AI Agents

Deployment patterns, production gates, observability, and operator-backed runbooks for AI agent stacks.

4 articles

Agent drift detection: building the baseline eval suite

How to catch model drift, prompt rot, and vendor silent updates before users complain. The 20-50 input fixed eval pattern that every production agent needs.

May 20264 min read

AI Agents

AI agent observability: what to log, why, and what to redact

The per-decision logging contract every production agent needs. Fields, retention, PII handling, and the queries you can answer in under 30 seconds when an incident lands.

May 20264 min read

AI Agents

The 30-criteria production-readiness audit for AI agents

Most agents shipped in 2024 fail at least eight of these. The full audit checklist DPL runs on every recovery engagement, with the why behind each gate and what failure looks like in production.

May 20266 min read

AI Agents

Prompt injection resistance: what production agents need at the input boundary

Sanitize before the prompt is built. Validate every output before a tool runs. The sanitization-plus-output-guard pattern that stops a pasted instruction from leaking data or running unintended tools.

May 20264 min read

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