Data Architects & Engineers
Design the layer between your data and your agents.
Inside the e-book:
- The 4 components of the context layer
- The compounding flywheel, step by step
- The inner and outer loops of context engineering
E-BOOK
WTF Is the Context Layer?
The definitive explainer on what the context layer is, how to build one, and why Gartner says it’s a critical differentiator for enterprise AI agents.
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THE AI CONTEXT GAP
AI doesn’t understand your business yet.
The heterogeneity sandwich
Context is scattered across systems and tools. Agents are fragmented across vendors. Without a unified layer, every agent has to learn your business from scratch — and each one thinks differently.
Context drift
Four agents with the same data give four different answers to the same question. Each learns on its own and stores new context internally. It’s an old problem at a newer scale and velocity.
CLOSE THE GAP
The 5-step path to production
01 — 051
DIAGNOSE
Map where context lives and where agents are fragmented.
2
DEFINE
Establish what the context layer actually is.
3
BUILD
Start a flywheel from column lineage, SQL query history, and BI semantics.
4
ENGINEER
Embed context engineering into the agent development process.
5
GOVERN
Move from “human in the loop” to “human on the loop.”
INSIDE THE GUIDE
A playbook for production-ready AI
WHO IT’S FOR
Built for the people putting AI into production
Whether you architect the layer or own the strategy, here’s what you’ll take away.
THE PROOF
Why agents stall at 50%
0x
agent performance improvement with a context layer
0%
accuracy ceiling where agents get abandoned without context
0
failure modes that stall every production rollout
Keep learning with Atlan
More guides and reports on building the context layer for production AI.
The CIO's Guide to Context Graphs
How CIOs are architecting context graphs as the connective tissue between fragmented data systems and fragmented agents.
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Inside Atlan AI Labs and the 5x Accuracy Factor
The research behind the 5x agent performance improvement — and what it takes to reach it through context quality, not bigger models.
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Evaluating Data Lineage for AI-Native Governance
The backbone of trustworthy context for data and AI.
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The 7 Shifts Reshaping the Data Stack for an AI-First World
Predictions for how the modern data stack is rebuilt for AI.
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The Ultimate Guide to Data Mesh
A practical playbook for designing and rolling out data mesh.
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Modern Data Leaders
How leading data teams operate, organise, and drive impact.
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The Ultimate Guide to Evaluating a Data Catalog
The criteria that matter when choosing a catalog for data and AI.
Read the e-book→
The CIO's Guide to Context Graphs
How CIOs are architecting context graphs as the connective tissue between fragmented data systems and fragmented agents.
Read the e-book→
Inside Atlan AI Labs and the 5x Accuracy Factor
The research behind the 5x agent performance improvement — and what it takes to reach it through context quality, not bigger models.
Read the e-book→
Evaluating Data Lineage for AI-Native Governance
The backbone of trustworthy context for data and AI.
Read the e-book→
The 7 Shifts Reshaping the Data Stack for an AI-First World
Predictions for how the modern data stack is rebuilt for AI.
Read the e-book→
The Ultimate Guide to Data Mesh
A practical playbook for designing and rolling out data mesh.
Read the e-book→
Modern Data Leaders
How leading data teams operate, organise, and drive impact.
Read the e-book→
The Ultimate Guide to Evaluating a Data Catalog
The criteria that matter when choosing a catalog for data and AI.
Read the e-book→