STAX IDE – A zoomable macOS canvas of terminals and tools

Hacker News

Hi HN. STAX IDE is a macOS app where every terminal session, code editor, and file browser is a movable, resizable window on a single zoomable canvas. `Cmd+wheel` to zoom out and see the whole workspace; zoom in to one window and use it like a normal app. I built it because I was running 8-10 Claude Code / Codex shells in parallel and tabbed terminal apps kept losing my place. I wanted to see every shell at once and drag them around like Post-its. And have my browsers and notes in there too. Implementation choices that might be interesting: • AppKit, not SwiftUI. I needed manual frame control during drag/zoom to avoid AppKit's display-cycle re-entrancy guard, and got it more reliably out of straight NSView land. • SwiftTerm (Miguel de Icaza's emulator) for VT100 + real PTYs (fork + openpty). One `LocalProcessTerminalView` per tab. OSC 7 → cwd → tab title. • `NSScrollView.magnification` for canvas zoom. Cmd+wheel events are coalesced to one mag-update per display frame and the resync broadcast is hopped to the next runloop tick. Earlier versions used to SIGTRAP inside `_postWindowNeedsLayoutUnlessPostingDisabled` because the broadcast was re-entering AppKit's layout pass under aggressive zooming. • Intentionally human-grep-able. No SQLite, no proprietary format. • NSPasteboard drag-and-drop. Finder→canvas drops a folder and spawns a new stack with that folder as cwd. File-panel→terminal drag inserts the absolute path at the cursor. •`NSTextStorageDelegate.processEditing` for syntax highlighting in the editor panels. 22 languages, extension auto-detect, plus a Sublime-style status-bar language picker. * macOS only. Install: brew install --cask vbario/staxide/staxide Site / DMG releases: https://staxide.com Built solo, used daily, lots of rough edges. Bug reports and corrections both welcome.

Visit product View on Hacker NewsMay 27, 2026

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

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 · Strong signals: para · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

56%56% 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: apps, para · Missing: mobile apps, ios, personal

56%56% 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

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

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

23%23% predicted probability of success on AppSumo, 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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