Orchid: Orchestrating Context Across Creative Workflows with Generative AI
Srishti Palani, Gonzalo Ramos

TL;DR
Orchid is a system designed to improve creative workflows with Generative AI by enabling users to specify, reference, and monitor context across multiple interactions, leading to more aligned and innovative outcomes.
Contribution
Orchid introduces a novel interface for managing context in complex, multi-session creative workflows with Generative AI, enhancing user control and creativity.
Findings
Participants produced more novel and feasible outcomes with Orchid.
Users reported greater alignment between intent and AI responses.
Orchid increased perceived control and transparency.
Abstract
Context is critical for meaningful interactions between people and Generative AI (GenAI). Yet mainstream tools offer limited means to orchestrate it, particularly across workflows that span multiple interactions, sessions, and models, as often occurs in creative projects. Re specifying prior details, juggling diverse artifacts, and dealing with context drift overwhelm users, obscure intent, and curtail creativity. To address these challenges, we present Orchid, a system that gives its users affordances to specify, reference, and monitor context throughout evolving workflows. Specifically, Orchid enables users to (1) specify context related to the project, themselves, and different styles, (2) reference these via explicit mentions, inline selection, or implicit grounding, and (3) monitor context assigned to different interactions across the workflow. In a within-subjects study (n=12),…
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