@claroboard · X

I built a whiteboard. The hardest part wasn't the coding. The hardest part was getting the first users. Want to give it a try?

@emir_ogz · X

Just shipped - AI-native workspace for solo devs Agent reads/writes your project notes automaticly

@aarsh_30 · X

@ak14053 · X

Xaminix

AI Powered Answer Evaluation for CA/CS/CMA

@fedeponte1 · X

my first saas. i think i built something people actually want and completely failed at the business side. would genuinely love help. openpaper ( writes full, cited research papers from a prompt. research, outline, writing, real citations, export. the honest numbers: - ~2,300 signups - ~1,500 generated a full paper. people actually use it. - ~5 have ever paid. ~$45/mo. activation is great, revenue is basically zero. i've been staring at this for weeks. the paywall is on export (pay ~$12 to download the pdf). but the full cited paper is right there on screen, free, you can read it and copy-paste it. so i'm charging for the gift wrap after handing over the gift. almost nobody even reaches checkout. 76% generate exactly one paper and leave. one-and-done, so subscriptions make no sense. the audience is mostly students and researchers on personal gmail, all over the world, almost none on university or company emails. traffic is x and github. so i genuinely can't tell

robot1996 · HN

AI Coloring Page Generator for printable classroom worksheets

eldar_hsnv · HN

Show HN: AI Notebook for Data Science – Kind of Like Cursor but for Jupyter

@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

@rubs_murga · X

@mr_wickedhacks · X

Write the doc once → get a notebook, slide deck, canvas, or resume from the same source. No rewriting for every format.