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Adding a logic channel next to pure text

Hacker News

Adding a logic channel next to pure text

This is an experiment for better communication. If anyone's got time for feedback (positive or negative), I'd love to hear it :) Especially about: • [core idea] Do you think the core idea of some logical channel for info display is promising, or do you think it's not worthwhile? • [current utility] Does the current logical channel help you understand the text better? • [reader interface] Assuming we have the logical markup of a text, how can we use that to help readers grasp the parts of the text they're interested in faster? How should we display the information? • [author interface] What would an ideal author interface look like, for marking up text while writing it?

Visit productView on Hacker NewsOct 13, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
66%66% 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
46%46% 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
41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · 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 · Missing: mobile apps, ios, personal
28%28% predicted probability of success on TrustMRR, 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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