Creating Code Playbacks with Storyteller

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I have been working for a while on a new medium to guide others through code examples. Devs use an editor (VS Code) to write code and then test it like normal. Then, the code can be played back in a browser and the author can add a narrative about its evolution. The narrative can include text, code highlights, hand drawn pictures, screenshots, audio/video files, and Q&A's. I call them 'code playbacks' (follow the link to see some examples in one of my 'books'). I have been making collections of these and using them instead of textbooks in the programming-focused CS courses that I teach for the last couple of years. My students don't like traditional programming books much anymore. They like videos but I don't think they are ideal for teaching with code. They have responded really well to the code playbacks. I've been thinking about making a new site to host these so that anyone can sell (or share for free) their collections of playbacks. Users would also be able to make professional portfolios to show potential employers how they think about and communicate with code. I don't really consider myself a web developer but I am pretty sure I can learn what I need to in order to build this. My dilemma is whether I should or not. Are playbacks a valuable enough new medium? Can they disrupt the traditional programming book market? Should I create a startup and write all of the code myself (probably slowly)? Should I raise money? Find a co-founder? Hire a seasoned web dev team? I'm looking for advice on next steps.

Visit product View on Hacker NewsFeb 26, 2023

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

94%94% 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: user, new, using · Missing: mac, agents, macos

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released

71%71% 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: ios, video, users · Missing: mobile apps, personal, entrepreneurs

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

AppSumoMay struggle as an AppSumo deal · Strong signals: host, users · Missing: plus, platform, intuitive

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

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

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: audio · Missing: web3, chat, crypto

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

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