All Articles
Antigravity × Python Structured Output Mastery: Building Type-Safe AI Data Pipelines with Pydantic and Google Gen AI SDK
A complete guide to designing and implementing type-safe AI data extraction pipelines using Google Gen AI SDK Structured Output and Pydantic in Antigravity. Covers schema design, error recovery, async processing, and cost optimization.
Multi-Agent Design Patterns in Antigravity — Building Workflows That Don't Break
Practical patterns for designing multi-agent workflows in Antigravity. Covers orchestrator architecture, state management, error recovery, and debugging techniques for building resilient systems.
Building an AI Test Pipeline with Antigravity Agents: Automating Quality Assurance in Production
Learn how to build a production-grade automated test pipeline using Antigravity's AI agents — from unit test generation to E2E testing with Playwright, complete with validation layers and CI/CD integration.
Build an AI Agent SaaS with Antigravity × AgentKit 2.0 × Stripe — A Complete Implementation Guide for Solo Developers
How to build a subscription AI agent SaaS with AgentKit 2.0, Stripe and Antigravity. Architecture, billing, Webhook idempotency, production deployment — plus the Redis concurrency-slot bug that quietly locks out your heaviest users.
How Claude Mythos Is Redefining AI Agent Limits—and What Project Glasswing Reveals
Explore Anthropic's Claude Mythos and Project Glasswing: AI agents that autonomously discover zero-day vulnerabilities with 93.9% accuracy on SWE-Bench. Why it's invite-only and what it means for developers.
Antigravity × AgentKit 2.0 × Gemma 4: Cut API Costs by 80% with a Local Multi-Agent System in Production
A complete implementation guide to combining AgentKit 2.0 with locally-run Gemma 4, cutting cloud API costs by 80% while maintaining production-grade quality. Covers hybrid LLM routing, fault tolerance, and cost monitoring.
Building a Coding Agent System with Gemma 4 × Antigravity — A Complete Implementation Guide for Code Review, Test Generation, and Refactoring
A hands-on guide to building a 3-agent collaborative system using Gemma 4 and Antigravity AgentKit 2.0, covering code review, automated test generation, and refactoring suggestions. Includes production-quality code and pitfall solutions.
Unit Testing AgentKit 2.0 Agents with Vitest — A Practical Guide
Learn how to unit test and integration test MCP skill servers built with AgentKit 2.0 using Vitest. Covers mock strategies, InMemoryTransport integration tests, and CI/CD setup with real working code examples.
Resilient AI Agents in Antigravity — Retry, Circuit Breakers, and Fallback Strategies for Production
Build fault-tolerant AI agents in Antigravity with retry strategies, circuit breakers, model fallback chains, and checkpoint recovery — plus a measured look at why exponential backoff alone leaves retry storms completely intact at 200-agent scale.
AI Agent Error Recovery Design: Building Pipelines That Don't Stop
Covers the typical failure patterns AI agents encounter in production and practical implementations of retry, fallback, and circuit breaker patterns to keep pipelines running.
AI Agent Design Patterns in Practice: From Implementation to Production
Master the four major AI agent design patterns used in production environments. Learn the strengths, weaknesses, and implementation strategies for each pattern with real-world enterprise insights.
AI Agent Orchestration: Designing and Implementing Multi-Agent Systems
One failing agent can erase the work of the ones that succeeded. Four orchestration patterns, plus the boundaries that break in production, with runnable fixes.