The current wave of AI agents promises to revolutionize how we interact with software. From coding assistants to autonomous research agents, these systems are becoming increasingly capable. But there's a fundamental problem with how most of them are built: they operate in large, opaque chunks that are nearly impossible to verify, debug, or trust.
The Problem with Monolithic Agent Actions
When an AI agent decides to "write a blog post" or "research a topic," it's typically executing a complex, multi-step process that's treated as a single unit. This creates several issues:
Lack of Observability: When something goes wrong, you can't pinpoint exactly where the failure occurred. Was it in the planning phase? The research? The synthesis? The output formatting?