Evaluation Driven Development (EDD) Series
An Applied Introduction to Evaluation Driven Development
Workshop
Are you shipping GenAI features without a clear way to prove they’re getting better?
EDD turns GenAI development into an engineering discipline by making quality measurable across retrieval, generation, and guardrails.
To win, your GenAI solutions need to improve through repeatable evaluation, not intuition.
The Challenge
Without a strong approach to GenAI evaluation, teams struggle to:
- Separate root causes — Retrieval issues, prompt issues, and model behavior blur together and waste cycles.
- Define what “good” means — Metrics drift, targets stay vague, and teams can’t align to business outcomes.
- Validate at scale — Ad hoc spot checks don’t catch edge cases, regressions, or real-world failure modes.
Evaluation gaps will drive quality issues, more hallucinations, slower velocity, and frustrated users.
Our Solution
In this hands-on workshop, your team learns how to apply EDD to instrument, evaluate, and improve GenAI solutions with a practical, developer-ready approach. Areas of focus include:
- EDD Methodology Selection — Compare EDD approaches and find the right fit.
- Observability and Tracing — Instrument and trace user requests across retrieval and generation to debug failures.
- Evaluation Targets and Metrics — Define targets aligned to business goals.
- Search and Retrieval Optimization — Use evaluation signals to improve retrieval quality and reduce errors.
- Guardrails and Human + Automated Evals — Pick the right mix of controls to reduce risk without slowing delivery.
Skills You'll Gain
- Metric-Driven Development — Turn quality into measurable targets.
- Faster Debugging — Trace failures to the right layer and fix the real root cause.
- Lower Hallucinations — Improve grounding by tightening retrieval evaluation and guardrail strategy.
- Repeatable Eval Workflows — Build evaluation practices that stay maintainable as use cases expand.
- Release Confidence — Catch regressions earlier and ship improvements with less operational risk.
Who Should Attend:
Data EngineersDevelopersTechnical Product ManagersSolution ArchitectsML Engineers
Solution Essentials
Format
Virtual or in-person
Duration
6 Hours
Skill Level
Intermediate Python and GenAI development familiarity recommended
Tools
Curated labs and evaluation examples aligned to common GenAI stacks
Explore our EDD Certification Workshops
Help your teams remove the “black box” from your GenAI solutions. Click below to explore the remaining workshops in the Evaluation Driven Development certification series.
A High-Level Introduction to Evaluation Driven Development (for non-Developers)
EDD Deep Dive - From Requirements to Evaluation
Curating Your EDD Data