Show HN: AI Agents: Zero to Hero – Learn AI Agents from Scratch in Pure Python (github.com)

A new educational framework titled "AI Agents: Zero to Hero," developed by Tanmay Sah, has been launched to demystify the concept of AI agents using pure Python. This open-source resource aims to address foundational questions about AI agents, such as their operational mechanics and internal workings, enabling users to build agent systems from scratch without any external dependencies or APIs. The framework is organized into a progressive curriculum, guiding learners from basic definitions to the complexities of multi-agent systems and production-ready applications. This initiative is significant for the AI/ML community as it promotes a better understanding of autonomous agent systems beyond typical prompt engineering and high-level abstractions. By providing hands-on coding experiences and clear definitions, the curriculum equips a wide range of users—from software engineers to curious developers—with the knowledge needed to understand and create functional AI agents. Key technical components include the cyclic Observe-Decide-Act loop and state management, which form the core of agent functionality, thereby paving the way for deeper exploration into topics like reinforcement learning and multi-agent coordination.