Resources
Practical assets for building AI systems beyond the demo.
Checklists, diagrams, and field-tested notes for engineers, students, and teams working on RAG, workflows, evaluation, and AI product architecture.
Resource system
A clearer resource library: learn, visualize, review, apply.
The goal is to make this site easy to use repeatedly. Every resource should fit into one of four jobs: learn the concept, see the diagram, review the risk, or apply the pattern.
Learn
Structured learning paths for AI system design and production thinking.
Visualize
Architecture diagrams, risk maps, and workflow visuals for explaining concepts quickly.
Review
Checklists and review guides for deciding whether an AI feature is ready.
Apply
Case studies and project patterns that show how the concepts fit together.
AI System Design Guide
A simplified learning path for production AI systems, rewritten as practical strategy frames.
Open resourceChecklistAI Feature Shipping Checklist
A practical review flow for quality, logging, fallback behavior, latency, cost, and release readiness.
Open resourceRAG reviewRAG Trust Review
A review guide for retrieval quality, source trust, citations, freshness, and user-facing fallback behavior.
Open resourceWorkflow reviewAgent Workflow Risk Map
A practical map for reviewing workflow boundaries, context risk, recovery paths, traces, and review gates.
Open resourceDiagramsAI Engineering Diagrams
Visual diagrams for explaining workflows, RAG trust systems, and production AI architecture.
Open resourceHow to use these resources
These resources are designed to support real product decisions, not just explain concepts. Use them when planning, reviewing, teaching, or debugging AI workflows.