GPT Orchestration
Definition
GPT orchestration coordinates model calls, tools, and data accesses within a workflow.
An application decides when to call a GPT model, what information it receives, and how its output is further processed. This can include tool calls, validation rules, and handover to humans.
Simply explained
A workflow distributes tasks and passes results on to the next appropriate point.
Why it matters in practice
Coordination connects individual responses with a comprehensible operational process.
Example from business
Hypothetical example: A workflow searches for suitable documents, has a draft response created, and then submits it for approval.
Limits and pitfalls
- Unlimited loops, unclear responsibilities, and unchecked tool calls can amplify errors.
Origin & history
The approach transfers software orchestration to workflows with language models.
Use in mid-sized companies
- Explicitly define inputs and outputs, error paths, and human decision points.
Frequently asked questions
Do you need multiple models?
No, even a single model can be orchestrated within a multi-step workflow.
Sources
- Multi-Agent Research System (2025) · Anthropic, Multi-Agent Research System (2025)
- Google ADK · Google ADK
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