Remote Sprint

React and Expert Q&A

Refine goals and questions while running structured expert Q&A threads.

Updated

Reacting to the Goal/Questions

The AI posts the draft goal and compiled questions. Team members react:

  • 👍 on things that are right
  • Reply with suggested edits or additions
  • The AI incorporates feedback and posts a refined version

This is NOT a debate — it’s a refinement. If there’s genuine disagreement about the goal, the AI escalates to the Decider.

Expert Q&A Threads

Instead of in-person expert interviews, the async sprint uses structured written Q&A in #sprint-experts.

How it works:

  1. The AI creates one thread per expert
  2. Each thread starts with the current goal, questions, and a draft map outline
  3. The AI posts 3–5 seed questions based on the expert’s area of knowledge:

🧑‍💼 Expert Q&A: [Name] — [Role/Area]

Here’s where we are so far: • Goal: […] • Key questions: […] • Draft map: […]

Questions for you:

  1. What are we getting wrong about how [X] works today?
  2. What do customers struggle with most at [specific step]?
  3. What’s been tried before? What happened?
  4. What’s the biggest risk you see?
  5. What opportunity are we missing?

Feel free to answer in any order, or share anything else you think we need to know. The team may follow up with additional questions in this thread.

  1. The expert responds at their convenience (within the phase window)
  2. Team members read responses and post follow-up questions in the thread
  3. Team members write HMW notes as they read (Activity 3)

Advantages Over In-Person Interviews

  • Experts have time to think and give more considered answers
  • Written answers are permanent — no reliance on note-taking
  • Team members can re-read at their own pace
  • Follow-up questions are precise because people have time to formulate them
  • Multiple experts can be “interviewed” in parallel

Disadvantage (and Mitigation)

  • Less spontaneous. Experts may not surface things they don’t know to mention.
  • Mitigation: The AI’s seed questions should be specific enough to draw out hidden knowledge. The prompt “What are we getting wrong?” is particularly powerful.