AI Context PlatformsFor Dummies

AI Context Platforms For Dummies, Atlan Special Edition, book cover

AI Context Platforms For Dummies, back cover

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

Table of Contents

In this chapter
- About This Book1
- Foolish Assumptions2
- Icons Used in This Book2
- Beyond the Book2
In this chapter
- Facing the AI Disappointment3
- Why smarter models still aren’t paying off4
- The context gap behind stalled projects4
- Contextual Intelligence: The Next Frontier4
- The Accuracy and Cost Problem5
- Context Is Intellectual Property6
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In this chapter
- Understanding Context: Knowledge, Expertise, and Norms8
- Can’t You Just Build an Agent for Every Job?9
- One to three agents: Bootstrapping context9
- Three to 30 agents: Keeping context current9
- Thirty and up: sprawl, drift, and lock-in9
- Why You Need a Shared Brain10
- The Principles of a Context Platform10
- Context Platforms in AI Architecture11
In this chapter
- The Building Blocks of Context13
- Building a map of the business with ontologies14
- Recording decisions in context graphs14
- Defining metrics with semantic models14
- Connecting meaning to data with catalogs and SQL intelligence14
- Encoding know-how as agent skills15
- Promoting experience into long-term memory15
- Trade-offs in Architecting a Context Platform16
- Keeping graphs virtual or materializing them16
- Choosing between a semantic layer and a context platform16
In this chapter
- Context Mining: Reverse-Engineering Context from Existing Systems17
- Context Management: Running the Context Development Lifecycle18
- Building and testing candidates19
- Reviewing, approving, deploying, and observing19
- Context Store, Retrieval, and Delivery19
- Context Feedback Loops20
- Turning traces and feedback into learning20
- Keeping memory in the right place20
- Context Governance and Observability21
- Detecting quality loss and drift21
- Controlling change and its blast radius22
- Treating Context like Code in a Repository22
In this chapter
- Assessing Your Context Maturity23
- Context Is a Team Sport24
- Setting Up the Context Operating Model24
- Global context creates company-wide alignment25
- Start with the work you want AI to improve25
- Make collaboration on context easier25
- Match context governance to the blast radius25
- Keep context portable26
- Making Context Compound26
In this chapter
- 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