Most engineering leaders I speak to have the same problem. Their teams are shipping AI agents, tweaking prompts, swapping models, iterating constantly — but nobody has a systematic way to measure whether any of it is actually making things better. Every change is a guess.
Traditional software testing wasn’t designed for systems that reason, plan, use tools and make autonomous decisions. Without robust evaluation, you can’t answer the questions that matter most as a leader — is the agent actually improving, which changes introduced regressions, how reliable is this in production, what should we prioritise next?
The most successful AI teams don’t just build agents. They build evaluation systems around them.
We’re hosting a hands on Agent Evals Bootcamp on June 27 with Ammar Mohanna, PhD, an AI engineer, researcher and expert in production AI and agent evaluation. 5 hours live, practical throughout.
Covers the full evaluation stack — component evaluation, trajectory evaluation, outcome evaluation and adversarial evaluation. Every attendee walks away with a practical framework they can apply immediately, 6 months access to an AI Evals assistant and an industry recognised certification.
Full details here: https://www.eventbrite.co.uk/e/agent-evals-bootcamp-tickets-1990306501323?aff=elh