Udemy - AI Incident Response - LLM and Agent Failures in Producti...

AI Incident Response: LLM & Agent Failures in Production

https://WebToolTip.com

Published 8/2026
Created by Dr. Amar Massoud
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 41 Lectures ( 3h 59m ) | Size: 3.5 GB

Detect, contain and recover from prompt injection, tool abuse, agent loops and hallucination incidents in production.

What you'll learn
⚡ Instrument an LLM or agent stack so incidents are visible — prompts, completions, tool calls, retrievals and cost
⚡ Triage an AI incident in the first five minutes and score its severity on blast radius, autonomy, data class and reversibility
⚡ Contain a misbehaving agent without making things worse — kill, throttle, revoke, roll back, isolate
⚡ Execute a named playbook for each of the eleven common LLM and agent failure modes
⚡ Preserve evidence and reconstruct root cause on a system that will not reproduce on demand
⚡ Recover safely — purge poisoned state, restore progressively, and gate re-enablement on evals
⚡ Run a blameless, model-aware post-incident review and stand up an AI incident response programme

Requirements
❗ Comfortable with Python and the command line
❗ Basic understanding of LLM APIs and tool/function calling
❗ Prior security or SRE incident experience helps, but is not required
❗ No attack-development experience needed — every lab incident is handed to you in progress
❗ A machine that can run a small local model (labs use Ollama — no API key, no cost)