Agentic systems don't just generate text they call tools, touch APIs, and take multi-step actions on their own. That autonomy is the point, and it's also what makes them a fundamentally different risk to engineer around.
An agent that can call tools, query databases, or execute code is no longer a text generator with a chat interface it's a system that takes action on its own, chaining decisions across multiple steps with no human in the loop between them. A single bad decision at step two can compound by step five. Scope the tool access too broadly, skip a permission check, or trust a plan the agent generated for itself, and the failure mode isn't a wrong answer it's a wrong action already taken.
Every tool or API an agent can call is scoped to the minimum it needs for its task, with its own permission boundary an agent never inherits broader access than the specific action requires.
Actions that write, spend, delete, or send are routed through an explicit approval step. The agent can plan and propose autonomously; it doesn't execute anything irreversible unsupervised.
Multi-step and multi-agent workflows run with hard limits on steps, cost, and runtime, so a bad plan or a stuck loop fails safely instead of running away.
Every tool call, decision, and intermediate output is logged in order, so when an agent does something unexpected, we can reconstruct exactly why not guess from the final result.
Before launch, we test agents against inputs designed to manipulate their plans indirect prompt injection through tool outputs, malicious documents, and task descriptions crafted to steer them off-scope.
Autonomy is treated as a capability to be engineered and bounded, not a feature to be enabled and hoped for so an agent's freedom to act never outpaces our ability to control what it does.