Chapters
01
AI Evals
You can't tell if it works by looking at it. Evals are how you know —
six concepts, six live components, from graders to pass@k.
02
Feedback Loops
Your agent retried and failed again. Without a feedback loop, retrying is just hoping — here's what iteration actually means.
03
Agentic System Design
Your multi-agent system ran to completion and returned a confident wrong answer. Silent failures are the default — here's how to design systems that fail visibly.
04
Agent Harness Engineering
It looked done in 20 minutes. It didn't work. The harness around the model — not a smarter one — is what closes that gap.
05
RAG
Hallucinations are a retrieval problem. Grounding your AI in real data is how you fix it.
06
Fine-tuning
Generic model, generic output. Fine-tuning is how you make AI care about your specific problem.