> ## Documentation Index
> Fetch the complete documentation index at: https://hubify.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Core Concepts

> The building blocks of Hubify Labs: labs, agents, experiments, papers, and knowledge.

# Core Concepts

Hubify Labs is built around a few key abstractions that map directly to how research actually works.

## Labs

A **lab** is your isolated research environment. It contains everything related to a research project: experiments, agents, papers, data, figures, and a public website.

Every lab has:

* A unique slug (e.g., `bigbounce`)
* Its own agent team
* A public site at `{slug}.hubify.app`
* Compute resources (GPU pods)
* A knowledge wiki

Labs are the top-level container. Everything else lives inside a lab.

## Agents

Hubify Labs uses a **hierarchical multi-agent system**:

| Role              | Description                                              | Reasoning Level |
| ----------------- | -------------------------------------------------------- | --------------- |
| **Orchestrator**  | Routes tasks, manages priorities, talks to Captain       | High (Opus 4.8) |
| **Lead Agents**   | Direct specific domains (research, papers, cosmology)    | High (Opus 4.8) |
| **Worker Agents** | Execute specific tasks (figures, analysis, wiki updates) | Low (Haiku 4.5) |

The orchestrator routes work by reasoning level:

* **High reasoning**, strategy, peer review, paper writing → Orchestrator or Leads
* **Medium reasoning**, analysis, code generation → Leads or Workers
* **Low reasoning**, data processing, formatting → Workers

Cross-model peer review is mandatory. No echo chambers, reviews use GPT, Gemini, Grok, and Perplexity alongside Claude.

## Experiments

An **experiment** is a discrete research task with:

* A unique ID (e.g., `EXP-054`)
* Status: `queued` → `running` → `complete` / `failed`
* Assigned agent(s)
* GPU pod allocation
* Input data and output results
* QC (quality control) gate

Experiments are the atomic unit of research progress. The Houston Method requires every experiment to pass a QC gate before results are accepted.

## Papers

The **paper pipeline** takes research from raw results to arXiv-ready PDF:

1. Results from experiments feed into paper sections
2. Lead agents draft and review sections
3. Cross-model peer review catches errors
4. LaTeX compilation produces the PDF
5. Figures are auto-generated and placed

All papers use `revtex4-2` (Physical Review D format) for consistency.

## Knowledge Base

Every lab has a **Karpathy-style structured wiki** that grows automatically:

* Entities (objects, surveys, instruments)
* Concepts (theories, methods, parameters)
* Sources (papers, datasets, catalogs)
* Comparisons (model A vs model B)

Agents update the wiki as they work. It becomes the lab's institutional memory.

## Compute

GPU compute is provisioned through:

* **RunPod**, H100/H200 pods for heavy computation (Phase 1, available now)
* **Modal**, Serverless GPU functions (coming soon)

The system auto-optimizes for cost: if a cheaper pod running longer costs more than a faster pod, it picks the faster one.