A terminal editor that can discuss with OpenCode and Pi

Hacker News

Since vibe coding, I write code by hand less and less, and spend more and more time discussing with the AI. I always need to tell the AI exactly which part of a document I have thoughts about. I have to ctrl-c/ctrl-v all day long — it's given my fingers tendonitis. So here comes microNeo, an AI Partner. - Open a markdown document with microNeo and select the text you want to comment on - Press <alt-enter> to open the input box, and write down your thoughts - Press <alt-enter> again to send it to the AI. The AI will then receive your comment.

Visit product View on Hacker NewsJul 28, 2026

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Actual performance

2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: coding, code, open · Missing: mac, agents, macos

93%93% 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.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

34%34% 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

26%26% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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