Tag: prompt-engineering
Posts with tag prompt-engineering
The Most Important AI Work Doesn't Show Up in Any Metric
Every company brags about their model's stats. Nobody tells you what you have to set up, and what you have to prompt, to actually hit those numbers. The hardest part of working with AI is the part no benchmark measures.
AI vs static analysis — when to use which (and why I use both)
A comment under my last post made me rethink where AI ends and static analysis begins. Here is how I draw the line — based on a system I run in production.
How I scale my AI code review system — and why every agent thinks like me
Adding a new agent to my system takes 2 days. Not because of the architecture — but because teaching it to think like me is the hard part.
Why I don't use one Opus for everything — model tiering in a multi-agent system
Running the most powerful model on every task is wasteful and slow. Here is how I split work across Haiku, Sonnet, and Opus — and why it matters at scale.
How I built an AI code review system with 9 agents — using only Markdown
No Python, no Node.js, no custom plugins. Just ~2,900 lines of prompt engineering and a fan-out/fan-in architecture that actually catches real bugs.