Episode 5- Planning and multi-step reasoning in agents

Most AI systems don’t actually “plan.” They respond. There’s a difference.In this episode, we break down what planning and multi-step reasoning in AI agents really mean. You’ll learn how agents take a high-level goal and turn it into structured, ordered actions instead of a single answer.We explain how goals are decomposed, how decisions are made step by step, and how feedback loops help agents adjust when things change. You’ll also understand where failures usually happen and why execution control matters as much as model intelligence.By the end, you’ll be able to evaluate agent designs, scope realistic use cases, and decide when multi-step autonomy is worth the cost and complexity.