Overview
Multi-agent content creation systems divide the content production process across specialized agents, improving quality and efficiency compared to single-agent approaches.
Architecture
Topic/Brief → Research Agent → Background Info
↓
Outline Agent → Structure
↓
Writer Agent → Draft
↓
Editor Agent → Polished Draft
↓
Fact-Check Agent → Verified Content
↓
SEO Agent → Optimized Content
↓
Image Selection Agent → Final with Media
Agent Roles
Research Agent
- Gathers background information
- Identifies key sources
- Extracts relevant data and quotes
Outline Agent
- Creates content structure
- Identifies key points to cover
- Ensures logical flow
Writer Agent
- Produces initial draft
- Follows style guidelines
- Incorporates research
Editor Agent
- Polishes prose
- Ensures consistency
- Fixes grammar and style issues
Fact-Check Agent
- Verifies claims
- Checks sources
- Ensures accuracy
SEO Agent
- Optimizes for search
- Adds metadata
- Suggests keywords
Image Selection Agent
- Identifies appropriate visuals
- Ensures proper licensing
- Optimizes for context
Quality Improvements
The multi-agent approach addresses common content issues:
- Thin Research: Dedicated research agent ensures depth
- Poor Structure: Outline agent creates logical flow
- Inconsistent Quality: Editor ensures polish
- Factual Errors: Fact-checker catches mistakes
Key Patterns
- Hierarchical Pattern: Sequential pipeline through roles
- Reflection Pattern: Self-critique at each stage
- Human-in-the-Loop: Final approval before publication
Common Failure Modes
- Hallucination Propagation: Fabricated facts from research phase
- Context Drift: Original brief lost through pipeline
- Over-Optimization: SEO agent hurting readability
- Conformity Bias: Agents agreeing on incorrect information