TryCase.

TryCase

TryCase provides disposable Linux desktop environments that empower AI coding agents to run, test, and verify applications autonomously. Instead of trusting code changes blindly, developers receive concrete proof—screenshots, video recordings, and logs—showing exactly how their agent-tested application performs in a real browser before deployment.

Product Highlights

• Disposable Linux Desktops: Spin up isolated, pre-configured Linux environments on demand that automatically clean up after testing, eliminating local setup overhead and environment inconsistencies.
• Agent-Native Integration: Install skills directly into Claude, Codex, Cursor, or any coding agent with a single command, enabling agents to launch environments, execute commands, and control browsers programmatically.
• Automated Visual Proof: Capture screenshots, video recordings, and terminal logs from every test run, creating auditable evidence that code changes work as intended.
• Iterative Self-Healing Tests: Agents can detect failures, apply fixes, and retest in a loop until flows pass, reducing manual intervention and accelerating debugging cycles.
• Real Browser Automation: Control headless browsers to simulate real user interactions—clicking, filling forms, and verifying UI states—just as a human tester would.

Use Cases

• Pre-Merge Verification: Have your coding agent test pull requests end-to-end before human review, catching functional and visual regressions automatically.
• Bug Reproduction & Resolution: Agents reproduce reported bugs in isolated environments, apply fixes, and provide before/after proof showing the issue is resolved.
• Dependency Upgrades: Validate that library updates don't break critical user flows by running the full application in a fresh environment and flagging any runtime or visual changes.
• Release Readiness Checks: Automate final shipping validation—testing login, core workflows, mobile layouts, and error states—with documented proof of passing scenarios.

Target Audience

TryCase is built for development teams and individual developers who rely on AI coding agents (Claude, Codex, Cursor, and others) and need trustworthy, verifiable proof that generated code actually works in production-like conditions before shipping to users.