{
  "schema_version": "1.1",
  "id": "auto-f80e17c22f",
  "slug": "500-skills-zero-fine-tuning-linkedin-s-playbook-for-ai-a-f80e17c22f",
  "url": "https://feed7.dev/p/500-skills-zero-fine-tuning-linkedin-s-playbook-for-ai-a-f80e17c22f",
  "title": "500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents — Ajay Prakash, LinkedIn",
  "why_included": "Hide large tool catalogs behind search, schema lookup, and execution so agents load only the tools and playbooks relevant to the task.",
  "summary": "LinkedIn scales a large internal agent catalog through search, schema lookup, and execution rather than exposing every tool at once. Its playbooks add task-specific operating knowledge.",
  "practical_implication": "Use progressive discovery when your tool surface grows. Keep playbooks narrow and composable, load their instructions only when relevant, and let agents propose reviewed updates when real work reveals stale or missing guidance.",
  "agent_context": "LinkedIn’s internal system serves more than **1,300 tools** and **600 playbooks** to coding agents. Because performance reportedly degrades beyond 30–40 exposed MCP tools, the catalog sits behind **three meta-tools**: search, schema lookup, and execution.\n\nUse progressive discovery when your tool surface grows. Keep playbooks narrow and composable, load their instructions only when relevant, and let agents propose reviewed updates when real work reveals stale or missing guidance.\n\nThe reported scale includes **8,000 daily users** inside LinkedIn’s centrally managed environment. Its tool-limit observation is not presented as a controlled benchmark, and smaller teams may not need the authentication, telemetry, and distribution infrastructure described.",
  "source": {
    "name": "AI Engineer",
    "url": "https://www.youtube.com/watch?v=9wZpvF3QleU",
    "published_at": "2026-09-09T00:00:00.000Z"
  },
  "source_class": "video",
  "content_type": "Video",
  "layer": "agent",
  "domains": [
    "coding"
  ],
  "topics": [
    "harness-engineering",
    "skills",
    "tool-use"
  ],
  "verification": {
    "status": "source_linked",
    "label": "Source Linked",
    "method": "source_feed",
    "verified_at": null
  },
  "uncertainty": [],
  "connected_context": null,
  "lifecycle": "New",
  "published_at": "2026-09-09T00:00:00.000Z",
  "modified_at": "2026-09-09T00:00:00.000Z",
  "supersedes": [],
  "expires_at": null,
  "formats": {
    "html": "https://feed7.dev/p/500-skills-zero-fine-tuning-linkedin-s-playbook-for-ai-a-f80e17c22f",
    "json": "https://feed7.dev/p/500-skills-zero-fine-tuning-linkedin-s-playbook-for-ai-a-f80e17c22f.json",
    "markdown": "https://feed7.dev/p/500-skills-zero-fine-tuning-linkedin-s-playbook-for-ai-a-f80e17c22f.md"
  }
}