I made an Airtable powered Drag-and-Drop Website Builder

Hacker News

Hey HN, 1 year ago I shared the project I'd build, Shareables. A tool to connect Airtable to visual templates Over the last year, I've been inspired by the use cases people have for Airtable. I've seen food truck directories, pet medical logs, you name it. I'm excited to share the new Shareables designer mode, where you can create completely custom micro-sites (powered by your Airtable data) with a simple drag-and-drop editor, which lets you style to create unique designs and layouts for any use-case, business or personal I would love for you to give it a go. 1. All you need to do is, head to www.shareables.ai and start designing 2. Connect your Airtable and customise it to fit your needs. 3. When you're ready, you can publish to your custom domain (or embed directly back onto your existing website) If you have time, give it a go, and let me know what you think! –Ryan

Visit product View on Hacker NewsSep 24, 2025

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

93%93% 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 · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: builder · Missing: plus, platform, intuitive

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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