TryCase is a cloud-based service that provides disposable Linux environments specifically designed for coding agents. It enables developers to automate the verification of their applications by allowing agents to run code, test functionality, and return tangible proof of success or failure. By offloading the execution and verification process to isolated cloud environments, developers can ensure that their applications perform as expected in a Linux runtime without relying solely on local testing. TryCase is designed to integrate seamlessly into existing AI coding agent workflows, providing a consistent way to verify changes, reproduce bugs, and perform end-to-end testing.

Some of the key features are:

• Disposable Environments: Each environment is a temporary, isolated Linux machine that is destroyed after the task is complete to ensure security and prevent state leakage.
• Agent Integration: Comprehensive CLI support and installable skills allow coding agents like Claude, Cursor, and others to autonomously manage environments, upload code, run tests, and collect evidence.
• Comprehensive Evidence Collection: Automatically generates and retrieves screenshots, video recordings, terminal logs, and custom artifacts to prove that code changes work as intended.
• Headless and Desktop Modes: Supports headless mode for CLI-driven automation and desktop mode for tasks requiring a visible Linux desktop to interact with browser-based Oauth, CAPTCHAs, or other human-centric UI steps.
• Flexible Compute Scaling: Offers multiple runner sizes ranging from nano for lightweight scripts to large for complex monorepos and Docker-heavy applications.
• Secure Secret Management: Provides encrypted storage for project-specific environment variables and secrets, ensuring sensitive data is only used within authorized test environments.

To operate the service, users or their agents use the TryCase CLI to initialize projects and manage the lifecycle of disposable environments. The process involves creating a project, optionally importing secrets, uploading the relevant local working tree, and executing tests via terminal or browser automation commands. Once the workload finishes, the agent retrieves the required proof artifacts and invokes a destroy command to clean up the environment and stop billing. This workflow ensures that developers can continuously verify their applications with high confidence while maintaining clean and reproducible test environments.

Some common use cases include:

• Verifying Bug Fixes: An agent reproduces a bug in a TryCase environment, applies a fix, and then runs automated tests to prove the bug no longer exists before submitting a pull request.
• Automated Feature Testing: Developers instruct agents to build new features and verify them in a clean environment, ensuring that the code functions correctly in a standard Linux runtime.
• Dependency Upgrades: Agents test dependency updates in TryCase to verify that the changes do not introduce runtime regressions or break critical user flows.
• End-to-End Visual Verification: Using the browser automation capabilities to navigate through a web application, capture screenshots, and record videos to verify UI layouts and interactive components.
• Manual Flow Assistance: Using desktop mode to allow agents or humans to interact with complex authentication steps, such as 2FA or external identity provider consent, which cannot be automated via standard headless scripts.