I forked JetBrains' new agent IDE to host Claude Code

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ThinkRail is JetBrains' open-source IDE shell for AI coding agents: worktree-per-tab, chat + file tree + terminal, but hardwired to one agent (Pi). My fork adds a plugin API so it can host others too, starting with Claude Code running in the same UI. What's new over upstream: - A prototype of real plugin system - Claude Code as a first-class citizen — config, IDE bridge, and terminal status all wired in as a builtin plugin, so you get Claude Code sessions in the same worktree-scoped UI as `pi`. - Seven other builtin plugins split out the same way: blueprint (interactive specs), PDF preview, branch graph, a live drawing/visualize surface, and file-type icons Nightly builds via a Homebrew tap are provided.

Visit product View on Hacker NewsSep 17, 2026

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

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.

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

57%57% 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

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

28%28% 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

24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

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