planning

The concrete uses, built so they hold up. This lesson covers plan decomposition and what it is actually good for, the documentation nobody writes, chasing and dependency tracking, retrospectives where clustering helps and candour does not survive recording, and the portfolio view a PMO can genuinely gain.

Project management is largely communication and judgement under uncertainty, which splits cleanly into work AI does well and work it cannot touch. This lesson separates the two, covers the administrative load that is the genuine target, and explains why estimation is the seductive case that mostly does not work.

When you know the full MDP model, dynamic programming finds the optimal policy exactly. Learn the Bellman optimality equation, the contraction argument that guarantees convergence, and the concrete difference between policy iteration and value iteration — with a value-iteration code walkthrough.

What separates an agent from a plain chatbot, the perceive-think-act loop they all share, and how to design one that doesn't loop forever or burn through your token budget.