Agent Orchestration
& Memory Layer
Infrastructure for coordinating agents, tools, context, memory, and long-running workflows. The plumbing layer that makes multi-agent systems actually work.
The Problem
Single agents are easy. Multi-agent systems that share context, hand off work, and recover from failures are not. The infrastructure that makes this reliable is the same problem distributed systems engineers have been solving for twenty years. Most AI tooling ignores it.
The Approach
A coordinator that routes tasks to specialized agents, manages shared memory across turns, and tracks workflow state with retries and timeouts. Agents communicate through structured messages, not natural language. Memory is typed, not a vector blob.
Architecture
The coordinator is deterministic code, not a model. Routing, retries, timeouts, and state transitions are a plain state machine. Models run only inside agents, and their output is forced into a schema before it can move to the next step.
Memory is split by scope. Working memory lives with the workflow and dies with it. Durable memory is typed records per entity that agents read and write through a fixed interface. Nothing is a shared vector blob.
Every handoff is a structured message appended to the workflow log. If a run dies mid-flight, it resumes from the last completed step instead of starting over. This is the part most agent frameworks skip and the reason long-running workflows fall apart.
Status
Early build. Core coordinator and memory primitives in progress.