{
  "source": "Agents First framework (agentsfirst.dev)",
  "terms": [
    {
      "term": "Agents First",
      "definition": "A design framework (Joshua Baer, agentsfirst.dev) holding that every product now has two customers — the human who pays and the agent who decides — so the agent interface should be designed and shipped first.",
      "url": "https://agentsfirst.dev"
    },
    {
      "term": "MCP",
      "definition": "Model Context Protocol — an open standard for connecting AI agents to tools and data via self-describing tool definitions. Baer: 'MCP is just the flavor of the day; Agents First is not tied to MCP at all.'"
    },
    {
      "term": "llms.txt",
      "definition": "A machine-readable plain-text file at a site's root giving agents a concise map of the site's key content."
    },
    {
      "term": "AGENTS.md",
      "definition": "A hand-written contract stating the non-obvious rules and context an agent needs — constraints it cannot infer from the page. Weighted highest in the Agents First rubric."
    },
    {
      "term": "Pre-activation funnel",
      "definition": "Discovery → Evaluation → Installation → First agent action → Repeat usage; the agent-first adoption path. Target time-to-first-action under 60 seconds."
    },
    {
      "term": "Groundedness",
      "definition": "Constraining an AI to answer only from a specific trusted corpus and to refuse when it cannot confirm — demonstrated in the 'Jarvis' aviation-maintenance demo."
    },
    {
      "term": "The harness",
      "definition": "The rules and guardrails wrapped around a vibe-coded app to make it reliable for high-stakes use — observability, evals, and LLM-as-judge."
    },
    {
      "term": "delegation.school",
      "definition": "Joshua Baer's free, agents-first interactive course that teaches delegation to AI by making you build, not just read."
    }
  ]
}