Explanans – Personalized video lectures for any topic

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I created this as a product for solving the long-tail of education, specifically with video lectures. YouTube obviously has great videos on subjects like "What is a derivative", "Germany post world war 2" or "History of the roman empire" but it won't always have great videos for more niche subjects like say "Swedish monetary theory through history" or "deep dive on the nutrients of raspberries vs blackberries vs blueberries". Here are some videos that I've created under a few different categories: Content with a personalized angle: - Biology from a computational perspective: https://explanans.com/videos/j9714e2pyxm0qysbkth4hn0tf57ve18... - Machine learning for a non-technical person: https://explanans.com/videos/j97a9d5xpqjq65r9s8zye66ak57vs67... Niche topics - Covid 19 clinical studies: https://explanans.com/videos/j97dvfc5r7xen50t3d1yg3jfvx7vsqv... - Swedish monetary policy: https://explanans.com/videos/j978hwrz0kp7dpr43zgv0bgwrd7vq1h... - Estimating North Korea's GDP: https://explanans.com/videos/j974ccfjrbbb6e4zmfgjqfwwtn7vrnc... And some random subjects: - Things to do in Ireland: https://explanans.com/videos/j971aex478rbthv5n0f6vk8m6h7vsyn... - Clinical studies from start to finish: https://explanans.com/videos/j979m7w6ba8xf4a4gnbjttcmh57vrm6... The accuracy of these videos are (and should be) about the same as you expect from the best LLMs, because this product is fundamentally based on LLMs with access to some tools. You can try it for free at https://explanans.com/ , every new user gets 2 free videos. Would love to give out more, but inference costs for generating a video are quite high. Free users can watch as many existing videos as they want, and you don't even have to sign up for that part. These videos are far from perfect right now, but I think one of the few killer use cases for LLMs are for learning. I think Explanans can be used in the same way that we use ChatGPT/Claude/Gemini, but where the output is in a different format than text. For some mediums I think that's a superior experience, for the same reasons that lots of people prefer YouTube over blog posts. There are a lot of features I want to add to this such as chat with video, some kind of quizzing for retention, or chat before generating to get a more specific output (like how deep research products do it) but I didn't wanna clutter the user experience for v1. Here to answers any questions you might have!

Visit product View on Hacker NewsNov 20, 2025

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

93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

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

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

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

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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

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