Pe

Pebble Graphics – A 3D Version of Turtle Graphics

Hacker News

Pebble Graphics – A 3D Version of Turtle Graphics

Note: If you’re logged into your Meta/Oculus/Facebook account when you visit the store page you should see an option for a free trial, if not let me know and I can send you a promo code or something Pebble Graphics is a modern take on Logo/turtle graphics partially inspired by stories of people’s first programming experiences on the Apple II with turtle graphics and partially influenced by essays like Bret Victor’s Learnable Programming [1]. It’s a 3D user interface for programming that emphasizes interactivity (being able to put together a program with 3D pieces and step forward and backward through execution as you’re building) and visualization of state and execution history. It’s been a bit of a journey to get to this point and it started here on Hacker News. I was first inspired to try out VR after seeing this post [2] of a live coding environment in VR by Brian Peiris back in 2014. After working on my own multi-user version of that project [3] I thought more about non keyboard interfaces for making programs since it wasn’t that easy with a headset on. After a few experiments, I ended up with a project where you could put together JavaScript abstract syntax trees with your hands and interactively execute them [4]. I took a brief break and then decided to see if there was anything interesting at the lower levels of computation and also take some time to study the amazing Nand to Tetris course [5], which resulted in a VR circuit simulator [6], VR CPU Emulator [7], and a very limited version of turtle graphics in VR [8]. A lot of this work was done at the wonderful Recurse Center [9], which I highly recommend and through some great discussions with members of the community there were a few stories of how people got their start in programming with turtle graphics so I decided to make a more user friendly version. I had a long time interest in startups and entrepreneurship so I took this as an opportunity to learn about that process as well and here we are. Here’s a playlist [10] of the app's development over time and the channel has some other VR and programming experiments as well. Thanks for taking the time to look! [1] Unfortunately it looks like the site is down at the time of this writing ( https://worrydream.com/LearnableProgramming/ ) , but here’s some HN discussion https://news.ycombinator.com/item?id=37746918 [2] https://news.ycombinator.com/item?id=8411638 [3] https://github.com/ih/construct [4] https://github.com/ih/jsvr [5] https://www.nand2tetris.org/ [6] https://github.com/ih/GatesVRE [7] https://github.com/ih/CPUEmulatorVR [8] https://github.com/ih/TurtleVR [9] https://www.recurse.com/ [10] https://www.youtube.com/playlist?list=PLhmEEtPzG7mW4JrBUhwbo...

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2points
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
96%96% 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.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, ide, io · Missing: https docs, excited, just released
78%78% 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: apple, user, new · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: entrepreneurs · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly, interface, user friendly · 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: active · Missing: arr, mrr, revenue
13%13% 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.

Incorrect prediction on native model

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