TRAINING COURSE
Testing & Evaluating AI Agents
AI agents fail differently from traditional software. This programme equips your team with the evaluation frameworks, failure pattern recognition, and operational disciplines to ensure agents perform reliably.
1 Day
8-20 Participants
Online or in-person
No Prerequisites
For product managers, technology leaders, quality and compliance professionals, and technical staff managing or building AI agent systems.
The Reliability Gap
AI agents produce outputs that look entirely reasonable while being subtly wrong — no error messages, no crashes, just confident responses containing errors
Most organisations deploying AI agents have no systematic way to know whether those agents are producing reliable work
The capability that makes AI agents valuable is also what makes them risky — and failures only surface after damage is done
40%
of agentic AI projects will be scrapped by 2027 due to escalating costs and unclear business value
Source: Gartner, June 2025
Who Should Attend
Product managers, technology leaders, quality and compliance professionals, and technical staff (beginner to intermediate) managing, commissioning, or building AI agent systems.
This is for you if…
✓
You're deploying or commissioning AI agents and need to know they're producing reliable work
✓
You want to understand how AI agents fail and how to catch problems before they reach clients
✓
You need to build evaluation processes that improve both the agent and the evaluations over time
✓
You want practical frameworks for continuous monitoring and production operations, not just pre-launch testing
This isn't for you if…
✗
You're looking for deep machine learning or model training skills (this is about evaluating agent outputs, not building models)
✗
Your organisation has no current or planned AI agent deployments
✗
You want self-paced e-learning rather than live facilitation with a running case study
Programme Overview
7 modules. 1 day. Real capability.
Full detailed agenda available on request
How the Day Works
This is live, facilitated training built around a realistic professional services case study that runs through every module. Your team learns by applying evaluation frameworks to real scenarios, not sitting through presentations.
~60%
Frameworks & Real-World Examples
Evaluation concepts, failure patterns, and quality check design explained clearly with real-world examples from professional and financial services.
~40%
Practical Exercises
Hands-on exercises building on a professional services case study: classifying outputs, mapping failure patterns, designing quality checks, conducting error analysis, and building evaluation criteria.
1 Case Study
Running Throughout
A professional services case study evolves through every module. You'll classify its outputs, map its failure points, design its quality checks, and build its monitoring plan — so you leave with a complete, worked example.
Available online (via Zoom/Teams) or in-person at your location
All materials, frameworks, and reference guides included
No prior technical knowledge required — Module 1 establishes the necessary foundations
Groups of 8–20 for meaningful discussion and peer learning
What Makes This Different
Evaluation, Not Just Testing
Goes beyond traditional pass/fail testing to teach the evaluation discipline that AI agents actually require: measuring quality across exact and judgment outputs, calibrating AI judges, and building layered quality architectures.
Case Study Throughout
Not abstract theory — a professional services agent case study runs through every module. You'll classify its outputs, map its failures, design its checks, and build its monitoring plan. You leave with a complete, worked example.
Actionable Roadmap
You won't just learn frameworks — you'll build a 30/60/90-day evaluation action plan for your organisation. Assess your current maturity, identify what to build next, and leave with specific next steps, not generic recommendations.
Ready to ensure your AI agents perform reliably?
Have questions? Email training@serpin.ai