Note: This post comes with a NotebookLM podcast (1linked at the bottom), and three generated audio recordings. You can read the conversation I had
A collection of articles highlights various approaches and insights into optimizing AI-assisted coding workflows, primarily focusing on Claude Code and its transformative impact on software development.
Follow <a href="https://micro.blog/webology">@webology on Micro.blog</a>.
I’ve been diving deep into Claude Code and wanted to share some notes on CLAUDE.md structure and best practices. Here’s what I’ve learned from various sources and experiments. File Imports and Structure One of the most powerful features is the ability to import additional files using @path/to/import syntax: See @README for project overview and @package.json for available npm commands for this project. # Additional Instructions - git workflow @docs/git-instructions.md You can also import files from your home directory, which is convenient for team members to provide individual instructions that aren’t checked into the repository:
Applied mathematician writing about neuroscience, machine learning, Python tooling, and practical software development. Exploring probability, stochastic processes, and the intersection of mathematics and code.
Applied mathematician writing about neuroscience, machine learning, Python tooling, and practical software development. Exploring probability, stochastic processes, and the intersection of mathematics and code.
Claude Code is a powerful CLI based coding agent. It comes with MCP support which enables it to use external tools like web browsers to automatically validate a