Eigenarc – A Chrome extension that turns ChatGPT into study coach

Hacker News

Eigenarc is a chrome extension that makes learning with ChatGPT structured. You can use the extension to create a step by step learning plan for your goal. The extension seamlessly integrates with ChatGPT to create learning materials for each step. Please try out and let us know your feedback. Here is a demo that shows how it works: https://youtu.be/YvL65pdc16U Relevant previous posts: https://news.ycombinator.com/item?id=45354754 - Demo video https://news.ycombinator.com/item?id=45190134 - launch of Eigenarc

Visit product View on Hacker NewsSep 29, 2025

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

61%61% predicted probability of success on Product Hunt, 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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

51%51% 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

21%21% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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