Study Runtime

UserTold interviews are evidence-first: capture real product usage, preserve what participants say and do, ask planned follow-up questions, extract reviewable evidence, route work, and watch future interviews for recurrence after Linear completion.

During observation, the runtime stays silent. Clean studies capture behavior, then hand that context to a focused talk debrief.

Three Segment Modes

Every segment uses one participant-facing mode.

Observe

The participant uses your product naturally while UserTold captures product usage, speech, clicks, navigation, and available snapshots. The assistant stays silent. Pauses, loops, confusion phrases, and help requests are preserved as evidence for interpretation and debrief.

Best for: usability testing, task completion studies, real workflow observation.

Speak

The assistant delivers scripted one-way transition text. Use it for intros, task instructions, transitions, and thanks. It is not a live help mode.

Best for: task handoffs, consent reminders, short setup or wrap-up messages.

Talk

The assistant conducts an active realtime interview. It asks questions, listens, follows up, clarifies, and can call complete_segment when the planned conversation segment is done.

Best for: discovery interviews, context conversations, and debriefing after an observation segment.

Observe To Talk Handoff

The evidence-first follow-up mechanism is observe-to-talk handoff:

  1. speak gives the task instructions.
  2. observe captures behavior without interruption.
  3. talk receives bounded context from what just happened.
  4. The interviewer asks focused follow-up questions grounded in observed behavior.
  5. Final speak thanks the participant or closes the interview when the script calls for it.

This keeps the research record clean. The participant's struggle remains visible for debrief and extraction.

Deterministic Advancement

Production scripts advance only by deterministic criteria:

  • max_duration_s
  • user Done / step_done
  • url:<substring>
  • action:<selector-or-pattern>
  • complete_segment for talk segments
  • scripted speak completion

Use URL and action rules when the product exposes a clear completion signal. Use max_duration_s as a safety valve for observation. Use complete_segment for natural endings in talk. Goals guide analysis and planned debriefs, not observe-mode advancement.

Designing Studies

Usability

{
  "segments": [
    { "id": "intro", "mode": "speak", "title": "Task instructions", "speak_text": "Please complete checkout and think aloud as you go." },
    { "id": "task", "mode": "observe", "title": "Complete checkout", "instruction": "Complete checkout from cart to confirmation.", "conductor_context": "Capture hesitation, errors, page paths, and recovery behavior for the debrief.", "advance_when": "url:/success", "max_duration_s": 420 },
    { "id": "debrief", "mode": "talk", "title": "Discuss experience" },
    { "id": "thanks", "mode": "speak", "title": "Thanks", "speak_text": "Thanks for completing the interview." }
  ]
}

Discovery

Use planned talk segments when the research question is conversational. Split long interviews into focused segments with clear goals so complete_segment has a natural boundary.

How It Connects To Evidence Extraction

After the interview, the captured record feeds evidence extraction:

  • transcript and participant quotes
  • navigation and interaction history
  • observation context and page snapshots
  • completed goals and segment timing
  • planned debrief answers grounded in observed behavior

This separation keeps the live runtime predictable while still giving extraction enough evidence to explain friction, desired outcomes, workarounds, and recovery.

See also