Practical AI Engineering

AI ships code.
You ship software.

Engineering-first takes on building with AI — intent, architecture, security, and the parts that actually break in production.

What's inside

Intent over artifacts

Use AI to explore quickly, then write down intent: decisions, constraints, priorities, and tradeoffs.

Lead the AI

Conventions, structure, and feedback loops that turn 'fast' into 'shippable' instead of 'fragile'.

Responsibility, not magic

AI accelerates creation, but it doesn't own your risk, upgrades, incidents, or long-term maintenance.

Systems thinking

Architecture, boundaries, failure modes, and operational reality — so the software survives contact with prod.

Reliability loops

Tests, observability, and tight iteration cycles that keep AI output honest as the codebase grows.

Engineering judgment

When the default stack is 'whatever the model saw most,' you need principles to choose intentionally.

Stay sharp.

Short, opinionated essays on AI-assisted engineering. No fluff, no hype.