Roadmaps
From Foundations to Production AI.
AI isn’t learned in a day, but it can be mastered through structure. That’s why we built this page: to turn a busy feed into a clear roadmap.
Whether you’re looking to build a second brain, understand the foundations of AI agents, or architect enterprise-grade systems, you can find your starting point here without digging through the archives.
We’ve organized our content into three categories so you can explore at your own pace:
By Level: Beginner, Intermediate, Advanced.
By Collections: Foundations, Case Studies, Projects.
By Series: End-to-End Roadmaps.
Level
Beginner | Intermediate | Advanced
Collections
Foundations: Master the first principles and mental models.
Case Studies: Deep dives into real-world architectures and systems.
Projects: Hands-on implementations where we turn theory into working AI apps.
Series
AI Agents Foundations: A framework-free, first-principles roadmap to learn building AI agents from scratch, covering everything from tools to planning and memory.
AI Evals & Observability: Learn how to integrate AI evals into your AI app to address your specific business problems and track and improve your product.
Software Engineering for AI: Applying good software engineering practices to build AI applications.
Designing Enterprise MCP Systems: A practical guide to architecting modular, production-grade AI systems using the Model Context Protocol (MCP) to build enterprise AI automation apps.
Second Brain AI Assistant: An end-to-end guide to engineering a production-ready agentic RAG system that connects LLMs to your personal knowledge base using MLOps best practices.
PhiloAgents: A hands-on series to build an AI-powered game simulation engine that brings historical philosophers to life. Learn to impersonate historical figures using LangGraph, agentic RAG, and long-term memory.
Recommender Systems: A roadmap for architecting real-time recommenders using the FTI architecture and Polars. Covers 4-stage design, two-tower neural networks, and MLOps workflows with the Hopsworks AI Lakehouse.
Resource Library
If you’re looking to go deeper with more structured guides, here’s where to look next. While the weekly content is great for staying sharp, if you’re ready to build a complete system from scratch without piecing together different articles, I’ve compiled the best of what I know into a few digital products.
Unlike the weekly posts, these include full codebases, video walkthroughs, and Q&A support to help you go from a blank IDE to a deployed system.
The LLM Engineer’s Handbook: A framework for building LLM and RAG apps.
Agentic AI Engineering Course: The end-to-end blueprint for designing, testing, and deploying autonomous agents.
Full Course Catalog: Write real code. Ship AI that actually works.
Not sure what to pick? I also have a 6-day free email course on the critical design mistakes that silently break agentic systems. It boils down 2+ years of production experience into a simple mental model for building reliable agents that actually scale.