Map the workflow
Identify tools, state, policies, dependencies, permissions and the evidence available when something goes wrong.
Methodology
We begin with the costly mistake.
The goal is not to create a large task count. The goal is to reproduce a failure that matters and determine whether an agent actually avoids it.
Define plausible failures
Describe the wrong result a capable agent may produce, why it appears reasonable and what downstream invariant it breaks.
Build the environment
Create deterministic services, representative synthetic or customer-approved data, reset behavior and solver-visible evidence.
Design the verifier
Measure resulting behavior and preservation invariants independently from the agent's written answer or self-reported status.
Attack the evaluation
Run oracle, untouched, wrong-target, duplicate-action, shortcut and reward-hacking controls.
Calibrate and explain
Run selected models or the customer's agent, retain trajectories and separate genuine agent failures from evaluation defects.
Delivery evidence
Traceable from task design to final result.
Each engagement can include environment source or hosted access, task and verifier packs, run manifests, machine-readable results, selected trajectories, a failure taxonomy, technical reporting and a next-experiment plan. Access is matched to the customer's security and IP requirements.
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