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AI Product Tools / MIF Explorer / Library / UX
Truth Layer
MeaningfulLeadingAI-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.
Time on Task
The time it takes a user to complete a specific task from start to finish.
Evaluation method
task_end_timestamp - task_start_timestamp
Signal type
leading
What it is best for
Measuring efficiency improvements after a redesign
What it tells you +
How efficient the experience is. Whether users can accomplish goals without unnecessary friction.
What it does not tell you +
Tell you whether users enjoyed the experience or whether speed came at the cost of comprehension.
When to use it +
- Measuring efficiency improvements after a redesign
- Comparing alternative flows in A/B tests
- Identifying bottleneck steps within multi-step processes
When not to use it +
- For content-heavy experiences where longer time may mean deeper engagement
- When comparing tasks with fundamentally different complexity
- As a standalone efficiency metric without task success context
How leaders misuse it +
- Assuming faster always means better without checking comprehension
- Comparing time on task across very different user segments without normalizing
- Using mean instead of median, letting outliers distort the picture
Anti-patterns +
- Optimizing for speed at the expense of user confidence or understanding
- Celebrating reduced time when users are actually skipping important steps
AI interpretation risks +
Scenario: AI auto-fills form fields or pre-populates answers
What happens: Time on task drops dramatically
What it really means: Reduced time may reflect AI doing the work, not a better user experience. Users may not understand what was submitted.
Recommendation: Separate AI-assisted time from unassisted time. Check whether users review AI-generated content before proceeding.
Companion entries +
This entry is stronger when paired with:
Conflicts and tension points +
Optimizing this entry alongside the following may create tension:
Instrumentation or evaluation guidance +
Use median, not mean — outliers from abandoned sessions skew averages heavily.
Sample events
task_started, task_completed Examples +
Median time to complete a support ticket dropped from 4m 30s to 2m 15s after introducing AI-suggested responses. However, ticket reopen rate increased 20%, suggesting users accepted AI responses without review.
Suggested decisions +
- If time increases after a release, check for added friction or confusion
- If time drops sharply with AI features, verify user understanding is maintained