A cost problem with AI agents and Batch API support
A Reddit user says their AI agent workflow costs are getting too high. They say background agents are sending too many tasks as real-time inference. The user asks whether any agent harness or orchestration pattern supports Batch API well. They also ask if others are grouping requests before sending them to models.
Key points
- The post is about high costs in AI agent workflows.
- The user says background agents are being handled like real-time inference.
- They are looking for tools that support Batch API inside the agent loop.
- They ask whether teams are building custom queues or buffers to group requests.
- The focus is on production tasks that do not need an immediate human response.
Quick term guide
- AI agent workflow
- A series of automated steps where AI tools work in sequence to complete a task without manual input each time.
- agent workflow
- A set of steps an AI follows automatically to complete a series of tasks in order.
- background agents
- AI helpers that can run tasks behind the scenes without the user actively watching them.
- real-time inference
- Getting an AI model’s answer right away after sending a request.
- agent harness
- A supportive framework that helps manage and control how an AI agent performs its tasks.
- orchestration pattern
- A common way to organize how different steps in a system run together.
- orchestration
- Coordinating multiple AI agents or steps to run in a specific order or in parallel to complete a task
- agent workflows
- Step-by-step work patterns where an AI agent handles a task.