How to Run a 3-Hour Discovery Sprint with AI
You don't need two weeks and a dozen user interviews to validate an idea. Here's a repeatable process for running a fast, evidence-backed discovery sprint using Specky.
The problem with slow discovery
Traditional discovery cycles take weeks. Schedule interviews, conduct them, transcribe, analyse, synthesise, present. By the time you have findings, the team has already moved on or made the decision without you.
AI changes this. Here's a process we use internally at Specky that consistently produces strong signal in under three hours.
The 3-hour discovery sprint
Hour 1: Signal gathering (60 min)
- Open the Discovery Workbench and search for the topic you're exploring
- Review the auto-surfaced themes from the last 90 days of Gong calls and Slack threads
- Open Alex Research and start a session: "Help me understand what customers are saying about [topic]"
- Use Alex to challenge your initial hypotheses — it will push back if the data doesn't support your assumption
By the end of this hour, you should have a shortlist of 3–5 signal clusters worth exploring further.
Hour 2: Opportunity mapping (60 min)
- For each signal cluster, create an opportunity node in the Opportunity Tree
- Use the AI to score each opportunity against your strategy filters
- Deploy an Alex campaign to 10–20 users in the relevant segment — a short 5-question interview
- While the campaign runs, draft a lightweight opportunity brief in the PRD editor
Hour 3: Decision prep (60 min)
- Review the Alex campaign responses as they come in (most complete within the hour)
- Update your opportunity scores with the new signal
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