Tracking AI Agent Decisions in Antigravity: Implementing Decision Logs and Explainability
Learn how to design decision logging systems that capture why your AI agents make specific choices. Includes working Python code examples, Before/After patterns, and a quality improvement cycle for production Antigravity agents.
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.
Defining 'Done' with Antigravity Agents: Writing Acceptance Criteria into Your Prompts
When Antigravity returns code that is only halfway working, the usual cause is a missing Definition of Done. Here is the three-layer fix.
Giving Your Antigravity AI Agents a 'Time Budget' — A Production Scheduling Design That Unifies Timeouts, Priorities, and Deadlines
Your AI agent's response time creeps up, users drop off, and unexpected costs pile on. Here is how I give Antigravity agents a single 'Time Budget' object that unifies timeouts, priority, and deadlines, plus the traps I hit after half a year in production.
Designing Confidence Scores for Antigravity Agent Outputs: Auto-Approve the Certain, Escalate the Ambiguous
Reviewing every Antigravity Agent output by hand does not scale. Attach a confidence score to each output, auto-approve the certain ones, and only escalate the ambiguous to humans. This guide walks through implementation and threshold calibration end to end.
The Self-Critique Architecture for AI Agents — Four Reflection Patterns That Make Antigravity Outputs Trustworthy
Four production-tested patterns for adding self-critique loops to Antigravity agents, with implementation code, stopping conditions, confidence calibration, and cost-control strategies.
Replay-Driven Agent Design — Time-Travel Debugging for Production AI Agents
Reproduce one-off agent failures from production on your laptop. A practical three-layer replay design — event, state, and decision — built on top of Antigravity's Manager Surface, with TypeScript code you can drop into your own stack.
Replacing Prompt Engineering with DSPy in Antigravity: A Production Playbook for Self-Optimizing LLM Programs
Replace hand-tuned prompts with self-optimizing LLM programs in Antigravity — DSPy signatures, optimizers, evaluation, and production deployment.
Stopping an Antigravity Agent Mid-Run: How to Pause and Resume Without Losing Your Work
When an agent starts heading in the wrong direction, hitting Stop without thinking can leave half-edited files and broken checkpoints. Here is the workflow I use to pause an agent and resume cleanly.
Designing Production Incident Runbooks for Antigravity Agents: A Practical Framework from Detection to Recovery
A complete guide to designing incident runbooks for production Antigravity Agents — detection, triage, mitigation, and postmortem, with working code you can drop into your stack today.
Letting Antigravity Be Your Night-Shift Engineer: A Solo Dev Operating Model
How to operate Antigravity agents as the second engineer who works while you sleep. Task hand-off, scope boundaries, and a morning three-point check turned into a script — the model I have refined while running multiple products solo.
Designing Antigravity Agent Traces That Tell You Why It Failed — Observability in Practice
Run Antigravity agents long enough and unreadable failure logs pile up fast. This piece walks span structure, attribute design, failure tagging, dashboards, cost visibility, and retry policy — backed by six months of production metrics — so you can cut post-incident debugging time in half.