The Missing Layer in the AI Stack

About this episode

This episode explores the need for a coordination layer in AI systems to describe purposeful work.

Over the past few years the AI ecosystem has been assembling itself into layers. First came the models. Then came the tools that allow those models to interact with the world. Now we’re beginning to see protocols that let AI agents communicate with each other and frameworks that help orchestrate their work. But when you zoom out and look at the emerging architecture, a small question starts to nag. What is the unit of work in AI systems? Not a prompt. Not a tool call. Not a message between agents. Something more like what humans already understand: a mission . In this episode we explore a simple but surprisingly deep idea: that AI systems may eventually need a shared way to describe purposeful work — goals, constraints, policies, and budgets — independent of the particular agents or tools involved. Along the way we talk about: Why the AI stack may be missing a coordination layer The difference between agents, tools, and missions Why reasoning and authority should probably be separated How runaway agent systems could create congestion Why TCP solved packet congestion — but not “work congestion” What might stop agents from spawning missions all the way down Whether this is just…

People in this episode

Host: Paul Henry Smith

Topics covered

• AI architecture
• coordination layer
• AI agents
• missions
• work congestion
• workflow systems

Keywords

• AI stack
• models
• tools
• protocols
• goals
• constraints
• policies
• budgets

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