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Git-Based Agentic Workspace

Experience the next generation of AI-Powered Work!

File Explorer

Browse your project files

AI Chat

Chat with your AI assistant

Terminal

Run commands and see output

The Agentic Approach

Outer / Inner Agentic Work

Two complementary modes of AI collaboration that transform how you work

Outer Agentic Work

AI assists your creative process in real-time, amplifying your capabilities with intelligent suggestions and instant iterations.

Leveraging AI Capabilities
Harness powerful search and processing for rapid insights
Creative Amplification
Enhance your ideas with AI-powered insights
Strategic Planning
Break down complex projects into actionable steps

Inner Agentic Work

AI agents operate autonomously on structured tasks, handling complex workflows while you focus on strategic decisions.

Systematic Automation
Automate repetitive and structured work patterns
Autonomous Execution
Agents complete entire workflows independently
Parallel Processing
Multiple agents work simultaneously on different tasks

Seamlessly switch between modes or use both simultaneously to maximize your productivity

The New Paradigm

Optimizing Work in an AI-First World

Different modes of agentic work require different human capabilities

Collaboration & Alignment

For outer agent work, focus on effective communication and ensuring AI agents understand and align with your goals.

Clear Communication
Express intent and goals effectively to AI agents
Goal Alignment
Ensure agents work toward the right objectives
Direction Setting
Guide agents with strategic vision and priorities

Observability & Steering

For inner agent work, maintain visibility into autonomous operations and guide agents when they need course correction.

Process Visibility
Monitor what agents are doing in real-time
Active Steering
Intervene and redirect when necessary
Progress Tracking
Understand agent progress and decision-making

Master these skills to thrive in the age of agentic AI

Living Documentation

Documentation That Stays Alive

CodebaseViews connect your documentation to actual code, ensuring docs stay accurate and AI agents understand exactly what you're talking about

The Problem

Traditional documentation becomes outdated the moment code changes. Files move, implementations change, but docs stay the same.

"The authentication system uses JWT tokens..."

❓ Which files implement this?
❓ Where are the JWT utilities?
❓ Is this still accurate?

The Solution

CodebaseViews create explicit, validated links between your documentation and the actual code files it describes.

Authentication System View

jwt: src/auth/jwt.ts, src/auth/tokens.ts
middleware: src/middleware/auth.ts
config: src/config/auth.config.ts

Always Accurate

Validation ensures all references point to real, existing files

AI Precision

AI agents know exactly which files to examine for context

Impact Analysis

See which documentation is affected when code changes

Automated Validation

Get alerts when files move or references break

Navigate Easily

Jump seamlessly between documentation and implementation

Coverage Tracking

Identify which code areas need documentation

Keep your documentation alive and give AI the context it needs to truly understand your codebase