---
title: "AI Context Platforms For Dummies, Atlan Special Edition | Atlan"
url: "https://atlan.com/resources/ai-context-platforms-for-dummies/"
description: "Get early access to AI Context Platforms For Dummies, Atlan Special Edition. A free book from Wiley on why enterprise AI stalls without context, what a context platform is, and what to ask before you buy."
---

# AI Context Platforms For Dummies

The ultimate introduction to the world of context, covering everything you need to know before beginning your context journey.

## Inside

- Why enterprise AI stalls without context
- What a context platform is, and what it isn't
- How to assess your context maturity
- Ten questions to ask before you buy

The book is free. Sign up for early access on [the book page](https://atlan.com/resources/ai-context-platforms-for-dummies/).

## Table of Contents

### Introduction (page 1)

- About This Book (page 1)
- Foolish Assumptions (page 2)
- Icons Used in This Book (page 2)
- Beyond the Book (page 2)

### Chapter 1: Why Enterprise AI Isn't Paying Off (Yet) (page 3)

- Facing the AI Disappointment (page 3)
  - Why smarter models still aren't paying off (page 4)
  - The context gap behind stalled projects (page 4)
- Contextual Intelligence: The Next Frontier (page 4)
- The Accuracy and Cost Problem (page 5)
- Context Is Intellectual Property (page 6)

### Chapter 2: Defining What Context Really Is (page 7)

- Understanding Context: Knowledge, Expertise, and Norms (page 8)
- Can't You Just Build an Agent for Every Job? (page 9)
  - One to three agents: Bootstrapping context (page 9)
  - Three to 30 agents: Keeping context current (page 9)
  - Thirty and up: sprawl, drift, and lock-in (page 9)
- Why You Need a Shared Brain (page 10)
- The Principles of a Context Platform (page 10)
- Context Platforms in AI Architecture (page 11)

### Chapter 3: What a Context Platform Is (and Isn't) (page 13)

- The Building Blocks of Context (page 13)
  - Building a map of the business with ontologies (page 14)
  - Recording decisions in context graphs (page 14)
  - Defining metrics with semantic models (page 14)
  - Connecting meaning to data with catalogs and SQL intelligence (page 14)
  - Encoding know-how as agent skills (page 15)
  - Promoting experience into long-term memory (page 15)
- Trade-offs in Architecting a Context Platform (page 16)
  - Keeping graphs virtual or materializing them (page 16)
  - Choosing between a semantic layer and a context platform (page 16)

### Chapter 4: Capabilities of a Context Platform (page 17)

- Context Mining: Reverse-Engineering Context from Existing Systems (page 17)
- Context Management: Running the Context Development Lifecycle (page 18)
  - Building and testing candidates (page 19)
  - Reviewing, approving, deploying, and observing (page 19)
- Context Store, Retrieval, and Delivery (page 19)
- Context Feedback Loops (page 20)
  - Turning traces and feedback into learning (page 20)
  - Keeping memory in the right place (page 20)
- Context Governance and Observability (page 21)
  - Detecting quality loss and drift (page 21)
  - Controlling change and its blast radius (page 22)
- Treating Context like Code in a Repository (page 22)

### Chapter 5: Getting AI into Production (page 23)

- Assessing Your Context Maturity (page 23)
- Context Is a Team Sport (page 24)
- Setting Up the Context Operating Model (page 24)
  - Global context creates company-wide alignment (page 25)
  - Start with the work you want AI to improve (page 25)
  - Make collaboration on context easier (page 25)
  - Match context governance to the blast radius (page 25)
  - Keep context portable (page 26)
- Making Context Compound (page 26)

### Chapter 6: Ten Questions to Ask When Evaluating a Context Platform (page 27)

- How much context does it mine automatically from our existing systems?
- Does it cover the components of context our agents need?
- Can our business experts add and approve context in plain language?
- 7 more questions in the book