The Spiral Method for AI Engineering
Learn, Build, Deploy - Ten Cycles, One Project
Most AI books teach you 200 pages of theory before you ever touch a keyboard - and by the last chapter, you still don't know if you actually understood any of it. This book does the opposite.
You'll build one real AI companion app - the same category of software as ChatGPT, Alexa, or Siri - and grow it across ten cycles, each adding exactly one new capability and one new professional habit: talking to a core model, giving it outside knowledge, measuring whether it's actually good, giving it long-term memory, giving it the ability to take actions, making it fast and reliable under load, monitoring it in production, making it safe, scaling it for real users, and knowing what to build next.
No detour into theory happens before it's needed - five appendices (glossary, math, tooling, full architecture, and a cycle-by-cycle checklist) sit at the back, ready exactly when a cycle calls for them, never front-loaded.
Who this is for:
- Engineering students who can explain transformers and RAG in an interview but freeze the moment they're asked to ship something real
- Working developers who've done AI tutorials but never carried a project end-to-end into production
- Technical leads who need a shared vocabulary and checklist to hold a team accountable for shipping safe, monitored AI systems
Written by Srinivas Yellugani, a technology leader with 20+ years turning ambitious AI and digital transformation programs into production systems across banking, healthcare, manufacturing, and utilities - and a Professor of Practice who has taught this exact gap to students and working professionals for 25 years.
By the last page, you won't have read about AI engineering. You'll have built it - one project, ten cycles, real impact.
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