Orchestration Layer

An orchestration layer works like a site supervisor directing several workers. If a company has one person who searches for code, another who runs code, and another who does design, someone needs to decide who does what and in what order. It's the same in AI systems: when a big task is split among several smaller AI agents, the orchestration layer is the part that decides who moves first and who receives the results next.

This supervisor role usually stays on at all times, while the other workers who do the actual tasks are called in only when needed. The supervisor itself doesn't write code or draw pictures. Instead, it looks at incoming requests, decides which specialist to hand them off to, and gathers the results to pass along to the next step. This kind of division of labor matters even more in environments with limited computing resources, since keeping every worker running at once would burn through resources quickly.

So the orchestration layer is used as a way to combine the abilities of multiple specialists while saving resources — keeping one supervisor on standby at all times, and waking up the other specialists only when there's work for them.

In articles about Unsworm, this concept appears under the term 'orchestrator.' There's a table example that separates the model kept always on (the orchestrator) from sub-agents called only when needed (for code search, execution, and design), and the whole structure that divides and sequences work like this is called the orchestration layer. One easy point to misunderstand: the layer itself doesn't produce the actual work output — it only manages who does what, and when.

You can get a feel for the orchestration layer by trying something like this with a coding harness or chatbot.

Example prompt: "You are the orchestrator. Break down the following task into three stages — code search, code execution, and document summarization — and just plan the order and which (hypothetical) sub-agent should handle each stage. Don't actually do the work, just give me the plan."

Try this and you'll see the model act out the supervisor role, dividing tasks and sequencing them rather than doing the work itself.