Learn and Build Apps and Games on Web3

Hacker News

Web3(Blockchains & p2p stuff) is a relatively new space today, so it's hard to learn and build on Web3. It's hard to - find resources that help you understand the concepts. - find examples/apps/tutorials that actually work. Most of them are broken as the projects introduce breaking changes, thus examples break. Plus the ones that work don't have many details on how the example works. SimpleAsWater[0], a YC SUS19 Startup: - Gives you Interactive Guides that help you understand the concepts like you are 10. - Has a ton of tutorials that help you build Apps and Games on Web3. Right now, the website has Guide for InterPlanetary File System or IPFS[1], and I'm working on Guides for other Platforms like - Libp2p[2] - Multiformats[3] - InterPlanetary Linked Data[4] - Filecoin[5] - IPFS Cluster[6] - State Channels & Side Chains[7] If you want to get a SimpleAsWater guide(pun intended) for your project, let me know here[8]. [0]: https://simpleaswater.com [1]: https://simpleaswater.com/ipfs [2]: https://simpleaswater.com/libp2p [3]: https://simpleaswater.com/multiformats [4]: https://simpleaswater.com/ipld [5]: https://simpleaswater.com/filecoin [6]: https://simpleaswater.com/ipfs_cluster [7]: https://simpleaswater.com [8]: hi@simpleaswater.com

Visit product View on Hacker NewsSep 15, 2019

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Hacker NewsStrong engagement from HN community · Strong signals: ide · 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.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apps, new · Missing: mac, agents, macos

49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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: active · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: web3, introduce · Missing: chat, crypto, cryptocurrency

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

Incorrect prediction on native model

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