The journey begins by laying a solid foundation in AI agent architecture and the critical role memory plays in enabling agents to reason, recall, and adapt. Early modules demystify the core principles of memory in AI, explaining types of memory and their use in cognitive experiences. Through a mix of clear visuals and conceptual overviews, learners understand why memory is no longer optional in next-gen agent design. As you progress, you'll build agents that persist memory without relying on any external frameworks—perfect for grasping how memory mechanics work from the ground up. These hands-on labs include complete coding walkthroughs and visual animations to solidify understanding. You’ll test, refine, and deploy your agents, gaining full-stack insight into memory-aware systems. Then, dive deep into cutting-edge frameworks like LangMem, Mem0, and Supabase. Each tool is explored through realistic use cases—from customer support bots to health coaches—highlighting how to structure, update, and scale memory using these libraries. Whether integrating LangChain’s cognitive agents or constructing memory layers via Supabase, you’ll learn to build robust agents that feel intelligent and alive. The capstone project ties everything together, delivering a production-grade health coach agent with full memory retention.