🚀 Agentic AI with Google Antigravity

Why I Built This

As a professional transitioning into Analytics and AI, I wanted to explore how Generative AI can solve a real-world problem faced by millions of job seekers.

This project demonstrates:

• AI-powered document analysis
• Business problem solving
• Prompt engineering
• Practical Generative AI implementation

Overview

This repository documents my journey exploring Agentic AI using Google Antigravity and modern AI agent frameworks.

The goal is to understand how autonomous AI agents can:

• Plan and execute tasks
• Use tools independently
• Collaborate with multiple agents
• Automate business workflows
• Solve real-world business problems

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What is Agentic AI?

Agentic AI refers to AI systems that can:

1. Understand objectives
2. Create execution plans
3. Use available tools
4. Make decisions
5. Adapt based on results
6. Complete tasks with minimal human intervention

Unlike traditional chatbots, agentic systems can perform multi-step workflows autonomously.

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Project Objectives

✅ Explore AI Agents

✅ Understand Google Antigravity

✅ Build Agent-based Workflows

✅ Experiment with AI Automation

✅ Learn Business Applications of Agentic AI

✅ Create Practical Use Cases

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Technologies

• Google Antigravity
• Gemini Models
• AI Agents
• Prompt Engineering
• Workflow Automation
• Python
• API Integrations
• Business Analytics

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Learning Areas

Agent Architecture

• Planning
• Reasoning
• Execution
• Memory
• Tool Usage

Multi-Agent Systems

• Task Delegation
• Parallel Execution
• Agent Collaboration

Automation

• Report Generation
• Data Analysis
• Content Creation
• Workflow Optimization

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Use Cases

Business Reporting

Raw Data
    ↓
AI Analysis
    ↓
Insights
    ↓
Automated Report

Research Assistant

Research Request
       ↓
Web Research Agent
       ↓
Summarization Agent
       ↓
Final Report

Data Analytics Workflow

Data Source
      ↓
Data Cleaning Agent
      ↓
Analysis Agent
      ↓
Visualization Agent
      ↓
Business Insights

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Repository Structure

Agentic_AI_Antigravity/
│
├── docs/
├── examples/
├── prompts/
├── workflows/
├── notebooks/
└── README.md

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Key Learnings

• Agentic AI extends beyond simple prompting.
• Multi-agent systems improve task execution.
• Business process automation is a major application area.
• AI agents can significantly enhance productivity when combined with structured workflows.

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Future Enhancements

• Build autonomous business agents
• Create analytics assistants
• Integrate Power BI workflows
• Implement data analysis agents
• Automate reporting pipelines
• Explore enterprise AI orchestration

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About Me

Nitish Malik

Business Operations Professional transitioning into:

• Analytics
• AI Automation
• Business Intelligence
• Agentic AI

Currently learning:

• SQL
• Power BI
• AI Agents
• Workflow Automation
• Business Analytics

Connect with me on GitHub and follow my learning journey.

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