All Articles
What I Delegated to an AI Agent — And What I Should Have Kept
After 12 years of solo app development and 50M+ downloads, I learned the hard way where to draw the line with AI agent delegation. Here's the practical framework I now use before handing off any task.
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.
Resolving AGENTS.md Precedence Conflicts in Antigravity Monorepos
When you place AGENTS.md in both the repo root and a subfolder, Antigravity merges them — but the agent often follows the wrong one. Here is how the precedence actually works, with concrete patterns to remove the conflict.
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. This guide walks through giving Antigravity agents a single 'Time Budget' object that unifies timeouts, priority, and deadlines, drawing on Masaki Hirokawa's production experience.
Why Antigravity Agents Can't Read Your .env File — Three Propagation Paths to Check First
When an Antigravity agent fails with Missing API_KEY but the same build works in your terminal, the cause is one of three env propagation paths. Diagnose each.
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.
Giving AI Agents an Aesthetic Sense — Building a UI Quality Evaluation Pipeline with Antigravity × Gemini Vision
Explore how to encode the vague judgment of 'is this UI good or bad' into code. Combines Antigravity with Gemini Vision to implement a complete pipeline — from screenshot capture to AI evaluation, improvement suggestions, automated fixes, and CI/CD integration.
Enterprise Multi-Agent Skill Management with gh skill — Profiles, CI Validation, and Cross-Agent Consistency
A complete architecture for managing SKILL.md across multi-agent teams. Covers role-based skill profiles, three-layer agent compatibility design, GitHub Actions CI validation, and automated release notifications.