Building Runtime Controls for AI Agents
Building Runtime Controls for AI Agents
As AI agents become more autonomous, the question of control becomes critical. How do you ensure an agent stays within its operational boundaries while still being useful?
The Problem
Traditional software has clear execution paths. You write code, it runs deterministically. AI agents are different. They make decisions, take actions, and interact with the world in ways that can be unpredictable.
This unpredictability is what makes them powerful, but it is also what makes them dangerous without proper guardrails.
Our Approach at Sekuire
At Sekuire, we are building runtime control infrastructure that sits between the agent and its environment. Think of it as a policy layer that evaluates every action an agent wants to take before it executes.
The key insight is that control does not have to mean restriction. Good runtime controls should be invisible when the agent is operating within bounds, and only activate when something goes wrong.
What is Next
We are working on making these controls composable and declarative, so teams can define their safety requirements in plain language and have them enforced automatically.