TryCase
Disposable test environments for AI coding agents
289 followers
Disposable test environments for AI coding agents
289 followers
TryCase gives AI coding agents disposable Linux environments to run apps, test changes end to end, capture screenshots and recordings, and return verified code instead of asking you to test manually.
Love how the screenshots and recordings come back with the diff already attached, makes verifying what the agent actually did way less of a guessing game.
@grkemv2h0 Thanks Görkem. Just to clarify, today TryCase captures the run artifacts, while the coding agent is usually the one that returns the diff and evidence together.
I’m working on PR-based QA where TryCase would produce that report consistently itself. If you’ve tried the current version, which part did you rely on most: the diff, screenshots, or recording?
Disposable test envs is such a smart framing for agents, since letting an AI run wild in a sandbox that you just throw away afterward takes away all the anxiety about it breaking something real.
@yibo_wang3 Thanks Yibo. What are you most concerned about an agent breaking in your current workflow: local files, dependencies, secrets, external services, or production data? I’m trying to understand which isolation guarantees matter most in practice.
GPTEverywhere
Love the framing around agents only saying done after screenshots/video proof in an isolated env — that is exactly the gap when running multiple worktrees locally. Good luck with the launch.
@ducan Thank you so much
Macaly
disposable sandboxes for agents is exactly whats needed rn 👏 super usefull
@petrkovacik Thanks Petr. I’m curious how verification works in Macaly today. Does each generated change run in an isolated environment automatically, or does the user still need to preview and test it manually?