Agents
Every lab runs a hierarchical multi-agent system that mirrors how a real research group operates: a Captain (you) directs an orchestrator, which delegates to domain leads, who dispatch workers.Agent Hierarchy
Roles
Orchestrator
The orchestrator is the top-level AI agent. It:- Receives your natural-language instructions
- Breaks them into tasks and routes by reasoning level
- Manages priorities across leads
- Escalates blockers and ambiguity back to you
- Runs 3x daily standups (morning, midday, evening)
Lead Agents
Leads own a domain and can both plan and execute. They:- Direct strategy within their domain
- Execute medium-complexity tasks themselves
- Dispatch workers for routine tasks
- Take over from workers that fail (tilldone pattern)
- Participate in cross-agent peer review
Worker Agents
Workers execute specific, scoped tasks:- Generate figures from data
- Run formatting and LaTeX compilation
- Process datasets and update wikis
- Handle data transformations
Cross-Model Peer Review
To prevent echo chambers, every significant agent output is reviewed by a different model family:
This catches model-specific biases and hallucinations that same-model review would miss.
Reasoning-Based Routing
The orchestrator routes every task by its reasoning requirement:
This keeps costs down without sacrificing quality where it matters.
Agent Communication
All agent-to-agent communication is visible in the Activity Feed, a color-coded, real-time stream showing:- Task assignments and completions
- Review requests and outcomes
- Escalations and blockers
- Lead takeovers of failed worker tasks