Cy, the time traveling terminal multiplexer

Hacker News

cy is a new terminal multiplexer (akin to tmux, screen, et al.) that records your terminal sessions so that you can replay and search through them at your leisure. It comes out of the box with a powerful fuzzy finder and uses Janet, a Lisp-like programming language, for configuration. As someone who does all of their software development in the terminal with text-based tools, I came to believe that it would be useful to be able to play back and search through everything that I do. I also felt like terminal multiplexers were stuck in a rut, and could be much more than what they are. cy was born from the idea that the terminal is a powerful medium that has yet to reach its full potential. A better terminal multiplexer will help it get there. cy is still experimental. If you encounter any issues or have suggestions, feel free to create an issue on GitHub or reach out! cy is open-source software (MIT license) and forever will be.

Visit product View on Hacker NewsJul 19, 2024

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

81%81% 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

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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

TrustMRRLess likely to generate early MRR · 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

15%15% 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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