Yiitap – AI-native Notion-style block editor

Hacker News

Hi HN, I built an open-source block editor designed for AI-native apps. It’s inspired by Notion, but built with AI workflows in mind: - Built-in AI capabilities to supercharge content creation and productivity. - Block-based editing (drag, split, reorder) - Markdown paste & copy - Built on top of Tiptap & ProseMirror Supports both Vue and React. Demo: https://yiitap.pileax.ai/demo/vue GitHub: https://github.com/pileax-ai/yiitap Would love feedback — especially what kind of AI features you'd expect in an editor like this.

Visit product View on Hacker NewsApr 30, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, open · Missing: mac, agents, macos

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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