Manus operates as a multi-agent AI system, coordinating a team of sub-agents to complete various tasks, from travel planning to financial analysis, rather than relying on a single neural network.

Manus employs a planner agent that creates a master plan by breaking tasks into manageable subtasks, ensuring precise execution and efficient task management.

Manus is being called the most impressive AI tool ever tried, showcasing its capabilities as a sophisticated computer using AI, unlike its predecessors that were merely specialized chatbots.

Manus utilizes a technique called chain of thought injection, allowing agents to actively reflect and update their plans, enhancing stability and reasoning capabilities during complex tasks.

However, Manus faces challenges with coordination among specialized agents as tasks scale in complexity, which can hinder its effectiveness.

Manus exemplifies these trade-offs well, as its multi-agent orchestration significantly reduces per-task costs to around $2, compared to competitors like OpenAI's Deep Research.

To measure Manus' capabilities, the Gaia benchmark tests AI agents on reasoning, multimodal handling, web browsing, and tool proficiency, with humans scoring about 92% and OpenAI's deep research scoring around 74%. Manus achieved an impressive benchmark score of 86.5% on the Gaia scoring system, just a few points shy of the average human performance.

The executor agent in Manus combines outputs from completed subtasks into a final synthesized output for the user, showcasing its sophisticated dynamic task decomposition algorithm.

The advantages of Manus, such as UX refinements and thoughtful integrations, are vulnerable to competitors who can replicate these features, posing a risk to its market position.