LLM AI Agent Evaluations and Observability with Galileo AI By Henry Habib
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LLM AI Agent Evaluations and Observability with Galileo AI · Program
About this program
LLM AI Agent Evaluations and Observability with Galileo AI
Online Course
Learning format
AI Agents
Subcategory
English
Course language
$39.99 (list $9.99)
Price
Price may change · updated within 1–2 weeks
Official program page
What you'll learn in LLM AI Agent Evaluations and Observability with Galileo AI
- Design an LLM observability plan: what to log, how to structure traces, and how to make failures diagnosable
- Build evaluation datasets with realistic inputs, expected behavior, metadata, and slices for edge cases and regressions
- Run repeatable Galileo AI experiments to compare models, prompts, and agent versions on consistent test sets
- Implement custom eval metrics for generation quality, groundedness, safety, and tool correctness (beyond accuracy)
- Apply LLM-as-judge scoring with rubrics, constraints, and spot checks to reduce evaluator bias and drift
- Debug agent failures using traces to pinpoint breakdowns in retrieval, planning, tool use, or response synthesis
- Set up production monitoring in Galileo with signals, dashboards, and alerts for regressions and silent failures
- Use eval results to prioritize fixes, validate improvements, and prevent quality or safety regressions over time
- Choose observability and eval methods for single-call LLM apps vs. multi-step agents, and explain tradeoffs
- Instrument LLM apps and agents in Galileo to capture traces, spans, prompts, tool calls, and metadata for debugging
- Design an LLM observability plan: what to log, how to structure traces, and how to make failures diagnosable
What's Included in LLM AI Agent Evaluations and Observability with Galileo AI
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