JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents

Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, audio clips, UI elements, storyboards, slides, and other creative assets, real-world creative work requires more than isolated prompt-output interactions. It involves references, drafts, alternatives, edits, failed attempts, version relations, tool actions, evaluation signals, and human feedback, which together form an evolving project state. Existing prompt-based, chat-based, and node-based generation systems only partially support this state, as they often discard intermediate context, rely on linear conversations, or require manually specified workflows. Recent commercial systems indicate a shift toward agent-assisted creative production, but their closed architectures make it difficult to study how agents represent context, choose tools, revise artifacts, recover from failures, and maintain consistency over time. To address this gap, we introduce JarvisHub, a canvas-native creative agent harness for long-horizon multimodal creation.

Introduction. Recent advances in multimodal generation have made high-quality images, videos, audio clips, UI elements, and other creative assets substantially easier to produce [7, 8, 10, 12, 14, 17, 23, 25, 33, 39, 41, 42]. These models are increasingly used in visual communication, UI/UX design, storyboarding, video production, slide-deck creation, and marketing content generation. Practical creative work, however, rarely follows a single promptoutput interaction. Creators typically collect references, specify styles or characters, plan layouts or shots, generate multiple candidates, revise local details, compare alternatives, incorporate feedback, and assemble intermediate results into a final deliverable. These intermediate materials—including prompts, reference images, drafts, candidates, edits, failed attempts, versions, and feedback—are not incidental by-products of creation. They form the evolving state of a creative project and provide the context needed for subsequent planning, revision, and evaluation. This project-state view creates a concrete challenge for creative agents.

Discussion / Conclusion. Why should the canvas be treated as an agent workspace? The canvas is useful not only because it gives users a visual interface, but because it can serve as a shared workspace for both humans and agents. In JarvisHub, prompts, references, candidates, edits, versions, dependencies, and feedback are represented as typed and addressable canvas nodes and links. This turns the canvas into both an external memory and an action space for the agent. Users can inspect and guide the same state that the agent reads and modifies. As a result, the agent can reuse prior artifacts, perform local updates, maintain dependencies, and continue unfinished work without hiding the process in private tool calls or transient chat history. What can an open harness enable for future creative-agent research? An open creative-agent harness can support research artifacts beyond a single system demonstration.