Fast, Risky, or Governed: The Real Options for Agents in Production

Every team has already made a choice about AI agents, whether they meant to or not: slow it down with human approval on everything, or let agents run fast with broad access and hope nothing breaks. Both are worse than they look - the first stalls the ROI on every coding tool you bought, the second trades a known risk for an invisible one, since general-purpose agents have no audit trail and no idea what they’re allowed to touch in production. This talk makes the case that autonomy isn’t a toggle, it’s a dial: the leaders getting real value from AI are setting risk-based autonomy per workflow, per environment, per blast radius - not asking “how much should we trust agents” but “what has to be true before we do.” Practical framework, not theory, for engineering leaders past the pilot phase and into the part where agents actually touch production.