In already a few short years, AI technology has evolved from basic chat completions to autonomous, long-running agents. This poses a challenge for IT teams who need to enable their builders to innovate while also providing guardrails and controls to reduce enterprise risk. More than just chatbots or assistants, agents are now autonomous entities capable of operating over extended horizons, crafting their own sub-agents, and using professional tools to complete multi-step plans. But as agents leave the developer's laptop and start interacting with production data and external APIs, freedom wit
The AI agent world is messy. Teams are reaching for LangChain, LlamaIndex, CrewAI, AutoGen, or building custom solutions from scratch. Good. That's how it should be during the creative phase. But once an agent leaves a developer's laptop and starts talking to production data, calling external application programming interfaces (APIs), or running on shared infrastructure, freedom without guardrails stops being a feature and starts being a liability.We've watched the industry go through waves: Model APIs (such as chat completions), agentic APIs (such as assistants and later the OpenAI responses