Kosshi
Simple, fast outliner for Mac and iPhone.
Kosshi launched on May 23, 2026 with 96 votes, #343 of 20,538 launches that month and more than 95% of that year's launches.
What it does
Kosshi is a simple native outliner for macOS and iOS. Fast and focused outline editing.
Kosshi is a native outliner for Mac, iPhone, and iPad with keyboard editing, Markdown, images, and iCloud sync.
Kosshi is built with Apple frameworks. Its custom rendering engine is designed for responsive typing, row movement, and collapsing. Data is stored locally on your device. Sync uses Apple's iCloud (CloudKit), where sync data is stored in your iCloud account. No separate Kosshi account is required. The data structures and layout engine are designed for large outlines. Initial rendering, scrolling, editing, and search are tested with the goal of keeping outlines usable beyond 100,000 rows. Press Tab to indent a row and create a hierarchy. Collapse sections or drag rows to rearrange the outline. Zoom into a row to show only that row and its children. Use the breadcrumbs to move up or return…from kosshi.app
Does a similar job
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Bike – macOS Native Outliner2022 · hogbaysoftware.com · ▲513Bike’s most original feature is the “fluid” text editing. Lots of text editors have animated some interactions (cursor movement, insert newline, etc), but I think Bike is the first designed from the ground up to support fluid editing. Give it a try, it feels different. (movie on home page if you don't have Mac) Other Features: • In text mode Bike works like a normal text editor. In outline mode rows are constrained to outline hierarchy. • .bike file format is HTML subset, so files are easy to parse and manipulate. Bike also supports .opml and .txt. • Scriptable via AppleScript. Javascript…



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Source: Product Hunt launch ↗
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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