class CosmosDBContribution:
    """
    🎯 Created the FIRST-EVER Python-based Model Context Protocol (MCP) servers
    for Azure Cosmos DB, enabling seamless AI agent integration with Microsoft's
    globally distributed database platform.
    """

    def __init__(self):
        self.achievement = "First Python MCP Server for Cosmos DB"
        self.organization = "Microsoft Azure"
        self.impact = "Enabling AI Agents → Cosmos DB Integration"
        self.technologies = ["Python", "MCP", "Azure Cosmos DB", "AI Agents"]

    def what_it_enables(self):
        return {
            "ai_agents": "Direct database operations through natural language",
            "developers": "Seamless integration with LangChain, AutoGen, etc.",
            "ecosystem": "Bridges AI agents with enterprise-grade NoSQL database"
        }

#!/usr/bin/env python3
"""
Mohammed Aftab - AI Engineer & LLM Architect
Building the future of intelligent systems, one agent at a time.
"""

class AIEngineer:
    def __init__(self):
        self.name = "Mohammed Aftab"
        self.role = "AI Engineer & Developer"
        self.location = "Bengaluru, India 🇮🇳"
        self.experience = "2.5+ years in GenAI & LLM Systems"
        self.passion = "Transforming AI research into production-ready solutions"

    @property
    def current_focus(self) -> dict:
        return {
            "🚀 Building": [
                "Multi-agent orchestration systems with LangGraph",
                "Advanced RAG architectures for complex workflows",
                "Production-grade AI applications with LangChain",
                "MCP & A2A protocol implementations"
            ],
            "🔬 Exploring": [
                "Anthropic's Model Context Protocol (MCP)",
                "Agent-to-Agent (A2A) communication patterns",
                "LLM fine-tuning & prompt optimization",
                "Vector database architectures at scale"
            ],
            "✍️ Writing": [
                "25+ technical articles on Medium",
                "2 new articles every week",
                "Deep-dives on AI/ML implementations"
            ]
        }

    @property
    def expertise(self) -> dict:
        return {
            "specialization": "LLM Applications & Agentic AI",
            "core_domains": ["RAG Systems", "Multi-Agent AI", "NL2SQL"],
            "frameworks": ["LangChain", "LangGraph", "AutoGen", "Phidata"],
            "cloud": ["Azure", "AWS"],
            "databases": ["Cosmos DB", "Pinecone", "Chroma", "Qdrant"]
        }

# Let's build intelligent systems together! 🤝
aftab = AIEngineer()
print(aftab.current_focus)