{
  "schema_version": "openagent.resource.v1",
  "id": "res_future_agi",
  "slug": "future-agi",
  "status": "published",
  "identity": {
    "name": "Future AGI",
    "one_liner": "Open-source platform for evaluating, observing, and improving LLM and AI agent applications.",
    "short_description": "Future AGI is an open-source platform for evaluating, observing, and improving LLM and AI agent applications. It covers tracing, evals, simulations, datasets, gateway workflows, guardrails, and self-hostable deployment."
  },
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      "workflow",
      "evaluation",
      "observability",
      "guardrails"
    ]
  },
  "positioning": {
    "why_it_matters": "Agent teams need more than traces or one-off eval scripts. Future AGI is interesting because it combines evaluation, observability, simulation, datasets, gateway, and guardrails in one platform.",
    "best_for": [
      "Teams operating LLM and agent applications",
      "Builders comparing self-hostable evaluation and observability platforms",
      "AI teams that need simulations, datasets, and guardrails together"
    ],
    "not_for": [
      "Small prototypes that only need a few manual test prompts",
      "Teams looking for a low-level agent framework rather than an operations platform"
    ],
    "use_cases": [
      "self-hosted-ai"
    ],
    "target_audience": [
      "developer",
      "agent_builder"
    ],
    "maturity": "active"
  },
  "decision_signals": {
    "deployment_modes": [
      "self_hosted",
      "cloud"
    ],
    "open_source": true,
    "local_first": false,
    "self_hostable": true,
    "has_api": false,
    "has_gui": false,
    "supports_mcp": false,
    "supports_docker": false
  },
  "facts": {
    "license": "Apache-2.0",
    "pricing_model": "open_source",
    "github_stars": 1127,
    "github_forks": 240,
    "github_repo_full_name": "future-agi/future-agi",
    "last_verified_at": "2026-06-11"
  },
  "capabilities": {
    "core_capabilities": [
      "automation",
      "workflow"
    ],
    "interfaces": [
      "repo"
    ]
  },
  "links": {
    "primary_url": "https://github.com/future-agi/future-agi",
    "items": [
      {
        "type": "github",
        "label": "GitHub",
        "url": "https://github.com/future-agi/future-agi"
      },
      {
        "type": "homepage",
        "label": "Homepage",
        "url": "https://futureagi.com"
      }
    ]
  },
  "media": {
    "thumbnail_url": "https://github.com/future-agi.png",
    "og_image_url": "https://github.com/future-agi.png",
    "thumbnail_brief": {
      "resource_type": "tool",
      "visual_motif": "clean utility panel and geometric control surface",
      "background_style": "minimal editorial surface with restrained open-source accent color",
      "title_overlay": "Future AGI",
      "subtitle": "Open-source platform for evaluating, observing, and improving LLM and AI agent applications.",
      "avoid": [
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      ]
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  },
  "tags": {
    "category": [
      "tool",
      "open-source"
    ],
    "capability": [
      "automation",
      "workflow"
    ],
    "constraint": [
      "open-source",
      "self-hosted"
    ],
    "scenario": [
      "self-hosted-ai"
    ]
  },
  "relationships": {},
  "machine_readable": {
    "canonical_url": "https://www.openagent.bot/tools/future-agi",
    "json_url": "https://www.openagent.bot/tools/future-agi.json",
    "markdown_url": "https://www.openagent.bot/tools/future-agi.md"
  },
  "seo": {
    "title": "Future AGI: Open-Source Eval and Observability Platform for Agents",
    "description": "Future AGI is an open-source self-hostable platform for LLM and AI agent evaluations, tracing, simulations, datasets, gateway, and guardrails."
  },
  "editorial": {
    "trust_note": "Verified from source links and project metadata.",
    "core_strengths": [
      {
        "title": "Evaluation and observability together",
        "description": "Future AGI combines tracing, evals, datasets, simulations, gateway, and guardrails.",
        "why_it_matters": "Production agent quality depends on multiple feedback loops, not just a dashboard."
      },
      {
        "title": "Self-hostable platform",
        "description": "The project describes itself as self-hostable.",
        "why_it_matters": "Teams with sensitive agent data often need control over telemetry and evaluation datasets."
      },
      {
        "title": "Agent application focus",
        "description": "Future AGI is explicitly aimed at LLM and AI agent applications.",
        "why_it_matters": "Agent systems need tool, trace, and workflow-level evaluation beyond plain chat completion metrics."
      }
    ],
    "use_case_notes": [
      {
        "title": "Agent regression testing",
        "description": "Track whether agent changes improve or degrade task performance."
      },
      {
        "title": "Simulation workflows",
        "description": "Use simulations and datasets to test agent behavior before production traffic."
      },
      {
        "title": "Guardrail monitoring",
        "description": "Pair traces with guardrails around risky model or tool behavior."
      }
    ],
    "compare_notes": [
      {
        "title": "When to choose Future AGI",
        "summary": "Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need."
      }
    ],
    "getting_started": [
      {
        "label": "Open the GitHub repository",
        "url": "https://github.com/future-agi/future-agi",
        "type": "github"
      },
      {
        "label": "Visit the project website",
        "url": "https://futureagi.com",
        "type": "homepage"
      }
    ],
    "seo_article": {
      "intro": "Future AGI is an open-source platform for evaluating, observing, and improving LLM and agent applications.",
      "what_it_is": "It combines traces, evals, simulations, datasets, gateway workflows, and guardrails in a self-hostable platform.",
      "why_it_matters": "Agent quality needs structured measurement and operations loops before workflows reach real users.",
      "how_it_works": "Instrument one agent path, add evaluation datasets, and use traces and guardrails to inspect regressions.",
      "faq": [
        {
          "question": "Is Future AGI open source?",
          "answer": "Yes. The GitHub repository is listed under the Apache-2.0 license."
        },
        {
          "question": "Who should evaluate Future AGI?",
          "answer": "Teams shipping production LLM or agent applications should evaluate it as an evaluation and observability layer."
        }
      ]
    }
  },
  "timestamps": {
    "created_at": "2026-06-11T00:00:00.000Z",
    "updated_at": "2026-06-11T00:00:00.000Z",
    "published_at": "2026-06-11T00:00:00.000Z"
  }
}