What developers run in agent sandboxes
Workloads that need an isolated computer for an AI agent, and how to build each one.
45 pages
- Explore many solutions in parallel with sandbox forksFork one prepared sandbox into up to 100 copies.
- How to add a code interpreter to a chatbotGive each conversation its own sandbox with a stateful interpreter.
- How to build a browser-based online IDE on cloud sandboxesBack each workspace with a sandbox.
- How to build a coding interview platform with sandboxesPrepare a snapshot for each question.
- How to build a data analysis agent that runs Python safelyUpload the user's data to a sandbox, run the model's pandas code in a stateful interpreter there, and return tables and charts.
- How to build a Lovable-style AI app builder on sandboxesGive each project a sandbox made from a template snapshot.
- How to build a text-to-SQL agent that queries your database from a sandboxRun the model's SQL in a sandbox that can reach only your database.
- How to build an AI code review bot that runs the code it reviewsCheck out the pull request in a sandbox.
- How to convert Word documents to PDF on a server with LibreOffice headlessInstall LibreOffice in an isolated sandbox image, upload the file, run soffice --headless --convert-to pdf, and download the PDF.
- How to extract text from PDFs, scanned ones included, in a sandboxOpen each PDF in a throwaway sandbox.
- How to generate charts from LLM-written code in a sandboxRun the model's plotting code in a sandbox's code interpreter.
- How to generate unit tests with an LLM and keep only the ones that passRun each model-written test in a sandbox three times.
- How to give an AI agent memory that persists between sessionsKeep each user's agent in a named sandbox that pauses between sessions.
- How to give an AI research agent a sandbox to fetch pages and run codeGive the agent one sandbox per research question.
- How to give an LLM a code execution tool with function callingDeclare a run-command tool in your model's function-calling format, run each call in a sandbox, and return exit code and output.
- How to give every hackathon team a cloud dev environmentCreate one named sandbox per team from a starter image, give teams SSH and a public demo link, cap the spend, and stop them all by label.
- How to give every user their own cloud dev environmentGive each user a named sandbox that pauses when idle and wakes on the next request.
- How to grade student code safely in a sandboxRun each submission in its own throwaway microVM with the internet off and a time limit, run your tests against it, and record the score.
- How to have an AI agent set up any repository in a sandboxClone the repository into a fresh microVM.
- How to host MCP servers for your agents in sandboxesStart MCP servers in a sandbox.
- How to keep an AI agent running for hours in a cloud sandboxRun the agent in a Runtime sandbox, which has no time limit, start it with spawn, and reattach to its output from any process later.
- How to let a Discord bot run code in a sandboxDefer the interaction within 3 seconds, run the code in a throwaway microVM with no network, then edit the original reply with the output.
- How to let a Slack bot run code safelyAcknowledge Slack within 3 seconds.
- How to let an AI agent analyze Excel spreadsheets safelyUpload the workbook to a sandbox with the internet off.
- How to let an AI agent test your own API in a sandboxRun your API and the agent's tests in one microVM.
- How to let an AI agent upgrade dependencies and prove nothing brokeInstall the project in a sandbox, fork one copy per outdated package, test each upgrade alone, and fix only the failures.
- How to preview apps an AI agent buildsRun the agent's app in its sandbox.
- How to reward an RL policy by running its code in sandboxesRun each sampled program in an offline sandbox.
- How to run a browser automation agent in a cloud sandboxGive the agent a Linux desktop in a sandbox.
- How to run a coding playground for your usersRun each visitor's code in its own microVM sandbox.
- How to run an agent's CI on every pull requestUpload each pull request's code to a fresh sandbox.
- How to run an AI code migration safely in sandboxesRecord which tests pass on the old toolchain, let the agent port the code on the new one, and accept a port only if none of them fail.
- How to run background AI agents in cloud sandboxesTake each task off a queue.
- How to run end-to-end tests in parallel cloud sandboxesPrepare one sandbox with the app, its database and the browsers running, snapshot it, and run one test shard in each copy.
- How to run Jupyter notebooks headless in the cloudUpload the notebook to a sandbox.
- How to run linters and security scanners on your own code with an AI agentRun Ruff, Semgrep and npm audit on your code in a sandbox.
- How to run LLM-generated transformation code in a data pipelineRun each batch's model-written transform in its own sandbox, with the internet off.
- How to run scientific computing jobs in cloud sandboxesBuild an image with your numerical stack.
- How to run SWE-bench-style agent evals in parallel sandboxesBuild each task's environment once.
- How to run tree search over an agent's environment with sandbox forksMake each sandbox a search node.
- How to run untrusted code from an LLM safelyRun the code in a disposable microVM.
- How to run visual regression tests with stable screenshotsMake and compare screenshot baselines in the same pinned sandbox image.
- How to train small machine learning models on CPU sandboxesBuild an image with scikit-learn or CPU-only PyTorch, train in a sandbox with every vCPU busy, and copy the model file out at the end.
- Sandbox for a coding agent: give an AI agent its own computerGive the agent a Linux microVM with the repository cloned.
- Sandboxes for RL environments: run agent rollouts in parallelPrepare the environment once as a snapshot.