Open book pages fanning with light catching edges — The Crossroads of AI Integration, 800 pages across 50 chapters on implementing AI across industries

Book

The Crossroads of AI Integration.

800 pages across 50 chapters. Co-authored with Brian S. Gagne. AI foundations, agentic architectures, industry-specific playbooks, and implementation strategy — written for operators who have to actually ship the thing.

Amelia S. Gagne — CEO and co-founder of Kief Studio. Full-stack developer and strategist. Perplexity AI Business Fellow.

Brian S. Gagne — CTO and co-founder of Kief Studio. UPenn AI program alumnus and IBM-credentialed AI technologist. The technical depth alongside Amelia's operating and behavioral lens.

Together we run a two-person studio whose engineering output matches a 10–14 person team. The book is the long-form version of the methodology we use day to day.

Available via briansgagne.com — unified fulfillment.

Structure

What's inside

Eight parts plus appendices. Each part is self-contained — read end-to-end or skip to the section that matches the problem in front of you.

  1. Part I

    AI foundations

    How modern language models actually work, and the working vocabulary teams need before they make architecture choices.

  2. Part II

    Prompting and orchestration

    Prompt design, structured output, retrieval, evaluation — the operating layer that sits between models and product.

  3. Part III

    Agentic architectures

    Multi-agent patterns, tool use, planning loops, supervision. Where agents help and where they actively hurt.

  4. Part IV

    Data, retrieval, knowledge systems

    Grounding models in real data — embeddings, vector stores, hybrid search, the data engineering that nobody pitches at the keynote.

  5. Part V

    Industry playbooks

    Sector-by-sector implementations across healthcare, finance, legal, gaming, education, and more — what works, what fails predictably.

  6. Part VI

    Security, governance, and risk

    Threat modeling, prompt injection, data leakage, evaluation harnesses, and the boring discipline that keeps AI systems from leaking by default.

  7. Part VII

    Implementation strategy

    Operating models, team shape, build-vs-buy, vendor selection, governance — turning AI from a project into a capability.

  8. Part VIII

    The road ahead

    Where the field is going, what to bet on, what to ignore. Honest about the uncertainty.

  9. Part Appx

    Appendices

    Reference material — glossary, evaluation checklists, prompt and architecture patterns, further reading.

Read it the way it works for you.

Digital PDF, pay-what-you-want. Same offer as Brian's site — fulfilled there until our own checkout is wired in.