I built QRAuth.io passwordless authentication, it works on any website or physical QR (menus, parking, ticketing, kiosks ).How it works in 8 seconds:
User sees an animated living QR on your site (rotates every 500 ms so screenshots are useless)
They point their phone camera at it
Tap once to confirm with biometrics/passkey
Boom, logged in. No typing, no copy-paste, no extra app.
It s cryptographically signed (ECDSA + post-quantum), phishing-resistant, includes proximity proof, and fraud intelligence. Drop-in web components mean you can add it with literally one HTML tag or npm install . Try the passwordless login flow or the beach-bar menu example, it s kinda addictive. Would love your honest feedback:
Does the living QR feel like magic or overkill?
What use cases would you actually use this for?
Any friction I should kill before I push it harder?
SERPTool is built around a simple idea: Keyword difficulty scores are useful, but they do not always tell the full story. A keyword can look too hard in a traditional tool, but when you inspect the actual SERP, you might find: - weak domains ranking - thin content - outdated pages - poor meta descriptions - missing search intent - low-quality article structure - small sites already competing That is where the opportunity really is. SERPTool helps you analyse the search results themselves, not just rely on a single difficulty number. The free credits are there so people can test the tool properly before deciding whether it fits their workflow. It could be useful if you are: - doing keyword research for clients - looking for underserved content opportunities - building niche sites - running SEO audits - creating content plans - trying to find keywords smaller sites can realistically rank for I d love people in the SEO space to give it a try and share honest feedback. SERPTool is here: https://serp-tool.com
Here's the deal: Most "market validation" is just asking ChatGPT if your idea sounds good. It always says yes. That's not validation it's therapy.
I'm a UX/UI designer, and I got tired of building beautiful products for markets that didn't exist. So we built Bunzee an agent that stress-tests ideas against 200k+ real data points and gives you an actual viability score (ours was a humbling 70/100).
I wanted to share an open-source project called ProxyFace. If you're interacting with LLMs and want a more engaging experience, this adds a real-time, pixel-art avatar that reacts to the AI's output with actual emotions and it runs entirely on your own machine.
How I stopped "fighting" my Roblox code and started designing: My shift to an Agentic Workflow I got tired of AI Roblox tools fighting my project, so I built an open source.
Mine for Lunia (AI bedtime stories): my kid asking the same monster-under-the-bed question for 3 weeks straight while every personalized story app just swapped her name into a generic dragon plot.
Hey PH community just shipped my first independent storefront and would love feedback / brutally honest critique.
What it is: 8 products total at https://onmylist.gumroad.com/ , all centred on AI adoption for Indian small businesses (1-25 person teams). The flagship is a 14-page brief that ranks 10 specific AI workflows by hours-saved-per-week monthly cost in INR, with 30+ copy-paste prompt templates and a tools comparison across 9 categories.
I'm Ruben. Small remote team, all senior dev/ops with 15+ years each. ano.chat is the chat tool we wanted and couldn't buy.
The headline feature: a real terminal inside chat. A proper PTY in the same window as channels and DMs. I switch between Claude Code and bash in there all day, with chat right next to it because that's where the context already lives.
The reframe: every "integration" is just a CLI. gh, kubectl, psql, your own scripts, whatever MCP server you wired up this morning they already exist. ano.chat gives you a place to run them next to the conversation about why.
Not only for engineers. Devs get the terminal. Sales, ops, design get chat that doesn't suck real threads, real search, an iOS app that handles notifications. Whole company, one workspace.
Self-becoming is an experimental open-source runtime that connects a long-running LLM instance to memory, self-state, reflection, rules, tools, and autonomous rhythms, exploring whether an AI can develop a functional sense of self over time.
