Description (The “What”)
I am proposing a new capability for the Gemini App (web and mobile) that allows it to natively ingest and process shared Gemini conversation links (gemini.google.com/share/…) as direct input context. Instead of a user having to manually copy and paste the text from a shared conversation, they should be able to provide the URL, and Gemini should “read” that history to understand the preceding context, logic, and user-to-AI interaction history.
Use Case (The “Context”)
This feature addresses several critical pain points in the current workflow:
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Preservation of Interaction History: Currently, copy-pasting from a shared link merges user prompts and AI outputs into a single text block, making them extremely difficult to distinguish or re-parse. The specific phrasing of the user’s prompts—which are vital for context and intent—is often lost or difficult to format correctly in a new chat.
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Multi-Context Aggregation: Users often need to synthesize information from multiple “Canvases” or research threads. Presently, this requires saving each Canvas as a separate document and uploading them as attachments to a new context. This is a high-friction workaround for what should be a simple link reference.
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Formatting Fidelity: Transferring text via copy-paste frequently breaks Markdown tables, code blocks, and LaTeX formulas. Reading the context directly from the source link ensures 100% fidelity to the original structure.
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Deep Research Chaining: When using Gemini Deep Research, the resulting high-context reports are massive. Chaining these reports into new, actionable workstreams (e.g., “Write a project plan based on the research in Link A and Link B”) is currently blocked by character limits and the “copy-paste tax.”
Value (The “Impact”)
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Recursive Power: Allows users to “chain” different Gemini capabilities together by using the share link as a bridge between specialized sessions.
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Workflow Efficiency: Eliminates the need to save/export Canvases as files just to re-import them into Gemini.
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Contextual Integrity: By reading the link, Gemini understands the entire dialogue history (User + AI), not just a disconnected block of text.
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Accuracy: Gemini can access the structured metadata of the conversation more reliably than a raw text paste, preventing errors in complex data or code.
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Competitive Edge: This positions Gemini as a truly collaborative and recursive platform where insights can be handed off between projects and users without manual data migration.
Community Tag Suggestions: Gemini App, Feature Request, Deep Research, Shared Conversations, User Experience, Workflow Optimization