Accelerated Innovation

Iteratively Tuning Your GenAI Solutions

Optimizing Your EDD Approach

Workshop
Is your Evaluation Driven Development practice strong enough to keep up with real-world usage, model changes, and rapid delivery cycles?

Many teams adopt EDD, but over time their metrics, tests, and workflows drift out of sync with live systems, evolving models, and agile delivery demands. This workshop focuses on tuning EDD as a living system that remains trusted, effective, and integrated in production environments. 

To win, your team must continuously evaluate and adapt EDD implementations so evaluation remains a reliable signal for quality, risk, and delivery decisions. 

The Challenge

When EDD practices are not actively tuned, teams encounter predictable breakdowns: 
• Stale or misaligned implementations: EDD setups in live environments no longer reflect how systems are actually used or deployed. 
• Weak metrics and tests: Evaluation metrics fail to surface meaningful quality, safety, or performance issues as models and data evolve. 
• Poor delivery integration: EDD workflows clash with agile cadences and are disconnected from existing QA and DevOps tooling. 

These failures erode trust in evaluation, allowing risk and quality regressions to slip into production. 

Our Solution

In this hands-on workshop, your team reviews and refines live EDD implementations to keep evaluation effective as systems and models change. 
• Review EDD implementation in live environments to identify gaps between intended and actual evaluation coverage. 
• Evaluate the effectiveness of existing metrics and tests against current quality and risk goals. 
• Fine-tune EDD practices to fit an agile development cadence without slowing delivery. 
• Adapt EDD plans as models, prompts, and architectures evolve over time. 
• Integrate EDD with existing QA and DevOps tools to strengthen release gating and observability. 

Area of Focus
  • Reviewing EDD Implementation in Live Environments
  • Evaluating Effectiveness of Metrics and Tests
  • Fine-Tuning EDD for Agile Dev Cadence
  • Adapting EDD Plans as Models Evolve
  • Integrating EDD with Other QA and DevOps Tools 
Participants Will
  • Assess whether current EDD practices reflect real system behavior.
  • Strengthen metrics and tests to produce clearer experimental signals.
  • Align experimentation with fast-moving, agile delivery cycles.
  • Adapt EDD strategies as GenAI models and architectures change.
  • Integrate experimentation more tightly into QA and DevOps workflows.

Who Should Attend:

Technical Product ManagersML EngineersDevOps EngineersGenAI EngineersEngineering LeadsQA Lead

Solution Essentials

Format

Virtual or in-person 

Duration

4 hours 

Skill Level

Intermediate 

Tools

Live EDD implementations, QA frameworks, and DevOps tooling 

Ready to evolve experimentation into a durable GenAI delivery capability?