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Weave – A tool to track how your habits work together

Hacker News

Weave – A tool to track how your habits work together

In 2014, I read the most impactful advice on how to progress long-term goals: In the book Fat Loss Happens on Monday, Josh Hillis opened Chapter 6 with an anecdote about how he catapulted himself from a novice to a trainer who got results by convincing his clients to keep a food log. After success with that, I ran with the idea of tracking small movements towards a large goal. It felt like carving something out with many small, precise cuts. I kept logs for EVERYTHING, and then when I reviewed them together, I could see how pursuing one goal affected the others. I made Weave to make that comparison more powerful. Weave is an event-based structured journal. It allows you to focus on different parts of your life and then makes it more straightforward to see how they fit together. Weave compresses and packages your data every month so you can download and store it forever. You can play around with the demo here: https://www.idiotlamborghini.com/strategies/weave Thank you for reading!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
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best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
27%27% 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
20%20% 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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