The Artifact Transparency System

Unlike black-box AI, Antigravity provides verifiable Artifacts

Complete visibility into every agent decision and action

Why Transparency Matters

❌

Traditional Black-Box AI

  • • Code appears mysteriously
  • • No insight into reasoning
  • • Difficult to debug issues
  • • Trust based on blind faith
  • • Hard to learn from mistakes
✅

Antigravity Transparency

  • • Full audit trail of actions
  • • Documented reasoning process
  • • Visual verification at each step
  • • Evidence-based confidence
  • • Clear learning opportunities

Six Types of Artifacts

🎥

Browser Recordings

Watch every step of Browser Automation as agents interact with live web applications

What's Captured

  • • Mouse movements and clicks
  • • Form inputs and submissions
  • • Navigation events
  • • JavaScript console outputs
  • • Network requests

Use Cases

  • • E2E test execution verification
  • • UI interaction debugging
  • • Cross-browser compatibility
  • • User flow validation
  • • Performance monitoring
📝

Code Diffs

Review precise changes before merging with line-by-line comparisons

Features

  • • Syntax-highlighted diffs
  • • Side-by-side comparison
  • • File tree navigation
  • • Conflict detection
  • • Change statistics

Benefits

  • • Understand exact modifications
  • • Spot potential issues early
  • • Learn coding patterns
  • • Maintain code quality
  • • Enable Inline Annotations
📸

Screenshots

Visual proof of Generative UI states at critical moments

Automatic Capture Points

Before/After States

UI changes comparison

Error Conditions

Visual bug documentation

Milestone Achievements

Feature completion proof

📋

Implementation Plans

Detailed markdown roadmaps before any code is written

Plan Contents

  • • Architectural decisions
  • • File structure changes
  • • Dependencies to add/remove
  • • Testing strategy
  • • Risk assessment

Your Control

  • • Approve before execution
  • • Request modifications
  • • Add constraints
  • • Set priorities
  • • Define acceptance criteria
🧠

Reasoning Summaries

Understand the "Why" behind every Task List item, powered by Gemini 3 Deep Think

Reasoning Includes

🎯 Problem Analysis

How the agent understood the requirement

🔍 Solution Exploration

Alternative approaches considered and why they were rejected

⚖️ Trade-off Evaluation

Performance vs. maintainability, complexity vs. features

📚 Context References

Relevant documentation, patterns, and precedents used

✅

Validation Steps

Automated logs ensuring Zero-Config API Testing passes

Unit Tests

Individual function and component validation with coverage reports

Integration Tests

API endpoints, database interactions, and service integrations

E2E Tests

Complete user journeys from start to finish with visual regression

Review-Driven Development

Artifacts enable a new workflow where you review and approve rather than write from scratch

1️⃣

Agent Proposes Plan

Review the Implementation Plan artifact to understand the approach before any code is touched

2️⃣

Provide Inline Annotations

Add comments, request changes, or approve sections using Continuous Feedback mechanisms

3️⃣

Agent Executes & Validates

Watch Browser Recordings, review Code Diffs, and check Validation Steps as work progresses

4️⃣

Learn from Reasoning

Study Reasoning Summaries to understand agent decision-making and improve future Natural Language Commands

Transparency Meets Security

🔒

Sandboxed Environment

All agent actions occur in a secure Sandboxed Environment with full audit trails

What's Protected

  • ✓ Host filesystem isolation
  • ✓ Network access controls
  • ✓ Process sandboxing
  • ✓ Credential management
  • ✓ Resource limits

What's Transparent

  • ✓ Every file read/write
  • ✓ All terminal commands
  • ✓ Network requests made
  • ✓ API calls executed
  • ✓ Resource consumption

Experience Transparency in the Editor View

See artifacts in action with our Agent-First Platform