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Output – An AI Agent That Controls Your Computer (Mac and Windows)

Hacker News

Output – An AI Agent That Controls Your Computer (Mac and Windows)

Hey HN, After months of building, we're excited to share Output — the first AI agent that can truly control your computer. You can speak or type instructions like: “Fill out this job application using the info in this PDF” “Edit this video in DaVinci Resolve” “Schedule a Zoom call and send the invite” Output understands your intent and directly clicks, types, and navigates apps across your system — without relying on scripts, plugins, or integrations. It's like giving your computer a brain. Works on both Mac and Windows No setup or scripting required Handles real apps like Chrome, Excel, Notion, Zoom, etc. Designed for general-purpose use — students, founders, creatives, you name it We're still early and improving every day, but we'd love your feedback. Live demo + early access: https://theoutput.co/ You can follow us on X: https://x.com/theoutputai Happy to answer any questions and go deep on how it works!

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Actual performance

15points
14comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agent, apps · Missing: agents, macos, cursor
95%95% 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
79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps, video, month · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist
40%40% 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
18%18% 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
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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