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InfoQ · September 19, 2026 · On the brief until October 3, 2026

Presentation: Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP

Computer ScienceInformation Systems
THE AI ANGLE
Automating software debugging, incident mitigation, and enterprise code generation

LinkedIn resolved the failure of AI coding assistants in its complex proprietary codebase by building Contextual Agent Playbooks and Tools using Anthropic's Model Context Protocol (MCP). By equipping agents with access to internal code search, runbooks, and procedural memory across thousands of repositories, the organization enabled autonomous debugging, incident mitigation, and code generation. This context-engineering approach resulted in a 20% productivity boost with zero loss in system reliability.

Summary written by AI Business Lens with an AI model from the article at infoq.com. It is not the article, and the publisher has not reviewed it. For publishers.

THE TEACHING ANGLE
Students can examine why generic LLM coding tools fail in complex enterprise environments without dedicated context-integration layers like MCP, highlighting the shift from manual prompt tuning to context engineering.

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