Hello everyone,
I’ve been using Gemini AI Studio and have some product ideas that I believe could significantly enhance its utility and user experience. I’d love to share them and hear what others think.
My Initial Product Ideas for Gemini AI Studio:
- User-Defined Prompt Templates with Organization:
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Capability: Allow users to create and save their own custom prompt templates.
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Organization: Support organizing these templates using a nested, directory-like structure (e.g., folders and subfolders) and also allow tagging for easier search and filtering.
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Rationale: Different scenarios and AI interactions have varying needs, often highly personalized, which official templates can’t always cover. This would allow users to tailor prompts for specific, recurring tasks.
- Multiple Chat Windows/Tabs on a Single Page:
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Capability: Support opening multiple independent chat sessions within the same AI Studio page or interface.
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Rationale: Our brains often spark new ideas while we’re engaged in one task. If we could ask new questions or explore new threads without waiting for the current model’s response or losing the context of the ongoing chat, our creativity and productivity would be significantly boosted.
- Create New Chats from Existing Chat History (Contextual Forking/Fine-Tuning):
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Capability: Allow users to initiate a new chat that directly inherits the context from a previous or ongoing chat.
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Rationale: There’s a concept in large models often referred to as “in-context learning” (or what I loosely termed “prompt fine-tuning” in the sense of the model becoming more attuned). The longer we converse, the better the model seems to understand our intent and provide more accurate answers. However, we often don’t want a single chat window to become too cluttered with diverse topics. If we could leverage this “tuned” context for a new, related topic without displaying the entire previous conversation, the experience would be much cleaner, and it would enhance reusability.
- Support for MCP (Machine Coordination Protocol) and Google Ecosystem Integration:
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Capability: Integrate support for MCP to allow Gemini AI Studio to seamlessly interact with other Google Workspace apps.
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Rationale: Google has a rich ecosystem of powerful tools like Google Translate, Google Docs, Google Keep, Google Photos, etc. If Google could first enable deep integration within its own suite, allowing AI Studio and Gemini to easily access and utilize these services, it would likely accelerate the entire industry’s adoption of MCP.
- Dedicated User Question History Repository:
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Capability: Implement a feature specifically for saving and organizing all questions a user has ever asked the AI.
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Rationale: Currently, user questions are scattered across various chat histories, making it difficult to quickly collect and review one’s own inquiries. It’s often said that “questions are more important than answers.” This collected history would be invaluable not only for individual users for reflection and knowledge management but also for AI providers as precious data for improving customized services and understanding user needs.