Now Learning

My current focus is on mastering the Generative AI engineering stack while deepening my expertise in cloud data platforms.

🗺️ Roadmap to GenAI Engineer Agentic AI Application development

1. GenAI Fundamentals & Prompt Engineering

• Understanding LLM architectures (Transformers, Attention mechanisms)
• Advanced Prompt Engineering techniques (CoT, ReAct)
• Evaluation frameworks (Ragas, TruLens)

2. RAG & Vector Databases

• Building production-grade RAG pipelines
• Vector Database optimization (Pinecone, ChromaDB, Weaviate)
• Advanced retrieval strategies (Hybrid search, Re-ranking)

3. Agents & Orchestration

• LangChain & LangGraph deep integration
• Building autonomous agents for data analysis
• Multi-agent systems

4. LLMOps & Production

• Model serving and fine-tuning
• Monitoring and observability for LLM inputs/outputs
• Cost optimization strategies

📚 Recent Notes & Resources

• Coming soon…