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Monogram aims to create the "graphical user interface for AI" by combining the speed of voice input with the efficiency of visual output. This model avoids the slowness of listening to AI responses, which founder Eren Bali notes is four times slower than reading, creating a more frictionless user experience.
The dominant AI interface will be a universal conversational layer (chat/voice) for any task. This will be supplemented by specialized graphical UIs for power users needing deep functional control, much like an executive sometimes needs to edit a document directly instead of dictating to an assistant.
While CLIs were an important stepping stone for agentic AI, the industry is rapidly moving back to rich Graphical User Interfaces (GUIs). These new UIs are designed for simultaneous collaboration between a human user and an AI agent, offering a more powerful and intuitive experience.
Current chat interfaces are compared to the command-line: they require users to learn a specific, procedural way of communicating ('prompt engineering'). New interaction models, which allow for natural, multimodal communication, could be AI's 'GUI moment,' democratizing access by letting users focus on the task, not the tool.
Power users of AI agents believe the ideal user interface is not graphical but conversational. They prefer text-based interactions within existing chat apps and see voice as the ultimate endgame. The goal is an invisible assistant that operates autonomously and only prompts for input when absolutely necessary, making traditional UIs feel like friction.
Until brain-computer interfaces are viable, the highest bandwidth way to interact with AI is through speaking commands (voice out) and receiving information visually (visual in), whether on a screen or via glasses. This is because humans speak significantly faster than they can type.
User expectations for AI responses change dramatically based on the input method. A spoken query demands a concise, direct answer, whereas a typed query implies the user has more patience and is receptive to a detailed, link-filled response. Contextual awareness of input modality is critical for good UX.
To feed AI models the rich context they require, advanced users are shifting from typing to speaking. They use high-fidelity, noise-canceling microphones to 'whisper' detailed prompts, dramatically increasing the amount of information provided per second and improving AI output quality.
The true evolution of voice AI is not just adding voice commands to screen-based interfaces. It's about building agents so trustworthy they eliminate the need for screens for many tasks. This shift from hybrid voice/screen interaction to a screenless future is the next major leap in user modality.
The interface for AI agents is becoming nearly frictionless. By setting up a voice-to-voice loop via an app like Telegram, users can issue complex commands by simply holding down a button and speaking. This model removes the cognitive load of typing and makes interaction more natural and immediate.
The magic of ChatGPT's voice mode in a car is that it feels like another person in the conversation. Conversely, Meta's AI glasses failed when translating a menu because they acted like a screen reader, ignoring the human context of how people actually read menus. Context is everything for voice.