Week 10 - AI Engineering & LLMOps on AI Platform Engineering Handbook

AI Observability & Production Monitoring

Mon, 01 Jan 0001 00:00:00 +0000

1. AI Observability

AI observability refers to the practice, and the collection of tools and techniques, used to gain genuine visibility into how an AI system is actually behaving in production — not just whether it’s technically running without crashing, but what it’s actually doing, step by step, and how well it’s actually doing it.

AI Safety, Guardrails & Governance

Mon, 01 Jan 0001 00:00:00 +0000

1. AI Guardrails

Guardrails are the checks and controls put in place, both before and after a language model actually processes a request, specifically to catch and prevent unsafe, inappropriate, or genuinely unintended behavior — the name itself is a deliberate and pretty fitting metaphor, borrowed directly from the physical guardrails you’d see along the edge of a mountain road, there specifically to keep a car from veering off the road entirely, even if the driver makes a mistake.

LLMOps Foundations & AI Delivery

Mon, 01 Jan 0001 00:00:00 +0000

1. LLMOps Fundamentals

LLMOps stands for “Large Language Model Operations,” and at its core, it’s the set of practices, tools, and processes used to reliably build, deploy, monitor, and maintain AI applications that are powered by large language models, once those applications move beyond just being a personal experiment and need to actually work well for real people, consistently, over time.