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Enables analysis and re-engineering of projects to align with AI-first design principles, enhancing project setup and transformation.

Analyzes user inquiries to AI agents, identifying coverage gaps and opportunities for product improvement using Amplitude analytics.

Analyzes Amplitude charts to uncover trends and anomalies, providing insights into metric changes and their drivers.

Analyzes user behavior differences between groups using Amplitude, providing insights for product managers and growth leads.

Generates Amplitude charts from natural language descriptions, simplifying event selection and visualization for data analysis.

Creates comprehensive dashboards in Amplitude, organizing data for clear insights and decision-making.

Transforms bug reports into reproducible steps by leveraging Amplitude Session Replay to identify user interactions leading to errors.

Diagnoses product errors by analyzing network failures and JavaScript errors to identify issues and improve reliability.

Generates a comprehensive list of analytics events from a change_brief YAML, aiding PMs in tracking and decision-making.

Identifies product opportunities by analyzing Amplitude data, synthesizing insights into actionable, prioritized recommendations.

Generates a structured JSON tracking plan for critical events based on existing analytics patterns in the codebase.

Analyzes AI agent sessions to identify root causes of failures, leveraging Amplitude for detailed insights and diagnostics.

Monitors product reliability by analyzing network requests and JavaScript errors, providing proactive health checks and quality metrics.

Analyzes Amplitude session replays to identify UX friction points, producing a ranked map of user struggles for improved design insights.

Provides a comprehensive framework for event taxonomy generation and data auditing in Amplitude, ensuring data quality and governance.

Facilitates human-in-the-loop workflows in Airflow, enabling approval processes and form inputs with various operators.

Enables Airflow tasks to be annotated with data lineage using inlets and outlets for enhanced tracking and visualization.

Guides users in creating and validating Apache Airflow DAGs using best practices and CLI commands for efficient workflow management.

Facilitates the conversion of dbt Core projects into Airflow DAGs using Astronomer Cosmos, ensuring compatibility and configuration.

Guides users in creating custom OpenLineage extractors for Airflow operators to capture detailed lineage data.