Learn Blender shortcuts with lots of tiny videos

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I've used blender for more than a decade and now ask myself what the best way to teach it would look like. Video generally seems the best format to explain how to solve a specific problem, but its not exactly great for larger collections of small bits of information – like blender shortcuts. This is why I made this video/text hybrid website from scratch. If you're a blender user or have experience in teaching others, I'd be very happy to hear your thoughts on it. I'm also posting this here because I assume many of your are professional web developers. I'm a learning hobbyist and wondering if there are any issues with the way I built the website. Thanks! Github: https://github.com/hollisbrown/blendershortcuts

Visit product View on Hacker NewsAug 16, 2024

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

86%86% 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

71%71% 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

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.

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

56%56% 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

48%48% 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

12%12% 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.

Correct prediction on native model

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