Ae

Aesthetic Computer

Hacker News

Aesthetic Computer

Aesthetic Computer is a mobile-first runtime and social network for creative computing. AC's client interface is designed to function like a musical instrument, on which users discover their own memorizable paths in the network of commands and published pieces. As users grow their literacy through play and exploration, they are able to improvise, recombine, and expand their performable repertoire. I started writing Aesthetic Computer in 2021 because I desired new tools to author, publish and connect the creative software toys I had been making in my art and education practice for 10+ years. The last of these before AC was https://nopaint.art , discussed on Hacker News in 2020.[0] ** Try Me ** Visit https://aesthetic.computer and press the top left of the screen or type any key to activate the prompt. In the AC prompt, enter names of built-in toy and utility pieces like `notepat`[1], or `boyfriend` and those published by user handles like `@bash/hub`. Return to the prompt by pressing the name at the top left corner, your browser's back button or the [Esc], [`], or [Backspace] keyboard shortcuts. Enter `list` at the prompt for a scrollable index of pieces and commands. Most of AC is open to anonymous users. Some pieces like `chat` or `moods` require a registered @handle to fully participate and post data. Every piece on AC is URL addressable. For example, users who enjoy using `notepat` can skip the prompt entirely by bookmarking https://aesthetic.computer/notepat . QR codes to share any piece can be generated by prefixing the piece with `share` at prompt as in `share notepat`. Here are a some recipes to try: A. Make a Painting 1. Enter `new 128` to start a new 128x128 pixel painting. 2. Enter `rect red` and drag to paint red (or any CSS color) rectangles. (Or try other primitive brushes like `line`, `shape`, and `fill`.) 3. Press the command name in the top left corner to return to `prompt`. (Or use the [Esc], [Backspace], or [`] on the keyboard.) 4. Enter `smear` and drag to use a pixel scattering brush, then return to `prompt`. 5. Enter `dl` to download a timestamped PNG, `done` to publish the painting on AC servers, or `print` to mail order a real sticker. B. Play a Melody 1. Enter `+` to open a second prompt window. 2. Enter `metronome 120` in the second prompt window to keep rhythm at 120 BPM. 3. Enter `notepat` in the first prompt window to play tones in regular time. (Or try `bleep:sine 4x4` for a randomized playable tone matrix.) - Bonus - 4. Record a `notepat` performance as a 7s looping, downloadable video by entering `tape notepat`. 5. Play `notepat` in person with others by generating a QR code via `share notepat`. C. Say "hi" in `chat`. 1. Enter `imnew` or press [I'm New] on a deactivated prompt to register. 2. Verify your email. 3. Set a @handle by entering `handle ur-handle-here`. 4. First-time handle setters are automatically routed to `chat`. 5. Say "hi" and request technical help from myself (@jeffrey) and others. To dive in more you can read the technical history [2] or try coding your own AC piece[3]. --- [0] No Paint HN discussion from 2020: https://news.ycombinator.com/item?id=23546706 [1] Recent HN discussion on `notepat` here: https://news.ycombinator.com/item?id=41526754 [2] The AC Story: https://github.com/whistlegraph/aesthetic-computer/blob/main... [3] Write a Piece: https://github.com/whistlegraph/aesthetic-computer/blob/main...

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, computer, new · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, 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.
AppSumoStrong fit for a featured deal · Strong signals: interface, users · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, users, education · Missing: mobile apps, ios, personal
46%46% 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
16%16% 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.

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