When a Cloud Nightly Batch Drifts From Yesterday's Result — An Input Contract and Snapshot Design for Reproducibility
When you push a batch to a cloud ephemeral worker via the Managed Agents API, the environment assumptions you took for granted locally vanish. Here is a three-layer design — environment snapshot, input contract, seed pinning — that keeps the same input producing the same result.
When Managed Agents Run in the Cloud, How Do You Hand Them Credentials?
The Antigravity 2.0 Managed Agents API runs agents in the cloud, away from your machine. Convenient, but the credential handling that was trivial on your own laptop suddenly gets hard. Here is a design for not handing over long-lived tokens, but issuing them per run and expiring them quickly.
Making My Managed Agents Batch Survive a Crash Without Redoing Everything
Running a 200-item batch on the Managed Agents API kept torching tokens, because every mid-run failure restarted from item one. Here is the checkpoint-and-idempotency design I added so the batch resumes from where it died.
Running Gemini's Managed Agents API: Where Cloud Execution Ends and My Local Agents Begin
A hands-on record of launching Gemini's Managed Agents (public preview) from Python — polling, artifact retrieval, and a cost guard — plus five criteria I use to decide what stays on my local CLI agents.