YouTube Summaries Using GPT

Hacker News

Hi, I'm Alex. I created Eightify to take my mind off things during a weekend, but I was surprised that my friends were genuinely interested in it. I kept going, and now it's been nine weeks since I started. I got the idea to summarize videos when my friend sent me a lengthy video again. This happens to me often; the video title is so enticing, and then it turns out to be nothing. I had been working with GPT for 6 months by the time, so everything looked like a nail to me. It's a Chrome extension, and I'm offering 5 free tries for videos under an hour. After that, you have to buy a package. I'm not making money yet, but it pays for GPT, which can be pricey for long texts. And some of Lex Fridman's podcasts are incredibly long. I'm one of those overly optimistic people when it comes to GPT. So many people tell me, "Oh, it doesn't solve this problem yet; let's wait for GPT-4". The real issue is that their prompts are usually inadequate, and it takes you anywhere from two days to two weeks to make it work. Testing and debugging, preferably with automated tests. I believe you can solve many problems with GPT-3 already. I would love to answer any questions you have about the product and GPT in general. I've invested at least 500 hours into prompt engineering. And I enjoy watching other people's prompts too!

Visit product View on Hacker NewsJan 27, 2023

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

88%88% 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, started · Missing: supports, reddit linkedin, podcasting

79%79% 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

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

48%48% 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

42%42% 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

19%19% 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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