About

I write about data visualization and how to apply Python to real-world problems in order to produce clear insight. A natural application has been US macro releases (e.g. inflation, jobs, GDP, and Federal Reserve policy) with occasional pieces on AI and technology. The focus is always the same: what is actually moving in the data and what it means.

I have spent my career working with data in the insurance industry, turning complex information into insight for stakeholders and senior management. I started gilboa.blog to practice that same discipline in public: timely reads of major economic releases and selected technology topics, supported by clear charts and reproducible code.

Charts are the main tool I use to surface patterns that are easy to miss in tables or headlines. I also use AI agents to automate much of the production pipeline, which frees up time to improve the figures, refine the writing, and make the posts more approachable to a broader audience. Most posts include the full Python code so the analysis remains reproducible.

What you’ll find here

  • CPI, PCE, and PPI releases with contribution and persistence analysis
  • Jobs reports (BLS and ADP) with sector and breadth detail
  • GDP and related demand-side breakdowns
  • FOMC decisions, minutes, and the dot plot
  • Occasional technology and AI pieces (e.g. open-weight models)

Elsewhere

If you have a question or a comment, I’d like to hear from you.