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Knify turns agent output into durable, shareable, interactive canvases. Instead of agents only replying with text, they emit structured canvases that can be viewed, linked, updated, forked, embedded, and consumed like APIs. 
Agent work -> structured artifact -> stable link -> reusable app/API surface

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The core idea

Canvas is the missing separation layer between agents and applications. Agents can change. Viewers can change. Workflows can change. The canvas remains the stable artifact.

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What Knify provides

LayerRole
Knify ProtocolDefines the canvas schema, blocks, events, actions, provenance, and exports
Knify HubStores canvases, versions, event streams, permissions, forks, and API access
Knify ViewersRender canvases on web, iPad, mobile, embeds, and branded surfaces
Agent AdaptersLet Cursor, OpenClaw, Claude Code, Python agents, and custom workflows emit canvases
Widget RegistryProvides standard and custom blocks without breaking portability

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First wedge

Start with interactive AI reports for agents. That wedge is concrete: agents produce reports with text, metrics, tables, charts, logs, tasks, images, and share links. Once users understand that value, expand into live canvases, exported APIs, applets, custom widgets, and self-hosting.

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Practical recommendation

Build the static report plus hosted link version first. Dogfood it with PixelFix audits or agent code-review reports. Add live updates, API exports, and applets after the core artifact is useful.