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AI Product Tools / MIF Explorer / Library / AI
Truth Layer
MeaningfulLaggingAI-Sensitive Truth Layer
The Truth Layer is the badge system that tells you how trustworthy, directional, or risky a measure is.
Why it matters: It helps teams separate meaningful signals from vanity, misuse, or AI distortion before they optimize the wrong thing.
Example: A metric can be Meaningful, Leading, or Vanity Risk.
AI Task Completion Rate
The percentage of tasks where AI assistance leads to successful completion.
Evaluation method
ai_assisted_completions / ai_assisted_attempts × 100
Signal type
lagging
What it is best for
Evaluating whether AI features are effective
What it tells you +
Whether the AI is actually helping users accomplish their goals.
What it does not tell you +
Tell you whether users understood the AI’s work or could have succeeded without it.
When to use it +
- Evaluating whether AI features are effective
- Comparing AI-assisted and unassisted success rates
- Identifying task types where AI adds genuine value
When not to use it +
- Without comparing to unassisted completion rates — a high AI rate is meaningless if unassisted is equally high
How leaders misuse it +
- Celebrating high AI task completion without checking user understanding
- Attributing all task success to the AI when users would have succeeded anyway
Anti-patterns +
- Counting tasks as "AI-completed" when the AI merely provided a suggestion the user ignored
AI interpretation risks +
Scenario: AI completes tasks that users could have done themselves
What happens: AI completion rate looks high, but it’s solving easy problems
What it really means: The metric inflates the perceived value of AI by counting tasks users would have completed anyway.
Recommendation: Compare AI-assisted completion with unassisted baseline. The difference is the real value.
Companion entries +
This entry is stronger when paired with:
Instrumentation or evaluation guidance +
Define "AI-assisted" clearly. Track what the AI contributed versus what the user did.
Sample events
ai_assist_started, ai_assist_accepted, task_completed_with_ai Examples +
An AI code assistant achieves 78% task completion rate for debugging tasks. Unassisted debugging completes at 65%. The 13-point lift confirms genuine AI value for this use case.
Suggested decisions +
- If AI completion rate significantly exceeds unassisted rate, the AI is adding real value
- If the rates are similar, the AI may not be necessary for this task type