Build a rock-solid mental model of AI — tokens, transformers, agents, benchmarks — so you can navigate the landscape with confidence and never be lost in an AI headline again.
You'll have a working mental model of the full AI stack: how models are trained, what tokens are, how transformer architecture enables language understanding, what the difference between AI/ML/deep learning is, how agents differ from chatbots, and how to evaluate AI benchmark claims. You'll be able to follow AI news and technical discussions with confidence.
No. Many engineers with software backgrounds find the AI Foundations pathway valuable because it covers AI-specific concepts (tokens, attention, inference vs training) that aren't covered in general CS education. The pathway is written for practitioners, not just executives.
The AI Foundations pathway includes 11 articles and takes approximately 4 hours total. Most people complete it in a single weekend or spread across a week.
Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.
13 articles · ~5h →Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.
15 articles · ~7h →Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.
16 articles · ~6h →What Is Generative AI? Complete Guide
GenAI vs discriminative AI, all modalities, history, and how to start — for everyone.
History of AI: 1950 to 2026
From Turing's 1950 test to AGI — the full arc in one read.
AI vs Machine Learning vs Deep Learning
The three terms everyone conflates, finally untangled.
What Are Tokens? How LLMs Count Text
Tokens are the unit of thought for language models. Learn why they matter.
What Is a Transformer? The Architecture Behind Every LLM
Attention, embeddings, and why transformers changed everything.
What Is Multimodal AI?
Text, image, audio, and video — how models process all modalities.
What Are AI Agents?
The shift from chat to autonomous action — a complete explainer.
Types of AI Agents
Taxonomy by autonomy, loop architecture, domain, and tool access — with a decision matrix for choosing the right design.
AI Benchmarks: MMLU, GPQA, SWE-bench Explained
How to read and not be misled by AI benchmark headlines.
How to Learn AI in 2026: Beginner to Expert Roadmap
A hands-on guide from first prompt to shipping agents.
How to Stay Current with AI Without Losing Your Mind
A sustainable system for following fast-moving AI news.
Practical AI adoption for your specific function — marketing, engineering, HR, finance, and more.
10 articles · ~4h →
