Building AI agents is becoming easier. Running them safely once they can take real action is the...
Building AI agents is becoming easier.
Running them safely once they can take real action is the harder problem.
The moment an agent can deploy, approve, investigate, escalate, refund, send, export, or trigger a workflow, the question changes from:
Can the agent complete the task?
to:
AI agents are moving from chat into action. They can call tools, send emails, update records, delete...
AI agent governance works when policy runs at the action boundary before tool calls, writes, spending, approvals, and recovery…
Most "AI agent" tutorials wire the model straight to execution: user asks → model decides → system...
Design an AI agent autonomy ladder with manual, copilot, autopilot, and supervised modes so agents can act safely with budgets,…
There's a pattern I kept seeing. A team gives an agent real capability, like moving money, shipping a...
Your agent decides. Code decides whether it is allowed to act. A deterministic safety gate for AI agents. Plain Python, no deps.
