# lab-research-patterns

> Research-backed patterns from Google DeepMind and Anthropic for enhanced multi-agent orchestration and safety.

- Source: https://doutorai.pt/en/components/skills__lab-research-patterns
- Type: Skills
- Category: AI research
- Downloads: 0
- Site: Doutor AI (https://doutorai.pt/en) - AI tools for small businesses

An open-source community component, curated and adapted by Doutor AI.

## What it does and how to use it

A **skill** that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

1. Install the skill (command above).
2. In Claude Code, describe what you need - the skill turns on by itself when the context fits.
3. No commands to memorize: you talk in plain language and the skill does the rest.

## Install (Claude Code)

```bash
mkdir -p .claude/skills/lab-research-patterns && curl -fsSL https://doutorai.pt/data/lib/skills__lab-research-patterns.md -o .claude/skills/lab-research-patterns/SKILL.md
```

Paste this command into the terminal, in your project folder, and the component installs automatically.

## Content

````
# Lab Research Patterns Reference

Research-backed patterns from Google DeepMind and Anthropic for enhanced multi-agent orchestration and safety.

---

## Overview

This reference consolidates key patterns from:
1. **Google DeepMind** - World models, self-improvement, scalable oversight
2. **Anthropic** - Constitutional AI, alignment safety, agentic coding

---

## Google DeepMind Patterns

### World Model Training (Dreamer 4)

**Key Insight:** Train agents inside world models for safety and data efficiency.

```yaml
world_model_training:
  principle: "Learn behaviors through simulation, not r

- 🔒 Full content on the Pro plan (€7.99/month) -
````

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Content by Doutor AI (https://doutorai.pt/en). When quoting, please cite the source: https://doutorai.pt/en/components/skills__lab-research-patterns