Presentation: Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP
Must ReadInfoQ · 2026-09-19 11:00 UTC AI
AI Summary
LinkedIn introduced Contextual Agent Playbooks and Tools built on Model Context Protocol (MCP) to provide procedural memory, code search, and runbooks for coding agents. The system delivers a 20% productivity boost without compromising reliability. It addresses limitations of AI agents in large codebases.
AI analysis by Groq
Why should I care?
Because it enhances AI agent productivity and reliability, aligning with your focus on AI Agents and foundational models.
Content
Ajay Prakash discusses how LinkedIn overcomes AI agent limitations in large codebases. He explains Contextual Agent Playbooks and Tools - built on Model Context Protocol (MCP) - which serves procedural memory, code search, and runbooks directly to coding agents. Prakash shares architectural details and operational guardrails that deliver a 20% productivity boost with zero loss in reliability. By Ajay Prakash