value:
Hey HN, we're Haakam, Michael, and Adi. We're building AgentMail (https://agentmail.to/), an API to give AI agents their own email inboxes. We’re not talking about AI for your email, this is email for your AI.
We started building email agents because they can converse with users in their inboxes, automate email-based workflows, and authenticate with third-party applications. Given these unique capabilities, we think email will be a core interface for agents.
But we were building on top of Gmail, which was a struggle: poor API support, expensive subscriptions, rate limits, sending limits, GCP Pub/Sub, OAuth, crappy keyword search, and an overall terrible developer experience.
Gmail and other providers didn’t work for us. So we decided to bite the bullet and build our own.
AgentMail is like Gmail, but API-first, with programmatic inbox creation, events over webhooks and websockets, simple API key auth, organization-wide semantic search, structured data extraction, and usage-based pricing that scales with emails sent/received.
Here’s a demo of building an email agent: https://youtu.be/1V7BISeFUTM, and here’s a demo of a voice agent with its own email inbox: https://youtu.be/eG2fCsRK4RY
So far AgentMail has been deployed to use cases such as apps with dedicated inboxes for each user, voice agents that receive documents in real time, automated account provisioning and QA testing, cold outbound platforms with thousands of inboxes, automations for processing invoices, and agents that coordinate work with humans and other agents.
We would love to hear your thoughts and feedback. You can try our playground at https://chat.agentmail.to

value: Show HN: AgentMail – Email infra for AI agents


value: metehanoz

value:
Hey! Latted is a weekend project I built to convert books into TikTok-like short form videos with AI-generated visuals. The first book I converted is "The Art of War" by Sun Tzu and you can try it out with no signups.
Why did I build this?
I have a long list of books that I never get to read. I always said 'I had no time' but that is simply a lie when I average 4 hours a day on YT shorts.
So I wanted a way to read books that would give me similar dopamine hits as YT shorts and maybe replace hours I’m spending on TikTok-like video with something more useful.
How is it different?
I tried audio books but I think they work better for passive listening when doing other chores. I wanted a deeper immersion with the book while decreasing the time I spend on YT shorts.
Would love to get your feedback on:
- Storytelling - is it actually compelling? How could it be better?
- Next books?

value: Show HN: Latted – Turning Books into TikTok-Like Short Form Content

author: metehanoz


value: alenmangattu

value: Just small prototype showcasing diffusion models

value: Show HN: Implementation of DDPM (Denoising Diffusion Probabilistic Models)

author: alenmangattu


value: lieret

value:
Hello from the SWE-bench/SWE-agent team at Princeton/Stanford.
When we created the SWE-bench benchmark in 2023 from hundreds of real-life GitHub issues/pull requests, the highest score was just a couple of percent. The tasks were so challenging for LMs, that most people didn't even want to work on them.
Half a year later, SWE-agent showed that the early 2024 LMs were actually good enough to resolve up to 20% of the GitHub issues in the benchmark. This kicked off a whole wave of coding agents.
Back then, developing agents was all about working around tons of silly behavior from the LMs. For example, if a command didn't work, they would try running the exact command again. If a command didn't return output, they would assume it never ran. They also couldn't get whitespace right in their edits, would get stuck into repetitive attempts and much much more.
So agents got pretty complicated to work around all of that bad LM behavior.
But now it's 2025, and LM companies have invested a whole lot of money to make their LMs really good at being agents.
So we asked two questions:
1. What's the simplest agent we can write that still scores near SotA?
2. How do LMs compare when we evaluate them using this simple agent?
Turns out, the agent can be very simple indeed! mini-swe-agent (https://github.com/SWE-agent/mini-swe-agent) has only 100 lines of code for the agent class (plus some 100 lines for environment etc.).
It is little more than a loop that parses LM output for shell commands, executing them in a subshell, and continuing.
We then took various LMs and put them to the test in a real apples-to-apples comparison without a fancy agent scaffold to prop up bad LMs.
Our new leaderboard https://www.swebench.com/ shows the results.
The highest score is currently 65% with Claude Sonnet 4 (which is not much less than the 70% that most fancier agents observe).
o3, o4-mini, and Gemini 2.5 Pro are significantly behind, but not hopeless, achieving 50-60%.
We were really surprised by these strong numbers overall: It shows that as LMs get stronger and better adapted at performing difficult, highly iterative tasks, we can take our hands off of the steering wheel, provide the minimal necessary environment, and let the LM figure out the rest.
Let us know if you have any questions, our team is here on HN today :)

value: Show HN: New SWE-bench leaderboard compares LMs without fancy agent scaffolds

author: lieret


value: notelm

value: Show HN: A desktop-pet app built with bevy

author: notelm


value: dmarinoc

value:
Hi HN! I'm sharing legal-markdown-js, a TypeScript port of an abandoned 2011 Ruby gem that solves a surprisingly complex problem: writing legal documents that don't break when you edit them.
The Problem: Legal documents have intricate numbering schemes (1.1.1, (a)(i), etc.) and cross-references. Change one section and you might need to renumber 50+ references manually. Plus there's tons of repetitive boilerplate clauses scattered across documents. Lawyers often avoid restructuring documents because it's too error-prone.
The Solution: Write contracts in Markdown with tons of helper functions: auto-numbering, variables, conditional blocks, cross-references, and imports.
Example

    ---
    party1: "ACME Corp"
    party2: "{{client_name}}"
    jurisdiction: "California"
    ---

    # Software License Agreement

    l. This Agreement is between {{party1}} and {{party2}}.
    l. License Grant
    ll. Restrictions
    lll. No reverse engineering
    lll. See section @[License Grant] for details

    {{#if enterprise}}
    l. Enterprise Features
    ll. Priority support included
    {{/if}}

    @import "clauses/standard_termination.md"

The l. markers become proper legal numbering, variables expand ({{client_name}}), conditional blocks show/hide content ({{#if enterprise}}), cross-references update automatically (@[License Grant]), and imports (@import) let you reuse boilerplate clauses.
Why I Built This
I stopped programming to build startups, became a corporate PM, and now I'm starting a fund. I wanted control over the legal documents we share with LPs and portfolio companies – tired of paying lawyers for simple template changes, but most importantly frustrated with losing version history in Word docs.
Scratching this itch became my late-night learning vehicle for modern development practices. What started as "I'll just port this Ruby gem" turned into a deep dive into TypeScript, testing frameworks, and the entire modern JS ecosystem.
Technical Details
- Full TypeScript with strict typing
- Extensive test coverage
- ESM-first with CommonJS fallback
- Remark/Unified integration for extensibility
- CLI + programmatic API
- Full processing pipeline with multiple format outputs including PDF with highlights
The original Ruby gem was solid but abandoned. The JavaScript ecosystem deserved a maintained version, especially with legal tech growing rapidly.
Who This Helps
- Humans and legal professionals tired of Word's auto-numbering disasters
- Legal tech companies building document automation
- Anyone generating contracts programmatically
- Developers who need to template complex documents
GitHub: https://github.com/petalo/legal-markdown-js/
Playground: https://petalo.github.io/legal-markdown-js/
Original Ruby Project: https://github.com/compleatang/legal-markdown

value: Show HN: Legal–Markdown-JS, Git-friendly legal docs with Markdown and helpers

author: dmarinoc


value: mawise

value:
Hi everyone,
This project started as a way for me to share pictures of my then-newborn kid with close friends and family.  I've always been privacy conscious and didn't really want to use Facebook or Instagram.  The more I've worked on it, the more it feels like it could be a healthier way for people to interact on the internet--avoiding the polarizing, engagement-optimized algorithms that generate modern news feeds.
I shared this project a few years ago: https://news.ycombinator.com/item?id=26013715
Since then (in addition to a lot of small things) I added a built-in feed reader.  Haven already published private RSS feeds, now you can subscribe to those feeds along with any other RSS/Atom feed right in Haven.
I'd love any feedback, thanks for taking a look!

value: Show HN: Haven – Selfhost a private blog instead of using Facebook

author: mawise


value: ceeb

value:
I'm Craig Buckler and Publican is my tiny, simple, fast, and free static site generator for Node.js.
I've used several SSGs including Jekyll, Metalsmith, and Eleventy. Why build another? The main reason: personal preference. All SSGs have features that I need, features I don't need, and features they don't support. Publican implements just enough with flexibility to extend it using JavaScript.
Publican templates use JavaScript literal ${ expressions } so there's no weird syntax to learn. You can also use !{ expressions } to output partially-built pages for runtime use in Express.js or elsewhere. Features include:
- process any content: markdown, HTML, CSS, JavaScript, TXT, SVG, RSS, XML, etc.
- simple JavaScript configuration
- clean URL routing
- automated navigation, pagination, directory, and tag index pages
- built-in syntax highlighting
- virtual content and templates (passed as strings)
- extendable function hooks
- use whatever client-side framework you like (or none!)
- fast site build and file watch rebuild
- full documentation at https://publican.dev/docs/
- starter themes at https://publican.dev/themes/
You can install Publican using npm: https://www.npmjs.com/package/publican
The code is available at: https://github.com/craigbuckler/publican
Also available for Publican:
- https://publican.dev/livelocalhost/ - a hot-reloading development server
- https://publican.dev/staticsearch/ - a search engine for any static site
All feedback is appreciated!

value: Show HN: Publican – an HTML-first static site generator for Node.js

author: ceeb


value: Dhavidh

value: Show HN: Made a tool that let customer retrieve live data and action on website

author: Dhavidh


value: rogutkuba

value:
Hi HN,
I built CoderScreen, the open-source platform for live coding interviews and coding assessments.
Most existing tools in this space (like CoderPad or HackerRank) feel like they’re built for enterprise sales teams, charging thousands per year for something that should be fast, simple, and developer-friendly.
Key Features:
- Real-time collaborative code environment
- Fast, sandboxed execution in 10+ languages
- Entirely open-source and self-hostable (on Cloudflare)
Coming Soon:
- Web development environments (React, Vue, etc)
- Coding assessments
- Take home projects
I’m actively looking for teams to try it out, give feedback, and help shape what comes next. If you're hiring engineers or have thoughts on what’s missing, I’d love to hear from you.
Try it: https://coderscreen.com
Give us a star: https://github.com/Coderscreen/coderscreen
Thanks,
Kuba

value: Show HN: CoderScreen, an open-source alternative to CoderPad and HackerRank

author: rogutkuba


value:
I'm Craig Buckler and StaticSearch is my simple client-side only search engine for any static site (such as those created by Publican - https://publican.dev/). An example can be seen on https://publican.dev/ - click the search icon or press Ctrl|Cmd + K.
Static sites cannot easily provide search facilities because there's no back-end framework, language, or database...
You can use third-party services such as Alogia, AddSearch, or Google's Programmable Search Engine. These provide a search API, but often have a cost and can take a while to index.
JavaScript-only options such as Lunr require you to pass all content in a specific format. Every page then has a full index of your site, so payloads can become large as your site grows.
Pagefind analyses your built site and creates WASM binary indexes. But it requires some HTML configuration, uses considerable JavaScript code, and causes Content Security Policy issues.
StaticSearch is a simpler option. It:
- can use npx so there's no installation
- quickly indexes built pages and adds them to your static site (like Pagefind)
- requires no special HTML markers
- respects robots.txt and meta tag settings
- generates pure JavaScript and JSON files
- is easy to add to your site using a native web component
- includes options for custom search facilities
- is vanilla JS compatible with all frameworks
- has a tiny payload (13Kb of JS and 4Kb of CSS at most)
- incrementally loads index data on demand and caches in the browser
- determines when new word indexes are available.
npm: https://www.npmjs.com/package/staticsearch
Github: https://github.com/craigbuckler/staticsearch
Full documentation: https://publican.dev/staticsearch/
All feedback is appreciated!

value: Show HN: StaticSearch – a simple search engine for static sites


value: tanduorou

value:
Hi! I made a website about blockchain history.
You know how we use phones to pay for things? Blockchain is the echnology that makes digital money safe.
My website tells this story from 1970 to today. It's like reading a story book!
What's cool:
- Easy words that anyone can understand
- Works in English and Chinese
- 13 short chapters
- Dark and light themes
- Clean and simple design
I made it simple so kids and adults can both learn. It shows how smart people invented new ways to keep our digital money safe.
The website is easy to read and perfect for students and teachers who want to learn about blockchain!
What do you think? Is it easy to understand?

value: Show HN: Learn Blockchain History – Simple and Fun

author: tanduorou


value: StanMakesThings

value: Hey, I'm Stan and I made a app called Contestit. It's a social media giveaway app that let's users create giveaways. It gives the user a link they can share to their followers. What I always disliked or found annoying about giveaways is the fact that they were all the same, here's the prize. All you got to do is like, follow, and comment to be entered. That always bored me so i wanted to make it more interactive. Here's how it works: Users still get a shareable link for their giveaway, but after people sign up, they can play games to earn more entries instead of just waiting around. Right now there are three game types:<p>-Daily spin wheel (self-explanatory)<p>-Custom trivia contests (creators set their own questions)<p>-Photo contests (either "best photo wins" judged by the creator, or points-based where more engagement = more entries)<p>The photo contest is my personal favorite. If you got any ideas for some games i could add let me know. :)

value: Show HN: Contestit.app – Social media giveaways with games

author: StanMakesThings


value: Fiblet

value:
I wanted to introduce Fiblet—a specialized platform built to elevate your customer support and internal communication through intelligent email workflows.
With Fiblet , Groww can get benefit from:
1. Automatically classify emails by topic, which appears as a tab on the top of the dashboard.
2.Topic-based email filtering: Easily view emails related to specific subjects by clicking on topic tabs
3. Prioritize urgent or time sensitive emails.
4. Each team can handle their relevant topics.
5. Get topic wise email volume analytics to identify consumer behaviour and trending issues
6. Auto- reply to common queries using predefined FAQ templates and skip repetitive conversations
7. Helpful for audits, compliance and historical search
8. Smarter planning with data- use topic trends to improve products,services and customer experience.
9. Maintain a clean and organized inbox .

     If you're open to exploring how Fiblet can fit into your current workflow, I’d be glad to share a quick demo.

Best regards,
Sachin Sharma Founder, Fiblet
Contact me via email - ss2256387@gmail.com

value: Show HN: Fiblet- We replaced chaotic inbox into smart tabs

author: Fiblet


value: zchmael

value:
Hey HN,
I’m Zack, CEO at Averi AI, and we just released Synapse, a modular AI architecture we built to solve a problem we kept running into within the marketing ecosystem:
“How do you get domain-specific intelligence without trying to recreate GPT-4 from scratch?”
The Problem
Most domain-specific AI tools (marketing, legal, ops, etc.) tend to fall into one of three camps:
Use GPT-4/Claude as-is and rely on prompt engineering
Train a small model from scratch but lose general reasoning
Go full frontier model… and burn millions trying
We’ve considered all three. None hit the mark.
Our Approach: Multi-Model + Human Routing
Synapse is our attempt at something better:
A routing architecture that matches tasks with the best resource whether that’s an LLM, a smaller domain model, or a vetted human expert
A way to balance specialization and scale, instead of choosing one
It powers our own domain-specific foundation model (AGM-2), and integrates GPT-4, Claude, and others alongside it. Tasks get routed based on complexity and type.
For example:
A quick product description → routed to AGM-2
A cross-channel campaign brief → goes through Strategic Cortex + GPT-4
A nuanced brand tone rewrite → routed to a human expert
Under the Hood
Architecture:
Synapse is structured around 5 specialized cognitive modules (we call them cortices):
Brief Cortex: Disambiguates messy requests
Strategic Cortex: Maps business goals to tactical plans
Creative Cortex: Writes content tuned to brand voice
Performance Cortex: Weighs historical campaign data
Human Cortex: Escalates to our expert network when needed
Routing Logic:
Dual-track complexity scoring: LLM + heuristic analysis
Tasks run in one of 3 “modes”: Express (quick), Standard, or Deep (multi-stage, may call a human)
Results fed back to improve future routing decisions
Training Data:
AGM-2 was trained on over ~2M marketing artifacts (positioning docs, campaigns, A/B test data, etc.)
We licensed real performance data and layered in structured messaging frameworks. It’s not the biggest model, but it’s trained with domain-native intent.
What Makes This Different
Rather than trying to force one model to do everything, Synapse behaves more like a strategist. It knows when to go fast, when to go deep, and when to ask for help.
We’ve been running it in production for 3+ months.
It’s shown strong gains in:
Brand tone consistency vs. GPT-4-only setups
Time-to-launch on full campaigns
Quality of briefs when humans are looped in
Try It + Read More
Demo (mention you're from HN and we'll get you right in): https://www.averi.ai/demo-sign-up
Technical overview: https://www.averi.ai/blog/averi-launches-synapse-a-new-ai-sy...
Open Questions We’re Exploring
Specialist vs. generalist tradeoffs — When does our domain-trained AGM-2 outperform GPT-4? When doesn’t it?
Human-in-the-loop scaling — How do you decide when to escalate to a human? We use ML for this but would love to hear other approaches.
Training data — What’s the right mix of public vs. proprietary when building domain-specific datasets?
Would love feedback from anyone building domain AI systems, orchestration layers, or multi-agent workflows. AMA on routing logic, model behavior, or anything else.
Thanks!

value: Show HN: Synapse – Multi-model AI combining LLMs and humans for marketing output

author: zchmael


value:
I was so excited to see "Enough AI copilots! We need AI HUDs" (https://news.ycombinator.com/item?id=44705445)
Not specifically because of the AI perspective, but because of the broader recognition that we need better development tooling. I spend a lot of time thinking about how developers work, reason about and mentally model software. I was specifically excited because of the example "HUD" that Geoffrey chose to share: "A custom debugger UI which visualized the behavior of my program".
Yes, please, I agree. That type of code flow interface should exist everywhere. So *I built one*. Ruby is my pilot language, but more will come later.
Code Beacon is a VS Code extension that analyzes and displays tracing data from a Ruby tracer gem. At its core, it filters non-application traces and rolls up the raw trace to a much smaller call graph so you can easily see and navigate to what files/classes/methods got run and how they interact.
It's not finished at all, but it's a start and it should mostly work. If it doesn't and you want to let me know, I'll fix it. It doesn't work in containers, it's not in all marketplaces yet, it will fall over if your call trace exceeds 10MB, and it could be a lot more performant. The UI/UX needs refinement and I'm sure there are plenty of bugs and edge cases to address.
I would love to hear your thoughts!

value: Show HN: Code Beacon – filter files and show call graphs in Ruby


value: pzullo

value:
Hey Pietro and Luigi here, we are the authors of mcp-use (https://github.com/mcp-use/mcp-use).
When the first MCP servers came out we were very excited about the technology, but as soon as we wanted to get our hands dirty, we found out that MCP could be used only through Claude Desktop or Cursor. As engineers, we did not like that. MCP seemed like something you wanted to use to build products and applications yourself, not something to hide behind a closed source application.
So we approached the SDK but were pretty dissatisfied with the developer experience (double async loops, lots of boilerplate). We decided to write mcp-use to make our lives easier.
mcp-use lets you connect any LLM to any MCP server in just 6 lines of code. We provide a high level abstraction over the official MCP SDK that makes your life easier and supports all the functionalities of the protocol.
Demo video here: https://www.youtube.com/watch?v=nL_B6LZAsp4.
The key abstractions we provide are called MCPClient and MCPAgent.
MCPClient takes in a set of server configurations, automatically detects the transport type and creates a background task which handles the stream from/to the server.
MCPAgent is a combination of the MCPClient, an LLM, and a custom system prompt. It consumes the MCP client by transforming the tools, resources and prompts into model agnostic tools that can be called by the LLM.
The library also contains some cool utilities:
- secure sandboxed execution of MCP servers (we know the protocol doesn't shine for security)
- meta-tools that allow the agent to search over available servers and tools (to avoid context flooding) and connect dynamically to the server it needs (you could create the omnipotent agent with this).
Some cool things we did with this:
- write an agent that can use a browser and create/read linear tickets updated with latest information on the internet
- write an agent that has access to the metrics of our company to automatically create weekly reports.
- I connected an agent to an IKEA curtain I hacked an MCP on to adapt the lighting of my room from images of the lighting situation.
- recreated am open source claude code like CLI, with full MCP capability but with custom models and BYOK (https://github.com/mcp-use/mcp-use-cli).
We recently crossed 100,000 download and we are used by many organizations, including NASA!
We’d love to hear what you think of it, most importantly how we can improve it! We are happy to answer any questions and look forward to your comments.

value: Show HN: Mcp-use – Connect any LLM to any MCP

author: pzullo


value: melvinzammit

value:
I have never smoked myself, but I know a lot of people that smoke and want to stop. This is for them. While researching the topic on various peer reviewed papers I was impressed how many parts of the body heal when a person quits smoking. It’s impressive that the body starts healing in the first 20minutes! This is why the app features a ‘heart avatar’ that heals with time reflecting the person’s journey.
Something which i think is very important if i had to use an app like this is privacy. This is why I kept all the data in a local database inside the app and never share or track any data. there is also no account, so its 100% private.
If you smoke and wish to quit feel free to try it and I really appreciate any feedback! Thanks

value: Show HN: If you smoke, this app helps you quit (no shame)

author: melvinzammit


value: malshaik

value:
Hey HN! My name is Mohammad, and I'm the founder of SEOLabs.
I built this after failing 3 startups with the same problem: zero distribution plan.
You can see the story here: https://www.youtube.com/watch?v=cIgGocOEm_I
Most SEO tools cost $300+/month and are built for agencies, not bootstrapped founders. They're complex and assume you have a marketing team.
SEOLabs uses AI to automate keyword research and content planning at founder-friendly pricing. Find low-competition keywords, get content plans, and actually rank on Google.
How it works:
Enter your product/niche
AI finds keywords people search for
Get automated content plans
Ship content that ranks
Takes minutes instead of hours of manual research.
We're launching in 10 days. Currently accepting waitlist signups.
Would love to hear what the HN crowd thinks!

value: Show HN: I made an AI powered SEO tool so that you never launch to 0 users again

author: malshaik


value: stelcodes

value:
I've created and open-sourced an Astro developer blog template with an interactive theme changer that includes all 60 themes bundled with the JS code highlighter Shiki. Changing the theme affects the whole website including the code examples and Giscus comments. Inspired by the aesthetics of raw markdown, I wanted to create a beautiful blog like https://github.com/panr/hugo-theme-terminal but supercharged with a modern redesign and the incredible features of Astro.
Features:

  - Simple configuration file
  - Multiple theme modes (single, light/dark/auto, select)
  - Giscus comments
  - RSS feed
  - SEO best practices + social card generation
  - Markdown extensions (TOC, admonitions, reading time, etc)

value: Show HN: Astro dev blog template with interactive colorschemes

author: stelcodes


value: stagas

value: Show HN: Pairfonts – A web application for pairing Google Fonts

author: stagas


value: wxhrO

value: Satirical song about Astronomer's CEO and HR chief resigned following a viral Coldplay concert incident, prompting leadership changes and a company commitment to uphold professional conduct.

value: Show HN: Astronomical Mistake – The Song

author: wxhrO


value: zacattk

value:
At every company I’ve worked at, people waste time asking around just to figure out who the right person is to talk to. Org charts are outdated, Slack threads get buried, and tribal knowledge stays siloed.<p>So I built Dark Matter — an AI-powered internal search tool that helps you instantly find experts across your company based on skills, experience, and responsibilities. Just ask it like you’d ask a coworker:
“Who can help with video production?” or “Who’s worked with Salesforce integrations?” — and it brings you the right people.

value: Show HN: Why Is Finding Internal Experts So Hard? I Built an AI to Change That

author: zacattk


value: Looking for early members to join Relay's network

value: Show HN: Relay – AI Agent that helps you connect with the best people


value: airjason

value:
Hey HN,

  We built an Airbnb data API because we were tired of the unreliable and expensive options out there.

  Our goal was to make it fast, cheap, and easy for developers to get the data they need.

  We're seeing people use it to build property management tools, fuel investment models, create rental calculators, and analyze tourism trends.

  Check it out:
   - general: https://www.airroi.com/api
   - See docs: https://www.airroi.com/api/documentation

value: Show HN: Airbnb API, powerful and developer-friendly

author: airjason


value: kptbarbarossa

value:
Hey HN
I’ve been building a small tool called *Validationly*. It's designed to help founders and indie hackers validate their startup ideas before writing a single line of code — by checking what the internet is already saying.
The concept is simple:
You type in your idea (e.g. “AI meeting assistant”) and Validationly pulls related signals from *Reddit*, *Twitter*, and *LinkedIn*, then analyzes the volume and tone to generate a *“validation score.”* You also get a quick snapshot of trending discussions, pain points, and real user language around the idea.
What makes it useful:
- No more guessing if your idea is “worth building”
- Helps avoid the build trap before you spend weeks coding
- Bonus: It even drafts a *tweet* and a *Reddit post* based on your idea — ready to share for feedback
I built this after running into the same loop: idea → excitement → build → launch → silence. So instead, I wanted a way to quickly test if anyone was already talking about a space — and if there’s real demand.
Live here: [https://validationly.com](https://validationly.com) (no login needed)
 Ideal for: indie makers, early-stage founders, solo builders
Still in early stages, looking for *feedback, brutal honesty, or ideas* on what you'd want next.
Thanks for checking it out!
– Built by a no-code maker who prefers flow over friction

value: Show HN: Validationly – Validate Startup Ideas via Reddit, Twitter and LinkedIn

author: kptbarbarossa


value: denchikceo

value:
My friend and I recently launched Roomsy - a simple app to track and schedule household chores.
We wanted to quickly test the niche of home cleaning trackers, so we built an MVP in about a month. It’s far from perfect, but it works - and we’d love any feedback or ideas.
If you want to try it out:
– On the App Store, use promo code SPARKLE2025 to unlock 1 year free (enter it on the paywall screen).
– On Google Play, there’s a 1-year free trial currently available.

value: Show HN: We built Roomsy – a better way to manage household chores

author: denchikceo


value: hitchyhocker

value:
Hi HN, I'm Ethan, founder of Tight Studio. (As Tuco said to Heisenberg - Tight tight tight)
I'm excited to introducte Tight Studio 1.0 - the easiest way to prepare impressive screen recordings.
Now publicly available at http://tight.studio/.
Tight Studio 1.0 features:
* one-click smart captions - lots of people play video on social media without sound on. We greatly simplify this for you with one-click auto captions, filler words removal, and simple editing tools if needed.
-> comparing to existing solutions, we allow you to generate captions much more easily and edit them easily if needed
* smart auto zoom-in - without auto zoom-in, audience could lose details on what you are trying to highlight, this is especially true when you want to highlight small texts within a large screen
* common video clipping and style customization tools to polish your screen recordings.
We are also offering 50% early supporter discount for the first 100 subscribers, you will get 50% discount for lifetime for Tight Studio screen recorder!
We are shipping quickly at tight quality, and we have much more to come on the roadmap. We would also love to incorporate any feature request you may have, please let me know!

value: Show HN: Tight Studio – impressive screen recordings made easy

author: hitchyhocker


value: mandarwagh

value:
This video was generated by NOTEBOOKLM from the research paper
paper link:https://arxiv.org/pdf/2507.07935

value: Show HN: Microsoft research on impact of GenAI on jobs

author: mandarwagh


value: I open-sourced this tool to generate colorful waveform images from audio files, inspired by Pioneer/Denon gear. No FFT required, just filters and peak windows.

value: Show HN: DJ-style audio waveform thumbnailer in Python


value:
Hi HN, Dylan and Shima here. Today we're launching the first version of our project, Safe Rate, an AI-native mortgage lender going all in on the chat experience, at saferate.com.
Mortgage shopping is an uncomfortable experience.  You have to share lots of sensitive data to get a single quote, and if you want to comparison shop, the rate aggregator websites straight up sell your data, so you end up with a lot of texts, emails, and phone calls from salespeople you've never met asking you to blindly trust them with a big financial decision.
Getting a mortgage quote should be on your terms. You should be able to share your relevant details anonymously and get real pricing.  You should know how competitive the offer is before speaking with someone.  And you should still be able to connect with a human if you need support.
So we've built a suite of tools in our AI chat to put shoppers in control:
1. Instant mortgage quoting without sharing any sensitive data (currently live for conventional loans in Illinois)
2. Automatically review a Loan Estimate, which every lender must provide you by law, and see how the estimate scores (0 to 100, benchmarked against 2 million loans).  We then can make an instant competing offer so you know if we can save you money.
3. For refinances, share a mortgage statement to see if you can save money today, and if not, create a personalized tracker so you can be notified when rates have fallen
4. Mortgage Q&A for commonly asked mortgage questions.  Still lots more to add!
5. Live - a Zoom-like call for mortgage shopping that instantly connects you with a loan officer while our AI assistant listens in, updates the quote details, and gets you pricing
We support this functionality in a variety of ways:
1. Chat on https://saferate.com
2. Email at buddy@saferate.ai
3. Live via our Zoom-like call tailored to mortgage shopping
4. Slackbot (please ask if you're interested in access)
5. Phone 1(888)850-6123
6. Coming soon RCS, SMS, and WhatsApp
Our chats are universal, so you can start with email and then transition to web chat, or vice versa, and it will retain the full context.  And we've built our chat to be embeddable on any other website via an iframe.  Safe Rate's main chat is actually an embedded iframe itself. And because we can't be wrong when giving a mortgage quote (regulation!) we've designed our AI so it does not hallucinate.
Here’s a 90 second demo video that shows this in action: https://youtu.be/6eIJukspmfU
You can also see a sample Live session: https://youtu.be/alAPtjUJ5xE
We're posting here today because any testing or feedback would be a great help.  We're able to join the Live Call if you're brave enough (in addition to building this system ourselves, we're also licensed loan officers).  And our quotes are only valid for Illinois with a max loan size of $806,500. We hope to expand nationally soon.  Thanks!

value: Show HN: SafeRate – AI chat-native mortgage lender


value: Tonje

value:
Hi HN! Going to meetups or conferences?
TL;DR: We’re building an AI tool that helps you capture leads, keep track of key details, and follow up fast starting with in-person events.
We’re Tonje and German, and we’re building Moots AI, a smart contact system for sales teams, founders, investors, recruiters, and partnership managers who rely on real-world events to meet leads, close deals, and build relationships.
Our first focus: make sure no contact or lead from a conference, summit, or meetup slips through the cracks.
The Problem: Most networking events are a waste.
You meet dozens of valuable people but the context fades fast, and follow-ups are often delayed or forgotten.
If you’re in sales, fundraising, or biz dev, missed follow-ups = lost pipeline.
- 80% of leads generated at trade shows are never followed up.
- 35-50% of sales go to the vendor that responds first after an event.
- Companies that follow up within 48 hours see a 25–50% higher conversion rate.
- After 2–3 days, interest drops sharply especially for leads from in-person events.
You’ve probably lived this:
You show up early, set up your booth, and wait while everyone’s in talks. Then suddenly, right after a session ends, the crowd rushes in.  You're juggling five conversations at once. No time to scan badges. No time to take notes.  After the event, it's a blur.
You vaguely remember someone from Minneapolis who mentioned tennis and his kid… but who was it?  Your lead capture tool didn’t save their name, photo, or context. That opportunity? Gone.  Customer? Partner? Hire? You don’t remember and you can’t follow up on what you’ve forgotten.
Ever bump iPhones with someone at an event then forget who they were the next day?
When someone shares their number by bumping iPhones, you’re left with a contact buried in your phonebook—no notes, no context, just a name and a number.
Our Solution: AI that captures and activates your relationships
Moots turns live conversations into rich, actionable contact profiles.
Scan a badge or card → Moots instantly builds a profile with job title, company, LinkedIn, education
It transcribes the conversation, tags key details, and qualifies the lead
It helps you prioritize follow-ups, suggests next steps, and can draft outreach for you
It even surfaces on the fly, contacts in common,  shared interests, or past locations to help you connect with context
Every person you meet becomes part of a searchable, AI-powered personal network.
Your AI agent remembers everything so you can focus on building relationships and closing deals.
Demo: https://youtu.be/tkC1DCQzHcY?si=Vlu-5TEUNXWyE09K
What Moots does today
- Scan lead badges or business cards at events
- Auto-enrich contacts with public info (title, LinkedIn, company, education)
- Dictate and attach notes to the right contact
- Qualify and categorize leads
- Search your network by event, tag, or date
- Draft follow-ups
- Build a private, living knowledge base for each contact
Our Team
Tonjé Bakang Tonje (CEO) – Previously founded Afrostream (YC W15), a media platform that reached millions. Former VC and dealmaker in Europe.
German Saprykin (CTO) – Engineering leader with deep experience in AI infrastructure and consumer-scale systems. Previously at Grab.
We just launched, download Moots AI on the App Store:
https://apps.apple.com/us/app/moots-ai/id6717572977
We’re always learning. Feedback is gold. Tell us how we can better support your business and your relationships.
Tonje & German

value: Show HN: Moots AI (YC W22) helps you turn meetup contacts into deals

author: Tonje


value: ntahami

value:
Hey HN,
I’m a solo builder, and I made Brandkiit after getting stuck too many times trying to name and brand new ideas. I’d get excited about a side project, but before I could start building, I’d lose days (sometimes a whole week) trying to find:
• a name that felt right
• an available domain
• a decent logo
• matching colors and fonts
…all before I wrote a single line of code.
Brandkiit is a tool that takes your idea and instantly gives you a full brand kit — including:
• name + domain availability
• logo
• color palette
• font pairing
• CSS file export you can send to your favourite code tool
It’s meant to help indie hackers, designers, and product folks get started without getting stuck in the branding spiral.
Would love your feedback!
Happy to answer any questions.
Nima

value: Show HN: I built an AI brand generator to stop wasting days naming side projects

author: ntahami


value: orsobi

value:
I've been an OmniFocus user for years but always felt something was missing – I could capture everything but couldn't see the bigger picture of my work. Traditional task managers are great at collection and to do lists but I think they don't solve the problem of  visualising and managing work.
*What It Does*
Flowcus is a macOS app that visualises your OmniFocus, Apple Reminders & plain text tasks as a customisable Kanban board. It's not intended to replace your task managers, rather it enhances them by providing:
- Visual workflow with customisable columns and swimlanes
- Drag-and-drop task management that syncs back to your original task managers
- Work-in-progress limits to prevent overcommitment
- Eisenhower matrix view for prioritising important vs. urgent work
- Ability to mark tasks as blocked and visualise dependencies
- A unified view of tasks from multiple platforms
- Throughput & ageing work metrics
For example, you might have research tasks in OmniFocus, meeting reminders in Apple Reminders and basic tasks in plain text. Flowcus shows them all on one board, letting you drag tasks from "In Progress" to "Done" and having that status change sync back to the original app.
## Why It's Useful
Traditional task managers aren't great at showing you a holistic view of your work. Flowcus bridges this gap by applying lean thinking principles to personal productivity:
1. *Makes work visible* - See all your tasks in one place across different stages
2. *Limits work in progress* - Stop starting, start finishing with WIP limits
3. *Manages flow* - Identify and eliminate bottlenecks in your workflow
4. *Provides feedback* - See how work moves through your system over time
For OmniFocus power users, Flowcus adds the visualisation layer that's always been missing. For people juggling multiple task systems, it unifies your tasks without forcing you to use multiple apps. That's the idea anyway...
## How I Built It
I started with Python scripts to extract OmniFocus data, but realised I needed proper two-way sync and a native Mac experience. I used Claude Code to help me build the first version to integrate with OmniFocus's AppleScript interface and Apple Reminders' EventKit framework. The app monitors changes in real-time and propagates updates back to the source systems. The first prototype was rough but I could see the benefits straight away: I could visualise my work, arrange it into swimlanes, identify when I was overcommitting and track the flow of work across different stages.
## Current Status
The app is currently in beta (v0.2.5). I use it every day to help me manage my work. I can't do without it now. I'm considering adding more task manager integrations at some point. I'd love feedback from any fellow productivity geeks and OmniFocus users – thanks!

value: Show HN: Flowcus – Kanban Board for OmniFocus and Apple Reminders

author: orsobi


value: rocknrollisdev

value:
Hey HN! I’m the founder of Patio and I’m excited to share our newest beta feature: Ask. It’s like Perplexity, but focused entirely on DIY and home improvement.
What it does:
Instant answers to your home improvement questions ("How do I weather-proof a deck?")
Curated how-to articles from top DIY sites
We built this because we hated hunting through dozens of tutorials to find one clear answer. Ask brings everything into a single, conversational interface—no more context switching between blogs and videos.
Would love your feedback
- Does it understand your DIY questions?
- Are the suggested articles relevant and high-quality?
- What features would make it indispensable for your projects?
Thanks for checking it out—looking forward to hearing what you think!

value: Show HN: Patio Ask, a Perplexity-style DIY home improvement assistant

author: rocknrollisdev


value: akhilcjacob

value:
Hi HN,
I built HypeBridge to fix influencer evaluation for brands. Our system creates “Carfax-like” vetting reports to pick authentic influencers fast.
Why?
Bad influencers with fake followers waste 70% of brand budgets. Manual vetting is a nightmare. We use AI to analyze content, engagement and audience fit, saving time and money.
Delivers instant reports (authenticity, engagement, red flags)
Tech: Next.js, Gemini, Firebase
Check it out, let me know what you think: thehypebridge.com.

value: Show HN: TheHypeBridge – AI-Powered Influencer Vetting Reports for Brands

author: akhilcjacob


value: rdrob

value:
Hi HN,
We just launched the free tier of Reality Defender, our deepfake detection platform. It lets you programmatically analyze images and audio to detect AI-generated content using our SDK.
The free tier includes 50 credits per month, no credit card required. You get back a confidence score via the API.
We also support detection for video and text, as well as integrations with Zoom, Teams, and contact centers for real-time audio and video — happy to talk more if you're working on those.
You can get started here: https://app.realitydefender.ai and read more about a Slack use case here: https://dev.to/manuel_abeledo/building-real-time-deepfake-de...
Would love your feedback.

value: Show HN: Reality Defender – Free Tier for Deepfake Detection in Images and Audio

author: rdrob


value: yiyingzhang

value:
I'm the co-founder of GenseeAI (https://www.gensee.ai). We've recently launched the public beta of Gensee, an AI agent/workflow platform oriented for developers and small teams.
Here’s what I’ve heard again and again: it's gotten much easier to build a proof-of-concept AI agent, but turning that prototype into a high-quality, scalable, and cost-effective product is still a massive chore, involving endless trial-and-error with prompts, models, tools, testing, analysis, etc.
We built Gensee to automate that "last mile" from prototype to production.
Here’s how it works:
- You provide the GitHub link to your project, a Docker image, or a Zipped package of your agent source to Gensee. They can be written in any framework or without a framework, as long as it’s in Python. No code modification or annotation needed.
- We handle input/output identification, model/tool call identification, test case generation, metrics generation, testing, automated optimization, server provisioning, containerization, tool/model calling, and endpoint creation to get it live as an API.
- You see detailed evaluation results with customized metrics and test cases, all fully automated.
- We optimize your agent automatically to achieve better quality, cost, and/or latency. You can download our optimized agent code, all transparent.
- You can choose any optimized or original agent configurations to serve. Simply copy the API endpoint to your frontend code calling the agent.
To support fellow developers, we give every new user 500 free monthly credits, enough to cover one to two agent deployment, optimization, and initial model and tool usage costs. If your usage grows, it becomes a cost-efficient pay-as-you-go service that scales with you.
We're still in beta and would love to get your feedback. Do you prefer no-code agent generation instead of source code uploading? Should Gensee also run your frontend and other code in addition to agents? Any other optimization goals you have? Any key missing features?
Thanks for taking a look!
Access Gensee: https://platform.gensee.ai

value: Show HN: Gensee – Free AI Agent Optimization and Deployment

author: yiyingzhang


value: averadev

value:
Hi HN,
If you're building a product — whether it's a SaaS, app, or startup — you know how crucial it is to listen to your users and build what they actually need. But feedback often ends up scattered in emails, chats, or lost in your memory.
That’s why I built Fidbaq: a simple (and free) app that helps you collect, organize, and prioritize user feedback — all in one place.
- Users submit ideas, bug reports, or suggestions
- Others vote so you know what matters most
- You build with confidence, based on real demand
Try it here: https://www.fidbaq.xyz
Would love to hear your feedback or ideas to improve it.
— Agustín

value: Show HN: I built simple free app to collect user feedback and build what matters

author: averadev


value: johntawfik

value:
Hi HN,
Most of our attention today is hijacked by short-form content on apps like TikTok and X. There's growing evidence this contributes to cognitive decline (https://pmc.ncbi.nlm.nih.gov/articles/PMC11236742/) and is only going to affect more people as video generation models advance.
One of the best ways to combat this is by reading more books. I built blen to help myself do this, and figured other people might want to join me.
Blen is a minimalistic PDF e-reader with a clean interface, bookmark and search features, and automatic progress tracking. Just put blen.ink/ in front of a url to a PDF of your favorite book (eg: blen.ink/https://www.sausd.us/cms/lib/CA01000471/Centricity/Domain/24...) or add the link within our interface.
There are no sign-ups, no paywall, no collection of your personal data, and blen will always be free.
I hope it helps you read more. I’d love any thoughts, feedback, or feature requests!

value: Show HN: Blen – A Minimalist EReader to Help You Read More Books

author: johntawfik


value: delduca

value: Show HN: Carimbo, a 2D game engine written in C++23 using SDL, featuring Lua

author: delduca


value:
EIRA-KEM is a symbolic algebra-based key encapsulation mechanism (KEM) designed for post-quantum cryptographic applications.
It uses symbolic entropy matrices, SHA3-512 + HKDF, and AES-GCM encapsulation to achieve IND-CCA2 security without relying on LWE, factoring, or ECC.
Resources : https://www.researchgate.net/publication/394065098_EIRA-KEM_...
https://www.researchgate.net/publication/394088076_EIRA-KEM_...
GitHub: https://github.com/CarlosStx99/EIRA_KEM3
 Google Colab Demo: https://colab.research.google.com/drive/YOUR_LINK_HERE
I'm looking for technical feedback, crypto analysis, and collaboration from the community.
This system is patent-pending (WO/2025/057369) but free for academic testing.
Benchmarks (C + Python), whitepaper, and license included.

value: Show HN: EIRA-KEM – a symbolic post-quantum KEM for academic testing


value:
Hi HN,
Just a quick update — FakeFind is back online.
We originally built FakeFind to help people spot fake reviews after Fakespot shut down. It scans product reviews on Amazon, Walmart, eBay, and others using AI to detect patterns like repetition, review hijacking, and mass posting. You get a Trust Score, an Adjusted Rating, and a short review summary so you know what’s real before you buy.
It’s browser-based, free to use, and doesn’t require installing anything.
If you tried it during our downtime — thanks for your patience. We’d love feedback from the HN community as we keep improving.
For those who are interested: https://fakefind.ai

value: Show HN: FakeFind is working again – AI tool to detect fake reviews


value: joaomeloplus

value: Show HN: Calystone – privacy-first note- & task-mnger that works with your files

author: joaomeloplus


value: siim

value:
Earlier this July, I had a rare week to focus, so I built a tool that let you call in, speak your idea, and schedule a Twitter post. My background is in voice tech, which gave me an intuition for how these systems work. In a three-week window, I launched that voice-first version, playing with ElevenLabs to make it happen.
After launch, I didn't get much traction. One fan from X tried it out and suggested having a UI for editing posts before publishing. I realized that pure voice wasn't enough.
Last week, I figured that a chat-based, cursor-like interface would be cool, so I quickly shifted to that. Now, X11.social lets you start with a voice brain dump or typed text, then edit and polish your posts before sending them to X.
I'm still absolutely figuring out the market here. With no marketing background, I started posting some video logs to X and just documenting the journey. I've met many interesting people during this journey in such a short period.
If you're interested in creating authentic posts for X without overthinking, I'd appreciate any feedback.
By the way, X11 is not that X11 protocol from the old days. "X" is for the platform, "11" is a nod to voice AI, originally inspired by ElevenLabs. I'm building custom voice infrastructure nearly done!, but kept the name - it just fits the "call to tweet" vision.

value: Show HN: I built a voice-first tool for Twitter, pivoted to cursor for X

author: siim


value: Conceived to put an end to petty online debates that consume too much time and energy.

value: Show HN: Factitio.us – Generate authoritative links to put arguments to rest


value: Show HN: If Pocket and Spotify Wrapped had a baby


value: pmbanugo

value:
WHat if you could take Node.js event emitter and turn it into a distributed pub-sub system?
I built Demitter to solve a problem I kept thinking about recently: how to easily share events between Node.js processes without the complexity of setting up Redis, RabbitMQ, or other heavyweight message brokers? It uses ZeroMQ for messaging and MessagePack for serialization, ensuring high performance even at high event frequencies.
What it does:
- Takes the familiar `emitter.on()` and `emitter.emit()` API you may already know in Node.js
- Makes it work seamlessly across multiple processes/machines
- Zero configuration required: just `npm install demitter` and go
Don't take my word for it, see it in action:
I created a live auction demo where multiple bidders run in separate terminal windows, all bidding in real-time on the same auctions. Watch it in action: https://www.youtube.com/watch?v=LqQShQ9-dsk – it's pretty satisfying to see ~7 processes staying perfectly synchronized in real-time.
Where I you might use it:
- Worker processes needed coordination without complexity
- You want to scale Socket.IO or WebSocket servers without heavy message brokers
- any other need for pub/sub across Node.js processes.
I built this because I wanted a lightweight solution that didn't compromise on the familiar Node.js event API. Existing solutions felt too heavy for simple pub/sub, and I wanted to keep the Node.js event API developers already know.
I'd love to hear your thoughts on this approach. Is it something you would find useful? What other use cases do you think it could solve for you?
I'm in EU and it's very late here, so I'll catch up on comments tomorrow.

value: Show HN: Demitter – Distributed Node.js Event Emitter (Pub/Sub)

author: pmbanugo


value: eddieos

author: eddieos

title: Show HN: Demitter – Distributed Node.js Event Emitter (Pub/Sub)


value: scrollaway

value: Show HN: Play NYT Connections in the Terminal

author: scrollaway


value: Suedish

value:
Hey HN! I'm Mike, based in Stockholm/Sweden and I'm the founder of Zero Waste Cloud (https://zerowastecloud.io) - a tool that scans AWS and GCP infrastructure to find cost optimization opportunities while calculating the environmental impact. Almost all businesses can save 20-40% of their cloud costs using this tool (sources at bottom)
TLDR: Sign up -> Connect your AWS/GCP -> Scan -> Save 20-40% of your cloud spend.
My backstory: I've been a CISO and in IT management for a long time and always been frustrated by how much waste I'd find in every environment - idle EC2 instances running 24/7, oversized RDS databases, forgotten storage volumes, test resources that never gets removed. What also bothered me was that nobody was tracking the environmental cost of this waste. Every unused resource burns electricity and contributes to carbon emissions unnecessarily.
What it does:
- Scans AWS accounts using IAM roles or access keys, GCP projects using service account keys
- Identifies specific optimization opportunities: unused EC2/Compute Engine instances, oversized databases, unattached storage, missed reservation opportunities and much more
- Calculates financial savings AND CO₂ reduction for each recommendation using region-specific grid emission factors
- Multi-account/project support
- Generates detailed reports with prioritized recommendations
Technical details: Built with React/TypeScript frontend, Supabase backend. Uses AWS SDK for EC2, RDS, Cost Explorer APIs and GCP's Compute Engine, Cloud SQL, and Cloud Billing APIs.
Carbon calculations combine cloud provider PUE data with regional electricity grid emission factors from government sources.
Try it out: The onboarding from creation to your first scan being run is only ~30 seconds. The scanning process is fully automated and typically completes in 5-30 minutes depending on account size of course.
I would genuinely love to get your feedback on it, just came out of beta a few days ago so if there's any bugs around please do let me know =)
If you're on Linkedin let's connect: https://www.linkedin.com/in/almstedt/
Sources:
"companies estimate that 21-50% of their cloud expenditure is wasted" (https://www.techmonitor.ai/hardware/cloud/cloud-waste-hits-b...)
"45% of cloud customer’s expenditures are spent on resources they will never use" (https://www.sciencedirect.com/science/article/abs/pii/S22105...)
"21% of enterprise cloud infrastructure spend /.. / in 2025*—is wasted on underutilized resources (https://www.prnewswire.com/news-releases/44-5-billion-in-inf...)

value: Show HN: Zero Waste Cloud – Finds 20-40% savings in AWS/GCP bills and CO2 impact

author: Suedish


value: Jsuh

value:
Hey HN. We’re two friends that love reading. We have an enormous backlog of books, blogs, and research papers but often lack the domain expertise and time to get through it all.
So we built Bitter, an AI reader that helps us quickly understand complicated books and papers. We’ve found it incredibly useful for skimming through long books / papers but then diving deep into the parts that seem especially interesting.
Currently, Bitter lets you:
Upload a PDF or add any webpage/PDF through a URL
Highlight text for instant explanations
Click section headers to get a quick summary
Instead of a chat UI, the focus is on the content and the AI is integrated in more ambient ways. We’re more interested in “AI helps me as I read” rather than “AI reads for me”.
We’d love for you to try it out @ readbitter.com
Jeremy and Arnav
Here are some links to books/papers we’ve finally gotten around to reading:
The Beginning of Infinity: https://avalonlibrary.net/ebooks/David%20Deutsch%20-%20The%2...
Seeing like a State:
https://files.libcom.org/files/Seeing%20Like%20a%20State%20-...
The Era of Experience:
https://storage.googleapis.com/deepmind-media/Era-of-Experie...

value: Show HN: Read Faster with LLMs

author: Jsuh

title: Show HN: Read Faster with LLMs


value: ozten

value:
Friday's HN link "Steam, Itch.io are pulling ‘porn’ games. Critics say it's a slippery slope" had a large and divisive discussion.
I spent 2 days playing with automating a "live action talking animals" 90 second short 100% automated from that discussion.
The result is the YouTube link for this post.
---
Here is a more detailed breakdown:
Sunday night at 2am in the morning, I had a question and a wild thought.
Could I point Gemini Deep Research at https://news.ycombinator.com/item?id=44685011 and ask it to analyze
and reduce it into 5 - 7 personas and extract key quotes, themes, etc.
If it could, then I had the idea of generating a short social video illustrating
the discussion in a short 30 second video.
If I avoided curation, cherry-picking, and manual intervention... would it be any good? All effort went into prompts and context, not review or massaging.
I then spent Monday and Tuesday on the idea in a time-boxed spike.
I ended up with the following process:
- Gemini Deep Research, HN discussion produced the report
- Using the report, a Gemini Pro prompt output characters and the themes
- For each character, a Gemini Pro prompt chose an animal and described their character in detail
- Using the character descriptions and the themes, a Gemini Pro output a time coded script with actions, sound effect and dialog
- For each character, Gemini Pro produced an image prompt feed into Imagen 4 which output a character sheet with that character from multiple angles with all of their accessories and quirks
- With the script, Gemini Pro split it into scene files
- For each scene and character description, Gemini Pro with a JSON schema produced the video generation prompt
- For each scene and character sheet, Image 4 produced the first frame image for that scene
- Given the first frame image and the video generation prompt, Veo 3 produced an 8 second clip which includes voice, sounds, etc.
- Some dialog was longer than 8 seconds and required manual steps, such as using ffmpeg to get the last video frame and save to .png and use as the first frame in a second extension video
For LLM input / output, I used the first result.
For Image 4 I generated between 2 and 4 outputs and manually chose the best. In 100% of these samples either the first or the second was acceptable.
For Veo 3 I generated between 2 and 8 outputs and manually chose the best. Voice continuity was the biggest challange.
I originally had complicated plans for a 16:9 mobile ratio video where the screen would be broken up into 3 panels. Tuesday at 2pm, I abandon this and went with a simple linear approach. I slapped things into iMovie and got it done.
I was impressed with Gemini Pro 2.5's ability to understand the 3-slot and use the verticality in it's directions. It had characters looking up and down like in Hollywood Squares.
This experiment was as minimally "Cherry Picked" as possible. I'm impressed with the quality of the LLM, image, and video generation output.
Lastly, I had forgot to have the LLM art direct the opening and last frame, so I made some stuff up and finished the project.
I learned a lot and this was a fun experiment. It was a mixture of automation and manual steps. When I did this, you could not automate Imagen 4 with a character sheet, nor Veo 3 with frame to video. Each of those I had to manually use Whisk and Flow (their respective UIs).
I wrote 5 scripts. I ended up with about 142 artifacts (input and output files).

value: Show HN: Experimental HN Discussion to Animated Video Pipeline

author: ozten


value: gurachek

value:
I've been through 50+ technical interviews as both a candidate and an interviewer. The current system is broken: we memorize algorithms we'll never use while real job skills go untested.
Prepto.tech generates interview questions directly from job descriptions using AI. Paste a JD, get relevant technical questions, practice with flashcards & deep focus mode. Not generic prep – study what they'll actually ask.
The goal: shift interviews from "can you reverse a binary tree?" to "can you build what we need?"
Demo: https://www.youtube.com/watch?v=t0oiCcAlqFs
Try it: prepto.tech
Built with Vue.js + Laravel. Feedback welcome.

value: Show HN: Prepto.tech – Interviews are simple with AI (no cheating)

author: gurachek


value: devxiyang

value:
Hi HN,
I built ChangeImageAspectRatio.com – a simple tool to change an image’s aspect ratio (e.g., from 4:3 to 16:9) without cropping or stretching.
It’s useful for preparing images for social media posts, websites, or specific device screens.
•Clean UI, no signup required
•Supports JPG/PNG/WebP
•Presets for common aspect ratios
•Works entirely in-browser (privacy friendly)
Would love your feedback or suggestions!

value: Show HN: Change Image Aspect Ratio Tool

author: devxiyang

title: Show HN: Change Image Aspect Ratio Tool


value:
Hi HN,
I made MergeImages.co, a lightweight web tool to combine multiple images vertically or horizontally.
•Drag-and-drop interface
•Rearranging supported
•JPG/PNG/WebP
•Instant merge in-browser (no uploads)
It’s built to be fast, privacy-friendly, and mobile-friendly. Hope it helps others too!

value: Show HN: Merge Images – A Minimal Tool to Join Multiple Images into One


value: Kehvinbehvin

value:
I love drawing out my ideas in Excalidraw and wanted to get my drawings into Claude Code context. Excalidraw's JSON exports are huge and full of metadata, so I created this tool to extract only the relevant information without poisoning my context.
This turned out to be useful for any relatively large JSON file where you only need specific fields - API responses, config files, data exports, etc.
Give it a try, any feedback is appreciated!

value: Show HN: A JSON MCP that doesn't clutter your LLM context

author: Kehvinbehvin


value: Show HN: Visual AI x RAG – Search, tag and edit photos with AI


value:
I’m a game designer, not a developer. But I’ve always wanted to build something small, clean, and fun—without clutter, ads, or monetization pressure.
So one weekend, I opened ChatGPT and vibe-coded my first playable game: a classic Word Search. Mobile-friendly. Fast. Lightweight. No logins. Just a simple grid of words for puzzle lovers.
It’s all static HTML/CSS/JS, with randomized word lists. Took surprisingly little time with the right AI nudges. Honestly, it felt empowering to build something solo.
Would love your thoughts—especially from devs and designers who’ve shipped something scrappy just for the joy of i

value: Show HN: I vibe coded a word game as a game designer (no ads, just fun)


value: rakeda

value:
Hey HN,
I'm Brandon, a solo dev, and I built KubeForge - a visual editor for Kubernetes deployments that helps you build and validate YAML configs.
Origin Story: Over the past couple weeks, I got fed up manually writing Kubernetes YAMLs, especially when working with nested structures like containers, env, and volumeMounts. Even small typos or misaligned fields added lost time to broken deploys.
So I started hacking together a tool to visualize the structure of Kubernetes objects based on the OpenAPI schema. That prototype quickly turned into a full manifest builder.
What KubeForge does:
- Pulls the latest Kubernetes OpenAPI schema (auto-updated daily)
- Generates field-level forms with type safety, required fields, and smart defaults
- Lets you visually build manifests like a flow editor
- Outputs clean, deploy-ready YAML, with multi-object exports
Personally, I wanted a tool that:
- Validates fields as I build, not after deployment
- Surfaces nested fields, tooltips, and types without switching tabs
- Lets me export or share real YAMLs easily
Try it out:
GitHub: https://github.com/kubenote/KubeForge
Live demo: https://demo.kubefor.ge
Website: https://kubefor.ge
It’s free and open source. I’d love feedback, bug reports, or ideas. Contributions welcome too .
Thanks, Brandon

value: Show HN: KubeForge – A GUI for Kubernetes YAMLs

author: rakeda


value: fahhem

value: Show HN: SonicInfra, Cloud at On-Prem Prices

author: fahhem


value:
Just released *Dingo 1.9.0* with major upgrades for RAG-era data quality assessment.
### Key Updates:
* Enhanced Hallucination Detection*
Dingo 1.9.0 integrates two powerful hallucination detection approaches:
- *HHEM-2.1-Open local model* (recommended) - runs locally without API costs
- *GPT-based cloud detection* - leverages OpenAI models for detailed analysis
Both evaluate LLM-generated answers against provided context using consistency scoring (0.0-1.0 range, configurable thresholds).
* Configuration System Overhaul*
Complete rebuild with modern DevOps practices:
- Hierarchical inheritance (project → user → system levels)
- Hot-reload capabilities for instant config changes
- Schema validation with clear error messages
- Template system for common scenarios
* DeepWiki Document Q&A*
Transform static documentation into interactive knowledge bases:
- Multi-language support (EN/CN/JP)
- Context-aware multi-turn conversations
- Visual document structure parsing
- Semantic navigation and cross-references
### Why It Matters:
Traditional hallucination detection relies on static rules. Our approach provides context-aware validation essential for production RAG systems, SFT data quality assessment, and real-time LLM output verification.
Perfect for:
- RAG system quality monitoring
- Training data preprocessing
- Enterprise knowledge management
- Multi-modal data evaluation
*GitHub*: https://github.com/MigoXLab/dingo
*Docs*: https://deepwiki.com/MigoXLab/dingo
What hallucination detection approaches are you currently using? Interested in your RAG quality challenges.

value: Show HN: Dingo 1.9.0 released: With enhanced hallucination detection


value:
Hello HN, i am the creator of Kali in Batch. This is a project i have been actively working on for months, and i want to show it here.
Kali in Batch creates a Unix-like environment on Windows. It uses subst to assign a drive letter to the root file system located at "%USERPROFILE%\kali", it even has some POSIX functions reimplemented (see https://github.com/Kali-in-Batch/kali-in-batch/blob/master/s...).
I hope anyone reading this can test it and find as many bugs to report as they can so i can improve the software. Please also consider making critiques and suggest improvement and feedback.

value: Show HN: Kali Linux-like environment written in Windows Batch


value: priyankaajsr

value:
Hello HN,
I'm launching MitiFresh, a marketplace that connects people with excess homegrown produce to buyers in their community.
The Problem: Millions of households grow fruits and vegetables that often go to waste because they produce more than they can consume. Meanwhile, others are looking for fresh, local produce but lack access.
Our Solution: MitiFresh creates a simple way for backyard gardeners to list their excess produce and for local buyers to discover fresh food grown in their neighborhood. Sellers earn passive income while reducing food waste.
Try it out: https://www.mitifresh.com/
I built this after noticing how much produce went unharvested in my neighborhood during peak growing seasons. As a developer with an interest in sustainability and local food systems, I wanted to create something that could simultaneously reduce waste, build community connections, and help people earn from their gardens.
Would love feedback from the HN community for this neighborhood marketplace, and scaling strategies as we expand to more regions.

value: Show HN: MitiFresh – A marketplace for homegrown backyard produce

author: priyankaajsr


value: seeyebe

value:
I built gmap, a command-line tool to visualize Git activity, weekly heatmaps, file churn, authorship stats, and more, right from your terminal.
Install with:
cargo install gmap
Or on Arch via AUR:
yay -S gmap
Repo: https://github.com/seeyebe/gmap
Feedback is welcome. Contributions too. if you’re into Git internals, CLIs, or terminal UX.

value: Show HN: Gmap: Explore Git Repos Visually from the CLI

author: seeyebe


value: davidgomes

value: Show HN: App.build, open-source AI agent that builds full-stack apps

author: davidgomes


value: I'm not so comfortable using C++ for making UI & I wanted quick prototyping so that I can try things with Chromium. I’m building a way to make chromium UI in HTML/CSS/JS. It’s being made on top of chromium’s WebUI framework, the same way its settings & new tab page are rendered.<p>This has been done before with an open source browser called Vivaldi & I think Microsoft Edge. Although, in the near future I want to add ADK (Arc Development Kit)[1] like features that allow me to tap into the main Browser’s context without doing a lot in C++.

value: Show HN: Trying to build Chromium UI in HTML to increase prototyping speed


value: ajabhish

value:
Demo: https://youtu.be/W4uBOTf9KtY
Today we’re rolling out beta access to our AI agent that talks to Google Slides.
- Ask a question → it jumps to the right slide
- Need a diagram? → “Show slide 3”
- Want to rewind? → “Go back two slides”
This can be a game changer for teaching new concepts, employee training (onboarding, explaining playbooks etc) ...
Our agent now has capability to display and navigate Google Slides based on conversation flow, creating truly interactive learning experiences.
Setup in 3 steps:
 1⃣ Get the embed URL from Google Slides (File → Share → Publish to web → Embed)
 2⃣ Enable the tool in scenario settings and paste the URL
 3⃣ Add slide instructions to your AI prompt (e.g., “Show slide 3 for the architecture diagram”)
Create your own: https://app.toughtongueai.com/advanced-scenario-create/
Try the one I used: https://app.toughtongueai.com/run/paris-tough-tongue-ai-pitc...
Or the one that teaches: https://app.toughtongueai.com/library/product-design-intervi...

value: Show HN: Transform static presentations → dynamic AI-guided experiences

author: ajabhish


value: Show HN: Dotfiles Management Tool

title: Show HN: Dotfiles Management Tool


value: mchahn

value: I've just released Function Explorer. It is a vscode extension that provides a sidebar explorer much like the built-in file explorer. The big difference is that you can expand the file items to show their functions. It also features marking functions much like bookmarks. It has a ton of features. Feedback would be appreciated (good or bad).

value: Show HN: New VSCode extension Function Explorer

author: mchahn


value: Show HN: Go-Pubsub – A Lightweight, Real-Time Pub-Sub Library for Golang


value: pompomsheep

value: Show HN: Snapmatch

author: pompomsheep

title: Show HN: Snapmatch


value:
I'm building *GistFans* (https://gistfans.com) - a developer-centric social platform where the community actually controls the platform's evolution through a Star-based governance system.
*The Problem:*
Every developer platform today is controlled by corporate boards making decisions that often ignore what developers actually need. Features get removed without consent, algorithms optimize for ad revenue instead of user value, and our feedback rarely translates into real changes.
*Our Solution - True Developer Democracy:*
- *Earn Stars* through contributions (sharing experiences, helping others, quality content)
- *Vote with Stars* on all platform decisions - features, policies, development priorities
- *Transparent governance* - all votes and decisions are public
- *Binding results* - community decisions become reality, not just "feedback"
*What makes this different:*
1. *No corporate overlords* - the community IS the decision maker
2. *Contribution-based voting* - your influence grows with your contributions
3. *Complete transparency* - every vote, every decision is public
4. *Developer-first* - built by developers, for developers
*Current Status:*
We're in closed beta, selecting active developers who want to help shape this from the ground up. Selected members get co-founder recognition and play a crucial role in establishing our governance foundation.
*Coming Soon - Open Resource Subscribe:*
We're also developing a system where open source maintainers can offer premium resources (advanced tutorials, exclusive content, early access) through community-validated subscriptions. The community votes on fair pricing and value, ensuring creators get sustainable income while maintaining open source principles.
*Why this matters:*
Imagine if GitHub's features were decided by developers who actually use it daily. Imagine if Stack Overflow's policies were voted on by the community that creates its value. That's what we're building.
*Questions for HN:*
1. What features would you vote for in a developer platform?
2. How do you think contribution-based voting should work?
3. What's your biggest frustration with current developer platforms?
The demo is live at https://gistfans.com - would love your thoughts on the concept and governance model!
*Tech Stack:* Next.js, TypeScript, Supabase, Vercel
*Status:* Closed beta, seeking founding community members
The future is community-owned: built by us, governed by us, belonging to us—not to corporate interests.

value: Show HN: GistFans–First developer platform with 100% community-driven governance


value:
Hi HN!
I built AgentSmith-HUB, an open-source security data pipeline platform with a built-in real-time threat detection engine.
What it is
AgentSmith-HUB helps security teams process, enrich, and analyze massive amounts of security logs and alerts. It features:
A flexible XML-like rules engine (regex, thresholds, custom logic, dynamic fields)
Built-in plugin system with custom plugin support for enrichment, threat intel queries, and automated actions
Cluster/distributed mode for scaling to large data volumes
A full-featured web UI for building and testing detection workflows visually
Easy integration with Kafka, Elasticsearch, and major cloud logging services
Performance
In our tests (8 complex rules), it handled ~40k messages/sec with sub-ms latency on a 2‑CPU, 4‑GB server.
Who is it for?
Security engineers building custom detection workflows
Teams looking for a flexible, lightweight alternative to heavy SIEMs
Anyone needing a scalable, real-time log processing and threat detection pipeline
Links
GitHub: https://github.com/EBWi11/AgentSmith-HUB
I’d love to hear your thoughts, especially on use cases or integrations you’d like to see supported!

value: Show HN: AgentSmith-HUB – Real-time security data pipeline and detection engine


value:
I live in Kyiv.
And there a demand for a goooood drone name.<p>In case you need something special try so called Dark Mode

value: Show HN: Made a Tinder but for drone names (18+ mode included)


value:
This is a project I've been working on since the start of the Year.
I built an app so that I don't have to pay for OpusClip or similar expensive tools...
https://shortgen.io
The app works entirely in the Browser. I'm selling the prebuilt version of the app to earn some revenue for my time.
If you want to try the app but can't afford the price of OpusClip, i have a FREE trial...
I would love to hear all the feedback/suggestions. Thanks!

value: Show HN: Shortgen.io – OpusClip but Way Cheaper


value: liuwei

value:
Hey HN! I built WanVideo (wanvideo.tv) to make the powerful Wan 2.2 video generation model accessible to everyone.
## What is Wan 2.2?
Wan 2.2 is an advanced AI video generation model that uses an optimized MoE (Mixture of Experts) architecture to create professional-quality videos. Key capabilities:
- *Cinema-Grade Aesthetics*: Professional lighting, smooth camera movements, and cinematic effects without any filming equipment
- *Natural Motion Dynamics*: Realistic human movements, accurate physics simulation, and believable character expressions
- *Multi-Modal Input*: Generate from text descriptions or animate existing images
- *Lightning Fast*: 5-10 minute generation (vs hours with other models)
## Why We Chose Wan 2.2
After testing multiple video generation models, Wan 2.2 stood out for its balance of quality and efficiency. The MoE architecture allows it to specialize different aspects of video generation (motion, lighting, scene composition) while maintaining fast inference times.
## Technical Implementation
- Built on Next.js 14 + Supabase + Cloudflare Pages
- Provider abstraction layer supporting Wan 2.2 via Kie.ai
- Credit-based billing ($0.25 = 10 credits)
- Webhook-driven async processing with real-time updates
## Real Results
Users are creating marketing videos, educational content, and social media clips that previously required $1000s in production costs. Every video includes full commercial rights with no watermarks.
Try it at [wanvideo.tv](https://wanvideo.tv) - free credits for new users.
Would love feedback on the UX and ideas for making AI video generation more accessible to developers.
Thanks!

value: Show HN: WanVideo – Wan 2.2 AI Video Generation

author: liuwei


value: skyzouw

value:
Hey HN,
I built a small AI tool that helps you reply to emails faster.
It reads the incoming message and generates a relevant response using GPT-4. You can tweak it, copy it, or just send it right away.
I got tired of answering the same kinds of emails manually (demo requests, support, etc.), so I built this to speed things up. No integrations, no setup — just paste your email and get a suggested reply.
→ https://www.replyfast.net/
Built it solo over a few weeks. Curious to hear your thoughts or feedback!

value: Show HN: I built an AI tool that writes replies to your emails automatically

author: skyzouw


value: alessandro-a

value:
Hi HN,
I got tired of making messy "just in case" commits every time AI or a big refactor might break my code. So I built ShadowGit: a macOS app that quietly creates local Git snapshots in the background.
No manual commits, no cluttered history, just instant local restore points.
It's free to download and use during early access and I'd really love your honest feedback.
Happy to answer anything here. Even if you think this idea is dumb, I want to hear it :)
Thank you!

value: Show HN: Automatic local Git snapshots while you code (macOS)

author: alessandro-a


value: cunjieliu

value: Show HN: A App Helped Me Climb Out of a Deep Burnout

author: cunjieliu


value: cbpark

value:
THE BETA'S JUST OUT PLEASE SHARE YOUR THOUGHTS!
Just enter your brand name, audience, and content type —
and you’ll instantly get post-ready visuals that match your feed vibe.
It’s for small biz owners, freelancers, and solo creators juggling way too much.
 Currently in beta — we’re looking for early users to help shape it with real feedback.
What it does:
 Auto-generates branded visuals
 Matches your tone + aesthetic
 No editing needed (unless you want to tweak)
 Save + reuse as templates
Why we’re building it:
To save creators hours of repetitive design
To help small brands show up consistently — without the burnout
To learn + iterate with early adopters from this community

value: Show HN: Built sth that makes social media suck less

author: cbpark


value: Show HN: I made a website to find relevant conversations about your brand


value: ishqdehlvi

value:
We're launching the beta of WTMF (working title) next week. It's designed to be an AI companion for those moments when your mind won't shut off late at night.
The idea came from those frustrating 2 AM situations where you feel the need to express what's on your mind but don't necessarily have someone available or want to reach out in a traditional way. WTMF offers a space to voice note your thoughts and receive a supportive response from an AI designed to simply listen and understand, without judgment. It's not intended as therapy, but more as a digital "bestie" for those isolated moments.
We've focused on creating a natural interaction, especially through voice, to try and capture the nuances of those late-night anxieties (the "uff yaar" feeling, as we've been calling it internally).
The beta will be rolling out to those on our waitlist initially. We're a small team based in Hyderabad, India, and are eager to get feedback and iterate.
More details on the launch date and how to potentially get access will be shared soon. We're hoping WTMF can provide a little bit of solace during those otherwise lonely hours.
Looking forward to your thoughts and feedback.
https://wtmf.ai
https://beta.wtmf.ai

value: Show HN: WTMF: An AI Companion for Late-Night Thoughts – Launching Next Week

author: ishqdehlvi


value: devxiyang

value:
Hi HN,
SquareImages.co lets you turn any image into a square without distortion. Great for profile pics, marketplaces, or Instagram.
•Add padding (choose color or blur)
•Download-ready square outputs
•Simple, clean UI
•Runs fully client-side
Feedback welcome — especially if you use it for social content!

value: Show HN: Square Images – Make Any Image a Perfect Square in One Click


value:
Hi HN,
CompressImageX.com is a straightforward image compressor that helps reduce file sizes without killing quality.
•Adjustable quality settings (lossy/lossless)
•Batch compression supported
•Fast, works offline (thanks to WebAssembly)
•No watermarks, no tracking
Useful for devs, bloggers, or anyone who wants lighter images. Let me know what you think!

value: Show HN: Compress Image – Simple Lossless and Lossy Image Compression Tool


value:
Hi HN!
I'm a developer who got tired of jumping between tabs just to run everyday tasks — decoding Base64, converting timestamps, generating UUIDs, etc.
So I built a small macOS menu bar app called CodeSwissKnife Bar. It gives you quick access to essential dev tools, all running 100% offline.
No accounts, no cloud, no tracking — just useful utilities where you need them.
Right now it includes:
- Base64 / URL / HTML encoder & decoder
- UUID and color converters
- Unix timestamp ↔ Date
- Text base conversions (binary / decimal / hex)
- A simple daily Scrum journal
- One-click feedback shortcut
It’s not trying to replace IDEs or big tools — I just wanted to remove friction from tiny, repetitive dev actions.
Happy to share it here and get your thoughts!
https://www.codeswissknife.com/codeswissknifebar.html

value: Show HN: CodeSwissKnife Bar – Dev tools in your macOS menu bar (offline)


value: bubudrc

value:
Hello HN!,
For the past three years, I have been developing a news aggregator app called Newsreadeck. I like to read news from several sources. However, most similar apps are primarily available in English and cater to U.S. users.
I initially tried using RSS feeds, but many websites don't offer them. Manually creating or finding RSS feeds was tedious. Additionally, RSS feeds often just opened articles in a web browser or displayed only snippets, not the full content.
To address these issues, I developed my own data sources. I've compiled over 16,000 curated sources, categorized by language, location, and topic, which I monitor for reliability. The app allows you to discover and follow sources without limits and access articles seamlessly. I also built a custom reader to remove ads, banners, and distractions, although some paywalls may still appear.
Some sources can be too aggressive in publishing articles. To address this, I've added options to mute certain words to avoid related articles, mute specific sources, and create a custom news feed by grouping your favorite sources.
The app features a search engine that allows users to apply filters such as language, country, and topic in addition to keywords, helping them discover top news and new channels to explore.
Finally, the app features widgets that bring the latest news straight to your home screen.
If you're as enthusiastic about news as I am, you're welcome to try out the app, available on the App Store.
App store Link: https://apps.apple.com/us/app/newsreadeck/id1593025917
Web Link: https://newsreadeck.com/
I'm open to any feedback you might have!

value: Show HN: I built a worldwide news app, because Apple doesn't want to

author: bubudrc


value: neis

value:
Hi HN, we’re Jacob, Boris and Xavi and we’re building Hunter (https://hiringagents.ai/hunter), an AI HUD for finding and landing your next job.
While running our AI recruitment agency for the past 2 years, we heard our engineering candidates consistently complain that they spend 100’s of hours finding and applying for jobs, often to never have their resume reviewed at all, let alone being contacted.
Job boards like LinkedIn and Indeed feel like they’re built for a previous age: manually scrolling through thousands of jobs to then fill out the same details again and again never to hear back, or getting overwhelmed by automated recruiter messages for jobs that don’t fit. On the other hand there are many experiments with AI job agents, that create a ChatGPT UI for jobs, which we didn’t like so much.
That’s why we built Hunter: a Job Search HUD that uses an AI voice to help you navigate an LLM-filtered job board.
This creates 3 advantages over the status quo:
- Deep Understanding. Express what you’re looking for not through filters and keywords, but with your voice. This way, it’s much easier for the system to truly understand that you wanna work on low level software, consumer products or series-A startups
- Highly Curated Jobs. Our job board only presents roles that meet your preferences. Because Hunter has a deep understanding, the jobs are high quality. We can also ping you when new jobs become available that are a great fit (and only then).
- Hiring Team. When you apply for a job, you’ll be competing with hundreds of others. Inspired by ‘AI SDRs’, we’ve built a feature that finds and helps you send personalized messages to the hiring team behind the job. This greatly increases your chances of getting your application actually seen by the right people.
You can watch a demo: https://youtu.be/HBfhP4AniJE
Or try it out for yourself: https://app.hunterscouts.com/job-search
We loved reading this great post here on HN earlier this week on copilots <> HUDs: https://news.ycombinator.com/item?id=44705445, and very much try to build a product where we combine the best of UI and AI in a HUD like experience.
Would love to get your thoughts and feedback!

value: Show HN: AI HUD for Job Search

author: neis

title: Show HN: AI HUD for Job Search


value:
I launched Open SaaS about a year and a half ago and surprisingly it’s become one of the most popular free SaaS boilerplate starters on github (https://github.com/wasp/open-saas).
After 2 years of work total, I’m pleased to launch what I’m calling “Open SaaS v2.0”.
Here’s a breakdown of all the features and updates I’ve made to it over time:
* New Big, Shiny Things for v2.0 *
- Complete redesign with Shadcn UI for a modern and consistent look (themeability coming soon...).
- Script that autogenerates an LLM-friendly version of the documentation https://docs.opensaas.sh/llms-full.txt.
- Added Zod validation for webhook payloads.
* Main Features *
- 100% open-source repo w/ a focus on open-source tools when possible.
- Auth that you own (no 3rd party services): email, google, github, discord...
- Full Payments Integration: easily swap out Stripe for Lemon Squeezy or Polar (coming soon!).
- Full-stack typesafety on top of React, NodeJS, Prisma.
- Admin dashboard w/ revenue and site analytics (Google or Plausible)
- OpenAI API & AWS S3 integrations.
* New Features*
- Added Lemon Squeezy as payment provider option (Polar and Paddle in the works!).
- Enhanced file uploads with progress bars and validation.
- Added a generic cookie consent banner (if you need one).
- Integrated Playwright for end-to-end testing.
- Added a 404 page.
* Fixes & Improvements*
- Upgraded Wasp (React/NodeJS/Postgres) framework to v0.17.0.
- Upgraded AWS and OpenAI SDKs to their newest-ish versions.
- Tightened S3 CORS configuration for better security.
- Improved payment webhook logic.
- Made UI components more consistent (e.g., controlled switches).
- Fixed various styling issues, including dark mode inconsistencies.
- Improved error handling and validation across the app.
* Refactoring & Code Organization*
- Major "vertical reorganization" of the codebase for improved modularity (auth, payments, users, file-upload).
- Significant refactoring of user management pages and queries.
- Refactored to use prisma transactions for safer DB mutations.
- Cleaned up and simplified various parts of the codebase.
* Docs & Content*
- Updated documentation for deployment, installation, and new features.
- Added a customization checklist.
There have been a slew of paid SaaS boilerplate starters popping up since we started, but Open SaaS will stay free and open-source forever.
So if you’re interested in becoming a contributor, or just wanna add a suggestion to the roadmap, feel free to create an issue https://github.com/wasp-lang/open-saas/issues.

value: Show HN: V2.0 of Open SaaS, a free, open-source SaaS boilerplate starter is here


value: TXTOS

value:
i’ve been building something called the WFGY engine, a semantic reasoning core to fix known LLM failures ~ hallucinations, logic collapse, memory jumps, retrieval drift...
as part of that, i started building TXT OS, a symbolic operating system powered by plain text files, reasoning layers, and modular logic.
people ask: is it really an OS?
i think so.
it has memory, reasoning cores, modular layers, and the whole thing runs without training ~ just through structure.
here’s the semantic blueprint ! the actual plan for what’s built and what’s coming next. some modules already live. others are sketched. all readable.
also: project recently got a star from the creator of tesseract.js
so that’s something.
happy to hear thoughts ~ or just let it sit. i’ll keep building anyway.

value: Show HN: I made a semantic OS for language reasoning (not kidding)

author: TXTOS


value: skyzouw

value:
Hey HN,
I built ReplyFast, a tiny AI tool that does one thing only:
 It replies to your emails instantly – in your own tone – with 1 click.
No chat interface, no fluff, no distraction.
Just paste the incoming message, hit “Reply”, and get a clean, human-sounding response ready to send.
Think of it as “muscle memory for email replies.”
Why I built it:
I was wasting too much time replying to basic emails or DMs. Most existing tools either sound robotic, take too many steps, or try to do too much. I just wanted something that feels like me, but faster.
Tech:
– Next.js + GPT-4
– Hosted on Vercel
– Just one page + a dashboard
– Tone selector, instant suggestions, no login required to try it
Pricing:
– Free to test
– Paid plan for frequent users (still finalizing based on feedback)
Would love your thoughts on:
– What features would you want for email productivity?
– Would you pay for this if it saves you hours weekly?
– Anything that feels off or unnecessary?
You can check it here :https://www.replyfast.net/
Thanks
– Viggo

value: Show HN: ReplyFast – Let AI reply to your emails, instantly and in your style


value: timzhangyuxuan

value:
I've been making YouTube videos for a while now, and honestly? My thumbnails sucked. I'd either spend way too much time in Photoshop trying to make myself look presentable, or just slap some text over a random screenshot and call it a day.
The worst part was trying to get consistent shots of myself. I'd end up taking like 50 selfies just to find one that didn't look completely awkward.
So I thought: what if I could just describe the thumbnail I want and have it generate one with my face already looking good?
I built something simple: you upload a few photos of yourself, we train a personalized AI model, and then you can just describe your thumbnail idea in plain English.
You can try it here: https://newhero.ai or see some examples: https://newhero.notion.site/ai-poster-showcase
Main questions I have:
Do the generated thumbnails actually look good enough to use?
Does this actually save time for creators making multiple videos per week?
Let me know how it goes, happy to answer any questions you have!

value: Show HN: I built a YouTube Thumbnail generator with your face

author: timzhangyuxuan


value: daizutabi

value: Show HN: HydraFlow – Type-safe ML experiment tracking with Hydra and MLflow

author: daizutabi


value: hauntedLogic

value:
Hi folks, I built Swatcher.ie as a side project to experiment with colours, and it grew into matching paint colours in Ireland as a way of helping some family and friends out.
It's free to use, and the paint exploration part doesn't require you to log in. Maybe others will find it useful.
I'm just enjoying working on it, so I'm always playing around with it. Thanks!

value: Show HN: Find paint colours in Ireland and generate your own palettes

author: hauntedLogic


value: dbvitapps

value:
Hey HN,
I'm the founder of Ninjadoc AI. I've spent years working with document processing, and I've always been frustrated by the existing solutions for structured data extraction.
The core problem is that most tools force you into one of two bad options:
Template-based extractors: You define fixed regions or rules. These are incredibly brittle and break the moment a document layout changes slightly (e.g., a new invoice template from a vendor).
ML-based extractors: These require you to gather hundreds (sometimes thousands) of your own labeled documents to train a custom model for each document type. It's a slow, expensive, and data-intensive process.
I wanted a "zero-shot" solution that worked out of the box, so I built Ninjadoc AI.
Our approach is different. Instead of training, you use a tool to define your desired schema once. For example, you define fields like invoice_id, due_date, and line_items.
The AI then uses this schema to understand the document's structure and context, allowing it to extract the correct data from any layout variation of that document type. It's layout-agnostic.
A few key technical features:
It's a REST API: Simple to integrate, returns structured JSON.
Bounding Box Coordinates: For every piece of extracted data, the API returns its precise coordinates on the document. This is useful for building verification UIs or for record-keeping. To my knowledge, we're the only zero-shot tool that provides this.
Visual Schema Builder: No code is needed to define what you want to extract. You just upload one example document and map fields visually. Those rules then apply universally.
No Training/No Templates: It works immediately on your documents without any model fine-tuning or sample uploads.
The goal is to provide a powerful, developer-friendly API that skips the most painful parts of document data extraction.
I'd be grateful for any feedback, especially on the API design and the overall developer experience.
You can try it out here: https://ninjadoc.ai
There's a free plan with 5,000 credits (no credit card required), which is enough to run a few hundred pages through it.
Thanks for checking it out!

value: Show HN: An API to extract structured data from any document without training

author: dbvitapps


value: JonyYadgar

value: Hey HN, I made this because I tried to make a faceless AI YouTube video for fun (in the style that channels like "Bible Stories" make), and it took me hours individually generating the AI stock footage. (For example, if you want an image to change every 10 seconds in a 1 hour video, you need to generate 360 images).

value: Show HN: I built an AI that turns scripts into AI stock footage

author: JonyYadgar


value: Show HN: A word game that I made for my friends


value:
Hey HN,
We’re Volodymyr and Volodymyr—two developers from Ukraine building WhiteLightning. It’s a tool that turns large LLMs (Claude 4, Grok 4, GPT-4o via OpenRouter) into tiny ONNX text classifiers that run anywhere—even on drones at the edge.
Why we built this:
Many developers want custom models (spam filters, sentiment analysis, PII detection, moderation tools), but don’t want to deal with constant API calls or deploy heavy models in production.
How it works:
WhiteLightning uses LLMs to generate training data and distills it into KB-sized ONNX models you can run on any device and in any language. Just describe your task in a sentence, grab the ONNX model, and run it locally—Python, JS, Rust, Java, Swift, C++, you name it.
Try it instantly in your browser:
https://whitelightning.ai/playground.html
Code & docs: https://github.com/Inoxoft/whitelightning
Community model library: https://github.com/Inoxoft/whitelightning-model-library
We’d love your feedback—what works, what doesn’t, and what to improve.

value: Show HN: WhiteLightning – ultra-lightweight ONNX text classifiers trained w LLMs