All Articles
Handing Dependency Updates to Antigravity Agents — Risk Tiers, Verification, and Rollback
How far can you trust Antigravity agents with dependency updates? A four-tier risk model that corrects semver optimism, worktree-isolated lots, a fixed verification script, and a rollback-first ledger — the operations design I settled on while maintaining multiple apps.
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.
Size Antigravity Agent Tasks by What You Can Review — a Practical Cure for Rework
A one-line request cost me forty minutes of agent time and a Monday rewrite. Here is the sizing rule I switched to — tasks I can review in fifteen minutes — with the three actual briefs, acceptance criteria phrasing, and file-boundary rules for worktree parallelism.
Scheduling an autonomous agent fleet to run 6 sites solo — a timetable that avoids collisions and spam flags
A real example of the autonomous-agent scheduling I built to run 6 sites and an app business in parallel, solo: off-peak distribution, a daily generation cap, and collision avoidance, drawn from the actual timetable and the reasoning behind it.
Choosing the Right Granularity for an Agent's Tools — Bundle or Split?
Should you split an agent's tools finely or bundle them coarsely? A single decision rule, an intentionally asymmetric two-tier design for destructive actions, and real numbers from running six apps.
Delegate the Undoable, Guard the Irreversible — Tiering Agent Autonomy by Reversibility
When you hand production work to an Antigravity agent, the thing that bites first isn't intelligence — it's whether the operation can be undone. Here is a design that sorts every operation into three reversibility tiers and routes each to auto-execution, checkpointed execution, or a human gate, with TypeScript implementations and real numbers from running six apps in parallel.
Keeping Secrets Out of Your Antigravity Agent's Output: Layered Defenses for Logs, Diffs, and PR Bodies
The three paths through which background agents leak secrets, and how to defend commit diffs, execution logs, and PR bodies with layered protection, drawn from running six apps and measured false-positive rates.
Teaching Antigravity's Agent to Keep Diffs Small: How a Month Changed the Way I Review
When an agent hands you one giant diff, a solo developer's review can't keep up. After a month of asking Antigravity to break work into small steps first, here's how the experience of reviewing changed — with the exact instructions I now use.
Rehearsing an Agent's Actions Before They Touch Production — Designing a Zero-Side-Effect Dry-Run Layer
Some accidents survive shadow mode and canaries: the very first time an agent touches an external API. This is the design and TypeScript implementation of a zero-side-effect dry-run layer you can bolt onto Antigravity's parallel agents, with the real numbers from running six sites autonomously.
Capping Parallel Agents With a Token Budget — Designing a Guard That Stops Runaway Cost
Running many agents in parallel quietly inflates your token bill. This is not about shrinking prompts — it is about a governance layer that meters spend in real time and cuts it off at a budget. Full design and TypeScript implementation, drawn from running six sites autonomously.
Rolling Back a Half-Finished Agent: Compensating Transactions for Partial Failure
When you let an Antigravity agent run work that spans several external systems, a failure in the middle leaves the world half-rewritten. Retrying doesn't fix that. Here is how to fold it back safely with compensating transactions (the Saga pattern), with TypeScript and real operational numbers.
Flow Control for Autonomous Agents: Backpressure and Queues That Keep Production Alive
Run several Antigravity agents at once and the problem stops being how smart they are and becomes how little your downstream can absorb. Here is a flow-control design — bounded queue, semaphore, token bucket, backpressure, dead-letter — with TypeScript and real numbers.