Generative AI is transforming how we build applications. From intelligent chatbots that answer questions using your own documents to AI agents that can research, plan, and act — the possibilities are endless.
This comprehensive guide will take you from the fundamentals of tokens and embeddings to building production-ready AI systems with RAG, agents, and multimodal capabilities. No PhD required — just Python and curiosity.
What You'll Learn
Generative AI with Python
By Hernando Abella
Master RAG pipelines, AI agents, tool calling, vector databases, and multimodal systems — with hands-on code throughout. Perfect for developers who want to build production-ready AI applications.
Series: Building Generative AI Applications
This series of articles will guide you through building real AI applications from scratch. Each article includes complete code examples and practical explanations.
Tokens, Embeddings & Attention
The fundamental building blocks that power every modern AI model.
Read article →Building a RAG System
Combine retrieval with generation for grounded, accurate answers from your own data.
Read article →AI Agents with Tools & Memory
Create intelligent agents that use tools, remember context, and reason through complex tasks.
Read article →AI Coding Assistant
Build a developer tool that explains code, finds bugs, and generates tests.
Read article →AI-Powered Knowledge Base
Transform company documents into an intelligent assistant using RAG.
Read article →Claude vs Cursor vs ChatGPT
A month-long comparison of the three biggest AI coding assistants building a real app.
Read article →Production AI Systems
Scale your AI applications with monitoring, evaluation, and best practices.
Read article →Why This Series?
Prerequisites
- → Basic Python knowledge (functions, classes, libraries)
- → An OpenAI API key (free tier available)
- → Willingness to experiment and build
Ready to master Generative AI? Start with the first article in the series — Tokens, Embeddings, and Attention — and build your way to production-ready AI systems.
Get the Complete Guide
Master RAG pipelines, AI agents, tool calling, vector databases, and multimodal systems.
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