"Semantic Kernel Skills: Plugin‑First Copilots for Enterprise Apps"

Enterprise copilots succeed or fail on architecture, not demos. This book is written for experienced software engineers, architects, and platform teams who want to build AI assistants that can safely act inside real business systems. Rather than treating Semantic Kernel as a prompt wrapper, it presents it as an enterprise runtime for governed tool use, service composition, retrieval, and agentic execution across complex application landscapes.

Readers will learn how to design plugin-first copilots that expose business capabilities as durable, auditable interfaces; compose kernels and AI services with clear execution boundaries; choose among native, OpenAPI, and MCP plugin models; and build retrieval layers with embeddings and vector stores. The book also covers automatic function calling, prompt assets, security filters, authorization, observability, feedback loops, agents, and multi-step orchestration, with an emphasis on trade-offs, production control, and long-term maintainability.

The treatment is practical but advanced: it assumes comfort with modern application architecture, APIs, dependency injection, and cloud-native operational concerns. Organized as a progressive technical guide, the book helps readers move from core runtime concepts to production reference architectures, making it especially valuable for teams designing enterprise AI platforms rather than isolated prototypes.