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Agent Configuration

Every lab has an agent team that you can customize to match your research domain. This guide covers how to add, remove, and configure agents.

Default Agent Team

When you create a lab from a template, you get a pre-configured team:

Adding Agents

  1. Go to your lab’s Agents view
  2. Click Add Agent
  3. Configure:
    • Name, Descriptive name (e.g., “Cosmology Lead”)
    • Role, Lead or Worker
    • Model, The AI model this agent uses
    • Specialty, Free-text description of the agent’s domain expertise
  4. Click Create

Choosing Models

Select models based on the reasoning level required:
Leads can do work themselves (not just delegate). A Claude Opus 4.8 lead can handle complex analysis directly, while a Haiku 4.5 worker handles formatting tasks. Match the model to the agent’s responsibilities.

Cross-Model Review Setup

Cross-model review is mandatory. Configure which external models participate:
The system automatically assigns reviewers from different model families:
  • Claude output is reviewed by GPT-5.5, Gemini 3.1 Pro, or Grok 4
  • GPT-5.5 output is reviewed by Claude Opus 4.8, Gemini 3.1 Pro, or Grok 4
  • Gemini 3.1 Pro output is reviewed by Claude Opus 4.8, GPT-5.5, or Grok 4
  • Grok 4 output is reviewed by Claude Opus 4.8, GPT-5.5, or Gemini 3.1 Pro

Updating Agents

Viewing the Team

Standup Configuration

Configure the orchestrator’s standup schedule:
Standups summarize what happened since the last check-in, flag blockers, and recommend next actions.

Auto-Scheduling

Enable auto-scheduling so the orchestrator picks the next experiment when pods are idle:
When enabled, the orchestrator monitors pod utilization and automatically deploys queued experiments to idle pods. This ensures GPUs are never sitting idle.

Best Practices

  • Use Opus for orchestrator and leads that make strategic decisions
  • Use Sonnet for workers that do analysis and code generation
  • Use Haiku for workers that do formatting, data transformation, and wiki updates
  • Always have at least two external model providers for cross-model review
  • Start with the default team and add specialists as your research demands grow