AI Agents Explained: Tools, Planning and Their Real Limits
AI agents combine language models with tools and feedback loops, but useful autonomy depends on clear boundaries, reliable checks and knowing when to stop.
Topic
AI Fundamentals
Plain-language explanations of how modern AI systems work, what the common terms mean, and where these systems are unreliable.
Temperature, Top-p and Sampling: How AI Chooses Its Next Word
Temperature and top-p shape how an AI samples its next token, but useful control starts with understanding what these settings can and cannot change.
How AI Benchmarks Work and Why You Should Read Them Sceptically
AI benchmarks can reveal genuine strengths, but understanding their tasks, scoring rules and hidden assumptions is essential before trusting a leaderboard.
How Large Language Models Actually Work: Tokens, Embeddings and Attention Explained
Learn how large language models turn text into tokens, build numerical representations and use attention to generate answers, with worked examples and practical exercises.