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Antigravity 2.0 The Complete Guide

Antigravity 2.0 The Complete Guide
This book is 100% completeLast updated on 2026-08-18
Juan Mora

Stop copying code snippets into chat widgets. Master closed-loop autonomous AI coding agents, local offline LLMs (Ollama/Llama 3.1), event-driven lifecycle hooks, and Model Context Protocol (MCP) runtimes.

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About

About the Book

Shift from Passive Autocomplete to Closed-Loop Autonomy

Software engineering stands at the precipice of its most profound paradigm shift since the compiler. Antigravity 2.0: The Complete Field Manual is the definitive, publication-grade guide to designing, deploying, and mastering autonomous AI coding agents.

Unlike conventional chatbots or IDE autocomplete extensions, Antigravity 2.0 introduces closed-loop autonomy: agents that perceive your environment, draft systematic architectural execution plans, execute edits across local codebases, run test suites in sandboxed terminals, and diagnose/repair bugs automatically before returning to you for review.

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What You Will Learn

* Local & Private AI Runtimes: Deploy offline LLMs (*Llama 3.1, Qwen 2.5 Coder, DeepSeek*) via Ollama for zero data-leakage development environments.

* Model Context Protocol (MCP): Connect your agent to external tools, databases, and APIs using standardized Stdio and SSE transport protocols.

* Event-Driven Lifecycle Hooks: Write custom `hooks.json` rule engines that enforce strict linter passes, security scans, and pre-commit checks dynamically.

* Custom Workspace Rules & Skills: Program project-specific heuristics using `GEMINI.md` guidelines and modular skill packages.

* Multi-Agent Orchestration: Harness the Python SDK to launch specialized subagent teams (researchers, copyeditors, graphic designers) working concurrently.

* Slash Command Execution: Master the forward-slash (`/`) control interface (`/goal`, `/schedule`, `/browser`, `/grill-me`, `/teamwork-preview`, `/learn`).

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Who This Book Is For

* AI Architects & Tech Leads designing high-velocity autonomous developer workflows.

* Senior Engineers looking to transition from manual coding to system architecture and agent oversight.

* DevOps Specialists automating local CI/CD feedback loops and sandbox environments.

* Privacy-Conscious Developers & AI Enthusiasts requiring 100% offline, local LLM execution.

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Table of Contents Summary

* Part I: Foundations— Evolution of AI tooling, agentic state machines (PPAV), and local model execution.

* Part II: Setup & Infrastructure — Installation, environment configuration, and local LLM binding.

* Part III: Interface & Control Mastery — Mastering the Chat Canvas, Artifacts system, and Slash commands.

* Part IV: Customization & Rules Engine — Custom Workspace rules, modular Skill creation, and hooks JSON specs.

* Part V: Model Context Protocol (MCP) — Stdio/SSE architecture, server creation, and database integration.

* Part VI: Multi-Agent Systems & Python SDK — Subagent spawning, communication protocols, and task isolation.

* Part VII: Enterprise Patterns & Troubleshooting — Failure recovery, context budget management, and security sandboxing.

* Appendices A–F — CLI Reference, Glossary, MCP Schemas, Hooks JSON Specs, Python SDK API, and Slash Commands Guide.

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Computer ScienceArtificial IntelligenceIDEs

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Author

About the Author

Juan Mora

Juan Mora is an AI and technology enthusiast with a deep passion for Google Antigravity, local LLMs, and autonomous agent workflows. As an active practitioner in the emerging field of agentic engineering, Juan loves experimenting with cutting-edge tools, multi-agent pipelines, and local AI runtimes. He wrote this handbook to share his practical discoveries, hands-on experiments, and complete field manual with fellow developers, creators, and AI enthusiasts.

Contents

Table of Contents

Here is the clean, semantic HTML code for the optional **Table of Contents HTML** field on Leanpub: ```html Part I: Foundations
  1. Chapter 1: Welcome to Agentic Software Engineering
  2. Chapter 2: The Antigravity 2.0 Ecosystem & Architecture
  3. Chapter 3: Local Offline Execution with Ollama & Open Models
Part II: Setup & Deployment
  1. Chapter 4: Environment & CLI Installation
  2. Chapter 5: Workspace Configuration & Global Rules
  3. Chapter 6: First Contact — Your First Autonomous Run
Part III: Interface Mastery
  1. Chapter 7: The Chat Canvas & Progressive Disclosure
  2. Chapter 8: Artifact Management & Interactive Previews
  3. Chapter 9: Slash Commands Complete Reference
Part IV: Customization & Extensibility
  1. Chapter 10: Custom Workspace Rules (GEMINI.md)
  2. Chapter 11: Modular Skill Architecture
  3. Chapter 12: Creating & Deploying Agent Skills
  4. Chapter 13: Event-Driven Lifecycle Hooks
  5. Chapter 14: System Sidecars & Custom Runtimes
Part V: Model Context Protocol (MCP)
  1. Chapter 15: Introduction to MCP & Tool Binding
  2. Chapter 16: Stdio vs. SSE Transports
  3. Chapter 17: Building Custom MCP Servers in Node & Python
  4. Chapter 18: Connecting External Databases & Services
  5. Chapter 19: Lazy Loading & MCP Security Sandboxing
Part VI: Multi-Agent Systems & Python SDK
  1. Chapter 20: Python SDK Architecture & Lifecycle
  2. Chapter 21: Subagent Spawning & Task Isolation
  3. Chapter 22: Agent-to-Agent Messaging Protocols
  4. Chapter 23: Swarm Patterns & Parallel Execution
  5. Chapter 24: Memory Management & Long-Context Optimization
  6. Chapter 25: Building Production-Grade Agent Teams
Part VII: Enterprise Patterns & Operations
  1. Chapter 26: Debugging & Diagnosing Agent Trajectories
  2. Chapter 27: Security, Privacy & Data Containment
  3. Chapter 28: CI/CD Pipeline & Automated Testing Integration
  4. Chapter 29: Cost Management & Token Budget Optimization
  5. Chapter 30: Enterprise Deployment Blueprints
  6. Chapter 31: The Future of Agentic Engineering
Appendices
  • Appendix A: CLI Command Reference
  • Appendix B: Glossary of Terms
  • Appendix C: MCP Server Configuration Reference
  • Appendix D: Hooks JSON Complete Reference
  • Appendix E: Python SDK API Reference
  • Appendix F: Slash Commands Complete Guide
```

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