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AI Engineering and Architecture
An informal knowledge base of evolving drafts to help you design, build, and deliver AI systems. These drafts contain conceptual models, frameworks, methods, and practices—but they do not guarantee success.
Selected Readings
A small selection of notes and drafts to start with.
AI Systems Require Behavioral Evidence
Why the quality of an AI system must be observed and measured under realistic conditions.
Evaluation
Drafts on evaluating AI systems, understanding their failures, and improving their behavior.
Natural Language Interface Substrate
A working model of how meaning, context, ambiguity, and intent shape natural-language interfaces.
Browse by Section
Use the site by major topic area when you want the broader map instead of a single highlighted note.
AI Engineering
Practical notes on LLM-based systems, evaluation workflows, and agent behavior.
System Design
Architecture, trade-offs, distributed systems, and interview-oriented design frameworks.
Engineering
General software engineering practices, architecture thinking, and implementation discipline.