AI Explained
Plain-language breakdowns of how AI systems work under the hood, for viewers without an ML background.
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- LV.1Why a Weekend AI Tool Is Not an Enterprise System
- LV.2Three Shifts in Product Work When Building Is Cheap
- LV.3Why Programmatic Agent Usage Gets Metered Separately
- LV.4Free Course Playlists for Moving Into AI Engineering
- LV.5Three Lectures That Cover Retrieval Properly
- LV.6Read an Article With Prompts Designed to Create Friction
- LV.7Two Mental Models for Why AI Job Predictions Keep Missing
- LV.8Three Self-Checks for Polished Work With No Substance
- LV.9Ethical and Low-Impact Ways to Use AI Actually Exist
- LV.10What the Research Says About AI and Emotional Closeness
- LV.11Why an Agent Says Done Without Having Verified
- LV.12Cognitive Coverage as the Next Test Coverage
- LV.13Microsoft SkillOpt: Auto-Improving AI Agent Skills Docs Without Retraining (41% → 80%)
- LV.14Why AI Labs Are Suddenly Obsessed With Taste
- LV.15A Category Map of the Modern AI Tool Ecosystem
- LV.16Agent vs Skill vs Workflow: The 3-Layer Mental Model
- LV.17Mixture of Experts: Why a Model Card Shows Two Numbers
- LV.18Why AI Generality Is Moving From Components to Systems