Learning path

Builder path — from prompts to reliable AI systems

A route through structured output, RAG, evals, routing and agent controls.

Start with contracts

Learn structured output and function/tool calling. Make model outputs machine-checkable before connecting important actions.

Add evidence

Build a small RAG workflow with citations and test retrieval separately from answer quality.

Measure changes

Create a golden set and track quality, latency and cost. Every model or prompt change should be compared to a baseline.

Add autonomy last

Only after tools, permissions and observability are stable should an agent choose multi-step actions. Keep approvals for irreversible operations.