Why Manus Chooses E2B: Inside the Architecture of a General‑Purpose AI Agent

Manus is a general‑purpose AI agent that runs in a full sandbox environment to deliver production‑grade results, unlike single‑LLM chatbots. User prompts are first sent to a Planner Agent , which breaks the task into subtasks, then an Executor Agent uses a variety of tools—from web browsing to terminal commands—to complete them [1][2].

The sandbox is built on E2B's Firecracker micro‑VMs , which AWS developed to launch a complete virtual computer in roughly 150 ms, far faster than Docker containers that need 10–20 s and cannot provide a full OS [3][4]. Manus requires 27 different tools (Chromium browser, terminal, Python, JavaScript, Bash, etc.), so a full VM is essential for human‑like operation [5].

From an architectural standpoint, Manus adopts E2B's self‑hosting deployment mode . By running E2B on its own machines, Manus retains full control over the sandbox infrastructure and simplifies operations; the team reports a half‑day implementation and deployment time [6][7]. Building the infrastructure from scratch would demand a dedicated 3–5‑person team for several months, diverting focus from product and R&D.

Session persistence is a key feature: sandbox sessions can run for hours and, for paid users, persist up to 14 days, enabling complex tasks that take tens of minutes. The sandbox also supports pause and resume , allowing agents to wait for user input, credentials, or human verification before continuing.

Multi‑tenant isolation is achieved by giving each user an independent sandbox instance, preventing task interference and ensuring security. Firecracker’s strong isolation guarantees that malicious code in one sandbox cannot affect the host or other sandboxes, addressing scalability and safety concerns as the user base grows [9].

Looking ahead, Manus plans to run agents on additional operating systems such as Windows and Android, expanding the range of tasks beyond web‑only workflows. This future vision requires a sandbox platform with flexibility and scalability, which E2B’s architecture provides [10].

Real‑world cases demonstrate the sandbox’s value: the Chinese edition of the Financial Times used Manus to generate a 3D‑printed model of a decade of US Treasury data, and a Dubai consultant produced a 50‑page content strategy document costing $6–7 to generate but worth thousands in the consulting market. Both examples show end‑to‑end task execution—from data analysis to visual design—within isolated virtual computers.