value: pllu

value:
Powerful market and geopolitical forces are driving AI labs in a race towards smarter-than-human intelligence. We're enjoying the benefits of the progress so far, but we're fast approaching a point where AI becomes so capable and widely deployed that it could trigger massive societal disruption or even existential threats. Many of us are deeply concerned but feel powerless to act against the industry momentum.
I built AI Safety Pledge (https://aisafetypledge.org) to channel that concern into measurable collective action. It's a public registry where you pledge donations to AI safety organisations and we track the total. You donate directly; we never handle money.
Why this matters:
Donations will directly support vital AI safety research, however the goal isn't fundraising alone. The real power is in creating visible social proof. A public tally ("£500K pledged by 2,000 people and counting") sends a clear signal to policymakers and AI labs that people are concerned about AI risk and demand more action on safety.
How it works:
- Browse 15+ vetted organisations (research labs, policy groups, educators)
- Donate directly through their own channels
- Record your donation to join the public count
Listed organisations include MIRI, Pause AI, Alignment Research Center, Doom Debates, and others working on reducing or raising awareness of large-scale AI risks.
Working on AI safety and want to be listed? Drop me a line: https://aisafetypledge.org/contact
Tech: Built with Cloudflare Workers + D1, server-side rendered with Hono/JSX.
So, if you're spending $20 or $200 this month on AI subscriptions or API fees, consider matching it with a donation towards AI safety. Your pledge on our website helps send a powerful signal about AI risk to policymakers and AI labs.
Curious to hear what HN thinks about the approach.

value: Show HN: I built a way to turn concern about AI risk into collective action

author: pllu


value: Show HN: Contract Extraction Assistant – Fast Batch Extraction


value: alva

value: Show HN: PDF Products Pro – Sell PDFs Securely on Shopify

author: alva


value: rodisproducing

value:
Hi HN,
Great to see you! I published this product today! Hope to help you to generate multiple videos(sora2) at once without any watermarks.
One more thing!
After all videos generated, you can order them in a timeline and merge them into a long video.
(You can re-genrate one or some of the videos if you're not satisfied with it/them.)

value: Show HN: Hoocta – Sora videos generator and timeline editor (without watermarks)

author: rodisproducing


value: pekingzcc

value:
github repo: https://github.com/zhangchenchen/tier_list_maker
I create this tool using next js + shadcn + tailwind. I know it is simple, still learn a lot during vibe coding.

value: Show HN: A 100% free and open source online tool to make tier list

author: pekingzcc


value: StellaMary

value: Show HN: Here we go again μWs-JS against its new rival Brahma-JS

author: StellaMary


value: cylinderthought

value: I've built a unique identicon system where any text input becomes your permanent digital domain - same input always generates the same beautiful pixel avatar.

value: Show HN: Identiqwe – Collect Deterministic pixel art avatars from any text

author: cylinderthought


value: Context Saver is a privacy-first Chrome extension/app that organizes your AI chat workflows effortlessly. Perfect for devs and founders wrestling with long, complex AI sessions. Try the MVP live and let us know what you think!

value: Show HN: Context Saver – Privacy-First AI Chat Organizer (Multi-LLM)


value: ccssmnn

value:
I've built a relationship journal to be a better friend.
Problem:
My friend mentioned they are finishing up their PhD and I forgot to ask how it went. I only remembered when I saw them a few months later. This kept happening.
Solution:
A relationship journal that is so simple, that I actually use it. And an AI assistant that makes it even easier to use.
Tech:
I built it as a single Astro project that contains PWA, API routes and marketing / blog sites.
- App: Tanstack Router, React, Shadcn UI (/app)
- API Routes: Hono (/api)
- DB: Jazz for local reads and writes and real time sync
- Auth & Billing: Clerk
- AI: Google Gemini 2.5 Flash with the AI SDK
Source:
It's open source under the AGPL 3.0 license.
Things I'm proud of:
It's a PWA that feels really good on mobile once added to your home screen. Reads and writes are instant thanks to local data via Jazz. It works offline.
The AI assistant is actually helpful, fast and cheap. I can say "Met steve today. He's finishing up his PhD thesis. The deadline is in 5 weeks" and the AI will find Steve, add a note and suggest and create reminders to follow-up.
You can export and import all data as a single JSON file. This makes it easy to move your data from prod to dev, or from my hosted version to your own instance (and back :)).
Speaking of: You can host it yourself using free tiers. I've written a self hosting guide in the blog.
What you can do:
You can try it without sign-up, data persisted locally. Sign up to sync your data across devices. Start a trial to see the AI agent in action.
Ask me whatever you like. I'm happy to answer any questions.

value: Show HN: Tilly – An Open Source Relationship Journal I Actually Use

author: ccssmnn


value: Crroak

value:
Kept seeing desk setup photos with 50 comments asking "what keyboard is that?"
Built Particulate - upload a photo, click to tag components, get a shareable link. No login required.
Tech: Next.js + Django + Cloud Run + MongoDB. Tags use percentage positioning so they stay accurate on any screen size.
Would love feedback on whether this actually solves the problem.

value: Show HN: Instagram-style tagging for PC setup photos

author: Crroak


value: thisisagooddayg

value:
Hi HN,
I’ve been looking into technical analysis for swing trading and ended up building a simple momentum-based system around three classic indicators: EMA, ADX, and Squeeze Momentum.
I first wrote a small Python script to check one ticker at a time. It worked but didn’t scale — thousands of symbols. So I turned it into a web app that scans whole collections and highlights symbols that might be worth watching. It’s not “buy/sell” — more like: “hey, this looks interesting”.
What it does
• Scans ~200 high-volume US stocks (S&P 500 / Nasdaq / Dow 30) or 25 ETFs (more coming)
• Computes EMA 10/55/200, ADX, Squeeze Momentum
• Shows price/close and a simple signal (Bullish / Bearish / Watchlist)
• Also includes a crypto collection (not working right now but i will get it ready soon)
Tech stack
FastAPI + SQLAlchemy + PostgreSQL + APScheduler
Next.js 14 + Tailwind + shadcn/ui
Polygon + Finnhub (equities) + Binance/Coinbase (crypto)
Hosted on Railway (API) + Vercel (frontend)
There’s a free tier to try it. I’d love feedback: features you’d interested in, that gives value to the product, performance tips, data ideas.

value: Show HN: ChartPilot – Momentum scanner for stocks, ETFs

author: thisisagooddayg


value: OfflineSergio

value:
We built a tool that lets you turn any public webpage into audio with synchronized text highlighting — directly in your browser.
No servers, no limits, no subscriptions. It’s free and works entirely on your device.
How it works:
- Take any URL and add "with.audio/" to the beginning
- Example: "with.audio/https://example.com/article"
- Open it in your browser, wait for the paragraphs to load, then click play
- The text-to-speech happens locally in your browser tab, with highlighting
The first time you try it, your browser will download a voice model (Kokoro ~300MB, Piper is lighter). After that, it works offline and almost instantly (depending on the device).
If you like to read a bit about how it works, take a look at this: https://blog.with.audio/posts/web-reader-tts
Note: we send the your URL to our backend to get the HTML content.
Would love your feedback — what works well for you, and what feels rough?

value: Show HN: On-Device TTS with Synchronized Text Highlighting in the Browser

author: OfflineSergio


value:
Mirrow is a TypeScript DSL that compiles to SVG with compile-time syntax checking and type safety. It reduces boilerplate while catching SVG errors before runtime.
Key features:
Attribute validation at compile time
Inline events (on:click, @hover)
Zero-config CLI: npx mirrow -i input.mirror -o output.svg
Works as static SVGs or components
Playground: https://mirrow.app/playground
GitHub: https://github.com/MirrowApp/mirrow
Built this because hand-writing SVG is error-prone and existing tools don't catch mistakes until runtime. Would love feedback on DX and docs!

value: Show HN: Mirrow – Build SVGs with TypeScript, get syntax checking for free


value:
Hey HN! I'm Jet, building LlamaPReview.
Most AI code reviewers only see the diff. They miss the real risks: a function rename that breaks 5 other files, a dependency change that shifts your architecture, a "small" PR that actually rewrites your auth logic.
We built a context retrieval engine that pulls in related code from across the repo before analysis. On complex PRs, it auto-generates Mermaid diagrams showing cross-file impacts.
Technical challenges:
1. Deciding which files are "related" without analyzing the entire repo every time (we use code graphs + call chains + git history)
2. Fitting it into LLM context limits (we rank by relevance and truncate aggressively)
3. Auto-detecting when to trigger deep analysis vs fast review (~35% of PRs end up needing it)
It's live now, free for all public repos. For private repos, we're trying to figure out a sustainable model: first 3 PRs get deep analysis free, then you choose between our always-free basic tier or a paid tier with persistent code knowledge graphs.
The controversial part: to do deep analysis well, we need to build a knowledge graph of your codebase (classes, methods, call chains). For private repos, this means storing structural metadata. Some teams are fine with this. Others want zero-knowledge architecture where even metadata is encrypted client-side.
Questions for HN:
1. What signals would YOU use to detect "this PR is complex enough to need deep analysis"?
2. Would you pay for code review tooling, and if so, what's your threshold?
3. Is storing structural metadata (no code content) acceptable, or is Zero-knowledge Storage the only way?
Site: https://jetxu-llm.github.io/LlamaPReview-site/
I'm here for the next few hours to answer technical questions or get roasted for my monetization strategy.

value: Show HN: AI code reviewer that analyzes cross-module impacts


value:
Hi HN,
As a weekend project, I hacked together a physical phone, a Raspberry Pi running Asterisk and Twilio, to let toddlers safely make international calls.
I’ve documented the setup in this write-up and published the code + Ansible playbooks on GitHub so others can replicate it.
I built this so kids of expats can easily stay in touch with family on other continents.
Would love feedback from anyone who’s worked on something similar or tries building this themselves!
writeup: https://wip.tf/posts/telefonefix-building-babys-first-intern...
github repos:
- https://github.com/nbr23/ansible-role-telefonefix
- https://github.com/nbr23/allo-wed

value: Show HN: Baby's first international landline


value: arora-raghav

value:
Hey HN,
I built QGen, a tool that extracts structured Q&A datasets from documents using RAG (retrieval-augmented generation). I’d love feedback from anyone working with ML, document processing, or AI pipelines.
Problem
Turning PDFs, Word docs, and other unstructured files into high-quality Q&A pairs for model training is slow and error-prone. QGen automates this process, making it fast and scalable.
How It Works
- Document ingestion – PDF, Word, Excel, PPT, OCR
- Embedding & retrieval – semantic search over chunks
- Q&A generation – LLM generates and filters candidate pairs
- Quality scoring – four-dimensional metrics for relevance, coverage, consistency
- Export / API – JSON, CSV, SQL, XML; on-prem or cloud deployment
Who It’s For
- Startups prototyping AI
- Data scientists training domain-specific models
- Enterprises processing large document sets
Early Feedback & Limitations
- Sometimes questions are too shallow
- Domain adaptation (legal, medical, research) needs tuning
- Runtime can be high for large batches
I’m especially curious about what features you’d want, what trade-offs matter most, and how you’d integrate this into your workflow.
Try It / Feedback
Comment, or email contact@qelab.org to try QGen or share thoughts
Disclaimer: Parts of this post were drafted and formatted with AI assistance.

value: Show HN: QGen – turn documents into AI-ready Q&A datasets(SaaS and on-prem)

author: arora-raghav


value: skrid

value:
Hi HN! I built CodeLens.AI - a community-driven AI benchmark using real developer code tasks.
The problem: Existing benchmarks use synthetic problems. I wanted to know which LLM is best at MY actual code challenges.
How it works:
• Submit code + describe your task ("refactor this", "find security issues", etc.)
• 6 models solve it in parallel: GPT-5, Claude Opus 4.1, Claude Sonnet 4.5, Grok 4, Gemini 2.5 Pro, o3
• AI judge scores each solution (correctness, security, performance, etc.)
• You vote on the real winner
• Public leaderboard shows which models actually win on real-world tasks
Currently have 10 evaluations live (100% vote completion rate). Early patterns emerging:
• GPT-5 leads overall with 40% win rate (4/10 wins)
• Gemini 2.5 Pro dominates security tasks
• GPT-5 strongest at refactoring
• Claude Sonnet 4.5 at optimization tasks
Queue system keeps costs predictable ($10/day = 15 free evaluations for the community).
Free during beta - would love your feedback!
https://codelens.ai

value: Show HN: CodeLens.AI– Community benchmark comparing 6 LLMs on real code tasks

author: skrid


value: echamussy

value:
Hi HN! I’m excited to share something I’ve been working on: MovePlay, an app that turns screen time into action time.
With MovePlay, kids don’t just sit and swipe — they jump, run, and move to play games. Using the device’s camera, the app recognizes and responds to their movements, turning passive screen time into active play.
I originally built it for my daughters. They really like playing games, but I didn’t want them spending all their time sitting on the couch. I wanted to see if I could make something fun that would get them moving instead.
MovePlay is built for iOS and Mac using Apple’s Vision framework. All video processing happens entirely on-device (no images or videos are ever transmitted). It uses real-time body pose detection along with a small custom ML model I trained for hand gestures (to start and stop games).
I’d love to hear your feedback — especially from parents or anyone interested in and active play.

value: Show HN: MovePlay – An app that gets kids moving

author: echamussy


value: avlaho

value:
We've been making enhancements to our MCP Server.
Now, you can build a backend completely out of VS Code, in agent mode (or tools like Cursor, Windsurf, Cline, Claude) connected to Snapser's MCP server. I've linked a video showing a demo of this. We're working on being able to have the agent actually integrate the backend SDK endpoints into an app's client code.  We'll demo that in a future part 2 video.
If you're interested in trying this out, you can sign up for a free account at snapser.com. Instructions to get this setup are on our documentation page.

value: Show HN: Build a back end in VS Code using Snapser MCP Server [video]

author: avlaho


value: Show HN: Spacelift Intent MCP – Cloud Infra Provisioning for Your AI Agent


value: filearts

value:
I built a ChatGPT App using the new Apps SDK and wrote down all the steps so that you can follow along and do it yourself. It's definitely a game-changer to have rich UI experiences and the power of MCP right in the king of AI Chat apps.
This tutorial should tell you everything you need to get started. HMU or send PRs if you have ideas to improve the walkthrough.
Some observations in putting this together:
* ChatGPT seems to cache tool definitions and resources *
Every time I changed my code, I had to:

  1. Update the resource URI to cache-bust it.

  2. Manually refresh my tools list in the Connectors UI.

The system's backend currently is a bit slow so the cycle time suffers.
* There is a docs gap in handling tool vs. UI lifecycle *
Because there is a consent screen to submit tool inputs and call the tool, the HTML is rendered long before the tool output is available.
This doesn't seem to be reflected in the docs yet, so heads-up.
I found that you can listen on the window-level `openai:set_globals` event and defer handling of tool output until that time.

value: Show HN: Step-by-step instructions to build your first ChatGPT Apps SDK app

author: filearts


value: bartx

value:
Hey HN - I wanted to share something I’ve been building and using in my day-to-day life, in case it resonates with others here.
A few problems I’ve always had:
- it’s hard to follow more niche updates (e.g. specific tech standards like MCP) because the activity happens across different platforms — releases and discussions on GitHub, community feedback on Reddit/HN, tips on Twitter, etc.
- I struggle to keep up with activity across platforms. Sometimes I only check Reddit and miss interesting stuff on HN or GitHub. It’s just hard to visit every forum or app daily.
- often I don’t want to dive deep into every topic — I just want a quick, ELI5-style summary.
- social platforms like Twitter can have useful content, but their algorithms are tuned for engagement and doomscrolling, which can waste a lot of your time.
Defeed is my attempt to solve this - a single feed/app that gives you all the updates you need.
Things that already work:
- aggregates activity from multiple 3rd-party sources (not just RSS)
- content-based recommendations using embedding similarity search
- short and long AI-generated summaries for each item (still improving)
- added some public example feeds (LMK if you want access to create custom feeds, or register for early access on the website)
I’d love your feedback on:
- What kinds of feeds would you find most valuable? (I can share example public feeds based on that.)
- Would you find it useful to include more personal or sensitive data (like emails) if the architecture allowed you to self-host those feeds privately (on your own infra)?
GitHub: https://github.com/defeedco/defeed
Demo feeds: https://defeed.co

value: Show HN: I'm building an open-source online activity aggregator

author: bartx


value: pacifika

value:
Todout is a local-first hierarchical todo outliner with powerful filtering, tagging, and keyboard-driven organization. I built it after using many outliners and task managements apps and needing a hybrid of both for tracking engineering tasks.
It works well on mobile, and hoping to get some feedback from folks that have relevant experience.
This is an MVP, but thinking of an upsell, I'm considering adding an low cost account system?
Key Features:
Hierarchical tasks with unlimited nesting and collapsible structure.
Inline #tags, priority (!) levels, and due dates (YYYY-MM-DD or YYYY/MM/DD) auto-detected.
Powerful filtering by tag, priority, and date range; full-text search; focus mode.
Keyboard-first: Alt+N new task, Tab/Shift+Tab indent, Ctrl/Cmd+Z undo, etc.
Status tracking (active/completed/archived), bulk operations, full undo/redo.
Local-first: all data stored in browser, no server, instant performance, full privacy.
Fast, local, and distraction-free—like a modern outliner built for productivity rather than project management overhead.
I'm looking forward to your responses.

value: Show HN: Todout – a local-first todo outliner

author: pacifika


value: AshBuk

value:
I couldn’t find a privacy-friendly and reliable voice typing app for my daily Linux use, so I built one.
This project uses Whisper.cpp for offline speech recognition and is written in Go. It works both on X11 and Wayland and aims to be a drop-in solution for dictation and voice commands on Linux desktops.
The goal is to provide a fast, local, and privacy-respecting alternative to Dragon or cloud-based STT tools.
Repo: https://github.com/AshBuk/speak-to-ai
Issues: https://github.com/AshBuk/speak-to-ai/issues
I’d appreciate feedback, testing on different distros/desktops, and any contributions or ideas for improvement.

value: Show HN: Speak to AI – offline speech-to-text for Linux (alternative to Dragon)

author: AshBuk


value:
This is an experiment i did in the past 3 weeks where i used AI (GPT 4.1 and Claude 4) to recreate my Declarative framework in c# which uses Html + Json in 6 languages.
I was suprised that AI can not only implement the logic in multiple languages, it can go from static typeed languages like c#, rust and go to dynamic languages like php and javascript in node.js to javascript at the client.
Another think i was suprised is that AI can even create the Index page by itself using the 4 declarative rules for which AI implemented the logic.
Even though it is not vibe code, since i controlled the structure of the implementation and asked ai to implemented extensive features like testing, structure dumps to validate the implementation, i have not reviewed the implementation and only in c# which i am familiar with i have briefly reviewed and i can see it is not optimal for implementating future declarative abstractions, but it works.
The implementation is complete to build static web apps using any client side framework
My takeaway using AI is implementing interative loops where you ask something, but also show how the AI can verify whether it has satisfied your requirement was the trick which helped it to complete the implementation in c# and using C# as the prompt helped AI to complete the other langs iteratively.
The output is published in smallest machine in fly under 6 different apps, namely https://csharpassembler.fly.dev/, https://rustassembler.fly.dev/, https://goassembler.fly.dev/, https://nodeassembler.fly.dev/, https://jsassembler.fly.dev/

value: Show HN: Polyglot Web Assembler done using AI


value: elfenleid

value:
Hey HN! I'm José, and I built Recall to solve a problem that was driving me crazy.
The Problem:
I use Claude for coding daily, but every conversation starts from scratch. I'd explain my architecture, coding standards, past decisions... then hit the context limit and lose everything. Next session? Start over.
The Solution:
Recall is an MCP (Model Context Protocol) server that gives Claude persistent memory using Redis + semantic search. Think of it as long-term memory that survives context limits and session restarts.
How it works:
- Claude stores important context as "memories" during conversations
- Memories are embedded (OpenAI) and stored in Redis with metadata
- Semantic search retrieves relevant memories automatically
- Works across sessions, projects, even machines (if you use cloud Redis)
Key Features:
- Global memories: Share context across all projects
- Relationships: Link related memories into knowledge graphs
- Versioning: Track how memories evolve over time
- Templates: Reusable patterns for common workflows
- Workspace isolation: Project A memories don't pollute Project B
Tech Stack:
- TypeScript + MCP SDK
- Redis for storage
- OpenAI embeddings (text-embedding-3-small)
- ~189KB bundle, runs locally
Current Stats:
- 27 tools exposed to Claude
- 10 context types (directives, decisions, patterns, etc.)
- Sub-second semantic search on 10k+ memories
- Works with Claude Desktop, Claude Code, any MCP client
Example Use Case:
I'm building an e-commerce platform. I told Claude once: "We use Tailwind, prefer composition API, API rate limit is 1000/min." Now every conversation, Claude remembers and applies these preferences automatically.
What's Next (v1.6.0 in progress):
- CI/CD pipeline with GitHub Actions
- Docker support for easy deployment
- Proper test suite with Vitest
- Better error messages and logging
Try it:
npm install -g @joseairosa/recall
# Add to claude_desktop_config.json
# Start using persistent memory

value: Show HN: Recall: Give Claude memory with Redis-backed persistent context

author: elfenleid


value:
Hi Hacker News,
Throughout my career working on native mobile apps, two problems constantly appeared across every company: managing forced updates/version control and managing maintenance mode without a painful backend update or new app release.
I built AppCockpit.dev to solve this. It's a centralized service that gives you a dashboard to control which version is enabled and which requires an update.
Key features:
* Centralized Version Control
* Instant Maintenance Mode
* Currently focusing on React Native (More SDKs will follow)
I'm already using this in a smaller application and am now looking for feedback from the broader community on the feature set and roadmap.
I have many more features planned, but I'm at a point where I need input from others to prioritize.
Let me know what you think about the approach. What is your team's biggest headache with forced updates?
Go check it out: https://appcockpit.dev/

value: Show HN: Appcockpit – Version and Maintenance Control for Native Apps


value:
Hi! I built SEE (Semantic Entropy Encoding) because the “data tax” (storage/egress) and the “CPU tax” (decompress/parse) keep rising together.
Tradeoff: it’s not always smaller than Zstd, but it stays searchable while compressed and minimizes I/O.
Key numbers (demo): combined≈19.5% of raw, skip≈99%, lookup p50≈0.18 ms (bloom≈0.30).
10-min reproduction (no marketing):
1) Download the Demo ZIP (Release).
2) Follow README_FIRST.md.
3) Run `python samples/quick_demo.py` → prints ratio/skip/bloom + p50/p95/p99.
ROI quick math: Savings/TB ≈ (1 − 0.195) × Price_per_GB × 1000  (e.g., $0.05/GB → ~$40/TB).
NDA/VDR (private, no confidential info in public): [https://docs.google.com/forms/d/e/1FAIpQLScV2Ti592K3Za2r_WLU...]
Happy to answer technical questions (schema-aware layout, delta strategy, bloom density, skip heuristics, failure modes).

value: Show HN: Searchable compression for JSON (p50≈0.18 ms; 10-min demo)


value: aeonfox

value:
Hi HN!
I made this as a passion project because I thought it would be fun to interact with Hacker News in a completely different way.
Each cell is a submission, and each little 'organelle' in each cell is an interactive comment thread.  Every shape represents an Elixir process that is sipping on a live Firebase stream.  The live data is piped to the user, but it is also stored and snapshotted on the server so the user can travel back in time and replay any moment.  You can click on a comment and story and scrub the timeline to watch it change over time.  It's fully keyboard navigable and I've made some effort to make it work with screen readers.  You can also share the state of Hacker News at any moment, and for any story, or comment, by simply copying the browser url.  Or just make it fullscreen and use it as a screen saver :)
Have a play.  Please let me know what you think, or if there's any annoyances, etc.  I enjoy using it myself, and judging by my server monitoring I might have got some of my friends hooked on it. Hopefully you'll like it too!

value: Show HN: Hacker News as a biological simulation (with time travel)

author: aeonfox


value: ToJans

value:
I wanted to get a better understanding of this paper, so I asked Claude to train and generate a small sudoku solver with some extra explaining.
Original paper:
https://arxiv.org/abs/2510.04871
New Link including link to source in github:
https://claude.ai/public/artifacts/1dde5d3c-4ad8-420f-9b62-4...

value: Show HN: Recursive Reasoning with Tiny Networks in the Browser

author: ToJans


value: tndibona

value: Show HN: TrendyZip – See how much US homes sell over asking price

author: tndibona


value: alessandro-a

value:
Hey everyone!
I've been building AI agents lately and kept running into the same problem: how do you test AI Agents?
I find that manually prompting the Agent for each release is tedious and not scalable. Also, existing solutions for testing agents are often complex to integrate.
To help with this I built a simple open-source testing framework that uses AI to validate AI: you define expected behavior and let an LLM judge if the output is semantically correct.
The LLMJudge returns a score (0-1) and reasoning for why it passed/failed.
You can try it live here (no signups): https://semantictest.dev
The playground runs real LLMJudge validation so you can see how the semantic testing works.
The code is completely open source and you can find extensive documentation here: https://docs.semantictest.dev
Would love feedback from you guys!
Thank you!

value: Show HN: SemanticTest – Test AI agents with semantic validation (open source)

author: alessandro-a


value: carushow

value: Hey HN - my friend and I built Prediction Hunt, a site that aggregates data from prediction markets like Kalshi, Polymarket, and PredictIt into one simple dashboard.<p>It updates every few minutes, shows probabilities for each event, and even highlights arbitrage opportunities when markets disagree. I made it after getting tired of flipping between tabs just to see how each market was pricing the same question. Would love feedback on the product, data accuracy, and any ideas for what you'd want to see next.

value: Show HN: PredictionHunt – Compare probabilities across prediction markets

author: carushow


value:
TypeMyVibe analyzes your Reddit or X profile (just by username), or you can upload a WhatsApp/Instagram chat to get a personality report with MBTI, Enneagram, Big 5, and more.
I built this because I’ve always been fascinated by personality theories, but also frustrated with how easily they’re biased. Most tests depend on self-perception, which changes with mood. I wanted to see if analyzing real language could reveal a person’s true type.
What made me to actually build it was when my sister got the same MBTI as me (INTP). I knew she wasn’t, so I built a system that could prove it using our chats. I got INTP and She got ISTP.
For privacy, nothing is stored — I only keep a temporary dictionary in memory that’s cleared after analysis. It runs on GPT-OSS-120B, so no big AI companies ever see user data.
I’m curious: are most people here INTPs, INTJs, or ENTJs? And how common are Enneagram 3s and 5s among founders? Would love if a few of you tried it out and shared what type you got — I’m hoping to get some insight into the HN crowd.
https://typemyvibe.ai

value: Show HN: TypeMyVibe – Find your Personality type from Reddit, X, or chat data


value: onounoko

value: Show HN: I built a website to find out what's trending on different platforms

author: onounoko


value: hackerpi

value:
Hey HN,
We're launching Loopdesk Beta v2 today after 6 months of working with 300+ creators. It's an AI-powered video editor that uses chat-based prompting and genre-specific workflows.
The Problem We're Solving
Video editing is time-consuming, especially for content creators who need to produce videos regularly. The traditional timeline-based editing workflow requires manual sorting, organizing clips, adding captions, generating highlights, and applying effects. For podcasters and educational content creators, explaining jargon or adding visual annotations adds another layer of complexity. We wanted to automate the repetitive parts while keeping creative control.
How We Got Here
We started this project because we were creating tutorial content ourselves and spending 4-5 hours editing a single 20-minute video. The bottleneck wasn't the creative decisions—it was the mechanical tasks: organizing footage, transcribing, captioning, finding key moments. We tried existing AI editors but found they either lacked control or couldn't understand context-specific needs (like podcast vs. tutorial editing patterns).
What We Built
Loopdesk uses an agentic chat interface for video operations. Instead of dragging elements on a timeline, you can prompt the AI to perform edits. The system analyzes your video content and suggests genre-specific workflows—it recognizes whether you're editing a podcast, tutorial, vlog, or product demo and adapts accordingly.
Technical Details:
CoEditor Agent: Chat-based interface with quick action buttons. Maintains chat history so you can switch between editing sessions or revert to earlier versions
Genre Recognition: Analyzes video content (audio patterns, scene composition, cut frequency) to determine content type and suggest appropriate workflows. For example, podcast workflows prioritize jargon explainers and chapter markers, while tutorial workflows focus on screen annotations and step highlighting
GPU Rendering Pipeline: Built custom rendering engine optimized for cloud GPUs. We're using CUDA for parallel processing of effects and exports
AI Automation Layer: Generates captions using Whisper-based transcription, creates summarizations for show notes, identifies key highlight moments using sentiment analysis and engagement pattern detection
Template System: Community-driven templates that can be shared and remixed. Templates define workflow sequences, not just visual styling
What's Different
Most AI video editors are either fully automatic (no control) or just add AI features to traditional timeline editors. We're treating the entire editing process as a conversational workflow. The AI is a collaborator that understands intent rather than a tool that executes commands.
The genre-specific workflow system is novel—we trained models on different content types to recognize patterns. A podcast has different editing needs than a tutorial, and the AI adapts its suggestions accordingly.
Current State
Beta v2 is live today. You can:
Upload videos (drag and drop)
Use chat prompts for editing operations
Generate captions, transcripts, and show notes
Get AI-suggested highlight moments
Add VFX animations that are context-aware
Use and create community templates
Access stock video/audio/image library
Render with GPU acceleration
The product is free during beta. We plan to charge $29/month for unlimited rendering once we exit beta, with a free tier for up to 3 exports per month.
Try It Out
We've removed signup barriers for HN—just visit loopdesk.ai and you can start editing immediately. We'd love feedback on the chat interface and workflow suggestions. Are the AI recommendations helpful or intrusive? What genres are we missing?
Demo video: https://www.youtube.com/watch?v=_03SpwgI8Ek
Would love to hear your thoughts on the approach, technical architecture, or UX decisions. What would make this more useful for your workflow?

value: Show HN: Loopdesk – AI video editor with chat-based workflows and GPU rendering

author: hackerpi


value: Show HN: SVG Generator Agent

title: Show HN: SVG Generator Agent


value: PolymvthicPunks

value:
Author here. My business partner and I have spent much time refining this stack - he optimizes for usability and design, I optimize for privacy and security (guilty tinfoil hat wearer).
The result is 150+ tools and 90+ books spanning privacy, OpSec, crypto, design, economics, philosophy, true crime, and much more. It's polymathic by design - not just another privacy tools list, but a resource covering everything from Bitcoin wallets to cartel memoirs.
It's pragmatic, not dogmatic - Discord is in here alongside Signal and Session because real-world tradeoffs matter. The goal was building a functional daily-driver stack, not theoretical purity.
GitHub repo has the full breakdown across 23 tool categories and 13 book genres. Open to feedback and contributions. Happy to answer questions about specific tool choices or the polymathic approach.

value: Show HN: Polymathic Resource List – 150 Tools and 90 Books

author: PolymvthicPunks


value: taruza

value: Show HN: Dipmatter – Deep Researcher for Finding Early Signals and Startup Ideas

author: taruza


value: neonwatty

value: Giphy never has the YouTube clips I want, so I built a Chrome extension to create GIFs right from the player. Select timestamps, tweak settings, export.  All in-player.

value: Show HN: Chrome extension to GIF YouTube videos in-player

author: neonwatty


value:
GitHub repo here: https://github.com/jram930/cadence
Just a side project to experiment with AI coding assistants that I had fun with and thought I'd share here :)
Enjoy!

value: Show HN: Cadence – Daily note taking app with mood tracking and AI querying


value: glossardi

value:
It's a single, asynchronous JavaScript snippet you add to your site's <head>.
It automatically converts it to clean Markdown, and makes it available for generative engines to consume.
Think of it as creating a compliant, machine-readable layer for your website—without any cloaking or negative impact on SEO or page speed.
The goal is Generative Engine Optimization (GEO): helping you control your narrative in AI and get cited as a trusted source.
The backend is built on Supabase, and it's privacy-focused: it does not track you or your visitors, only anonymous usage counts.
It's in a free beta right now. I'm looking for direct feedback from developers, SEOs, and anyone managing a web property. I'd love to know:
What's your biggest headache with how AI engines use your content?
Is the async JS-snippet approach the right one for your stack?
What features would make this a must-have tool for you?
Cheers, and I appreciate you taking a look.

value: Show HN: I built GEOfast to make your websites readable by AI

author: glossardi


value: josvdwest

value: Show HN: Open-source Unity MCP for game developers

author: josvdwest


value:
Good morning!
As an avid quake 3 defrag player, this project started out for me as a tool for Quake 3 and Q3 mods that would solve some of the issues that the in-game UI has. It is essentially an external launcher for the game built with Tauri v2.
Where this launcher shines is it lets you toggle your Quake 3 client exe and with 1 click the launcher is now targeted to that mod (servers / demos / levels refresh). Note there is a nice GIF of the app in the readme of the repo
The project uses Tauri (webview) which some people scoff at - and I get it. Although I think most of the webview stigma is due to electron apps bloating everyone's PC.  In any case - I tried my damndest on the UI :).
So try it out - this is for all the Q3 old heads!
Benefits over in-game UI below:
Faster server browser,
Ability to favorite servers,
Ability to trash servers (this is useful as many servers advertise using fake players which pollutes the in-game browsing experience - trashing these resolves this),
Ability to add custom servers that are not advertised on the Q3 master servers,
Unlimited number of demos/levels can be displayed (Q3 client exes have hard limits on the amount of demos / levels that can be displayed in the in-game UI),
Ability to play demos on a loop (a feature inspired by the old Demo Show Creator tool https://alt.3dcenter.org/dsc/index_english.php),
Ability to auto-close the client at demo end,
Managing the EXE (basically closing and re-opening the client on subsequent launches),
More data is parsed from demos, levels, and servers and is displayed in a nice fashion,
You can read back the console activity in demos (chat history etc) without having to play the demo. I don't think this has been done before in any other tool

value: Show HN: Sarge Launcher – A Quake 3 Arena Utility


value: jmrobles

value: Show HN: Autocache – Cut Claude API costs 90% (for n8n, Flowise, etc.)

author: jmrobles


value: aegrumet

value:
I worked on early podcast software in 2004 (iPodder/Juice) and have been a heavy podcast consumer ever since. I wanted a podcast app that respects your privacy and embraces the open web—and to explore what's possible in the browser.
The result is wherever.audio, which you can try right now at the link above.
How it works: It's a progressive web app that stores all your subscriptions and data locally in your browser using IndexedDB. Add it to your home screen and it feels native. Works offline with downloaded episodes. No central server storing your data—just some Cloudflare/AWS helpers to smooth out browser limitations.
What makes it different:
- True local-first: Your data stays on your device
- Custom feeds: Add any RSS feed, not just what's in a directory
- On-device search: Search across all feeds and episodes, including your custom ones
- Podcasting 2.0 support: Chapters, transcripts, funding tags, and others
- Auto-generated chapters: For popular shows that don't have them
- AI-powered discovery: Ask questions to find shows and episodes (this feature does send queries to a 3rd party API, and also uses anonymized analytics while we work out the prompts)
- Audio-guided tutorials: Interactive walkthroughs with voice guidance and visual cues
The basics work well too: Standard playback features, queue management, speed controls, etc.
I'm really interested in feedback—this is more passion project than business right now. I've been dogfooding it as my daily podcast app for over a year, and I'm open to exploring making it a business if people find it valuable. Curious if there are unmet needs that a privacy-focused, open web approach could address.

value: Show HN: I built a local-first podcast app

author: aegrumet


value: saiyampathak

value: vcluster is an open source tool for Kubernetes multi tenancy and over the years it has matured to have hosted controlplane virtual cluster, shared virtual clusters but the host cluster problem was always there. With vcluster standalone, you can now create the first cluster also with the same developer experience and consolidate the multiple vendor problem. With this, you can now use vcluster for entire multi tenancy spectrum. Feel free to discuss, happy to answer any questuons.

value: Show HN: Solving the cluster 1 problem with vCluster standalone

author: saiyampathak


value: kevinhacker

value:
Kostenloser KI-Musikgenerator für deutsche Songs. Text rein → professioneller Song in wenigen Minuten.
Gebaut für Content Creator, die Copyright-freie Musik brauchen.
https://kisongerstellen.com/
 GitHub: https://github.com/kisongerstellen
Probiert es aus!

value: Show HN: KI Song Erstellen Kostenlos – AI Music Generator für Deutsche Musik

author: kevinhacker


value: caoxhua

value: Show HN: Magic Vizion – highlight anything, visualize instantly with one click

author: caoxhua


value: dioptre

value:
After months of work, we've created something we think the HN community might find interesting: a spreadsheet interface that connects to 600+ exchanges with 1000+ built-in analysis tools.
The core idea: if you already know spreadsheets, you shouldn't need to learn Python/R or set up complex infrastructure to do serious quantitative analysis.
What's inside:
Portfolio optimization (including Dalio's risk parity approach)
Monte Carlo simulations for backtesting
Sharpe ratio, Black-Scholes, and risk analysis
Real-time data from 10,000+ sources via connectors
Direct execution to platforms like Robinhood
AI assistants that can explain concepts and analyze your positions
The AI layer is particularly useful for learning - it can walk you through why certain strategies work, explain the math behind models, or help debug your analysis.
We're offering a free tier to start, and we'd genuinely love feedback from folks here who've built their own trading systems or struggled with existing tools.
Try it at: https://sourcetable.com/quant
Happy to answer questions about the architecture, data pipelines, or design decisions.

value: Show HN: Run your own Hedge Fund in a Spreadsheet

author: dioptre


value: asdev

value:
Hi HN! I've recently been finding productivity in running parallel CLI coding agents(after not believing in them initially).
After having to do a ton of git stashing and branch fumbling, I decided I needed to something to more ergonomically run these agents in their own dedicated spaces.
I tried a lot of the existing products but they either were too convoluted or flat out didn't work. Some of them also seem to roll their own chat UI which I don't think is the right approach, I wanted to something to lightly wrap my terminal sessions.
So I built FleetCode! It uses git worktrees and let's you run multiple agents at once. It's made my multi agent coding workflow much easier.
It's free and open source, would love some feedback!

value: Show HN: FleetCode – Open-source UI for running multiple coding agents

author: asdev


value:
TLDR
Type one sentence describing the business you want to start. FounderBox returns a full “business kit”: your company name, incorporation guidance, website, Stripe checkout, supplier matches, ads, and a basic SOP to operate.
Why we built this
We all know this pain:
Starting a small business today means gluing together five consultants, seven subscriptions, and hundreds of small tasks, even though 90% of it has already been automated by AI.
You have lawyers charging $1,200 to file basic paperwork, marketing consultants writing the same “About Us” copy with ChatGPT, and agencies billing $3K to embed a Stripe button. The process feels broken optimized in parts, but still fragmented and overpriced.
We wanted to fix that.
We built FounderBox.dev to collapse the entire “consulting chain” into one seamless prompt → company pipeline. Instead of paying for each disconnected step, you get an orchestrated system that does the whole job, end-to-end.
We believe the consulting and services industry law firms, marketing agencies, operations consultants is about to go through its “Napster moment.” AI has automated the heavy lifting, but the industry still charges human-era prices. FounderBox is our attempt to *democratize entrepreneurship* giving anyone, anywhere, the ability to start a business without gatekeepers, invoices, or endless glue work.
Our goal isn’t to replace humans; it’s to *free humans from the admin* and let them build the part that matters the vision.
Early access
We’re currently accepting our *first 500 founders* to test the closed beta.
You’ll get full access to the “one-prompt business builder,” early feedback calls, and lifetime founder pricing when we launch publicly.
Join the waitlist: https://founderbox.dev/
We’d love your feedback especially from folks who’ve built legaltech, no-code, or supplier-API products.
Are we overshooting or undershooting what “one-prompt company formation” should mean?

value: Show HN: FounderBox: Prompt → Form company, website, payment, suppliers and SOP


value: allynjalford

value: Show HN: Seamlessly combine and switch between blockchain RPC providers

author: allynjalford


value: Vincent lets users safely grant apps/agents limited, revocable permission to use their wallets. Think “OAuth for crypto actions”: you define scopes (e.g., “rebalance stables on Aave up to $1k/day”), users approve, and your app runs within on-chain guardrails. Non-custodial. Built with Lit Protocol's decentralized programmable signing.

value: Show HN: Vincent – A delegation framework for wallet automation


value:
Hey HN,
I'm Willem from Confident Security, we've built CONFSEC, a provably private AI inference engine. Today, we're excited to open-source twoway:
https://github.com/confidentsecurity/twoway
twoway is a Go package that makes it easy to implement secure, encrypted request-response flows. It powers CONFSEC's blind prompt handling, ensuring no one, not even us, can see client requests.
We built twoway on Cloudflare's circl/hpke, it uses Hybrid Public key Encryption to implement two flows:
- A one-to-one flow where a sender communicates with a single receiver. This flow is fully compatible with RFC 9458 Oblivious HTTP (OHTTP), and the chunked OHTTP draft RFC.
- A one-to-many flow where a sender communicates with one or more receivers. Similar to the Apple's PCC's request flow.
Other features include:
- Compatibility with any transport, twoway deals with just the messages.
- Chunked messages.
- Allows for custom HPKE implementations for specialized needs like cryptographic hardware modules.
Our README has clear examples to get you started, all you need to do is go get and try an encrypted "Hello world" exchange.
Our team will be popping in to answer questions, we'd love to hear your feedback.
Cheers!
Willem

value: Show HN: Twoway, a Go package for HPKE encrypted request-response flows


value: mceoin

value:
Today we're releasing Quant (https://sourcetable.com/quant), an AI analyst that connects to 600+ exchanges with 1000+ built-in analysis tools. Andrew, CTO, has a background building software at hedge funds so we put his knowledge and experience into this application.
The core idea: if you already know spreadsheets, you shouldn't need to learn Python/R or set up complex infrastructure to do serious quantitative analysis. One way to think of Quant is a low-cost Bloomberg Terminal alternative.
What's inside:
Portfolio optimization (including Dalio's risk parity approach), Monte Carlo simulations for backtesting Sharpe ratio, Black-Scholes, and risk analysis Real-time data from 10,000+ sources via connectors. Direct execution to platforms like Robinhood AI assistants that can explain concepts and analyze your positions
The AI layer is particularly useful for learning - it can walk you through why certain strategies work, explain the math behind models, or help debug your analysis. We're offering a free tier to start, and we'd genuinely love feedback from folks here who've built their own trading systems or struggled with existing tools.
Happy to answer questions about the architecture, data pipelines, or design decisions.

value: Show HN: Quant, the AI stock trading analyst

author: mceoin


value: kuberwastaken

value: Show HN: Spica – OSS Tool to Generate Infinite Length Sora-2 Videos

author: kuberwastaken


value: gbriano

value:
Hi HN,
I’m Giovanna, a designer who built Recall Watch, an app that aggregates real-time recall data from the USDA and FDA.
It covers food, pets, household products, medical devices, and supplements — all displayed in a clean, modern interface.
The motivation: government recall websites are outdated and hard to navigate, and there’s no reliable way to receive recall alerts. Most people only hear about them sporadically — through the news or social media — which makes it easy to miss something important.
Features:
• Real-time USDA + FDA recalls
• Risk levels (High / Moderate / Low / Advisory)
• Clean, card-based interface
• Save recalls for later
This is my first app launch — I’d love feedback or thoughts on how to take it further.

value: Show HN: Recall Watch – Real-time USDA and FDA recall alerts

author: gbriano


value: syx

value:
Source: https://github.com/syxanash/maxheadbox
Hi HN, I've always been fascinated by local inference, especially on small hardware like Raspberry Pi. After researching online, I found that many pre-made solutions seemed to have a piece of the puzzle, like speech-to-text or LLM handling, that was managed by a cloud service. Because of this, I decided to give it a try and build this tiny agent that can run entirely on a Raspberry Pi 5 (16GB/8GB) and it's 100% local. It is capable of executing tools and runs some of the best small models I could find, such as Qwen3:1.7B and Gemma3:1B.
From wake-word detection (using vosk), to transcription (faster-whisper), to the actual LLM inference, everything happens on the Pi 5 itself. It was definitely a challenge given the hardware constraints, but I learned a lot along the way.
I've added a demo and detailed everything in my blog post if you're curious: https://blog.simone.computer/an-agent-desktoy
Cheers!

value: Show HN: I built a local AI agent desk toy

author: syx


value: itayd

value: Show HN: Leash: Replace PagerDuty with a Spreadsheet

author: itayd


value: lmxxf

value: Show HN: A Field Report on Teaching a Chinese AI to Deconstruct Its Censorship

author: lmxxf


value: Theoleff

value: Show HN: I wrote an eBook about building modern UI components without JavaScript

author: Theoleff


value: msoloviev

value:
This is a tool that I have long wished somebody else would make. I'm struggling to produce a good one-line or even one-paragraph description of what exactly it does, but a good analogy is the Linux kernel's `menuconfig` or CMake's curses-based `ccmake` configuration editor, except that rather than operating on a highly constrained config file format, it can edit basically any textual format in place, as long as that format has some notion of comments. The comments then can be made to hide "meta-instructions" that confy understands: define a number of typed parameters, perform some simple computations on them, and either inactivate or activate (by (un)commenting) designated blocks of the "object-level" file, or outright regenerate them from a template. As a basic example, you could write
//! bool $flag = true;
//! if($flag) {
printf("The flag is true!");
//! } else {
//-printf("The flag is false!");
//! }
and confy would expose a graphical interface to toggle "$flag" on or off, and comment/uncomment the appropriate line of text in the file, while also saving the updated initial value in the first line that defines $flag in the file.
Interaction is possible both via a curses-style terminal interface, and by scriptable getters/setters (like `confy filename.txt set variableName true` or `confy filename.txt get variableName`).

value: Show HN: Confy – programmable TUI controls for almost any structured text

author: msoloviev


value: krzysztofc

value:
Hey everyone
I wanted to share something I made: vcdir.com - a global, 100% free directory of 1300+ venture capital firms.
Most VC databases I found were either outdated, overly complex, or hidden behind a paywall.
So I decided to make one that’s:
It’s 100% free to browse, no signup or paywall required.
It lists 1,300+ VC firms from around the world (and the number keeps growing).
Lets you filter by country, continent, investment phase, and market focus
Each firm’s page includes basic informations like short description portfolio links, website, contact info, investment focus.
Includes categories, breadcrumbs, and a bookmarks for easy navigation and browsing
I wanted a better domain, but everything decent was taken or insanely priced :(
If you ever find yourself fundraising, or just wonder who’s really out there backing startups feel free to check it out :)

value: Show HN: I made a free global VC directory (1,500 firms, no signup)

author: krzysztofc


value: idanatomix

value:
We launched Codimix - a platform where developers network by building together.
The concept is straightforward: join coding events, meet other developers, and collaborate on something. The best way to know someone is to work with them on something.
We're running timed events at different hours so developers worldwide can participate. Teams typically work together for a few hours on small projects.

value: Show HN: Build Connections, One Commit at a Time

author: idanatomix


value: kevinlarsson

value: Just launched Huddlekit — drop comments, inspect CSS, and compare breakpoints side-by-side directly on any website. No embed/script/installation needed.<p>Would love some honest feedback on this.

value: Show HN: In-browser website annotation, inspect mode and breakpoint comparison

author: kevinlarsson


value: pearlyshells

value:
Hey HN,
We spent 5 months turning technically "transparent" but practically useless hospital pricing data into something patients can actually use.
The problem: Hospitals publish prices in massive CSV and JSON files (billions of rows, inconsistent formats, missing codes). Legally transparent, realistically worthless.
What we found: Same colonoscopy costs $2,675 at one hospital, $7,431 at another in Florida. Same insurance. 3x difference.
What we built: Simple tool to compare 100+ procedures across Florida hospitals, filtered by insurance.
Still very early (Florida only, lots of rough edges), but would love HN's feedback:
- What am I missing?
- How would you improve this?
- Is this solving a real problem?
Technical details about the data wrangling happy to share in comments if anyone's interested in that nightmare.
Thanks for any feedback!

value: Show HN: Healthcare Price Comparison Tool

author: pearlyshells


value: FitchApps

value: An LLM assistant runs entirely in your browser, all web-based.

value: Show HN: WebLLM and WebGPU enabled LLM app – CodexLocal

author: FitchApps


value: quintussss

value: Redstart is a lightweight Lisp interpreter written in C++ with a focus on shell scripting. It lets you combine the expressive power of Lisp with the practicality of the Unix shell: you can run commands, capture output, pipe between processes, and still use Lisp syntax for logic and structure. Think of it as writing your shell scripts in Lisp instead of Bash.

value: Show HN: A Lisp Interpreter for Shell Scripting

author: quintussss


value: Show HN: Runbook – Plain English Jupyter Notebook with Web/ PDF Action


value: BlackZephyr

value:
I'm Raph, and I had a video editing agency and one of the biggest pain points I had was finding specific clips from long videos.
If a wedding video is 6 hours long and I need to find romantic moments, I'd need to watch the whole thing.
What if I can just type in "romantic moments" and then it'll give me the clips? That's how spottr was born.
Shared the idea with a few communities and they were also interested with the idea being applied to sports analysis, surveillance, and documentaries.
Any other verticals I can apply this to?

value: Show HN: Spottr: Ctrl+F for Videos

author: BlackZephyr

title: Show HN: Spottr: Ctrl+F for Videos


value: justvugg

value:
Hi HN,
I built llm-use, an open-source system for routing, caching, and A/B testing between large language models like GPT-4, Claude, Llama, and models provided via Ollama. It intelligently routes prompts across these models based on complexity and usage, helping optimize cost and performance in production.
Would love your feedback!

value: Show HN: LLM-use – Routing, caching and A/B testing for LLMs

author: justvugg


value: My cofounder Marcelo and I spent all evening last night building support for OpenAI apps SDK. Developing with Apps SDK is pretty restricted right now as it requires ChatGPT developer mode access and an OpenAI partner to approve access. We wanted to make that more accessible for developers today by putting it in an open source project, give y’all a head start.

value: Show HN: We built an open source dev tool for OpenAI Apps SDK


value: jvmeshan

value:
Hey Everyone!
This is my first app that I have made and it’s called Trackwme!
It is basically starva but for habits, where you see people’s progress and compete with your friends!
I’ve been working hard to make this app, and I hope you guys like it!
Would love your thoughts, feedback, or ideas!
https://apps.apple.com/us/app/trackwme-social-habit-tracker/...

value: Show HN: I Made Strava for Habits

author: jvmeshan

title: Show HN: I Made Strava for Habits


value: bloppe

value: Show HN: A better way to run Bazel in Docker

author: bloppe


value: vipin-tanna

value:
We just launched Gabriel Operator — a browser-based platform that transforms your screen activity into fully executable AI agents. You simply record what you do in the browser, and we turn it into a repeatable agent that runs like a workflow—no APIs, no code.
What makes it different? • Works entirely off your screen (great for websites without APIs) • Agents can loop, branch, and request input • You can publish & monetize your automations • Fully web-based, no installation needed
Next week, we’re rolling out Creator Mode — allowing anyone to publish, share, and sell their own “Digital Angels” (our name for agents). We’re offering free access for the first month to early adopters who want to shape how this platform grows.
Would love feedback, thoughts, or AMA. We’re building this for real-world automation beyond devs — and we’re still early.

value: Show HN: We turned browser screen recordings into customizable AI agents

author: vipin-tanna


value: DeveloperOne

value: Show HN: A new platform for devs, hackers, and crypto folks

author: DeveloperOne


value: cylinderthought

value: Show HN: Identiqwe – Collect Deterministic pixel art avatars from any text

author: cylinderthought


value: blourvim

value:
it is pretty rough around the edges, but I had a lot of fun coding it.
it is both kind of a quine and a polyglot
It was challenging to make both the html render and rust source code look like a ghost.
I like how browsers don't give errors and display the trash i send to best of their abilities

value: Show HN: I made an ASCII Art rust server that serves its own source code

author: blourvim


value: pmig

value:
Hi HN, my name is Philip, I’m the co-founder of Glasskube and one of the creators of HyprMCP.
This project started when we did what everyone was doing — building a remote MCP server and launching it. Building the first local MCP server for testing was quite simple, and we had our first tools ready within a day. The next step was turning that into a production-ready remote MCP server.
As we exposed the MCP server to our users, we wanted to authenticate them with our existing authentication methods. We dove deep into authentication. Our approach was to build an auth proxy and plug it in front of our MCP. It took a while to figure out Dynamic Client Registration (DCR) and the OAuth spec, and especially the gaps between existing OIDC IDPs and what LLM clients needed.
We thought authentication would be the hard part — but it wasn’t. When we shared the MCP server with a few friendly startups, we realized that different MCP clients behave differently. Especially if something didn't work, it was hard to figure out the root cause. We ended up storing all the raw gRPC method calls to see if the initialization and subsequent requests worked. This is especially useful if you are on a serverless environment with limited debugging functionality, like Cloudflare Workers.
Once we solved auth and compatibility, we launched to a small customer base — done, right? Unfortunately, not quite. Technically everything was working, but when we started talking to users, they told us the MCP server didn’t always respond with the right tools for their prompts. We had a working enterprise-grade MCP server — but it wasn’t very smart. After talking to some startup friends, we realized we needed an evaluation layer. That’s when we added prompt analytics — letting us see which prompts triggered which tools and how well they performed. That alone dramatically improved our MCP’s behavior and overall user experience.
After building all of this into our proxy, we realized that everyone building a remote MCP was facing the same challenges. So we decided to package it all up and release it to the community.
We’re thrilled to launch and open-source HyprMCP.
It acts as a proxy that you can plug in front of your MCP server(s) with zero code changes. You get authentication, logging and debugging, prompt analytics, and an MCP connection instructions generator.
Under the hood, HyprMCP leverages dynamic Kubernetes Operators (Metacontroller) to automate infrastructure provisioning.
On the roadmap: MCP aggregation — combining multiple MCP servers under one single remote URL for large organizations running servers with different lifecycles.
All of it without storing end user credentials on the server and connecting the MCP to the organizations existing authentication methods.
You can check the project out on GitHub: https://github.com/hyprmcp/jetski
For testing, we also have a hosted version here: https://app.hyprmcp.com
We even created a demo video on YouTube: https://www.youtube.com/watch?v=m2-YyfjXap4
We’d love to get your feedback, hear what features are missing, and learn how you’re building and running your own MCP servers.

value: Show HN: HyprMCP – Analytics, logs and auth for MCP servers

author: pmig


value: Show HN: Puter.js Docs

title: Show HN: Puter.js Docs


value: SaulGallegos

value:
Hey HN,
I'm the founder of 64Careers, an all-in-one ATS and career page builder tailored for small businesses. We know hiring can be a nightmare for SMBs—spreadsheets, lost applicants, and expensive tools like Greenhouse or Lever that cost $300-600+/month.
With 64Careers, you can:
Launch a SEO-optimized, mobile-friendly career page in under 5 minutes (no coding or IT needed).
Use a drag-and-drop Kanban ATS to track applicants, with auto-resume parsing, LinkedIn imports, email notifications, and analytics.
Get a custom URL (e.g., yourcompany.64careers.com) that makes your business look like a Fortune 500.
Start free forever (1 job, basic features), or scale to unlimited for just $25/month—10x cheaper than competitors.
We've focused on simplicity for non-HR folks in retail, cafes, clinics, etc. Built with Nextjs mongodb and tailwind
Feedback welcome! What's your biggest pain in small biz hiring?
https://64careers.com

value: Show HN: 64Careers – Build a pro career page and ATS in 5 minutes for $25/mo

author: SaulGallegos


value: connorpeters

value:
We just launched Fuzzypass, an alternative to a master password that uses cued recall to make remembering an extremely strong secret easier. Unlike a password, you don't need to type your entire Fuzzypass to log in, just 3 lowercase words. While at first it's a little more difficult since it's new and different, once you do it a few times, your brain will "peg" your words to the locks and you should be able to login easily.
We don't think Fuzzypass is necessarily for everyone, but I think it will really appeal to a certain type of person (those who are more visually inclined). Try it out and let me know what you think!
Fuzzypass is available for free as part of Locke ID, our password manager and secure inbox. The linked post has a detailed write up on the security of Fuzzypass, using the concept of perplexity from LLMs converted into entropy.

value: Show HN: Fuzzypass

author: connorpeters

title: Show HN: Fuzzypass


value:
I built Kooder, an AI software engineer that generates fully functional full-stack applications from natural language prompts. The goal is to streamline the development process for both engineers and non-technical founders.
Key features:
Natural language app generation (describe your idea, get working code)
Support for major frameworks (React, Next.js, Node, Python, and more)
Backend API scaffolding and database setup
Smart code suggestions and refactoring
Continuous deployment integrations
Kooder is already helping solo founders, indie hackers, and internal engineering teams build faster. I’d love feedback from the HN community—feature requests, critiques, and questions are all welcome!
Try it free at kooder.dev and share your thoughts below!

value: Show HN: Kooder – AI Software Engineer for Full-Stack Development


value: khaulafatima

value:
Hi ,
I am abu. Just build this plugin for my personal use. Thought about sharing with community.<p>It took me 2 hours to develop with vibe coding.

value: Show HN: Google Chrome plugin "Hacker News Summarizer"

author: khaulafatima


value: SafeDusk

value:
ToolKami CLI is a modified version of Shopify's CEO Tobias try implementation[0]. It extends the implementation with sandboxing capabilities and designed with functional core, imperative shell in mind.
I had success using it to manage parallel coding agents with a minimal TUI interface.
It is free and open source, have fun playing around with it, roll your own or contribute!
[0]: https://github.com/tobi/try

value: Show HN: ToolKami CLI – Simple Agents Made Easy (Extending Shopify Tobi's Try)

author: SafeDusk


value: soasme

value: Show HN: Popomo – Program Your Puppets Alive Tell Stories. Not Keyframes

author: soasme


value: adrienditta

value:
I’ve built a site that uses mathematical models like Poisson, Dixon-Coles and Glicko ratings to estimate real football probabilities and generate betting insights.
Feedback is welcome — especially about how I present the data or improve calibration.

value: Show HN: PlayAiOdds – Football probabilities from AI and mathematical models

author: adrienditta


value: lakshikag

value:
I built nooki.me, a simple and minimal discussion platform powered by ATProto (the open social protocol behind Bluesky).
The idea is to bring back the feel of old-school forums and early web discussions which slower, calmer, and more personal but with the benefits of a decentralized social network.
Most modern social platforms optimize for engagement, not conversation. I wanted something that felt like a place that is small, intentional, and owned by users. ATProto made this possible because posts, comments, communities and identity are all yours — not locked into one app.
Everything but not limited to posts, comments, communities are stored on the AT network, meaning you can move between compatible apps anytime.
The UI is intentionally minimal and only supports text posts at the moment.
I’d love feedback — especially from those who care about the open web, digital minimalism, or the future of social protocols.

value: Show HN: nooki.me - I built a distraction-free discussion platform on ATProto

author: lakshikag


value: teamechomode

value:
Hey HN! I’m Sean, and I built EchoMode to solve a frustrating problem with long LLM conversations: persona drift — when models slowly forget their intended tone, style, or role after multiple turns.
The Problem:
Even well-prompted models (GPT-4, Claude, Gemini) start to lose persona after ~8 turns. Studies like Measuring and Controlling Persona Drift (arXiv:2402.10962) confirm that tone consistency decays fast with topic shifts and long contexts.
The Solution:
EchoMode is a middleware protocol that keeps LLMs consistent by monitoring tone drift in real time and repairing deviations automatically. Think of it as TCP/IP for language stability.
How it works:
– Finite-state machine (Sync / Resonance / Insight / Calm) tracks conversation state
– Calculates a driftScore between each output and baseline persona
– Triggers a repair loop if deviation > threshold
– EWMA smoothing (λ≈0.3) prevents overcorrection
– Works across OpenAI, Anthropic, Gemini, Mistral APIs
Tech Stack:
TypeScript SDK • Drift telemetry dashboard (soon) • Apache-2.0 open core + commercial observability layer
Use Cases:
AI agents that must stay on-brand, compliant, or emotionally consistent over long sessions.
Try it:
 github.com/Seanhong0818/Echo-Mode

value: Show HN: EchoMode – A stability layer that prevents persona drift in LLMs

author: teamechomode


value: artiomyak

value: Show HN: Reading Light

author: artiomyak

title: Show HN: Reading Light


value: gptlocalhost

value: Run your favorite and local LLMs in Microsoft Word — right on your computer. GPTLocalhost lets you use latest AI models locally, ensuring complete data privacy, zero monthly fees, and effortless switching between models anytime.

value: Show HN: GPTLocalhost – Use your local LLMs in Microsoft Word

author: gptlocalhost


value:
I built a simple PDF to PNG converter that runs entirely in your browser using PDF.js. No files are uploaded anywhere – everything happens locally on your device.
Key features:
Converts all pages of single/multiple PDFs
Batch processing with ZIP download
Scale and background options (white/custom/transparent)
Works on mobile, completely free
I wanted something fast and private for converting PDFs to images without worrying about uploading sensitive documents. The tool uses PDF.js for rendering and handles everything client-side.
Try it at: https://pdftopng.cc/

value: Show HN: PDF to PNG – 100% client-side converter with no uploads


value: wushi

value:
Since Sora’s second-gen video tool, the corner watermark has become noticeably harder to deal with. When distributing clips to other platforms—especially for vertical edits, mashups, or remixes—it looks out of place.
I often need a clean version for editing and packaging, so I built a simple button: upload → click → download.
Site: sorawatermarkremover.net
What it does
Automatically detects the corner region and cleans it with AI in one click;
Works with default settings—no manual tweaking for most clips;
Outputs common formats that drop straight into your edit/distribution flow.
Boundaries & use
For content you own or are authorized to edit only. Please don’t remove marks that must remain or use it for infringement.
This isn’t an ownership check; I rely on user responsibility. If stronger guardrails are needed, I’m open to adding them.
Privacy
No login required to try;
Processing is server-side; I don’t use uploads for training or share them;
Retention/deletion policy will be tightened and clarified based on feedback.
Known issues
Fast motion + complex textures may show subtle artifacts;
Heavily compressed footage is more likely to reveal edges. I welcome hard cases.
Why HN
This started as a small button for my own distribution workflow, and I’d love honest feedback:
Web app vs a Chrome extension—which would you prefer?
Any watermark scenarios in distribution that I’m missing?
Suggestions on policy/abuse prevention.
What’s next
Batch processing and API if there’s demand;
A “light blend” mode that favors natural look over total removal.
Thanks for reading—feel free to share short clips that break it, and I’ll follow up.

value: Show HN: Sora2 watermark is heavy, so I built a one-click remover

author: wushi


value: TDYSKY

value: I made this because I'm tired of paying for Windsurf. It's not perfect and still in very early access, so please be kind and write me your feedback on my Discord the link is on GitHub!

value: Show HN: Tdycoder – Local AI code editor using Ollama LLM

author: TDYSKY


value: SherlockShi

value:
Hi HN,
Recently, while experimenting with pixel art for a game prototype, I encountered a challenge: existing tools either required downloads, added watermarks, or didn't preserve image details effectively. Determined to find a solution, I developed Pixelate Image—a fast, free, and privacy-first pixel art maker that transforms any JPEG, PNG, or WebP file into stylized pixelated artwork directly in your browser.
Whether you're creating retro game assets, social media visuals, marketing campaigns, or mood boards, Pixelate Image streamlines the entire process. No downloads, no watermarks, no learning curve—just a smooth experience on desktop and mobile. All processing happens locally in your browser, so your files never leave your device.
Key Features
· One-click pixelation: Convert images to pixel art instantly with adjustable intensity levels.
· Smart detail preservation: Maintain essential outlines and silhouettes for professional-looking pixelated images.
· Multi-format support: Upload JPEG, PNG, or WebP images up to 5MB and export high-quality files.
· Real-time preview: See every change as you adjust pixel sizes and quickly iterate toward the perfect look.
· Full commercial usage: Download pixelated artwork with unrestricted rights for personal or commercial projects.
· Privacy-first workflow: 100% browser-based processing—no uploads, no tracking, no watermarks.
· Responsive design: Optimized UI for desktop, tablet, and mobile so you can pixelate on the go.
How It Works
· Upload a JPEG, PNG, or WebP image (max 5MB) via drag-and-drop or file picker.
· Select your pixelation level—minimal, light, medium, heavy, or extreme.
· Review the live preview and fine-tune the effect until it matches your creative vision.
· Download the final pixelated image in your preferred format and start sharing or editing.
I'd love for you to try it out, break it, and share feedback or suggestions. If you have ideas for new features, edge cases, or just want to say hi, please comment below!
Website: https://pixelate-image.net

value: Show HN: Pixelate Image – Image Pixelator to convert image to pixel art

author: SherlockShi


value: azeemkafridi

value: Show HN: StartEndContain – Find words, animals, cities using alphabets

author: azeemkafridi


value: seekerquest

value:
Alongside Twick SDK, we have now launched Twick Studio - our new UI for visual video editing.
Try it now: https://twick-studio.vercel.app/
Key features:
- Multi-track timeline with drag & drop
- Live video preview & customizable dimensions
- React-based canvas for easy drag, resize, rotate
- Undo/redo, element controls (text, video, audio, image)
- Media utils for metadata, thumbnails, and more
Check out the docs for full details:
https://ncounterspecialist.github.io/twick/docs/intro
Explore the full source-available toolkit on GitHub:
https://github.com/ncounterspecialist/twick
If you find Twick useful, please give the repo a  to support ongoing development.
We would love to hear your feedback and suggestions for new features.

value: Show HN: Twick Studio and SDK – React Video Editing Toolkit with Visual UI

author: seekerquest


value: sachithrrra

value: Show HN: Font Info Inspector

author: sachithrrra

title: Show HN: Font Info Inspector


value:
I built a completely FREE, open-source AI coding assistant in Python over a weekend. It works with any codebase, keeps your data local, and rivals paid alternatives.
What is Lynecode?
 Open Source: You can customize if you want
 Terminal first: Works with ANY language, ANY project size
 30+ tools from ASTSearch to SEMGREP
 Your data stays LOCAL
 Built in safety, Auto-backups before every change without even having git
The "Holy Sh*t" moment
I built my entire website (https://www.lynelabs.com/) using Lynecode in under 2 hours. That’s when I realized this thing actually works and could rival the expensive alternatives.
Why this matters for developers everywhere:
 No more $20/month subscriptions draining your budget
 Data sovereignty: Your code doesn’t leave your machine (or host on your own Azure for extra privacy)
 Learn from readable code
 Toolset which can rival it's paid alternative and easily expandable
The bigger picture
This isn’t about claiming to be the absolute best (I honestly haven’t tested every tool out there). It’s about showing that you don’t need million dollar funding or fancy marketing to build something useful

value: Show HN: Built Open Source AI Coding Assistant Which Rivals to Cursor


value:
Hi! This is an open-source game that teaches how to build an emulator from scratch. It also has a "free mode" where players can skip the tutorials and build an emulator for another platform (like the Game Boy, for example). I hope you enjoy it!
The source code is MIT-licensed and the guides are CC BY-NC.
https://github.com/afska/emudevz

value: Show HN: EmuDevz – Open-source interactive emulator dev tutorial


value: Marlinski

value:
Since I mostly work within the terminal, I wanted an AI coding assistant that integrates seamlessly with it. Something I could call from SSH, integrate into scripts or just invoke quickly without leaving the shell. Most existing tools (at the time) were either closed, required various dependencies, or tied to a specific vendor. I wanted a free, open-source alternative that:
- installs with a single binary (useful on bare servers)
- talks to any LLM endpoint and especially self-hosted open weight model
- could run headless, composable, and Unix-like
SHAI stands for SHell AI! Along the way I couldn’t find a `lite-llm` equivalent for Rust, so I built the crate `shai-llm`. I tried to make it as modular as possible so new tools can be added, UIs swapped, or an API layered on top. It was also my first major project in rust, I hope you'll like it :)
Key features:
- Open-source and LLM-agnostic: connect to any OpenAI-compatible endpoint
- Works out of the box using OVHcloud AI Endpoints (unauthenticated, strongly rate-limited)
- Function calling and MCP support (with OAuth)
- Custom Agent Configuration (model, system prompt, tool set)
SHAI is still evolving, but it's part of Hacktoberfest so contributions and feedback are most welcome.

value: Show HN: SHAI – a (yet another) open-source, terminal-native AI coding assistant

author: Marlinski


value: sumit-paul

value:
Hey HN,
I built SnapSort, a cross-platform app that uses Google’s Gemini to automatically sort and categorize your photos.
Why I built it:
Ever taken a screenshot to send to a friend… and then forgotten about it? Or downloaded a photo and never moved it from Downloads? Your Photos, Desktop, and Downloads folders slowly turn into chaos.
I was tired of cluttered folders filled with screenshots from the last three years. I wanted something that automates photo organization using AI.
What it does:
- Sorts photos into categories like portraits, food, nature, or documents using Gemini
- Let's you copy or move organized images into folders automatically
- Works on macOS (Intel & ARM), Windows, and Linux
- Pro version adds background monitoring, custom categories, and move operations
- One-time license, lifetime updates & no subscription
You bring your own API key; SnapSort never stores or sends your images anywhere else. The analysis happens through your key, and all results stay on your device.
If you have a messy Pictures folder, SnapSort can help you bring order in minutes.
Download here: https://snapsort.dev
Would love feedback on:
- Ease of setup (especially Gemini API key)
- Categorization accuracy
- Features you’d want next (e.g., local embeddings, auto-tagging, duplicates handling)
Thanks for checking it out!
— Sumit

value: Show HN: SnapSort – Automatically sort and organize your photos with AI

author: sumit-paul


value:
Hi HN,
After building kexa.io, the open-source solution to scan your clouds for misconfigurations, we’re excited to announce the premium version, powered by AI for remediation assistance.
When we first launched Kexa, our goal was to give developers and security teams a simple, unified, and Infrastructure-as-Code native tool to automate compliance and security checks across AWS, GCP, Azure, and more.
Thanks for the feedback we got on our last post on HN !
One piece of feedback stood out: while developers loved the IaC approach, many teams wanted a way to visualize their security posture, manage rules, and track remediation without diving into config files.
That’s why we built the premium version.
We added a web interface to:

        Visualize your entire multi-cloud security posture from a single web interface.

        Manage your rules through UI & edit with our no-code rule builder.

        AI Remediation assistance with clear insights based on CIS benchmarks and Kexa rules.

We’d love for you to check it out at https://www.4urcloud.eu/
Please support us by giving a star to the kexa.io open source project on Github !
Happy to answer any questions. What do you all think? How are you currently handling multi-cloud compliance and misconfiguration scanning at scale?
contact@kexa.io

value: Show HN: Kexa.io – Open-Source IT Security (Now Premium UI and AI)


value: Show HN: Multiple web search providers via one TypeScript package


value:
Hey all! I'm building these collection of APIs to help query SERP, PDP and Reviews data from Ecommerce sites solo since the past few years. I have hundreds of customers and revenue. ScrapingBee (a popular scraping API service) has started copying me now so I thought of doing a Show HN finally.
Please butcher my product. I'd really appreciate your feedback.
Do reach out via email if you'd like extra free credits, will add them to your account if your email address doesn't look like spam.

value: Show HN: Unwrangle - E-commerce Content Retrieval APIs


value:
Hi HN,
I built a small web app that lets you transform your own photos into different artistic styles using AI — things like oil painting, surrealism, impressionism, pencil sketch, or fantasy renderings.
The goal wasn’t to create another “filter app,” but a way to give ordinary photos a new life through custom-trained models that emphasize detail, texture, and lighting.
The project started as an experiment in making AI-generated art more personal and less generic — users upload their own images, tweak the result, and can then optionally have it printed on a canvas, poster, or other material.
I’d love feedback from the HN community — on the UI, model quality, or ideas for improving control over the output.
Link: https://artsnappy.com/design-editor/

value: Show HN: Turn any photo into AI-generated artwork


value: NadezdaS

value: Show HN: Built AI assistant for 300 products using Google Gemini (zero cost)

author: NadezdaS


value: Excited to launch Context Saver for AI users—bookmark and restore your chats from ChatGPT, Gemini, Claude and more instantly. No account required, works cross-platform. Demo inside, be among the first to help shape this new product.

value: Show HN: Validating New AI tool to save, restore and save context


value: minfrin

value:
Hi HN, I built connectcap, a CONNECT proxy for diagnostics.
The problem I had to solve was I had a network problem only visible in one part of the internet, that had to be fixed by a cloud provider present on another part of the internet who could not see the problem, and I was fighting a lot of technology designed to work around problems that hid things and in so doing downplayed the seriousness of the problem.
What does it do?
- Connectcap is an RFC9110 http CONNECT proxy; that
- Gets libpcap to record each connection through the proxy and save it as a separate pcap file for analysis by tcpdump or wireshark; then
- Optionally emails a summary and the pcap file back to the user who used the proxy.
What does it not do?
- Connectcap makes no attempt to compensate for broken network behaviour; like
- Trying a different server if the first connection failed; or
- Falling back to IPv4 if IPv6 failed (no Happy Eyeballs).
Why not just tcpdump?
It can be difficult to predict what server you will connect to, and in turn what to record. Couple this with a cloud provider in another region or timezone needing to collaborate to generate the traffic, and life becomes very difficult.
Instead, deploy a connectcap proxy on the network giving trouble, and provide login details to the cloud provider, who can see the problem for themselves at their convenience, and receive all the diagnostics they need without waiting.
What about other proxies?
Many proxies try hard to compensate for broken networks, broken servers and so on. A diagnostic tool needs to do the complete opposite, not compensate for problems at all, and be completely clear this is the case.

value: Show HN: Connectcap – diagnostic CONNECT proxy that records traffic with libpcap

author: minfrin


value: Imposter Game Generator started from a simple idea: "make gatherings effortless"

value: Show HN: Imposter Game Generator

title: Show HN: Imposter Game Generator


value: techyKerala

value: A minimal demo of SIP ↔ WebRTC. This example shows how a WebRTC browser client can register, call, and communicate through a SIP signaling server.

value: Show HN: A minimal demo of SIP ↔ WebRTC

author: techyKerala

title: Show HN: A minimal demo of SIP ↔ WebRTC


value: sweaver

value:
Hi HN,
I’m Sam, co-founder of Plural (https://plural.sh/). Today we’re launching the next generation of our platform—an AI-powered experience for DevOps.
Our view is simple: what Cursor has done for software development, Plural is doing for DevOps.
DevOps teams are overwhelmed by:
- Kubernetes upgrades that break downstream workloads
- Endless YAML diffs and drift
- Reactive firefighting when incidents hit
Plural’s new release integrates AI directly into GitOps workflows, so platform teams can move faster and more safely:
- Autonomous upgrade assistant → orchestrates complex Kubernetes upgrades with guardrails
- AI-powered troubleshooting and Fix → leverage the resource graph from our GitOps engine to provide deep RAG into devops data, generating well-informed root cause analysis, and fixes PRs for a broad set of kubernetes and IaC issues
- Query Your Infrastructure with Natural Language - we will vectorize and index your devops information as they’re instantiated, giving a clean semantic understand of your entire estate which is useful for ad-hoc search and discovery and agentic workflows
- DevOps agents tuned to terraform and kubernetes - use all the information above to provide agentic workflows for modifying infrastructure managed via GitOps.  Ask Plural to “double the size of my production database” and the combination of our semantic index and ability to do deep RAG against your infra and code will guide the AI to make the necessary change and issue a PR for you to review.
The future of DevOps isn’t more dashboards or more YAML. It’s AI-augmented workflows that multiply team productivity while keeping humans in the loop for control.  GitOps is the ideal surface for that since it is fully auditable, easily composable with proven and rapidly improving capabilities around LLM coding, and provides a clean review-approval loop to ensure changes are performed safely.
We’d love feedback from the HN community on:
1. Where you’d want AI to take the toil out of your DevOps workflows
2. What would give you trust in AI systems operating in production
3. The biggest blockers you face managing Kubernetes at scale
Full launch post here with more technical details: https://www.plural.sh/blog/plural-now-with-ai-that-understan...
Excited to share this with you all — happy to dive deep on any part of the system.
— Sam, CEO/co-founder of Plural

value: Show HN: Plural – Bringing AI to DevOps the way Cursor did for coding

author: sweaver


value: trebligdivad

value: Show HN: Using an LLM to sensibly sort a shopping receipt

author: trebligdivad


value: ashtonjamesd

value: Show HN: I built a web framework in C

author: ashtonjamesd

title: Show HN: I built a web framework in C


value: Show HN: Adobe Wakatime – Track time spent in Adobe software


value: firstnod

value:
This Is Nod
Nod is a new programming language I've been working on for five years.  It's a serious effort to design a language that I wished someone else would have invented while I was still working as a professional software engineer.
This is my first post to HN, so hopefully I'm not stepping on any guidelines.  It's real news, it's mine, and you can learn more about it on the Nod dev website.
Why I Built Nod
I was a professional programmer/software engineer for almost 40 years. During most of my career, C and its descendants ruled the day. In fact, it can't be overstated just how influential C was (is) on the field of programming. But that influence can also be characterized as burden. Newer C-based languages like C++, Java, C#, and others, are improvements over the original for sure, but backward compatibility and adherence to familiar constructs have stifled innovation and clarity.  C++ in particular is an unapproachable Frankenstein.  Powerful, yes, but arcane syntax and semantics has raised the barrier of entry to all but the most motivated.
Although C++ was usually my first or only choice for a lot of projects, I kept waiting (hoping) that a viable successor would come along. Something fresh, performant, and pragmatic. Something that broke cleanly from the past without throwing away what worked. But nothing really did. Or at least nothing worth the effort did. So, in 2019, newly retired and irrationally predisposed, I decided to build that fresh, performant, pragmatic language myself. That language, imho is Nod.
What Nod Is
Nod is an object-oriented language designed from the start to be a fresh and practical alternative to the current status quo. The goal is to balance real-world trade-offs in a language that is uniquely regular (consistent), efficient (fast), reliable (precautious), and convenient (automatic). While Nod respects the past, it's not beholden to it. You might say that Nod acknowledges the past with a respectful nod, then moves on.
Nod has wide applicability, but it's particularly well-suited for building low-level infrastructure that runs on multiple platforms. A keen awareness of portability issues allows many applications to be written without regard to runtime platform, while kernel abstraction and access to the native kernel provide the ultimate ability to go low. Furthermore, built-in modularity provides a simple and robust path for evolution and expansion of the Nod universe.
What Next?
Although I've worked on Nod for five years, it's a long way from being finished. But it's far enough along that I can put it out there to gauge interest and feedback from potential early adopters and collaborators.
The language itself is mature and stable, and there are the beginnings of a Nod Standard Library residing in a public GitHub archive.
I've written a compiler (in C++) that compiles source into intermediate modules, but it's currently in a private archive.
There's still much more that needs to be done.
If you're interested, please go to the website (https://www.about-nod.dev) to find links to the Nod Design Reference and GitHub archive.  In the archive, there's a brief syntax overview that should let you get started reading Nod code.
Thanks for your interest.

value: Show HN: Introducing Nod, a new object-oriented language I'm working on

author: firstnod


value: filippofinke

value: Show HN: I built a tool to automate Slack status with rules and schedules

author: filippofinke


value: lindesvard

value:
Hey,
I’ve been using BullMQ for several years and have been super happy with it. But lately, I realized I really needed grouping (being able to run only one job per group in sequence).
Since this is for an open-source, self-hostable project, I didn’t want to force users to pay for BullMQ Pro licenses for using it.
So, I decided to build my own queuing solution called GroupMQ, which allows you to group jobs together and run jobs in sequence based on a groupId.
I also needed a way to order jobs by timestamp, since my project receives events and maintaining the correct order is critical.
Some goodies:
- Scalable with performance on par with BullMQ (except when ordering is enabled, since it requires delays)
- Ordering based on Unix timestamps
- Grouping jobs so they run sequentially (per groupId)
- Scales with concurrency and multiple workers
- Runs several groups in parallel
It’s available on npm as groupmq, and you can check out the repo here: https://git.new/groupmq
Note: The package could never be possible without BullMQ, all credit to them for building such a great library.

value: Show HN: GroupMQ – A FIFO job queue for node and Redis

author: lindesvard


value:
I built a tiny fix for time-zone friction.
What it does
- Hover any time string on any website to see your local time + zone (e.g., Asia/Tokyo)
- One-click copy in 12-hour / 24-hour / ISO 8601
- Options UI; Pro adds default format, per-site enable/disable, and import/export
Under the hood
- Chrome MV3: background service worker + content script
- Permissions: `storage` only (to save preferences)
- No tracking, no external calls for tooltips
Links
- Chrome Web Store: <CWS_URL>
- Landing & screenshots: https://doooooraku.github.io/Time-Zone
Feedback I’m looking for
1) Your preferred default format (12/24/ISO)
2) Sites/locales where parsing fails (please share sample strings)
3) Whether per-site control covers your workflow
Thanks for taking a look!

value: Show HN: Time-Zone Hover – see your local time on any site (copy 12/24/ISO)


value: Well, apparently, human-created videos are not trendy anymore. Slap the Sora watermark on any of your videos and see how your friends react.

value: Show HN: Slap the Sora watermark on any video, because why not?


value: siddharthdeswal

value:
Hey people, we built Enfra, a Chrome extension that pipes live SEO & Google Ads data into ChatGPT so you’re not prompting “blind.”
Enfra is a Chrome extension that pulls Google SERPs, Ads, and page markup for a keyword or URL you choose, and adds that context in your chat. Works in ChatGPT, Claude, Gemini, and Perplexity.
The problem: we built a Marketing agent, but end-users in design partner companies weren't using it. So we asked them how they're using AI currently, and they said "we have a ChatGPT tab open at all times".
What it does: injects structured data from SERPs, Google Ads, URLs and Search Console so that users can run their own chat workflows.
The big change is that users don't have to learn a new interface. They're already using ChatGPT and others for a ton of Marketing work, now they get better answers because the AI tools have better context.
And about privacy, we only fetch and insert Marketing data, we don't read your chats.
We'd deeply appreciate any comments or feedback.

value: Show HN: Enfra – Live SEO/Ads Data Inside ChatGPT (Chrome Extension)

author: siddharthdeswal


value: Virock

value: Tired of losing your favorite app's installation file? Need a simple way to backup your installed Android applications? Our APK Extractor is the ultimate utility tool for every Android user!

value: Show HN: An APK extractor for installed Android apps

author: Virock


value: adeptads

value:
Are you manage PPC campaigns for clients?
Are you a business or startup founder?
Create a fully bootstrapped Google Ads campaigns in one click and 15 minutes wait time!
Connect your ads account, fill in the basic campaign's traits, description of the target product and users - get a unique campaign generated on each run, with multiple ad groups with ads / asset groups for Pmax.

value: Show HN: Google Ads campaigns from 0 to live in 15 minutes, by Multi-Agent AI

author: adeptads


value: ddmdd

value:
Hey HN, I’m Hang. Today I’m open-sourcing InsForge, a context aware backend for AI coding agents.
When using agents like Cursor or Claude to build applications, they often assume what the backend looks like instead of inspecting it. Without access to the actual backend state, they fall back on outdated information, which leads to concrete issues. For example:
1. Storage, edge functions, and database logic are closely connected. Without understanding how these parts interact, existing setups get overwritten and important flows break.
2. Database migrations conflict with foreign keys or miss functions because the agent never inspects the live schema.
3. Recreating tables or adding columns that already exist, which leads to conflicts and failed deploys.
These problems are not about the agent’s ability to code. They happen because there’s no structured way for the agent to inspect and understand the actual backend before acting.
To address this, I built InsForge, which exposes the backend in a structured way and gives the agent direct control:
1. Introspection endpoints for schema, relations, functions, triggers, policies, routes, storage, roles, documentation, logs and events
2. Control endpoints for operations usually done through CLI, dashboards or SQL editors
InsForge is a full backend platform that includes:
- Postgres
- Authentication
- Storage
- Edge functions
- Built in AI-model endpoints (via OpenRouter)
On top of this, it exposes structured backend metadata and control capabilities through an MCP server and tools, providing a structured, self-describing interface for agents to inspect schemas, policies, triggers, and docs, and interact with the backend.
It’s open source and can be self hosted (https://github.com/InsForge/InsForge) or try our cloud service at (https://insforge.dev/).
We love feedback!

value: Show HN: A context aware backend for AI coding agents

author: ddmdd