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6 posts with this tag.
Most support teams assign severity by gut feel or customer loudness — this post explains why structured extraction, confidence gating, and code-location matching are the only reliable way to protect engineering triage time.
This post shows support and engineering teams how to replace the manual rewrite tax — the 15–30 minutes spent reformatting a Zendesk or Intercom ticket into something actionable — with structured extraction, CODEOWNERS-aware routing, and a closed feedback loop.
Most teams fix the bug but never tell affected customers what happened — that silent close is a churn trigger. This post explains how to write and deliver a structured, jargon-free root cause analysis that converts a support cost into a retention signal.
The support-to-engineering handoff breaks at the format boundary — free-form Zendesk and Intercom tickets are structurally incompatible with what engineers need, and no amount of Slack messages or Jira fields fixes a format mismatch.
Support queues mix billing questions, feature requests, and real bugs — this post shows exactly how to separate them using structured extraction, reproduction criteria, and a routing model that protects senior engineering triage time.
This post walks through how Watari automates the lossy, manual path from a Zendesk support ticket to an engineering-ready bug report — including OAuth setup, structured extraction, noise filtering, code mapping, and draft PR generation.