
docs.dev — AI drafts your docs. Your team makes them true.
AI drafts documentation for your codebase; your team edits and publishes via Git commits.
linktothenew · HN
Docs.dev – A docs site you own, where AI drafts and you edit in place
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AI drafts documentation for your codebase; your team edits and publishes via Git commits.
linktothenew · HN
Docs.dev – A docs site you own, where AI drafts and you edit in place

Convert documents and text into podcast audio with AI voice generation and editing.
Inpodcast AI — 将文档转成播客音频,支持 PDF、Word、Markdown 和 TXT 文件格式

Convert screen recordings into formatted PDF guides automatically.
@vanmurten_eth · X
Guidesnap: turn any screen recording into a polished PDF guide.

AI-powered video and image review tool with transcription and pixel-accurate commenting for creative teams.
@codesharpdev · X

Store and share prompts, rules, and context that AI tools like Claude Code, Cursor, and ChatGPT can access via MCP.
@vibexp_io · X
Your plan is now code. Claude Code Dynamic Workflows fan out up to 1,000 subagents, 16 at once, each in its own context, verifying until the results converge. Built for big bug hunts, migrations and audits. Source:

Manage academic conferences: submit and review papers, handle scheduling and registration.
@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