Socratix – an AI tutor for proving mastery, not memorizing

Hacker News

The idea for Socratix was formed from constant "completion" of online courses and videos without the ability to actually use the material. How it works: give it a learning objective, and it creates an personalized curriculum in the form of a DAG of prerequisite concepts rather than a list of videos. Each concept comes with theory and interactive practice (with actual code running in browser for technical subjects), and instead of a pass/fail metric, it analyzes mistakes you make in order to diagnose conceptual problems, not simple errors. A concept opens the next one only when it is demonstrated that you know it well enough (practice + diagnostics). Additionally, I'm creating a live voice AI Viva (oral exam style test of knowledge where you will have to justify the answers) that is not live yet, but is coming. It covers various domains, not just programming (mathematics, economics, sciences, etc.) Will appreciate any feedback, especially on curriculum generation part and if the loop of practice/diagnostics feels different from regular quizzes.

Visit product View on Hacker NewsSep 11, 2026

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

80%80% 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.

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

62%62% predicted probability of success on AppSumo, 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.

Product HuntUnlikely to reach the leaderboard · Strong signals: code, open · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% 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 · 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.

Correct prediction on native model

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