Step 1: Receive goal
You describe what you want done in natural language. Computer analyzes the goal and identifies the required steps.
Step 2: Build dependency graph
Computer decomposes the task into subtasks with dependencies, priorities, and completion criteria.
Step 3: Route to models
Each subtask is assigned to the best suited AI model from the pool of 19. Claude for reasoning, Gemini for research, Nano Banana for images, and so on.
Step 4: Execute in sandboxes
Sub agents work in isolated cloud environments with real browsers, file systems, and authenticated connectors.
Step 5: Deliver results
Finished artifacts (documents, spreadsheets, deployed apps, emails) are delivered to you or to connected services.
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What does multi model orchestration actually mean?
Instead of being locked to one AI company's models, Computer picks the best tool for each part of the job. Think of it like a project manager who assigns the right specialist to each task: one person for writing, another for data analysis, another for design. Except here, the "specialists" are different AI models from Anthropic, OpenAI, Google, and xAI, each with different strengths.