"Percent of code AI-generated" is this era's lines-of-code: easy to compute from a diff, trivially gamed, and silent on whether anyone can explain the system in six months. Here is what the field data actually shows when authoring gets cheap, why the number you're setting OKRs against measures the stage that stopped being the bottleneck, and four replacement metrics graded by whether you can compute them today.
Explore the evolution from basic LLM interactions to crafting sophisticated System Instructions, and discover how meta-prompting—using AI to refine AI prompts—can unlock more powerful and collaborative AI agents. This post details the journey and a practical approach to building AI that helps you build better AI.
Stop wrestling with Python versions and dependencies. Learn how to build a fast, simple, and unified development environment using uv
A case study on migrating a decade-old Jekyll website to Astro in just 3 days by partnering with AI (Google Gemini) for planning, coding, and building custom development tools.
A contemporary look on Brooks' essay No Silver Bullet: Essence and Accidents of Software Engineering
