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The Magic of Code – book about the wonders and weirdness of computation

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The Magic of Code – book about the wonders and weirdness of computation

I recently published a book called “The Magic of Code” which is about the delights of the computational world, examining computing as a kind of “humanistic liberal art” that connects to so many topics, from art and biology to philosophy and language. The link I’ve shared is to a page on my book’s website where you can download a pdf of the introduction, to give HN readers a taste of what is inside. Right now there is so much worry and concern around technology that I feel like some people—though not the folks here—have forgotten how much fun that code and computation can also be. So I wanted to rekindle some of that sense of wonder. But, as I’ve written elsewhere, this is also the kind of book I wish I had when I was younger and getting interested in computers. I’ve always enjoyed the kinds of writing that talks about computing but in the context of so many other big ideas, especially ones I’ve explored at various points in my own life, from evolution to simulation. And that’s what I tried to do. But while “The Magic of Code” is certainly for a wide audience, and for people who are unfamiliar with programming and code, I’ve also (hopefully!) designed it to be of interest to those who are more expert in this realm, with lots of rabbit holes and strange ideas to pursue. And if there exists a genre of book to explain to outsiders why you love a topic, this is in that genre, for computing and code. I think the HN community will really enjoy it.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% 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: computer, context, code · Missing: mac, agents, macos
81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
34%34% 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
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.

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