Foundation
Learn AI
Start with the ideas that remain useful after a product launch or model name changes. These guides explain the concepts, trade-offs, and vocabulary behind practical AI use.
Published foundation guides
Durable explanations of the concepts and choices behind useful AI.
3 articles
AI Basics: Models, Assistants, and Agents Explained
A model generates an output, an assistant turns models and product rules into an interface, and an agent can pursue a goal through tools and repeated actions. Risk rises with access, autonomy, and consequence—not with the label on the product.
Learning outcome
Distinguish AI from generative AI and models from assistants and agents; explain training, inference, tools, and memory; and choose a proportionate permission level.
OpenAI vs Anthropic vs Google: What the 2026 Model Race Means for Normal Users
The practical model race is about product workflow: OpenAI emphasizes broad ChatGPT and developer surfaces, Anthropic emphasizes careful assistant behavior, and Google emphasizes ecosystem reach.
Learning outcome
Evaluate AI providers by workflow fit, release stability, ecosystem lock-in, and verification needs rather than benchmark headlines alone.
AI Is Moving Beyond Chat: What OpenAI, Anthropic, and Google Just Signaled
A cluster of launches from OpenAI, Anthropic, and Google showed the same durable shift: AI products are moving from isolated chat answers into research, coding, design, speech, and desktop workflows.
Learning outcome
Understand why model capability, tool access, interface design, permissions, and review steps now have to be evaluated as one system.