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iOS Client for Claude Code SDK

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iOS Client for Claude Code SDK

I just released an iOS app that lets you start a new Claude Code instance from your phone. There are a lot of apps to transfer or resume Claude sessions from laptop -> phone but I wanted something that worked 100% from my phone and wasn't dependent on a connection to my laptop. How it works: spins up a virtual machine for each user (on fly.io), clones a GitHub repo, and spins up a Claude Code instance. The VM spins down after 2hrs of inactivity. I've been using it to open small PRs for new ideas or ask questions about my codebase when ideas pop into my head on the go. lmk what you think!

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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, claude, apps · Missing: agents, macos, agent
98%98% 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
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: just released, ide, io · Missing: https docs, excited, exist
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps · Missing: mobile apps, personal, entrepreneurs
51%51% 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
30%30% 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
26%26% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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