The night my agent shipped nothing: giving generation agents an abstain outcome
When you score a background generation agent by how much it produces, the quality gate quietly loosens over time. Here is a three-valued ACCEPT / ABSTAIN / REJECT design that counts a zero-artifact run as a success, with the code and the measurements from running it.
Canary Deployment with Auto-Rollback for AI Agents — Protecting Production with Antigravity and Burn-Rate SLOs
A practical playbook for shipping new AI agent versions through canary deployment on Antigravity, with automatic rollback driven by burn-rate SLOs. Includes a lightweight setup that solo developers can sustain.
SRE for Antigravity Agents — Taming Probabilistic Systems with SLOs and Error Budgets
AI agents are probabilistic by nature, so running them in production without SRE thinking is risky. This guide applies SLIs, SLOs, and error budgets to Antigravity agents with working code, and shows why the textbook 14.4x burn-rate alert never fires on a loose SLO.
Designing a 4-Tier Fallback Architecture for Antigravity Agents — Catching Model Degradation, API Outages, and Cost Overruns Across Layers
How to design a 4-tier fallback hierarchy for production AI agents on Antigravity, drawn from 24 months of running 11 agents across 6 indie apps. Includes the decision logic, code, and real demotion statistics.