Launching today
TryCase
Disposable test environments for AI coding agents
165 followers
Disposable test environments for AI coding agents
165 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.
'Return verified code instead of asking you to test manually' is the exact gap. My coding agent writes the fix, then I'm the one clicking through the app like it's 2015. The agent proving its own work with screenshots and recordings flips the trust equation completely. How isolated are the environments - can it safely test against a copy of production data? Congrats on the launch.
How do you handle state between runs if the agent needs to verify something like a running database or queued background jobs from a previous step?
I’m curious about the differences between GPT-5.5 browsing and testing and TryCase. What makes TryCase unique, apart from just screenshots and videos? Thank you
Congrats on the launch, this is a real problem. My question is more about the iteration loop than the verification side - if an agent fails, tweaks the code, and needs to test again, does it get a brand new disposable box each time, or does it reuse the same one until the task is done? Fully fresh every retry sounds cleanest for isolation but on a repo with a slow install/build step that could add up fast if the agent is iterating 10+ times on one bug.
how does it handle cleanup of those disposable environments when an agent spins up a bunch in parallel, anything to worry about resource-wise?
finally something that lets my agent actually run the code instead of me playing QA. tried it on a small flask app and got back screenshots plus a clean diff, which honestly saved me a whole round trip.
the disposable linux envs actually working from a single prompt blew me away, screenshots and all. finally lets the agent go end to end without me babysitting every shell command.