Receiving Managed Agent Async Jobs Through a Propose, Verify, Adopt Pipeline
The Managed Antigravity Agent, now in public preview via the Gemini API, autonomously plans, executes, and verifies inside a sandbox. Here is a design for catching its async deliverables through three stages — propose, verify, adopt — before they reach production, with implementation code and operational pitfalls.
Running Multiple Repositories in Parallel with Antigravity 2.0 Projects and Worktrees
Combining Antigravity 2.0 projects with git worktrees to run several repositories in parallel safely. From isolating agent workspaces to avoiding conflicts and connecting to scheduled execution, organized from real work.
Before Gemini CLI Shuts Down (June 18): Audit Every Hidden Dependency Before Moving to Antigravity CLI
When Gemini CLI shuts down on June 18, the things that actually break are not in your terminal—they're the gemini calls buried in CI, git hooks, and cron. Here's how to surface every reference, validate with a dry run, and design a rollback before you cut over.
Stop Letting Antigravity Agents Self-Report 'Done' — Completion Contracts and External Verification
An Antigravity agent reporting 'done' when the work was not actually finished is a failure mode I kept hitting. Moving the completion decision out of the agent and into code fixed it. Here is the contract, a three-layer verifier, and how it holds up under unattended, scheduled runs.
As Tools Consolidate Into Antigravity, Measure Your Lock-In and Keep an Exit Path
As Google consolidates its AI coding tools into Antigravity and the personal Gemini CLI sunsets on June 18, here is a practical design for quantifying vendor lock-in and keeping a configuration you can step away from at any time.
Calling a Managed Antigravity Agent from the Gemini API: Design Notes on the Preview Model
antigravity-preview-05-2026, now in public preview on the Gemini API, is a Managed Agent that plans, runs code, edits files, and browses the web autonomously inside a sandbox. Here is how it differs from rolling your own orchestration, and where to draw the line.
Containing Failure in Antigravity Multi-Agent Systems: Three Boundaries That Stop Cascades
Antigravity multi-agent setups run beautifully in isolation but cascade in production, where one small failure drags the whole orchestration down. These notes organize the fix around three boundaries—layered control, trust separation, and observability with idempotency—down to the TOML and the correlation-ID wrapper.
Stop Adding a Ternary Every Time a New iPhone Ships: A Table-Driven Resolution Design
Every time a new resolution arrived—iPhone Air, 17 Pro—I was bolting another screen-size ternary onto a 29-branch pile. Here is how I reshaped that into a table-driven design where adding the next device is a one-line data change, with the actual Swift from my wallpaper apps.
Designing Schema Evolution So Sub-Agent Handoffs Never Break
Put a typed contract at the boundary where a downstream agent receives an upstream agent's output, and learn how to evolve that schema without breaking existing flows — with validation code, a migration sequence, and the production symptoms to watch for.
Regression-Testing Antigravity Agent Output in CI
Agent output drifts between identical runs and turns CI red for no real reason. Here is how I stabilized snapshot regression testing for Antigravity agents using a normalization layer and pytest golden files, drawn from running it in my own indie developer CI.
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.
After Gemini 3.5 Flash Became the Default, Route Flash and Pro Per Task
Now that Antigravity's default Flash is Gemini 3.5 Flash, leaving everything on Flash wastes accuracy and forcing everything onto Pro wastes time. Here is a two-axis decision table for splitting work between Flash and Pro, plus the routing setup to wire it into your agents.