E2B does one thing and its documentation reflects that discipline. The thing is running untrusted code, specifically code a language model just generated, inside an isolated Linux microVM that spins up in a fraction of a second, does its work, and goes away. If you have built a data analysis agent, a code interpreter, or anything where the model writes and runs Python, you have already run into this problem, and if you solved it by calling exec on your own server then you have a security incident waiting for a slow afternoon. The docs are organised in three parts: quickstarts for creating a sandbox, connecting an LLM, handling files and installing packages; use-case examples including computer vision agents and CI/CD flows; and a full SDK reference for Python and JavaScript.
The quickstart genuinely is quick, which matters more than it sounds. A significant amount of infrastructure documentation buries the first working result behind concept pages, and a reader who gets something running in five minutes reads the concept pages afterwards with far more attention. There is one detail I want to call out because more projects should copy it. The documentation is published as a public MCP server at docs.e2b.dev/mcp with no authentication, and also as plain markdown.
That means your coding agent can read the current docs directly rather than working from whatever it half-remembers from training. For a tool whose entire audience is people building with agents, making the docs machine-readable is exactly the right instinct, and it measurably reduces the amount of confidently wrong generated code you have to debug. Pricing is clear. Hobby is free with a one-time $100 of usage credits, up to 20 concurrent sandboxes, one hour sessions and 10 GiB storage.
Pro is $150 a month plus usage with 100 concurrent sandboxes and 24 hour sessions. Enterprise starts at a $3,000 monthly minimum. Compute is billed per vCPU-second and per GiB-second. The $100 free credit is generous for learning and prototyping, and you will get a long way on it.
The gap between free and $150 is the awkward part, because the person running a small production workload with modest traffic has nothing sensible to buy. As education, this is deliberately narrow. It teaches a capability, not a discipline. You will not learn agent architecture here, or evaluation, or orchestration.
You will learn how to execute generated code without handing an attacker a shell, and that is a genuinely important thing to know that a lot of otherwise competent builders get wrong. What the docs do well beyond the mechanics is explain why isolation is necessary, which turns a configuration exercise into an understanding of the threat model. The use-case section is the weakest part and the most improvable, since a few end-to-end worked examples would help people see where this fits in a larger system. Three point nine.
Clear, fast, well-scoped technical documentation with unusually good machine-readability, limited only by how narrow the subject is.