All Articles
Multi-Agent Orchestration in Practice — Design Patterns and Implementation
Learn how to coordinate multiple AI agents with orchestration patterns. Covers router, pipeline, and consensus patterns with TypeScript implementation examples.
Antigravity Remote Agents Guide — Run AI Agents in the Cloud
Run Antigravity AI agents on remote servers and cloud VMs via SSH. Execute large-scale tasks without consuming local resources.
Antigravity Advanced Prompt Engineering — Agent Instructions, AGENTS.md & Context Design
Extract maximum performance from Antigravity's AI agents through advanced prompt engineering. Covers AGENTS.md design, context window optimization, role-playing techniques, chain-of-thought, self-verification loops, and real-world agent rule definitions.
Multi-Agent Orchestration with Antigravity — A Production Implementation Guide
Build production-grade multi-agent systems using Antigravity. Covers orchestrator/worker separation, DAG-based task management, parallel execution, retry logic, and cost optimization with real Python code.
LangChain and Antigravity Pipelines, Designed Backwards from Permissions, Failures, and Cost
Design pipelines starting from where they resume after a crash, not from how the chains connect. With permission tiers, checkpointing, and measured before-and-after numbers from my own runs.
Custom Agent Creation Guide — Build Specialized AI Assistants in Antigravity
Master custom agent creation in Antigravity. Build specialized AI assistants tailored to your project's unique workflows and requirements.
Gemini × Antigravity Integration Guide — Model Selection and Practical Implementation
Master Gemini 3 Pro/Flash selection, Claude Sonnet comparison, agent automation, and Google Workspace integration for advanced AI workflows.
Multi-Agent Workflows — Coordinate Multiple AIs for Faster Development
Learn to build multi-agent workflows in Antigravity. Task decomposition, parallel processing, automated code review, and practical patterns for team development.