My Claude Code Experience

This page is a personal guide to using AI code agents as a junior economist — not from the perspective of a seasoned researcher with deep domain expertise, but from someone learning both economics and AI tooling at the same time. My goal is to share what actually works (and what doesn’t) when integrating code agents into an economics research workflow, based on my own hands-on experience. If you’re early in your PhD and want to use AI to get more done without yet having a strong command of the literature or a highly specialized skill set, this is for you. A note upfront: all of the content here is produced from my own input with the help of code agents.

Two resources that have helped me a great deal are Claude Blattman and the claude-howto guide on GitHub. Both are written primarily with Claude in mind, but in practice I have found they translate very naturally to Copilot, Cursor, and Codex as well — the underlying ideas carry across tools.

My setup when I share this:

Primarily Mac user, but sometimes use Windows for large dataset handling
Finishing my PhD in Economics
Claude Pro plan · GitHub Copilot Student Free Version · Cursor Pro plan

Getting Started
Setting up the environment · Understanding the basics in under three minutes

What Works vs. What Doesn't Work
Honest takeaways from months of daily use in an economics research context

Comparing Across Agents & Chat Interfaces
Copilot vs. Claude vs. Codex · Gemini vs. ChatGPT vs. Claude

A Typical Example of My Workflow
Different settings, different tasks, different approaches — how I actually use these tools day to day

Sharing Skills & MCPs I Used and Created
Curated integrations, shortcuts, and tools that have made the biggest difference