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I wrote a $5 guide on Digital Minimalism for Creators

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I wrote a $5 guide on Digital Minimalism for Creators

I'm a creative who was drowning in tools, tabs, and distraction. I used digital minimalism to rebuild my focus and workflow. I turned what I learned into a 90-page e-book for creators who want less chaos and more clarity. It’s called Digital Minimalism for Creators: How to Focus in a Distracted World . It includes: - A minimalist toolkit - Focus ritual guide - A 7-day digital reset challenge Link (Gumroad): https://gum.new/gum/cmcbwwomr000y04jyhqs0a5aw Happy to answer questions!

Visit productView on Hacker NewsJun 25, 2025
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Launch Intel predictions

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
28%28% 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
16%16% 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.

Correct prediction on native model

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