Create an Interactive Demo in under a minute [video]

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Hello HN, I created a browser extension that records your screen and then sends keyframes over to the GPT Vision API for annotation. The use case for my software is creating interactive product demos. Here is my app giving a demo of itself (a milestone I am extremely proud of!): https://www.interactivedemo.ai/d/APRNDj9hoONXXDu In the demo, you can see how I'm extracting key frames from the screen recording and sending them over to the LLM with various annotations. I use AWS Lambda with FFMpeg layers for that. For the keyframes, I draw a red dot on the cursor using Python Imaging Library (PIL) and I also draw sequence and timestamp information under the frames. I have a prompt I've been tuning for a while and it's not perfect but, it still saves a ton of time and has great results. The system prompt is: "Generate brief, action-oriented web interaction descriptions. Use varied verbs, focus on direct results, and leverage provided context. Pay close attention to both original and scaled coordinates." but the user prompt is my secret sauce ;-) I am launching it on Product Hunt in a few days here: https://www.producthunt.com/posts/interactivedemo-ai I created InteractiveDemo.ai because I like how Screen Studio feels, but it is Desktop Mac only, and it doesn't have interactive features. Also, I like the ability to create my own A.I. features on top of interactive demos and just the space in general because I've been developing and showing off software for 24 years. It's a natural fit for me. Check it out at https://www.InteractiveDemo.ai I appreciate your support and am happy to answer any questions HN has.

Visit product View on Hacker NewsSep 14, 2024

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

96%96% 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

94%94% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

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

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

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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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