Books

The books I wish existed when I needed them.

Six books on AI — five principle-first volumes for enterprise architects, exec teams, security leaders, boards, and data leaders, and one hands-on guide for developers who want to stop watching demos and start building.

Enterprise AI Agents — Design Principles and Practical Guidance, by Mehul Jain. Book One of The AI Black Book series.
The AI Black Book · Book One

Enterprise AI Agents

Design Principles and Practical Guidance

Book One of The AI Black Book. A principle-first guide to designing, evaluating, and deploying AI agents in enterprise settings. Written for architects and engineering leaders who must decide which tasks warrant an agent, where on the autonomy spectrum it should sit, and how to structure its tool surface, memory, and evaluations so the first version ships and the tenth does not collapse into maintenance debt. Vendors and frameworks appear as examples; the substance is decision reasoning that survives the next three vendor cycles. If you own cross-cutting architecture decisions for AI, this is the reference.

Published 2026 · Kindle & paperback
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The AI Transformation Playbook — From Pilots to Production, by Mehul Jain. Book Two of The AI Black Book series.
The AI Black Book · Book Two

The AI Transformation Playbook

From Pilots to Production

Book Two of The AI Black Book. Most enterprise AI programs are stuck in pilot purgatory: the demos impressed, the budget tightened, and the program flattened. The Transformation Playbook treats this as a program-design problem rather than a pilot-quality one. Written for the exec team — CEO, CTO, CIO, CFO, CISO — and the transformation leaders who advise them, it names the failure modes and gives the decision reasoning that produces durable outcomes. Each chapter grounds a discipline in a composite case, isolates the principle, and supplies criteria that survive vendor cycles, model shifts, and the pattern-of-the-month AI press.

Published 2026 · Kindle & paperback
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AI Security for the Enterprise — A Threat-Model-First Playbook, by Mehul Jain. Book Three of The AI Black Book series.
The AI Black Book · Book Three

AI Security for the Enterprise

A Threat-Model-First Playbook

Book Three of The AI Black Book. Enterprise AI has a security problem, and it is not the one most programs are working on. Dealership chatbots sell cars for a dollar. Deepfaked execs wire twenty-five million to attackers. Coding agents delete production databases. This book argues for a threat-model-first response: catalogue the failure modes that have produced material loss, map each to the control that would have caught it, and treat the rest as theatre. Written for CISOs, CIOs, Chief AI Officers, and audit-committee chairs, the book is anchored in the public incident record — not abstract frameworks.

Published 2026 · Kindle & paperback
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AI-Native Business Models — Reinventing Companies in the Age of AI, by Mehul Jain. Book Four of The AI Black Book series.
The AI Black Book · Book Four

AI-Native Business Models

Reinventing Companies in the Age of AI

Book Four of The AI Black Book. An AI-native business is not an existing business plus AI. Its unit economics, its moats, its pricing surface, and often its product are structurally different. Incumbents that bolt AI onto an unchanged model surrender the margin pool to whoever rebuilt for this. Written for the exec team that owns the strategic bet — CEO, Chief Strategy Officer, CFO, board — the book installs the vocabulary (AI-enabled vs AI-inside vs AI-native, the four business-model archetypes, the moats that compound and the ones that evaporate), catalogues the plays (workflow capture, data-as-product, incumbent's dilemma reframed, pricing past per-seat), and turns to execution (capability-vs-viability tests, M&A under AI-talent scarcity, board-level framing, and how six industries are rewiring in public). Principle-first. Vendor-free. Written to survive two model generations.

Published 2026 · Kindle & paperback (yellow-paper experiment)
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Data Strategy in the Age of AI: Building the Retrieval-Ready Enterprise, by Mehul Jain. Book Five of The AI Black Book series.
The AI Black Book · Book Five

Data Strategy in the Age of AI

Building the Retrieval-Ready Enterprise

Book Five of The AI Black Book. Most enterprise AI failures are data failures one or two steps removed. Pilot demos land, production rollouts stall, retrieval quality drifts, and the diagnostic always points back at the same place: the data the organisation had learned to live with was never retrieval-ready. This book names that category, walks the seven canonical pipeline stages, and prescribes the capture, cleaning, quality, lineage, retrieval, governance, and measurement moves that produce AI-grade data. Written for the CDO, CIO, and CTO who have to make the data layer actually work under an AI program, with a CFO-readable measurement surface for the exec who funds it.

Published 2026 · Kindle & paperback
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Introduction to Gen AI for Curious Developers, by Mehul Jain. A hands-on Python guide to building multi-modal AI applications with Gemini.
Standalone

Introduction to Gen AI for Curious Developers

Building Multi-Modal Applications with Gemini (2nd Edition)

A hands-on, beginner-friendly introduction to generative AI for developers who want to stop watching demos and start building. Across ten chapters in Python using the Gemini SDK, you will generate structured output, call your own tools, describe images, transcribe audio, reason over video, and build your first agent — then stitch it all into a single multi-modal application in Chapter 9. No ML theory, no framework bloat, no credit card required. If you have Python and an editor open, you are ready. This is the book I wish existed when I first wanted to build with AI.

Published March 2024 · 2nd edition 2026 · Kindle · ~140 pages
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