{
  "schema_version": "newruntime-agent-readable-v0.1",
  "type": "raw_signal",
  "id": "tg-2620",
  "slug": "ai-product-okrs-measure-result-adoption",
  "title": "AI product OKRs should measure result adoption",
  "description": "Outcome metrics such as accepted work, overrides, completion, and retained use are more useful than model activity counters.",
  "observed_at": "2026-07-05",
  "why_it_matters": "Tokens, prompts, and generated artifacts can rise while user value remains flat, so teams need goals tied to decisions and completed work.",
  "novelty": "notable",
  "verification_level": "source-inspected",
  "signal_type": "field-report",
  "evidence_kind": "mixed",
  "status": "published",
  "telegram_message_id": 2620,
  "telegram_url": "https://t.me/qwgai/2620",
  "topics": [
    "ai-product",
    "product-metrics",
    "human-feedback"
  ],
  "entities": [
    "Jeff Gothelf"
  ],
  "related_patterns": [],
  "source_urls": [
    "https://jeffgothelf.com/blog/how-to-write-okrs-for-an-ai-product"
  ],
  "import_batch": "telegram-2026-07-17-v1",
  "routes": {
    "html": "https://newruntime.com/signals/ai-product-okrs-measure-result-adoption/",
    "markdown": "https://newruntime.com/signals/ai-product-okrs-measure-result-adoption.md",
    "json": "https://newruntime.com/signals/ai-product-okrs-measure-result-adoption.json"
  },
  "source_format": "telegram-export-normalized-json"
}