Co

Coyote – Wildly Real-Time AI

Hacker News

Coyote – Wildly Real-Time AI

Hey all, we just shipped coyote. it's an ai assistant but built different — everything runs async and feels way more natural. You text it, it handles work in the background and you can keep talking to it. No more stop button. Instead of creating another app we put it in WhatsApp (iMessage coming soon) so you can just text it for free and get the feeling. The core idea: most ai assistants make you sit there waiting for an answer. coyote's like texting a friend. you ask it to grab something for you, they say "on it," and you just keep chatting while it's out getting it. no awkward silence, no being stuck. Built it to handle real tasks — emails, calendar stuff, research, whatever. all non-blocking. Everything happens concurrently so you're never left hanging. We're still early but it's live and working. Happy to answer questions or get feedback. We've also worked hard to make it snappy, and friendly. Try it out and would love some feedback! Thanks!

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Actual performance

7points
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Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, tasks · Missing: mac, agents, macos
91%91% 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 · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, 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
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.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly, soon · Missing: plus, platform, intuitive
36%36% 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, revenue
21%21% 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 · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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