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Resurrecting Infocom's Unix Z-Machine with Cosmopolitan

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Resurrecting Infocom's Unix Z-Machine with Cosmopolitan

I recently spent some time looking at Infocom's original z-machine source code and bringing it back to life on modern systems. A month ago I released v3.0 of Status Line, my own bespoke z-machine for the Pico-8, and I was curious to understand more deeply the roots of the long-lived virtual machine. This blog post talks about the state of the original source, the porting process, and the invaluable role Justine Tunney's Cosmpolitan project played in bringing the Zork trilogy to a wide variety of modern computer systems.

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, computer, code · Missing: agents, macos, agent
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 · Missing: supports, reddit linkedin, podcasting
56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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