I created a free browser extension purpose-built for product demos

Hacker News

Hi HN! I wanted something easy to use like Loom but purpose built for creating product demos to explain how software works. I added the ability to do Pan and Zoom animation (with Framer-Motion), animate informational popovers (with floating-UI), and add voiceovers. You can see a demo of the demo editor I created on the homepage. I'm looking for feedback on how to make it better, so please download the extension HN and let me know what you think!

Visit product View on Hacker NewsMay 23, 2024

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Launch Intel predictions

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

87%87% 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: created · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

57%57% 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

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

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

45%45% 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

18%18% 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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