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edX

The Google Antigravity Agentic Workflow: Plan, Execute, Verify

Pragmatic AI Labs via edX

Overview

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Most agent tooling asks you to trust a black box. This course opens it. You will see where 208 megabytes of binary actually goes, why two commands that look identical in the palette work by completely different mechanisms, and how the customization surface is built - because an agent, in the end, is a file you can read.

Key Course Features:

  • A skill built and proven end to end, not described
  • The goal command, and objectives that survive a turn
  • Custom agents as plain files under version control
  • Attaching an MCP server - NVIDIA's CUDA documentation - live
  • Hooks and plugins: what a bundle actually contains

Perfect for:

  • Developers already using Antigravity who want to extend it
  • Engineers deciding what to standardise across a team
  • Anyone whose agent output has to be reproducible by someone else

The organising idea is a ladder: six rungs from an ad-hoc question to a packaged, shareable skill. Every rung is a real artifact you can inspect, version and hand to a colleague - which is what separates a workflow from a habit.

Syllabus

  • Explain what the Antigravity binary contains and why its size is what it is
  • Distinguish compiled behaviour from loaded behaviour behind one palette
  • Climb the ladder from question to reusable, packaged skill
  • Build a skill and prove it works end to end
  • Write an objective that survives past a single reply
  • Design questions the agent must ask before it builds
  • Author a custom agent as a readable, versionable file
  • Attach an MCP server and source answers from vendor documentation
  • Use hooks and bundle customization as a plugin

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