Ne
New Ensō – first public beta
Hacker NewsNew Ensō – first public beta
Ensō is a writing tool that helps you enter a state of flow by separating writing from editing and thus making it harder for you to edit yourself - https://enso.sonnet.io/ After 6 years and 2 million words of daily writing I feel like I've learned enough to make Ensō simpler and more accessible. Related thread: https://news.ycombinator.com/item?id=38025073
Share cardActual performance
251points
87comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released73%73% 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 HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% 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, revenue15%15% 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, crypto0%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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