AI Engineering

Building real systems with LLMs: retrieval, evaluation, agents, latency, and cost. The signal for engineers shipping AI in production, not hype.

AI Engineering Brief

Official

What matters this week in AI engineering.

From the AI Wall

LLM features add new attack surface. A handful of habits handle the most common risks before they reach users.

Before you merge, run the same questions a good reviewer would. Most regressions are caught by asking, not by luck.

A calm process for staying current on AI coding tools without letting the feed run your day.

Where agentic tools help on real codebases, and where a human still needs to hold the line.

A retrieval evaluation approach that tracks the metrics tied to real user success, not vanity scores.

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