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

Captain (You)
  └── Orchestrator (high reasoning — Opus 4.6)
        ├── Research Lead (high reasoning)
        │     ├── Analysis Worker (medium)
        │     ├── Figure Worker (low)
        │     └── Data Worker (low)
        ├── Paper Lead (high reasoning)
        │     ├── Draft Worker (medium)
        │     └── LaTeX Worker (low)
        └── Compute Lead (medium reasoning)
              └── Pod Worker (low)

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)

The orchestrator uses the highest-reasoning model available (currently Claude Opus).

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

Workers use lower-reasoning models (Sonnet, Haiku) for cost efficiency.

Cross-Model Peer Review

Warning: Cross-model review is mandatory in Hubify Labs. No single model reviews its own output.

To prevent echo chambers, every significant agent output is reviewed by a different model family:

Primary Agent	Reviewers
Claude (Anthropic)	GPT-4 (OpenAI), Gemini (Google)
GPT-4 (OpenAI)	Claude (Anthropic), Grok (xAI)
Gemini (Google)	Claude (Anthropic), Perplexity

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:

Level	Models	Task Examples
High	Opus, GPT-4o	Strategy, peer review, paper writing, novel analysis
Medium	Sonnet, GPT-4o-mini	Code generation, data analysis, experiment design
Low	Haiku, GPT-3.5	Formatting, data ingestion, wiki updates, figure export

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

Nothing happens in the dark. Every action is logged and auditable.

Configuring Agents

You can customize your agent team per lab:

# Add a new lead agent
hubify agent add --role lead --name "Data Lead" --model claude-opus

# Change a worker's model
hubify agent update worker-3 --model claude-haiku

# View agent roster
hubify agent list

See the Agent Configuration guide for detailed setup instructions.