PostHog → Claude → Linear: Product Bug Prioritizer
Analyze product analytics and error data from PostHog with AI to automatically prioritize bugs and create well-documented tickets in Linear for your engineering team.
Workflow Steps
PostHog
Capture error events and user impact data
Configure PostHog to capture frontend exceptions, API errors, and performance regressions alongside user session data. Set up cohort analysis to measure how many users are affected by each issue and track the correlation between errors and user churn or conversion drops. Use PostHog's session replay feature to collect reproduction context automatically.
Claude
Prioritize bugs by business impact
Send the error and impact data to Claude for prioritization analysis. Prompt it to rank issues by a composite score that weighs user impact, revenue risk, frequency, and engineering effort. Generate detailed bug reports with reproduction steps, affected user segments, and recommended fix approaches. Claude also groups related errors that likely share a common root cause.
Linear
Create prioritized bug tickets
Automatically create Linear issues with the AI-generated priority levels, detailed descriptions, and labels. Assign tickets to the appropriate team based on the affected system component and attach links to the relevant PostHog sessions for debugging context. Set cycle targets based on the AI-recommended urgency so the most impactful bugs are addressed first.
Workflow Flow
Step 1
PostHog
Capture error events and user impact data
Step 2
Claude
Prioritize bugs by business impact
Step 3
Linear
Create prioritized bug tickets
Why This Works
Bug prioritization often devolves into opinion-based debates that waste engineering time. Grounding priority decisions in actual user impact data ensures the highest-value fixes ship first. AI-generated ticket details save engineers the time spent on bug triage and investigation, letting them jump straight into fixing the issues that matter most.
Best For
Product and engineering teams who need a data-driven approach to bug prioritization rather than relying on who reports loudest.
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