Everything You Need to Know about AI

This comprehensive guide covers foundational AI concepts and practical applications for building AI products. It explains the four-layer hierarchy of intelligence (representation, generalization, reasoning, and agency), learning paradigms (supervised, unsupervised, reinforcement learning), neural network architectures (CNNs, RNNs, Transformers), and generative systems. The guide progresses to applied knowledge covering agent systems, scaling laws, emergence phenomena, and alignment challenges.

The latter chapters focus on real-world implementation, detailing the eight-layer AI system stack necessary for reliable products: input sanitation, retrieval, model invocation, orchestration, safety constraints, memory systems, evaluation, and drift monitoring. It positions PMs as systems architects who must understand probabilistic thinking, data curation, constraint design, and behavioral governance.