Didacu – The fastest way to learn something new

Hacker News

Hi HN, I built didacu because I kept bookmarking articles and tutorials I never read. The friction of learning something new hasn't kept up with the speed of everything else. You type what you want to learn. You get an interactive course in seconds with slides, quizzes, images, and cited sources. You can also drop in a PDF or image and it turns it into a course. The courses are designed around short-form slides you swipe through, one concept at a time. No walls of text. Quizzes are woven in so you're testing yourself as you go, not just passively reading. There's a Claude Code skill (`/didacu-create-course`) that generates courses from your terminal. Onboarding onto a new repo? Generate a course from the codebase. Need to understand unfamiliar documentation? Drop it in and get a structured walkthrough. The best moment to learn something is when you need it. Credit-based, not subscription. A full course costs about $2 at the best tier. Free tier gives 1 credit/week (free courses are shared publicly). Credits only deduct on successful generation. What's different from just reading docs or asking a chatbot: The output is a structured, navigable course. Not a wall of text you have to parse. Every source is cited and clickable. Quizzes test retention. And you can tap any concept and a focused deep-dive course generates instantly. Available on web, mobile app (closed beta), and the CLI skill. Multi-language (English, Spanish, Portuguese). Solo founder, bootstrapped, launched on Product Hunt today. Would love feedback from HN on the course quality. Try a technical topic you actually want to learn. https://didacu.com

Visit product View on Hacker NewsFeb 28, 2026

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

74%74% 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: claude, new, code · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, 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

33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription, bootstrapped, active · Missing: arr, mrr, revenue

23%23% 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.

Correct prediction on native model

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