Resolved PromptFlow data mapping and observability issues

• Day: 2025-05-02
• Time: 04:10 to 04:50
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Promptflow, Troubleshooting, Data Mapping, Observability, Job Funnel

Description

Session Goal

The goal of this session was to troubleshoot and resolve data mapping errors in PromptFlow, improve observability, and analyze job funnel processes.

Key Activities

• Troubleshooting PromptFlow Data Mapping Errors: Addressed issues related to missing fields in the job_data.jsonl file by following a structured troubleshooting guide.
• PromptFlow Observability: Reviewed a comprehensive guide to enhance data inspection and auditing capabilities within PromptFlow.
• Job Funnel Analysis: Evaluated a job funnel run, assessed job proposals, and identified strategic tensions in job filtering and recommendations.
• Post-Run Artifacts: Planned and outlined the creation of post-run artifacts for improved observability and tracking.
• Job Enrichment and Markdown Generation: Developed a pipeline for job enrichment and Markdown report generation using Jinja2 templates.
• Data Transformation: Implemented a Python script to convert JSON arrays to JSONL format, facilitating integration with LLM pipelines.

Achievements

• Successfully resolved data mapping errors and improved observability in PromptFlow.
• Conducted a detailed analysis of job funnel inputs and proposed actionable recommendations.
• Developed a scalable pipeline for job enrichment and report generation.

Pending Tasks

• Further refine the job funnel analysis and proposal evaluation process to align with strategic goals.
• Continue monitoring demand patterns in automation and AI roles for strategic positioning.

Evidence

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