between motion, a third for lip-sync. I wanted a single studio that keeps identity consistent and aligns visuals with audio—useful for product explainers, character spots, and quick social posts.
What’s different
 • Built around multi-modal conditioning rather than single-input T2V.
 • Emphasis on identity/subject preservation across the whole clip.
 • Frame-level audio alignment for more natural lips and motion.
 • Workflow extras like shot lists / playbooks to speed up iteration.

value: Show HN: HuMo AI – Multi-modal human-centric video generator (text+image+audio)


value: scyclow

value: I made an art project about stablecoins. Enjoy!

value: Show HN: Burnt US Dollars

author: scyclow

title: Show HN: Burnt US Dollars


value:
Post:
Hey HN! I built GPTShirt to make it ridiculously easy to create and buy good looking custom t-shirts, no design skills required. It's at https://gptshirt.app.
How it works:
1) Describe your idea in a prompt, with optional reference images (people, objects, styles, etc.)
2) AI generates your design. Iterate and refine until happy. Powered by Nano Banana.
3) Order it - we handle printing and shipping
4) (Optional) Share it - handy for group orders.
Some example shirts:
- Family picnic with Totoro - https://gptshirt.app/designs/2910ae97-8c7a-4631-9271-291364f...
- Cosmic Cat Island - https://gptshirt.app/designs/0d65835c-ea70-4a56-9f5e-92a0ec4...
- Tropical Escher - https://gptshirt.app/designs/72cda84a-0862-4499-abf9-39ad3f9...
It costs $20 per t-shirt, plus shipping. Shipping takes 3 to 5 business days.
Would love to hear feedback - thanks for taking a look!

value: Show HN: GPTShirt – Describe shirt. Wear shirt.


value: jcasman

value:
What is FastOpp?
FastOpp is an open source starter package based on FastAPI built for creating AI web applications more easily. It offers ready-built components —- admin panels, templating, authentication, database migrations -— packaged in an opinion-driven structure so you can skip boilerplate and focus on building features.
Key features:
Admin panel like Django, with role-based authentication.
SQL database models and migrations inspired by Django’s model structure.
HTML templates (Jinja2) with modern UI (Tailwind, DaisyUI, AlpineJS, HTMX) so you can build simple but decent UIs without heavy JavaScript.
API endpoints with auto-generated documentation (FastAPI style) so you can later add React, Flutter or other frontends.
Management tools:
• oppman.py for core commands (server start/stop, migrations, backups)
 • oppdemo.py for switching between demo/full mode vs minimal mode, handling sample/demo data
Why Post Here?
We're two guys in California, trying to figure out if there's something useable building AI apps. We like Python and Django but had trouble tacking on async to Django and started investigating FastAPI. We're working with multiple LLMs, we stream output, we save conversations to a database, we add different types of web search. And a lot more. It's super promising.
We're hoping to work with students using the repo as a template to build out standalone projects that extend functionality. We have a built (still working on it) tutorials and a curriculum and documentation to create a learning path. It's intended for student learning. And our learning, too. :-)
Try It Yourself
Lots of details in the README. If you want to try it out yourself, there's step-by-step instructions: https://github.com/Oppkey/fastopp
You can explore the live site here: https://fastopp-site.fly.dev/
Example demo site, extending functionality, like you can do: https://fastopp-site.fly.dev/example
Article:
https://dev.to/jcasman/fastopp-a-student-friendly-starter-fo...

value: Show HN: FastOpp: A Student-Friendly Starter for AI Web Apps

author: jcasman


value: bl-ue

value:
I built Splitrail, an open source Rust TUI that turns Codex CLI, Claude Code, and Gemini CLI session logs into token usage and cost so you can measure real productivity (local first; optional free and OSS cloud and leaderboard integrations). I wanted vendor agnostic, fast, and local analytics across agentic tools.  I also wanted to be able to easily track usage across multiple devices.
Codex CLI v0.32.0 added token fields to its JSONL “rollout” files (cached/input/output). Splitrail v1.1.0 supports the new event-based format today.
Links:
GitHub: https://github.com/Piebald-AI/splitrail
Cloud/Leaderboard (optional): https://splitrail.dev/
Release: https://github.com/Piebald-AI/splitrail/releases/tag/v1.1.0
Happy to answer questions and take feature requests.

value: Show HN: Track Token Usage from Codex CLI with Splitrail (OSS, Rust)

author: bl-ue


value: Show HN: CLI for Managing Mentat Agents

title: Show HN: CLI for Managing Mentat Agents


value: stopachka

value:
Hey HN, manyminiapps is the world first massively multiplayer online mini app builder (MMOMA)
*Here’s what it does:*
You load the page. You write 1 prompt and you get a mini app back in under 2 minutes. There’s no sign up, and you can see what everyone’s creating in real-time!
Each mini app comes with it’s own database and backend, so you can build shareable apps that save data.
*What’s different*
There are a lot of app builders that promise you’ll build production software for others. But we think true production software can take a long time to get right. Even if you don’t need to program there’s a lot of work involved.
What if we turned the promise around? Instead of “you vibe code software companies”, it’s “you build fun software for yourself”.
If you cut the problem right, LLMs as they are today can already deliver personal software. manyminiapps is meant to be an experiment to demonstrate this.
You may wonder: do you really need personal software? We’re not 100% sure, but it’s definitely an interesting question. Using manyminiapps so far has been surprising! We thought our friends would just try to build the common todo app, but instead we found them building wedding planners, chord progression helpers, inspiration lists, and retro games.
*How it works*
Instead of spinning up VMs or separate instances per app, we built a multi-tenant graph database on top of 1 large Postgres instance.
All databases live under 1 table, on an EAV table (entity, attribute, value). This makes it so creating an “app” is as light as creating a new row.
If you have heard of EAV tables before, you may know that most Postgres experts will tell you not to use them. Postgres needs to know statistics in order to make efficient query plans. But when you use EAV tables, Postgres can no longer get good statistics. This is usually a bad idea.
But we thought it was worth solving to get a multi-tenant relational database. To solve this problem we started saving our own statistics in a custom table. We use count-min sketches to keep stats about each app’s columns. When a user writes a query, we figure out the indexes to use and get pg_hint_plan to tell Postgres what to do.
*What we’ve learned so far*
We’ve tried both GPT 5, Claude Opus, and Claude Sonnet for LLM providers.
GPT 5 followed the instructions the best amongst the models. Even if you told it a completely nonsensical prompt (like “absda”, it would follow the system prompt and make an app for you. But GPT 5 was also the “most lazy”. The apps that came out tended to feel too simple, with little UI detail.
Both Claude Opus and Sonnet were less good at following instructions. Even when we told them to return just the code, they wanted to returned markdown blocks. But, after parsing through those blocks, the resulting apps felt much better.
To our surprise, we didn’t notice a difference in quality from Opus and Sonnet. Both models did well, with perhaps Sonnet following instructions more closely.
To get good results we iterated on prompts. We initially tried giving point-by-point instructions, but found that a prompt with a full example tended to do better. Here’s what we landed on:
https://gist.github.com/stopachka/a6b07e1e6daeb85fa7c9555d8f...
Let us know what you think, and hope you have fun : )

value: Show HN: One prompt generates an app with its own database

author: stopachka


value: beckford

value:
Today there is no nix for Windows, and Docker with Windows containers hasn't had real adoption.
dk is both a build system and a scripting language. This Show HN is about dk's new build system which builds packages declared in JSON files. You can write the JSON files by hand or use your favorite language to generate them.
dk has some unusual differences from other build and package managers: Windows, macOS and Linux are supported equally. Minimizing supply chain security risk is a focus. Packages can be based on binary assets. Incremental adoption by language communities is a goal.
There is a reference implementation written in OCaml, a from-scratch walkthrough the writes the JSON build files for the somewhat random package (7zip), some security principles, and a specification document. The reference implementation and the spec are primarily to help port the dk build tool to other languages for incremental adoption.
I'd like to get feedback before I launch a community package registry. There are two feedback areas in particular:
1. I suspect there will be some controversy about asking package authors to use their real names and/or pay a micropayment to validate their identities (ex. $1 a year), even though I think controls like these are required for any semblance of supply chain security.
2. I have heard complaints about nix's lack of static typing. A JSON-based build system suffers from the same issue. One possibility is to add JSON schema. Another is to couple the build system with the OCaml-based scripting system in dk, like how the nix functional language is coupled to nix derivations. But I have been hesitant to do that coupling since it would be harder for language communities to incrementally adopt the build system.

value: Show HN: dk, a Windows-friendly, Nix-like build system

author: beckford


value: Show HN: Playing Doom Using a Phone Call


value: jancek

value:
Hi HN,
TL;DR: Django boilerplate with everything needed to launch SaaS. CLAUDE.md and AGENTS.md files that prompt the AI specifically to follow Test Driven Development approach to get better results, alongside other useful conventions (boring code better than smart code). Boilerplate also includes some nice to have stuff like Posthog with session replays and analytics.
I built this Django boilerplate because I was tired of rebuilding the
same essential features for every new SaaS idea. I was searching for existing solutions, but they were
either outdated or really expensive for Django.
This boilerplate includes all the boring yet essential features needed to launch and also a specific focus on using AI for development. I've been experimenting with how to get the most out of AI coding tools
and found that a Test Driven Development (TDD) approach is the best option because of the continuous feedback the AI gets.
What’s inside:
- Optimized for AI: Includes CLAUDE.md and AGENTS.md files with instructions to make AI assistants follow TDD and other best practices.
- Modern Admin: A custom-styled admin page using the Django Unfold package with custom styling.
- Complete Authentication: Full user auth system with social logins, registration, and password reset pages including templates for authentication pages and mails.
- Stripe integration: Pre-built Stripe integration for handling subscriptions.
- Dockerized Setup: A container-based setup for consistent development and deployment.
- Simple Deployment: All it takes is to fill up the .env file, then you are ready to deploy.
- Automated SSL: Automatically issues and renews SSL certificates.
- Background Tasks: Asynchronous job processing with Celery.
- Email Integration: Multiple email services to choose from, plus Mailpit for local development.
- Monitoring: Error tracking with Sentry and user analytics/session replays with PostHog.
- Frontend Stack: A clean and modern frontend using Alpine.js, HTMX, and Tailwind CSS.
- and more
Future Plans:
I'm planning to add a React integration option, but I'm starting with a Django templates/HTMX/Alpine.js to keep the initial complexity low. Also, most apps don’t even need React in the first place.

value: Show HN: Quarkkit, Django SaaS boilerplate optimized for AI coding

author: jancek


value: stephbeaugoss

value:
TL;DR: Vibemind is an AI-native “mini OS” — a single canvas where you interact through thoughts, spaces, and flows instead of switching apps. Multi-agent orchestration, live knowledge graphs, and OCR-driven UI automation are built-in. We’re opening a small waitlist for early builders and power users: [your-waitlist-link].
What this is
We built Vibemind because context switching is wasting everyone’s life. Instead of tabs and apps, you get a single workspace that spawns tiny agents (Planner, Coder, Researcher, Automator), links knowledge into a live graph, and can operate parts of your desktop through OCR + scripted flows. It’s part note-taking, part agent orchestra, part automation playground.
Why it might matter to you (technical folks)
• Agent-first architecture: each task is an agent with capabilities and failure-memory, so retries get smarter.
• Knowledge graph at runtime: nodes are live (files, API responses, chat snippets) — queries return provenance, not guesses.
• OCR UI automation: pick a UI region, teach an agent, and it repeats actions reliably even on dynamic pages.
• Developer-first: CLI + tiny SDK so you can extend agents, add custom fitness functions, or run components locally.
Current status & numbers (honest)
• Prototype: frontend + working agent orchestration, knowledge-graph POC, OCR automation demo.
• Team: small, product-driven. Open to early contributors.
• Waitlist: limited early seats (beta invites will be staggered). We’re not pretending we have millions of users; we have a focused demo and want feedback from people who break things.
Privacy & safety (short)
You can run agents locally or in our hosted environment. We log actions for reproducibility but plan fine-grained export/delete controls. We’re building with minimal data retention by default.
What we want from HN readers
• Try the demo if you’re curious.
• Sign the waitlist if you want early access and can give feedback.
• Tell us what would make you replace a dozen tabs with one canvas.

value: Show HN: Building an AI-native mini-OS for developers

author: stephbeaugoss


value: nicktay

value:
Hey all, Nick here. I am building Vicoa (Vibe Code Anywhere) https://vibecodeanywhere.com, a tool for you to use Claude Code (and Codex) anywhere.
With Vicoa you can:
- Run a regular Claude Code session from terminal
- Pick up the same session on mobile or tablet
- Get push notifications when Claude Code needs your input
- Keep everything in sync across devices
Demo video here: https://www.youtube.com/watch?v=ZBpNzqqLYmg
I built this because I kept hitting the same pain point with Claude Code: you have to sit and babysit it. Often Claude stops mid-flow waiting for input. If I stepped away — even just for coffee — I’d come back later to find progress stalled and needs my input. So I built the Vicoa.
You can install it with a simple command: `pip install vicoa && vicoa`
Download iOS App here: https://apps.apple.com/app/id6751626168
This is an early version. Looking forward to your feedback and comments.

value: Show HN: Vicoa – Code with Claude and Codex Anywhere (Laptop + Mobile + Tablet)

author: nicktay


value: mingtianzhang

value: Naively uploading long PDFs to Claude will go beyond the context limit. This PageIndex MCP uses Vectorless RAG to allow you to chat with super-long PDFs. Any feedback is welcome.

value: Show HN: PageIndex MCP – Chat with Long PDFs on Claude or Cursor

author: mingtianzhang


value: lilistar

value:
Hi HN, I’ve been working on SandBox, a project that lets you explore possible futures using autonomous AI agents. You can build scenarios (environmental, social, governance, etc.), make decisions, and see how things might unfold under different paths.
Some of the things you can do:
Generate speculative news and events under your scenario settings
Visualize how small decisions ripple over time
Run multiple agent-based simulations in parallel
Built with Python, LangGraph + Azure OpenAI, plus a front-end for visualization. Still in active development; feedback, critiques, ideas & contributions are very welcome.
Live demo: https://sandboxes.live/
Github: https://github.com/abozaralizadeh/SandBox
If you like it, a  helps me know this is worth pushing further. Thanks!

value: Show HN: SandBox – AI agents simulating possible futures

author: lilistar


value: antonreshetov

value:
I originally built app in 2019 as a small side project for generating email signatures. Over time, I didn’t have much bandwidth to maintain it, and the project stayed idle for a few years.
This month I finally found the time to give it a full rewrite. Version 2 is out:
- Rewritten from scratch with Vue 3 + Vite
- Styling with Tailwind + shadcn
- Uses Bun as the runtime tooling (fast installs and builds)
- New UI/UX, including dark mode
- Accessibility improvements (keyboard navigation, ARIA, better defaults)
- Cleaner architecture and contributor-friendly setup
The old version had a lot of technical debt. Starting fresh makes it easier to maintain, extend, and keep alive as an OSS project.
Repo: https://github.com/antonreshetov/mysigmail
Would love feedback, especially from folks interested in Vue, Bun, or email-related tooling.

value: Show HN: Clean, open-source alternative to expensive email signature tools

author: antonreshetov


value:
I got fed up with habit apps that let you "make up" for missed days or give you endless second chances. What's the point of a streak if you can just fudge it
when life gets messy?
So I built NoZeroDay around one brutal rule: miss a single day, and your challenge dies. No exceptions, no mercy streaks, no "oops I forgot" buttons.
Here's how it actually works:
You pick a challenge length (7, 14, 30, or 66 days) and commit to showing up every single day with proof — could be a quick text update, a photo, even a voice note about what you did. The format doesn't matter, but the consistency does.
Miss one day? Game over. Hit every single day? You actually earned that streak.
Why I made it this way:
I was tired of apps that felt like participation trophies. The whole point is that it should be hard to maintain a real streak. When there's no way to cheat the system, you stop trying to cheat yourself.
The psychology is pretty simple when failure is immediate and final, you find a way to show up. Even if it's just 5 minutes before midnight logging "did 10 pushups in my pajamas."
Want to try it?
Jump in and start a challenge right now no signup fees or trial periods. I'm really curious to hear what you think. Does the zero-tolerance thing actually motivate you, or does it just stress you out? And how's the overall experience feel?
Honestly, I built this for people like me who need that extra kick in the pants, but I'm wondering if I'm the only weirdo who finds the harshness motivating.

value: Show HN: NoZeroDay – strictly-enforced daily streak challenges


value: gabyhaffner

value: Show HN: Supercharging RL with Hyper-Efficient Online Opt, +165% in 2h, $10

author: gabyhaffner


value:
This was an interesting porting project for a few reasons (IMO):
- The original game is/was awesome and, from a programming perspective, a wonder -- smooth scrolling arcade game on a 128kb Mac in 1984...
- The port was done with a lot of help from AI (mostly Claude Code, but some Gemini CLI as well). I'm a programmer; it wasn't vibe-coded. But I couldn't have done the port of 68k assembly without it. FWIW, Claude seemed better at actually porting the 68k assembly but Gemini was better at finding bugs. YMMV.
- I love Redux and Redux Toolkit for state management. For the port, I put the entire game state in Redux, including all the physics, movement, etc. Every thing that happens in the game is a little redux action. You can watch the whole game get played in the RTK debugger. For some reason that makes me happy.
I've released all my code as MIT. Would love to make a "modern" version some day, but for now I've just tried to be faithful to the original.
There are a few bugs, noted as issues in the github repo. Feel free to add more.

value: Show HN: Continuum Game (68k Mac) Ported to JavaScript


value: tiemster

value:
For purely selfish needs, I created a self-hosted API for CRUD-ing JSON data in GO. Optimized for simplicity and interoperability. Perfect for small personal projects.
The API is based on your JSON structure. So the example below is for CRUD-ing [key1][key2] in file.json. The value (which can be anything) is then added to the body of the request. Moreover, there are helper functions for appending and incrementing values.

  DELETE/PUT/GET: /api/file/key1/key2/...

value: Show HN: API for CRUD-ing JSON data

author: tiemster

title: Show HN: API for CRUD-ing JSON data


value: martintrif

value: Neon Shower is a playful tool for creating light burst animations that can be used as backgrounds / overlays in videos. Feedback is very welcome!

value: Show HN: Neon Shower, a fun tool for animating light rays

author: martintrif


value:
I’ve been working on a side project that helps compare and analyze AI prompts. You can test prompts side-by-side, collect ratings, and see which one performs best.
This came out of a chatbot project I built at work last year. We discovered how sensitive LLMs are to small prompt changes and with our setup being storing prompts in a `.ts` file checked into the repo, it meant analysing effectiveness of prompts was impossible. Existing tools I tried were either overloaded with data or locked me into their own models.
So over the last few months I’ve spent my very limited free time (new Dad) building something simpler:
- Compare prompts with real user feedback.
- Clean analytics without information overload.
- Bring your own OpenAI key and choose any of their LLM models.
It’s up and running and free to try (signup required, no credit cards though). This is no where near a finished product in terms of the website design, it’s a bit rough and ready since design is not my thing. Feedback on the idea and direction would be really appreciated.
https://testune.xyz

value: Show HN: My lightweight prompt management and analytics tool.