Already have an AI feature or agent but do not know where it breaks, drifts, overreaches, or fails to use its tools correctly? I run one focused evaluation and turn the failures into concrete hardening actions.

The starter scope covers one bounded AI surface. I define representative and adversarial cases around its real job, inspect the observed failures, separate model limitations from prompt, tool, context, or workflow problems, and produce a prioritized hardening plan.

Good fit for:

an agent that behaves inconsistently

a prompt or tool flow that works in demos but fails on edge cases

an AI feature that needs clearer limits and failure handling

teams preparing to trust an existing AI capability more seriously

Process:

You send the current AI surface, intended job, prompt/configuration, tools, examples, and known concerns.

I define a focused evaluation set around the agreed risks and expected behavior.

I run the evaluation, classify failures, and identify likely causes.

You get the findings and prioritized hardening actions plus one focused correction pass on the evaluation itself.

This starter package is one focused evaluation. A complete system rebuild, large benchmark program, production monitoring platform, or broad security/red-team engagement is separate scope.