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JaimeLucena/README.md

👋 Hi there, I'm Jaime Lucena

🤖 Generative AI Engineer
I build practical AI applications and share what I learn along the way.
Passionate about making AI development accessible through hands-on projects and clear explanations.

LinkedIn

🚀 What I Do

  • 🧠 Design and orchestrate AI agents and multi-agent systems
  • 🔍 Build RAG (Retrieval-Augmented Generation) applications
  • 📘 Create educational content for AI engineering
  • ⚙️ Architect production-ready AI solutions with FastAPI & Streamlit

📚 Progressive Learning Path

A structured, hands-on journey from Python fundamentals to building production-ready AI applications.

🎓 Core Learning Modules

Module Repository Description
01 python-fundamentals The Python you really need for LLMs (concise, modern, hands-on)
02 langchain-beginners Learn LangChain fundamentals the modern way (LCEL, prompts, RAG)
03 agents-and-apps-foundations Build and orchestrate AI agents using LangGraph, CrewAI, FastAPI & Streamlit
04 ai-learning-projects 7 Learning AI applications showcasing advanced patterns

💡 Start with module 01 and progress sequentially. Each module builds on the previous one!

🎯 Current Focus

  • 🕸️ Advanced multi-agent architectures
  • 🧩 Memory and context in long-running agents
  • 🚀 Scalable RAG pipelines
  • 🧱 LangGraph & CrewAI orchestration patterns

❤️ Support Open Source

  • ⭐ Star the repositories you find useful — it helps others discover them
  • ☕ Buy Me a Coffee — support my work and tutorials
  • 📢 Share tutorials on social media or with your community

Thank you for helping keep Generative AI education free for everyone 🙏

💡 "Learning by building. Sharing to empower others."

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  1. 01-python-fundamentals 01-python-fundamentals Public

    Python fundamentals for LangChain: focused notebooks covering the essential concepts you need to start building AI applications. Quick and practical.

    Jupyter Notebook 4

  2. 02-langchain-beginners 02-langchain-beginners Public

    Practical notebooks to learn LangChain fundamentals — LCEL, prompt templates, RAG and vector stores — with modern, non-deprecated examples.

    Jupyter Notebook 3

  3. 03-agents-and-apps-foundations 03-agents-and-apps-foundations Public

    A hands-on guide to building and orchestrating AI agents with LangGraph and CrewAI, from fundamentals to deployment with FastAPI and Streamlit. Learn agent architecture, memory management, and prod…

    Jupyter Notebook 4

  4. 04-ai-learning-projects 04-ai-learning-projects Public

    7 production-ready AI applications showcasing advanced LangChain, LangGraph, CrewAI, and RAG patterns. Full-stack projects with FastAPI and Streamlit.