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WTF Is the Context Layer? The Missing Infrastructure for Production Agents — Prukalpa Sankar

Source
youtube.com
Author
AI Engineer
Date

Context

A sales can keep pitching outdated messaging after the marketing team changes it. Atlan's founder recounts this failure in the company's internal agents: separate systems held separate , and the team lacked a clear view of their dependencies.

The proposed context layer gives agents shared business definitions, procedures and organizational knowledge that they can retrieve for a task. But sharing a repository creates a maintenance problem of its own. When competitive research changes positioning, the sales material that depends on it may also need updating. The talk argues for named maintainers, versioning and review of dependent material so that improvements in one agent's knowledge do not silently leave another behind. This is the company's account, not a measured productivity result.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Key quotes

“the problem we solve is we say AI doesn't know your business, we fix that”

Prukalpa Sankar

“Intelligence has 1,000x'd in the last decade. Just in the last 6 months, we have 2x'd on that axis.”

Prukalpa Sankar

“building an agent was really easy. Took like 5 minutes. Uh but giving it the business context that it took to actually get it to be accurate took forever.”

Prukalpa Sankar

“We realized that context kind of needs to be managed like code.”

Prukalpa Sankar

“in a world where you and your competitor have access to the same models and the same intelligence, what differentiates a company?”

Prukalpa Sankar
Chapters
  • 0:12Introduction: The Context Moment
  • 1:51Why AI Agents Struggle with Business Context
  • 3:19Performance = Intelligence + Context
  • 4:27The Human Learning Model: Lessons from Maya
  • 7:20Evolution of Agent Architecture at Atlan
  • 10:00The Challenges of Isolated Agent Systems
  • 11:06Transitioning to General Purpose Agents
  • 12:43Marketing Team Case Study: The Context Layer
  • 14:36The Challenges of Context Engineering
  • 15:31Defining the Context Layer: The GitHub for Context
  • 16:43Compounding Learning Loops and Traces
  • 17:18How to Start Building Your Company Brain
  • 18:07Defining the Context Layer Architecture
  • 19:31Conclusion: Context is IP
Read the source www.youtube.com
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