macOS status bar app for better interaction with web AI chats

Hacker News

Hi HN! Heydi's main goal is to reduce context switching. All interactions can be initiated with keyboard shortcut to either open a chat window or send an audio message to a chat. No need to stay on a chat window waiting for response or keep it in focus – you'll be notified once it's ready. It supports ChatGPT, Claude, Copilot, Gemini and Perplexity. Looking forward for feedback!

Visit product View on Hacker NewsMar 19, 2024

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, claude · Missing: agents, agent, cursor

96%96% 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 HackersFits the IH revenue-focused audience · Strong signals: supports, gemini · Missing: reddit linkedin, podcasting, created

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

50%50% 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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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 · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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