Learning Hub
Learn practical AI. Build knowledge that compounds.
Structured learning paths for building useful AI systems and creating a Personal Knowledge Management practice that supports clearer thinking, continuous learning, and better execution.
Choose a track below. Each guide will be grounded in practical work, honest limitations, and reusable lessons rather than theory alone.
Track 01
AI Engineering
Learn how practical AI applications are designed, built, evaluated, and improved—from LLM fundamentals to retrieval systems, agents, and automation workflows.
LLM Application Foundations
Understand the essential components, design decisions, and trade-offs behind useful LLM-powered products.
RAG: From Documents to Grounded Answers
Explore ingestion, chunking, retrieval, prompting, citations, and the evaluation choices that make RAG reliable.
AI Agents and Automation Workflows
Learn where agents add value, how tools and state fit together, and when a simpler workflow is the better design.
Evaluating AI Systems
Move beyond demos with repeatable tests for quality, grounding, failure cases, cost, latency, and user value.
Track 02
Personal Knowledge Management
Build a knowledge practice that helps you capture what matters, connect ideas, retrieve context, and turn information into useful work.
PKM Foundations: From Information to Useful Knowledge
Create a lightweight system for turning scattered inputs into connected, retrievable, and actionable knowledge.
Obsidian: Capture, Connect, and Create
Use notes, links, metadata, and deliberate review to support learning without overengineering your vault.
Designing a Knowledge Workflow That Lasts
Shape capture, processing, retrieval, and creation habits around your real needs and available attention.
AI + PKM: Working with Your Own Knowledge
Explore where AI can help review, connect, and retrieve your notes—without outsourcing your thinking.
Where the tracks meet
Better AI begins with better knowledge systems.
The most useful overlap is not AI replacing thinking. It is AI helping us work more effectively with trustworthy, well-structured knowledge.
Guides coming soon.
Tools & templates
Reusable starting points
Practical checklists, worksheets, and starter structures will live here alongside the learning paths—so Resources stays part of the experience without becoming a separate empty destination.
AI project evaluation checklist
RAG architecture worksheet
PKM workflow audit
Obsidian starter structure
Keep exploring
Learn from active projects, not only finished lessons.
The Learning Hub provides structured paths. The Blog captures experiments and lessons in progress, while the Portfolio shows how ideas are applied in real projects.