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Module · 5 lessons
Production Monitoring & Guardrails
Shipping isn't the finish line — quality drifts, prompts regress, and bad outputs slip through. Learn production monitoring and alerts, drift and regression detection, prompt regression tests in CI, and guardrails with human feedback, then build a monitoring and guardrails harness for Docent.
At a glance
Level
Intermediate
Lessons
5 lessons
Time to complete
1 week
Cost
Free forever · no sign-up
Welcome to Production Monitoring & Guardrails, the eighth and final teaching module. Launch is not the finish line — it’s where the hardest problems start. A prompt tweak silently breaks a third of answers, a model upgrade shifts tone, real user questions drift away from your test set, and every now and then an output slips through that never should have. This module is the discipline that keeps Docent good after it ships.
You’ll set up continuous monitoring with the right metrics and alert thresholds, learn to detect drift and regressions before your users report them, and treat prompts like code by running regression tests in CI so a quality drop fails the build instead of reaching production. Then you’ll add guardrails — input and output checks that block the unsafe, the off-topic, and the malformed — and close the loop with human feedback that flows back into your datasets. The guided project brings it together into a monitoring-and-guardrails harness that makes Docent genuinely production-ready.
Start with Lesson 1, where the question shifts from “was it good when we shipped?” to “is it still good right now?”
Lessons in this module
1
Monitoring in Production: Dashboards & Alerts
Turn Docent's observability data into continuous production monitoring: the handful of metrics an on-call engineer watches, rolling windows that keep a fresh regression visible, and static and relative alerts that fire on a real refusal-and-latency incident.
2
Detecting Drift & Regressions
Learn how Docent's quality silently degrades and how to catch it — distinguish input drift, quality drift, and sudden regressions, then build a deterministic detector that flags a topic shift and a windowed score drop.
3
Prompt & Model Regression Tests in CI
Treat Docent's prompt and model like code: gate every change behind an automated eval suite in CI that fails the build when quality drops or a critical case regresses.
4
Guardrails & Human Feedback
Wrap deployed Docent in input and output guardrails that block, rewrite, or flag bad requests and answers, then close the loop by feeding human feedback back into the golden eval set.
5
Guided Project: A Monitoring & Guardrails Harness
Assemble Module 8 into one production-readiness harness for Docent: guardrails, rolling alerts, a CI regression gate, and a feedback loop that ends in a single ship-or-hold report.
Achievement
Complete all 5 lessons to finish the Production Monitoring & Guardrails module.
