Imagine having a personal assistant who doesn't just give you a list of links, but actually navigates the web, coordinates with your friends' assistants, and handles the logistics of your next vacation.
That's the promise of the new wave of "AI Agents," and we're moving past simple chat boxes into tools that can actually do things for us.
The Simple Version
Think of these three agents like different types of travel concierges. Muse is the hyper-efficient pro with a neatly organized clipboard who gives you a table of options instantly.
GrokBot is the visual guide who pulls out a physical map and takes photos of the listings to show you exactly what he's seeing on the screen.
Instinct is the mysterious fixer who works entirely via text; you don't see him doing the work, but he can call other fixers (other people's agents) to coordinate your group's schedule behind the scenes.
How It Actually Works
The User Experience Gap
The testers used a specific prompt: finding an Airbnb in Bear Valley for January 14th through 17th that sleeps three and has an EV charger. The results varied wildly in how the information was delivered.
Instinct delivers results via iMessage or WhatsApp. As Michael Galpert explains, it uses "cute little emojis to indicate that it had did it," but the results are basic text and links, requiring the user to click through each one manually.
GrokBot takes a more visual approach, providing browser screenshots and maps. This allows the user to see the agent's process and even "take over" the browser session if they want to finish the task themselves.
Muse focuses on structured data. Instead of just links, it generates tables with ratings and cancellation dates, making it much easier for a human to compare options at a glance.
The Speed Factor
One of the biggest friction points in AI agents is latency. The video highlights a massive difference in how these tools feel during a live conversation.
Instinct and GrokBot often take 5 to 10 minutes to return complex search results. This creates a "disconnect" where the user leaves the app and waits for a notification, breaking the flow of the interaction.
Muse, by contrast, was described as "near instant" for many follow-up questions. This speed transforms the experience from a "request-and-wait" transaction into a real-time conversation.
Multiplayer Agents and Coordination
Instinct introduces a concept called "multiplayer agents." Instead of a group chat where an AI reads every message (which is computationally expensive and noisy), each person has their own agent.
These agents communicate with each other in the background. If you and a friend are planning a trip, your Instinct agent and their Instinct agent coordinate schedules and preferences—like the need for an EV charger—to find a solution that fits everyone.
Technical Deep Dive
Under the hood, these tools are moving from simple LLM completions to Agentic Workflows. While a standard chatbot predicts the next token, an agent operates in a loop: it perceives the environment (the web), reasons about a plan, takes an action (clicks a button), and observes the result.
GrokBot's use of screenshots suggests it utilizes a Vision-Language Model (VLM) to interpret the DOM (Document Object Model) of a webpage visually, rather than relying solely on HTML scraping. This is often more robust because it sees the page exactly as a human does.
The mention of Zapier MCP brings up a critical piece of modern AI architecture: the Model Context Protocol. MCP is an open standard that allows developers to provide a consistent way for LLMs to access data and tools without writing custom integrations for every single model version.
By using MCP, an agent can connect to over 8,000 apps while maintaining strict permission boundaries. For example, you can grant an agent the power to read and draft emails but explicitly block the "Send" action, preventing the agent from autonomously emailing your boss a hallucinated report.
Instinct's "agent harness" likely involves a sophisticated state-management system that allows the agent to maintain context over long periods (the 5-10 minute wait) and a routing layer that handles the agent-to-agent communication protocol for its multiplayer features.
Why This Matters
We are witnessing the shift from Generative AI (which creates content) to Agentic AI (which executes tasks). The difference is the move from "Tell me how to book a trip" to "Book the trip for me."
The competition between these three models shows that the "winner" won't just be the one with the smartest model, but the one with the best UX integration. Whether it's the invisibility of iMessage or the structure of a table, the interface determines how much we trust the agent with our credit cards.
Furthermore, the move toward "multiplayer" agents suggests a future where our digital twins handle the mundane friction of human coordination, leaving us to only make the final high-level decisions.