The complete path to building AI agents in Python with Promptise Foundry, from your first agent to production. You start with what an agent is and how to build one, give it tools through the Model Context Protocol, add memory and retrieval, and choose reasoning patterns. Then you make it safe and dependable: guardrails, prompt injection defense, human approvals, tracing and debugging, cost limits and evals. The path ends with running agents in production: triggers, crash recovery, deployment and the promptise run project runner. Every guide explains one concept and shows runnable code.
Read the lessons in order; they are arranged so each one prepares the next. Every lesson is a guide, so you can also open any of them on its own.
71 lessons, in order. Each opens with the full list beside it, so you always know where you are and what comes next.