Almost every software vendor now says it builds AI agents. These ten questions separate partners who can run agents safely in production from those who can only demo them.
Ask what runs in production today, with which approval points and which metrics.
How agent quality, safety and tool use are measured before and after release.
Who owns the code and prompts, and how inference and run costs are controlled.
An agent is software that reasons over a goal and acts — calling tools, updating records, triggering workflows. That makes partner selection different from a normal application build: you are buying judgement about autonomy, safety and evaluation, not just code.
A scoped first workflow with success metrics, the approval design, the evaluation plan, the guardrail test plan, a run-cost estimate and an ownership clause. For governance, ISO/IEC 42001 provides a management-system frame many enterprises now reference.
VVnT SeQuor builds on its own agentic platforms — each with human-approval gates and action logging — and pairs development with independent AI testing and evaluation.
A chatbot answers questions. An agent works towards a goal and takes actions — calling tools, updating systems or triggering workflows — which is why approval design and guardrails matter.
Not necessarily, but it provides a useful governance frame for AI risk, roles and controls, and many enterprise buyers now reference it.
With task-level evaluation sets, regression evaluations on every model or prompt change, guardrail and red-team testing, and production monitoring of outcomes and escalations.
You should. Contracts should assign ownership of code, prompts, evaluation sets and any fine-tuned assets to the client.