Output Library
Proof by output: projects, diagrams, resources, notes, and teaching assets.
Strong creator platforms do not only say what they know. They make their thinking visible. This page collects the public artifacts visitors can inspect today.
Flagship case study
The strongest project artifact: a production-focused AI workflow with diagrams, traces, evaluation thinking, and runnable references.
Visual explainers
Reusable diagrams that make system-design concepts easier to understand, teach, and share.
AI Engineering Diagrams
SVG diagram library covering production workflow, RAG trust, and workflow risk maps.
Inspect artifact →Resource diagramRAG Trust System Diagram
Visual path from documents to retrieval, citations, fallback behavior, feedback, and evaluation.
Inspect artifact →Risk mapWorkflow Risk Map
Visual review map for context risk, approval points, recovery paths, audit trail, and evaluation.
Inspect artifact →Practical resources
Assets visitors can reuse while designing, reviewing, or teaching production AI systems.
AI System Design Guide
Structured learning path for interviews and production AI system design.
Inspect artifact →ChecklistAI Feature Shipping Checklist
Release-readiness checklist for quality, logging, fallback behavior, latency, cost, and operational review.
Inspect artifact →Review guideRAG Trust Review
Review guide for retrieval quality, source trust, citations, freshness, and fallback behavior.
Inspect artifact →Writing and reading notes
Field notes that show how I read engineering work and convert it into simpler system-design lessons.
Context Layer Reading Note
Reading-note format with a custom animated reading map and Mermaid diagrams.
Inspect artifact →Architecture noteProduction RAG Copilot
System-design thinking for building a RAG copilot beyond a basic demo.
Inspect artifact →Positioning essayFull-Stack AI Engineering
Positioning essay explaining AI product architecture across UX, backend, data, model behavior, and operations.
Inspect artifact →Teaching evidence
Workshop and teaching assets that show the ability to convert complex concepts into learning paths.
Proof rules going forward
This keeps the site honest. We should add stronger proof, but only when the artifact exists and visitors can inspect it.