VSCode Working Memory – Capture everything in a single text file

Hacker News

It's a dead simple VSCode extension based on Cal Newport's idea of a single text file productivity system. Capture everything in a single markdown or text file. Specify the file and use shortcut to open it in new tab from any VSCode project/workspace. Also, there's a quick capture option to append line to the top of the file without opening it. That's it, nothing much. I have few simple ideas on how to extend this workflow without making, so any feedback or contribution is welcome. Here's Cal Newport explaining the gist of the idea: http://www.youtube.com/watch?v=3-MOxvedJXM&ab_channel=CalNew...

Visit product View on Hacker NewsAug 22, 2022

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

80%80% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

38%38% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · 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 · Missing: plus, platform, intuitive

22%22% 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

14%14% 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.

Correct prediction on native model

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