@Pnlytix · X

u/NotGeorge1 · Reddit

I built a tool that scores how Ai-written your site sounds. My own homepage got 6 out of 100. I've spent the last month building SiteTell . It crawls a site and scores the copy against a curated rule set of the patterns that make writing read as Ai-generated. Generic vocabulary, structural tells, the openers that show up on every generated landing page. When it was working well enough to test, I decided to run it on my own site. It scored 6 out of 100. I'll be honest, in the first instan

u/jwwpua · Reddit

I built a PDF redactor that auto-detects names, SSNs, and account numbers without sending your file anywhere - works on your phone too. Free, no sign-up. Plenty of redaction tools upload your file to their server first (no thanks for legal/medical/tax docs). Some keep the file local but send the text off to an AI, so the text still leaves. And most of the truly local ones only let you draw black boxes by hand, which is how those "redacted" documents in the news keep getting un-r

@kimindiehacker · X

i built it's a platform for students to master math concepts by breaking them down step by step.

@ShadowGuarg · X

ShadowGuard analyzes video frames, on-screen text, and visual signals so you can review potential issues before your video reaches your audience.

Dinjure · HN

Dinjure – Bulls and Cows in one HTML file, with a fallible AI

@harryjwang · X

I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age

@dev_adarsh286 · X

PortLume AI - Findout exactly why you got rejected then get hired next time

@chatmouthai · X