500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents That Actually Know Your Codebase
Everyone's building custom AI agents. We didn't. Instead, we built CAPTAIN — an MCP server that makes any off-the-shelf coding agent understand LinkedIn's entire engineering stack. The secret: a meta-tool architecture (discover → inspect → execute) and composable skills that encode tribal knowledge as executable workflows. 500+ skills later, it's used across all of LinkedIn engineering. I'll show you the architecture in 10 minutes and why context engineering beats model engineering every time.
About the Context Engineering Track
Context Engineering sessions at AI Engineer World's Fair 2026 in San Francisco.
When
Wednesday, July 1, 2026
11:40 AM - 12:00 PM·20m
Where
Track 8 · Room 2020
Capacity: 250 attendees
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Speaker
Ajay Prakash
@ajay_prakash_ai
Ajay is a software engineer at LinkedIn with 14 years of experience in software, building large-scale systems and AI. For the past four years, his work has shifted fully into AI: LLMs, prompt engineering, context engineering, and AI agents. He previously led AI platform and product initiatives for LinkedIn Sales Navigator. Over the past year, he's led efforts to improve the effectiveness of coding agents by connecting them to LinkedIn's internal tools and context, making them genuinely useful inside a large engineering organization. He now leads AI agent platform efforts at LinkedIn, the most interesting work of his career so far.