All Articles
Stopping Parallel Agents from Clobbering the Same File
When you run several agents at once in Antigravity 2.0, two of them can write to the same file and one set of changes silently disappears. Here is how to design write arbitration inside a shared workspace.
After Generating Several Candidates, Which One Do You Adopt? Designing Best-of-N That Arbitrates by Verification
With Gemini 3.5 Flash's speed, generating several implementations of the same task has become practical. The hard part is no longer generation but arbitration. Here is the design and TypeScript implementation of a Best-of-N arbiter that picks the winner using verifiable signals only — not majority vote, not self-reported confidence.
Accounting for Which Agent Spent What: A Cost Attribution Design by Task
Your month-end bill is one number, but running multiple agents on Gemini 3.5 Flash hides which task ate the cost. Separate from a budget guard, I share a cost-attribution accounting design that maps usage to per-task and per-site cost, with a solo-operator implementation and numbers.
Tracing Parallel Agents After the Fact: Observability with Structured Logs and Spans
Running multiple agents in parallel on the Antigravity 2.0 desktop makes it impossible to tell which one is doing what. I share an observability design that drops tangled print debugging for run_ids and spans you can trace afterward, with a solo-operator implementation and numbers.
Making Managed Agent Batches Safe to Re-run: Idempotency and Checkpoints
Running overnight batches on the Antigravity 2.0 Managed Agents API makes recovery from partial failure unavoidable. Starting from a duplicate-post incident, I share the implementation of idempotency keys, a checkpoint store, and resume logic, with real numbers from solo operations.
When Your Antigravity Agent Eval Gate Keeps Flickering — Build Notes on Pass/Fail That Survives Non-Determinism
Same code, yet the eval passes in the morning and fails by noon. The first thing that breaks when you put agent evaluation into CI on Antigravity is the stability of the verdict. Here's how I separate noise from real regression and lock down pass/fail in code.
Generating Multilingual Release Notes with the Managed Antigravity Agent via the Gemini API
A hands-on record of building a pipeline that turns git commit logs into multilingual App Store and Google Play release notes using the Managed Antigravity Agent, now in public preview through the Gemini API.
Bundling Nightly Tasks With agy Async Jobs — A fan-out, poll, join Design
The Go-based Antigravity CLI (agy) can detach jobs and run them asynchronously. Here is a fan-out, poll, join design for firing many long-running tasks at once, collecting their job IDs, and waiting for completion — drawn from an actual nightly batch.
Treating the Managed Agent as a Cost-Capped Throwaway Worker: Isolating Untrusted Input from Production
How to use the Managed Antigravity Agent, now in Gemini API public preview, as a throwaway worker that is born and discarded per request. Cost caps, isolation, and idempotency with implementation steps.
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.
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.
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.