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.
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.
Supervising Long-Running Antigravity Agents — Watchdog and Tiered Recovery
Eight weeks of running AdMob revenue optimization on Antigravity background agents revealed three quiet failure modes. Here is the watchdog plus tiered recovery design I landed on.
Forensic Audit Trail for Antigravity Background Agent — Cloudflare R2 logging that reconstructs decisions six months later
How to design a decision-log audit trail for long-running Antigravity Background Agents so you can still reconstruct why an agent did what it did six months later — schema, R2 write layer, PII masking, and Polars queries.
Designing Knowledge Freshness for Antigravity AI Agents — A Runtime Architecture for Model Cutoffs, Corpus Staleness, and Real-World Time Drift
Antigravity agents have to juggle three independent time axes — model cutoff, RAG corpus update, real-world clock — or they will confidently cite six-month-old documentation. Here is the runtime architecture I use, with working TypeScript code and the TTL thresholds I run in production.
Three Weeks of Letting Antigravity Run wrangler tail Across Six Cloudflare Workers
I run six Cloudflare Workers in parallel — four Lab sites and two storytelling blogs — and the morning log review was quietly eating an hour and a half every day. Here is what changed when I handed wrangler tail interpretation to Antigravity's Inline Agent for three weeks, what I trusted it with, and what I kept for myself.
An Observability Blueprint for Antigravity Agents in Production
A definitive guide to designing observability for AI agents running on Antigravity in production. Presents a practical framework that unifies traces, metrics, and outcome logs.
Observing Antigravity AI Agents with Langfuse — A Practical Setup Before You Ship
Before you push an Antigravity AI agent to production, wire up Langfuse so you can actually see traces, token spend, and cost. A hands-on guide with real Python code and lessons from the field.
Antigravity × Prometheus + Grafana — Build an Application Monitoring Stack with AI Agents
Learn how to build a production-ready application monitoring stack with Prometheus and Grafana using Antigravity's AI agents. Covers metrics collection, alert rules, and dashboard creation step by step.