Cosmo – Desktop agent with generated UI

Hacker News

Hey there! I’m Shiyuan, a recent college grad working on this. Cosmo lets you interact with your computer through generative UI. Examples: - Type “github action status for my website” → desktop dashboard of all the action run statuses - Speak “create a linear issue” → instant UI on desktop to select the assignee, labels, etc. It is integrated with GitHub, Vercel, Jira, Supabase, Linear, Posthog, Google Workspace etc. so people can see charts, make edits, and complete tasks through these generated interfaces. And everything happens on your desktop, it’s not another app window you have to switch to. We hope to use generative UI to kill app windows :P The concept is still early, and generation speed may be suboptimal (meant to be instant, faster than human navigation on traditional UIs). But I’d love to hear if it can boost productivity somewhere in your workflow. Feedback is greatly appreciated! Try: https://www.buildcosmo.com/

Visit product View on Hacker NewsApr 22, 2026

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Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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

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 · Missing: supports, reddit linkedin, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

44%44% 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

39%39% 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: google · Missing: mobile apps, ios, personal

35%35% 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

17%17% 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.

Correct prediction on native model

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