I wrote a book about how to work remotely

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Hey all. Today the book on remote working that I wrote for The Pragmatic Bookshelf has gone into beta. It's called Effective Remote Working. I didn't plan on writing a second book, but 8 months ago during a conversation with the publisher we agreed that it was the right time for a book like this. My first book was Become an Effective Software Engineering Manager, which I did a Show HN on before: https://news.ycombinator.com/item?id=22033129 That book has so far been successful with lots of great reviews and over $100,000 in net sales. A beta book with PragProg means that you get DRM-free access to the first 9 chapters, and the following 6 chapters will be delivered to your inbox as they're finished off, along with any fixes. It's available with free excerpts here: https://pragprog.com/titles/jsrw/effective-remote-work/ I'd love to hear your feedback, and if there are any bugs or errata then they can all be ironed about before the thing goes to print. Once again, I've had a great experience writing for PragProg, and would highly recommend them for anyone who wants to write a book for our industry. Thanks again, everyone.

Visit product View on Hacker NewsOct 20, 2021

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Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released

82%82% 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

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

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

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, inbox · Missing: mac, agents, macos

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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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