TermRover – a native tmux-first terminal for iOS and Android

Hacker News

I do a surprising amount of dev from my phone now: SSH into a box, attach to tmux, and drive couple of coding agents here and there. Termux gets me pretty far on Android, and I still love it for its simplicity. But once I had a few tmux sessions across a couple of hosts, I wanted something that reduced keystrokes and felt friendlier for driving AI agents, especially things like sending them images. On iOS, I couldn't find something that gave me a similar experience to Termux. So I built TermRover: a native iOS/Android terminal built around tmux sessions and windows, with shortcuts for the actions I kept doing over and over on mobile, while still trying to stay minimal. Short walk-through: https://termrover.sh/guide#quickrow It's free for normal terminal/SSH/tmux work. The paid tier unlocks themes and convenience extras for agent workflows: unlimited image attachments and voice mode. Mosh isn't supported yet, but I'm working on it. Honestly, I hadn't used Mosh before building this. Enough people have asked for it that I clearly need to support it. Happy to answer questions or hear what feels missing.

Visit product View on Hacker NewsJun 29, 2026

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

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 HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

56%56% predicted probability of success on TrustMRR, 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

47%47% 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

38%38% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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