Situation
You've had three customer calls this week and they all mentioned the same pain point. You need to turn those signals into a PRD without starting from scratch or losing the context.
What you need
Steps
1. Let Specky index your Gong calls
If you just connected Gong, wait 2–5 minutes for the initial sync. Specky pulls call transcripts, scores them for signal density, and indexes them into your Product Graph automatically.
You can verify by opening Product Graph and filtering by source_type: GONG.
2. Open AI Chat and ask directly
``
What are the top 3 feature requests from my Gong calls in the last 30 days?
Include the specific customers who mentioned each one and their exact quotes.
`
Specky searches your Product Graph, finds the Gong nodes, and synthesises themes with verbatim evidence.
3. Turn the top theme into a PRD
Once you have the themes, ask:
`
Draft a PRD for [feature name] based on the Gong evidence.
Include: problem statement, success metrics, scope, and open questions.
Cite the specific calls that evidence each section.
``
4. Review in the PRD Editor
The draft lands in Documents → PRD Editor. Review the inline citations — each claim links back to its source call. Edit the scope, adjust success metrics, and mark it as ready for review.
5. Push to Jira
From the PRD Editor, click Generate tickets → Push to Jira. Specky creates structured tickets with acceptance criteria, linked back to the PRD.
Output
Variations
No Gong? Works identically with Slack threads — Specky pulls the same signal from your Slack integration. Ask: *"What feature requests are in my #product Slack channel?"*
Want customer validation first? Before drafting the PRD, ask Specky to queue an Alex interview campaign targeting the customers who raised the issue. Get more signal before writing scope.
Working on a sensitive initiative? Add context via the AI Chat: *"I'm working on a pricing change — treat all mentions of billing and pricing as high priority."* Specky adjusts its synthesis accordingly.