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 generationLinkedIn 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.
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.Read the original at infoq.com Generate teaching or study materials
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