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Trane, an automated system for learning complex skills

Hacker News

Trane, an automated system for learning complex skills

Hi HN, I released Trane over the weekend: https://github.com/trane-project/trane . Trane is an automated system for learning complex skills. Think of it like defining a skills tree (technically a graph) of all the smaller skills you need to master a complex skill and having an automated system to automatically traverse the graph as you master them. The seed for Trane was planted after my frustration trying to learn music, and jazz in particular. There are simply too many things you need to master first (e.g. knowing the names of a note, knowing where the notes are in your instrument, timing, etc) and it becomes difficult to track what it is that you should focus on, and there is a process of constant atrophy, even if you practice consistently. Trane is an early state, but is already usable. I have released a command line interface at https://github.com/trane-project/trane-cli and some music courses at https://github.com/trane-project/trane-music . I would like to get some ideas in regard to what other skills could be a good fit for Trane. I am thinking chess, programming, or languages could be a fit. I am wondering if Trane could be applied to something like learning pure mathematics. I would love to hear any suggestions. Perhaps there's some of you who have found a similar issue while practicing your own hobbies.

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: interface · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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.

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