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Bug triage on autopilot with Neuro OS

Engineering and support roles ingest Sentry, tickets, and reviews — dedupe, score severity, attach reproducers, file one issue per root cause, Ask before customer-facing status updates.

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Neuro OS workflow

400 alerts/day is noise; 2–8 actionable issues is a queue. Neuro OS runs bug triage as a continuous loop: multi-source ingest, dedupe across Sentry + support + social, severity by user/revenue impact, reproducer attempt, single Linear/GitHub issue per root cause.

How it runs

Multi-source ingestion

Webhooks: Sentry, Datadog, Intercom, app store reviews, status page comments.

Dedupe layer

Link customer reports to Sentry groups via session IDs; collapse duplicate surfaces.

Severity scoring

S0 revenue-blocking → S3 cosmetic; factors: % users, MRR exposure, growth rate.

Reproducer synthesis

For S0/S1: stack trace + recent commits + session replay → draft Playwright/curl reproducer attached to issue.

Routing

S0: page human + draft status update (Ask to publish). S1: urgent issue with reproducer. S2/S3: weekly batch review.

Customer comms

Support role acknowledges within SLA with real issue id and ETA — Ask before send.

Pre-deploy regression check

PR diff cross-referenced against closed bugs from last 90 days.

Roles on Neuro OS

  • Engineering triage role
  • Support investigator role
  • Human on-call for S0

What you get

  • One issue per root cause
  • 60–80% S1 issues with reproducer before human opens IDE
  • Customers get named issue + ETA, not templates

Related: Engineering solutions · Support solutions

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