@foldtaskapp · X

u/Capital-Top3289 · Reddit

I built a spreadsheet where every column is an AI agent (research, scrape, or API) — looking for feedback I got tired of pasting the same 50 company names into ChatGPT one by one, then copying websites / CEOs / LinkedIn URLs back into Excel. So I built MySheets: it looks like a spreadsheet, but each column can be: an AI prompt that runs row by row a web scrape an HTTP API call Columns can read previous cells, so you chain: name → website → product summary → CEO → LinkedIn. You

@mesbahlab · X

@shahsyeddanish4 · X

orbbt is a job tech saas, which helps you keep your job hunt sane and organized in this economy where it takes on avg of 100s of job applications

@mj_jimmi · X

@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