AI Prompt Engineering

Prompt engineering has often been treated as a soft skill — a mix of intuition and trial and error with a few useful heuristics thrown in. AI Prompt Engineering takes a more disciplined approach, grounding prompt design in a real understanding of how large language models process and respond to input, and building from there toward systematic methods for designing, testing, and refining prompts across the full development lifecycle. Nelson Ming covers both generative and agentic AI contexts, recognizing that the prompting strategies appropriate for a one-shot generative task look quite different from those needed to reliably guide an agent through a multi-step workflow. The book spans development, testing, and deployment phases, treating prompt engineering as something that needs to be managed with the same rigor applied to other software components rather than figured out informally and left undocumented. That lifecycle framing is relatively rare in prompt engineering resources and gives the book genuine practical value for teams building AI-powered systems rather than individual users experimenting with a chat interface. At 345 pages, it develops its ideas with enough depth to serve as a real reference rather than a quick read, suited to engineers and technical practitioners who want a solid conceptual foundation alongside actionable guidance for their actual work.

Author:
Nelson Ming