Pre-Launch Agent Failure Simulation (QA)

Pre-Launch Agent Failure Simulation (QA)

1. 01

   Freeze the agent's scope boundary in writing before simulation begins

   List every tool, API, and data store the agent may touch, and mark which ones carry client-facing or CRM write access. The n8n architecture guidance from September 2026 recommends classifying each workflow by autonomy level so human-review checkpoints land where liability is highest.

2. 02

   Build a persona matrix that mirrors the client's real user base

   Cover at least the top five intents plus three adversarial personas: the impatient user who interrupts, the user who changes their mind mid-flow, and the user who supplies contradictory account details. Cekura's simulation approach runs thousands of these scenarios against voice and chat agents before go-live.

3. 03

   Run the scenario suite and capture every trace, not just failures

   Passing runs establish the baseline that drift detection later compares against. Arize structures this as span, trace, and session-level evaluation so a single bad tool call can be isolated from a bad retrieval step.

4. 04

   Score outputs against a written rubric with a calibrated judge

   Define pass criteria for accuracy, tone, refusal behavior, and task completion, then tune the judge against a sample of human-labeled runs. Hume AI's human feedback infrastructure exists precisely because automated judges drift from human judgment without periodic recalibration.

5. 05

   Replay the ten worst failures and confirm each has a named owner

   Assign every failure to either a prompt fix, a retrieval fix, or a scope restriction, and record the decision in the client's delivery log. Agnost AI surfaces production failure patterns as actionable intents and can generate reviewed fixes, but a human still signs off.

6. 06

   Set the go-live gate: no deployment until failure classes are closed or explicitly accepted

   Document accepted risks in the client-facing scope note, including the residual failure modes the client agreed to tolerate. This is the artifact that protects the retainer when an edge case surfaces in month two.

7. 07

   Schedule the first post-launch trace review within seven days

   Simulation catches known failure modes; production surfaces the ones nobody imagined. A seven-day window is short enough to catch a bad launch before the client's own team notices.