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Definition

The session task progression test evaluates whether a conversation makes steady progress toward the user’s inferred task. An LLM-as-a-judge reads the full session and scores it against four criteria:
  • Each turn logically advances the task
  • Steps are ordered sensibly (prerequisites before follow-ups)
  • Intermediate milestones are acknowledged before moving on
  • The conversation doesn’t loop, repeat itself, or backtrack unnecessarily

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Taxonomy

  • Task types: LLM.
  • Availability: and .
  • Evaluation level: session.
  • Polarity: higher score = better. 0 = no progress, 1 = excellent steady progress.

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Why it matters

  • A session can end with the goal achieved and still have been inefficient — looping through blind alleys before finding the answer.
  • Tracking progression complements Session goal achievement: together they tell you both whether the task was completed and whether the path to completion was clean.

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Required columns

  • Input: The user’s message in each turn.
  • Output: The assistant’s response in each turn.
  • Session ID: Groups turns belonging to the same conversation.
  • Timestamp: Used to reconstruct turn order within a session.
This metric relies on an LLM evaluator. On Openlayer you can configure the underlying LLM used to compute it. Check out the OpenAI or Anthropic integration guides for details.

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Test configuration examples

[
  {
    "name": "Session task progression above 0.7",
    "description": "Ensure sessions make steady progress toward the user's task",
    "type": "performance",
    "subtype": "sessionTaskProgression",
    "thresholds": [
      {
        "insightName": "sessionTaskProgression",
        "measurement": "meanScore",
        "operator": ">=",
        "value": 0.7
      }
    ],
    "subpopulationFilters": null,
    "mode": "monitoring",
    "usesProductionData": true,
    "evaluationWindow": 3600,
    "delayWindow": 0
  }
]