Navigating Remote Work

Hacker News

I wrote a book for personal guide for remote workers that want to be more effective at it. There are great playbooks now for how to move an organization to remote work, run distributed product teams, and manage things like HR remotely. But most of the issues with remote work that cause *people* to want to return to the office are personal issues related to how they work. Issues like: 1. Boundaries 2. Communication 3. Productivity 4. Mindset People become isolated, procrastination distracts them, they have issues keeping up with their coworkers, and they can't separate work from home. The book is a guide for those that want to solve these issues and be a more effective remote employee. Free chapter and table of content available here: - http://davidtate.org/files/nrm/Sample-Chapter-NavigatingRemoteWork.pdf - http://davidtate.org/files/nrm/Sample-TOC-NavigatingRemoteWork.pdf Full landing page: https://navigatingremotework.com/ Twitter thread explaining a bit more here: https://twitter.com/mixteenth/status/1394643365547888640 Thanks in advance for any and all feedback!

Visit product View on Hacker NewsMay 31, 2021

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

71%71% 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 · Strong signals: para · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

29%29% 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

28%28% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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